S. HRG. 110–98 

Senate Hearings 

Before the Committee on Appropriations 

Agriculture, Rural 

Development, Food and 

Drug Administration 

and Related Agencies 

Appropriations 

Fiscal Year 2008 

110th CONGRESS, FIRST SESSION 

H.R. 3191/S. 1859 

DEPARTMENT OF AGRICULTURE 

DEPARTMENT OF HEALTH AND HUMAN SERVICES 

Food and Drug Administration 

NONDEPARTMENTAL WITNESSES 
Agriculture, Rural Development, Food and Drug Administration and Related Agencies 

Appropriations, 2008 (H.R. 3191/S. 1859) 
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WASHINGTON : 

For sale by the Superintendent of Documents, U.S. Government Printing Office

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33–905 PDF 2007

S. HRG. 110–98 

AGRICULTURE, RURAL DEVELOPMENT, FOOD AND 

DRUG ADMINISTRATION AND RELATED AGENCIES APPROPRIATIONS FOR FISCAL YEAR 2008 

HEARINGS 

BEFORE A

SUBCOMMITTEE OF THE 

COMMITTEE ON APPROPRIATIONS 

UNITED STATES SENATE 

ONE HUNDRED TENTH CONGRESS 

FIRST SESSION 

ON

H.R. 3191/S. 1859 

AN ACT MAKING APPROPRIATIONS FOR AGRICULTURE, RURAL DEVELOPMENT, FOOD AND DRUG ADMINISTRATION, AND RELATED AGENCIES PROGRAMS FOR THE FISCAL YEAR ENDING SEPTEMBER 30, 2008, 

AND FOR OTHER PURPOSES 

Department of Agriculture 

Department of Health and Human Services: Food and Drug 

Administration 

Nondepartmental witnesses 

Printed for the use of the Committee on Appropriations 

( 

Available via the World Wide Web: http://www.gpoaccess.gov/congress/index.html 
(II) 

COMMITTEE ON APPROPRIATIONS 

ROBERT C. BYRD, West Virginia, Chairman 

DANIEL K. INOUYE, Hawaii 

PATRICK J. LEAHY, Vermont 

TOM HARKIN, Iowa 

BARBARA A. MIKULSKI, Maryland 

HERB KOHL, Wisconsin 

PATTY MURRAY, Washington 

BYRON L. DORGAN, North Dakota 

DIANNE FEINSTEIN, California 

RICHARD J. DURBIN, Illinois 

TIM JOHNSON, South Dakota 

MARY L. LANDRIEU, Louisiana 

JACK REED, Rhode Island 

FRANK R. LAUTENBERG, New Jersey 

BEN NELSON, Nebraska 

THAD COCHRAN, Mississippi 

TED STEVENS, Alaska 

ARLEN SPECTER, Pennsylvania 

PETE V. DOMENICI, New Mexico 

CHRISTOPHER S. BOND, Missouri 

MITCH MCCONNELL, Kentucky 

RICHARD C. SHELBY, Alabama 

JUDD GREGG, New Hampshire 

ROBERT F. BENNETT, Utah 

LARRY CRAIG, Idaho 

KAY BAILEY HUTCHISON, Texas 

SAM BROWNBACK, Kansas 

WAYNE ALLARD, Colorado 

LAMAR ALEXANDER, Tennessee 

TERRENCE E. SAUVAIN, Staff Director 

BRUCE EVANS, Minority Staff Director 

SUBCOMMITTEE ON AGRICULTURE, RURAL DEVELOPMENT, FOOD AND DRUG

ADMINISTRATION AND RELATED AGENCIES

HERB KOHL, Wisconsin, Chairman 

TOM HARKIN, Iowa 

BYRON L. DORGAN, North Dakota 

DIANNE FEINSTEIN, California 

RICHARD J. DURBIN, Illinois 

TIM JOHNSON, South Dakota 

BEB NELSON, Nebraska 

JACK REED, Rhode Island 

ROBERT F. BENNETT, Utah, 

THAD COCHRAN, Mississippi 

ARLEN SPECTER, Pennsylvania 

CHRISTOPHER S. BOND, Missouri 

MITCH MCCONNELL, Kentucky 

LARRY CRAIG, Idaho 

SAM BROWNBACK, Kansas 

Professional Staff 

GALEN FOUNTAIN

JESSICA ARDEN FREDERICK

DIANNE PREECE

FITZHUGH ELDER IV (Minority) 

STACEY MCBRIDE (Minority) 

GRAHAM HARPER (Minority) 

BRAD FULLER (Minority) 

Administrative Support 

RENAN SNOWDEN
(III) 

C O N T E N T S 

TUESDAY, FEBRUARY 27, 2007 

Page 

Department of Agriculture: Office of the Secretary .............................................. 1 

Department of Health and Human Services: Food and Drug Administration ... 479 

Nondepartmental Witnesses ................................................................................... 721 

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AGRICULTURE, RURAL DEVELOPMENT, FOOD 

AND DRUG ADMINISTRATION, AND RELATED AGENCIES APPROPRIATIONS FOR 

FISCAL YEAR 2008 

TUESDAY, FEBRUARY 27, 2007 

U.S. SENATE, SUBCOMMITTEE OF THE COMMITTEE ON APPROPRIATIONS, Washington, DC. 

The subcommittee met at 10:02 a.m., in room SD–192, Dirksen 

Senate Office Building, Hon. Herb Kohl (chairman) presiding. 

Present: Senators Kohl, Harkin, Dorgan, Feinstein, Nelson, Reed, 

Bennett, Specter, and Craig. 

DEPARTMENT OF AGRICULTURE 

OFFICE OF THE SECRETARY

STATEMENT OF HON. MIKE JOHANNS, SECRETARY 

ACCOMPANIED BY: 

CHARLES CONNER, DEPUTY SECRETARY 

W. SCOTT STEELE, BUDGET OFFICER 

DR. KEITH COLLINS, CHIEF ECONOMIST 

OPENING STATEMENT OF SENATOR HERB KOHL

Senator KOHL. Good morning. Today we will begin hearings for 

the fiscal year 2008 budget. Our first panel will include Secretary 

Johanns and other distinguished guests from the Department of 

Agriculture, and following that we’ll hear from FDA Commissioner 

von Eschenbach on that agency’s budget. 

This is our first hearing for the year and it will be the only general hearing on the fiscal year 2008 budget. The other hearings 

that we’ll have will focus more on issue-specific areas such as food 

safety, conservation, and food aid. I hope this is a change in format 

that will allow us to study certain issues in more detail. 

As everyone knows, the fiscal year 2007 appropriations process 

was finished only a few weeks ago. While we understand the President’s request for 2008 is not changed by that action, our bills by 

necessity build on previous year’s action, and so we’ll need specifics 

as soon as possible regarding how the USDA and the FDA will 

carry out this year’s programs. I hope you will all work as quickly 

as you can to make sure that that information is available to us. 

The President’s budget includes fiscal year 2008 discretionary 

spending levels of more than $16 billion for USDA and more than 

$1.6 billion for FDA. This includes an increase of $43 million for 
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the Food Safety and Inspection Service, an increase of more than 

$260 million for the Farm Service Agency, and an increase of $180 

million for WIC. However, the budget also proposes the elimination 

of the Commodity Supplemental Food Program, which was proposed last year and which was rejected by this subcommittee. 

I would note that while the budget does include some new fee 

proposals, they are presented in such a way that there is little effect on 2008 funding levels. This is an improvement over previous 

years. However, there are a few legislative proposals, such as those 

regarding WIC and other programs, that will cause us some concern. So, Mr. Secretary, I look forward to your comments on those. 

There are a number of other issues in the budget that we will 

need to discuss, for example, eliminating the direct single family 

housing program, and a number of other rural development programs which are problematic. 

This has already been a busy year, with much yet to come. As 

we move through the appropriations process, I pledge to you that 

we will maintain a constructive dialogue with USDA and FDA. I 

can tell you that we intend to send our bills to the President well 

in advance of September 30, so we all need to work together so we 

can come to an agreement on administration priorities and congressional prerogatives as easily and as swiftly as possible. 

Having said that, I’d like now to turn to my good friend and the 

ranking member, Senator Bennett. As I’ve said many times, I want 

to publicly thank him and his staff for the helpful and bipartisan 

manner in which he has guided this subcommittee over the past 

few years, and I assure him and everyone else on this subcommittee that I intend to continue that very admirable practice. 

So, Senator Bennett, I would ask if you have any opening comments, and then we will turn to other members for their opening 

statements before we ask the Secretary to share his thoughts with 

us. We’ll recognize members in turn based on their arrival, and in 

moving from majority to minority for the first round of questions 

I ask that we use the 5-minute rule. So, Senator Bennett. 

STATEMENT OF SENATOR ROBERT F. BENNETT

Senator BENNETT. Thank you very much, Mr. Chairman, and I 

congratulate you on your assuming again the chairmanship of this 

subcommittee. I tried to follow your lead in the way that we ran 

things, and I am very grateful to you for your kind words. I believe 

we have an excellent working relationship on a bipartisan basis 

and I’m sure it will continue. 

I want to welcome Senator Nelson and Senator Reed, new members of this subcommittee. I think they will add a great deal to our 

deliberations. We areKntering a very busy time for USDA and the 

FDA because in the next few months Congress will consider and, 

one hopes, pass the farm bill, the Prescription Drug User Fee Act, 

and the Medical Device User Fee Modernization Act. These are 

some of the most important reauthorizations that the Congress will 

deal with, and while it’s the responsibility of the authorizers to address these issues, naturally that will strongly influence the work 

of this subcommittee. 

Now that the fiscal 2007 appropriations are in fact finally behind 

us and we focus on 2008, I’m delighted, Mr. Chairman, with your 
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commitment to get this bill done in a timely fashion. We’ve done 

it before, and either the full committee or the House was unable 

to follow our excellent example and get things done in a timely 

fashion, but I know you will do that and I’ll do everything I can 

to help you. 

So this morning I welcome Secretary Johanns and those accompanying him, and look forward to his testimony, and I also look forward to the second panel with Dr. von Eschenbach and those who 

will accompany him. 

This is a unique subcommittee. The life of every person in this 

country comes in direct contact with some of the product regulated 

or the programs carried out as a result of the appropriations we 

made in this subcommittee, and I don’t think any other subcommittee can say that. Every single American is affected here, so 

that’s how we will evaluate the budget proposals of USDA and 

FDA. 

Now, taking advantage of this opportunity, I want to offer some 

praise to three USDA employees in Utah, so that the record will 

show that I recognize their contribution: Bruce Richardson, who is 

the Farm Service Agency State Executive Director; Jack Cox, the 

Rural Development State Director; and Sylvia Gillan, the Natural 

Resources Conservation Service State Conservationist. Mr. Secretary, these are all three good people, and I wanted to make that 

comment for the record. 

Thank you very much for your courtesy, Mr. Chairman. 

Senator KOHL. Thank you, Senator Bennett. We’ll turn to Senators for their comments, starting with Senator Dorgan. Then we’ll 

recognize Senator Craig, then Senator Nelson, then Senator Reed, 

and then Senator Feinstein. Thank you. 

STATEMENT OF SENATOR BYRON L. DORGAN

Senator DORGAN. Mr. Chairman, thank you. Thank you and the 

ranking member, and let me say that I sure do support the notion 

of getting this bill done, getting it done on time, getting it through 

the Senate, in conference, and getting to the President for signature. The mess that was created last year, it cannot be repeated, 

and the mess doesn’t belong to any one person certainly, but we’ve 

got to finish all of these appropriations bills on time. 

I’m going to be asking Secretary Johanns some questions about 

disaster relief, as he might well expect. The three times I’ve gotten 

it through the Senate Appropriations Committee, twice through the 

full Senate, twice have gotten to conference, and it was blocked in 

conference. And I know the President at that point had opposed 

disaster relief. I’m going to ask Secretary Johanns about that 

today. 

I also want to ask some questions about the issue of opening the 

market to live Canadian cattle above 30 months of age, which will 

I’m told result in about 1.3 million head of Canadian cattle coming 

in this year, at a time when we have just heard of the ninth—I 

guess actually tenth case, if you consider the Canadian cow in the 

State of Washington—the tenth case of BSE in Canada. I just held 

a hearing on that subject in North Dakota last week, and I am very 

much opposed to the proposed rule offered by the USDA. I hope we 
4 

can overturn that rule. I guess I hope the comment period will persuade the Secretary not to proceed. 

But both of these are very important issues. I want to especially 

focus on the issue of disaster relief, and I will wait until I question 

Secretary Johanns. Let me thank the Secretary and the other 

members of USDA who have come here. 

And, Mr. Collins, we had a discussion in North Dakota about 

you, as a matter of fact. Someone was quoting the USDA Economist, and I asked who, and they told me your name. I said, ‘‘Well, 

I know him.’’ And I used to teach economics, but I was able to recover and move on. So we had a discussion about you. But let me 

thank you for being here again, as you have for many years, and 

being willing to visit with us about the agriculture economy. 

Secretary Johanns, welcome. 

Senator KOHL. Thank you, Senator Dorgan. 

Senator Craig. 

STATEMENT OF SENATOR LARRY CRAIG

Senator CRAIG. Well, Mr. Chairman, because I certainly want to 

hear from the witnesses, and we have a lot to cover, I will be brief. 

But let me join with my colleague, Senator Bennett, in welcoming 

you to the chairmanship of this committee. We do cover a lot of 

areas of major importance to a good number of citizens in our country. 

We come to Ag Appropriations at a time when the business of 

crafting a new farm bill—and, Mr. Secretary, we’re pleased that 

the work you have done puts you into the middle of that process. 

That’s where a Secretary of Agriculture ought to be, and frankly, 

some of our Secretaries have not been there, and Congress has 

been doing the work in part on its own. 

But I think it is a cooperative kind of shaping of policy that is 

going to be extremely important for American agriculture and U.S. 

consumers in the future; and, I must also say, and the role agriculture is increasingly playing in the production of energy. That is 

where I spend a fair amount of my time these days, on that issue, 

and it is exciting for me to see a future in which agriculture becomes an increasingly major contributor to energy independence in 

this country, and policy is certainly going to reflect that, loan guarantees, the whole combination of things. 

Mr. Chairman, I recently said before a hearing that I felt that 

maybe we ought to take DOE’s authority under Title 17 of the Energy Policy Act and give it to USDA. They seem to know how to 

get loan guarantees done, know how to do them, and that’s not a 

criticism as much as it is an observation of where we are on that 

issue. That’s important, and of course we’ll hear from FDA in a few 

moments. That, too, is critical to us. 

I would hope that as we look at policy—and here is where my 

friend from North Dakota and I oftentimes agree more than disagree—Mr. Secretary, and as we shape policy that will be reflected 

in the new farm bill, that we be as much focused on our domestic 

needs as we are to our international trade obligations. I know there 

are certain pressures there as it relates to where we may or may 

not be in the discussion of trade with our neighbors from around 

the world. 
5 

At the same time, I find it increasingly difficult to give and not 

get in return. And, having said that, the ability of American agriculture to produce is tied in part with trade. I know there needs 

to be balances, but there also needs to be balances. 

Mr. Chairman, thank you very much. I look forward to the testimony of you, Mr. Secretary. 

Senator KOHL. Thank you, Senator Craig. 

Senator Nelson. 

STATEMENT OF SENATOR BEN NELSON

Senator NELSON. Thank you, Mr. Chairman. 

Mr. Secretary, panelists, good to have you here today. The future 

of agriculture I think is not only based on what we want in terms 

of food, but also what we need in terms of fuel. You’ve already 

heard me suggest changing the name of the bill from a farm bill 

to the Food and Fuel Security Act of 2007, to focus more on what 

it is we intend to do with American agriculture as we move forward. 

I’m hopeful today that you will be able, as a result of this hearing, to establish that the planning in this bill is based on the contingencies of everything going okay as well as if everything goes 

bad. All too often we look at the current market situation, we see 

$4 corn, the countercyclical payments, they’re not what they have 

been, so we therefore don’t need the money. If everything—as my 

dad used to say, the problem is, when everything is going bad you 

never think it will go good; when everything is going very, very 

well, you never think it’s going to go bad again. 

And I’m hopeful that this bill doesn’t constitute that kind of a 

bill, so that we are in a position, if things do change and the market changes dramatically and things are going downhill, that this 

bill will protect American agriculture. Because if we continue to 

import at the level we are and we can’t export at the level that 

we’re unable to export to right now, I don’t know whether we’re 

close, but maybe you can enlighten us on this in your testimony, 

whether we are right at becoming net importers of our food. And 

if that’s the case, I have said if you like importing 70 percent of 

your oil, you’ll love importing 70 percent of your food. 

So that’s why I think it has to be about food security, produced 

here at home, and fuel security. Thank you, Mr. Chairman. 

Senator KOHL. Thank you, Senator Nelson. 

Senator Reed. 

STATEMENT OF SENATOR JACK REED

Senator REED. Thank you very much, Mr. Chairman. I’m eager 

to hear the testimony of our witnesses, and welcome them here this 

morning. Thank you. 

Senator KOHL. Senator Feinstein. 

STATEMENT OF SENATOR DIANNE FEINSTEIN

Senator FEINSTEIN. Thank you, Mr. Chairman. I have just a brief 

comment. 

Mr. Secretary, I want to thank you for your prompt declaration 

of a secretarial emergency in the California frost situation. The 
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Governor has submitted costs of approximately $1.3 billion so far. 

It is a very major frost problem for the State, and of course we 

don’t know how many of the trees are going to be taken out or 

crops prevented for the next 3 years because of the absence of bud 

wood, so it’s an ongoing struggle. 

I wanted to mention one point, and that one point, and I’m going 

to ask you some questions about it, is that since USDA transferred 

responsibility for port inspections to the Department of Homeland 

Security, the number of inspections has gone down seriously in 

California. I just sent my staff to the State, and the number one 

problem they came back with is the concern over the absence of 

adequate inspections and the belief that next year is going to be 

a very bad year, with infiltrating pests coming through the borders. 

My information is that 60 percent of agricultural inspection specialists indicated they were doing fewer inspections since the transfer, and there’s a problem. They don’t believe that Customs and 

Border Patrol respect their work. 

As you know, Mexican fruit fly larvae have been picked up, and 

it took 4 months for it to be identified, is what it was. And of 

course the problem is that a resulting quarantine, quarantines vast 

areas of the State, so I’m going to ask you a little bit about that 

when my time for questions comes up. 

Thank you very much for being here. Thank you, Mr. Chairman. 

PREPARED STATEMENT

Senator KOHL. Thank you very much, Senator Feinstein. 

And now we turn to the Secretary for your remarks. 

The subcommittee has received a statement from Senator Cochran which will be placed in the record. 

[The statement follows:] 

PREPARED STATEMENT OF SENATOR THAD COCHRAN

Mr. Chairman, thank you for holding this hearing on the fiscal year 2008 United 

States Department of Agriculture and Food and Drug Administration budgets. I 

welcome Secretary Johanns and Commissioner von Eschenbach back to the Committee. 

An important aspect of the Agriculture Appropriations bill is the funding it provides for agriculture research. This research is a critical part of ensuring that U.S. 

producers remain the leaders in food and fiber production. The funding this bill invests in agriculture research is a small sum compared to the economic benefit it has 

on a farmer’s bottom line. I am concerned about the Administration’s proposal to 

combine the Agricultural Research Service and the Cooperative State Research, 

Education, and Extension Service into a single agency. The current structure of the 

Agriculture Research Service is working well and I believe it is important for the 

Agriculture Research Service to maintain its independent role in the Department 

of Agriculture. 

I was pleased that the fiscal year 2007 Senate Agriculture Appropriations bill 

fully funded the Wetlands Reserve Program. It is unfortunate that Congress was 

unable to complete this bill. The Wetlands Reserve Program has taken 1,750,000 

acres of marginal croplands out of production and converted to more beneficial uses 

of enhanced flood protection, carbon sequestration, improved water quality, and 

wildlife habitat. Many of these acres are located in the Lower Mississippi River 

Flyway, the Nation’s largest waterfowl flyway for wintering habitat. 

Last year, the Natural Resource Conservation Service adjusted the method it uses 

to appraise land for consideration under the Wetlands Reserve Program. I have 

heard from many constituents in my State and conservation organizations that this 

change would shift acres away from this important flyway to areas with significantly higher appraisal value. I would like to work with the Department to find a 
7 

solution that would ensure this important program is implemented the way Congress intended. 

The Food and Drug Administration has the important role of protecting the public 

by ensuring the safety and efficacy of drugs and our Nation’s food supply. Commissioner von Eschenbach, I look forward to your comments on the FDA’s plan and priorities for the upcoming fiscal year. One example of the FDA’s commitment to protecting the public is the Center for Food Safety and Applied Nutrition’s research on 

the safety of natural products used as dietary supplements by many Americans. The 

National Center for Natural Products Research at the University of Mississippi is 

a partner with the FDA to provide research-based information on plant-derived 

products. With many new dietary supplements coming to the market, this research 

is increasingly important. 

STATEMENT OF SECRETARY MIKE JOHANNS

Secretary JOHANNS. Thank you very much. Mr. Chairman and 

distinguished members of the committee, it’s an honor to be here. 

I am joined today by some gentlemen that can assist me in answering questions. To my right is our deputy, Chuck Conner; to my left, 

Scott Steele, who is our budget officer; and of course you all know 

Dr. Collins, our chief economist. 

I am happy to report over the past year we’ve made a lot of 

progress in meeting the needs of the Nation by improving the rural 

economy and strengthening U.S. agriculture. Based on our conversations with Americans on the farm and off the farm, we developed a comprehensive list of farm bill proposals to strengthen the 

farm economy in rural America, and those were announced on the 

last day of January this year. 

My primary focus of course will be on the budget, but I would 

like to take just a few minutes to give an overview of the proposals. 

The 2007 farm bill proposals and the 2008 budget were developed 

on parallel tracks. The administration’s farm bill proposals represent the final phase of what was a 2-year process. We listened 

to producers and stakeholders all across the country, and we took 

a reform-minded and a fiscally responsible approach to making 

farm policy more equitable and predictable and protected from 

challenge in the world trade arena. 

While I firmly believe that the current law was the right policy 

for the time, times do change and times have changed. When the 

2002 farm bill was passed, commodity prices were low, exports had 

declined for several years, and the debt-to-asset ratio was nearly 15 

percent. 

Today we see a different economic picture. Commodity prices are 

strong for most program crops. Exports have set records now several years in a row, including a record of $68 billion in 2006, and 

projections suggest we will reach another record of $77 billion in 

2007. We are experiencing the lowest debt-to-asset ratio actually in 

recorded history. It’s at about 11 percent for 2006. 

Add to all of this the enormous impact of renewable energy on 

the economy, and it’s clear a lot of things have changed since 2002. 

The time has come to move forward with a farm program that’s 

market-oriented and considers more than commodity prices when 

determining the appropriate level of support. 

Our farm bill proposals bolster this administration’s commitment 

to conservation, with an additional $7.8 billion over 10 years for 

conservation purposes. We propose an additional $1.6 billion over 

10 years to advance the development and production of renewable 
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energy. This will help to achieve the President’s goal of reducing 

our dependence on gasoline by 20 percent in 10 years. We propose funding to support $1.6 billion in loans to rehabili- tate over 1,200 rural critical access hospitals. Another $400 million 

would be focused on trade, making sure that our producers have 

a level playing field. 

These are just a few highlights. When combined, we spend about $10 billion less than what was spent under the 2002 bill over the 

last 5 years, excluding the ad hoc disaster assistance. It would be 

about $18.5 billion less if you include that. But, importantly, we 

uphold the President’s plan to eliminate the deficit in 5 years. On 

the other hand, looking forward, our proposals would provide about 

$5 billion more than the projected mandatory spending if the 2002 

farm bill were just simply extended. 

And this brings me to a quick review of the budget. The 2008 

budget accommodates the farm bill proposals by including an additional $500 million per year in the total for the Commodity Credit 

Corporation. That was put there as a place-holder, anticipating the 

release of our proposals, the discretionary appropriation request 

pending before this committee, which does not include the Forest 

Service, is $16 billion. It funds the highest priorities while exercising necessary fiscal discipline. 

I would like to note that the President’s budget was developed 

prior to congressional action on funding for the remainder of fiscal 

year 2007. Therefore, our printed materials reflect an estimate for 

2007 under terms of the Continuing Resolution that provided funding through February 15. 

Now that action has been taken on funding the balance of 2007, 

I do want to thank the committee for addressing some really critical needs. Key among these resources are resources to ensure our 

meat and poultry inspection system can meet the demand for inspections, support for the Census of Agriculture, and funding to 

permit the Department to participate in reconstruction efforts in 

Iraq and Afghanistan. 

Utilizing $91 million in emergency supplemental funding, USDA 

has significantly increased our efforts relative to avian influenza 

overseas. The 2008 budget requests $82 million to continue and enhance ongoing efforts to fight AI, an increase of $32 million over 

the 2007 level. This funding will be used for surveillance and 

diagnostics work, preparedness, response efforts, international veterinary capacity-building, and research relative to poultry vaccines. 

The budget proposes $341 million for USDA’s part of the President’s Food and Ag Defense Initiative. This includes $325 million, 

an increase of $148 million, to enhance our ongoing efforts to detect 

and respond to food emergencies and threats to agriculture. To 

keep USDA in the forefront of avian disease research, the budget 

also requests $16 million to complete the planning and design of 

the Consolidated Poultry Research Facility in Athens, Georgia. 

We are making considerable progress in ensuring the safety of 

meat, poultry, and egg products. The Centers for Disease Control 

and Prevention has reported significant declines in foodborne illnesses. In order to continue protecting the Nation’s supply of meat 

and poultry and egg products, this budget meets the demand for 

inspection services. The budget also requests funding to expand the 
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Food Emergency Response Network, to increase the capability of 

State and local labs to handle large volumes of testing that would 

be needed in the event of a widespread food emergency. 

Moving on to energy, renewable energy supported by American 

agriculture and forestry does hold tremendous promise for our 

country. The budget proposes $397 million in loans, grants, and research, an increase of $161 million for our renewable energy programs. This amount includes $70 million for energy research. The 

majority of this will be focused on cellulosic energy. In addition to 

this research, the budget makes available over $320 million in 

grants and guaranteed loans to assist efforts to support the commercialization of renewable energy. In the farm program area, our discretionary budget supports $3.4 

billion in direct and guaranteed farm loans, which reflects the actual usage in recent years. The budget also requests $1.5 billion for 

the Farm Service Agency to deliver our farm programs. The level 

of funding is necessary to support approximately the same number 

of staff as we had in 2007. 

In 2008, crop insurance is expected to provide coverage for nearly $68 billion in agricultural production, double the amount of coverage provided in 2000. Recognizing the needs of all partners in the 

crop insurance system, the 2008 budget fully supports activities to 

ensure the integrity of the crop insurance program. These efforts 

have achieved savings of more than $456 million since the 2000 

crop year, and program abuses have been curbed. 

Expanding access to global markets is essential for agriculture. 

Our budget proposals for 2008 support our continued commitment 

to trade expansion activities. Increased funding is proposed to permit FAS to maintain its overseas office presence and continue its 

representation and advocacy on behalf of U.S. agriculture. The budget includes $100 million for the McGovern-Dole International Food for Education and Child Nutrition Program. Additionally, we request funding in the Office of the Secretary to support the department’s efforts in Afghanistan and in Iraq. In order 

to respond to emergency food needs during 2007, supplemental appropriations of $350 million are requested for the Public Law 480 

Title II donations program. 

The 2008 budget includes discretionary funding for conservation 

technical assistance to meet high priority natural resource concerns. It supports about $4 billion in mandatory funding to continue implementation of the conservation programs. In aggregate, 

funding in the budget will support enrollment of an additional 17.8 

million acres in conservation programs, bringing total enrollment 

to 215 million acres. That’s the highest enrollment in history. 

For rural development, the 2008 budget provides a $15 billion 

program level of activities to improve the economic opportunities 

and quality of life in rural America. The assistance will be used to 

finance home ownership, rural business, renewable energy, electric, 

telecommunications, water and wastewater disposal, other community facilities, and it will also support revitalization of our multifamily housing portfolio. 

In the research area, the 2008 budget funds the highest priority 

research. It also increases the use of competition to improve the 

quality of research, including a total of $257 million for the Na-
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tional Research Initiative. The budget includes $104 million in increases for high priority research in areas such as food and ag defense, avian influenza, bioenergy, animal genomics and genetics. Finally, the budget includes an increase of $25 million to support 

the 2007 Census of Agriculture. 

The budget does fully fund the expected requirements of our 

three major nutrition programs: WIC, food stamps, and the school 

lunch program. For WIC, which is our largest discretionary program, the budget proposes $5.5 billion in program level to support 

the estimated 8.3 million participants. For food stamps, the budget 

includes resources to fully fund the estimated food cost inflation 

and participation, and provides a $3 billion contingency in case 

costs exceed the estimated level. We expect an increased level of 

school lunch participation due to the increased number of school 

age children, so we include an additional $632 million for our Children Nutrition Programs. 

We have had tremendous response to MyPyramid, and I’m confident the awareness of eating a nutritious diet and being active 

will improve the health of Americans. So in order to continue this 

success, the budget includes a small increase to make enhancements to MyPyramid. 

PREPARED STATEMENTS

Let me just wrap up and say I want to emphasize that the budget before you strengthens agriculture and rural economies. It protects our food supply. It builds on our conservation efforts, and provides for the neediest of our citizens. With that, those of us at the 

table would be happy to respond to your questions verbally or to 

submit answers in writing where appropriate. Thank you, Mr. 

Chairman. 

[The statements follow:] 

PREPARED STATEMENT OF MIKE JOHANNS

Mr. Chairman and distinguished members of this Committee, I am pleased to appear before you to discuss the fiscal year 2008 budget for the Department of Agriculture (USDA). 

I am joined today by Deputy Secretary Chuck Conner; Scott Steele, our Budget 

Officer; and Keith Collins, our Chief Economist. 

It is a pleasure to come before the Committee to discuss U.S. agriculture and our 

efforts to make it stronger. I want to thank the Committee again this year for its 

support of USDA and for the long history of effective cooperation between this Committee and the Department in support of American agriculture. I look forward to 

working with you, Mr. Chairman, as well as the other Members to make progress 

on these issues during the 2008 budget process and to ensure strong programs for 

our Nation’s farm sector and many other USDA programs. 

Over the past year, USDA has worked with and heard from people throughout 

the Nation about the importance of agriculture to the economy and the everyday life 

of all Americans. I am happy to report that we have made much progress in meeting 

the needs of the Nation, improving the rural economy, and strengthening U.S. agriculture. I would like to point out that: 

—Under President Bush’s economic policy, rural America and U.S. agriculture has 

prospered. 

—Renewable energy production has grown dramatically and is contributing to the 

energy security of the United States as well as improving the farm economy. 

—Utilizing $91 million in emergency supplemental funding, USDA significantly 

increased its efforts to prepare for a potential influenza pandemic and participated in the worldwide effort to stop the spread of the H5N1 virus overseas. 

—We are making considerable progress in ensuring the safety of meat, poultry, 

and egg products. Recalls of meat and poultry and processed egg products have 
11 

been cut in half during the last 4 years due to improved oversight and the 

downward trend is continuing. 

—U.S. agricultural exports again reached a record level in 2006, and are forecast 

to set another record in 2007. The 2007 forecast level represents an increase 

of more than 50 percent since 2000. 

—We have continued our efforts to open new markets. During the past year, 

Trade Promotion Agreements were signed with Colombia and Peru, and negotiations were completed with Panama. 

—We remain committed to our objective of achieving fundamental reform of agricultural trading practices through the Doha Round of multilateral trade negotiations. Although no major breakthroughs have been achieved, we are actively 

engaged in discussions with our trading partners on technical aspects of each 

of the three pillars in the agricultural area. We continue to believe a successful 

outcome is achievable. 

—We are continuing to regain our beef export market. Markets have been reopened or maintained in the countries that closed their borders to U.S. beef 

products after the first detection of BSE. Recent progress has been made in 

such countries as Russia, Columbia, Peru, and Panama. 

—We have had tremendous response to MyPyramid, and I am confident that as 

awareness of the importance of eating a nutritious diet and being physically active increases, so will the health of Americans. 

On January 31, 2007, I announced a comprehensive set of 2007 Farm Bill proposals for strengthening the farm economy and rural America. The 2008 budget is 

based on the current Farm Bill. However, beginning in 2008, the budget incorporates a $500 million increase each year in the Commodity Credit Corporation 

(CCC) estimates to accommodate the cost of new Farm Bill proposals to be allocated 

among the various titles of the bill. 

2008 Budget 

The President and the Congress are facing many challenges. The President’s 2008 

budget meets these challenges by funding our highest, most important priorities, 

while exercising the fiscal discipline that is absolutely necessary to achieve the 

President’s goals of strengthening the economy and balancing the budget. 

Today, I will be focusing on the proposals contained in the 2008 budget. Let me 

take a moment to briefly point out how this budget supports our highest priority 

programs—programs that achieve results. This budget: 

—Fulfills our commitment to reduce trade barriers and expand overseas markets; 

—Supports the President’s vision for energy independence by significantly increasing funding for biofuels; 

—Continues programs vital to the protection of agriculture from disease, pests, 

and human threats, including avian influenza and BSE; 

—Supports policies that ensure Americans continue to enjoy a safe and wholesome food supply; 

—Provides sufficient resources to fully fund expected participation and food cost 

inflation in our major nutrition assistance programs; 

—Enhances the environment by providing a record level of funding to enroll a 

record number of acres into conservation programs; 

—Builds a strong rural economy by supporting policies that enhance job creation, 

improve rural infrastructure, and increase homeownership opportunities; and 

—Supports on-going basic and applied sciences that provide the technology and 

information necessary for the development of innovative solutions facing American agriculture; 

USDA also shares the responsibility of controlling Federal spending. This means 

doing more with less, eliminating programs that are not getting the job done, cutting out wasteful spending, and reforming the earmark process. We are pleased that 

the House Joint Resolution for 2007 continuing appropriations significantly reduced 

USDA’s earmarks, and hopes that the Committee will continue those worthy efforts. 

So, you will see throughout the 2008 budget proposals that terminate or reduce 

spending. These proposals will produce real savings in both mandatory and discretionary spending. 

The President’s 2008 budget, which was released on February 5, 2007, proposes 

to increase USDA’s total budget authority from $88 billion in 2007 to $91 billion 

in 2008. For the Department’s discretionary budget, the overall request is $20 billion, about the same level as in 2007 level. The discretionary appropriation request 

pending before this Committee, which does not include the Forest Service, is $16 

billion. 

I would now like to focus on some specific program highlights. 
12 

Pathogenic Avian Influenza (AI) 

The infrastructure developed in response to outbreaks of highly pathogenic AI has 

enabled the Department to strengthen its global leadership in combating its spread 

and keeping it from entering the United States. Utilizing the supplemental funding 

provided in fiscal year 2006, the Department has worked closely with international 

agencies and other countries to enhance the international capacity and technical 

skills necessary to keep AI at bay. Domestic efforts have built upon USDA programs 

that have been in place for more than two decades to prevent an outbreak of dangerous strains of AI in our country. The 2008 budget requests a total of approximately $82 million to continue and enhance on-going efforts related to AI, an increase of $32 million over the amount 

estimated for 2007, not including supplemental funds. Of the increase, $20 million 

is related to continuing activities related to highly pathogenic AI, including: surveillance and diagnostics work; preparedness and response efforts; and international 

veterinary capacity building. An additional increase of $6 million is requested for 

the development of methods to detect AI in the environment and further AI research, including development of poultry vaccines. Another $6 million increase is requested to expand activities related to the on-going program for low pathogenic AI. 

Low pathogenic AI is of concern for its potential costs to the poultry industry and 

potential ability to mutate into highly pathogenic AI. 

Food and Agriculture Defense Initiative 

USDA continues to be vigilant in ensuring the safety of agriculture. The Department is a strong partner in the Administration’s efforts to prepare for any potential 

bioterrorist attack. We have established effective working relationships with other 

Federal agencies to ensure an appropriate Government response to a wide array of 

threats. 

To protect American agriculture and the food supply from intentional terrorist 

threats and unintentional introductions, the budget proposes $341 million for 

USDA’s part of the President’s Food and Agriculture Defense Initiative. Funding for 

ongoing programs is $325 million, an increase of nearly $148 million from the 2007 

level. Of the total amount for on-going programs, an increase of about $36 million 

for Food Defense would enhance the Food Safety and Inspection Service’s (FSIS) 

ability to detect and respond to food emergencies and for USDA research agencies 

to conduct related research. For Agriculture Defense, the budget includes an increase of about $39 million for research on emerging and exotic diseases to, among 

other things, improve animal vaccines and facilitate rapid response to agricultural 

threats. An additional $72 million would be used to improve USDA’s ability to safeguard the agricultural sector through enhanced monitoring and surveillance of pest 

and disease threats, improved response capabilities, and other efforts, such as an 

expansion of the National Veterinary Stockpile. 

In order to keep USDA in the forefront of avian disease research, the budget requests an increase of $16 million for planning and design of the Consolidated Poultry Research Facility in Athens, Georgia. This facility is critically needed to conduct 

research on exotic and emerging avian diseases that could have devastating effects 

on animal and human health. 

Food Safety 

Americans enjoy one of the safest food supplies in the world. Data from the Centers for Disease Control and Prevention shows improvements based on historical reductions in the incidence of foodborne illness. The continued reduction in illnesses 

from pathogens associated with the consumption of meat, poultry, and egg products 

is a tremendous success story. These results demonstrate that we are moving in the 

right direction. USDA is committed to continuing this positive trend in the future. 

We will continue to pursue the development and implementation of risk-based inspection systems that are grounded in science. These systems will make us smarter 

about where we focus our resources and our expertise to make the most difference. 

The 2008 budget requests record funding of nearly $1.1 billion, an increase of 

$104 million over 2007, for FSIS to protect the Nation’s supply of meat, poultry and 

egg products. This includes $930 million in appropriated funds. About 80 percent 

of the increase in funds is for pay, including monies required for Federal and State 

inspection programs to meet the demand for inspection services. The budget requests an increase of $21.7 million to expand the Food Emergency Response Network (FERN and strengthen food and agriculture defense. With this funding, FSIS 

will continue to develop the network of food laboratories and the result will be an 

increase in the capability of a network of coordinated Federal, State and local laboratories to handle large volumes of testing that would be needed for biosurveillance 

or in the event of a widespread food emergency. 
13 

The budget estimates that $135 million in existing user fees for voluntary inspection will be collected. For 2008, we will be submitting authorizing legislation to Congress to collect an additional $96 million in user fees. The budget does not assume 

the use of these fees. Discretionary funding to cover the total cost of the program 

is included in the request. This includes legislation to authorize a licensing fee to 

collect $92 million from meat, poultry, and egg products establishments. In addition, 

it would also authorize the agency to recover $4 million for the cost of providing 

additional inspection services from establishments as a result of performance failures, such as sampling violations, recalls, or an outbreak of foodborne illness. 

Energy 

Another priority for the Department and the Administration is a continued focus 

on expanding renewable energy. I sit before you today with the belief that renewable energy, supported by American agriculture and forestry, holds tremendous potential for the Nation’s future. We are starting to see that the benefits of renewable 

energy are far-reaching and will continue to grow as energy production from renewable sources continues to expand in the near future. Renewable fuels reduce our dependence on foreign oil, which contributes to our Nation’s security. Renewable fuels 

are environmentally friendly and produce fewer emissions of greenhouse gases than 

fossil fuels. Furthermore, renewable fuels are often produced in rural areas, providing a source of income for farmers, ranchers and rural Americans. 

USDA is committed to ensuring that renewable fuels production continues to help 

meet the Nation’s energy and security needs. The budget includes $396 million, an 

increase of $161 million, for the Department’s energy initiatives. Part of USDA’s 

commitment is demonstrated through research activities. The 2008 budget includes 

$70 million, an increase of $29 million, for energy research supported by ARS and 

CSREES. A majority of this research will focus on improving cellulosic ethanol production by improving feedstock growth potential and introducing new ways to harvest, handle, and transport the feedstock to production facilities. In addition, USDA 

is working to improve the conversion efficiency of biomass feedstocks into biofuels 

and bioproducts. This research will lead to new opportunities to expand renewable 

fuel’s potential to meet the Nation’s energy needs, while creating significant opportunities for farmers, ranchers, and rural communities. 

In addition to this research, the budget would make available nearly $320 million 

in grants, guaranteed loans, and other efforts to support the commercialization of 

renewable energy production. Through the Rural Development mission area, USDA 

is making financial support available to leverage private sector funding for small 

and large-scale, renewable energy generation activities. This financial support provides incentives for individuals and cooperatives to choose renewable energy production methods. USDA has also encouraged the development of various renewable energy projects, including ethanol plants and wind farms. We remain committed to expanding these opportunities to improve the Nation’s energy security and environment, while providing additional possibilities to U.S. agricultural and rural communities. 

Farm Commodity and Agriculture Credit Programs 

Rising crop prices, particularly for corn, has had a major impact on farm program 

costs, which is due to the rapid growth in ethanol production. As a result, farmers 

are relying more on the market for revenue rather than payments from the Government. As such, net outlays for the farm commodity programs funded through the 

Commodity Credit Corporation (CCC) are expected to decline significantly in 2007 

and 2008 as rising prices for corn and other major commodities are reducing outlays. Compared to estimates made when the 2002 Farm Bill was enacted, actual 

spending for CCC funded programs, which excludes some conservation programs, 

has been about $17 billion below the 2002 projections when ad hoc disaster assistance is excluded. Beginning in 2008, the budget incorporates a $500 million increase 

each year in the CCC estimates to accommodate the cost of the new Farm Bill proposals. This additional funding will be spread among various titles of the Farm Bill. 

USDA’s farm credit programs provide an important safety net for farmers by providing a source of credit when they are temporarily unable to obtain credit from 

commercial sources. The 2008 budget supports about $3.4 billion in direct and guaranteed farm loans. The 2008 budget proposes loan levels that generally reflect actual usage in recent years. 

The budget requests $1.5 billion for the Farm Service Agency to deliver farm programs. This level of funding will support approximately the same number of staff 

years as in 2007 and includes the funding to support ongoing operational needs 

based on current programs and the current delivery system. Once the parameters 
14 

of the new Farm Bill are known, we may need to re-evaluate resource needs for program implementation, including staffing and information technology (IT). 

Crop Insurance 

Crop insurance is designed to be the primary Federal risk management tool for 

farmers and ranchers. In 2008, crop insurance is expected to provide coverage for 

nearly $68 billion in risk protection, double the amount of coverage provided as recently as 2000. This growth has been accomplished, in part, through the development of new and innovative plans of insurance. These innovations have expanded 

coverage to new crops or improved the coverage available under existing policies. 

Over the years, Congress has challenged USDA to expand the availability of crop 

insurance to under-served commodities, in particular, to livestock and pasture, 

rangeland, and forage. I am happy to say that USDA is meeting that challenge. 

Currently, the crop insurance program offers protection for swine, fed cattle, feeder 

cattle; and, new for 2007, lamb. Also new for 2007, the crop insurance program is 

offering two innovative programs covering pasture, rangeland, and forage. 

In order to build on these successes, Risk Management Agency’s (RMA) aging information technology (IT) system needs to be modernized. The existing IT system 

has been in service for more than a decade and needs to be upgraded to address 

evolving programmatic needs. That system was designed for a much smaller and 

simpler program. As a result, RMA must use numerous manual over-rides and 

work-arounds to support the new insurance products. This manual intervention increases the costs to maintain and operate the system. It also increases the risk of 

data errors that could jeopardize the integrity of the crop insurance program. The 

2008 budget includes a legislative proposal to initiate a small participation fee in 

the Federal crop insurance program to fund modernization and maintenance of a 

new IT system. The fee would generate about $15 million annually, which would 

initially supplement the annual appropriation to modernize the IT system. However, 

in future years, the fee would replace appropriated funding for IT maintenance. 

In addition, the 2008 budget includes about $79 million in discretionary funding 

to administer the Federal crop insurance program, compared to about $76 million 

for 2007. The increase would accommodate pay costs and inflationary increases. The 

budget also includes a general provision to fund data mining and the common information management system through the crop insurance mandatory account. 

International Programs 

Expanding access to global markets is essential for U.S. food and agricultural 

products, and plays a critical role in our efforts to provide a prosperous future for 

America’s farmers and ranchers. In this regard, we must ensure that our producers 

and exporters have the tools they need to compete for a greater share of the benefits 

flowing from trade agreements and the resulting expansion in global markets. 

Our 2008 budget proposals support our continued commitment to trade expansion 

activities. Increased funding is provided for the Foreign Agricultural Service (FAS) 

to maintain its overseas office presence and continue its representation and advocacy activities on behalf of American agriculture. 

The FAS budget includes funding to restore the Cochran Fellowship Program to 

its traditional annual appropriated level of $5 million and also provides funding for 

FAS trade capacity building activities. Those activities assist developing countries 

to strengthen their agricultural policy making and regulatory systems adhere to 

internationally recognized standards and become better trading partners. By assisting them to adopt policies that meet World Trade Organization standards and adopt 

regulatory systems that are transparent and science-based, we improve access for 

U.S. products to their markets. 

For the foreign food assistance programs, the budget continues to place the highest priority on meeting emergency and economic development needs of developing 

countries. Appropriated funding for the McGovern-Dole International Food for Education and Child Nutrition Program is increased to $100 million, which will allow 

USDA to extend school feeding and educational benefits to about 2.5 million women 

and children during 2008. The program is helping children in countries with severe 

educational and nutritional needs. In recent years, more than 13 million children 

throughout the world have received benefits from the McGovern-Dole program and 

its predecessor, the Global Food for Education Initiative. 

In order to respond to emergency food needs during 2007, supplemental appropriations of $350 million are being requested for the Public Law 480 Title II donations program. The additional funding will be used to address urgent humanitarian 

needs in the Darfur region of Sudan, including for refugees and others in Chad and 

surrounding areas who are affected by the violence. The funding will also assist in 
15 

meeting other critical food needs, particularly in the Horn of Africa, southern Africa, 

and Afghanistan. 

For 2008, the budget requests appropriated funding of $1.2 billion for the Public 

Law 480 Title II program, which is expected to support the donation of 2.5 million 

metric tons of food commodities. In addition, to help improve the timeliness, efficiency, and effectiveness of the U.S. Government’s response to emergency situations, 

increased flexibility is requested in the purchasing of Title II commodities. 

In addition, the budget requests funding in the Office of the Secretary to support 

the Department’s efforts to assist in agricultural reconstruction activities in Afghanistan and Iraq. USDA is providing technical advisors assigned to the Ministry of Agriculture in Iraq who are assisting in agricultural planning, extension, and food 

safety and inspection. Other agricultural advisors are serving on the Provincial Reconstruction Teams (PRTs) working in the rural provinces of Afghanistan and Iraq 

on activities such as irrigation system rehabilitation, post-harvest loss reduction, 

marketing system improvements, and livestock health. These advisors are providing 

much needed, valuable assistance in addressing a wide range of problems brought 

on by years of neglect and mismanagement in the agricultural sectors of these two 

countries. 

Conservation 

USDA also fosters environmental stewardship through conservation programs 

supported with mandatory CCC funding. The 2008 budget reflects an unprecedented 

commitment to conservation and includes nearly $4 billion in mandatory funding to 

provide conservation financial and technical assistance on a cumulative total of 215 

million acres, the greatest amount of conservation assistance provided in the Nation’s history. 

Within the total amount of mandatory funds, the budget proposes over $455 million for the Wetlands Reserve Program (WRP), an increase of $191 million, or nearly 

72 percent over 2007. The projected WRP enrollment for 2008 would be the largest 

ever, involving up to 250,000 acres, and will bring the total acreage enrolled in the 

program to 2,275,000 acres, the maximum level authorized by the 2002 Farm Bill. 

The WRP is the principal supporter of the President’s goal to restore, protect, and 

enhance 3 million acres of wetlands by 2009. 

The Conservation Reserve Program (CRP) accounts for more than half of the mandatory funds with total funding of just over $2 billion. Enrollment in CRP is expected to decline by about 9 percent to 33.6 million acres in 2008. Although continuous sign-ups will be maintained, no general signups are assumed for 2007 and 

2008 due to the increase in corn production to meet the demand for ethanol. Funding for the Environmental Quality Incentives Program will be maintained at $1 billion to treat more than 170 million acres in 2008. The budget requests an increase 

of $57 million for the Conservation Security Program for total funding of $316 million. This level of funding will continue support to the more than 19,000 contracts 

signed in prior years. 

The 2008 budget includes $825 million in discretionary funding for on-going conservation work, a decrease of $94 million below the 2007 level. This level of funding 

supports programs that provide the highest quality technical assistance to farmers 

and ranchers and address the most serious natural resource concerns. The budget 

includes a proposal to reduce the number of Federal coordinator positions funded 

under the Resource Conservation and Development (RC&D) program, for a savings 

of $36 million. Under this proposal, the number of authorized RC&D areas would 

be maintained at the current level of 375, but coordinators would provide assistance 

to multiple areas by focusing on programmatic oversight. 

Rural Development 

Through Rural Development (RD) programs, USDA improves the economy and 

quality of life in all of rural America by supporting essential housing and public facilities, such as water and sewer systems, health clinics, and electric and telecommunication systems. In addition, RD promotes economic development by providing guaranteed loans to businesses in coordination with the private sector. 

The 2008 budget supports $14.9 billion for the RD programs. This is about $985 

million more than the amount estimated to be available for 2007. At the requested 

level, most key rural development programs would be maintained at their historic 

operating levels. 

The 2008 budget does, however, contain some important changes in policy and 

funding priorities. In particular, the 2008 budget significantly increases funding for 

single-family guaranteed loans. Guaranteed loans, which are unsubsidized, have accounted for almost all of the growth in USDA’s homeownership assistance. Due to 

the success of guaranteed single-family loans in meeting the needs of rural citizens, 
16 

the budget does not include funding for direct single-family loans, a reduction of 

nearly $1.2 billion. While not funding direct loans is a change in policy for USDA, 

it is consistent with Federal housing policy as reflected in the programs administered by the Departments of Housing and Urban Development and Veterans Affairs. 

Moreover, it reflects recent changes in the home mortgage market that allow more 

low-income families to qualify for private sector loans. USDA’s single family guaranteed program is expected to provide 39,000 homeownership opportunities in 2008. With regard to multi-family housing, the 2008 budget includes $567 million for 

rental assistance payments. This funding is needed to provide for a higher rate of 

renewals due to recent action to reduce the renewal period from 5 to 1 year. The 

2008 budget also includes $27.8 million to continue the Administration’s initiative 

to revitalize USDA’s portfolio of multi-family housing projects, which are home to 

close to half a million low-income families. A recent Supreme Court decision allows 

project sponsors to prepay their loans and convert their projects to uses other than 

low-income housing, putting tenants at risk of higher rents and potential loss of 

housing. The Administration’s initiative includes providing housing vouchers to protect the rents of tenants of projects that are withdrawn from the portfolio, as well 

as the restructuring of existing loans in exchange for the project sponsor’s agreement to stay in the program and make improvements to their projects. A pilot program, as authorized by the 2006 Appropriations Act is already underway. The Administration plans to resubmit to the Congress draft legislation to authorize debt 

restructuring and other revitalization incentives. 

For the on-going electric and telecommunications programs, the 2008 budget supports about $4.8 billion in direct loans, of which $4.1 billion would be for the electric 

programs. Most electric loans would be at interest rates that are currently comparable to the direct municipal and direct Treasury rate programs. Combined, these 

programs would simplify the overall program with essentially no adverse impact on 

borrowers. The electric program would focus on financing the distribution and transmission of power and the improvement of existing generation facilities. The commercial sector should be relied on for financing new power generation. For the water 

and waste disposal program, the 2008 budget provides for $349 million in grants 

and almost $1.1 billion in direct loans. This reflects a lower grant-to-loan ratio than 

the current program because the Administration is re-proposing its plan to reduce 

interest rates in exchange for a reduced amount of grants. For most rural communities, which receive a combination of loan and grant assistance, the reduction in 

interest rates would be of greater benefit because it would reduce the overall debt 

servicing costs of their projects. 

The 2008 budget includes additional funding for the renewable energy and energy 

efficiency loan and grant program. It includes $15 million for grants and supports 

$195 million in guaranteed loans, compared to $11 million for grants and $175 million in loans estimated to be available for 2007. 

The business and industry guaranteed loan program would be increased to $1 billion, which is the historic funding level for this program. This program and the 

intermediary re-lending program have been an important source of job creation in 

rural communities. 

Research 

Over the last century, productivity has been a major focus of agricultural research. Driven by advances in plant and animal genetics, nutrition, and health, this 

research has paid off with major gains. Agricultural research is taking on the challenges of a new century and USDA’s leadership will continue through innovative research in bioenergy production, obesity prevention, and food and agricultural defense. 

Advances in science have opened new frontiers in agricultural research that have 

put solutions to national challenges within our reach. It is important that we seize 

the opportunity by focusing our resources and efforts on the highest priority work 

relevant to the needs of producers and consumers of agricultural products. Our 

budget requests over $1 billion for the Agricultural Research Service. The proposed 

level includes $104 million in increases for high priority research on food and agricultural defense, bioenergy, plant and animal genomics and genetics, and human 

nutrition and obesity prevention. These lines of investigation have great potential 

to benefit producers and consumers; assure an abundant, safe, and inexpensive supply of food; and ensure the preservation of our natural resource base. The budget 

proposes elimination of $293 million of earmarked research and facility projects in 

ARS. 

A key factor in the success of agricultural research has been our continuing partnership with the land-grant universities and other performers of agricultural, natural resource and food research. These institutions provide a unique set of expertise 
17 

in the range of scientific disciplines needed to address complex issues facing the 

food, agriculture and natural resource communities. Further, these partnerships foster the transfer of knowledge through higher education and the unique system of 

Extension that has been so successful in America. Our budget continues our support 

for university-based research, higher education and extension programs and addresses the need to focus those resources on the highest priorities. Under our proposal we are placing a greater emphasis on merit-based, peer-reviewed grants to 

achieve the highest quality research from taxpayer dollars. In addition, $157 million 

of earmarked Cooperative State Research, Education, and Extension Service research grants and lower priority projects would be eliminated. A major element of the research budget is an increase of $68 million, for total funding of $257 million, for the National Research Initiative—the Nation’s premier 

competitive, peer-reviewed research program for fundamental and applied sciences 

in agriculture. This increase includes funding for bioenergy and biobased fuels, one 

of the Department’s highest priority initiatives. It also supports integrated projects 

that focus on water quality, food safety, organic transition, and pest management. 

In total, $29 million would be added to CSREES programs for research in bioenergy. 

A longstanding part of USDA support for the university research partnership has 

been through the Hatch Act and McIntire-Stennis Act formula grant programs. As 

stated above, the budget continues funding for these programs with a proposal to 

emphasize funding for competitively awarded multi-state research programs to ensure the highest quality research proposals are supported. We will be working in 

close consultation with our university partners to craft the details of these modifications. 

The budget includes an increase of $25 million to support the 2007 Census of Agriculture, the most comprehensive source of statistically reliable information regarding our Nation’s agriculture. With information collected at the national, State, and 

county levels, the Census provides invaluable, comprehensive data on the agricultural economy which are relied upon to keep agricultural markets stable and efficient. 

Nutrition Assistance 

The budget contains sufficient resources to fully fund expected participation and 

food cost inflation for the Department’s three major nutrition assistance programs— 

Food Stamps; Women, Infants and Children (WIC); and Child Nutrition. Participation levels fluctuate with economic conditions and the budget keeps pace. WIC participation is expected to grow slowly in 2008 to a total of 8.3 million participants, 

while Food Stamp participation is estimated at 26.2 million, roughly the 2007 level. 

School Lunch participation is estimated to grow about 2 percent to keep pace with 

the growing student population, as it has in recent years, to a new record level of 

31.5 million children per day. 

For Food Stamps, legislation will be proposed that would exclude all retirement 

and education savings accounts from eligibility determinations regardless of how 

other programs treat them. By 2010, this would allow about 98,000 additional people to participate who, otherwise, would have been ineligible unless they spent down 

their retirement and education savings. This would add an estimated $44 million 

in costs for 2008 and about $138 million in 2010 when fully implemented. The 2008 

budget also reproposes legislation to restrict participation among certain households 

with incomes or resources above normal eligibility thresholds. Affected households 

are those that do not receive cash Temporary Assistance for Needy Families (TANF) 

benefits, but become categorically eligible for food stamps because they receive a 

TANF-funded service, such as a one-time referral. This change would reduce costs 

by an estimated $65 million in 2008, with additional savings in subsequent years. 

The WIC request provides full funding for all those estimated to be eligible and 

seeking services. At the same time, the Department will work with stakeholders to 

contain costs and continue to improve the program’s performance. WIC legislative 

proposals include limiting administrative funding to the 2006 per participant level 

and limiting categorical eligibility to those with incomes under 250 percent of poverty. 

The 2008 budget reproposes elimination of the Commodity Supplemental Food 

Program (CSFP), which is not available nationwide and duplicates two of the Nation’s largest Federal nutrition assistance programs—Food Stamps and WIC. Eligible women, infants and children participating in CSFP will be encouraged to migrate to the WIC Program. Eligible elderly CSFP recipients will be encouraged to 

migrate to the Food Stamp Program, where most are believed to be eligible. The 

budget includes temporary transitional benefits for CSFP participants 60 years of 

age or older equaling $20 per month for the lesser of 6 months or until the recipient 

starts participating in the Food Stamp Program. 
18 

As I mentioned earlier, we have had a great deal of success in promoting healthy 

eating habits and active lifestyles with MyPyramid. The MyPyramid website has received 2.6 billion hits since it was made available in April 2005. In order to continue 

this success, the budget includes an increase of $2 million to make enhancements 

to MyPyramid and to begin planning for the 2010 Dietary Guidelines for Americans. 

This supports two pillars of President Bush’s HealthierUS Initiative, to eat a nutritious diet and to be physically active, and will help reduce obesity in America. 

Department Management 

The 2008 budget continues our progress in improving the overall management of 

the Department. Increased funding is being sought for selected key priorities including: 

—Replacing the Department’s outdated, core financial system and supporting systems that no longer meet all Federal standards for financial reporting and management. The budget requests funding to begin a multi-year implementation of 

a replacement system that will provide consistency and increase efficiencies for 

financial reporting across the Department. The new system will strengthen internal controls, eliminate material weaknesses, and diminish improper payments, which will improve the Department’s overall financial management. 

—Expanding Civil Rights compliance reviews of agency hiring practices and program activities. These reviews allow the Department to identify and address 

issues of inequality and unfairness in personnel decisions and the delivery of 

its program benefits. 

—Continuing capital improvements to USDA facilities to ensure that employees 

and customers have a safe and modern working environment. 

In closing, I want to emphasize that the USDA budget fully supports the President’s goals to strengthen the economy, increase security, and restrain spending. 

The budget before you addresses these goals by funding our highest priorities. These 

funding priorities strengthen agriculture and rural economies, protect our food supply, build on our conservation efforts, and provide for the neediest individuals. 

That concludes my statement. I look forward to working with Members and staff 

of the Committee and will be glad to answer questions you may have on our budget 

proposals. 

PREPARED STATEMENT OF BOYD K. RUTHERFORD, ASSISTANT SECRETARY FOR

ADMINISTRATION, DEPARTMENT OF ADMINISTRATION

Mr. Chairman and members of the Subcommittee, thank you for the opportunity 

to submit this statement supporting the President’s budget proposal for fiscal year 

2008 for the Department of Agriculture’s (USDA) Departmental Administration. 

Departmental Administration (DA) is at the core of USDA’s management initiatives. Through a strong commitment to the President’s Management Agenda, we 

have realigned our services to provide continued leadership and better program 

management, resulting in greater efficiencies, enhanced internal controls and effective customer service. DA enhances Department-wide strategies by ensuring appropriate administrative policy and by providing essential management to all agencies 

and staff offices. This is accomplished through our Department-wide management 

services, which include: human capital management; facilities operations; security 

services; procurement and property management; small business utilization; Administrative Law support; and ethics guidance. 

FISCAL YEAR 2008 OBJECTIVES

DA has the following objectives for fiscal year 2008 that contribute to the Department’s ability to successfully fulfill its mission: 

—Ensure USDA has a diverse, ethical, results-oriented workforce able to meet 

mission priorities and work cooperatively with USDA partners and the private 

sector. 

—Ensure USDA has a trained acquisition workforce with the procurement policies 

and systems needed to ensure responsiveness, high quality, cost-effectiveness, 

and accountability using an increasingly diverse vendor pool and range of products. 

—Promote the efficient and economical use of USDA’s resources to support customers, promote organizational productivity, and ensure accountability. 

—Provide the policies, technical guidance, and operating environment that enhance the safety and security of USDA personnel, information and facilities, 

and the continuity of its vital programs and operations. 

—Provide formal adjudicative support. 
19 

—Expand the implementation of the BioPreferredSM Program within USDA and 

other Federal agencies. The BioPreferredSM Program, authorized in the 2002 

Farm Bill, is a Federal procurement program that requires that Federal agencies provide a preference for the purchase of USDA designated biobased products. In fiscal year 2008 DA will be jointly focused on establishing USDA as a 

leader in biobased purchases and providing support and guidance to other Federal agencies and to biobased manufacturers. 

FISCAL YEAR 2008 REQUEST

DA’s fiscal year 2008 budget request is divided into three separate appropriations: 

DA Direct; Agricultural Building and Facilities and Rental Payments; and Hazardous Material Management. 

DA DIRECT

The DA Direct fiscal year 2008 budget is $24,608,000, which funds personnel and 

office operations costs. The increased request will address the following: 

—An increase to cover personnel costs for 2007 and 2008. This appropriation 

funds administrative support in the National Capital Area and on-going programs in human capital management and small business utilization across the 

Department. 

—An increase for Continuity of Operations (COOP) for the Office of the Secretary, 

providing guidance and training to the mission areas, and providing support 

and training to USDA’s National Emergency Preparedness Team. These efforts 

will ensure USDA is compliant with Executive Orders and Presidential Directives associated with Emergency Preparedness and requirements for Executive 

Branch COOP. 

AGRICULTURE BUILDINGS AND FACILITIES AND RENTAL PAYMENTS

The fiscal year 2008 budget request for Agricultural Building and Facilities and Rental Payments is $216,837,000, of which $156,590,000 is for rental payments to 

the General Services Administration (GSA) and Department of Homeland Security 

for security payments and $60,247,000 for Building Operations and Maintenance. 

The increased request addresses the following: 

—An increase for the Central Rent Account is needed to fund the estimated cost 

of GSA space assignments and physical security costs payable to the Department of Homeland Security, increased lease expenses, maintenance services, 

and preventative maintenance services of the fire alarm and switchgear systems 

located at the USDA Headquarters Complex. 

—An increase for repairs and maintenance projects for the USDA South Building. 

The South Building of the Headquarters Complex was built between 1930 and 

1936 and houses approximately 4,600 employees. It is in much need of repair 

and maintenance. Repairs are needed to bring several major systems up to current code requirements and to generally improve employee safety. Providing a 

safe and healthy work environment for our employees supports our Human 

Capital Objective. 

—An increase to cover the rising cost for steam and electric utilities for the USDA 

Headquarters Complex. GSA has notified USDA to expect significant increases 

in 2007 and 2008 utility costs. In 2005, the price of GSA’s district steam increased by 22 percent. Paying utility costs from current Building Operations 

funding will reduce funding available to address the existing maintenance and 

repair needs for the facilities and possibly contribute to future system failures. 

—An increase for annual contract increases due to the Fair Labor Standards Act 

and collective bargaining. This request is needed to pay mandatory increases for 

payroll and other fixed and discretionary costs associated with operating USDA 

facilities. This request supports DA’s continuing efforts to provide high quality 

services so that USDA personnel have the space, facilities, mail and property 

services, personnel support and resources needed to deliver their program services in a timely and effective manner. 

—An increase to support the Building Operations and Maintenance staffs in performing preventive and routine maintenance and repairs in the USDA Headquarters’ Complex, including the George Washington Carver Center. This increase will cover rising general operating costs and preventive maintenance repairs to major systems within the Headquarters’ Complex. The lack of funding 

in previous years for major repairs has led to a series of system failures which 

includes: repairs for building roofs and major plumbing, electrical, heating, and 

air conditioning systems. Instead of being able to address these matters before 

they fail, the Department is often patching and repairing damage resulting from 
20 

the failure of systems long past their useful life. Routine maintenance and 

minor repairs to major systems, when done on a timely basis, prolong the life 

of equipment and avoid costly repairs and replacement if the equipment is allowed to fail. 

—An increase for the 2007 and 2008 pay costs. This increase is necessary to be 

able to maintain this office’s current staffing levels without compromising its efforts to provide a safe workplace for USDA Headquarters and the George Washington Carver Center. 

HAZARDOUS MATERIALS MANAGEMENT

The fiscal year 2008 budget request for Hazardous Material Management is 

$12,200,000. The increase represents pay costs. This request will fund clean-up activities under the Comprehensive Environmental Response, Compensation, and Liability Act (‘‘CERCLA’’) and the Resource Conservation and Recovery Act (‘‘RCRA’’). 

The purposes of the Hazardous Materials Management Program are to cleanup and 

restore USDA-managed lands. 

CONCLUSION

The goal of DA is to provide the tools necessary for USDA to accomplish its mission of providing effective leadership on food safety, agriculture, and natural resources. Accordingly, we respectfully ask for your support in this effort. 

Thank you for this opportunity to present Departmental Administration’s fiscal 

year 2008 request. 

PREPARED STATEMENT OF DAVID M. COMBS, CHIEF INFORMATION OFFICER

INTRODUCTION

Mr. Chairman and members of the Subcommittee, thank you for the opportunity 

to share with you our progress on using information technology (IT) to improve service delivery to the customers of the Department of Agriculture (USDA), while implementing Enterprise Architecture (EA) principles and Electronic Government 

(eGovernment) throughout the Department. 

USDA participates in 22 of the 30 government-wide President’s Management 

Agenda (PMA) eGovernment initiatives and eight of the nine lines-of-business. At 

the same time, under the framework of the Department’s EA, the Office of the Chief 

Information Officer (OCIO) is managing USDA IT investments to promote collaboration across common lines-of-business, reducing duplication through our internal Enterprise Shared Services, and finding savings by leveraging the USDA’s size/economies-of-scale in Department-wide IT acquisitions. 

The President’s fiscal year 2008 budget request for OCIO is $16.4 million to continue to guide the Department’s IT Strategy. We are requesting approximately 

$663,000 to cover pay costs. 

USDA’S FISCAL YEAR 2008 INFORMATION TECHNOLOGY INVESTMENT SUMMARY

During the fiscal year 2008 USDA budget preparation process, OCIO staff scrutinized agency IT investment plans to ensure alignment with USDA program delivery 

plans as well as the USDA EA. In fiscal year 2008, the Department is requesting 

about $2.1 billion for IT. Components of the IT portfolio include: 

—$816 million (39 percent of fiscal year 2008 IT spending) for transfer to the 

States for the development and maintenance of automated systems to support 

Food Stamps, WIC, and related programs. 

—$1.3 billion in IT discretionary funding as broken down, includes: 

—$467 million (36 percent) for support services (e.g. architects, design engineers, project managers, and consultants). The Department seeks to use small 

businesses, especially disabled veteran owned businesses for these services. 

—$373 million (27 percent) for Federal IT personnel costs. 

—$170 million (13 percent) for computer and network equipment, such as routers, servers, workstations and printers. 

—$188 million (15 percent) for out-sourced services (e.g. telecommunications, 

help desk services, technical design and architect services). 

—$93 million (7 percent) for software to support our data centers, desktops, 

helpdesks and other hardware. 

Overall, the IT related proposals in this request represent about 3 percent of the 

total $67 billion proposed for IT investments for the Federal Government in fiscal 

year 2008. 
21 

SERVICE CENTER MODERNIZATION INITIATIVE—(SCMI)

The Common Computing Environment (CCE) initiative is managed by OCIO 

working in collaboration with the Service Center Agencies’ (SCA). CCE supports 

over 36,000 Federal employees from the SCA and Information Technology Services 

(ITS), volunteers and partners in the delivery of over $55 billion in programs 

through our field office delivery system. The infrastructure is flexible and built 

around maximizing information sharing both within USDA and with other Federal, 

State and local agencies, the private sector, and USDA customers. 

The CCE is the commonly defined, commonly acquired, and commonly deployed 

IT infrastructure for the USDA county-based SCA, namely the Farm Service Agency 

(FSA), Natural Resources Conservation Service (NRCS), and Rural Development 

(RD). CCE was established to maximize data sharing, leverage investments and 

support true ‘‘one-stop shopping’’ for customers of the county-based agencies, and is 

managed by the ITS of OCIO. ITS serves as one unified organization dedicated to 

supporting both the shared and the diverse IT requirements of the SCA and their 

partner organizations. 

Several of ITS’ significant accomplishments in 2006 include: 

—Deployment of database management systems in support of several FSA applications was completed. 

—Completion of the Software Update Service (SUS) migration for large offices 

was completed. SUS keeps computers up-to-date with the latest critical updates, 

security updates, and service packs. To date, a total of 89 security patches have 

been tested, certified and deployed since SUS went live on August 2004. 

—Completed and awarded a Blanket Purchase Agreement (BPA) for operational 

contract support. This allows for the consolidation of many existing legacy contracts resulting in cost savings and increased operational efficiency. Another 

BPA was awarded that allows for the SCA to purchase hardware such as 

workstations and certain peripherals as their need dictates and as their funds 

allow. Over $13.7 million was spent on workstations at the end of fiscal year 

2006. 

—Deployed the Encrypted File System (EFS) to all laptops and tablet personal 

computers (PC) in the end user computer environment. EFS provides for the 

encryption of files, thus reducing the risk of compromising sensitivity data in 

the event of a lost or stolen laptop or tablet PC. 

—Conducted a disaster recovery test to simulate a loss of the Kansas City Web 

Farm; one major FSA financial application was successfully restored in St. 

Louis. Participated in the Kansas City Regional Inter-Agency Continuity of Operations Plan (COOP) Exercise. The Federal exercise tested COOP essential 

functions in the Greater Kansas City metropolitan area and their ability to efficiently perform their duties during emergency situations. More than 600 officials representing over 30 Federal agencies participated in the exercise. This 

was the third annual exercise and it exists as the largest interagency COOP exercise outside of Washington, DC. 

ITS management of CCE is maturing into a fee-for-service activity, while still supporting the ‘‘one-stop shopping’’ aims of the SCMI. This support includes contract 

consolidation, BPAs, and negotiating with the SCA for needed levels of service, 

while at the same time researching and implementing ways to achieve economies 

of scale. Because of the establishment of ITS as a fee-for-service entity, funds necessary to maintain the SCA shared IT infrastructure will be based upon the level 

of service delivery the SCA choose to effect. 

To that end, the fiscal year 2008 CCE budget is requesting no funds. For fiscal 

year 2008, the funds normally requested in the CCE appropriation can be found in 

the individual agencies’ budget requests. 

ITS provides unified management of the shared IT infrastructure of the SCA, including CCE but also non-CCE legacy technologies, and manages the use of the CCE 

funds. While the responsibility for developing IT applications remains with the 

agencies with little or no involvement from ITS, ITS does deploy the applications, 

provides the platforms they run on, and provides those components of the infrastructure that make them available, reliable, and secure. 

The organization measures its success against service level agreements with each 

of the SCA that define performance metrics and customer expectations. This provides openness to the agencies regarding the costs of IT infrastructure, maximum 

leverage for large-scale system management techniques and technologies, and a 

basis for continuous improvement. To implement these agreements, ITS and the 

SCA negotiated the service lines, the appropriate metrics, and acceptable levels of 

service. 
22 

Going forward in fiscal year 2008 and beyond, ITS will determine the agency obligations based on the service usage. This will be a more equitable method that can 

also provide the agencies with the information they need to reduce costs by effectively managing their IT infrastructure use. 

Congressional support for the CCE initiative has been key to its success. As we 

move forward with ITS, Congressional support will remain critical. 

TELECOMMUNICATIONS

USDA continues to evolve its telecommunications services to meet customer needs 

and provide secure infrastructure for the President’s expanding eGovernment initiatives. Following the successful deployment of the Department’s enterprise telecommunications network, the Universal Telecommunications Network (UTN), all 

USDA agencies are accessing the Internet via the UTN. USDA agencies continue 

to move their existing networks to the UTN. Agency network migration and optimization activities are achieved through a UTN Technical Review Board that is 

aligned with the Department’s IT governance methodology. 

We are also developing a Department-wide strategy for Voice over Internet Protocol (VoIP). During fiscal year 2007, we will complete an enterprise ‘‘roadmap’’ for 

USDA agencies to use in their businesses cases for VoIP investments. Additionally, 

USDA is heavily engaged in the General Services Administration (GSA) Network acquisition (which we expect will help further reduce our costs) and transition activities as well as migration activities for the transition to Internet Protocol version 6. 

NATIONAL INFORMATION TECHNOLOGY DATA CENTER (NITC) HOSTING

NITC continues to be USDA’s centralized source for IT services offering 24/7 operations and customer support. The organization began fee-for-services operations in 

July 1973. NITC serves the needs of over 25 USDA agencies, and more than 15 nonUSDA agencies. Our customer portfolio grew by 10.5 percent in fiscal year 2006 to 

a total of $85.6 million. 

Certified by GSA as a Level 4 Facility, as delineated in the Department of Justice 

Security Level standards, NITC operates as a Tier IV Electrically and Tier III Mechanically data center. An electrical upgrade has been completed that eliminates 

any single point of failure, increases availability, and adds redundancy. 

Recently NITC received an Office of Inspector General Unqualified Opinion in 

2006 for Internal Controls, the Commissioner’s Special Citation from the Food and 

Drug Administration for software development work, the Office of Small and Disadvantaged Business Utilization Award for Service Disabled Veterans, an ePermits 

Award, and a customer survey response of 85 percent satisfied or highly satisfied. 

INFORMATION SECURITY

For many years USDA has been slow to meet all Federal information security requirements. To address this situation, we have significantly improved the posture 

of our security program by shifting funds and developing policies and procedures. 

But there is still a tremendous amount of work to be done. The Federal Information 

Security Management Act (FISMA) and the Office of Management and Budget 

(OMB) Circular A–130 require all Federal agencies, to certify and accredit (C&A) 

their systems. Through this effort we have improved our security plans, updated 

and corrected our security documentation, tested our networks and applications for 

security weaknesses, and successfully engaged our business organizations in the discipline of security management. 

USDA IT security staffs are now in the process of addressing security issues that 

arose through our C&A activities. Action plans have been established to mitigate 

specific security weaknesses and implement improved controls, and to meet the 

FISMA performance measures designed by OMB. These plans also support the remediation of information security weaknesses identified during the Department’s 

implementation of the Circular A–123 review. Within the OCIO, we have established a rigorous process to track agencies in these corrective actions and to ensure 

they are completed in a timely and efficient manner. 

In order to eliminate the root causes for our security weaknesses, we must mature 

our information security processes. Automated tools are necessary to quickly and efficiently address cyber security risks. We must improve our ability to secure our 

data with monitoring devices and automated processes that assist in preventing disruption by intrusion or the introduction of malicious programs. During fiscal year 

2006, we deployed an improved incident tracking system to help us better manage 

and report detected breaches. We will continue to maintain a rigorous security 

training and awareness program which requires annual participation by all USDA 

and contract personnel. 
23 

Through good preventative planning, such as system C&A combined with improving the Department’s overall operational response to security challenges, we are reducing the risk associated with the electronic use and delivery of USDA information 

and services. Congressional support for the initiatives we have planned is critical 

to their achieving the desired outcome. 

ELECTRONIC GOVERNMENT

We continue to move aggressively to implement inter-agency and inter-Departmental services to support common needs. The primary goals of our approach are 

to reduce costs and improve the quality of interactions with our customers. 

USDA, along with our partners in the other Federal agencies, has worked hard 

over the past 5 years to simplify citizen’s access and interaction with their government. The results of these efforts are remarkable. As part of our support of the 

PMA’s promise of easy access to the government, customers may now easily locate 

USDA’s online information and services at www.usda.gov, and with ‘‘MyUSDA’’, 

visitors can customize USDA’s Web-site to provide immediate access to the information they regularly want to see. Currently, 59 Web-sites have moved to the Department’s Web standards, and another 31 agency sites are in the process of doing so. 

Our efforts reduced the burden on citizens, partners, and employees by simplifying 

access to the Department’s information and services and streamlining internal processes. In addition, USDA is a partner in 30 inter-Departmental projects to improve 

citizen access to government. All fourteen USDA rulemaking agencies migrated in 

2006 to the Federal Docket Management System which provides citizens easy access 

to USDA regulatory action. As a result, the public can review and comment on 

USDA regulatory actions through Regulations.gov. 

USDA posts all discretionary grants to Grants.gov which provides a single location for citizens to find funding opportunities and the ability to apply online for 

them using common forms, processes, and systems. 

USDA is a major geospatial data producer and contributor to the Federal Government’s www.geodata.gov. USDA’s partnership with the initiative allows cross-Departmental sharing of geospatial information and the opportunity for reducing costs. 

Through the USDA eAuthentication Service all USDA employees and over 

130,000 customers use a secure, single sign-on to access applications, thereby reducing our customer support needs through improved security and usability. In addition to the 230 USDA applications, users can also use their eAuthentication credentials to access any of the 24 systems integrated with the Federal E-Authentication 

Federation. The eAuthentication Service is a component of the streamlined implementation of Homeland Security Presidential Directive 12 (HSPD–12. 

AgLearn is USDA’s implementation of the E-Training initiative. The consolidation 

of training and learning management functions within AgLearn allows agencies to 

cooperate in developing, tracking, and purchasing training. Training that has 

proved successful for one agency can easily be made available for others, eliminating 

redundant costs for course development and sharing subject matter expertise to a 

broader audience and the coordination of agency purchases of online courseware 

provides volume discounts. USDA provides its mandatory training through AgLearn 

including the annual Ethics, Security Awareness, and Privacy Basics. In an average 

month, more than 16,000 AgLearn users complete nearly 27,000 training events. 

This has significantly reduced the overall USDA training costs normally associated 

with courses that require travel. 

ENTERPRISE ARCHITECTURE (EA) AND IT MANAGEMENT PROGRAMS

USDA is managing its EA as a high-level roadmap to achieve our organizational 

and business needs within an efficient IT environment. USDA’s EA program identifies similar processes and opportunities to improve and when possible share and 

reuse IT solutions across our agencies. We continue to assemble and refine the data 

needed, at both the Departmental level and within individual agencies, to better organize and analyze our business processes, information needs, and supporting technologies. The USDA EA Program is fully integrated with the Department’s IT Capital Planning and Investment Control (CPIC) process. USDA’s central CPIC body reviews, monitors and approves all major IT investments to ensure alignment with 

the Department’s strategic goals and objectives. The EA provides a formal basis for 

evaluating a single investment against other investments in terms of its contribution to enhanced delivery of customer services and opportunities for collaboration 

and reuse. In addition to strengthening the CPIC process, EA enables USDA to improve key Department-wide enterprise hardware, software, and service agreements. 
24 

The quality of this work is supported by an IT Project Management Program. 

USDA has trained 480 project managers who have helped us keep our IT projects 

on schedule and within budget. 

CONCLUSION

Mr. Chairman, we are always looking for creative ways to improve our services, 

reduce our costs and be good stewards of the tax payers dollars. With the continued 

support of this Subcommittee and the Congress, I am confident that we will continue to be successful in achieving our objectives. 

PREPARED STATEMENT OF CHARLES R. CHRISTOPHERSON, JR., CHIEF FINANCIAL

OFFICER, OFFICE OF THE CHIEF FINANCIAL OFFICER

Mr. Chairman and members of the Subcommittee, I am pleased to present the fiscal year 2008 budget request for the United States Department of Agriculture 

(USDA), Office of the Chief Financial Officer (OCFO) and the Department’s Working 

Capital Fund (WCF). 

The myriad of programs at the Department of Agriculture create a large financial 

organization. If compared to companies in the private sector, USDA would be both 

the ninth largest company and the ninth largest bank in the United States. Under 

the Chief Financial Officers Act of 1990 (CFO Act), the Chief Financial Officer 

(CFO) is responsible for the financial management of the Department including financial policy, personnel, systems, and budget execution. First, this testimony will 

address the key areas of my responsibility under the CFO Act and then proceed into 

the specific budget of the OCFO and WCF. 

The President’s budget for the Department of Agriculture is a comprehensive effort that involves the input of each mission area and staff office. The budgeting office does an exceptional job at managing and compiling the vast amount of financial 

information from each of the agencies within the Department. Over the years, the 

budget of the Department has remained relatively flat. The budget for fiscal year 

2008 is lean and focused on the highest priorities of the Department. 

Summary of Financial Operations and Processes 

In the area of financial operations and policy, the Department of Agriculture continues to make vast improvements in business processes, improper payments, and 

internal controls. For fiscal year 2006, the Department of Agriculture attained another clean opinion on its annual financial statements. 

Also during 2006, USDA achieved compliance with OMB Circular A–123, Appendix A by completing the assessment of Internal Controls over Financial Reporting 

in a single-year. This effort involved over 1,000 USDA employees from 29 agencies 

and staff offices. These employees documented over 5,000 controls within 13 financial cycles, 76 processes, and 92 financially significant systems. A significant number of the controls documented during this process were also tested. The assessment 

resulted in identifying four materials weaknesses which are: 

—Obligations—Forest Service and Commodity Credit Corporation 

—Management Estimates and Accruals—Forest Service and Commodity Credit 

Corporation 

—Producer Payments and Commodity Loans—Commodity Credit Corporation 

—Information Technology Controls—All Organizations 

Software Change Controls 

Disaster Recovery 

Access Control—Logical 

Access Control—Physical 

To manage the internal controls and eliminate material weaknesses, the Department has instituted a Senior Management Control Council, Chaired by the Deputy 

Secretary and Co-Chaired by the CFO with its committee members comprised of the 

highest ranking officials in each of our agencies and staff offices. The members of 

this committee are dedicated to the proper management and safe keeping of the 

funds of our Nation’s tax paying citizens. 

In order to provide the most effective and efficient financial operations, this last 

year we started a dedicated effort of refining several of our processes and are actively moving to uniform processes, procedures, and systems across USDA. For example, this year we formed a grants committee to document the grants process 

across all mission areas of the Department. In the near future, a formal USDA process, with all of the correct internal controls, will be formally documented and we 

will start reducing the 13 grant systems into one. This will not be a new system, 

but one developed from a system currently in use in one of the agencies. The agency 
25 

that currently operates that system will retain the management of the system while 

OCFO will manage the policy, process changes, and approve system modifications. 

We are also moving toward uniform processes for loans, contract invoices, and insurance. 

For all processes, we are moving toward solutions that provide electronic interfaces with the customers, automate document flow and approvals, and automate 

payments. The majority of the work will be accomplished with USDA employees and 

software that we currently own. 

Over this last year, we strengthened our policy on measuring improper payments 

to be in better alignment with the Improper Payments Act. Under the Act, agencies 

are required to measure both incorrect payment amounts and incomplete qualifying 

paperwork. Under this new policy, the Department continued to reduce incorrect 

payment amounts, but incomplete qualifying paperwork increased. The majority of 

the paperwork errors are in the Farm Service Agency. So as not to misinterpret the 

outcome of the information and to show the Department’s commitment to correcting 

the paperwork problem, we met with House and Senate Committees. During these 

meetings we communicated both the results and the corrective plan. The agency 

continues to move forward with the corrections and we expect to see a vast reduction in paperwork issues in this year’s review. 

Financial Systems 

The Department’s current primary financial systems were developed in the late 

1970’s and early 1980’s. For the 2008 OCFO budget, includes a request to continue 

the replacement of financial systems that are critical for payments, reporting, and 

fiscal management. 

Two financial systems are in need of replacement at USDA. The first is the core 

financial system; the second is the farm payments system. Currently the core financial system is comprised of nine general ledger systems which have not been supported by the vendor for several years. The systems do not meet Federal financial 

system requirements, and are showing the early signs of failure. The primary objective of the Financial Management Modernization Initiative (FMMI) is to replace this 

20 year old, outdated mainframe technology providing for Department-wide expanded functional capability, full integration of critical system components and 

high-quality production and customer support. FMMI also addresses a critical and 

growing need for better integration of program, financial, and budgetary information 

to support more efficient and effective management of USDA’s missions and improved delivery of programs against established performance goals and objectives. 

Based on both the risk and the savings, we have accelerated the implementation 

timeline of this system to a 3 year implementation. 

The farm payments system is in critical need of modernization through replacement. This system manages the requirements and interactions of over 120 farm programs to create producer payments. The systems are homegrown, in an outdated 

programming language, and on hardware that is no longer manufactured. In addition, the systems cannot be modified to meet current Federal IT security requirements. Over the years, core financial software vendors have improved their products 

to support broader operational flexibility and requirements. Included in the request 

for proposals (RFP) for FMMI are the requirements and business cases to address 

the basic requirements of a modern farm programs system. We believe that the new 

financial system will provide a strong foundation to a modern and upgradeable payment system to support the farm programs. 

These critical systems are in the early phases of failure and require a multi-year 

implementation cycle. It is very important that the funds for these systems are approved at their requested fiscal year 2008 budget levels. 

Financial Personnel 

Employee turnover in the Department for fiscal year 2005 equaled 8.36 percent. 

The majority of this turnover is related to retirements in the Department (4.6 percent). I believe that it is also safe to speculate that USDA turnover is impacted by 

promotions due to retirements in other government entities. We project that turnover due to retirements will increase by approximately 1 percent each year which 

equals approximately 8 percent (at least 12 percent with other elements of turnover) 

by fiscal year 2009. This high level of turnover places a significant amount of responsibility on our management teams, as they must transition knowledge based 

jobs. To address the transition and the shrinking workforce, the Office of the Chief 

Financial Officer is training the financial workforce, standardizing and documenting 

processes, and competing work skills that are available in the private sector. 

Employee Training.—Office of the Chief Financial Officer has started training employees in the skills of Lean Six Sigma, which is characterized as an improvement 
26 

methodology because it uses data to identify waste and non-value added activities; 

reduce them, while improving service delivery. Through the Lean Six Sigma process, 

employees’ document current business processes and then refine the process for a 

zero tolerance for errors; while using fewer resources and improving customer service. In addition, the Office of the Chief Financial Officer holds various training sessions every year in order to address the knowledge gap in financial and USDA 

knowledge due to the high turnover rate. 

Competitive Sourcing.—Competitive sourcing provides a resource to supplement 

skills and resources of the Department’s workforce. The Center for Naval Analysis 

conducted a study titled Long-run Costs and Performance Effects of Competitive 

Sourcing, and found that competition drove costs down over 30 percent while improving performance. The process is designed to select the competitor who can provide the most cost effective service delivery methodology to the Department and ultimately the taxpayers. Returns on investment are even greater for the activities 

that agencies have identified most frequently from competition: IT, maintenance/ 

property management, logistics, HR/personnel servicing and education, and financial management. Two-year savings per Full-Time Equivalent studied in these categories generally range from $25,000 to $33,000. As required skill sets and technology change, the Federal sector, by using an external firm, can be flexible in the 

knowledge skill sets of technology teams by adjusting the requirements of the vendor’s contract. Our veteran owned companies, small and disadvantaged businesses, 

as well as other private companies have been important to the past success of our 

government and will continue important technical skills in the future. 

Recruitment.—Last, we need to continue to recruit employees from our nation’s 

universities into the Federal workforce. These young employees bring excitement to 

the work environment and complementary technical skills to our knowledge based 

employees. Since the Federal requirements for accounting are slightly different than 

those taught in the universities, we will partner with the USDA Graduate School 

to provide the additional Federal knowledge. 

This comprehensive approach to address the high turnover in the financial workforce should provide the Department with the employees required for the management and safeguarding of the assets appropriated by the Congress. 

National Finance Center 

Before we move to the budget request, I would be remiss if I did not discuss the 

National Finance Center. The National Finance Center (NFC), located in New Orleans, provides payroll processing and related services for approximately 33 percent 

of the Federal civilian workforce in more than 175 government entities. In fiscal 

year 2006, the NFC processed $30 billion in payroll for approximately 595,000 Federal employees. The NFC provides a human resources suite of services to approximately 150,000 employees of which 72,000 are USDA employees in Farm Service 

Agency, Rural Development, Natural Resources Conservation Service, and Forest 

Service; and 69,400 Department of Homeland Security employees in Transportation 

Security Administration (TSA), Coast Guard and Headquarters. The NFC services 

the Office of Personnel Management performing health benefit reconciliations and 

health care premium processing on a Government-wide level. Finally, the NFC provides personnel transaction processing services for several agencies including TSA, 

Coast Guard and Federal Emergency Management Agency (FEMA). 

The National Finance Center continues to prove the efficiencies and effectiveness 

of a very focused shared services operation. The payroll, human capital, and data 

center operations continue to be a low cost provider with a very high level of customer satisfaction. During fiscal year 2006, the NFC operations returned to New Orleans after relocating due to Hurricane Katrina. At the time of the return, the New 

Orleans area was still in the early stages of rebuild. The NFC employees have endured long lines at the limited number of grocery facilities, the constraints of living 

in FEMA trailers, slow payments of insurance proceeds, inflation in the cost of property insurance, and other hurdles. In addition, employees have increased workload 

as the employee vacancy rate has increased due to separations and retirements. 

Even with all of these hurdles, the work from the three CFO operations at the NFC 

is exceptional. We are very proud of these employees and consider them pioneers 

in the rebuild of New Orleans. Last year’s significant results for the National Finance Center include: 

—Reduction of backlogs to pre-Katrina levels. 

—Implementation of the Department of Justice to the payroll system (30,000 employees). 

—First stage implementation of Forest Service to the Human Resource Line of 

Business suite of services. 
27 

—Selection of and significant progress on the Primary Computer Facility (PCF). 

As disclosed in our report to Congress, the Primary Computer Facility is located 

at the Denver Federal Center. The project is on target to complete the relocation of the systems from the temporary disaster recovery facilities to the PCF 

by June 2007. 

Budget of the Office of the Chief Financial Officer 

The OCFO is responsible for the financial management of an enterprise with almost $75 billion in annual spending, over 106,000 full time equivalents (staff years) 

and over $134 billion in assets. 

Areas of focus for fiscal year 2008 include supporting shared services that reduce 

the cost to USDA mission areas and the Federal Government; strengthening the financial operations of the program areas; completing uniform processes and procedures; creating efficient IT solutions; remediation of deficiencies in internal controls, 

and progressing in the implementation of the systems in critical need of replacement. 

Our fiscal year 2008 operating budget request is for $30.8 million, which includes 

increases for 2007 and 2008 pay costs as well as the replacement of the core financial system. Approximately 90 percent of the OCFO’s obligations are for the salaries 

and benefits of the OCFO employees. OCFO is a labor intensive staff office with 

very little ability to absorb pay cost increases without holding a large number of 

positions vacant for the entire fiscal year; thereby adversely affecting its ability to 

lead the Department in the areas of financial management, oversight, and guidance 

necessary to prevent fraud, waste, and abuse; reduce risk of improper payments, 

plan for financial systems, and to institute proper internal financial controls. The 

pay-related increases requested are necessary for us to accomplish key outcomes 

and to successfully meet our goals for fiscal year 2008. 

OCFO is requesting an increase in funding to partially fund the implementation 

of the system used to replace our core financial management systems and provide 

a foundation to the farm payments system. These systems are in critical need of replacement. As I stated above, this core system is replacing nine general ledger systems currently operating in USDA and provides the foundation system for the modernization of the farm payment system. Currently these systems do not meet the 

requirement of financial systems as required by the Federal Financial Management 

Improvement Act, are showing early signs of failure, and are no longer supported 

by the vendor. If the current systems fail, the Department will not be able to report 

required financial information, manage receipts, or produce payments. This system 

will also replace the four general ledger systems and five payment modules currently contained in the farm payment systems (all of which are no longer supported 

by the vendor). Continued reliance upon this old technology poses unacceptable risks 

to USDA financial operations and data. I greatly appreciate your support in the replacement of these key systems. 

USDA Working Capital Fund 

The CFO is responsible for the budget of the Department’s Working Capital Fund 

(WCF). The WCF serves as the Department’s principal investment engine to achieve 

progress in developing and implementing new corporate systems. 

Unobligated Funds.—Under the authority of Congress, USDA is allowed to transfer unobligated balances from discretionary accounts into the WCF. For fiscal year 

2005 the transfer was approximately $2 million and for fiscal year 2006 the transfer 

was approximately $4 million. During that same period we have received capital 

project requests for unobligated funds in excess of $30 million. While all of the requests appear to be very important, we have placed a priority to statutory obligations. The first obligation is for the capital required to meet the reporting requirements of the Transparency Act passed by Congress in this fiscal year. The next priority is to meet a small amount of the capital requirements of the PCF. As previously reported to Congress, the PCF will be operational by June of this year. The 

information concerning the transfer of unobligated funds and the capital requests 

for these funds will be reported to the Committees on Appropriations in the near 

future. 

Working Capital Funds—Capital.—For fiscal year 2007, request for the hardware 

to support corporate systems and facilities equaled $84.5 million. The Department’s 

available balance for allocation was $24.8 million. The Department graded the investments with statutory, security, and disaster recovery receiving the highest 

scores for funding. Statutory investments include NFC’s PFC, NFC’s backup facility, 

and Homeland Security Operation Plan system. We are grateful for the support and 

look forward to working with the Committee as we repair and improve our corporate 

systems. 
28 

Working Capital Funds—Operations.—In addition to the investments in corporate 

systems, the WCF supports the operations of our shared service activities. These 

services include financial management, information technology, payroll, human capital systems, communications, administration, as well as record keeping and item 

processing. It is our objective to use this financing mechanism to provide to the mission areas and the Federal Government the most effective cost-efficient services 

available. 

The President’s fiscal year 2007 budget estimates that total costs for recurring operations in the WCF in fiscal year 2008 will be $534.3 million, a 3.7 percent increase 

over the fiscal year 2007 estimate. The majority of this increase is to move the Department to a uniform human resource system hosted at the National Finance Center and an increase in the cost of services at the National Information Technology 

Center. Also included in the fund are such services as: video and teleconferencing 

production services provided by the Broadcast and Media Technology Center in the 

Office of Communications; personal property, mail, duplicating, and acquisition system provided by Department Administration. 

I would like to point out that the WCF financing mechanism, as a reimbursement 

for goods and services provided, gives us an opportunity to refine our estimates as 

newer and better information becomes available regarding customer demand and 

costs. Our office is working with activity centers to review fiscal year 2008 estimates 

with the goal of reducing the cost of individual services that are provided to USDA 

agencies. It was with this objective in mind that we were able to submit an operating estimate for fiscal year 2008 that is consistent with expected inflation. 

One thing we have done to impose more discipline on costs is to require individual 

activities to begin compiling and reporting costs for specific business lines within 

their respective activities. This method is being developed and refined as we move 

forward in fiscal year 2007 and will be a critical element as we revisit fiscal year 

2008 cost estimates. As we begin development of the fiscal year 2009 budget this 

spring, we will be reexamining fiscal year 2008 estimates for more economies and 

savings. As has been the practice for the last 2 fiscal years, we will establish spending targets for WCF activities that take into account the Department’s spending priorities among its agencies reflected in the President’s budget. 

Last year, we expressed to the Committee our appreciation for all of the assistance and support provided to the Department in the wake of Hurricane Katrina. It 

was a critical ingredient in our ability to resume normal business operations and 

recover from that event. We have continued to strengthen our business continuity 

practices, and we are working to ensure that in the event of the need to respond 

to a similar natural disaster in the future we are positioned even better to respond 

and ensure uninterrupted service to our customers. For your continued support in 

that effort, we are grateful. 

Thank you, Mr. Chairman, for the opportunity to share the results we have 

achieved and our fiscal year 2008 budget request with the Subcommittee. We have 

very dedicated employees that are passionate about nature and conservation, food 

assistance and the Nation’s health, rural America and renewable energy, food production and safety, and the vast benefits of scientific research. The budget for such 

a large Department is an effort based on the goals of our 5 year strategic plan, the 

highest priorities of each mission area, and replacing critical support infrastructure. 

We look forward to working together with you and the Subcommittee in fulfilling 

the vision for financial management and accountability we all have for USDA. 

PREPARED STATEMENT OF MARGO M. MCKAY, ASSISTANT SECRETARY FOR CIVIL

RIGHTS, OFFICE OF THE ASSISTANT SECRETARY FOR CIVIL RIGHTS

Mr. Chairman and members of the Subcommittee, thank you for the opportunity 

to submit this statement supporting the President’s fiscal year 2008 budget proposal 

for the United States Department of Agriculture’s (USDA) Office of the Assistant 

Secretary for Civil Rights (ASCR). 

The Office of the ASCR provides policy guidance, leadership, outreach, coordination, training, and complaint prevention and processing for USDA. Our mission is 

to provide equal opportunity, equal access and fair treatment for all USDA customers and employees. 

The Office of Civil Rights, under the ASCR, has made significant progress in complaint processing and complaint prevention. Overall USDA experienced a 15 percent 

decrease in the number of new Equal Employment Opportunity (EEO) complaints 

filed during fiscal year 2006 as compared to fiscal year 2005. The decrease in EEO 

complaint filing is attributed to factors such as increased usage of the Alternative 
29 

Disputes Resolution (ADR) process, improved compliance and accountability, and an 

overall decrease in the size of the workforce. 

We have also strengthened our compliance and outreach efforts. In August 2006, 

we convened our Third Annual Partners’ Meeting. This is a principal outreach effort 

for organizations representing underserved populations, including minority, small 

and limited resource farmers. These meetings continue dialogue with USDA stakeholders, providing a forum through which the voices and concerns of underserved 

constituents can be heard by USDA, and avenues can be found for resolving longstanding issues of access and accountability. 

FISCAL YEAR 2008 OBJECTIVES

The Office of Civil Rights (CR) has the following strategic objectives for fiscal year 

2008 that contributes to the Department’s success. They are to: 

—Ensure employees and applicants are provided equal opportunities in all aspects 

of employment activities. 

—Ensure USDA employment activities are conducted in a nondiscriminatory manner and agencies comply with CR/EEO laws, rules and regulations related to 

women, minorities, and persons with disabilities. 

—Ensure equal access to USDA programs. 

—Ensure Program and EEO complaints are timely processed. 

—Ensure complaints are processed in an efficient and cost-effective manner. 

—Increase USDA-wide awareness and use of Alternative Dispute Resolution 

(ADR), and resolution of conflicts through ADR in the early stages of workplace 

and program disputes (non-civil rights). 

—Establish effective outreach programs in the Department to ensure equal and 

timely access to USDA programs and services for all customers, with special 

emphasis on the minority and underserved. 

FISCAL YEAR 2008 KEY OUTCOMES

CR plans to achieve the following key outcomes in fiscal year 2008: 

—Decrease in the number of individual EEO and Program complaints filed. 

—Reduction in the average number of days to process Program and EEO complaints to issuance of Report of Investigation and Final Agency Decisions. 

—Increase in the efficiency and cost-effectiveness of processing of Program and 

EEO complaints within the regulatory timeframes. 

—Increase in ADR usage. 

—Increase the number of minority, underserved, and socially disadvantaged persons made aware of USDA programs and services. 

FISCAL YEAR 2008 BUDGET REQUEST

The fiscal year 2008 Appropriation request for CR is $23.1 million. The funding 

request includes increases for the following: 

—Civil Rights Enterprise System Improvements.—Funds for the Civil Rights Enterprise System are requested to continue the expansion of the complaints processing system. Funding is necessary to support the President’s Management 

Agenda initiative of expanding electronic government by improving complainant/customer access to information about the complaints and providing a more 

accountable mechanism for EEO and Program complaint filing. USDA agencies 

will be able to interface on a Web-based system that will provide customers and 

employees real-time data regarding their discrimination complaints. The system 

encompasses a planned multi-year phased approach projected through fiscal 

year 2009. After fiscal year 2009, the implementation of the system will be complete and funds will only be needed to support operation and maintenance. 

—Compliance Monitoring Activities.—Funding is needed to meet new requirements designed to meet the affirmative employment goals of the Equal Employment Opportunity Commission’s Management Directive 715. In addition, CR 

will undertake significant compliance activities in the field offices. Compliance 

reviews will result in civil rights complaint prevention and new complaint reductions. 

—Pay cost.—Funding is needed for the 2007 and 2008 pay raises. 

I would like to emphasize the importance of the Subcommittee’s approval of the 

President’s $23.1 million budget for CR. The proposed budget will help ensure that 

USDA continues to make substantial progress toward providing fair and equitable 

delivery of our services and programs to our customers and protecting the civil 

rights of USDA employees. 
30 

PREPARED STATEMENT OF TERRI TEUBER, DIRECTOR, OFFICE OF COMMUNICATIONS

Mr. Chairman and members of the Subcommittee, I am pleased to discuss the fiscal year 2008 budget request for the Department of Agriculture’s Office of Communications (OC). 

When Congress wrote the law establishing the U.S. Department of Agriculture in 

1862, it said the Department’s ‘‘. . . general designs and duties shall be to acquire 

and to diffuse among the people of the United States useful information on subjects 

connected with agriculture in the most general and comprehensive sense of the 

word.’’ OC coordinates the implementation of that original mandate. 

OC coordinates communications with the public about USDA’s programs, functions, and initiatives, providing vital information to the customers and constituency 

groups who depend on the Department’s services for their well-being. For example, 

OC is coordinating the Department’s communications efforts relating to the threat 

of avian influenza (AI) and is prepared, if necessary, to activate a Joint Information 

Center (JIC) funded through the Supplemental Appropriation, which would support 

the Department in meeting its obligations in the event of an AI detection and/or outbreak. This effort is a follow-on to efforts OC has undertaken in the past to inform 

the public of the Department’s actions taken to protect animal and human health. 

OC assisted in addressing such serious issues as bovine spongiform encephalopathy 

(BSE), which have been of interest to consumers around the world. In addition, OC 

also coordinates the communications activities of USDA’s seven major mission areas 

and provides leadership for communications within the Department to USDA employees. 

OC is adopting new technologies to meet the increased demands for the dissemination of accurate information in a timely manner. Using the Internet, radio, television and teleconference facilities, we are able to ensure that the millions of Americans whose lives are affected by USDA’s programs receive the latest and most complete information. As the continuing concern over AI and BSE incidents demonstrate, these technologies are a critical resource used by the Secretary and the 

agencies to provide timely information, which helps to maintain consumer confidence and stabilize agricultural markets. 

OC’s 5-year strategic goal is to provide maximum support to all mission areas of 

the Department in the development of programs and in creating awareness among 

the American public about USDA’s initiatives and services. This is essential to providing effective customer services and efficient program delivery. As a result, we expect more citizens, especially those in underserved communities and geographic 

areas, to access helpful USDA services and information. A central element of this 

support is OC’s active participation in the Department’s eGovernment initiative as 

part of the President’s Management Agenda. OC plays a key role in ensuring that 

the Department’s eGovernment implementation results in the public’s improved access to more current, accurate, relevant, and organized USDA products, services, 

and information. The USDA.gov portal, managed by OC, is customer- or citizen-centric, allowing OC to target information by audience preference, subject and personalization. On average, 1.5 million citizens access the site weekly. The demand by citizens and other constituencies for information, via USDA.gov, Web casting, electronic 

mail distribution, teleconferences, and publications, is expected to continue to increase. 

OC will continue to take an active role in policy and program management discussions by coordinating the public communication of USDA initiatives. We will continue to provide centralized operations for the production, review, and distribution 

of USDA information to its customers and the general public. Also, we will monitor 

and evaluate the results of these communications. Our staff is instructed to use the 

most effective and efficient communications technology, methods, and standards in 

carrying out communications plans. 

Also, we are focusing on improved communications with USDA employees, especially those away from headquarters, which will enhance their understanding of 

USDA’s general goals and policy priorities, programs and services, and cross-cutting 

initiatives. 

Our office will continue to work hard to meet our performance goals and objectives. We will work to communicate updated USDA regulations and guidelines, conduct regular training sessions for USDA communications staff about using communication technologies and processes to enhance public service, foster accountability 

for communications management performance throughout USDA, and continue to 

work to create a more efficient, effective and centralized OC. 

Increasing availability of USDA information and products to underserved communities and geographic areas through USDA’s outreach efforts is integral to our per-
31 

formance efforts. OC will continue to provide equal opportunity for employment and 

promote an atmosphere that values individuals. 

FISCAL YEAR 2008 BUDGET REQUEST

OC is requesting a budget of $9,720,000, which includes an increase to cover fiscal 

year 2007 and fiscal year 2008 pay costs. 

As more than 89 percent of OC’s obligations are for salaries and benefits, the requested increase is vital to support and maintain staffing levels for current and projected demands for our products and services. While OC has realized some cost savings by replacing high grade employees who have retired with lower grade employees, our current budget leaves little flexibility for absorbing increased costs. In fact, 

OC would not be able to absorb the increased salary costs in fiscal year 2008 without placing considerable constraints on daily operations or affecting staff size and 

therefore the timely delivery of information to the public. 

Our central task is to ensure the development of communications strategies, 

which are vital to the overall formation, awareness and acceptance of USDA programs and policies. OC has led the adoption of content management software which 

speeds the addition of new material, improves our quality control measures to ensure the accuracy of the information available through USDA.gov, and reduces the 

staff time required for overall maintenance of the site. 

This improved control greatly reduces the time necessary to post important information to the media and the public while providing a greater ability to ensure the 

accuracy of the information. This allows OC to use a large document and Web repository, sharing resources and information with mission areas and agencies as well 

as the public. 

OC looks forward to continuing our commitment to the American public by providing timely, accurate information about our programs and services. 

This concludes my statement, Mr. Chairman. I will be pleased to respond to any 

questions. 

PREPARED STATEMENT OF KEITH COLLINS, CHIEF ECONOMIST

Mr. Chairman and members of the Subcommittee, thank you for the opportunity 

to discuss the general economic situation in U.S. agriculture as background for the 

Subcommittee’s review of the Department of Agriculture’s (USDA) fiscal year 2008 

budget submission. I will review the major factors affecting agricultural markets in 

the coming year and their implications for financial conditions in U.S. agriculture. 

U.S. agriculture continues to prosper following the economic slowdown at the start 

of this decade. With solid growth in domestic and export demand, large crop harvests, and record-high cattle, broiler and milk prices, net cash farm income reached 

a record high $81.5 billion in 2004. In 2005, net cash farm income was nearly as 

high and the second highest on record despite a large increase in crop stocks which 

reduced crop prices; multiple hurricanes that shut down the central marketing infrastructure of the country; sharply higher energy prices that raised production, 

marketing and processing costs; continued loss of Asian beef markets; and the emergence of global Avian Influenza (AI) concerns. In 2006, net cash farm income is estimated at $66.7 billion, down from the previous 2 years, reflecting lower milk prices 

and government payments, smaller crop harvests, plus higher production expenses, 

especially energy costs. 

In 2007, global economic growth and food demand is expected to remain strong. 

However, growing demand for biofuels is expected to be the key factor driving crop 

prices. Markets for most major crops will experience stronger prices as stock levels 

decline. In addition, continued expansion of livestock production following several 

years of profitable returns could lead to slightly lower market prices for cattle and 

hogs. Weather, energy costs, higher interest rates, and a slow recovery of foreign 

markets due to animal health concerns are also likely to be factors affecting economic performance. Together, these factors suggest that net cash farm income will 

rise modestly in 2007. Rising expenses will cause financial stress for some farming 

operations, particularly livestock and poultry producers, but the overall farm economy is expected to perform above long-term average levels with net cash farm income forecast at $67.2 billion, farm household income remaining strong, and farm 

net worth continuing to increase. 

Global Economic Growth and Farm Product Demand 

The U.S. economy grew at 3.4 percent in 2006, up from 2005’s 3.2 percent but 

below 2004’s 3.9 percent. For 2007, U.S. Gross Domestic Product (GDP) growth is 

expected to be slightly less than last year. The decline in the rate of growth in 2007 
32 

from last year is expected to be due to slower growth in consumption, weak housing, 

and tight energy markets. Increased tightness in labor markets is likely also to be 

a factor. As the unemployment rate remains low, productivity growth and output 

growth usually remain at or just below trend. 

Real foreign economic growth accelerated in 2006 to 4.0 percent from 2005’s 

strong growth rate of 3.7 percent, with many areas improving, particularly Western 

Europe and Asia. This year, Western Europe is expected to grow at above 2 percent 

for the second consecutive year, the first time this has happened since 1999–2000. 

Growth in Japan, Canada, and Mexico are expected to be slightly below 2006. Asia, 

excluding Japan, will likely grow at 7 percent in 2007, above trend for the 4th consecutive year. Foreign economic growth is expected to be 3.7 percent in 2007, down 

slightly from 2006, but well above trend, as has been the case beginning in 2004. 

With the U.S. economy expected to have another year of steady growth, consumption expenditures on food continue to rise, although the rate of growth is likely to 

decline to near 4.4 percent from the unusually high 6 percent growth in 2006. 

Growth was less than 2.5 percent during the economic slowdown in 2001 and 2002. 

This year, slower growth in consumer spending on food is likely, as consumers face 

heavy debt loads and high energy costs and are less likely to use household assets 

to finance consumption. Consumer spending, which accounts for two-thirds of GDP, 

increased by 4.4 percent in the last quarter of 2006, well above the third-quarter, 

but a slowdown is expected in the first quarter of 2007. 

U.S. Agricultural Trade 

Turning to foreign demand for U.S. agricultural products, our latest quarterly 

forecast for farm exports in fiscal year 2007, released in March, is a record-high $78 

billion, up $9.3 billion from fiscal year 2006’s record. Gains are expected across the 

board in grains and feeds, livestock, and horticultural products. 

U.S. agricultural imports are forecast at a record $70 billion, $6 billion more than 

in fiscal year 2006. The agricultural trade surplus for fiscal year 2007 is forecast 

at $8 billion, up from $4.7 billion in fiscal year 2006. 

While the agricultural export-weighted value of the dollar appreciated in the first 

half of 2006, it has depreciated steadily since July, continuing its declining longterm trend from 2001. The current period of strong foreign economic growth and 

continued effects of the decline in the value of the dollar from several years ago 

should result in higher U.S. agricultural exports in the future and a modestly improving trade balance. However, strong consumption growth in the United States 

and consumers’ desire for year-round fruits and vegetables, as well as more variety, 

suggest the trade surplus in the future will be smaller than in the past. USDA’s 

long-run projections issued February 14, 2007, forecast U.S. agricultural exports rising to nearly $94.8 billion by fiscal year 2016 and imports rising at an even faster 

pace to $92.7 billion, leaving a trade surplus of $2.1 billion. 

Major Crops: Supply, Demand, and Price 

The 2005/06 marketing year began with relatively ample world crop supplies. 

Thus, despite declines in production of grains and cotton, stocks remained relatively 

stable year-to-year. Global oilseed production was record high in 2005/06, boosting 

stocks to record levels. As a result of these generally plentiful supplies, market 

prices were relatively flat. In 2006/2007, global wheat and coarse grain production 

declined as weather problems affected output. World oilseed production set another 

record and world cotton production rose slightly. Global total use this year is expected to rise for rice, coarse grains, oilseeds, and cotton. Global wheat use is expected to decline modestly, reflecting tighter supplies and higher prices. With generally lower production and rising consumption, global stocks of most major commodities, except oilseeds, will decline in 2006/2007, and grain (wheat and coarse 

grain) stocks will fall well below last year’s levels. In the United States, supplies 

for feed grains, cotton, and rice are well below their record levels in 2005/2006. U.S. 

wheat supplies are down sharply from 2005/2006, but soybean supplies set another 

record. 

With world grain consumption during 2006/2007 expected to exceed last year’s 

record high and again exceed world production, world grain stocks as a percent of 

total use are expected to fall to 15.5 percent, compared with 19.5 percent in 2005/ 

2006. The picture for oilseeds is quite different as global soybean production is forecast to be record high for the third consecutive year, exceed consumption, and result 

in higher global stocks. For soybeans, global stocks as a percent of use is forecast 

to exceed the high set in 1986. World cotton stocks are expected to decline slightly 

as consumption exceeds production for the second consecutive season. 

For the United States, good grain and oilseed harvests and strong demand have 

supported above average farm income in recent years. Current market prospects 
33 

look even brighter as growth in demand, particularly for producing biofuels, has 

pushed grain prices to 10-year highs. High grain prices and demand for vegetable 

oil have also pushed soybean prices higher, despite the higher soybean supplies. 

U.S. soybean stocks are expected to be record high at the end of 2006/2007, rising 

132 percent above the level of 2 years ago. This jump reflects the bumper harvest 

this past fall and the highest beginning stocks in 20 years. This stock buildup is 

projected despite expected record soybean crush and exports. Still, U.S. soybean 

prices this winter have been strong in the face of the prospective stock buildup, reflecting higher corn prices, purchases by index funds, and strong, biodiesel-driven 

soybean oil prices. For the year as a whole, the farm price received for soybeans 

is expected to average $6.30 per bushel compared with $5.66 last marketing year. 

Despite prospects for record production in the Southern Hemisphere and the increase in U.S. stocks, soybean prices will likely remain strong in the second half of 

the year, reflecting relatively high corn prices. 

For 2007/2008, high corn prices relative to soybeans likely will cause a sharp 

swing away from soybean planting. We expect a reduction in soybean planted area 

of about 5 million acres. Lower planted area, combined with trend yields, would result in production below expected use; consequently, carryover levels would decline 

significantly. Reduced production, lower stocks, and high corn prices should keep 

soybean prices strong into 2007/2008. 

The U.S. corn market in 2006/2007 is expected to see a second year of declining 

carryover as ending stocks fall markedly from 2005/2006. Corn prices have risen 

sharply since September 2006 when the market began to reflect the extraordinary 

ongoing expansion in corn-based ethanol production capacity. Additional factors supporting the rapid rise in corn prices have been the decline in 2006-crop corn acreage 

and yield and strong export demand. Farm-level corn prices are expected to average 

$3.20 per bushel this marketing year, up substantially from $2.00 per bushel last 

year. The increase in prices nearly eliminated loan deficiency payments (LDPs) and 

marketing loan gains (MLGs) for 2006-crop corn. As of March 2007, LDPs and 

MLGs totaled only $3 million on 2006-crop corn with all of these payments occurring in the first weeks of the marketing year. For the 2005 crop, LDPs and MLGs 

totaled $4.6 billion, with 97 percent of that year’s production receiving an average 

payment of $0.42 per bushel. 

Biofuels is now the most important influence on corn and other crop markets. 

Ethanol production this marketing year is expected to account for 20 percent of U.S. 

corn production. The USDA’s long-term projections to 2016, released on February 

14, 2007, project ethanol production will account for 30 percent of corn use by 2009/ 

2010 and drive corn prices to $3.75 per bushel. Biodiesel production has increased 

from less than a half million gallons in 1999 to over 225 million in 2006, equivalent 

to 8 percent of soybean oil production. 

In 2004, ethanol accounted for about 2 percent of motor gasoline use in the United 

States on a volume basis. Under the Department of Energy’s Annual Energy Outlook 2007, ethanol use is expected to grow to over 7 percent of motor gasoline use 

by 2010. The USDA projections to 2016 put corn-based ethanol production at 11 billion gallons by 2010/2011. This would be a 3-fold increase in corn ethanol production 

since 2004/2005. 

As a result of higher prices and returns for corn fueled by the expansion in ethanol use, corn area is expected to expand by about 9 million acres in 2007. Much 

of this increase will come from soybeans. Additionally, area for cotton, hay, and 

other crops are all expected to decline to meet the demand for more corn production. 

Even with higher acreage and production, corn ending stocks are likely to tighten 

again in 2007/2008 and remain at relatively tight levels in the coming years as ethanol demand continues to be strong. 

The 2006/2007 wheat market reflects tighter world supplies, but continued strong 

demand. U.S. wheat stocks at the end of this marketing year are projected to decline from their levels in 2005/2006 as a result of weather problems that reduced 

yields in 2006. Farm prices are forecast to average $4.25 per bushel, up from $3.42 

in 2005/2006 and $3.40 in 2004/2005. Prices in 2006/2007 have been boosted by 

weather problems in the United States and in Australia that reduced this year’s 

production. Wheat prices have also benefited from rising corn prices. 

For 2007/2008, wheat acreage, which has been trending downward over the past 

25 years, is expected to increase by nearly 3 million acres due to higher prices last 

fall that encouraged more seeding of winter wheat. Heavy fall rains limited seeding 

in the eastern Corn Belt, but the area is up for all classes of winter wheat. Yield 

prospects for the 2007 crop remain favorable at this time as winter storms have 

brought much needed precipitation to the Central and Southern Plains. Global 

wheat production prospects are also good with most major wheat producing countries expected to expand acreage in 2007 because of strong prices. Weather in most 
34 

of the major-producing countries has remained favorable for winter seeded crops. 

This suggests global wheat production will rise in 2007/2008. Based on trend yields, 

U.S. wheat production is expected to rebound in 2007, hitting its highest level since 

2003. Despite higher expected demand, especially for feeding, ending stocks are expected to increase. Prices, however, are expected to be higher than in 2006/2007 as 

higher corn prices put a floor under wheat feeding value. 

U.S. cotton production fell 9 percent in 2006/2007 from the previous year’s record, 

however, carryover stocks are still expected to rise for the third consecutive year 

and reach nearly 9 million bales. The increase is the result of declining domestic 

textile mill use and cotton exports. U.S. cotton mill use continues to trend down as 

textile mill activity continues to move offshore. Mill use this year is forecast at 5 

million bales, compared with 5.9 million last season. Exports are forecast to decline 

by over 20 percent from last year’s record to 14.0 million bales. Lower exports are 

due mainly to reduced import demand by China, the largest U.S. customer. Farm 

prices of cotton have been running about the same as year-ago levels. For 2007/ 

2008, lower acreage and production are expected to support prices. With the prospect of stronger exports due to rising world demand, ending stocks will likely decline. 

Tighter domestic rice supplies and higher global prices have helped to boost U.S. 

farm prices in 2006/2007. The global rice market is a major factor contributing to 

strong U.S. farm prices as global ending stocks are expected to be the lowest since 

1983/1984 and the lowest stocks-to-use ratio since 1981/1982. The season-averagefarm price is forecast at $9.85 per cwt, over $2 per cwt above the year earlier average price and the highest since 1996/1997. Rice ending stocks are forecast at 31 million cwt, down from carry-in stocks of 43 million cwt. Medium and short grain 

stocks, at about 8 million cwt, are the tightest since 1998/1999. 

A reduction in area in 2006 led to a decline in production. Higher fuel and fertilizer prices, difficulty acquiring bank loans, and weather-related problems in some 

areas—especially Louisiana and parts of Arkansas—accounted for much of the area 

decline in the South. A second consecutive cold, wet spring prevented California 

growers from boosting rice acreage, despite high prices and expectations of tight 

global supplies of medium-grain rice. 

On the demand side, impact in some markets from the discovery of trace elements 

of a genetically engineered strain of rice—Liberty Link Rice 601 (LL601)—in U.S. 

long-grain supplies and reduced production are behind expectations of weaker U.S. 

exports in 2006/2007—forecast at 102 million cwt, down 12 percent from the year 

earlier. Despite an expected drop in exports to Europe due to the European Union’s 

rejection of U.S. rice due to LL601, U.S. exports to markets in the Western Hemisphere, Northeast Asia, and the Middle East are expected to be strong. 

For 2007/2008, U.S. farm prices of rice are expected to strengthen on continued 

tight domestic supplies and firm global prices. Planted area is expected to be about 

the same as 2006 with a rebound in California, but a reduction in area in the South. 

Higher net returns for competing crops—mostly corn, restrictions on the planting 

of Clearfield CL131 seed and low government payments could lead to reduced rice 

planted area in the South. Total use and ending stocks are expected to be about 

the same as 2006/2007. 

Farm program costs for the 2006 program crops are sharply lower due to higher 

grains and oilseeds prices. Counter-cyclical payments are projected at $1.5 billion, 

down from $4.7 billion from the 2005 crops. Outlays for 2006-crop marketing loan 

benefits are projected at $900 million, down substantially from $6.3 billion for the 

2005 crops. Program crop producers also receive more than $5.2 billion annually in 

direct payments. 

The 2006/2007 sugar market has differed from other crops this year as prices 

have declined, returning from the extreme highs attained when hurricanes drastically reduced supplies in 2005/2006. To meet this year’s demand and help relieve 

market tightness, USDA increased import quotas above the minimums established 

under the World Trade Organization. However, 2006/2007 sugar imports, forecast 

at 2 million tons, would be down from 3.4 million tons last year. 

Farm sales of fruits, nuts, vegetables, and nursery and greenhouse products are 

expected to remain steady at $53 billion in 2007, accounting for 40 percent of all 

crop cash receipts. Fiscal year 2007 U.S. horticultural exports are forecast at $18.4 

billion and imports at $31.2 billion, indicating a continuing widening of the sector’s 

traditional trade deficit. 

Livestock & Livestock Products: Production, Demand, and Price 

Turning to livestock and poultry markets, U.S. red meat and poultry exports are 

expected to reach a record high in 2007. Pork exports are forecast to lead the way, 

increasing for the 17 consecutive year and exceeding 3.1 billion pounds carcass 
35 

weight or 14.6 percent of production. After depressed sales in early 2006, poultry 

sales increased as foreign concerns about AI abated and United States broiler meat 

prices declined. Broiler exports likely will increase to 5.4 billion pounds in 2007, but 

fall short of the record 5.6 billion pounds exported in 2001. Beef exports are expected to increase with the gradual expansion of exports to Japan and Korea. However, Korea’s import restrictions and Japan’s age limits on imported beef from the 

United States continue to limit growth. Although total beef exports are expected to 

increase 17 percent to 1.3 billion pounds in 2007, the level of exports will remain 

below the 2003 pre-bovine spongiform encephalopathy level of 2.5 billion pounds. 

Total U.S. production of meat and poultry is expected to be record-high in calendar year 2007, but nearly flat growth in supplies of broiler meat are expected to 

support higher broiler prices and help maintain cattle and hog prices near last 

year’s levels. For livestock and poultry producers, feed prices will be an important 

component of producer production decisions in the upcoming year. 

Beef production is currently forecast to increase 1.6 percent in 2006 as both 

slaughter numbers increase. Slaughter weights could decline in 2006 due to higher 

feed prices. Steer prices will likely remain near last year’s $85.41 per cwt and average $84–$89 per cwt. Poor forage conditions resulted in higher cow slaughter during 

2006 as many producers lacked sufficient forage resources to support their herds. 

Herd expansion is expected to be slow as the January Cattle report indicated a 

small calf crop and producers expected to retain 0.5 percent fewer heifers for addition to the beef breeding herd. 

Pork production in 2007 will expand about 2.6 percent, marking the 7 year of expansion as producers continue to respond to favorable returns over the last several 

years. Given farrowing intentions reported in the most recent Hogs and Pigs report, 

inventories will continue to expand, albeit at slower rates. The increase in 2007 production primarily will reflect increased slaughter as weight gains will be limited as 

producers respond to higher feed prices. Hog prices are expected to reflect the increased production, declining from 2006’s $47.26 per cwt to average $45–47 per cwt. 

Broiler producers have endured several periods of low returns due to relatively 

low broiler prices in 2005 and 2006 and higher feed costs. Consequently, producers 

reduced chicks placed in 2006, resulting in the lowest rate of production growth 

since the early 1980s. Production growth in 2007 is expected to be even slower. With 

tighter broiler meat supplies, prices are expected to average 72–77 cents per pound 

in 2007, up 16 percent from 2006. 

Milk producers are expected to respond to higher feed prices and lower 2006 milk 

prices by modestly reducing cow inventories and as a result, the rate of growth of 

milk production in 2007 will be slower than in 2006. Production in 2006 increased 

almost 3 percent and the all-milk price declined to $12.90 per cwt from $15.15 per 

cwt in 2005. Output per cow in 2006 was affected by abnormally high temperatures 

in much of the country during the summer, but growth is expected to follow a more 

normal pattern in 2007. Demand for dairy products, both domestically and for export, is expected to remain relatively firm in 2007. Commercial exports of nonfat dry 

milk and whey are likely to remain strong, reflecting limited supplies from competing exporters. Domestic demand for cheese and butter is also likely to remain 

firm, thus, prices of cheese, butter, nonfat dry milk, and whey are all forecast higher 

in 2007 and will support the all-milk price at $15.05–$15.65 per cwt. With product 

prices above support, no Commodity Credit Corporation net removals are forecast. 

Implications for the Financial Situation of U.S. Agriculture 

Net cash farm income declined to $66.7 billion in 2006 from the record and near 

record levels of 2004 and 2005 but is expected to be slightly higher at $67.2 billion 

in 2007. This year strong crop prices and a modest increase in livestock receipts are 

expected to lead to a $16 billion rise in cash receipts to a record-high $258.7 billion. 

This large increase in cash receipts is not translating into a large increase in net 

cash farm income because much of the increase in market receipts is expected to 

be offset by higher cash expenses and declining government payments. 

In 2005, government payments to producers were a record high $24.3 billion, declined to $16.3 billion in 2006, and are expected to fall to $12.4 billion in 2007. In 

2005, increased marketing loan costs, higher counter-cyclical payments, ad hoc disaster assistance, and tobacco program buyout payments, all contributed to higher 

government payments. Lower ad hoc disaster payments, marketing assistance loan 

outlays, and counter-cyclical payments will combine to reduce direct government 

payments in 2007, as they did in 2006. 

Cash production expenses are expected to rise 6 percent, or $12.2 billion, in 2007 

following increases of 5 percent in 2006 and 7 percent in 2005. Energy-related inputs (fertilizer, lime, fuels, oils, and electricity) increased by $1.9 billion in 2006 and 

are expected to rise by nearly $1 billion in 2007. Fuels and oils expenses are ex-
36 

pected to moderate in 2007 as the Department of Energy projects that diesel prices 

in 2007 will fall by 1.8 percent from 2006. 

Farm household income is also expected to recover in 2007, after its first decline 

in 7 years in 2006. At over $80,700 in 2006, farm household income would still be 

20 percent higher than in 2003 and well above the average of all U.S. households. 

Farm real estate values are expected to rise again in 2007, following a 7.5 percent 

gain in 2006. Another land value increase would continue the recent strong improvement in the farm sector balance sheet. The ratio of real estate value to net 

cash farm income, a concept similar to a price-to-earnings ratio, is forecast to remain high in 2007, near the highest level since the early 1980s. Between 2003 and 

2006, farm net worth went up by $510 billion or about $170 billion per year, which 

is far more than the annual increase in farm income and farm debt. In 2007, increases in farm real estate values are expected to slow to 4.7 percent and farm net 

worth is expected to increase by $66 billion. Farm net worth is expected to reach 

another record high at $1.76 trillion by the end of 2007, and the debt-to-equity ratio 

is forecast to remain at 13.4 percent, which would be the lowest on record. 

A return to slightly above average national farm income, for the second consecutive year, is likely to keep U.S. agriculture on a sustainable foundation. Most production sectors in U.S. agriculture are expected to see net cash income the same 

or higher in 2007, with hogs being the main exception. Farm prosperity in the coming year will be influenced by the durability of the United States foreign economic 

growth, oil prices, the value of the dollar, the ongoing biofuels production expansion 

and its impacts for feed costs, and trade-related animal health issues. The outcome 

of trade and farm bill negotiations will also be crucial determinants of the future 

direction of U.S. agriculture. 

FISCAL YEAR 2008 BUDGET REQUEST

The Office of the Chief Economist (OCE) advises the Secretary of Agriculture on 

the economic implications of USDA policies, programs and proposed legislation. 

OCE serves as the focal point for the Nation’s agricultural economic intelligence and 

projections, risk analysis, global change issues, and cost-benefit analysis related to 

domestic and international food and agriculture, provides policy direction for the Department’s bioenergy and biobased product programs, and is responsible for coordination, review and clearance of all commodity and aggregate agricultural and foodrelated data used to develop outlook and situation material within the Department. 

The OCE budget request for fiscal year 2008 is $11,347,000, which includes an 

increase of $360,000 for 2007 and 2008 pay costs. The budget request also includes 

an increase of $500,000 for the Methane-to-Markets Initiative. The Methane-to-Markets Partnership is designed to promote cost-effective, near-term methane recovery 

internationally through partnerships with fourteen other countries, including Russia, China, the United Kingdom, Italy, Mexico, and Brazil. Under this initiative, 

USDA will promote the international adoption of technologies to reduce methane 

emissions from animal waste systems and demonstrate United States leadership in 

reducing methane emissions. 

USDA support for the Methane-to-Markets Partnership will be used to: identify 

and promote areas of bilateral, multilateral, and private sector collaboration on 

methane recovery and use; develop emissions estimates and identify the largest relevant emission sources to facilitate project development; identify cost-effective opportunities to recover methane emissions and potential financing mechanisms to encourage investment; improve the legal, regulatory, financial, institutional and other 

conditions necessary to attract investment in methane recovery and utilization 

projects; identify and implement collaborative projects aimed at addressing specific 

challenges to methane recovery, such as raising awareness in key stakeholders, removing barriers to project development and implementation, identifying project opportunities, and demonstrating technologies; and develop and implement a process 

for evaluating progress and reporting results. 

That completes my comments and thank you. 
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PREPARED STATEMENT OF PHYLLIS K. FONG, INSPECTOR GENERAL, OFFICE OF THE

INSPECTOR GENERAL

Thank you for the opportunity to submit testimony to the Subcommittee about the 

Office of Inspector General’s (OIG) recent and ongoing audit and investigative work, 

and our fiscal year 2008 Budget Request. 

My testimony presents the highlights of our audit and investigative work for the 

period of March 2006-March 2007. OIG conducted extensive work in 2006 on important issues and USDA activities regarding food safety, the risks posed by plant and 

animal-based diseases, fraud that impairs vital nutrition and hurricane-relief programs, and financial management accountability within USDA agencies. 

To ensure that OIG devotes its resources to the most pressing issues and challenges facing USDA agencies, stakeholders, and consumers, we have formally 

prioritized our work and organized our resources according to three Strategic Goals. 

They are improving Safety, Security, and Public Health in USDA operations; enhancing Program Integrity in the many USDA benefit programs that touch the lives 

of your constituents; and oversight work regarding USDA’s Management of Public 

Resources. This statement presents the key elements of our recent and current work 

to the Subcommittee under the framework of these three strategic priorities. 

SAFETY, SECURITY, AND PUBLIC HEALTH

One of OIG’s top priorities is conducting independent and professional audits and 

investigations to protect the safety and security of USDA entities and the many agricultural stakeholders and consumers who benefit from USDA operations each day. 

In fiscal year 2006, we issued 12 audit reports involving safety, security, and public 

health issues related to USDA programs and operations. During the fiscal year, OIG 

referred a total of 120 cases for prosecution. 

Assessing the Performance of Consumer Safety Inspectors in Meat and Poultry Establishments 

In our prior audits we determined that the Food Safety and Inspection Service’s 

(FSIS) management control system needed strengthening to ensure accountability 

of consumer safety inspector performance. A key component of the FSIS management control system is the In-Plant Performance System (IPPS), which was estab-
46 

1Such as hazard analysis and critical control point system procedures. 

2 As established by the Federal Meat Inspection Act and the Poultry Products Inspection Act. 

lished to strengthen supervision and improve inspector accountability. In response 

to several OIG audits, FSIS has cited IPPS reviews as a critical measure to improve 

monitoring of food safety at meat and poultry establishments. 

In our most recent audit of this area, issued in 2006, we evaluated the adequacy 

of agency policy and procedures related to preparing for, executing, and monitoring 

IPPS reviews. FSIS did not require supervisors to complete and/or document the 

completion of all IPPS review procedures when evaluating inspectors. In 84 percent 

of the inspector assessments OIG reviewed, certain elements of inspector duties— 

some of which could be considered critical 1—were not addressed. We found that 

FSIS did not have a system to schedule and track the completion of IPPS reviews 

and supervisors were not required to use the extensive guidance available to help 

them prepare for the reviews. As a result, supervisors had not used significant segments of the guidance to enhance their onsite review of consumer safety inspectors. 

FSIS agreed to closely monitor field managers and supervisors involved in the 

IPPS process, analyze IPPS review data, and periodically evaluate the IPPS review 

process. FSIS also agreed to revise its guidance to require supervisors to examine 

specific data sources and system reports before performing an IPPS review and complete and provide narratives for all IPPS review elements during an inspector’s performance rating period. 

Improving Pathogen Reduction Testing in Meat and Poultry Establishments 

The Pathogen Reduction Enforcement Program (PREP) is a system used to support FSIS’ pathogen reduction efforts by scheduling microbiological product sampling at FSIS-inspected meat and poultry establishments and generating automated 

reports that allow FSIS managers to monitor both the sampling process and the results of laboratory tests. 

OIG evaluated the effectiveness of FSIS’ process for scheduling and conducting 

microbiological testing of meat and poultry products. We found that in the testing 

programs for the adulterants E. coli 0157:H7 and Listeria monocytogenes, FSIS had 

developed procedures to transfer establishment data from the Performance Based 

Inspection System (PBIS) to the PREP (two separate systems) and was selecting the 

identified meat and poultry establishments for testing within reasonable timeframes. 

However, we found that Salmonella testing program controls needed strengthening to ensure that all applicable establishments are included in the universe for 

microbiological testing. A significant number of establishments were excluded from 

Salmonell a testing due to ineffective processes for identifying establishments eligible for testing. FSIS district office personnel did not fully understand the process 

for inserting/updating establishments into the testing database. In one district we 

visited, 28 percent of the establishments subject to Salmonella testing were excluded from testing. We also found that establishments whose slaughter or processing activity falls below a specific threshold or produces non-intact beef products 

(such as raw ground beef sausages and meatballs) were also excluded from the universe for testing. 

We recommended that FSIS strengthen its procedures to ensure that all establishments subject to Salmonella testing are identified and modify PBIS to allow PREP 

to draw establishment information for testing from PBIS rather than depend on 

manual updates. The agency should develop a risk assessment to support its policy 

for excluding low-volume establishments from Salmonella testing or conduct testing 

in all plants. Further, FSIS should obtain scientific advice to evaluate whether its 

policy of not testing certain raw ground beef products for E. coli O157:H7 contamination should be continued. FSIS officials generally agreed with OIG’s findings and 

recommendations. 

Assessing FSIS Oversight of State Meat and Poultry Inspection Programs 

FSIS has oversight responsibility for State meat and poultry inspection (MPI) programs to ensure that meat and poultry products sold intrastate meet inspection 

standards ‘‘at least equal to’’ 2 Federal laws and regulations. OIG initiated a review 

to examine the effectiveness of FSIS management controls and procedures to ensure 

that State MPI programs were ‘‘at least equal to’’ Federal inspection programs. 

We determined that FSIS was not providing timely oversight of State MPI programs. From October 2003 through June 2005, FSIS had conducted only 8 initial 

onsite reviews from a total of 28 State MPI programs. After our fieldwork began 

and since July 2005, FSIS initiated reviews of 16 more State MPI programs and 

developed plans to conduct the 4 remaining reviews prior to the end of fiscal year 
47 

3FSIS issued a report in January 2007 that contained the results of all 28 reviews. 

4The plan is intended to complement regional, State, and industry plans that are written to 

be more specific to local issues and needs. States should continue to develop plans that are specific to their poultry industries and requirements. The USDA/APHIS plan will evolve as additional information and experience is gained. 

2006. Completing the review process is important, especially since four of the eight 

programs initially reviewed needed corrective actions to achieve ‘‘at least equal to’’ 

Federal standards.3

Moreover, FSIS had not performed timely onsite fiscal reviews and reviews of new 

programs and did not timely implement its year-end grant closeout procedures to 

ensure that State MPI programs promptly returned any excess Federal funds. FSIS 

had not recovered $260,201 in excess Federal funds from one State for fiscal year 

2004. In this State, during fiscal year 1997–2004, unnecessary interest costs of approximately $100,000 were incurred by the Federal Government because the State 

retained unused Federal funds. 

OIG made numerous program improvement recommendations based upon this 

audit. We recommended that FSIS establish criteria to determine how deficiencies 

in meat processing establishments affect State acceptability determinations. FSIS 

should analyze the staffing requirements of State MPI programs and confirm that 

laboratories adhere to standards ‘‘at least equal to’’ Federal requirements. The agency needs to eliminate the backlog of onsite fiscal reviews and perform timely, yearend grant closeouts of State MPI programs and seek prompt recovery of $260,201 

from the identified State MPI program. FSIS responded positively to OIG’s recommendations, and management decision was reached on 6 of the 12 recommendations. 

The USDA Response to Avian Influenza 

The emergence of highly pathogenic Avian Influenza (HPAI) as a potential pandemic has rapidly changed the environment in which the Animal and Plant Health 

Inspection Service (APHIS) operates. The November 1, 2005, issuance of the President’s strategy for the preparation, detection, and response to a pandemic accelerated APHIS’ actions in dealing with AI. The strategy recognizes roles for all segments of society, including Federal, State, local and Tribal governments, private industry, international trade partners, and individual citizens. 

In our June 2006 review of APHIS’ oversight of Avian Influenza (AI), we concluded that APHIS has made commendable progress in developing plans and establishing the networks necessary to prepare for, and respond to, outbreaks of AI. However, APHIS had not yet developed a comprehensive approach for surveillance and 

monitoring of AI in domestic poultry. APHIS relies on a variety of voluntary State 

and commercial programs to monitor and test domestic poultry and wild birds. Because these programs are voluntary, APHIS did not know the extent of surveillance 

activity in place and was not gathering consistent data to properly detect changes 

in epidemiological parameters (e.g., subtype of AI or rate of prevalence) or to report 

incidents of AI in accordance with new international trade requirements. 

In regard to USDA’s National AI Preparedness and Response Plan, OIG found 

that APHIS needed to provide additional guidance on preparing and responding to 

HPAI or notifiable AI outbreaks in live bird markets or other ‘‘off farm’’ environments.4 APHIS also needed to clarify actions that employees should take in obtaining and administering necessary vaccines and anti-virals in the event that a culling 

operation for HPAI occurs. Finally, APHIS needed to finalize interagency coordination on the process and procedures for notifying owners of susceptible animals of 

the current infectivity risks and the necessary protective actions they should take 

when an outbreak of AI occurs. In its response, APHIS described a number of initiatives planned and in process to address our concerns. 

OIG currently has a related audit underway. We are evaluating the effectiveness 

of APHIS’ implementation of the Homeland Security Council’s National Strategy for 

Pandemic Influenza (issued May 2006). We will also follow up with the agency on 

its corrective actions responding to our prior audit. 

Targeting the Smuggling of Animals and Plant Products 

The smuggling of animals and animal/plant products into the United States is of 

significant concern. The smuggling of these products presents both a human health 

risk and a risk to the United States’ animal and plant populations because of the 

potential for the transmission of disease. 

OIG works closely with USDA regulatory agencies such as APHIS and FSIS that 

enforce standards for the importation for meat, poultry, and live animals into the 

United States. As stated in our testimony before the Subcommittee last year, OIG 
48 

5 Public Law 107–203, enacted July 24, 2002, established the statutory requirement for a 

USDA–OIG investigation of FS fatalities occurring due to wildland fires. 6 The emergency declaration authorized the transfer of $44.1 million from emergency contingency funds to APHIS to expand the TB eradication program. 

works with USDA agencies to achieve a balance among risk mitigation efforts, regulatory investigations, and criminal investigations when such products are smuggled 

into the United States. To achieve this goal, we have been working to establish protocols to clarify each USDA agency’s role in response to smuggling. We anticipate 

the Department will issue these protocols this summer. 

One of the groups in which OIG is participating is an interagency working group 

comprised of both regulatory and law enforcement agencies from the Department of 

Homeland Security (DHS), the Department of Justice, and the Department of Interior. While the initial objective of this working group was to improve smuggling investigations concerning HPAI, OIG’s participation has also improved our investigative capabilities to respond to smuggling investigations involving any type of prohibited product. The inter-agency working group fostered productive relationships and 

communications between OIG and those departments and more clearly defined our 

respective roles. 

OIG participated in a joint investigation at the Port of Newark known as ‘‘Operation Fowl Play.’’ The investigation led to the seizure of approximately 1 million 

pounds of prohibited poultry, fowl, meat, pork, vegetables, fruit, and other merchandise over several months. The investigation, which began in 2005, involved several 

New York based companies responsible for importing these products from China. 

Preparing for Agricultural Emergency Situations and Wildland Fire Fatalities 

OIG’s Emergency Response Team (ERT) and Wildland Fire Investigation Team 

(WFIT) engaged in training and were both actively deployed in fiscal year 2006. The 

ERT has the capability to safely and effectively respond to criminal acts that could 

threaten or compromise the United States’ food supply, agricultural infrastructure, 

or USDA facilities. The WFIT is responsible for conducting an independent investigation into the deaths of any Forest Service (FS) firefighters who are killed as a 

result of a burnover or entrapment. We thank the Members of the Subcommittee 

for your continued support of these important programs. 

During 2006, ERT members participated in several tabletop exercises concerning 

AI and Foot and Mouth Disease, attended Food Defense Exercises, and State and 

local emergency preparedness meetings. Our ERT works with various Federal, 

State, and local agencies to educate them about the assistance and resources OIG 

can provide when an agriculture-related incident occurs. Coordination with and outreach to our counterparts at the State and local level is vital to build the skills and 

partnerships necessary for effective, multilevel government responses to agricultural 

emergencies. 

During the execution of a search warrant in one investigation in 2006, the ERT 

assisted with the identification and depopulation of game fowl at an illegal cockfighting pit in Oklahoma. Birds utilized in animal fighting competitions present a 

health risk to humans and animals because the birds may carry infectious diseases 

such as Exotic Newcastle Disease and AI. 

Our WFIT members undergo extensive training to gain the skills and experience 

necessary to conduct wildland fire-related investigations.5 The OIG agents comprising the WFIT attend the FS’ Basic Fire Academy that incorporates training in 

Incident Command, Basic Wildfire Suppression Orientation, Firefighter Training, 

Introduction to Wildland Fire, and Interagency Serious Accident Investigation 

Training. In October 2006, WFIT members responded to the Esperanza Fire that 

claimed the lives of five FS fire engine crew members near Cabazon, California. 

WFIT members arrived at the site within 24 hours of the fatalities to begin organizing their investigation. OIG’s investigation of the circumstances leading to the 

Esperanza Fire deaths is ongoing. 

The Bovine Tuberculosis Eradication Program 

APHIS administers the Bovine Tuberculosis Eradication Program (BTEP) that 

was established in 1917 to eliminate bovine tuberculosis (TB) in the United States. 

Because of concerns we previously identified regarding the agency’s systemic classification and testing of relevant TB cases in one State, OIG conducted a more comprehensive audit of APHIS’ administrative controls over BTEP. We found that 

APHIS had made improvements to BTEP since the Secretary’s Emergency Declaration in October 2000,6 but weaknesses in oversight made it difficult for the agency 

to timely detect and eradicate the disease. APHIS’ status system—important because it dictates the extent of Federal testing and movement controls for cattle in 
49 

7Such as air passengers and truck cargo AQIM inspections. 

each State or zone—did not capture most TB cases. From fiscal year 2001 through 

2005, 272 TB-infected cattle were detected through slaughter surveillance, but 

APHIS excluded 96 percent from the status system because it could not locate the 

source herd or find an additional infected animal in that herd. Approximately 75 

percent of the TB-infected cattle detected through slaughter surveillance originated 

in Mexico, and these animals spent months at U.S. farms and feedlots with no restrictions to prevent commingling with domestic cattle. Mexican cattle are tested before entry, but APHIS had not established controls to compensate for the 3- to 2 

month TB incubation period. 

We recommended that APHIS perform program reviews periodically; review and 

approve States’ annual and monthly reports and use them to assess/minimize areas 

of highest risk; enhance its two key BTEP control functions (the status classification 

and slaughter surveillance systems); and strengthen movement/testing controls to 

address the disease’s incubation period. The agencies agreed to take corrective actions based on our findings and recommendations. 

Agricultural Inspection Efforts on the U.S. Border 

With the creation of DHS in March 2003, U.S. Customs and Border Protection 

(CBP) assumed responsibility to inspect agricultural goods arriving at U.S. ports 

while APHIS retained responsibility for agriculture related policies and procedures. 

We issued a report in February 2007 from our joint review with DHS–OIG of border 

inspection issues. We assessed selected agricultural inspection activities that were 

transferred to CBP. 

Our joint review found that CBP generally complied with agricultural inspection 

requirements at the ports we visited. However, improvements are needed regarding 

risk identification activities. CBP’s sampling for Agricultural Quarantine Inspection 

Monitoring (AQIM)—which helps USDA predict future risks to agriculture from 

pests/diseases—did not meet sampling requirements for 13 of 18 pathway activities 

at four ports.7 CBP also lacks a current staffing model for agriculture specialists 

and performance measures for many activities that would ensure personnel are used 

effectively. 

APHIS officials agreed to develop a risk assessment process for incoming rail 

cargo. However, agency officials cite operational difficulties (such as obtaining timely cargo manifests) as a barrier to developing a workable system. APHIS has not 

yet issued policies and uniform procedures to clearly define how transportation/export shipments will be monitored. We also found that APHIS needs to issue instructions to CBP clarifying APHIS policy on labeling and packaging seized agricultural 

products. 

PROTECTING AND IMPROVING THE INTEGRITY OF USDA PROGRAMS

OIG’s second strategic priority is audit and investigative work to protect the integrity and efficiency of USDA programs and benefits. A substantial amount of 

OIG’s audit and investigation resources in fiscal year 2006 were focused on Farm 

Service Agency (FSA) and Risk Management Agency (RMA) programs and operations. OIG continues to work to combat fraud and deter criminal activity in farm 

programs, such as payment limitations, crop insurance, and conversion of mortgaged 

property. 

Food and Nutrition Service (FNS) programs providing food assistance to needy 

Americans is a major portion of USDA’s annual budget—the Food Stamp Program 

helps over 26 million people each month, and 15.5 million children receive a free 

or reduced-price school lunch. Fraud in FNS programs such as the Women, Infants, 

and Children (WIC), Food Stamp, and the Children and Adult Care Feeding Programs remains a high priority for OIG. 

USDA Compliance with the Improper Payments Information Act 

Within USDA, the Office of the Chief Financial Officer (OCFO) is designated as 

the lead agency for coordinating and reporting on the Department’s efforts to implement the Improper Payments Information Act (IPIA). OCFO has designated IPIA 

compliance as a top priority for fiscal year 2007. 

To determine the Department’s compliance with IPIA, OIG initiated audits of four 

USDA agencies in fiscal year 2006—FSA, FS, Rural Development’s (RD) Rural 

Housing Service (RHS), and the Natural Resources Conservation Service (NRCS). 

Our objectives included reviewing agency efforts to quantify improper payments for 

high risk programs, assessing agency corrective actions related to our previous audits, and substantiating agency results reported in USDA’s Performance and Accountability Report for fiscal year 2005. 
50 

Our audits revealed significant findings on agency compliance with IPIA. OIG 

found that valid statistical samples had not been performed for three of the four 

agencies reviewed. Improper payments reported in fiscal year 2005 were not properly calculated and the estimated improper payments reported in fiscal year 2005 

did not always include payments made to ineligible recipients. We determined that 

corrective actions were too narrow in scope and ineffective in addressing our prior 

findings. OCFO generally agreed with our recommendations to correct these conditions and we are working with agencies to improve their implementation of IPIA 

requirements. OIG is currently auditing several USDA agencies to assess their efforts to quantify improper payment error rates for high risk programs. 

Farm Programs—Improving Agency Controls to Prevent Loans to Ineligible Recipients 

When farmers and ranchers are unable to repay their Farm Loan Programs (FLP) 

loans in full, Congress requires that FSA consider them ineligible for future loans. 

Using data-mining techniques, we reviewed the approximately 139,000 loans active 

in FSA’s database (as of the beginning of fiscal year 2005) to isolate 239 borrowers 

who were potentially ineligible for having received prior debt forgiveness. Our detailed review of six potentially ineligible borrowers revealed that three were, in fact, 

ineligible and should not have received FLP loans. FSA subsequently reviewed all 

239 borrowers and ultimately found 113 loans totaling over $7.5 million, issued during 1999–2004, were ineligible. In general, we determined that the unauthorized assistance occurred because FLP loan officials did not follow established procedures 

for determining applicants’ eligibility and FSA’s automated management tools 

lacked the applicants’ complete debt history. 

FSA took action to collect the 113 ineligible loans as appropriate. Further, FSA 

issued guidance to help employees determine whether applicants have received prior 

FLP debt forgiveness and is developing a new automated system that will automatically display applicants’ complete debt histories. FSA is currently pilot testing the 

new system at two State offices and plans to implement it nationwide. 

Improving the Integrity of the Crop Insurance Program 

Due to continuing concerns about costs incurred by the Federal crop insurance 

program, OIG conducted an overview of the program. In collaboration with FSA and 

RMA, OIG identified conditions that are often associated with fraud, abuse, and 

mismanagement. 

We identified two major factors that must be in place to enhance the integrity of 

the crop insurance program: effective management controls to ensure program operations are meeting program objectives and aggressive enforcement through criminal 

investigations and agency compliance reviews. 

Based on this overview and our discussions with FSA/RMA about the current 

state of the crop insurance program, we presented a series of recommendations that 

are consistent with OIG’s prior work. Among other recommendations, we found that 

agency officials should accelerate plans to create a single comprehensive information 

system for crop insurance, conservation, and farm programs; increase coordination 

and communication between RMA and FSA to ensure more effective growing season 

inspections; and strengthen RMA’s oversight and monitoring of the private sector’s 

application of the quality control review system. 

Investigating Fraud in USDA Farm Programs 

A recent OIG investigation resulted in a Montana producer and a former loan officer being sentenced for a scheme in which the producer filed false claims with FSA 

in order to receive program payments. The producer circumvented program payment 

limitations to fraudulently receive $1.4 million. The private loan officer provided 

false financial documents to FSA regarding the other partners’ participation in the 

farming operation. In July 2006, the producer was sentenced to serve 10 months in 

Federal prison and ordered to pay $226,035 in restitution. The former loan officer 

was sentenced the following month to a period of home confinement and probation. 

Another OIG investigation into potential farm program fraud resulted in orders to repay the Government over $1 million and the sentencing of two individuals and 

three corporations in 2006. Our investigation revealed that two individuals and 

three corporations in the Texas panhandle fraudulently obtained approximately 

$400,000 in RMA crop insurance indemnity payments and FSA disaster program 

payments by shifting their unreported cotton production for program payment purposes. The producers assigned their hidden cotton production to other established 

accounts at a cotton gin owned by one of the individuals. A producer and two corporations were sentenced in August 2006. The producer was sentenced to 12 

months’ imprisonment, followed by 36 months’ supervised release, and was ordered 

to pay approximately $331,000 in restitution. The corporations each received sen-
51 

8 Examples would be food safety concerns affecting public heath, such as contaminated food 

or black-market WIC products. 

tences of 60 months of probation and were ordered to pay restitution totaling approximately $331,000. In September 2006, the second individual and the remaining 

corporation were both sentenced to 60 months of probation and were ordered to pay 

restitution of $362,775, severally and jointly. 

A third OIG investigation involving farm program fraud resulted in the repay- ment of $1,085,000 to FSA. The Idaho producer involved received 3 years of probation and 80 hours of community service. The producer’s son was also sentenced to 

3 years probation and was fined $4,000. The sentence included a joint restitution 

order of $1,085,000 imposed on the two defendants. The OIG investigation disclosed 

that the mother and son converted 305 head of cattle pledged as collateral to FSA. 

They pled guilty in May 2006 to theft/conversion of FSA collateral. FSA also has 

a lien against their property that is valued at more than $1 million. 

USDA Food Programs—FNS Oversight of Electronic Benefits Transfer Operations 

In fiscal year 2007, FNS estimates that Food Stamp benefits of about $30 billion 

will be provided to over 25 million participants. State agencies now deliver Food 

Stamp Program (FSP) benefits almost entirely through Electronic Benefit Transfer 

(EBT) systems using EBT benefit cards issued to recipients. OIG has monitored and 

audited the implementation of EBT by FNS and States since the system’s inception 

in the 1990s. We recently issued a follow-up audit to evaluate corrective actions 

FNS has taken in response to our prior audits and to ensure adequate agency oversight of EBT systems. 

We concluded that FNS oversight of EBT operations was generally effective. However, despite FNS requirements to safeguard EBT systems, inadequate control over 

State agency access to the system remains a problem. Based on our earlier work, 

FNS had agreed to strengthen procedures for controlling access to State EBT systems and directed States to conduct semiannual reviews of employee access. However, FNS did not independently confirm that States adequately controlled access. 

EBT trafficking through the illegal and unauthorized use of Point of Sale (POS) 

equipment is another system vulnerability. Unscrupulous retailers have circumvented the EBT security controls by fraudulently obtaining new equipment and/ 

or illegally moving existing machines to unauthorized locations. Our September 

2006 report found that in their contract proposals to acquire EBT systems, States 

were not required to consider equipment functionality and/or technological specifications that could prevent the illegal removal and unauthorized use of existing EBT 

POS equipment. 

Based on our audit, FNS agreed to take steps to ensure that States limit unauthorized access to EBT systems and to require States to implement, via the EBT 

contract, formal processes during POS equipment replacement to prevent retailers 

from fraudulently obtaining equipment. 

This year, we will conduct further audits regarding FNS oversight of EBT systems. Our work will include reviewing FNS oversight of the largest private EBT 

processor and two State agencies. 

Investigations of EBT Trafficking 

OIG devotes extensive resources to investigate unscrupulous retailers who circumvent EBT security controls by fraudulently obtaining new equipment and/or illegally moving existing machines to unauthorized locations. In our Food Stamp Program investigative work, we focus our resources on high impact cases, such as those 

involving large-scale traffickers, those with potential connections to terrorist activity, and cases involving additional types of criminal activities beyond benefit fraud.8

Comparing our final fiscal year 2006 investigative statistics to the prior fiscal year, 

the number of food stamp trafficking investigations we opened increased from 77 to 

84; the number we referred to DOJ increased from 21 to 31; and the number of indictments resulting from OIG food stamp investigations increased from 70 to 146. 

EBT fraud cases are very complex investigations, so OIG worked in 2006 to develop and conduct training focused on improving methods to detect and analyze 

trends indicating fraud. OIG is creating a database that will capture vital information regarding EBT trafficking investigations to identify large scale fraud networks. 

OIG has initiated numerous investigations as a result of our collaborative efforts 

with multiple Federal and local law enforcement agencies. A major OIG food stamp 

fraud investigation resulted in a Chicago grocery store owner being sentenced in August 2006 to 51 months in prison and ordered to pay $1.4 million in restitution. The 

store owner pled guilty to wire fraud and money laundering. Two months earlier, 

the store owner pled guilty in Federal court in Florida to conspiracy for providing 
52 

funding to the Palestinian Islamic Jihad, in violation of the International Emergency Economic Powers Act. The store owner had conspired with other persons and 

unauthorized stores to conduct thousands of illegal electronic food stamp benefit 

transactions. 

Expanding Efforts to Deter WIC Fraud 

WIC is a vital Federal program to provide supplemental foods and nutrition education to lower-income pregnant, breast-feeding, and postpartum women, and infants and children who are at nutritional risk. 

The main product purchased with WIC vouchers is infant formula. Theft rings 

around the country are stealing, re-labeling, and reselling infant formula. When infant formula is stolen, it is taken out of the regulated retail system, and there can 

be no guarantee the formula is safe and wholesome. In response to this growing concern, OIG is expanding alliances with State and local law enforcement agencies to 

better coordinate jurisdictional investigative efforts into broader regional efforts. 

Our ultimate objective is to develop a national initiative that will enable OIG to 

track and maintain records of stolen infant formula incidents across the United 

States. 

A recent OIG infant formula investigation involved an Ohio furniture store owner 

who led a nationwide network that trafficked in stolen merchandise and food 

stamps through inner-city markets. The stolen merchandise included infant formula, diabetic blood glucose test strips, and over-the-counter medications. The stolen merchandise was transported to wholesalers and warehouses in States including 

Indiana, Illinois, Wisconsin, New York, Florida, and California. The store owner and 

24 other individuals were charged with crimes ranging from food stamp trafficking 

to transportation of stolen property and money laundering. During 2005–2006, 21 

individuals have pled guilty or were found guilty, including the leader of the criminal organization. Sentences imposed on the defendants ranged from 8 months to 11 

years, and monetary judgments and restitutions totaled over $2.7 million. On February 20, 2007, two of the three store owners involved in the scheme in Wisconsin 

pled guilty to false statements and conspiracy; the third is awaiting trial. This was 

a joint investigation with the FBI and the Ohio Organized Crime Investigations 

Commission. 

A second OIG infant formula investigation determined that a Pennsylvania convenience store owner was trafficking in food stamps and operating and engaging in 

an unlicensed money transmitting business. From 2001 to May 2006, the store 

owner transmitted more than $7 million without the license required by Federal and 

State law. The store owner bought and sold stolen goods such as infant formula, 

drug paraphernalia, and counterfeit cigarettes and music CDs. The store owner pled 

guilty in Federal court in November 2006 to operating an unlicensed money transmitting business and agreed to forfeit over $252,000. This investigation was part of 

a taskforce that included OIG agents and several other Federal and State enforcement agencies (FBI, Immigration and Customs Enforcement, Secret Service, IRS, 

and the Pennsylvania Department of Revenue). 

The OIG Response to Hurricanes Katrina and Rita: Audit Oversight and Investigative Support 

During last year’s testimony, we discussed USDA’s role in the Federal recovery 

efforts related to Hurricanes Katrina and Rita. OIG continues to work with the 

President’s Council on Integrity and Efficiency (PCIE) and DHS working groups to 

coordinate related investigative efforts and thereby maximize Federal investigative 

resources and prevent duplicative efforts. We coordinated efforts with both the Department of Housing and Urban Development’s (HUD) OIG and DHS–OIG to develop computer matching agreements with RHS. These agreements facilitate the 

ability of the participants to identity improper and fraudulent disaster assistance 

payments. Data matching is a highly effective tool in disaster assistance payment 

investigations for all of the agencies involved. 

OIG special agents are working Hurricane Katrina Fraud Task Force investigations in the Gulf Coast region. We continue to receive referrals throughout the country on individuals who have submitted false claims or provided false statements to 

obtain Federal benefits for which they were not entitled. At this time, as hurricane 

reconstruction efforts in the Gulf Coast region continue, OIG has begun receiving 

investigative referrals from FSA and RD that involve larger monetary amounts of 

fraud or theft and more complex fraud cases. 

A recent example of our hurricane relief investigative work involved an Illinois 

woman who obtained at least $23,000 in Hurricane Katrina housing, food stamps, 

and cash assistance for which she was not entitled. OIG worked with the Postal 

Service’s OIG to determine that the individual never resided in Louisiana or Mis-
53 

sissippi and thus would not have been affected by Hurricane Katrina. The individual sought benefits for non-existent family members. She pled guilty in October 

2006 to mail fraud and false statements and was sentenced in January 2007 to 48 

months in Federal prison, followed by 36 months of supervised release, and was ordered to pay $23,982 in restitution. 

We have also committed significant audit resources to conduct reviews of the Department’s hurricane relief efforts. In view of the substantial Federal funds appropriated for hurricane disaster relief, a continuing concern for both program managers and the Congress is the potential for excessive or duplicative payments to individuals in hurricane-affected communities. 

In the aftermath of Hurricanes Katrina and Rita, RD—through RHS—placed 

11,000 evacuees into 4,100 Rural Rental Housing (RRH) apartment units in 45 

States and provided $2.6 million in emergency rental assistance. OIG evaluated 

RHS management controls for multifamily housing funds targeted for disaster assistance. We found that most residents placed in RRH apartments needed only adequate housing and not rental assistance because the Federal Emergency Management Agency (FEMA) was already providing financial assistance. As a result, much 

of the $2.6 million provided by RHS duplicated FEMA assistance. 

Specifically, our review determined that RHS’ database system contained generally inaccurate/incomplete information on hurricane victims and the amount of 

rental assistance they received. Some property owners required tenants to pay rent 

even though the owner had already received rental assistance directly from RHS. 

The agency was also not able to identify victims who used the FEMA identifying 

numbers of other individuals to obtain housing assistance. OIG found that some 

property owners had reclassified existing tenants as hurricane victims even though 

the tenants had no change in income or other circumstances. This resulted in unnecessary RRH rental assistance to the tenants. 

RHS agreed to improve its information system and related management controls. 

To better prepare for future disaster situations, the agency is implementing corrective actions regarding coordinating its actions and information with other Federal 

agencies providing housing assistance. 

This year, we will continue our oversight work regarding USDA’s response to 

major hurricanes. OIG currently has 11 audits in process pertaining to the Department’s hurricane relief operations, including reviews of FNS’ Disaster Food Stamp 

Program payments in five hurricane-affected States and RMA controls to provide 

hurricane victims in Florida with timely and accurate indemnity payments. 

Assessing USDA Trade Programs and Operations 

In 2002, the Farm Bill and the President’s Management Agenda (PMA) established a number of new goals and requirements for the Foreign Agricultural Service 

(FAS), the agency charged with coordinating USDA’s international activities. The 

2002 Farm Bill’s trade section contained 13 provisions affecting FAS programs, including export credit guarantees, market development, export enhancement, food 

aid development, and technical barriers to trade. OIG initiated a review to determine the status of FAS’ efforts to implement the 2002 Farm Bill’s trade and food 

aid programs and to evaluate the agency’s efforts to address problems that the PMA 

identified in food aid programs. 

We found that FAS took prompt action to implement 10 out of the 13 Farm Bill 

trade provisions within 1 year of enactment. However, FAS has not developed a 

business process to ensure that the Farm Bill’s global market strategy requirements—coordinating USDA resources and programs with other Federal agencies to 

identify export opportunities and remove trade barriers—are being met on a global 

basis. FAS managers have followed a strategy of supporting agricultural exporters 

(referred to as ‘‘cooperators’’) when implementing their individual country and regional market strategies. In our view, such efforts have not been sufficiently integrated to produce a focused, global strategy that would allow FAS to effectively 

identify and react to changing trends in global markets. The U.S. share of global 

agricultural exports declined from 22 percent to 9.7 percent during 1984–2005, yet 

FAS officials do not believe that a central planning process or formal global marketing strategy is necessary. 

The PMA cited several problems in U.S. food aid programs, including program duplication between FAS and the U.S. Agency for International Development (USAID) 

that wasted donated food supplies and excessive administrative/transportation costs. 

OIG found that FAS has strengthened its program planning and improved consultation and coordination with USAID, USDA’s Economic Research Service, and other 

organizations to develop better outcome-oriented performance measures and reporting. However, we recommended that FAS develop outcome-based performance measures to more accurately reflect program accomplishments in recipient countries. OIG 
54 

is assessing the agency’s response to our draft report and we anticipate issuing a 

final report in April 2007. 

Identifying Barriers to U.S Agricultural Exports 

OIG received a congressional request in 2006 to review certain aspects of FAS 

market development programs in fostering expanded trade activities for U.S. agricultural exports. We initiated an audit to examine the extent to which FAS conducts 

outreach to U.S. agricultural interests to identify trade constraints and foreign agricultural business opportunities; determine if the agency is presenting information 

on identified trade barriers to the U.S. Trade Representative (USTR) and FAS’ private sector cooperators; and review whether USDA efforts to promote U.S. agricultural exports are being presented, with measurable benchmarks, in the National Export Strategy. OIG’s report was issued in February 2007. We found that FAS does 

not formally track its efforts to expand trade activities or conduct outreach to U.S. 

exporters and does not have a formal process for summarizing and presenting trade 

barriers to the USTR. 

Ensuring Accountability in Foreign Food Aid Programs 

FAS administers foreign food aid programs, largely through grants to intermediaries known as private voluntary organizations (PVOs), the charitable, nonprofit organizations responsible for implementing program objectives abroad. FAS 

expended approximately $400 million for its food aid programs in fiscal year 2006. 

In March 2006, we issued a report assessing FAS’ progress in addressing management control weaknesses regarding the Food for Progress program identified in an 

earlier OIG audit. Our latest report also reviewed eight judgmentally selected PVOs, 

three of which were the subjects of a hotline complaint. The audit evaluated issues 

such as internal agency controls/processes for evaluating grant proposals and 

awarding grant agreements, monitoring compliance with grant terms and conditions, and determining program results. 

OIG found that many of the recommendations from our prior audit report had not 

been implemented, and therefore FAS could not provide reasonable assurance that 

PVOs were meeting their program objectives or spending funds appropriately. FAS 

lacked procedures to confirm that PVOs were recognized by their host governments 

and were able to operate effectively in-country. FAS did not pursue grant funds lost 

due to PVO mismanagement. Due to these internal control weaknesses, we concluded that FAS did not adequately follow up and determine whether there was 

mismanagement of $2.2 million in grant funds. 

We recommended that FAS strengthen its ability to monitor food aid agreements 

by implementing procedures to review PVOs’ semiannual reports, conduct onsite reviews, and complete closeout reviews of food aid agreements. The agency should confirm that PVOs are viable agents in their host countries before shipping donated 

commodities to these private groups and aggressively seek recovery of grant funds 

lost due to PVO mismanagement. Generally, FAS agreed with our recommendations 

and stated that agency efforts were underway to implement several of them. 

Oversight of Farm, Conservation, and Research Programs in 2007 

OIG has initiated or plans to conduct several audits to review USDA farm and 

conservation programs. Work is underway to examine RMA’s effectiveness in monitoring private insurance providers and determine if its compliance activities are adequate to improve the crop insurance program and reduce fraud, waste, and abuse. 

We are planning to review FSA’s management controls in 2007 to assess their effectiveness to prevent farm program payments being made to producers who have been 

disqualified due to civil, criminal, or administrative actions. 

There is considerable congressional interest in expanding USDA’s role in our nation’s efforts to develop a viable renewable energy program. The Department’s activities include financial incentives (loans, loan guarantees, grants for capital equipment) for farmers to grow crops that can produce renewable energy products such 

as ethanol. USDA research agencies are engaged in developing and improving methods to produce renewable energy. In 2007, OIG will evaluate the Department’s efforts to foster renewable energy technologies as well as the coordination between 

USDA agencies and other Federal agencies. These audits are currently underway. 

NRCS’ Wetlands Reserve Program (WRP) is a voluntary program offering landowners the opportunity to protect, restore, and enhance wetlands on their property. 

NRCS provides technical and financial support to help landowners with their wetland restoration efforts. We are reviewing the legitimacy of restoration costs and the 

agency’s ability to monitor restoration efforts. A related voluntary agency program 

is the Conservation Security Program (CSP), in which payments are provided to 

landowners to maintain and enhance natural resources. CSP identifies and rewards 

those farmers and ranchers who are meeting the highest standards of conservation 
55 

and environmental management on their operations. The Government Accountability Office reported that NRCS lacked adequate controls to prevent participants 

from receiving financial assistance from multiple programs for the same conservation practice. OIG has initiated an audit to determine whether NRCS has adequately implemented provisions of CSP. We are focusing on whether the agency has 

properly handled key issues such as program eligibility, the calculation of program 

payments, and the detection of improper payments. 

OIG also has an audit underway to review the agency’s procedures to assess and 

prioritize the rehabilitation of dams constructed with NRCS funding. Many of these 

dams are nearing the end of their 50-year design life. A recent survey of known rehabilitation needs in 22 States revealed that more than 2,200 dams need rehabilitation at an estimated cost of more than $540 million. The cost of rehabilitation will 

only increase with time as deterioration increases, construction costs rise, and more 

rehabilitation needs are identified. The Watershed Rehabilitation Program budget 

reported in the USDA fiscal year 2008 Budget Summary and Annual Performance 

Plan is $6 million. Our primary objective is to review the adequacy of NRCS program controls for the rehabilitation of flood control dams to mitigate potential threat 

or danger to life and property. 

Congress has provided substantial resources to support Agricultural Research 

Service (ARS) research regarding a wide array of food quality and safety issues, nutritional needs, and our environment’s natural resource base. ARS spends approximately $1.1 billion annually on 1,200 research projects organized into 22 national 

program areas at 100 locations and 4 overseas laboratories. We are currently evaluating the efficacy of ARS management controls over its intramural and extramural 

research agreements to ensure they are properly implemented. Our audit is examining ARS procedures to ensure that research funding is used for its intended purposes, research projects are adequately monitored, and project milestones are properly managed. 

THE MANAGEMENT OF USDA’S PUBLIC RESOURCES

Information Technology Security in USDA 

In recent years, USDA’s Office of the Chief Information Officer (OCIO) and OIG 

have placed a major emphasis on the need to plan and implement effective information technology (IT) security for the Department. OIG continues to conduct various 

audits and reviews of the Department’s IT security systems to assess and improve 

their performance. 

Based on our reviews in 2006, the National Information Technology Center 

(NITC) in Kansas City, Missouri, sustained its unqualified opinion on its general 

control structure, and OCFO’s National Finance Center (NFC) in New Orleans, Louisiana, received its first unqualified opinion on its design of its general control structure. However, we issued a qualified opinion on the effectiveness of NFC’s controls 

because the controls were not operating during the entire year. This effectiveness 

qualification was primarily attributed to the disruptive effects of Hurricane Katrina 

on NFC’s normal operating procedures. When our review determined that certain 

controls were not adequately designed, OCFO NFC updated its procedures to address our concerns. 

As required by the Federal Information Security Management Act of 2002, our annual audit of the Department’s IT security program continued to find significant 

weaknesses. These included needed improvement in contingency planning and testing, annual risk assessments, and configuration management. Due to the significance of the issues identified in our reviews, we continue to classify IT security as 

a material internal control weakness for USDA. 

USDA’s Universal Telecommunications Network (UTN) is the critical general support system serving the Department’s data network backbone for telecommunications and network support services. We identified weaknesses in OCIO’s ability 

to effectively manage and secure the UTN. OCIO had not completed required system testing, security control testing, and certification/accreditation of the UTN network prior to implementation. OCIO concurred with our recommendations and has 

taken significant actions to address identified weaknesses. 

Reducing Risks From Stolen USDA Computer Equipment 

In light of the disclosure or theft of Privacy Act/sensitive information from several 

Federal agencies in 2006 and OMB’s recent mandates on securing such information, 

OIG is assessing potential risks at USDA. We issued a report on February 27, 2007, 

from our review of stolen equipment within USDA. 

To the extent possible, we identified the information maintained on the stolen 

computers as well as sensitive information currently maintained on computers with-
56 

9FSA, NRCS, RD, and OCIO. 

10 ‘‘Follow-up on Prior Recommendations for Civil Rights Program and Employee Complaints,’’ 

issued September 2005. 

in the Department. OIG found that controls over stolen computer equipment were 

lacking in the four USDA agencies reviewed.9 Specifically, we found Privacy Act/sensitive information was stored on computers that were stolen and the agencies did 

not notify the individuals whose information may have been compromised. Additionally, these agencies lacked policies and procedures to adequately notify proper authorities and affected parties when thefts of computer equipment occurred. The 

agencies agreed with OIG’s recommendations. 

To date, OCIO has provided agencies with limited guidance on what actions to 

take if computers are lost or stolen. OIG recommended that OCIO implement Departmentwide guidance regarding tracking and reporting requirements for lost/stolen computer equipment. This should include procedures for determining whether 

the subject equipment may have contained Privacy Act or sensitive information. 

USDA Procedures to Assess Employee Civil Rights Complaints 

We have previously presented testimony to the Subcommittee about our audit 

work focusing on the Department’s processes and performance in handling allegations of discrimination against USDA employees or in USDA programs. Our most 

recent civil rights audit 10 assessed the Office of the Assistant Secretary for Civil 

Rights (ASCR) implementation of prior OIG recommendations that focused on the 

agency’s management and oversight of program and employment complaints. In response to a 2006 congressional request, we initiated an audit to evaluate the Department’s progress in addressing employee civil rights complaints and employee accountability for acts of discrimination. OIG will identify and evaluate the adequacy 

of the Department’s controls to properly process employee civil rights complaints 

and its processes to hold employees accountable for discrimination towards employees or in USDA programs. We anticipate issuing this report by the end of March 

2007. 

The National Computer Forensic Division: Advanced Investigative and Evidentiary 

Support 

As an authoritative resource in the investigation and analysis of network intrusions and attacks on USDA networks, OIG’s National Computer Forensic Division 

(NCFD) conducts thorough and accurate analyses of any IT network compromise by 

analyzing compromised servers, firewall logs, Intrusion Detection System logs, and 

Internet Protocol traffic logs. The NCFD continues to provide support, training, and 

advice on evidence collection and analysis to USDA agencies. During the past year, 

the NCFD provided onsite search warrant assistance for 12 warrants and analysis 

for 38 cases involving criminal activity, employee misconduct, and network intrusions. 

An example of NCFD’s work includes an investigation that was requested by the 

Department relating to a network intrusion and two servers that were compromised. 

NCFD determined that while two computer servers had been compromised multiple 

times by hackers in June 2006, the database containing personal identity information for 26,000 USDA employees had not been compromised or transferred from 

USDA computers. OIG is working with OCIO to ensure that all USDA networks and 

employee personal information are secure. 

Another recent investigation involved a woman employed as a Geographic Information Systems (GIS) technician with FSA. The woman reproduced and sold 41 pirated copies of USDA-licensed software on two Internet auction websites. The 

woman received $7,120 from the sales of the pirated software although its retail 

value exceeded $326,000. In June 2006, the woman pled guilty in a Federal court 

in Indiana to copyright infringement and was sentenced to 5 years of probation, restitution of $7,120 to the company owning the software copyright, and forfeiture of 

all computer-related equipment seized at her residence. This case resulted in the 

first Federal criminal conviction in Indiana involving the illegal sale of copyrighted 

materials over the Internet. 

NCFD forensically imaged and analyzed the hard drives of eight computers in the 

GIS lab of FSA’s Indiana State office for evidence that the software was copied utilizing one of the FSA computers. The forensic analysis produced evidence that was 

utilized in negotiating a guilty plea. 

USDA Financial Management 

As defined by the Government Accountability Office (GAO), success in Federal financial management is an unqualified audit opinion with no reportable conditions 
57 

11Federal Crop Insurance Corporation, Commodity Credit Corporation, FS, Rural Telephone 

Bank, FNS, and RD. 12 Primarily State and local governments. The crews at issue in this report were obtained 

from the Oregon Department of Forestry’s list. 13Private organizations that represent wildlife suppression contractors and provide training 

to their employees. 

and no instances of noncompliance with laws and regulations. In 2006, the Department’s financial statements received unqualified audit opinions, as did six USDA 

entities.11 This is an improvement from previous years. However, the Department 

and three agencies had material weaknesses and reportable conditions. The Department and four agencies also had instances of noncompliance with laws and regulations. 

Specifically, the Department’s material weaknesses related to improvements needed in overall financial management across USDA and IT security and controls. A 

reportable condition existed related to improvements needed in certain financial 

management practices and processes. Three instances of noncompliance were identified relating to the Federal Financial Management Improvement Act, the Improper 

Payments Information Act, and Managerial Cost Accounting practices. OIG continues to work with OCFO to ensure effective financial management throughout 

USDA. 

The Role of USDA and Agriculture in Protecting the Chesapeake Bay Watershed 

The Chesapeake Bay Program, which is administered by the U.S. Environmental 

Protection Agency (EPA), is mandated to direct restoration of the Chesapeake Bay 

through a regional partnership of Federal, State, and local agencies, academic institutions, and non-government organizations. OIG participated in a joint review of the 

program with EPA’s OIG that concentrated on the agricultural best management 

practices used to address non-point nutrient and sediment loading to the Chesapeake Bay watershed. 

Despite significant efforts to improve water quality in the Chesapeake Bay watershed, excess nutrients and sediment continue to impair the Bay’s water quality. Our 

joint review found that few of the agricultural practices in the State tributary strategies have been implemented because the agricultural community considers many 

of these practices to be either unprofitable or to require significant changes in farming techniques. We found that EPA must improve its collaboration with its Bay 

partners and the agricultural community to reduce the agricultural nutrients and 

sediments entering the Chesapeake Bay watershed. Members of the agricultural 

community have been reluctant to participate in this endeavor with EPA because 

of its regulatory enforcement role. 

We recommended that the Secretary or Deputy Secretary assign a senior-level official with commensurate authority to coordinate relevant USDA goals and programs with EPA and the Chesapeake Bay Program. USDA should consider the feasibility of targeting USDA funds on a regional and/or geographical basis to assist 

the Bay’s environmental restoration. The Department should also direct USDA 

agencies to expedite the establishment of outcome-based performance measurements 

to properly evaluate their conservation activities. USDA generally agreed with our 

recommendations. 

Evaluating Forest Service Use of Private Wildland Firefighting Crews 

As wildfire activity on National Forests (NF) has become more intense, FS has 

made increasing use of contract suppression crews to supplement agency resources. 

FS incident management personnel had previously noted numerous performance 

problems with poorly trained and inexperienced crews. Other reports (GAO, incident 

management personnel) have indicated similar problems. We evaluated FS’ administration of these contracts and its coordination with other parties 12 that also use 

these contracts. 

We determined that FS needed to improve its contract oversight to ensure that 

contract employees had met both the training and experience requirements for the 

positions they held on fire fighting crews. Our review found that a significant number of contract firefighters may not have been qualified to perform the duties required under the contract. FS needed to address control weaknesses with wildfire 

suppression associations 13 that provide training to contract employees. Language 

proficiency assessments should be improved to ensure contract crew personnel can 

communicate adequately with FS incident management personnel. Finally, we recommended that FS coordinate with other Federal agencies to identify undocumented 

workers on contracted crews. FS officials agreed with all of OIG’s recommendations 

and established timeframes for corrective actions. 
58 

Reducing Forest Service’s Large Fire Suppression Costs: Shared Responsibilities 

FS’ wildfire suppression costs have exceeded $1 billion in 4 of the past 7 years. 

Our audit focused on the most significant ‘‘cost drivers’’ that were impacting fire 

suppression costs. We determined that the majority of FS’ large fire suppression 

costs are directly linked to protecting private property—as opposed to National Forest System land—in the wildland urban interface (WUI). FS managers need to 

evaluate their agreements with State and local governments to ensure the costs of 

protecting the WUI are appropriately apportioned. A significant portion of these 

costs can be avoided and the safety of firefighters improved if the Federal Government can proactively work with State and local governments regarding prudent 

‘‘Firewise’’ zoning and building codes. 

In another report focusing on wildland fire issues and the Healthy Forest Initiative, we determined that FS needs to change some policies regarding wildland fire 

use (WFU). Hazardous fuels such as dead vegetation and undergrowth in our national forests are increasing the size and complexity of wildland fires. FS needs to 

reduce these fuels, increase the number of qualified personnel, and expand WFU to 

help control the costs of future fires. OIG further recommended that the agency implement improved processes to more effectively hold managers accountable for the 

financial impact of their decisions. 

FS agreed with our findings and recommendations and initiated corrective actions. These include working with OIG to jointly develop training for FS personnel 

conducting reviews of large fire operations. FS and OIG will jointly conduct the 

training prior to the 2007 fire season. 

OIG’S FISCAL YEAR 2008 BUDGET REQUEST

Before concluding, I would like to briefly comment on OIG’s fiscal year 2008 Budget Request. With your assistance and support, we are pleased to have built a solid 

record of constructive audit oversight and investigative accomplishment. Over the 

last 4 years we have produced a return on investment of $5.34 for each dollar of 

appropriated funds you have provided. During that period, our work has produced 

over $1.65 billion in monetary recoveries and cost avoidances, 1,449 indictments and 

1,358 convictions. In addition to our monetary results, we have made numerous recommendations that resulted in substantive management and program improvements. For example, in fiscal year 2006 we issued 425 program improvement recommendations and USDA managers agreed to implement 384 of them. These recommendations involved issues of congressional and public concern such as improving surveillance and monitoring of AI in domestic poultry, strengthening USDA’s 

food inspection operations, and improving the collection of unauthorized farm program payments. 

In addition to the statistical accomplishments mentioned above, fiscal year 2006 

and the first few months of fiscal year 2007 have been a particularly productive 

time for OIG in other ways as well. The following activities may be of particular 

interest to the Subcommittee. 

—OIG has devoted over $2 million and several staff years to providing oversight 

to USDA programs supporting the Gulf Cost region devastated during the 2005 

hurricane season in order to increase accountability in these programs and 

avoid waste and fraud in the distribution of benefits. The $445,000 Congress 

authorized in the fiscal year 2006 emergency supplemental to support these efforts was of great assistance. Currently, we have 11 audits and 11 investigations underway pertaining to USDA hurricane recovery assistance programs. 

—We also directed resources to review Departmental plans to deal with the 

threatened avian influenza pandemic, by advising the Department on how it 

could improve its plans and programs. 

—OIG took prompt and comprehensive action to evaluate the implementation of 

the Department’s IT security system. Through a coordinated program of audits, 

investigations, and other reviews, USDA OIG is addressing the areas of highest 

risk and providing insight and support to USDA program agencies. 

—We formed an Office of Inspections and Research (OIR) to address emerging 

issues that may require scientific, legal, statistical, or other expert competencies. Generally, OIR will conduct short-term, focused reviews and inspections of USDA’s programs and operations. OIR projects completed in the last 

year and currently underway include: 

A review of the Federal crop insurance program that, in collaboration with FSA 

and RMA, identified a number of fraud indicators or conditions that are often 

associated with fraud, waste, and mismanagement. 

An inspection regarding the coordination of the Department’s international activities and agreements. 
59 

An inspection of the security practices at a USDA laboratory that found the laboratory had made many improvements, both physical and through extensive 

training of personnel. 

—With the support of our congressional appropriators, we were able to strengthen 

our ability to support USDA programs through effective audits and investigations. Five years ago our information technology systems were inadequate to 

support our audit and investigative program. Thanks to your continued support, 

our IT environment is current and able to support sophisticated audit and investigative techniques. From fiscal year 1996 to fiscal year 2006, OIG’s staff 

level fell a total of 21 percent—which directly translates into a commensurate 

reduction in our audit and investigative capacity. With your support, we were 

able to arrest that trend in fiscal year 2006 and have begun—in a very small 

way—to strengthen our capacity. 

We respectfully request your support in continuing our efforts to maintain, and 

in some areas even improve, OIG effectiveness in fiscal year 2008. The President’s 

request asks for the minimum necessary to support our staffing level and advance 

our ability to safely and effectively respond to emerging public health and agriculture security threats. Specifically, the President’s fiscal year 2008 request of $84 

million for OIG provides for: 

—$1.9 million for 2008 mandatory pay costs. 

—$994,000 for 2007 pay costs. 

—$340,000 to fund five staff to reinforce our audit, investigation, and inspection 

programs focusing on the approximately $20 billion spent annually on USDA 

farm programs. 

—$757,000 for necessary equipment and training updates to the Computer 

Forensics Unit and the Emergency Response Team, and implementation of an 

automated audit workpaper system that will improve the timeliness of our audits and ensure that audit evidence is kept in accordance with Department of 

Justice standards. 

This concludes my testimony statement. I thank the Members of the Subcommittee for the opportunity to present information about OIG’s activities and our 

fiscal year 2008 Budget Request. 

PREPARED STATEMENT OF NANCY C. PELLETT, CHAIRMAN AND CHIEF EXECUTIVE

OFFICER, FARM CREDIT ADMINISTRATION

Mr. Chairman, Members of the Subcommittee, I am Nancy C. Pellett, Chairman 

and Chief Executive Officer of the Farm Credit Administration (FCA or Agency). On 

behalf of my colleagues on the FCA Board, Leland Strom of Illinois and Dallas 

Tonsager of South Dakota, and all the dedicated men and women of the Agency, 

I am pleased and honored to provide this testimony to the Subcommittee. 

I would like to thank the Subcommittee staff for its ongoing assistance during the 

budget process, and before I discuss the role and responsibility of the Farm Credit 

Administration and our budget request, I would respectfully bring to the Subcommittee’s attention that FCA’s administrative expenses are paid for by the institutions that we regulate and examine. In other words, FCA does not receive a Federal appropriation but is funded through annual assessments of Farm Credit System (System) institutions and the Federal Agricultural Mortgage Corporation 

(Farmer Mac). We fully support the proposed 2008 Budget Submission of the President. 

Mission of the Farm Credit Administration 

As directed by Congress, FCA’s mission is to ensure a safe, sound, and dependable 

source of credit and related services for agriculture and rural America. The Agency 

accomplishes its mission in two important ways. 

First, FCA ensures that the System and Farmer Mac remain safe and sound and 

comply with the applicable law and regulations. Specifically, our risk-based examinations and oversight strategies focus on an institution’s financial condition and any 

material existing or potential risk, as well as on the ability of its board and management to direct its operations. Our oversight and examination strategies also evaluate each institution’s efforts to serve all eligible borrowers, including young, beginning, and small farmers and ranchers. 

Secondly, FCA approves corporate charter changes, and researches, develops, and 

adopts regulations and policies that govern how System institutions conduct their 

business and interact with their customers and provides other necessary guidance. 

If a System institution violates a law or regulation, or operates in an unsafe or un-
60 

sound manner, we use our supervisory and enforcement authorities to ensure appropriate corrective action. 

Fiscal Year 2006 Accomplishments 

In 2006 we continued our efforts to achieve our Agency’s strategic goals through 

(1) responsible regulation and public policymaking and (2) effective risk identification and corrective action. FCA has worked hard to maintain the System’s safety 

and soundness. We also continually explore ways to reduce regulatory burden on the 

FCS and to ensure that all System institutions are able to provide agriculture and 

rural America with continuous access to credit and related services. 

EXAMINATION PROGRAMS FOR FCS BANKS AND ASSOCIATIONS

One of the Agency’s highest priorities is the development and implementation of 

efficient and effective risk-based oversight and examination programs that meet the 

high standards and expectations of the Congress; investors in System debt obligations; the farmers, ranchers, and cooperatives that own System banks and associations; and the public at large. Our examination programs and practices have worked 

well over the years and have contributed to the present safe and sound overall condition of the System, but we must continue to evolve and prepare for the increasingly complex nature of financing agriculture and rural America. 

With the changes in the System and our human capital challenges within the 

Agency (i.e., pending retirements, normal attrition of staff, and the ever-increasing 

need for more sophisticated skills in the financial sector), we have undertaken a 

number of initiatives to enhance our skills and level of expertise in key functional 

examination areas. We have also realigned our organizational structure to make the 

best use of our resources. The evolving nature of agriculture and the Farm Credit 

System necessitates a flexible organizational structure at FCA. At the present time, 

the sound financial condition of the System also provides us a unique opportunity 

to prepare for the future. In 2006 our Office of Examination completed its transition 

from a regionally based field office structure to division examination teams that are 

organized on a national basis. Office locations have been retained, but the examination programs are now managed nationally to better match examiner skills to material and strategic risks faced by the FCS institutions. 

On a national level, we actively monitor risks that may affect groups of System 

institutions or the entire System, including risks that may arise from the agricultural, financial, and economic environment in which the System institutions operate. Our job is not to forecast specific events but to understand the environment so 

that we can take steps to help System institutions take pre-emptive actions before 

adverse trends develop. 

Examiners also use a risk-based examination and supervision program to differentiate the risks and develop individualized oversight plans for each FCS institution. 

We set the scope and frequency of each examination based on the level of risk in 

the institution. In addition, we continually identify, evaluate, and proactively address risks within each institution. Examiners base the scope of their oversight and 

examination activities on their assessment of an institution’s internal control environments and the ability of the institution’s board and management to manage 

risks, both present and future. The frequency and depth of our examination activities may vary, but each institution is provided a summary of our activities and a 

report on its overall condition every 18 months as required by the Farm Credit Act. 

As part of our ongoing efforts, we monitor each institution’s risk profile. The Financial Institution Rating System (FIRS) is the primary risk categorization and rating tool used by examiners to indicate the safety and soundness of an institution. 

The rating system is similar to other Federal financial regulators’ CAMELS (capital 

adequacy, asset quality, management performance, earnings, liquidity, and sensitivity to interest rate risk) rating scale. FIRS ratings range from 1 (for a sound institution) to 5 (for an institution that is likely to fail). Throughout fiscal year 2006, 

FIRS ratings as a whole continued to reflect the stable financial condition of the 

FCS. The overall trend in FIRS ratings continues to be positive, with eighty-three 

1-rated institutions and seventeen 2-rated institutions, and one 3-rated institution. 

Importantly, there were no 4- or 5-rated institutions. In addition, no FCS institutions were under enforcement action and no FCS institutions were in receivership. 

The overall financial strength maintained by the System remains strong and does 

not pose material risk to investors in FCS debt, the Farm Credit System Insurance 

Corporation (FCSIC), and FCS institution stockholders. 

During fiscal year 2006, FCA also performed various examination and other services for the Small Business Administration, the U.S. Department of Agriculture, 

FCSIC, and the National Cooperative Bank. Each of these entities reimburses FCA 

for its services. The safety and soundness of the System and Farmer Mac remains 
61 

our primary objective. However, we believe the continuing use of FCA examination 

resources by other agencies is a positive reflection on the expertise of FCA examiners and serves to broaden their examination skills while increasing job satisfaction 

and employee retention. It also helps us defray some of the costs of our operations 

while providing a valuable service. 

REGULATORY ACTIVITY

Congress has given the FCA Board statutory authority to establish policy and prescribe regulations necessary to ensure that FCS institutions comply with the law 

and operate in a safe and sound manner. The Agency’s regulatory philosophy articulates our commitment to establishing a flexible regulatory environment that enables 

the System, consistent with statutory authority, to offer high-quality, reasonably 

priced credit to farmers and ranchers, their cooperatives, rural residents, and other 

entities on which farming operations depend. This translates into developing balanced, well-reasoned, flexible, and legally sound regulations. We strive to ensure 

that the benefits of regulations outweigh the costs; to maintain the System’s relevance in the marketplace and rural America; and to ensure that FCA’s policy actions encourage member-borrowers to participate in the management, control, and 

ownership of their Government-sponsored enterprise (GSE) institutions. 

For 2006 and early 2007, the Agency’s regulatory and policy projects included the 

following: 

—A final rule on governance of FCS institutions that provided enhanced oversight 

of management and operations by strengthening the independence of System institution boards and by incorporating best governance practices. 

—A final rule that amended and updated the regulations governing the termination of System status by a System institution. 

—A final rule to improve the transparency of public disclosures, strengthen board 

and management accountability and auditor independence, and increase shareholder and investor confidence in the System. 

In addition, relative to Farmer Mac, the Agency finalized a rule updating the 

Farmer Mac Risk-Based Capital (RBC) Stress Test. We amended the RBC regulations in response to changing financial markets, new business practices, and the 

evolution of the loan portfolio at Farmer Mac, as well as continued development of 

industry best practices among leading financial institutions. The rule is intended to 

more accurately reflect risk in the model in order to improve the model’s output— 

Farmer Mac’s regulatory minimum risk-based capital level. 

The Agency has also adopted an ambitious regulatory and policy agenda for 2007. 

The agenda includes the following goals: 

—Evaluating comments received on a proposed rule to change the ownership requirement for the eligibility of processing and marketing entities. 

—Continuing to evaluate how System partnerships and investments can increase 

the availability of funds to help stimulate economic growth and development in 

rural America under a pilot program initiated during fiscal year 2005. 

—Continuing to review current regulatory requirements governing eligibility and 

scope of lending to determine if these requirements are reasonable in light of 

agriculture’s changing landscape. Agency staff will identify issues and explore 

options for the Board’s consideration. 

—Developing and issuing an Advance Notice of Proposed Rulemaking to solicit 

public input on appropriate changes to FCA’s capital adequacy requirements for 

the System in light of Basel II and IA proposals by the other Federal banking 

agencies. 

CORPORATE ACTIVITIES

The pace of System restructuring remained slow in fiscal year 2006. Only one corporate application was submitted for FCA Board review and approval during fiscal 

year 2006, compared with four applications the prior year. As of January 1, 2007, 

the System had 95 direct-lender associations and five banks for a total of 100 banks 

and associations. Seven service corporations and special-purpose entities brought 

the total number of FCS institutions to 107 entities. Through mergers, the number 

of FCS associations has declined from 172 to 95 since 2000, and the number of FCS 

banks has dropped from seven to five. 

Condition of the Farm Credit System 

I will now turn to the condition of the Farm Credit System. I am pleased to report 

that the System’s overall condition and performance remained strong throughout 

2006. The FCS is fundamentally sound in all material aspects, and it continues to 

be a financially strong, reliable source of affordable credit to agriculture and rural 
62 

America. Capital levels continued to be strong, especially in consideration of the 

System’s risk profile. Asset quality remained high, loan volume growth was strong, 

and favorable credit conditions enabled the System to achieve almost $2.4 billion in 

earnings for the 12 months ended December 31, 2006. 

Loan volume continued to grow at a strong pace during 2006 while loan quality 

remained high. Gross loans increased by 16.2 percent to 123.4 billion. The level of 

nonperforming loans, including nonaccrual loans, decreased to 0.50 percent of gross 

loans outstanding. Delinquencies also remained minimal. The System has earned 

more than $1 billion consistently since the early 1990s; as a result, capital remains 

strong and is made up largely of earned surplus, the most stable form of capital. 

A strong capital position will help the System remain a viable, dependable, and 

competitive lender to agriculture and rural America during any near-term 

downturns in the agricultural economy. 

Federal Agricultural Mortgage Corporation 

FCA also has oversight, examination, and regulatory responsibility for the Federal 

Agricultural Mortgage Corporation, which is commonly known as Farmer Mac. 

Congress established Farmer Mac in 1988 to provide secondary market arrangements for agricultural mortgage and rural home loans. In this capacity, Farmer Mac 

creates and guarantees securities and other secondary market products that are 

backed by mortgages on farms and rural homes. Through a separate office required 

by statute (Office of Secondary Market Oversight), the Agency examines, regulates, 

and monitors Farmer Mac’s disclosures, financial condition, and operations on an 

ongoing basis and provides periodic reports to Congress. 

Like the Farm Credit System, Farmer Mac is a GSE devoted to agriculture and 

rural America. FCA and the financial markets recognize Farmer Mac as a separate 

GSE from the System’s banks and associations. Farmer Mac is not subject to any 

intra-System agreements or to the joint and several liability of the FCS banks, nor 

does the Farm Credit System Insurance Fund back Farmer Mac’s securities. However, by statute, in extreme circumstances Farmer Mac may issue obligations to the 

U.S. Treasury Department to fulfill the guarantee obligations of Farmer Mac Guaranteed Securities. 

In conclusion, we at FCA remain vigilant in our efforts to ensure that the Farm 

Credit System and Farmer Mac remain financially strong and focused on serving 

agriculture and rural America. 

Fiscal Year 2008 Budget Request 

Earlier this fiscal year, the Agency submitted a proposed total budget request of 

$47,482,520 for fiscal year 2008. The Agency’s proposed budget includes an assessment on System institutions for fiscal year 2008 of $42,550,000. The total amount 

of assessments collected from the FCS and Farmer Mac with carryover funds equals 

$46,000,000. Since approximately 82 percent of the Agency’s budget goes for salaries, wages, and related costs, almost all of the total budget amount will be used 

for these purposes. 

It is our intent to stay within the constraints of our fiscal year 2008 budget as 

presented, and we continue our efforts to be good stewards of the resources entrusted to us in order to meet our responsibilities. The Agency has worked hard to 

hold down the assessment to the System for our operations, and I believe we have 

achieved that objective over the past several years. While we are proud of our record 

and accomplishments, I assure you that the Agency will continue its commitment 

to excellence, effectiveness, and cost efficiency and will remain focused on our mission of ensuring a safe, sound, and dependable source of credit for agriculture and 

rural America. On behalf of my colleagues on the FCA Board and at the Agency, 

this concludes my statement and I thank you for the opportunity to share this information. 

Senator KOHL. Thank you very much, Mr. Secretary. We’ll now 

begin our rounds of questions. 

FSIS FUNDING LEVEL

Mr. Secretary, I was pleased to see an increase in the budget for 

the Food Safety and Inspection Service of approximately $100 million over the level provided in fiscal year 2006, but as you know, 

Mr. Secretary, there were some very serious budget problems last 

year, even though we provided the requested funding. Can you 

commit that this funding level will be adequate, in light of increas-
63 

ing workload and industry growth, for FSIS to maintain the proper 

amount of staff with the ability to do the proper testing and the 

work throughout the country? 

Secretary JOHANNS. Yes, we believe it will. And you’re absolutely 

right, last year we were in a very tough situation with the budget, 

and about 80 percent of this area is staffing, so if you get in a 

tough situation there’s not much you can do. It’s just a very, very 

difficult situation. But with the increased funding we have requested, we believe we can cover the anticipated need out there 

and meet the needs of this inspection area. So we appreciate your 

understanding of the situation, but we believe this will get us 

there. 

Senator KOHL. All right. Mr. Secretary, the problems faced in fiscal year 2006 and fiscal year 2007 were the result of several years 

of FSIS being shortchanged in their pay costs, although Congress 

has always provided the full amount requested. We seem to have 

dug ourselves out of that hole. Will this funding level keep us 

above board, or is FSIS going to have to dig into their program levels to fully fund pay costs? 

Secretary JOHANNS. Well, I’ll ask Scott to talk about pay costs, 

but again I think we’re in good shape with this funding request to 

get the job done. But, Scott, talk about pay costs, if you will. 

Mr. STEELE. Thank you. Yes, Senator, we have fully funded the 

on line inspection staff. We’re anticipating the growth in the industry in terms of meat and poultry inspection requirements. Of 

course there is some uncertainty with that, in terms of how much 

demand for inspection will be out there in the meat industry, but 

this is our best estimate right now. Based on that, we have fully 

funded all the inspection requirements, on line inspectors, that we 

need. 

And of course, as the Secretary pointed out, a large part of the 

budget is for wages and benefits, so there is a limited amount of 

flexibility. But we are doing audits on the agency right now. We’ve 

had people come in and look at that, outside auditors to look at the 

financial balance sheets of the organization. We’re doing a better 

job of tracking the expenditures in the agency. I think we’re at this 

point in time on top of the workload and funding requirements, but 

we will keep the committee and staff informed as we move through 

the year and report to you if there are any changes to our estimates. 

Senator KOHL. That’s good. 

AVIAN INFLUENZA (AI)

Mr. Secretary, the problem of avian flu, as we all know, has not 

gone away. In fact, there have been recent reports of an outbreak 

in England, and with spring weather around the corner there will 

be a lot of activity in migratory bird flyways. Can you tell us the 

total amount within APHIS that will be spent on avian flu activities this year, and tell us what this money will buy? 

Secretary JOHANNS. Yes. The 2008 budget requests a total of $82 

million for avian influenza. This will continue efforts initiated with 

the supplemental funding, which if you’ll remember was $91 million. $57 million of that is specifically designated for APHIS highly 

pathogenic AI activities. 
64 

Funding will be used to continue our surveillance, diagnostics, 

preparedness and response efforts, and then a piece of that is for 

international veterinary capacity-building. Of the total requested, 

$3.2 million is to develop methods to detect AI in the environment 

and over $5 million is for further AI research, including development of poultry vaccines. The 2008 budget also includes about $17 million for the APHIS 

ongoing low pathogenic program. Low path AI is a concern for its 

potential cost to the poultry industry, but it’s also a concern to us 

because of the potential that it might mutate into the highly pathogenic variety, so we also pay attention to that. So that details what 

we’re doing with the AI funding. 

Senator KOHL. Mr. Secretary, can we expect more outbreaks of 

avian flu this spring? And if we can, what precautions do you have 

in place? 

Secretary JOHANNS. Low pathogenic AI is common in the United 

States, so to address low path first, it’s been around about 100 

years. Birds go through a flu season much like humans go through 

a flu season. It’s typically not fatal to birds, and it’s not a problem 

to human consumption of poultry. You cook the bird and you kill 

the virus. And that would be true of both low and high path. But 

we will see low path. We have strategies in place to deal with that, 

but again, it’s fairly common. 

We’ve only had high path avian influenza in the United States 

on three occasions. The most recent was in 2004. And so far in this 

most recent international outbreak of high path avian influenza, 

we have not detected it. 

And we have been doing aggressive testing, in cooperation with 

the Department of the Interior, of wild birds and in Alaska, birds 

that would come down through the United States, through the 

flyway. In fact, we’ve done 79,000 wild bird samples to date. We 

haven’t detected it, which is good news. We will continue our efforts to monitor and detect, will continue to do environmental samples, but so far, so good, on the high path. 

EMERALD ASH BORER

Senator KOHL. Good. I’d like to ask you about emerald ash borer. 

Would you speak to the efforts of APHIS in undertaking to control 

and eradicate emerald ash borer where it has been found, and also 

please say a word about the surveys that the budget requests funding for in order to prevent the spread of emerald ash borer in 

States like my own of Wisconsin? 

Secretary JOHANNS. The budget includes $30.7 million, an increase of about $21 million over the 2007 Continuing Resolution, 

for emerald ash borer efforts. The funding will support survey efforts and regulatory activities to prevent additional spread of the 

pest. The budget also requests $2 million in APHIS plant methods 

development, a line item to develop control methods to do a better 

job of managing EAB. 

The program’s immediate goal is to protect infested areas by containing the current infestation—mainly that would be in Michigan, 

Ohio, and Indiana—and eliminate isolated outbreaks, such as those 

detected in States like yours or Illinois or Maryland, and develop 

a long term control and eradication strategy. So we’ve boosted our 
65 

request for funding here by about $21 million over where we were 

with the Continuing Resolution. 

Senator KOHL. I thank you very much. I’d like to call on Senator 

Bennett. 

Senator BENNETT. Thank you, Mr. Chairman. 

FSA COMPUTER SYSTEM

Mr. Secretary, we’re becoming increasingly aware of the situation 

regarding the computer system in the Farm Service Agency. I’m 

sure you’re familiar with that. I understand it has gotten so bad 

that direction has been given to State and county officers as to 

what times of day they could use the system because it’s not up in 

a uniform fashion. 

Can you walk us through the issues in relation to that and what 

you’re doing? The funding request did not appear in this year’s 

budget, so I assume you have a strategy for dealing with it. Just 

talk us through that one. 

Secretary JOHANNS. Well, we are working with staff. In fact, I 

think it was yesterday we gave an extensive briefing with our computer experts on some of the problems we are facing. And I’ll just 

be very candid with you. This is an area where we’re going to need 

some help. 

Senator BENNETT. Does ‘‘help’’ mean money? 

Secretary JOHANNS. It always does in government, doesn’t it? 

Senator BENNETT. Yes. 

Secretary JOHANNS. Here is the challenge we face. Beginning in 

November 2006, FSA experienced performance problems in its webbased software for programs such as the MILC program, Direct 

and Counter-Cyclical Payments, and the 2007 crop year farm reconstitutions. The amount of time systems were off line, in other 

words, dark, became progressively longer. A number of corrective 

actions were put in place, but again, the problem just continued to 

worsen. 

So FSA did what you said, they rationed web access time to try 

to alleviate that overloading of computing resources, as a means to 

try to continue serving producers while other steps were put in 

place to aggressively diagnose the problem we’re facing. That policy 

was suspended on February 9. 

A team was put together of USDA and private sector experts to 

observe the Kansas City Web Farm under a load situation. The 

team’s recommendations to optimize the performance of the computing environment in applications systems are being implemented, and service has been restored at a pre-November level. 

That’s my understanding. But I will tell you that I don’t believe, 

in fact, no doubt about it, the problem is not solved. 

FSA and the department’s OCIO have compiled a comprehensive 

list of investments in managed services that are needed to stabilize 

the infrastructure used by FSA to deliver program benefits. There’s 

dozens of reasons as to why this is happening now, but suffice it 

to say that over time a lot has been added to this system, and 

maybe at times not enough money to deal with the issues that the 

system was asked to face. 

So what happens now, as it has been explained to me, and this 

is very nontechnical language, but let’s say a farmer shows up and 
66 

we put that farmer’s information into the system to assist that 

farmer in some way. That is routed to our Kansas City facility, 

where that request works its way through a very complex system 

of lap and overlap and overlays, and quite honestly patched-together systems over a period of years. And as it’s working its way 

through all of that and trying to make this work, a period of time 

elapses, and if you don’t get your request met within that period 

of time, it will just kick you out. 

Senator BENNETT. Yes. I don’t want to go that deep into it because I want to hang onto my time, but I’m glad to know you’re 

on top of it to that degree. Can we expect a request for reprogramming or a supplemental or something? 

Secretary JOHANNS. In the next 3 weeks we hope to have in front 

of you, your staff, a business case for what’s going to be involved 

in this system. Here is what I will tell you, Senator, just to cut to 

the chase. 

I think there’s going to be a short term response to this, because 

building a new system takes time and it’s very expensive. It takes 

time. It could take 3 years plus. And so because of a new farm bill, 

because of a whole bunch of other things that just come along, I 

think there will be a short term response that we’re going to have 

to deal with and then a long term approach to a system. 

Senator BENNETT. I see. Well, thank you. 

INTERNATIONAL TRADE

Let’s talk about international trade. You mentioned exports 

being up, record levels. Trade Promotion Authority is set to expire 

this year. How much of the increase that we’ve seen in farm exports can be attributed to TPA, and also Trade Adjustment Assistance, or TAA, for farmers? How effective has all of this been with 

respect to that, and what would be the effect if TPA expired without being renewed? 

Secretary JOHANNS. Personally, I think it would be a very bad 

situation for farmers. Our exports have been growing. There are 

better experts here on the panel that can tell you or offer thoughts 

about what is related to Trade Promotion Authority or what is not, 

but here is the bottom line. 

I don’t think you will see another trade agreement negotiated or 

approved without Trade Promotion Authority. I think the trade initiative will just stop. It will just stop. Why? Why would a country 

negotiate with us, if the end result is there really is no agreement? 

There really is no end to the negotiations, and the possibilities for 

shaking on the deal and then the deal not really being a deal. So 

I personally believe it’s critically important. 

I will also offer this, because I’ve said it publicly. To me it doesn’t 

matter who is in the White House, it doesn’t matter if it’s one party 

or another party, I would have the same argument for Trade Promotion Authority no matter who was in the White House. I believe 

it’s just an important part of what we do. 

Now, I think there’s always an opportunity for discussion and 

analysis and debate about are we doing it well enough, are we not 

doing it well enough, what should we be doing, are we taking care 

of labor issues, environmental issues, trade issues, all of that. I 

think that’s a very, very appropriate discussion. But I think with-
67 

out Trade Promotion Authority we disarm whoever is in the White 

House to negotiate trade agreements and bring those to the Senate 

and the House for approval. 

Senator BENNETT. Thank you. I was going to discuss ag disaster 

assistance, but I think Senator Dorgan has signaled that he is 

going to deal with that. 

NATIONAL ANIMAL IDENTIFICATION SYSTEM (NAIS)

Let me ask you one last question quickly about the National Animal Identification System. There is some confusion about that. We 

have given you some money in the past. You have asked for some 

more money. But can you help us understand exactly where that 

is and where you see it going in the coming year? 

Secretary JOHANNS. The first thing I want to tell you is that it 

is a voluntary system. The system that we have designed and articulated basically says to the producer, ‘‘this is for you to make a 

decision as to whether this is the best approach for what you’re 

doing in your operation.’’ It is a voluntary system. 

The first piece of funding, if you will, actually predates me, but 

it was funding designed to put in place the structure necessary to 

do premises identification and lay the groundwork for the next 

steps. I can tell you that we had a goal at the end of January of 

having 25 percent of our premises registered, and we met that goal. 

We were right there. It was about 24.6 percent, so we have met 

that goal, and we continue to work with States across the country. 

The bottom line is this, Senator. Some States are really doing 

well. They’re doing great. They’re registering premises. People believe in it. Other States are not doing as well. They are behind. 

They are not registering premises as aggressively. There is a debate in the country as to how important this might be, but I think 

we’re overcoming that. We’re working to get good information out 

there. 

Ultimately, I think it has to happen. I was an advocate when I 

was Governor. I’m an advocate now as Secretary. I do believe the 

voluntary approach beats the mandatory approach. I think that’s 

where we need to be now. So I personally believe it is where we 

need to be headed. 

Senator BENNETT. Thank you very much, Mr. Chairman. 

Secretary JOHANNS. Thank you, Senator. 

Senator KOHL. Thank you very much, Senator Bennett. 

Senator Dorgan. 

Senator DORGAN. Mr. Chairman, thank you very much. 

DISASTER AID

Mr. Secretary, welcome. I intend to try to offer a disaster aid provision to the emergency supplemental bill. I mentioned to you that 

I’ve done that three times. Twice it got through the full Senate, got 

to conference, and was blocked by the administration. If I am successful in getting a disaster aid bill through the Senate on this supplemental, I’m wondering whether the administration will continue 

to want to block it or whether you’ll be working with us to try to 

pass it. 

Secretary JOHANNS. As you know, the administration’s historic 

position is to require offsets to find a way to pay for disaster aid, 
68 

and I don’t see anything that would indicate a change in that historic position. 

Senator DORGAN. Well, the President doesn’t request any offsets 

for any emergency supplemental bills. 

Secretary JOHANNS. In this area, the administration’s position, 

though, has been to require offsets. Here is what I would say, Senator, and you know I went through this when I was governor, and 

it hasn’t changed. On an annual basis we talk about disaster, and 

there will be disasters. This is a very, very large country. Weather 

patterns are different north to south and east to west. Probably the 

one guarantee I can make you each year is that somewhere in the 

United States there will be a disaster. 

It’s just a big country. Somewhere there’s going to be drought. 

Somewhere there’s probably going to be hurricane and tornado and 

hail damage and all of the things that farmers and ranchers deal 

with. And yet in other parts of the country they oftentimes experience historically best years. I won’t go through the figures. You 

know the figures. But I could cite figures about corn production 

this year and soybean production, etcetera. 

I personally believe that the long term answer to this is to look 

at what we’re doing here in terms of the policy and try to figure 

out, is there a solution? I would love to sit down with you and talk 

to you about some of the proposals we’ve made in the farm bill, because I believe they’ll make a big difference. I believe they will help 

this situation. Revenue countercyclical does work better—— 

Senator DORGAN. Mr. Secretary, I only have 51⁄2 minutes of it is 

now gone. I’m very interested in what you are saying, but that— 

I’m interested in a response to the question of will the administration attempt to block a disaster piece that I put in the emergency 

supplemental. 

Secretary JOHANNS. I can tell you, Senator, today the administration’s position has been and will be that offsets will be required to 

finance that. 

Senator DORGAN. Mr. Secretary, did the administration request 

offsets when we provided farm disaster aid for farmers who lost everything during Hurricane Katrina? 

Secretary JOHANNS. We have programs for disaster aid that we 

administer, and we administered some of those programs there 

that were funded and we literally could identify some funding and 

go out there and try to help in the Katrina situation. 

Senator DORGAN. Mr. Secretary, with respect to Katrina, that 

disaster had a name. Last year’s drought, the epicenter of which 

was in North and South Dakota, but it spread substantially, had 

no name. But the farmers in the Gulf region, as a result of Hurricane Katrina, did get disaster relief. A significant portion of that 

was declared emergency, signed by the President. 

I think it is unfair to suggest somehow that other farmers who 

lost everything, and there are others that did, should be subject to 

a different standard. And I just would say to you that I’m going 

to attempt once again to put a disaster provision in the emergency 

supplemental, and my hope is that this time the administration 

will not block it. 
69 

COUNTRY-OF-ORIGIN LABELING

I want to ask—again, we have such limited time—I want to ask 

about Canadian beef. I don’t understand why the administration is 

so anxious to almost have a cattle drive from Canada coming to 

this country. One-third of the cattle that have been identified with 

BSE in Canada were born after the feed ban, and yet the administration tells us because of the imposition of a feed ban that we 

won’t have any risk associated with this. 

It seems to me, Mr. Secretary, if you’re at least considering, as 

you are, bringing in substantial additional animals from Canada, 

who just recently discovered their ninth case—or tenth, if you consider the American cow—of BSE, that before you would do that you 

would agree to implement country-of-origin labeling and be aggressively interested in country-of-origin labeling, after which we then 

have a discussion about whether it is protective of this country’s 

economic interests and this country’s beef industry to bring in additional cattle from Canada in the shadow of their ninth case of BSE. 

Would you respond? 

Secretary JOHANNS. I’d be happy to. In reference to the question 

about country-of-origin labeling, let there be no mistake. Countryof-origin labeling is the law, effective October 1, 2008. I want you 

to understand that although I may have personal feelings about it 

and desire to have a great debate about it, those personal feelings 

aren’t important at this point. We will administer the law that 

Congress has put in place. 

In reference to the minimal risk rule that you referred to, that 

is in the rulemaking process at this point in time. We have sought 

comments. The deadline for that is coming up pretty quickly. We 

will very carefully review those comments and then make a decision about the appropriate course of action. 

We oftentimes say, and you’ve heard me say it, and probably 

read my comments when I speak of Japan and South Korea, that 

they must live by international standards. It’s not fair to have a 

personal country standard. And so I will endeavor to do everything 

I can to make sure we live by those standards, and that not only 

do I preach them, but I’m willing to recognize those standards in 

this country. So that’s kind of how we approach it. 

Senator DORGAN. Mr. Chairman, first of all, thank you. I would 

like to submit additional questions, and I’d like the record to show 

my great personal restraint in not responding to the cheerleading 

about Fast Track. 

Senator KOHL. Thank you, Senator Dorgan. 

Senator Craig. 

Senator CRAIG. Byron, message received. 

USDA LOAN GUARANTEE AUTHORITY

Mr. Secretary, I have twice passed legislation seeking to increase 

USDA loan guarantee authority from the $40 million it is now to 

about $100 million. Your lawyers said then that they couldn’t handle the logistics for projects this size. Now the President has proposed in his fiscal year 2008 budget a USDA loan guarantee package much larger than I ever tried to pass, as you know, to get into 

the ag portfolio new technologies. We must go beyond where we 
70 

have been. I sensed that some years ago with anaerobic digestion 

and a combination of other things, not only to solve waste problems 

but to enhance energy production. 

Question: Since we are now talking in the backdrop of a new 

farm bill that will likely increase the energy title and therefore the 

loan guarantee authority for USDA, could you talk about the process of the USDA’s loan guarantee program and your opinion as to 

how the department will handle this new loan guarantee authority? 

Secretary JOHANNS. Well, we do loan guarantees. They’re not 

new to us, as you know, Senator, and they are something we’re familiar with. In the farm bill proposal that we have submitted, we 

are proposing, for example, $2.1 billion in loan guarantees targeted 

at cellulosic ethanol. 

Senator CRAIG. Right. 

Secretary JOHANNS. And I guess probably the best way of answering your question is that the process that we have in place, we 

really envision as the process that would move us through those 

loan guarantees. So, again, it’s not new for us. It’s something we 

have done in the past. We feel confident that we can do it for what 

we’re proposing in the future. 

Senator CRAIG. Okay. Well, we’ll work with you on it. We’re glad 

that USDA is moving more aggressively in that direction. That’s 

certainly part of the solution of getting us over the hump in some 

of these changes necessary in technology, cellulosic being one of 

them. 

THE NATIONAL VETERINARIAN MEDICAL SERVICE ACT

In December 2003 the President signed into law a USDA program called National Veterinarian Medical Service Act that provides incentive to bolster the number of veterinarians in the field 

who would serve as first responders in emergency situations. Now, 

we’re primarily talking about large animal industry type veterinarians in rural areas. 

As I said in my opening statement, we are dumping millions of 

dollars into livestock disease research, and this panel helped provide hundreds of millions of dollars to create a National Animal 

Disease Lab in Ames, Iowa. I find it ironic that after spending all 

this money, we find ourselves in a crisis situation where we have 

a shortage of livestock veterinarians whose sole purpose is to intercept and defend this country against catastrophic animal diseases. 

Congress provided $500,000 in 2006, $750,000 in the 2007 budget bill, to implement a pilot program, but your fiscal year 2008 

budget still does not support this program. Now I’m hearing from 

veterinarians that your department has no plan to implement the 

rules and regulations for the law passed over 3 years ago to reverse 

the spiraling reduction in our first responders, i.e. large animal 

veterinarians. Your response to that? 

Secretary JOHANNS. You are right, there was $500,000 worth of 

funding in 2006. Here’s what it boiled down to. By national standards, in trying to pull off a national program, it wasn’t a huge 

amount of money, I think we would both agree. It turned out to be 

a rather complex program. It was a program that took some effort, 

if you will, to get together. 
71 

I will assure you, Senator, it’s not a program that we are opposed 

to, not at all. We see the need out there. Vets are educated and 

only a few of them decide to go with large animals versus the small 

animal practice. You see that in your State, we saw it in our State. 

Senator CRAIG. It’s where the money is. 

Secretary JOHANNS. Yes. Well, and you know, there’s just a certain difference in the kind of work that is performed, too. 

Senator CRAIG. Sure. 

Secretary JOHANNS. But we believe in the program. The only defense I can offer, and I don’t want to sound defensive because we 

do like the program, is it just turned out to be more complicated 

than what it would appear. 

Senator CRAIG. Then my question is, is there a process of rules 

and regulations that will be implemented? Is this program something that will come into function, or is it at idle? 

Secretary JOHANNS. We are moving ahead with the design and 

the implementation of the program, so the answer to your question 

is yes. 

Senator CRAIG. Thank you. Thank you, Mr. Chairman. 

Senator KOHL. Thank you very much. 

Senator Nelson. 

Senator NELSON. Thank you, Mr. Chairman. 

ADMINISTRATIVE EXPENSES FOR EARMARKS

Mr. Secretary, as you know, during recent months there has been 

a great deal of attention drawn to earmarks, and we can certainly 

agree that transparency, accountability, and disclosure is extremely 

important on this topic. With that in mind, and this is sort of—it’s 

a budget issue and question—can you tell me if 100 percent of the 

congressionally-directed earmarks that go through USDA are actually allocated to the congressionally-directed recipient? 

Put another way, does USDA take some money, a certain percent 

of the earmark, for its own administrative expenses in connection 

with the earmark, both related and unrelated to the earmark? And 

would you support greater transparency, so that Congress and the 

public are aware of exactly how USDA directs this money? And it 

may be something you want to refer to somebody else, but—— 

Secretary JOHANNS. I’ll have Scott Steele offer a thought on that. 

Mr. STEELE. Senator, yes, as I understand it, each of the agencies 

that pass through money through earmarks do take some administrative costs from that amount, and I think the percentages vary 

by agency. But yes, we think it should be transparent. I think that 

we do identify, and I’d have to check the records on this, and I can 

respond more for the record exactly what percentages agencies do 

take, but the Cooperative State Research, Education and Extension 

Service I know does take a certain percentage, and NRCS and the 

others do, but I think they do vary by agency. 

Senator NELSON. But what is the authority to do that? Because 

I’m not sure that there’s any mandated percentage that is part of 

the earmark, that directs the agency to be able to do this. And so 

is the amount determined within the agency? Why is that not included within the appropriations process for the agency’s budget, so 

it doesn’t become skimming? 
72 

Mr. STEELE. Well, I don’t know if it’s called skimming or not. I 

think it’s an issue of the cost of doing business. There are some administrative costs in dealing with implementing programs, and 

they can’t all be ignored. 

Senator NELSON. Well, why wouldn’t that be, without being argumentative, why wouldn’t that be in the budget process, in the appropriations process we approve here? 

Mr. STEELE. Well, the earmarks themselves, we have not requested earmarks in our budget request. We receive the earmarks 

from the Congress. So in our justification to the committees, we 

would not be justifying the earmark to the committee. 

We receive the money. In turn, we make use of it and follow the 

legislative intent, and I think in that process certain agencies have 

taken a percentage of the earmark for their administrative costs of 

tracking the expenditures and making sure that the work is carried 

out properly and there is some overhead costs that have to be covered in this process. 

Senator NELSON. But that’s not an agency expenditure that’s appropriated as part of the budgetary process. 

Secretary JOHANNS. No. I think what’s happening here, Senator, 

is this. Historically earmarks have not been included in the administration’s budget request. Even before the discussion really heated 

up on earmarks, you could go and look at past budget requests and 

we don’t include them, so therefore there would be no administrative costs to include. 

But, as Scott indicates—and you probably have the numbers in 

front of you but we would be happy to supply them to the committee, too—there is a certain cost in just administering the earmark that has been established, and so that administrative cost 

has been covered by some piece of that, and I’m not even aware 

how much, for the program itself. 

Senator NELSON. Well, some are 2.5 percent for expenses related 

to implementing the President’s Management Agenda; agency assessment of about 8 percent to pay for administrative support; program assessment, 2.5 percent to 9 percent, to support overall program direction. It means that the range could be from somewhere 

from 13 to 20.5 percent, or higher if the department charge is 

raised. 

It is something I think we need to look into as part of the appropriations process, so that we don’t end up with, in effect, off-budget, outside appropriation, taking of certain expenses to the agency 

for the process of doing that. Or at least it ought to be formalized 

in some uniform way, so that if an earmark is in fact directed to 

a certain agency, that you know in advance what it’s going to be, 

so it doesn’t erode the amount of the earmark that you’re expecting 

to go to the recipient. 

Secretary JOHANNS. We would be happy to work with you to find 

a very transparent approach, because I think the dilemma we find 

ourselves in is, we do have certain oversight responsibilities and so 

that’s how this is coming about. But again, we want to be transparent about it. If we’re doing something that you’d like to see different, we’re open to—— 
73 

Senator NELSON. As a matter of compliment, you were able to 

provide us some of this information when we requested it. Some 

other agencies told us it was none of our business. 

Secretary JOHANNS. No, we’re happy to provide it and happy to 

work through the issue. 

[The information follows:] 

ADMINISTRATIVE COSTS FOR EARMARKS

Several USDA agencies administer funds as a result of Congressional earmarks. 

The amount of administrative costs withheld from an earmark differs based on the 

nature of the earmarked funds and the agency administering the particular earmark. There are some specific statutory set-asides that all agencies within USDA 

are required by law to apply against programs, including from earmarks. For example, all funding related to extramural research and development is subject to a requirement to set aside 2.5 percent of funds to be used for the Small Business Innovation Research Program (Small Business Research and Development Enhancement 

Act of 1992, Public Law 102–564, as amended). In addition, all biotechnology research projects are required to set aside 2.0 percent of funds to support the Biotechnology Risk Assessment program (Section 1668 of the Food, Agriculture, Conservation, and Trade Act of 1990, Public Law 101–624, as amended). 

In addition to statutory set-asides, agencies also have authority to use a portion 

of the appropriated funds to pay for administrative costs. The portion of the appropriated funds used to pay for administration costs may differ for each agency and 

program. Specific examples include: 

—The Cooperative State Research, Education and Extension Service (CSREES) 

has specific statutory authority (Section 1469 of National Agricultural Research, 

Extension and Teaching Policy Act of 1977, Public Law 95–113, as amended) 

to retain up to 4 percent of amounts appropriated for research, extension and 

teaching programs for administration of these programs. 

—The Agricultural Research Service (ARS) assesses 10 percent of all appropriations to finance management costs associated with the conduct of their nationwide research programs. ARS does not have a separate budget line item to 

cover management support. 

—The Animal and Plant Health Inspection Service (APHIS) assesses a rate between 2.5 percent to 9 percent depending upon the program. APHIS, like ARS, 

does not have a separate budget line item to cover management support. 

Senator NELSON. My time has expired. Thank you, Mr. Chairman. Thank you, Mr. Secretary. 

Secretary JOHANNS. Yes. 

Senator KOHL. Thank you, Senator Nelson. Senator Reed, then 

Senator Feinstein, then Senator Specter. Senator Reed? 

Senator REED. Thank you very much, Mr. Chairman, and Mr. 

Secretary and gentlemen. 

PROVINCIAL RECONSTRUCTION TEAMS (PRTS)

I understand that this budget for the first time includes $12.5 

million to support USDA personnel in provincial reconstruction 

teams in both Afghanistan and Iraq. Is that correct, Mr. Secretary? 

Secretary JOHANNS. That is correct, yes. 

Senator REED. Any reason why this is the first time it’s been in 

the budget? I can tell you they are really high valued items over 

there. 

Secretary JOHANNS. Scott tells me that it was actually in last 

year’s budget at $5 million, so maybe what caught your attention 

is that it’s there this year at $12 million. The reason why it’s there 

is that we do have a presence. We think that presence is important. We think we can do some good things in those countries. 

In fact, in one of the farm bill proposals we made, we identify 

a place for this kind of activity, whether it’s Iraq or Afghanistan 
74 

or some other place. We have international expertise. We have offices in 75 foreign countries or 70 foreign countries. We are all over 

the world, and we think we can be very helpful. 

Senator REED. Well, Mr. Secretary, I second that. I’ve been out 

visiting these PRT teams numerous times and talking to military 

leaders. I was up in Tikrit with General Nixon of the 25th Infantry 

Division, and he said he could use many more USDA experts. 

Secretary JOHANNS. Yes. 

Senator REED. Will you be able to fill all the requirements that 

you’ve received with this money? 

Secretary JOHANNS. Yes, we believe we will. I can give you an 

update today, that we have staff in Iraq and we have had from the 

beginning. We have, on the PRTs I think we have six positions, five 

of which are already there, and I think the sixth one will be heading over there in April of this year. So this would fund what we’ve 

been asked to do. 

Senator REED. Are these contract personnel or employees? 

Secretary JOHANNS. No, they’re employees. 

Senator REED. There are some non-DOD agencies that are having difficulty getting personnel to go over, for a couple of reasons. 

One is, they don’t get all the benefits that DOD gets, but also 

there’s a fear that if they leave their job in the United States or 

elsewhere, that they will suffer in terms of promotion or their management will suffer in terms of losing a key person without replacement. 

How are you dealing with that? Say for example an expert from 

the Southeast of the United States goes overseas. Can you put a 

replacement in there, or does that agency or that unit have to get 

along without them? 

Secretary JOHANNS. I’ve never run into it, but I would tell you 

my personal approach would be that they not lose anything; that 

if they want to go over and do a period of time in Iraq, that is of 

real value, or Afghanistan, they should not be set back in their career pathway. But, like I said, I haven’t run into it, so I’m hoping 

that’s an indication that that has not been a problem. In fact, one 

of our personnel—he just refreshed my recollection—actually came 

back because they got a promotion, and so they came back to fill 

that promotion. 

Senator REED. Well, I think this is a key area, and it’s not just 

for the Department of Agriculture, it’s for all the agencies that are 

complementing our military efforts, and I would ask you to go back 

and look seriously about the incentives or disincentives, about the 

ability to fill all of the requested slots and the sufficient funding 

to do that. But I note this is some progress. It’s taken 4 years or 

so to finally gear up, but at least we’ve geared up. 

LOCALLY PRODUCED FOOD TO SCHOOLS

Let me change topics quickly. In Rhode Island there’s a number 

of organizations that are working with farmers in our State to 

bring locally produced food to schools, and I’m glad that one of the 

recent USDA farm bill proposals indicates support for fresh fruits 

and vegetables in schools. However, since the Farm-to-Cafeteria 

program was authorized in Section 122 of the 2004 child nutrition 

and WIC reauthorization, the program has received no funding in 
75 

the administration’s budget. Why is that the case, if we’re trying 

to get fresh food into the school cafeteria program? 

Secretary JOHANNS. Scott, do you know about past funding? 

Mr. STEELE. Senator, I think that there was a pilot for the 

schools in prior years that we did fund, and we’ve been trying to 

get local sponsors to work and continue those pilots. But I think 

that the farm bill proposal is going to accelerate our efforts in dealing with this question. 

Secretary JOHANNS. Our farm bill proposals, and I’ll turn to that, 

would dramatically boost our efforts here. We’re proposing $2.75 

billion—and these are all scored in a 10-year basis—$2.75 billion 

in funds to purchase fruits and vegetables for our food assistance 

programs, and an additional $500 million to increase the purchase 

of fruits and vegetables in our school meals program. So over $3 

billion will go into fruits and vegetables purchases in nutrition or 

school lunch. 

Senator REED. And just a final question because my time has expired, but there will be an emphasis on purchasing local produce 

from local farmers? 

Secretary JOHANNS. Absolutely. Wherever we can buy locally, we 

want to do that. And the other thing I would point out is that our 

proposals at least are for mandatory money, so again if Congress 

agrees with us, your fruit and vegetable producers, your specialty 

crop farmers, will see a pretty significant presence in the farm bill 

that they have never seen before. 

Senator REED. Thank you. Thank you, Mr. Chairman. 

Senator KOHL. Thank you, Senator Reed. 

Senator Feinstein. 

Senator FEINSTEIN. Thank you very much, Mr. Chairman. 

DHS AGRICULTURAL INSPECTIONS AT U.S. BORDERS

If I might, Mr. Secretary, why don’t we go to this question that 

I had about DHS taking over ag inspections at the border. Just 

from the California experience, there is some indication to me that 

this may not be the best way to go. Could you comment? 

Secretary JOHANNS. We have a cooperative effort that goes on 

here with Homeland Security, and the USDA is a part of that. We 

can give you some numbers of things that we have done together. 

I can tell you from the USDA standpoint it is our goal to work as 

seamlessly as we possibly can with DHS in the administration of 

this program, and our attitude is, if we have resources that might 

be helpful, we want to provide those resources and be of assistance. 

I think, Senator, part of what is maybe being experienced here, 

this was a change, and sometimes it just takes a while for the system to adjust to that change. Every time I go to California, and I’m 

there on a frequent basis, this issue does arise from the agricultural community, because they’re worried about pests coming in 

and that sort of thing. 

Senator FEINSTEIN. And they’re coming in. 

Secretary JOHANNS. Well, and from the USDA standpoint, I want 

you to know that we’re ready to do whatever we can to make the 

system work, and we’ll work as seamlessly as we possibly can to 

do that. 
76 

Senator FEINSTEIN. Well, I am told that fewer ag inspections are 

being done since the transfer. 

Secretary JOHANNS. I don’t have those numbers in front of me, 

but—— 

Senator FEINSTEIN. May I ask you to take a look at that? 

Secretary JOHANNS. I will. 

Senator FEINSTEIN. And get back to me, because California’s ag 

is so big and affects so many States, and the penalty that comes 

from having fruit fly and then you quarantine three counties, the 

penalty is enormous. The key has to be to keep contaminated fruit 

out. Right now there’s a problem with avocados coming in with a 

pest attached, and it’s not being caught. 

Secretary JOHANNS. I will be happy to dig into the numbers and 

we will provide you with that information. 

[The information follows:] 

AGRICULTURAL QUARANTINE INSPECTION 

[Inspection Data] 

Pathway United States California 

Fiscal Year 2002: 

Air Passengers arrivals .................................................................................................. 55,220,906 10,728,329 

Air Passengers inspected .............................................................................................. 10,521,155 1,560,235 

Cargo inspections/clearances ........................................................................................ 2,821,221 518,040 

Fiscal Year 2003: 

Air Passengers arrivals .................................................................................................. 56,690,220 10,584,656 

Air Passengers inspected .............................................................................................. 9,814,540 1,789,183 

Cargo inspections/clearances ........................................................................................ 3,208,140 544,973 

Fiscal Year 2004: 

Air Passengers arrivals .................................................................................................. 57,204,756 11,354,159 

Air Passengers inspected .............................................................................................. 11,757,977 1,551,359 

Cargo inspections/clearances ........................................................................................ 2,544,184 644,893 

Fiscal Year 2005: 

Air Passengers arrivals .................................................................................................. 66,254,784 12,538,889 

Air Passengers inspected .............................................................................................. 10,092,452 1,384,565 

Cargo inspections/clearances ........................................................................................ 2,316,903 724,088 

Fiscal Year 2006: 

Air Passengers arrivals .................................................................................................. 68,457,060 12,832,403 

Air Passengers inspected .............................................................................................. 8,523,178 1,437,212 

Cargo inspections/clearances ........................................................................................ 2,110,075 752,715 

One of the major benefits of transferring all port of entry inspections to one agency is a front line inspection for all types of contraband by one individual. As a result, the front line inspectors today are not solely agricultural, narcotics, or weapons 

inspectors, but rather they have been trained to detect any and all contraband. This 

system allows for an efficient use of resources without compromising protection. 

However, having the front line inspectors trained to detect multiple forms of contraband does not allow for a direct comparison with the inspection regime prior to the 

transfer. For example, all international air passengers must be cleared through the 

Department of Homeland Security’s Customs and Border Protection’s (CBP) primary 

inspection. They may be directed to undergo a secondary agricultural inspection for 

a variety of reasons. While the actual number of secondary agricultural inspections 

of air passengers has decreased since the transfer, the primary inspection now includes a much stronger agriculture component because APHIS provides basic agricultural training to all CBP inspectors. Additionally, CBP has a more sophisticated 

risk identification system and database that allows for more targeted inspections. 
77 

AGRICULTURAL QUARANTINE INSPECTION (AQI) FEES

Senator FEINSTEIN. All right, because don’t you have $133 million for administrative expenses? Is that for new ag inspectors, or 

is that something else? 

Secretary JOHANNS. Scott, do you know? 

Mr. STEELE. Senator, this is the Agricultural Quarantine Inspection fee program that we carry out. We collect these fees from airline passengers, and that money is collected and those fees do 

change periodically in terms of how much money we recover from 

them. Then some of that money is transferred over to DHS from 

the Department. At this point in time for the 2008 budget, it looks 

like we have estimated obligations in this program of about $482 

million, and about $299 million, almost $300 million, of that would 

be transferred to the Department of Homeland Security to carry 

out the inspections you’re talking about. 

Now, APHIS does keep some of those fees for their own internal 

use in helping DHS carry out its responsibility, but DHS is now in 

charge of the front line inspectors. They would be the one checking 

the baggage and those kinds of things. APHIS would be called in 

if there needed to be fumigation, training, and other things, sort 

of a secondary back-up role to the DHS people. Now, those DHS 

people, they were transferred from APHIS over to DHS. They originally worked for USDA, and they are now working for DHS, and 

they are being assigned and managed by DHS. 

NUMBER OF AQI INSPECTORS

Senator FEINSTEIN. How many of them are there? 

Secretary JOHANNS. I don’t have an exact number, of the total 

number of inspectors, but we can provide that for the record and 

tell you exactly who is doing what. 

Senator FEINSTEIN. Well, for the record, this is one Senator— 

Secretary JOHANNS. Yes, and how many are in California. 

Senator FEINSTEIN [continuing]. That doesn’t really like that 

transfer. I don’t think that inspections are well served by taking 

agricultural people and putting them under DHS, where the mission is totally different, and I don’t want to see my State suffer because of it, either. So I’m going to watch carefully, and I hope you 

will as well. 

Secretary JOHANNS. We will, and we’ll get you that information 

you have requested. 

[The information follows:] 

AGRICULTURAL QUARANTINE INSPECTION POSITIONS TRANSFERRED TO DHS 

In fiscal year 2002, the Animal and Health Inspection Service (APHIS) had 3,484 

Agricultural Quarantine Inspection (AQI) full time equivalents (FTEs). Of these 

FTEs, 2,515 were inspection personnel. 

In fiscal year 2003, APHIS transferred 2,655 positions (529 of those positions were 

in California with 75 vacant positions) to the Department of Homeland Security. Of 

these 2,655 positions, 2,407 were inspection positions (including Plant Protection 

and Quarantine Inspectors and Technicians). Of the inspection positions, 346 were 

vacant at the time of the transfer (accordingly, 2061 inspection personnel were 

transferred). Of the total 2,655 positions, 387 were vacant. 

In fiscal year 2007, DHS informs the Department that they have 2,188 agricultural specialist positions, including 130 vacancies. DHS also indicates that there are 

337 inspectors currently located in California. 
78 

E. COLI IN SPECIALTY CROPS

Senator FEINSTEIN. Thank you. Let me go to E. coli. The outbreak of E. coli that essentially came from California products, at 

least the spinach, I mean, 90 percent of the United States is fed 

with that spinach, and I note that the budget increases by $4 million food safety research, but you also discontinue the food safety 

project at the Albany station in California which specifically targets E. coli, and so my question is, why? 

Secretary JOHANNS. This is one of the things that I mentioned 

in my opening statement. We did a farm bill proposal on kind of 

a parallel track with the budget, but eventually these two have to 

marry together because in 2008 we have a new farm bill. 

When it comes to specialty crops, I think you’re going to like the 

proposals we have made. We are proposing not only that increase 

of additional fruit and vegetable purchases, which of course would 

be really good for California, but we’re also proposing to increase 

research in that area by $1 billion—and again, these numbers are 

all on a 10-year score—because one of the things that we heard 

from our specialty crop farmers was, we need assistance in this 

area of research and phytosanitary/sanitary issues. 

So we heard them, and again, never, I promise you, never in the 

history of farm bills have we had such a significant presence for 

specialty crop producers as what we are proposing. So if these proposals were to be adopted, there would be a major step forward for 

research in this area. It would be very significant. 

Senator FEINSTEIN. My time is up, Mr. Chairman, but if I might 

just say—and you don’t have to answer it, we can talk about this 

later—the time has perhaps come for some regulations from your 

department with respect to the phytosanitary handling of crops, to 

prevent this from happening again, instead of leaving it up to each 

State. 

Secretary JOHANNS. California has a very, very mature ag industry, as you know. They do good work. Some of their counties actually produce more agricultural products in value than some States. 

And so I guess what I would say to you is, we like what we’re seeing there. They really do seem to be aggressively addressing this 

issue. Any time you go to a national phenomenon, it becomes that. 

I mean, it tends to be uniform, one-size-fits-all. I really want to 

talk to you about that before maybe any of us reach some conclusions on that. 

I would also mention that APHIS does work with California, and 

the FDA, in this area. But again, I think this would really warrant 

some serious thought and discussion, and I would really want to 

consult with our producers across the country, especially in California. They do some good work, as you know. 

Senator FEINSTEIN. Thank you. Thank you, Mr. Secretary. Thank 

you, Mr. Chairman. 

Senator KOHL. Thank you, Senator Feinstein. 

Senator Specter. 

Senator SPECTER. Thank you, Mr. Chairman. 
79 

COMMODITY SUPPLEMENTAL FOOD PROGRAM (CSFP)

Mr. Secretary, I am concerned about the budget request which 

is $4 billion lower than the 2006–2007 level, and the termination 

of the Commodity Supplemental Food Program which provided 

some 6.4 million food packages to over 500,000 people in low income brackets, also seniors. I know that the projection is that the 

WIC program and food stamps will meet the needs, but that really 

isn’t applicable when the seniors are not included in those programs. 

So my question, how can your department really keep up with 

the demands for very important services, and have a budget cut 

and not have even an inflationary increase, and continue to provide 

important programs like the Commodity Supplemental Food Program? 

Secretary JOHANNS. Overall, our nutrition programs are fully 

funded—not only funded for what we have today but the anticipated need. They’re fully funded for the inflationary increase we 

anticipate, and they’re even fully funded in terms of a contingency 

amount of money for WIC and food stamps. So we believe that we 

will meet the needs that are out there, and if we don’t, if we have 

underestimated those, we have a contingency program that is 

available. 

Senator SPECTER. What is the contingency program? 

Secretary JOHANNS. It’s a large amount of money. Scott, how 

much? 

Mr. STEELE. Senator, yes, we have set aside additional money in 

a contingency fund if we would need to use it. It’s $3 billion for the 

Food Stamp Program. If our estimates are wrong on participation, 

we could then go to that contingency fund to make up the difference, the shortfall. 

In the WIC program it’s $200 million. If we miss the estimate 

that we have now for 8.3 million women, infants and children, we 

would be able to tap into that $200 million if our estimate is 

wrong. So we have asked for that additional amount of money in 

the budget request. 

Secretary JOHANNS. Here is the situation on CSFP, and it is a 

popular program. It’s certainly well received out there. Here is why 

it keeps popping up. The administrative costs get people’s attention. They are about 46 percent of the food that is purchased. It 

is not a nationwide program. It’s in 32 out of the 50 States, and 

I think we have it on some Indian reservations. 

And, again, we just believe—and we have monies in the budget 

for outreach—that if we can identify the people and move them to 

one of our other programs, it will work better for them. So that’s 

why it keeps popping up every year. 

Senator SPECTER. Mr. Secretary, let me thank Keith Collins, 

your chief economist, for substantial help he has given us in the 

past when we’ve had some tough milk issues in Pennsylvania. I recall one incident where he came to the State and was enormously 

helpful. 

I’m not going to be able to stay for Commissioner von 

Eschenbach’s testimony. I want to note with approval his confirmation. Good to see him on the job, past that hurdle. 
80 

And one question which I would like him to answer for the 

record. It involves the—I note an increase in user fees, $15.7 billion, on some of the drug review programs. We hear comments 

from time to time that the people who are awaiting those programs 

would be glad to increase their user fees if we could have more expeditious treatment. I’d like him to take a look at that question 

and give us a response in writing. 

Thank you very much, Mr. Chairman. 

Senator KOHL. Thank you, Senator Specter. 

Senator Harkin. 

Senator HARKIN. Well, thank you very much, Mr. Chairman. 

Thank you, Mr. Secretary, Mr. Deputy Secretary, and all of you 

who are here. I just had a couple of questions. 

ORGANIC FARMING

Again, we tried in the last farm bill, Mr. Secretary, to put in 

some funds and different programs to help organic farmers. There 

has always been this sort of ‘‘valley of death’’ as they call it, when 

a farmer wants to transition to become an organic. Well, you take 

3 years. You’ve got to have 3 years. Well, during those 3 years you 

can’t really say it’s organic, so how do you get through that sort 

of ‘‘valley of death’’ from being nonorganic to being organic? 

So we put funds in the bill and we put a couple of programs in 

there to help farmers do this. I see that the budget now zeros this 

out, zeros this out. Let’s see, where was it? Yes, we had $1.8 million, very small, in discretionary funds last year, and the budget 

would provide no funds at all. 

Now, we do have some money that we put in there, mandatory 

money. We do have some of the mandatory money in there, that’s 

true, but that’s sort of on research and stuff. But the transition 

funds—we do the research, and that money is there, Mr. Chairman, for research in organics and what farmers might do and how 

they set up marketing things and stuff like that. That’s that research, but the transition funds were extremely important, and 

they’re just zeroed out at a time when consumers can’t get enough 

organics. 

The fastest growing part of the food industry in America is 

organics, 20 percent a year. People at Whole Foods say they can’t 

get enough organics. They can’t even keep up with it. So people 

want it. The producers can’t keep up. It seems to me a great opportunity, and I just want to know what kind of justification there is, 

because I’m looking at the farm bill this year, and if nothing else, 

I’d like to actually beef that up and do more in that area, Mr. Secretary. 

Secretary JOHANNS. I was just looking at our proposals that we 

submitted to your Agriculture Committee, Mr. Chairman, relative 

to organic farming, and we’re doing a number of things here that 

I think would be helpful. I don’t pick up that proposal in what 

we’ve put here, though, I don’t think. 

So I guess what I would offer to you, I’d be anxious to sit down 

with you and see if there’s something we can do there, because 

you’re right, there is a period of time where you transition. We do 

have some money in this year’s budget, some mandatory funding, 
81 

as you point out, but in the next farm bill there’s probably an opportunity here to take a look at this issue again. 

Senator HARKIN. I’m open for any suggestions you’ve got on 

things where we can work together and how we focus on this. 

And the other thing that I heard, Mr. Secretary, was that we just 

had a meeting with some of these farmers in Iowa recently, sometime in January, I think it was, and the problem seems to be in 

terms of marketing, regional kinds of processing facilities and stuff, 

where a small farmer could take this in and get it processed and 

packaged and sent out, someplace like that, so I would like to visit 

with you about that. 

Secretary JOHANNS. Okay. 

DHS AQI INSPECTORS

Senator HARKIN. I am told that in my absence Senator Feinstein 

covered the problems with the inspectors coming in. I think we’ve 

got a real problem there, and we’re going to have to think about 

whether or not, Mr. Chairman, whether or not these inspectors 

ought to be brought back under USDA or should they stay under 

DHS. And quite frankly, everything I have heard is that they were 

doing their job under Ag, they had a good structure for it, and now 

they have been shifted and it’s sort of the tail end of everything 

out there under DHS. I just wonder if we shouldn’t somehow bring 

them back in under USDA. I assume you spoke about that in my 

absence. 

Secretary JOHANNS. Yes. Senator Feinstein has asked for some 

information on where were we on inspections before the change, 

where are we at now, and we’ll provide that. 

FOOD AID

Senator HARKIN. Okay. The last thing I just want to cover is food 

aid. Because of the continuing crisis in Africa and everywhere else, 

we have been obligated to provide additional emergency funding for 

Title II international food aid above and beyond the appropriated 

levels, and this goes back for the last several years. 

Again, the administration—we’re talking about a budget here, 

now—the administration has been unwilling to acknowledge that 

increased demand. They have not requested any funding above the 

recent level of $1.2 billion for Title II, and I’m wondering why, 

since we know we’re going to have to provide more, why there isn’t 

more of a budget thing and why there isn’t some justification in the 

budget for this food aid? It just makes it tough on us when it’s not 

in that budget. 

Now, if you don’t have the answer now, if you could submit it in 

writing, that would be fine with me. 

Secretary JOHANNS. Okay. We’ll submit it in writing. 

Senator HARKIN. That’s fine. Just look at that. 

Secretary JOHANNS. Okay. 

Senator HARKIN. Same level it has always been every year. We’ve 

got to come in and get more and more every year. And I think as 

you look around the world now, we’re going to be asked to do that 

again, so it should be part of the budget. 

Secretary JOHANNS. Okay. 

[The information follows:] 
82 

2008 BUDGET REQUEST FOR PUBLIC LAW 480 TITLE II DONATIONS

The 2008 budget requests just over $1.2 billion of appropriated funding for Public 

Law 480 Title II donations; this is a slight increase above the level provided in 2007. 

The requested funding will be supplemented by reimbursements from the Maritime 

Administration for prior year cargo preference costs, which are expected to total just 

over $120 million in 2008. 

The appropriations request reflects a careful prioritization among the competing 

demands for international humanitarian assistance. The United States has a number of different programs and authorities for responding to humanitarian needs 

overseas, each of which is important and makes a unique contribution to our humanitarian response efforts. 

In addition, it is important to understand that emergency food needs are difficult 

to predict in advance, especially given the complex nature of evolving, rapidly 

changing conflicts and the unpredictability of rainy seasons in drought-prone areas. 

However, should unanticipated and extraordinary emergencies arise during the 

course of the year, the Administration has a number of options for responding, including a supplemental appropriations request and a release of commodities from 

the Bill Emerson Humanitarian Trust. At present, the Trust holds 915,000 metric 

tons of wheat and $107 million of cash. The wheat tonnage equivalent of that cash 

is approximately 500,000 metric tons, so in total the Trust has resources equal to 

about 1.4 million metric tons of wheat. 

In view of these considerations, the Administration believes the 2008 budget continues our commitment to addressing the most severe and critical emergency food 

aid needs. 

Senator HARKIN. Thank you very much, Mr. Chairman. 

Senator KOHL. Thank you, Senator Harkin. 

Senator Nelson, do you want to make comments? 

Senator NELSON. Thank you, Mr. Chairman. 

CONTINGENCY FUNDING

One quick item: Mr. Chairman, I commend the contingency fund 

to deal with the challenges of food stamps and making sure that 

the numbers match with the requirements. I wonder if it’s possible 

to do a similar thing with mitigation funding, with a contingency 

fund. 

We know every year we’re going to have disasters that will relate 

to agriculture, whether it’s hurricanes or whether it’s continuing 

drought. In the past they’ve been offset typically from some program within the previous farm bill, 2002. I remember Nebraska 

being a beneficiary of that when you were Governor. It’s an ongoing 

situation. We don’t know where it’s going to happen, but we know 

that it will happen. 

Why aren’t we in a position to set aside a contingency? If we’re going to take $18 billion, roughly, out of the farm bill, why don’t 

we preserve some of that to deal with the fact that disasters will 

occur that are not going to be adequately covered by crop insurance? 

There isn’t any way an 8-year continuing drought can be covered 

by crop insurance. We went over that, I think, in the Senate Ag 

Committee, in talking about how we will balance that all out. But 

isn’t it possible to set aside $5 billion or $6 billion? If we can set 

aside $3 billion for food stamps, it would seem to me that we ought 

to be able to hedge our bet a bit on natural disasters for crop coverage. 

CROP INSURANCE GAP COVERAGE

Secretary JOHANNS. Here is the challenge you will face if you 

want to establish a fund and just have money in it, whatever that 
83 

amount would be. Keep in mind during the last farm bill, notwithstanding the attempts to pass recent disaster relief, we spent about 

$8 billion on disaster relief programs, and the current discussion 

is somewhere along the lines of $3 or $4 additional billion, so you 

could be up to around $12 billion. And you’re going to start with 

a baseline just like we did, and everything outside of that is above 

the baseline, and you know the drill on amounts above the baseline. 

Here is what I would offer to you, though. I do believe that this 

crop insurance approach is worth looking at. One of the big criticisms with crop insurance today is, you can’t cover the gap, so 

we’re proposing a gap coverage be made available to cover that 

typically 30 percent gap in coverage between 70 percent and 100 

percent. 

And then the second thing is the revenue-based countercyclical 

program just will work better. We can’t talk about the specific 

product, we’re forbidden, but there is some effort to look at this 

issue of ongoing disaster and its impact on crop insurance and—— 

Senator NELSON. Well, you just reach the base, so that ultimately you’re out of business unintentionally. 

Secretary JOHANNS. Exactly. Dr. Collins can give you a great 

briefing on that. But we’re looking at some of the very issues you’re 

talking about, and this actually might—I would respectfully suggest—be a better model than just the fund. 

Senator NELSON. Well, I would agree with you for the occasional 

loss. I don’t think that you can rely on crop insurance to cover a 

disaster that continues for 8 years. It’s not designed to do that. 

That’s like insuring your house and having it burn down every year 

for 8 years. The mechanism just doesn’t presuppose that in the actuarial computations. 

But statistically I’m sure Mr. Steele could calculate over the last 

20 years what, adjusted for current dollar value, what the crop 

losses have been that would be disaster occurrences, so that you 

could calculate highs and lows and treat it as, if you will, a contingency fund on an actuarial or statistical basis within the budget, 

and have it covered. 

Now, it’s true, sometimes it’s better to cover that 30 percent. I 

understand that difference. But I don’t think your crop insurance 

is going to work for a multiyear drought that goes on and on and 

on and on. For occasional losses, I think that’s the way to go for 

2 or 3 years, but not an 8- or 9-year loss as you know we’re experiencing in southwest Nebraska. 

Something for you to consider, and I hope that you will take a 

close look at it, and I hope as we put together the appropriations 

package, we can work in that direction. 

Secretary JOHANNS. Okay. We would be anxious to sit down with 

you, and we’ll consider your comments. 

Senator NELSON. Thank you. 

ADDITIONAL COMMITTEE QUESTIONS

Senator KOHL. Thank you very much, Senator Nelson. 

And we would like to thank you, Secretary Johanns, along with 

Mr. Conner, Mr. Steele, Mr. Collins. Your testimony and your re-
84 

sponse to our questions has been really good, and we look forward 

to continuing to work with you as the process unfolds. 

Secretary JOHANNS. Mr. Chairman, thank you. 

[The following questions were not asked at the hearing, but were 

submitted to the Department for response subsequent to the hearing:] 

QUESTIONS SUBMITTED BY SENATOR HERB KOHL

VEAL

Question. Mr. Secretary, I am very concerned that we have some serious trade distortions with Canada which disadvantage U.S. veal producers. 

Wisconsin veal producers believe that Canadian policies, particularly access to 

low-priced feed coupled with support from the Quebec production price insurance 

program, give their competitors in Canada an unfair economic advantage in the 

form of lower production cost which encourage over production. Some of the increased production is exported to the U.S. market where it is further processed and 

sold as U.S. produced product. The relatively low cost of production in Canada also 

encourages many Canadian producers to purchase replacement calves in the United 

States which drives up prices for U.S. producers. 

I would like the USDA’s Economic Research Service to review this topic and provide some updated data on this matter. I’m particularly interested in an updated 

comparison of subsidies which apply to U.S. veal producers and their counterparts 

in Canada. 

Answer. The information is submitted for the record. 

[The information follows:] 

In 2005 the cost of production for a milk- or formula-fed veal calf raised to about 

450 pounds in the United States was $682.50 versus a net cost of $699.97 in Canada, which includes a payment from the Canadian Agricultural Income Stabilization 

(CAIS) program. 

Exports of veal meat from Canada to the United States in the carcass, cuts-bonein, and cuts boneless categories (assumed to be available for further processing in 

the United States) have increased from 2000 to 2005. 

Carcass exports to the United States have risen rapidly due to increased slaughter capacity in Canada and restrictions on live animal trade as a result of BSE-related border measures. U.S. cattle export data to Canada do not provide breakouts 

by size so we cannot readily determine how many calves are really being shipped 

to Canada for veal. A category in USDA export statistics that includes these calves 

is Cattle not for Breeding which we show here for 2002 to 2006. 

Exports fell with the onset of BSE-related border measures, dropping from about 

133,500 animals in 2002 to a low of 14,200 in 2004 and rebounding slowly afterward. Exports reached 36,050 animals in 2006. Purchases of veal calves by Canadians make up some unknown share of these exports. 

Veal market data reports show the following calf slaughter numbers in Canada 

and the United States in recent years. 

Canada U.S. 

2003 ........................................................................................................................................ 251,309 971,459 

2004 ........................................................................................................................................ 284,334 838,405 

2005 ........................................................................................................................................ 267,900 717,338 

2006 ........................................................................................................................................ 245,341 698,618 

Question. I would also like to receive a summary of steps you have taken in conjunction with the U.S. Trade Representative to resolve this dispute. 

Answer. USDA, along with the Office of the United States Trade Representative 

(USTR), is aware of the concerns that have been identified and has examined Canadian Federal and provincial policies regarding support provided to Canadian veal 

producers. To date, USDA has not identified components of the Quebec Income Stabilization Program that are inconsistent with Canada’s international obligations but 

remains open to additional information and assessment. There are several recent 

factors that have changed the dynamics of the United States and Canadian veal and 

veal calf markets, including the imposition of U.S. BSE restrictions on Canadian 

cattle. USDA will continue to monitor the situation closely. If new information indicates that Canada is not fully meeting its international obligations, USDA and 

USTR will take prompt action to address the matter. 
85 

AFGHANISTAN/IRAQ PROVINCIAL RECONSTRUCTION ACTIVITIES

Question. Last August, we received notification from the U.S. Department of State 

that $7.8 million of the Iraq Relief and Reconstruction Fund was being transferred 

to USDA to restore and expand a sustainable agriculture sector in Iraq. Your request for 2008 includes $12.5 million for Provincial Reconstruction Teams to restore 

and stabilize the agricultural economies in Afghanistan and Iraq. 

Please tell us the amount of funds that USDA has used for these activities since 

the beginning of fiscal year 2006, including funds directly appropriated to USDA or 

transferred from other Departments. Also tell us what specific activities were carried out with these funds. 

Answer. Since the beginning of fiscal year 2006 through March 2007, USDA has 

expended approximately $3.39 million in Afghanistan ($2.45 million transferred 

from USAID, $140,000 from the CCC-funded Emerging Markets Program, and 

$800,000 from USDA appropriated funding) to support USDA participation in the 

Provincial Reconstruction Teams (PRTs); to provide technical assistance and capacity building to the Ministry of Agriculture; and to support development of agriculture and trade programs at institutions of higher education. This amount will 

grow as additional expenses are incurred during fiscal year 2007. 

Since the beginning of fiscal year 2006 through March 2007, USDA has used approximately $6.56 million in Iraq ($5.3 million transferred from the State Department to support revitalization of Iraqi agricultural extension programs; $260,000 

transferred from USAID to support USDA participation in the PRTs; and $1 million 

from USDA appropriated funding) to provide both agricultural advisors to the PRTs 

and Ministry of Agriculture, and public affairs specialist to work with the Iraq Reconstruction Management Office (IRMO). This amount will also increase as we move 

through fiscal year 2007. 

Question. What specific outcomes have been realized by the expenditure of these 

funds and are these consistent (and on schedule) with the original objectives of the 

allocations? 

Answer. With this funding, USDA has been an active participant in the ongoing 

reconstruction initiatives in both Afghanistan and Iraq. In the case of Afghanistan, 

USDA has been able to introduce modern agriculture production and marketing 

techniques to the rural provinces. Among other things, efforts have been focused on 

irrigation system rehabilitation, post-harvest loss reduction, marketing system improvements and livestock health. 

In Iraq, USDA’s Agricultural Extension Revitalization Program is on schedule to 

provide the first training of Iraqi extension agents in June 2007. In addition, USDA 

has deployed PRT and ministry advisors as well as public affairs specialists who are 

now embedded into the Iraqi and U.S. institutions to which they were assigned. Recruitment for additional advisors is ongoing. USDA is cooperating with other U.S. 

Government agencies to continue identifying appropriate assignments. 

The outcomes that have been achieved through these activities have been consistent with the purposes for which the funding was originally allocated. 

Question. How do you recruit people to take assignments in locations such as Iraq 

and Afghanistan, and how do you assure their security? 

Answer. The Foreign Agricultural Service coordinates the recruitment and selection of USDA agricultural advisors, drawing upon the expertise of the Department’s 

agencies such as the Natural Resources Conservation Service, the Animal and Plant 

Health Inspection Service, and the Agricultural Marketing Service, as well as the 

Land Grant Universities and 1890 colleges. A panel from USDA interviews and selects candidates, matching their technical skills, as well as their anticipated ability 

to operate in an insecure area, to skills needed in the PRTs. Recommendations are 

sent to the Secretary for final approval. 

Prior to deployment, all advisors attend a two-week security training program. 

Once deployed, each advisor is embedded with the U.S. military to ensure personal 

security. 

Question. In Afghanistan, there had been hopes that poppy production could be 

replaced with food crops that could help sustain their people. Yet we hear that 

poppy production there is still their leading crop and that the World Food Program 

considers that country in serious need of humanitarian food assistance. 

Explain what has been done to try and move Afghan farmers away from poppy 

production and why does it not seem to be working? 

Answer. USDA’s role in support of the Administration’s efforts to promote alternative livelihoods includes providing expertise to the Afghanistan Ministry of Agriculture to strengthen programs in agricultural extension, animal health, plant protection, and natural resources, and helps the Ministry extend its programs to all 
86 

provinces and districts of the country. USDA’s advisors on the PRTs work with their 

ministry counterparts to build capacity and develop programs at the local level. 

USDA helped to establish and continues to support the Afghan Conservation 

Corps which has employed thousands of Afghans in projects for reforestation, soil 

and water conservation, and conservation education. With local sales proceeds derived from the monetization of USDA food aid commodities, USDA has supported 

the renovation of agricultural and veterinary teaching facilities at Kabul University 

and the training of faculty. USDA also is working to build the capacity of five agricultural universities in Afghanistan, through faculty training, construction, and renovation of laboratories and classrooms. 

Finally, because livestock is vitally important to the Afghan economy, USDA is 

training Afghan veterinarians in the recognition, diagnosis, and control of animal 

diseases. 

CCE AND INFORMATION TECHNOLOGY

Question. Mr. Secretary, the budget for the Common Computing Environment is 

spread to the 3 agencies it serves this year—Rural Development, the Natural Resources Conservation Services, and Farm Service Agency. However, total funding for 

CCE decreases by nearly $30 million. 

It is not my understanding that information technology needs at USDA have decreased—in fact, at the Farm Service Agency—the opposite is true. We have all 

heard about the problems and delays at the county offices—when the East Coast 

is working, the West Coast can’t work, and vice versa, or FSA risks overloading the 

system. This is clearly unacceptable, and although the Farm Bill is scheduled to be 

reauthorized this year, which will obviously increase FSA’s workload, funding increases in their budget for IT will only maintain the antiquated system in place 

now. It’s like trying to stop a dam from bursting with duct tape. 

Why is the budget for CCE decreasing this year, when needs are certainly not? 

Answer. Funding for the CCE has been comprised of Service Center Agency (FSA, 

NRCS, RD) information technology (IT) purchases through their own appropriations, 

in addition to funding provided through the CCE direct appropriation. This funding 

has been used to develop an infrastructure to support the business delivery functions of the Service Center Agency (SCA) field offices located across the country. The 

2008 budget requests that $78.5 million with an additional $12 million for CCE activities specific to FSA be included in the SCA salaries and expenses appropriations 

to meet the ongoing business delivery needs. This funding will support the continued IT activities of the SCAs as they jointly maintain the CCE infrastructure. In 

addition, the SCAs will continue to work with the Information Technology Services 

(ITS) division of the Office of the Chief Information Officer in USDA. ITS is funded 

through reimbursable agreements with the SCAs and delivers staffing and services 

to the agencies in support of the CCE. In coordination with ITS, the agencies will 

be able to ensure that the necessary services and staffing are available to maintain 

the infrastructure and program delivery. 

Question. Does the USDA have a solid budget estimate of the cost to replace the 

current outdated FSA computer system? 

Answer. FSA is planning to implement a long-term modernization effort known 

as MIDAS to replace its obsolete equipment. At this time, FSA anticipates submitting a business case for this investment to the Office of Management and Budget 

during March 2007. Preliminary cost estimates indicate that this planned transition 

would require about $278 million over fiscal years 2007 through 2009. It would also 

have a total 10-year lifecycle cost of $463 million unadjusted for risk and an estimated cost of $617 million when adjusted for risk. 

In addition to this modernization effort, further costs must be incurred to stabilize 

the FSA IT system components at field offices in the short term. These additional 

costs are estimated to be about $150 million to bring the Kansas City web-based 

system up to at least moderate reliability; about $97 million to implement likely disaster assistance and Farm Bill legislation; and nearly $29 million to replace obsolete 

field office components. Thus, estimated total costs of nearly $553 million over fiscal 

years 2007 through 2010 will be required to bring the current system up reasonable 

operating capability and to transition to a modernized system. However, the actual 

modernization component as noted above is estimated to cost about $278 million. 

Question. Is this part of the Farm Bill proposals submitted? If not, where will this 

funding come from, since it is not in the President’s budget? 

Answer. Funding for modernization of FSA’s information technology systems is 

not included in the Administration’s Farm Bill proposal. USDA is working with the 

Office of Management and Budget to identify an appropriate funding source for this 

investment. 
87 

AGRICULTURAL RESEARCH

Question. Federal support for agricultural research is one of the most important 

contributions we make to support productivity for our farmers, ranchers, and all 

parts of our rural economy. A very good case can be made that this type of research 

is not getting the full support it needs in terms of funding, but the results have been 

impressive. 

What, if anything, is broke about the current agricultural research programs? If 

there is a need to combine agencies like ARS and CSREES, isn’t that just a matter 

of coordination? Isn’t that the role of the Under Secretary now? 

Answer. While current agricultural research programs are functioning well, they 

can be strengthened. Currently, both ARS and CSREES support basic and applied 

research spanning the full spectrum of agriculture related issues including plant 

and animal systems, food and nutrition, and natural resources. 

Our proposal will greatly facilitate closer collaboration by establishing a single 

National Program Staff (NPS) to manage programs and resources across all areas 

of research, both intramural and extramural, as well as extension and education. 

This will help ensure that resources will be maximized and that the comparative 

strengths of our intramural and extramural system are better utilized to address 

critical problems facing agriculture. 

While the Under Secretary has a role in coordinating programs between the REE 

agencies, it is important that this coordination be institutionalized. This can best 

be accomplished by merging the agencies. 

Question. Can you please give us your view on how Federal support for agricultural research should be administered? For example, what is the role of the State/ 

Federal partnerships that have worked so well over the past? 

Answer. Continued Federal support for agricultural research is critical to the future of American agriculture. It is important to maintain both strong intramural 

and extramural research programs. Central to USDA’s extramural efforts is the 

State/Federal partnership with the Land Grant Universities and other cooperators. 

These efforts should be maintained and strengthened. 

Question. Do you think that USDA should have its own in-house research agency? 

As you know, there are proposals under consideration that would remove agricultural research from the jurisdiction of USDA and place it with an independent agency. How do you feel about that? 

Answer. Agricultural research and education is a core mission of USDA and it is 

important to maintain a strong intramural research capacity. The Administration 

strongly supports keeping intramural research efforts within the jurisdiction of 

USDA and does not support moving these efforts into an independent agency. 

One of the Administration’s farm bill proposals would make significant changes 

to the Research, Education, and Economics mission area within USDA. Specifically, 

CSREES and ARS would be folded into one agency. The thrust of the argument for 

this change is that it will provide better coordination and allow for enhanced efficiency and effectiveness of program implementation and resource allocation. 

Question. How do you think we best meet the needs for long-term research that 

can be well served by long-term formula funds and competitive grants and the short 

term problem solving needs that can perhaps be best served by use of your special 

grant authorities? Do you think we need to maintain a balance to meet both these 

type of research needs? 

Answer. Our experience is that a mixed portfolio of formula funds and competitive 

grant programs allows us to address the needs of research for American agriculture. 

Our programs support the goals and objectives of USDA, and incorporate stakeholder input on a continuing basis. Formula funds ensure that each State has an 

immediate response capacity to address emerging issues and problems. When an 

issue arises, existing resources can be mobilized quickly to begin to deal with the 

problem. 

For those areas of longer-term concern, competitive programs are able to lay the 

scientific groundwork needed to address specific problems. Because these programs 

are designed at the Federal level, with stakeholder input, and take into account the 

needs of the entire nation, they apply available resources to America’s highest agricultural research priorities. In our experience, well developed and logically structured competitive programs take no longer and can be as responsive to solving 

science based issues as legislatively mandated special research grants. 

NATIONAL VETERINARY MEDICAL SERVICES ACT

Question. Please provide an update on the implementation of the National Veterinary Services Act. 
88 

Answer. We plan to publish a Final Rule delegating the National Veterinary Medical Services Act program to CSREES in the Federal Register on March 19, 2007. 

Although there are additional administrative steps that must be completed prior to 

the distribution of funds, a framework for the program has been developed by 

CSREES. The Department recognizes the importance of this Act to the veterinary 

community and those that they serve and is moving forward in the implementation 

of this program as quickly as possible. 

AVIAN FLU

Question. Secretary Johanns, as you are aware, we provided in the Joint Resolu- tion we recently passed more than $47 million to annualize funding provided in an 

fiscal year 2006 supplemental bill for avian flu activities in APHIS. Further increases are included in the budget, although we understand that this may change 

some based on passage of the joint resolution. Although it may seem that there was 

certainly a few months where we didn’t hear about too many avian flu outbreaks, 

very recently there has been a new outbreak in Britain, and we are headed into the 

spring, when the birds will be migrating and we know their migratory patterns 

must be monitored closely. I know that you are aware of the importance of staying 

ahead of this situation—this is evidenced by your budget request. 

What is the total amount within APHIS that will be spent on avian flu activities 

this year? What will this money buy? Answer. APHIS is planning to spend $107.7 million ($30 million in 2006 supplemental funding, $16.8 million carryover from Low Pathogenic Avian Influenza 

(LPAI), $47.2 million for highly pathogenic avian influenza (HPAI) appropriated 

funding and $13.7 million for LPAI appropriated funding) during fiscal year 2007. 

The use of these funds will increase surveillance in wildlife, domestic poultry, and 

game birds; increase and enhance existing preparedness; and provide capacity building for highly pathogenic avian influenza (HPAI) in the international community. 

Additionally, APHIS is increasing its interdiction activities to reduce the threat of 

an HPAI introduction through smuggling. 

Question. Can we expect more outbreaks of avian flu as we enter Spring? 

Answer. The United States has not experienced any introductions of the Asian 

strain of highly pathogenic avian influenza. APHIS is confident that the current 

surveillance activities in wildlife, domestic poultry, as well as smuggling interdictions provide an ample early warning solution that will enable Federal, State, and 

local resources to rapidly respond to an incursion of the virus, and thereby limit its 

potential for spread. 

EMERGING PESTS

Question. Secretary Johanns, I was pleased to see an increase of $20.5 million in 

the Emerging Plant Pests program for Emerald Ash Borer, bringing total funding 

to respond to this pest to more than $30 million. I was also pleased to see that a 

portion of this increase is going to support surveys in States where EAB is most 

likely to occur next, one of which is my home State of Wisconsin. USDA estimates, 

as you know, that if EAB is not contained and eradicated, it could cost State and 

local governments and landowners $7 billion over the next 25 years for tree removal 

and replacement. It has already devastated areas where it has shown up. 

Could you please speak to the efforts APHIS is undertaking to control and eradicate Emerald Ash Borer where it has been found? Also, please talk about the surveys the budget requests funding for in order to prevent the spread of EAB. What 

do you do if you find it in a new place? 

Answer. APHIS and USDA’s Forest Service have been cooperating with affected 

States since 2002 to address EAB. The program uses a management strategy with 

survey, regulatory, outreach, and control components designed to contain the general EAB infestation and find any isolated infestations and take appropriate action 

to contain or eradicate them. In December 2006, APHIS expanded its EAB quarantine regulations to cover the entire States of Illinois, Indiana, and Ohio, more 

than tripling the existing regulated area to prevent additional spread of EAB. 

Regulatory activities include monitoring high-risk businesses and ensuring that 

they move regulated articles only under compliance agreement with the EAB program as well as working to identify pathways for the potential movement of regulated articles and conducting special operations such as weigh station blitzes. The 

regulatory program also includes a strong outreach component to ensure that businesses and residents in quarantined areas are aware of the risk of moving items. 

Survey activities, including visual surveys and the use of detection trees, which 

are trees that have been stressed to release volatile chemicals attractive to the beetle, are used to detect the presence of EAB in new areas and delimit the extent of 
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known infestations. If the program detects EAB outside of the known infested areas, 

delimiting surveys are conducted to determine how old and how large the infestation is and what action would be appropriate. The only available eradication method 

requires the removal of all ash trees within a half-mile radius of a young infestation. Such activities take place only at small, truly isolated infestations. 

APHIS is also investing in methods development projects for EAB, including more 

accurate survey methods and control options. The fiscal year 2008 Budget also requests funds to expand survey efforts into States near currently infested areas, including Wisconsin, Minnesota, Iowa, Missouri, Kentucky, Tennessee, West Virginia, 

Virginia, Pennsylvania, and New York. These States have risk factors based on the 

movement of EAB host materials. 

Question. How does APHIS work to prevent things such as Emerald Ash Borers 

(EAB) and the Asian Longhorn Beetles from entering the United States? What improvements need to be made at the borders to prevent these incredibly expensive 

pests from entering and causing these problems? 

Answer. The Agriculture Quarantine and Inspection program protects the United 

States from the risks associated with the introduction of invasive agricultural pests 

and diseases. APHIS and the Department of Homeland Security cooperate to carry 

out this program, and fund the programs through a combination of appropriations 

and user fees. The Pest Detection program supports APHIS’ goal of safeguarding 

U.S. agricultural and environmental resources by ensuring that new introductions 

of harmful plant pests and diseases are detected as soon as possible, before they 

cause significant damage. USDA is requesting a $15 million increase in the Pest Detection program for fiscal year 2008. 

Exotic wood boring and bark beetles such as EAB and Asian longhorned beetle 

(ALB) likely entered the United States through infested solid wood packing materials such as pallets, crates, and other materials used in international shipping. 

These materials are often reused and reshipped many times throughout the world. 

Many countries have recognized the need to deal with the pest risk. APHIS worked 

with its international counterparts to develop standards for safely moving solid 

wood packing materials and implemented regulations based on the developed standards. While APHIS and affected States are still dealing with the effects of EAB and 

ALB and several other exotic forest pests already in the United States, we believe 

that the new regulation of wood packaging materials should help prevent future infestations of this type. 

ERADICATION VERSUS MANAGEMENT

Question. At what point do you make a determination that the eradication of a 

disease isn’t possible, such as in the case of citrus canker? What are the next steps 

once that determination has been made. 

Answer. Although each pest or disease situation must be analyzed separately, 

there are several factors we consider when determining whether or not eradication 

is feasible. Among these are: the availability of adequate funding and active participation from Federal, State, and industry cooperators; weather and any other environmental constraints; the potential of the pest to do significant economic damage 

to agricultural or forest resources; the extent to which the pest or disease has 

spread; the availability of effective detection, diagnostic, and control technology; the 

availability of acceptable alternatives to eradication; public support for an eradication program; the disease’s public health significance; and the vectors associated 

with a disease (e.g., mosquitoes, ticks, etc.). 

Federal officials take all of these and other factors into consideration as they determine whether the eradication of a pest or disease is possible. If one or more of 

these factors change considerably during the course of an eradication effort, the 

planned course of action will be reevaluated. Prior to making any major decisions 

about discontinuing an eradication effort, Federal officials will consult with their 

State and industry cooperators, then update policies and regulations as appropriate. 

INVASIVE SPECIES

Question. Please provide a list of current plant and animal invasive species, 

ranked by their threat level. What is APHIS’ short and long-term plans to deal with 

these? 

Answer. The Administration has not ranked invasive species by threat level. 

Invasive species that APHIS addresses include, but are not limited to, the programs 

focused on cattle fever tick, Mediterranean fruit fly, emerald ash borer, potato cyst 

nematode, sudden oak death, citrus diseases, brucellosis, pseudorabies, and chronic 

wasting disease. APHIS addresses each of these threats as resources allow. 
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Over the long term, APHIS develops response plans for exotic pests and diseases 

that have the potential to cause significant economic or environmental damage and 

uses its safeguarding system, which involves prevention, detection, and management components, to protect U.S. agriculture. Under the Pest and Disease Exclusion 

mission area, APHIS works to prevent exotic pests such as cattle fever tick and 

Mediterranean fruit fly from entering the United States. These and other pests have 

direct pathways into the United States. APHIS takes action at U.S. borders or in 

other countries to mitigate the risks associated with them. 

Under the Monitoring and Surveillance mission area, APHIS conducts plant pest 

surveys, animal health surveillance, and other activities designed to detect exotic 

plant pests and foreign animal diseases if they are present so that we can deal with 

them quickly if needed. These programs target a changing list of high-risk plant 

pests depending on trade and travel pattern and outbreaks in other countries. These 

programs also conduct intensive monitoring and emergency preparedness efforts. 

APHIS analysts follow animal and plant health situations around the world and frequently adjust monitoring and surveillance efforts and pest and disease exclusion 

priorities to safeguard U.S. agriculture and natural resources from high-risk pests 

and diseases. 

APHIS also works to control or eradicate high priority invasive species through 

programs in the Pest and Disease Management area, including, but not limited to, 

emerald ash borer, potato cyst nematode, sudden oak death, several citrus diseases, 

brucellosis, pseudorabies, and chronic wasting disease. 

CHRONIC WASTING DISEASE/STATE MATCH

Question. The budget request includes a decrease of over $6 million for activities 

related to chronic wasting disease. One of the justifications for this decrease is a 

match in which the Federal Government will pay for 60 percent of anticipated program needs, and the State will fund the rest. Similar proposals for State match are 

mentioned throughout the APHIS budget. 

Specifically for Chronic Wasting Disease, how will the requirements for the States 

change with this proposal? Will their funding level need to increase? 

Answer. The 2008 budget proposes a reduction of about $4 million. The program 

requirements for the chronic wasting disease (CWD) herd certification program 

(HCP) will not change with the funding reduction. At the requested funding level, 

USDA anticipates the States and cooperators would contribute additional resources 

to support the efforts at current levels. 

Question. More broadly, what amount does APHIS anticipate saving by requiring 

increased State matches for APHIS activities? Is there currently a mandated match 

level for States, or is this an entirely new proposal? If a State can’t or does not provide the requested match amount, what will APHIS do then? 

Answer. The following table is provided for the record. 

[The information follows:] 

Line Item Savings 

Chronic Wasting Disease ..................................................................................................................................... $4,400 

Emerging Plant Pests—Citrus Health Response Program (Florida) ................................................................... 2,300 

Emerging Plant Pests—Asian Longhorned Beetle (NJ & NY) ............................................................................. 1,691 

Emerging Plant Pests—Glassy-Winged Sharp Shooter (California) ................................................................... 1,001 

Johne’s Disease .................................................................................................................................................... 5,005 

Noxious Weeds ...................................................................................................................................................... 300 

Total ........................................................................................................................................................ 14,697 

There is currently no mandated match level for States, nor is USDA proposing 

a mandated level. It is our goal to leverage increased participation from the States 

to maximize the benefits received from Federal dollars. 

If a State is unable to contribute the estimated amount for a particular program, 

USDA will evaluate the overall impact to program efforts and adjust future funding 

requests accordingly. 

JOHNE’S DISEASE

Question. Mr. Secretary, the APHIS budget for Johne’s disease includes a decrease 

of nearly $10 million approximately 75 percent. One of the reasons for this justification is the supposition that States, universities, and producers, would be responsible 

for testing, herd clean-up, risk assessments and disease management, as well as the 

continuation of the national Johne’s demonstration herd project. 
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Was there any input gathered from those whose responsibilities will be increased 

before this proposal was put forth? Are these activities that the States, etc. are currently undertaking, or would have to pick up? 

Answer. USDA has consulted with our partners in the Voluntary Bovine Johne’s 

Disease Control Program (VBJDCP), and they are aware of our request. From its 

inception, the VBJDCP has been a cooperative effort among APHIS, State departments of agriculture, and industry. States have been the main driving force of the 

VBJDCP. A large part of the Johne’s disease funds not requested in the President’s 

Budget has been used by the States to pay for producer testing and risk assessment 

fees. With a reduction in Federal funding, these costs will need to be covered by 

producers who benefit from this program. In addition, State and University partners 

would assume responsibility for continuation of the Johne’s disease demonstration 

herd projects implemented in each region. These projects focus on new and current 

testing schemes and control methods to determine the most effective cost management practice options. 

APHIS will continue to provide oversight to the VBJDCP and support analysis of 

the national demonstration projects, along with continuing laboratory approval and 

licensing diagnostic tests and vaccines for commercial use. 

NATIONAL ANIMAL IDENTIFICATION SYSTEM

Question. What is the status of the development of a National Animal Identification System? 

Answer. The National Animal Identification System is composed of three components: premises registration, animal identification, and animal tracing. Premises 

registration is the foundation of the program. As of March 12, 2007, all 50 States, 

60 Tribes, and 2 U.S. Territories are capable of registering premises according to 

USDA standards, and approximately 378,000 locations have been registered. 

Significant progress has also been made on the second component of NAIS, animal 

identification. As of March 12, 2007, approximately 1 million Animal Identification 

Number devices have been distributed. 

The third component of the NAIS, animal tracing, is currently under development 

with the help of USDA’s industry and State partners. Industry, through private systems, and States will manage the animal tracing databases that maintain the movement records of animals. Full deployment of the Animal Trace Processing System 

is planned for the near future. 

Question. If such an animal identification system is made voluntary, what effect 

does APHIS anticipate that will have on participation? What efforts will be made 

to encourage participation? 

Answer. Participation in the NAIS is voluntary. The USDA remains committed 

to building upon our strong partnership with the States and industry to meet producers’ needs and establish a versatile system that makes sense for everyone. 

Moving forward with this voluntary approach has allowed producers the opportunity to test the program and recommend the most practical solutions for a more 

effective system. In this sense, producers themselves are playing an active role in 

helping to shape the NAIS program so that it works well for their particular needs. 

Additionally, a voluntary NAIS allows for the best price competition between service 

providers (identification device manufacturers, database providers, etc.) and leaves 

room for market applications (such as age/source/process verification) to help drive 

the system. 

To encourage participation, USDA has provided funding to facilitate development 

and implementation of an efficient system, and flexibility to adapt to producers’ operations and needs. On February 2, 2007, USDA published a request for proposals 

from nonprofit organizations that wish to enter into cooperative agreements with 

USDA to advance premises registration. USDA will make up to $6 million available, 

subject to the availability of funding, for the cooperative agreements. These cooperative agreements will support the efforts of such organizations to promote the NAIS 

and, specifically, increase participation in premises registration—the foundation of 

the program. 

SMALL FARM/ORGANICS/AMS SEED MISLABELING

Question. We continue to hear reports that the number of farmers in the United 

States is getting smaller and the farms are getting larger. Still, we have a responsibility to promote programs and policies to help small and beginning farmers be productive and able to maintain a reasonable life style. After all, these small independent farmers are truly small business entrepreneurs who need the government 

to be their friend, not their obstacle. I fear that in too many cases, government is 

their obstacle. 
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Last year I asked you a question about how USDA can help these small farmers. 

What have you done since then to improve their opportunities? 

Answer. Through a number of different programs, USDA helps operators of small 

and medium-size farms. For example, the Farm Service Agency (FSA) provides a variety of farm loan programs, including traditional operating loans, beginning farmer 

and youth programs. The Agricultural Marketing Service (AMS) helps small producers obtain greater access to marketing channels and engage in more profitable 

farm marketing activities through research, alternative market development, and 

grant programs. Additional information will be provided for the record. 

[The information follows:] 

FSA offers direct and guaranteed farm ownership and operating loans to familysize farmers and ranchers who cannot obtain commercial credit from a bank, Farm 

Credit System institution, or other lender. Borrowers include beginning farmers who 

do not qualify for conventional loans because they have insufficient financial resources, as well as established farmers who have suffered financial setbacks from 

natural disasters, or whose resources are too limited to maintain profitable farming 

operations. FSA loans can be used to purchase land, livestock, equipment, feed, 

seed, and supplies; they can also be used for building construction and improvements. FSA guaranteed loans provide conventional agricultural lenders with up to 

a 95 percent guarantee of the principal loan amount. The lender is responsible for 

servicing a borrower’s account, including the collection of payments, for the life of 

the loan. All loans must meet certain qualifying criteria to be eligible for guarantees. Farmers interested in these loans must apply to a conventional lender, which 

then arranges for the FSA guarantee. 

AMS conducts or supports applied research to help small and medium-sized farm 

producers and processors make better informed business decisions in the face of 

changing marketing conditions and practices; maintains a centralized information 

clearinghouse of agricultural marketing research materials and resources on the 

agency’s website and disseminates research results, technical assistance, and data 

via internet, publications, conference presentations, and outreach efforts; administers the Farmers Market Promotion and Federal-State Marketing Improvement 

grant programs; and collaborates with other agencies that support small farm marketing, including State departments of agriculture, land-grant universities, Tribal 

governments, trade associations, non-profit organizations and private foundations. 

During fiscal year 2006 and early 2007 AMS supported four national and four regional farmers market and direct marketing workshops, and AMS personnel presented or trained at nineteen conferences and meetings that support small farms, 

farmers markets, and agricultural community outreach to improve food marketing 

practices among small-scale and socially disadvantaged farmers, and expand awareness of available marketing services and resources. Further, AMS created a regularly updated Farmers Market Resource Guide in March 2006 that provides a onestop information source about available financial and technical assistance for farmers market and direct farm marketing activities. 

AMS also provides specific funding assistance. AMS awarded $1 million through 

20 Farmers Market Promotion Program (FMPP) grants for 2006. Agricultural cooperatives; local and Tribal governments; non-profit, public benefit and economic development corporations; and regional farmers’ market authorities are eligible for 

FMPP grants. The Federal-State Marketing Improvement Program (FSMIP) funded 

27 competitive matching grants worth $1.334 million to State Departments of Agriculture and other appropriate State agencies to assist in exploring new market opportunities for U.S. food and agricultural products and to encourage research and 

innovation aimed at improving the efficiency and performance of the U.S. marketing 

system. The majority of FSMIP projects are geared toward small to medium sized 

producers. In addition, the Specialty Crop Block Grant Program makes funds available to State departments of agriculture to enhance the competitiveness of specialty 

crops. It has made $6.58 million available to 50 States (and to Puerto Rico and the 

District of Columbia). 

Question. When we see problems like the mis-labeling of GM grain that gets into 

the market place, that sends a very troubling message to our trade partners and 

can create problems that small operators can’t absorb. 

We have heard several reports of genetically modified material getting into crops 

intended for commercial sales, the most well-known being rice. What has the economic effect been of instances such as this? 

Answer. The economic effect can be reductions in seed available for planting and 

potential trade restrictions. For example, two popular long grain rice varieties can 

no longer be planted for commercial production due to the presence of genetically 

modified material. The value of certified seed of these varieties produced in 2006 

for planting in 2007 is estimated to be $39 million. 
93 

Question. What programs does USDA have in place to make sure those sort of 

labeling problems don’t happen? 

Answer. The Agricultural Marketing Service administers the interstate labeling 

provisions of the Federal Seed Act, a truth-in-labeling law that regulates the interstate shipment of agricultural and vegetable seeds. Enforcement of the Act by AMS 

helps ensure that seed purchased by small independent farmers is of high quality 

and truthfully labeled. However, the Act does not regulate biotechnology traits or 

biotechnologically derived seeds. Instead, the Act considers biotechnology derived 

seeds found in traditional varieties as ‘‘other’’ crop seeds and they have to be labeled 

as such. If the biotechnology derived seeds exceed 5 percent, they have to be listed 

as a separate component on the seed label. 

Question. As you know, the organics label is a very important label, what are you 

doing to protect the integrity of that label? 

Answer. USDA’s National Organic Program (NOP) is responsible for administering the organic regulations and ensuring that all requirements are met to protect the integrity of the organic label. The 2008 budget includes an increase of about 

$1 million above the 2007 level of $2 million to ensure that the NOP can meet the 

needs of the rapidly growing organic industry. The increase will support, among 

other efforts, development of standards requested by the industry and regulatory enforcement to maintain labeling credibility. To ensure compliance with the regulations, the NOP directly oversees its accredited certifying agents to monitor organic 

producers and processors, conducts retail surveillance, conducts investigations, 

takes action on complaints, and imposes penalties where appropriate. 

GENETICALLY MODIFIED MATERIALS IN COMMERCIAL CROPS

Question. How is AMS, and USDA overall, working to prevent the introduction 

of genetically modified materials into crops intended for commercial sales? 

Answer. The Animal and Plant Health Inspection Service (APHIS) is involved in 

regulation of the biotechnology industry. Various measures are used in authorized 

field tests to ensure that genetically engineered organisms are confined to the test 

site. The measures include isolation distances to mitigate cross pollination with 

other crops and weedy relatives, cleaning of farm equipment to mitigate the inadvertent spread of seed, timely disposition of the field test, and post-harvest monitoring for volunteers. To ensure compliance, inspections of the test site, facilities, 

and records are conducted. Once a crop is deregulated, that crop is considered no 

different than conventional crops and may be planted without restrictions from 

APHIS. 

For organic products, regulations of AMS’ National Organic Program prohibit the 

use of genetically modified organisms in organic production. Accredited certifying 

agents review organic production and handling plans before certified organic production begins to ensure that no genetically modified organisms are used in production 

and that handling procedures protect organic products from contact with genetically 

engineered materials. Penalties are in place for intentional disregard of the regulations. 

COUNTRY OF ORIGIN LABELING (COOL)

Question. Please provide an update on plans to implement COOL. 

Answer. AMS has entered into cooperative agreements with 14 States for the purpose of conducting audits of retail establishments to enforce the COOL regulations 

for fish and shellfish. Audits in States without cooperative agreements were conducted by USDA personnel. In fiscal year 2006 1,159 retail stores were audited; the 

number of audits in fiscal year 2007 will increase slightly. 

For the remaining covered commodities, AMS will issue proposed regulations for 

public comment and issue final regulatory actions to implement COOL by the statutorily established effective date. 

Question. If language was enacted that would move the current implementation 

date for COOL forward to sometime during fiscal year 2008, please explain what 

steps would be required to implement it on an accelerated schedule. What funds 

would be required to implement COOL during fiscal year 2008? 

Answer. To implement COOL for the remaining covered commodities on an accelerated schedule, it could be necessary for AMS to issue final regulatory actions without the benefit of a public comment process. 

Given the current implementation date, AMS will not need additional funding in 

fiscal year 2008. To include the additional commodities, the program needs to develop the necessary regulations. Once regulations are established, the program must 

expand retail and supplier enforcement through adequate Federal staffing and by 

establishing additional cooperative agreements with State agencies and U.S. terri-
94 

tories to conduct retail surveillance audits. The program would focus on training 

and educating Federal and State employees on their enforcement responsibilities; 

overseeing the uniform application of the requirements from the Federal level; conducting educational and outreach activities with interested parties; conducting routine surveillance and product trace-back audits throughout the supply chain to ensure proper labeling and enforcement; responding to formal complaints; and initiating enforcement actions against violators. Since expanding the current program 

to all commodities in the statute will constitute an increase in program activity, implementation will require an increase in funding. 

RISK MANAGEMENT AGENCY

Question. Is RMA developing any new products to serve regions of the country 

that currently have few, if any, options for risk management? If so, please explain 

them. 

Answer. The Risk Management Agency (RMA) has undertaken an evaluation of 

its product portfolio to identify gaps in availability, particularly with respect to underserved crops and/or regions. This evaluation found that, with few exceptions, 

crop insurance coverage is generally available for the most economically significant 

crops in the underserved regions. This result is consistent with the conclusions of 

a recent independent evaluation of RMA’s product portfolio. This suggests that RMA 

should place greater emphasis on improving currently available products to provide 

more effective risk management protection, and target efforts on the development 

of new products towards filling the few remaining gaps. RMA is currently conducting comprehensive evaluations of several crop programs to identify areas for improvement, particularly among underserved regions. 

In addition, RMA has implemented several new products, most notably Adjusted 

Gross Revenue (AGR), Adjusted Gross Revenue-Lite (AGR-Lite), and two Pasture, 

Rangeland and Forage (PRF) pilot programs. The AGR, AGR-Lite and PRF programs are particularly oriented to producers for whom traditional crop insurance 

products were either impractical, or did not provide effective risk management protection. In addition, over twenty pilot programs are currently active that pertain to 

specialty crops, including pilot programs for processing chili peppers, Hawaii Tropical Fruit, and Florida Fruit Trees. RMA also has ongoing development efforts for 

a revenue insurance product for certain specialty crops, as well as an umbrella 

weather-peril product that could provide effective coverage for certain crops with 

relatively limited market value. Additional risk management tools are developed 

through partnership agreements that impact underserved producers. These partnership agreements deal with a wide range of topics including the development and understanding of markets, pest and disease control, and water management. 

The Crop Insurance Board also accepts private sector submissions that allows persons to develop and submit for approval their own products targeted to specific risk 

management needs. 

GLOBAL WARMING

Question. USDA conservation programs provide a model for natural resources protection on a vast scale. Today, there is much discussion about the issue of global 

climate change. 

Please describe any current agricultural activities that may contribute to global 

climate change. 

Answer. Through a portfolio of beneficial conservation programs and energy conservation practices Producers have opportunities to save money and time while reducing greenhouse gas emissions. There are several agricultural and forestry production systems that can be implemented to reduce GHG emissions and increase 

carbon storage, called sequestration, in soils and vegetation. Many conservation 

practices used by agricultural producers can mitigate negative effects attributed to 

climate change. One example of a specific practice is Conservation tillage. Residues 

and tillage can be managed to build organic matter and to sequester carbon while 

also reducing energy requirements and soil erosion. Another example is Comprehensive Nutrient Management systems. These systems can capture methane for energy 

production while also reducing negative water quality impacts. 

Question. Please describe any changes in agricultural production or conservation 

practices that might better mitigate against the threat of global climate change. For 

example, what are the benefits of carbon sequestration as a means to reduce greenhouse gasses or other potential contributors to global warming? 

Answer. USDA is providing incentives and supporting voluntary actions by private landowners in targeting efficiency improvements through the USDA/Department of Energy (DOE)/Environmental Protection Agency (EPA) AgSTAR, as well as 
95 

many other programs. USDA has instituted new standards and is targeting specific 

incentives that encourage carbon sequestration and greenhouse gas (GHG) emission 

reduction efforts. USDA also is sponsoring improved monitoring and reporting 

guidelines for voluntary initiatives. USDA agencies and their partners are developing tools to estimate the amount of carbon stored and GHG emissions reduced at 

the field and producer level. Such tools will make it easier for producers to estimate 

carbon storage and GHG emissions reductions. 

The Agricultural Research Service conducts global climate change research under 

the Global Change National Program. This research focuses on four aspects of global 

change: Carbon Cycle and Carbon Storage; Trace Gases; Agricultural Ecosystem Impacts; and Changes in Weather and the Water Cycle at Farm, Ranch, and Regional 

Scales. These factors may significantly affect agricultural productivity and are not 

addressed specifically by other ARS National Programs. Recently, in response to 

concerns about global climate change, a strong interest has developed in determining how agricultural activities and practices can be used to store carbon, particularly in soil. A Federal multi-agency research initiative on the carbon cycle, the 

U.S. Global Change Research Program Carbon Cycle Initiative, is under development to address carbon cycle science. 

VALUE-ADDED GRANTS

Question. Funding has been provided for Value-Added Agricultural Product Market Development Grants since the Agricultural Risk Protection Act of 2000. Ample 

time has elapsed to evaluate the effectiveness of this program. 

Please describe the types of products that have been funded. 

Answer. A wide variety of projects are funded, including value added products 

made from meat, dairy products, grains, fruits and vegetables, oilseeds, and renewable energy sources. Grant funds totaling $150,000 were used as working capital for 

the start up phase of a new tilapia production facility where the fish will be raised 

and processed into fillets. Other types of products include wine, compost made from 

diary waste, wind energy, soy-flour, identity-preserved yogurt, dehydrated apple 

slices, and branded cuts of beef. 

Question. Are these products becoming marketable and sustainable? 

Answer. Information about the long-term sustainability became available early 

this year from a study that the University of Missouri has done. The study indicates 

that approximately 60 percent of the projects funded resulted in a marketable product. 

Question. What are the outcome measures that are being used to determine the 

success of this program? 

Answer. Several measures evaluating the program are in place, including the 

number of jobs created, the increase in producer revenue due to the project, the increase in customer base due to the project, and the sustainability of the business 

receiving the grant. 

Question. How many grants and how much funding has been provided to energyrelated projects? 

Answer. Since 2001, 155 grants have been made for energy-related projects, totaling $25.2 million. 

Question. How successful are these energy-related projects and how do you define 

success? 

Answer. We define the success of energy-related projects in the same way as for 

other project types—we consider any project that resulted in a marketable product 

to be successful. We estimate that approximately 48 percent of energy related 

projects resulted in a marketable product. This compares to 60 percent success in 

projects over all for the value added program. 

SINGLE FAMILY HOUSING LOAN PROGRAMS

Question. Mr. Secretary, the Budget terminates the direct single family housing 

loan program that has served very low and low income rural households well for 

over 40 years. The 2000 Census reveals that 7.8 million of the non-metropolitan 

population is poor, 5.5 million face housing cost overburden, and 1.6 million nonmetro housing units are either moderately or severely substandard. 

While the direct loan program is terminated, funding for the guaranteed loan program is given a concomitant increase. However, this increase comes with a 50 percent rise in the fee to participate. Average incomes of households in the guaranteed 

program are about twice as high as in the direct program, and this fee increase will 

force those incomes higher. 

The Administration proposes to submit legislation for subsidized guaranteed options, but no language has been provided and no funding is requested in 2008. 
96 

Given the large income differential between direct and guaranteed program participants, how will very low income households gain assistance for homeownership 

loans? 

Answer. We anticipate that many very-low income families will be able to participate in our guaranteed homeownership program. Currently about 30 percent of 

those families who have received guaranteed loans have very low and low incomes. 

Question. When does the Administration expect to send up legislation on subsidized guarantees? 

Answer. We anticipate the legislative package will be delivered soon. 

Question. The current direct program can provide mortgage interest rates as low 

as 1 percent for very low income households. How deeply subsidized do you expect 

the proposed guaranteed program to be? 

Answer. We are currently developing options to assist very low and lower income 

families through the subsidized guaranteed program. Our goal is to help more lower 

income families to achieve homeownership through a guaranteed loan originated 

and serviced by private sector lenders. Currently interest rate reduction provisions 

have not been developed. 

Question. Do you expect the guarantee fee increase to result in a deterioration in 

the credit quality of the guaranteed portfolio? 

Answer. No, all applicants will be required to meet current credit quality standards. The proposed fee increase, which can be financed as part of the loan, will only 

increase the average customer’s loan payment by about $7 per month. 

Question. How much do you expect the average income of guaranteed program 

participants to rise as a result of raising the fee? 

Answer. We do not expect to see an increase in the income of our guarantee program participants. 

OFFICE CONSOLIDATIONS

Question. Mr. Secretary, delivering a direct single family housing program is 

clearly much more labor intensive than a guaranteed program. In conjunction with 

refocusing housing lending from direct to guaranteed loans, Rural Development is 

proposing to reduce staff somewhat and consolidate its field office structure. 

What is the proposed magnitude of staff reductions, and extent of field office consolidations? 

Answer. Any office consolidations that may occur will be done so as recommended 

by each Rural Development State Director in order to accommodate a reduction of 

management levels in each State while recognizing population shifts, the need to 

improve delivery systems in order to deliver all programs in all locations and to accommodate enhancements in technology enabling us to do business in new ways. 

Since the State plans are currently being reviewed, we do not know the number 

of offices to be closed or that will operate on a part-time basis. RD will keep the 

Committee informed of its plans. It is RD’s intent that the realignment be completed 

by March, 2008. 

Rural Development operated with 6,475 FTE’s in fiscal year 2006, and expects to 

operate with 6,300 FTE’s in fiscal year 2007. Rural Development is not proposing 

a Reduction-in-Force and all employees will be offered a position at their current 

grade and pay level. We are also seeking Voluntary Early Retirement Authority 

which could be of interest to those employees who are several years short of being 

eligible for regular retirement. 

COMMUNITY FACILITIES GRANTS

Question. Rural Development’s Community Facilities program includes direct 

loans, guaranteed loans, and grants to support essential community facilities in 

poor, remote rural communities. Through this program communities can finance 

rural hospitals, health clinics, day care centers, libraries, town halls, fire trucks and 

other first responder vehicles and equipment, and a myriad of other essential community facilities. This has been one of the most successful programs in Rural Development’s portfolio. 

Budget authority may be transferred among the loan and grant programs. However, this Budget appears to eliminate the grant program, leaving only direct and 

guaranteed loans to meet needs of small rural communities. 

What is the back-log of applications and pre-applications for loans and grants? 

Answer. As of March 13, 2007, there were 667 applications and pre-applications 

totaling $955,581,290 for the Community Facilities direct loan program, 48 applications and pre-applications totaling $176,316,844 for the guaranteed loan program, 

and 757 applications and pre-applications totaling $62,511,425 for the grant program. 
97 

Question. Will the aggregate requested program level be adequate for the fiscal 

year 2008 demand? 

Answer. The aggregated requested program level will be adequate to meet our 

highest priorities in fiscal year 2008. 

Question. How will small, low income communities, who in the past relied on 

grant assistance, finance the community infrastructure they need? 

Answer. There are a number of Federal community development programs and 

State and local economic development agencies designed to serve low-income and 

rural communities. A recent GAO report highlighted 73 Federal agencies which 

serve the purpose of economic development, with several of these specifically supporting the construction of facilities in low-income rural communities. 

Question. Has Rural Development estimated the impacts of this proposal on communities by size, region and income level? What are the results of that study? 

Answer. No, RD has not estimated the impacts by size, region and income level. 

However, as there are other Federal agencies providing grant funding for low-income rural communities, the impacts of the proposal will be ameliorated. 

MUTUAL AND SELF-HELP HOUSING

Question. The Self Help Housing Program has been hugely successful in assisting 

very low income households become successful homeowners. With technical assistance provided by grantees, program participants jointly contribute sweat equity as 

they construct their new homes. Long term financing has been provided by the Sec. 

502 direct program. However, this Budget terminates the direct program, terminates the Sec. 523 Self-Help Land Development loan program, and reduces SelfHelp grants by 72 percent. 

In the face of the success and long term support for the Self-Help program, why 

is the Administration taking this action at this time? 

Answer. Increasing cost in other Rural Housing Programs and fiscal year 2008 

budget constraints require program reductions. Rural residents participating in the 

Self Help Housing program are encouraged to seek financing using the Section 502 

guaranteed program or obtain financing from the private sector. 

Question. What are the private sector funding sources that will replace this program, and provide homeownership opportunities for these very low income households? 

Answer. Most Self-Help Housing grantees have been successful in securing other 

financial assistance to operate their programs. We anticipate that grantees can seek 

further funds from outside sources and use the Habitat for Humanity model which 

does not rely upon Federal financing. 

RURAL RENTAL HOUSING

Question. Mr. Secretary, this Budget again proposes to terminate direct rural 

rental housing loans (Sec. 515), to rely solely on the Sec. 538 guaranteed loan program for affordable rural rental housing construction. The direct program provides 

subsidized mortgage loans and allows the opportunity for rental assistance for very 

low income tenants. Subsidized financing, coupled with rental assistance that caps 

certain tenants’ rent payments at 30 percent of income, allows the program to serve 

tenants with mean incomes under $10,000. 

The bulk of Sec. 515 tenants are very low income, with a majority female headed 

households, elderly and/or handicapped. Without the Sec. 515 program, what will 

be the source of new affordable rental housing for these, most vulnerable, rural residents? 

Answer. Section 538 guaranteed multi family rural rental housing program has 

experienced great success and will be the primary source of multi family units without Section 515 funding. 

Question. Rental assistance is not available in Sec. 538 projects. Without rental 

assistance, how can the Sec. 538 program reach the very low income rural population now being served? 

Answer. The section 538 program reaches very low income rural population in two 

ways. Leveraged tax credit financing is present in nearly 80 percent of section 538 

projects. Nearly 7,000 units currently enjoy tax credits. Additionally, savings incurred from interest credit subsidies are passed on to the tenants through lower required rent payments. 

Question. Are there areas of the country where the Sec. 515 program, even without new rental assistance, could reach very low income households that would not 

be served through the Sec. 538 program? 

Answer. The section 538 program can provide rents that are comparable to the 

rents created by the section 515 program without rental assistance. This is because 
98 

the section 538 is eligible to be combined with 9 percent tax credits, as well as other 

affordable funding sources. The 538 program also offers an interest credit which 

buys down the interest rate of up to $1.5 million of the lender’s loan to the Applicable Federal Rate for the entire term of the loan and loan amortizations of up to 40 

years. These factors all aid in the creation of units with affordable rents. 

MULTI-FAMILY HOUSING REVITALIZATION

Question. Mr. Secretary, Rural Development has a direct loan portfolio reflecting 

over 17,000 properties, containing over 460,000 affordable rental units. Many of 

these properties are in excess of 20 years old, in need of substantial repair and rehabilitation. A recent study indicated that the portfolio could be segmented into three 

components: 10 percent are in growing markets in which it is economically feasible 

for owners to prepay, leave the program, and raise rents; 10 percent are in declining 

markets where the costs of maintaining the properties exceed the foreseeable benefits and need; and the 80 percent balance of the portfolio that is appropriate for revitalization and retention in the affordable housing program. Last year the Administration proposed revitalization legislation, including restructuring tools such as interest rate reductions, loan deferrals, reamortizations, subordination, debt forgiveness, etc. Funds were provided in fiscal year 2006 for a demonstration revitalization 

program for rural rental housing properties. 

Please provide a summary of actions taken under the fiscal year 2006 revitalization demonstration program. 

Answer. Last year we were able to approve and obligate funding to revitalize 78 

properties with over 2,300 apartment units in 16 States, using $8.9 million in budget authority provided to the demonstration program. 

Question. How much of the funds were utilized and in what manner? 

Answer. We were able to obligate the following program level amounts: $48 million in debt deferral, $4.5 million in soft ‘‘bullet’’ (any loan that requires a generous 

repayment term usually at the end of the life of the loan and it is anticipated that 

the loan will be refinanced) loans, $.28 million in zero percent loans and $.21 million 

in grants. 

Question. What is the status of a demonstration for fiscal year 2007? 

Answer. With a similar level of budget authority this year, we anticipate that the 

funding NOFA will be released during the month of April. Our key demonstration 

goals this year are to fund revitalization transactions in every State, fund an increased number of portfolio level transactions and increase the use of leveraged 

funds. 

Question. What is the status of the Administration’s revitalization legislation proposal? 

Answer. Our legislative proposal is currently in the final stages of review. We expect to transmit it to Congress shortly. 

Question. What were the lessons learned under the fiscal year 2006 demonstration 

and have you revised the legislative proposal accordingly? 

Answer. We found last year that by using debt deferral and carefully underwriting revitalization transactions, we were able to approve transactions with very 

limited rent increases. We also found last year that applications were received from 

approximately 4,100 properties or a quarter of the Section 515 properties in our 

portfolio. The large number of applicants reflects the clear need to have new cost 

effective revitalization tools to help preserve this valuable portfolio. 

MULTI-FAMILY HOUSING VOUCHERS

Question. In the face of loan prepayment demands by multi-family housing property owners, raising the specter of increased rents for very low income rural tenants, 

$16 million was provided in fiscal year 2006 for rental housing vouchers. 

How many properties, containing how many units, prepaid in fiscal year 2006? 

Answer. In fiscal year 2006, owners of 151 properties containing 2,330 units went 

through the Rural Development prepayment process. In addition, 58 properties containing about 1,000 units completed the foreclosure process. This was a total of 209 

properties containing 3,330 units. 

Question. How many properties and units do you expect to prepay in fiscal year 

2007 and in fiscal year 2008? 

Answer. We are currently forecasting a total of 225 properties containing about 

3,600 units to prepay or complete foreclosure proceedings in fiscal year 2007. We 

are currently forecasting a total of 275 properties containing about 4,400 units to 

prepay or complete foreclosure proceedings in fiscal year 2008. 

Question. How many vouchers, using how much of the funds, were obligated in 

fiscal year 2006? 
99 

Answer. In fiscal year 2006, we offered vouchers to all tenants in properties where 

the mortgage was prepaid after September 30, 2005. The first voucher was issued 

in April, 2006. Three hundred and eight one-year vouchers were obligated for a total 

of $601,000 which represents 12 months of payment. 

Question. What are your forecasts for voucher utilization in fiscal year 2007 and 

fiscal year 2008? 

Answer. In the first 6 months of fiscal year 2007, approximately 600 vouchers were obligated for a total of $1.5 million. We are estimating to obligate a total of 

1,800 vouchers this fiscal year and we estimate obligating about 2,200 vouchers in 

fiscal year 2008. Our experience, somewhat limited at this point, is that about half 

of a property’s tenants accept the offer of a voucher, and of those about half utilize 

the voucher. The majority of the tenants utilize the voucher in the property where 

they were living at the time of prepayment or foreclosure, although the voucher can 

be used in any property where the owner will accept it. 

RURAL BUSINESS DEVELOPMENT GRANTS

Question. Mr. Secretary, this Budget, again, terminates successful grant programs 

that promote economic development and job creation in rural America. Rural Business Enterprise Grants (RBEG) facilitate development of small and emerging business enterprises, while Rural Business Opportunity Grants (RBOG) provide technical assistance for business development planning. Current funding levels would 

create or save about 24,500 jobs, through 560 recipients, in rural areas desperately 

needing development assistance. 

On a cost per job basis, these grant programs are probably the most effective in 

the Rural Development portfolio. Why is the Administration proposing to terminate 

such successful programs? 

Answer. Funding can be provided by other business loan and grant programs 

within the Federal Government and rural development. 

Question. This proposal was soundly rejected last year. What has changed in the 

rural economy to make this proposal now more palatable? 

Answer. Limited discretionary funding, higher priorities, and the need to support 

other Departmental priorities all played into the Administration’s proposal. Rural 

Development intends to focus its resources on programs with higher potential for 

encouraging private-sector investments, and that would reach a broader range of 

rural communities. 

FINANCING NEW ELECTRIC GENERATION FACILITIES

Question. Mr. Secretary, we understand that there are about 66 electric Generation and Transmission (G&T) cooperatives and 864 distributional cooperatives, 

many of which rely on the Rural Utilities Service (RUS) electric loan program for 

financing. These cooperatives serve about 13 percent of U.S. electric customers, provide 11 percent of electric sales, and own about 4 percent of total U.S. operational 

capacity. 

Cooperatives are entering a new wave of power plant investment to increase capacity and replace aging infrastructure that dates from the mid-1970’s to mid 

1980’s. Planning for new construction takes several years, followed by construction 

periods that can span 5 years or longer. Cooperatives depend on the Federal Government for adequate, low cost financing to accommodate the Nation’s growing energy needs. Financing is principally provided by Federal Financing Bank (FFB) 

loans guaranteed by RUS, which is offered at Treasury interest rates plus 1⁄8 percent. 

We are concerned that this Budget will not meet capital needs of rural electric 

cooperatives. RUS currently has applications exceeding $10 billion for generation 

and transmission purposes, scheduled for funding in fiscal year 2007 and fiscal year 

2008. About 80 percent of this total is for construction of new baseload generation. 

This Budget seeks only $4.1 billion in fiscal year 2008 funding, and, for the first 

time, bars funding for new baseload generation. 

Prohibiting new baseload generation will make many of these plants less feasible 

economically at a time when electricity demand is growing rapidly. Rural consumers 

already pay an average of 12 percent higher electric rates than neighboring utilities. 

Terminating Federal funding will force rural electric cooperatives to face higher interest rates, shorter loan terms, and raise rates charged to rural customers. 

In the face of demonstrated needs for extensive infrastructure replacement and 

expansion, why is the Administration barring access to financing for new baseload 

generation? 

Answer. There are significant demands on RUS electric loan resources. Needs for 

transmission and plant upgrades, including environmental upgrades, as well as the 
100 

need for new generation plans are high. Due to the inherent risks associated with 

construction of baseload generation, other significant demands on loan resources 

and the ability to obtain commercial financing, the Administration determined that 

restricting the use of electric loan funds made the best use of taxpayer funds while 

still providing significant support for rural electric needs. 

However, understanding the concerns of Congress, the Administration has committed to providing a generation only subsidy rate. 

Question. What studies has the Administration performed that indicate sufficient 

private financing is available to meet this immediate need for baseload generation? 

Answer. Though no studies have been conducted by the Administration, there is 

significant liquidity in the capital markets to absorb demand for this segment of the 

energy sector. 

Question. Has the RUS estimated the impacts of this policy change on electricity 

costs of rural consumers? What are the impacts? 

Answer. The Administration has not estimated the impacts of this proposal on 

electricity costs. 

WATER AND WASTE PROGRAM

Question. Mr. Secretary, Rural Development’s Water and Waste Water program 

has provided loan and grant funds for years to small rural communities to ensure 

adequate clean water and sanitary waste disposal systems. This Budget again proposes to alter the method to determine borrower interest rates. Poverty and intermediate interest rates would float such that the poverty rate would be 60 percent 

of the market rate and the intermediate rate would be 80 percent of market. In the 

current interest rate environment, poverty and intermediate interest rates would 

substantially fall. Projects would be financed with substantially more debt and reduced grant funds, but with little change in communities’ debt burdens due to the 

dramatic interest rate reductions. 

Will you provide assurance that small, poor communities will not be left out of 

the program, and that debt burdens will not increase and raise water and sewer 

rates? 

Answer. The lower interest rate would allow a small community to borrow more 

loan funds without an increase in their annual debt repayment. While a community’s total debt may increase, their annual debt burden should not increase and 

will not raise water and sewer rates. Our objective is to provide a funding mix of 

low interest loan and grant funds to keep user rates reasonable and consistent with 

the cost of similar systems in the area. It is still anticipated that grant funds would 

be focused on helping the neediest communities. With lower interest rates, we would 

be able to increase our reach to more communities with lower incomes. 

Question. Do regulations still allow borrowers with loan funds obligated but not 

closed to receive the interest rate in effect at the time of obligation or closing? 

Answer. Yes. 

Question. What is the magnitude of loan funds currently obligated but not closed? 

Answer. As of March 13, 2007, there were $2,482,693,545 in loan funds obligated 

but not closed. This represents 1,813 unclosed loan obligations. 

Question. Please provide a distribution of unclosed obligations, by year. 

Answer. As of March 13, 2007, the unclosed obligations by year were: 

[The information follows:] 

Fiscal year No. Amount 

2007 ........................................................................................................................................ 209 $270,506,775 

2006 ........................................................................................................................................ 655 845,439,746 

2005 ........................................................................................................................................ 399 569,531,323 

2004 ........................................................................................................................................ 226 328,100,059 

2003 ........................................................................................................................................ 116 164,029,838 

2002 ........................................................................................................................................ 113 172,123,226 

2001 ........................................................................................................................................ 25 37,473,080 

2000 ........................................................................................................................................ 24 39,727,518 

1999 ........................................................................................................................................ 19 21,932,140 

1998 ........................................................................................................................................ 15 23,712,840 

1997 ........................................................................................................................................ 5 4,201,300 

1996 ........................................................................................................................................ 4 4,260,700 

1995 ........................................................................................................................................ ........................ ........................

1994 ........................................................................................................................................ 1 300,000 

1993 ........................................................................................................................................ 2 1,355,000 
101 

Fiscal year No. Amount 

Total ........................................................................................................................... 1,813 2,482,693,545 

INFORMATION TECHNOLOGY (IT) ISSUES

Question. Mr. Secretary, it appears that automated systems for the Farm Service 

Agency (FSA) are currently in an untenable situation. The current spate of severe 

access and response problems emerged last November, peaking in January with 

field offices experiencing only sporadic, random access to program software. FSA 

program participants faced substantial delays while FSA field staff endured long, 

erratic periods of unresponsive software. 

Please describe how this Budget addresses FSA IT needs. 

Answer. The fiscal year 2008 President’s Budget provides sufficient funding to 

maintain the IT system at its current level of operation. USDA is working with the 

Office of Management and Budget to identify an appropriate funding source for stabilization and modernization. 

Question. Our understanding is that it will take hundreds of millions to fully resolve the unstable IT situation. Please provide a detailed plan, with associated costs, 

that generates a long-term, sustainable, solution to this problem. 

Answer. A business plan is being prepared to address the requirements and resources necessary to stabilize the current system, prepare it for implementation of 

a potential disaster bill and the new farm bill, and replace the current system with 

a fully modernized and integrated new system. 

FSA’s business plan includes the following major components: 

—Network Stabilization (e.g., expand equipment capacity, purchase monitoring 

tools and hire personnel to monitor the system) 

—Stabilize Databases and Farm Program Payment Applications (e.g., establish 

proper test environment; employee training and consultants to address database 

design, configuration and problems; update applications; establish data warehouse for queries and reporting) 

—Disaster Bill (e.g., hardware, software development and testing) 

—Farm Bill (e.g., hardware, software development and testing) 

—Modernization (e.g., capital investments and incremental operating costs) 

—Field office system replacement (e.g. replacement of field office servers) 

The following table summarizes the estimated costs. 

[The information follows:] 

FSA IT SYSTEM STABILIZATION AND MODERNIZATION 

[Preliminary Cost Estimate] 

Fiscal Year Total Cost 

Requirement 2007 2008 2009 2010 

Capital Requirements: 

Network Stabilization .............. 11,467,850 12,966,667 12,548,750 ........................ 36,983,267 

Database/Application Stabilization ............................. 12,983,000 44,047,100 12,067,100 ........................ 69,097,200 

Disaster Bill ............................ 8,500,000 ........................ ........................ ........................ 8,500,000 

Farm Bill 1 ............................... 16,000,000 42,000,000 ........................ ........................ 58,000,000 

Modernization .......................... 675,521 132,154,811 120,572,189 ........................ 253,402,521 

Total ................................... 49,626,371 231,168,578 145,188,039 ........................ 425,982,988 

Incremental Operating Requirements: 

Network Stabilization .............. 4,949,286 5,307,077 6,798,435 1,556,275 18,611,072 

Database/Application Stabilization ............................. 8,120,857 7,245,800 8,864,800 ........................ 24,231,457 

Disaster Bill ............................ ........................ 5,080,000 25,420,000 ........................ 30,500,000 

Farm Bill 1 ............................... ........................ ........................ ........................ ........................ ........................

Modernization .......................... ........................ 12,118,000 12,364,000 ........................ 24,482,000 

Field Office System Replacement 2 ................................. ........................ 19,200,000 9,600,000 ........................ 28,800,000 

Total ............................... 13,070,143 48,950,877 63,047,235 1,556,275 126,624,530 
102 

FSA IT SYSTEM STABILIZATION AND MODERNIZATION—Continued 

[Preliminary Cost Estimate] 

Fiscal Year Total Cost 

Requirement 2007 2008 2009 2010 

Total Cost: 

Network Stabilization .............. 16,417,136 18,273,743 19,347,185 1,556,275 55,594,339 

Database/Application Stabilization ............................. 21,103,857 51,292,900 20,931,900 ........................ 93,328,657 

Disaster Bill ............................ 8,500,000 5,080,000 25,420,000 ........................ 39,000,000 

Farm Bill 1 ............................... 16,000,000 42,000,000 ........................ ........................ 58,000,000 

Modernization .......................... 675,521 144,272,811 132,936,189 ........................ 277,884,521 

Field Office System Replacement 2 ................................. ........................ 19,200,000 9,600,000 ........................ 28,800,000 

Total ................................... 62,696,514 280,119,454 208,235,274 1,556,275 552,607,517 

1 Farm Bill estimate includes only IT related costs. Additional expenditures to deliver the 2007 Farm Bill will be required. For example, temporary employee cost for the 2002 Farm Bill was approximately $26 million for 1,100 temporary employees. 2 Includes only those costs necessary to upgrade network servers located in field office locations. Estimate does not include normal replacement costs for other field office equipment (e.g. phone systems, printers, workstations, mobile devices, GPS systems, etc.) which may also be 

approaching the end of their expected useful life. 

FSA FIELD STAFF AND OFFICE STRUCTURE

Question. Mr. Secretary, adequate FSA field staffing and office locations have 

been issues for some time. Substantial concerns were raised in the recent past in 

response to FSA plans to restructure. 

What are current plans for altering FSA field staffing levels and field office locations? 

Answer. FSA has asked each State Executive Director (SED) to conduct an independent local-level review of the efficiency and effectiveness of FSA offices in their 

respective State. There is no national plan or formula for closing or consolidating 

offices. SEDs and State committees have been directed by the FSA Administrator 

to form a review committee to identify what the optimum network of FSA facilities, 

staffing, training and technology should be for their State. Efficiencies will be based 

on each State’s individual needs and will be within existing budgetary resources and 

staffing ceilings. FSA is also committed to coordinating with Congress, stakeholders, 

local groups and customers to ensure the agency offers the best service possible. 

FINANCIAL MANAGEMENT SYSTEM

Question. The budget request includes an increase of $24.8 million for the financial management system of the Chief Financial Officer. 

What will the total cost for completion of this system be? 

Answer. The estimated cost for implementation of USDA’s new financial management system is approximately $90 million. 

Question. How many years will it take for this system to be completed? 

Answer. Our preliminary schedule shows completion of implementation at the end 

of fiscal year 2011. USDA is presently in the acquisition phase and has yet to award 

a contract for services or hosting. 

Question. If no funds are provided for this, will work continue? 

Answer. If appropriated funding is not provided, the project will continue, but will 

do so at a pace that reflects the funding that would be available, and this is likely 

to be at a much slower pace than projected. Funding would be sought from other 

sources—the Working Capital Fund, reimbursements from customer agencies, purchase card rebate proceeds, and/or any funds that might be made available under 

authority to transfer unobligated balances. By relying upon these alternative 

sources, implementation timing will be affected as these resources may also be needed for other important corporate investments. To the extent that implementation is 

delayed, USDA will need to maintain operation of the legacy financial system, adding additional costs. 

CAPITAL SECURITY COST SHARING PROGRAM

Question. The budget includes an increase of $5,241,000 under the Foreign Agricultural Service for the Capital Security Cost Sharing Program. Since fiscal year 

2005, this program has increased substantially. 

When do you expect funding for this to plateau and then start to decline? 
103 

Answer. The Capital Security Cost Sharing (CSCS) program is designed to generate a total of $17.5 billion to fund 150 new diplomatic facilities over a 14-year period. The FAS assessment comprises approximately 70 percent of USDA’s total annual contribution to the program. In the case of FAS, its assessment started at $0.6 

million in 2005 and increased to over $5.5 million in 2007. It is estimated to increase annually until 2009, at which time the estimated annual assessed level will 

total approximately $9 million. This level is assumed to remain constant at that 

point for the next 9 years with FAS payments totaling as much as $140 million over 

the life of the program. 

Question. What assurance have you received from the State Department that FAS 

is paying for space that they actually occupy? 

Answer. FAS Washington staff have worked closely with our field offices and with 

the State Department’s Office of Building Operations to correctly identify positions 

that should be billed to FAS. Also, according to Section 604 of the Secure Embassy 

Construction and Counterterrorism Act of 1999, the funds collected under the CSCS 

program are devoted entirely to the construction of new embassy and consular compounds worldwide, regardless of presence. 

Question. Is the agency currently paying for space in facilities where they do not 

have a presence? 

Answer. The CSCS program funds construction of new U.S. embassy compounds 

by contributions from all agencies in proportion to their overseas presence. Of the 

80 planned security projects in the next seven years, FAS will occupy space in 27 

of the new facilities. 

Question. Which agencies at USDA contribute to the Capital Security Cost Share 

Program? 

Answer. Other USDA agencies that contribute to the CSCS program include the 

Animal and Plant Health Inspection Service, Agricultural Research Service, Rural 

Development, Natural Resources Conservation Service, and Grain Inspection, Packers and Stockyards Administration. 

Question. Is this reflected in all of their budget justifications? If not, why? 

Answer. Like FAS, APHIS and ARS display their contributions to the CSCS program in their explanatory notes. In the case of the other agencies, the amounts involved are less than $60,000 for 2008, and the agencies have not displayed them 

separately from other administrative funding. 

PUBLIC LAW 480 TITLES I AND II AND FOOD FOR PROGRESS

Question. Over the past several years, funds have been transferred from Public 

Law 480 Title I to carry out activities under the Food for Progress program. Please 

explain the impact of your request to eliminate the Title I program will have on the 

Food for Progress program. 

Answer. Food for Progress programming in 2008 will continue to be carried out 

through Commodity Credit Corporation funding. The 2008 President’s budget 

projects that CCC-funded Food for Progress programming will total approximately 

$163 million. 

Public Law 480 Title I funding to carry out Food for Progress will no longer be 

available in 2008. Although no funding was appropriated for Public Law 480 Title 

I for 2007, approximately $39 million of Title I funding that was carried over from 

prior years is being used to support Food for Progress programs this year. No similar carry over balances are expected to be available during 2008. 

Question. Is it your anticipation that there will be increased availability of funds 

in fiscal year 2008 for non-emergency programs under Title II? If not, is the Title 

I elimination another overall reduction in non-emergency food aid programs? 

Answer. It is difficult to predict with certainty what the level of emergency needs 

will be in 2008 and, therefore, difficult to state whether funding for non-emergency 

programs will increase above this year’s level. When the 2007 budget recommended 

no further funding for Public Law 480 Title I, a corresponding increase of $80 million was requested for Public Law 480 Title II donations. That increase was approved and remains in the base funding level for Title II and can, therefore, be used 

to support either emergency or non-emergency Title II programming. 

AGRICULTURAL RECONSTRUCTION ACTIVITIES

Question. The Department supports the use of Provincial Reconstruction Teams 

as a way to assist, re-stabilize, and promote agricultural production in certain areas 

of the world, such as Iraq and Afghanistan. However, it seems that many of the developmental aspects of these teams could also serve in developing countries, such 

as in sub-Saharan Africa, where the ability to promote food security is crucial. 
104 

Do you think that the use of a mechanism similar to the Provincial Reconstruction 

Teams could serve a useful purpose as part of an overall global food security strategy? 

Answer. The PRTs were first established in Afghanistan for the international 

community to provide improved security and to facilitate reconstruction, along with 

economic development, throughout the country. The PRTs are seen as transitional 

structures and operate in high risk, unstable and difficult situations. The PRTs 

have a broad mandate in bringing reconstruction to the local people and allow the 

U.S. Government to engage with key government, military, tribal, village, and religious leaders in the provinces, while monitoring and reporting on important political, military and reconstruction developments. They also provide protective services 

to experts providing assistance. 

USDA has found PRTs to be effective in allowing USDA agricultural advisors to 

work and directly affect agriculture on a local level in Afghanistan and Iraq. PRTs 

could serve a useful purpose as part of an overall global food security strategy, especially in reconstruction and stabilization situations. In other situations they might 

have usefulness but, as transitional structures, they would need to be modified considerably to make them relevant and cost effective. 

Question. If not, then why do you think they will be successful in Afghanistan and 

Iraq? 

Answer. USDA believes that PRTs in Afghanistan and Iraq are effective platforms 

from which our specialists can operate. USDA’s PRT advisors continue to make significant contributions to the training of Ministry of Agriculture staff at the local 

level, and they provide valuable expertise to local and international non-governmental organizations, donors, and others working in agricultural development. PRTs 

allow USDA to work in close collaboration with other agencies to plan and implement projects that utilize a combination of resources. Many of these projects would 

be beyond the capacity of USDA alone. 

CONSERVATION OPERATIONS

Question. For Conservation Technical Assistance, there is an increase of 

$1,000,000 for a stand-alone financial audit. 

Why is this audit necessary? 

Answer. The Conservation Technical Assistance program is the foundation for all 

of USDA’s conservation efforts. This makes it vital for policy officials to have the 

most accurate information possible in order to make the best programmatic and 

management decisions. An independent financial audit will help the agency identify 

weaknesses in program implementation and help institute improvements for program management and accountability. 

Question. What concerns were raised in order for these funds to be needed? 

Answer. During preparation of the 2008 President’s budget request, issues of program management and accountability were closely looked at. It was determined that 

an independent financial audit would help identify steps needed to address concerns 

regarding improper or duplicate payments; large number of up(down)ward adjustments, proper use of commitments and obligations; and validity of open obligations 

and reimbursable accounts. 

Question. The budget includes a decrease of $17,225,000 for the Grazing Lands 

Conservation Initiative but retains $10,000,000 for a competitive grants program. 

Please explain the purpose and aspects of this program. 

Answer. By Congressional directive in recent years, NRCS provided technical assistance to owners and managers of private grazing lands to improve long-term productivity and ecological health. In fiscal year 2006, Congress directed that 

$4,188,000 (of the $27,500,000 GLCI earmark) be used on efforts to manage the 

spread of invasive species. A nationwide competitive grants process was used to 

carry out the fiscal year 2006 Congressional directive. The President’s 2008 budget 

proposes to continue the competitive grants program to control invasive species. It 

is estimated that invasive plants infest over 100 million acres of grazing land in the 

United States. 

Question. How will these funds be awarded? 

Answer. A nationwide announcement would be issued to attract viable applications from eligible government and non-government organizations and individuals 

to compete for the available funding. The grants would be awarded based on various 

elements in the applications including purpose and goals, soundness of approach, 

proposed project management, and transferability (technology transfer). A matching 

contribution would be required of the applicant. A portion of the funds would be set 

aside for competition among limited resource farmers and ranchers and Tribes. 

Question. What are the goals and expected outcomes of this program? 
105 

Answer. The objective of the invasive species grants would be to encourage and 

support the management and control of invasive species affecting grazing lands. We 

will use the ‘‘cooperative conservation’’ approach to address invasive species concerns on a local, statewide, or regional basis. The use of Integrated Pest Management techniques and biological pest control methods would be encouraged. 

RESOURCE CONSERVATION AND DEVELOPMENT

Question. The budget includes a decrease of $37,717,000 for Resource Conservation and Development program activities. Included in this is a proposed consolidation of RC&D Coordinators, reducing the number from 375 to 50. 

Why is this consolidation necessary? 

Answer. The Program Assessment Rating Tool (PART) analysis found the program to be duplicative of other conservation and rural development programs and 

the program does not prioritize or target funding effectively. Specifically, the purposes and services provided by the RC&D program overlap with other similar resource conservation planning, rural economic development, and community facilities/amenities development services provided by other USDA agencies (such as the 

Forest Service and Rural Development) and other Federal departments (such as the 

Department of Commerce’s Economic Development Administration). 

Question. What plans are currently in place should the Committee decide to decrease funding for RC&D? 

Answer. While the overall program budget will decrease, NRCS will continue to 

provide support through a state-wide RC&D coordinator. The coordinator’s role will 

focus more on coordinating USDA assistance toward the implementation of RC&D 

Area Plans rather than day-to-day operations of RC&D councils. For several years, 

USDA has partnered with the National Association of RC&D Councils, Inc. to increase the capacity and sustainability of RC&D councils across the country. Many 

councils have increased their partnerships and financial portfolios so they are less 

reliant on NRCS direct technical and financial assistance. The budget proposal reflects an expectation that more councils will be able to take on the additional responsibility. 

Question. Will staff be folded into other agencies within the Department? 

Answer. The majority of RC&D coordinators are classified in such a way that they 

will fit well within other jobs and activities of NRCS. Most RC&D Coordinators 

were previously NRCS Soil Conservationists prior to becoming RC&D Coordinators. 

The majority would easily adjust to soil conservationist type work at the field level. 

AGRICULTURAL MARKETING SERVICE

Question. How does AMS intend to protect the organic standard in light of current 

FDA proposals to approve food from cloned animals, with no requirement for labeling? 

Answer. In response to the FDA announcement regarding cloned animals, AMS 

issued a notice to the industry that, pursuant to the National Organic Program 

(NOP) regulations, cloning is a prohibited practice in organic production. AMS also 

consulted the National Organic Standards Board (NOSB) and received a recommendation to prohibit not only cloning as a production method, but the use of 

their progeny in organic production as well. AMS intends to develop rulemaking or 

guidance related to clones and their progeny in organic production. 

Question. What actions has AMS taken in response to the audits performed by 

the American National Standards Institute in 2004 and by the USDA Office of Inspector General in 2005, which made strong recommendations about changes needed 

in the administration of the National Organic Program? 

Answer. The audit conducted by the American National Standards Institute 

(ANSI) found that there were many procedures, required by an ISO Guide 61 system (since revised by ISO and reissued as ISO 17011), that the ANSI auditors were 

not able to identify during the onsite audit. In response, AMS assigned a task force 

of experienced quality system specialists to work on the NOP quality management 

system. Those processes were completed by the September 2005 target date agreed 

to by AMS. Some processes that require participation by certifying agents or certified operations, such as our reinstatement procedures, have been posted on the 

NOP website. Some additional procedures have been posted as they were approved 

by the Office of the Inspector General, who conducted a separate but similar review 

at about the same time. The OIG audit found similar deficiencies as the ANSI audit 

and identified 10 action items to be completed by the NOP. All of the OIG action 

items have been completed. 
106 

NATIONAL ORGANIC CERTIFICATION COST SHARE PROGRAM

Question. Of the $5 million provided in the fiscal year 2002 Farm Bill for the National Organic Certification Cost Share Program, how much remains unobligated 

and/or unspent? Please provide a breakdown of the States with remaining unobligated and/or unspent funds, as well as a list of States that have spent all of their 

funds. 

Answer. The information is provided for the record. As of March 20, 2007, $148,340 is unobligated and unspent funds total $247,100 for the 24 States with 

funds remaining. 

Eighteen States have exhausted all of their allotted funds: Arkansas, Colorado, 

Florida, Georgia, Illinois, Iowa, Massachusetts, Minnesota, Montana, New Hampshire, New York, North Carolina, Oklahoma, Pennsylvania, Tennessee, Virginia, 

Washington, and Wisconsin. 

Seven States that have spent more than 90 percent of program allotted funds: 

California, Maine, Michigan, North Dakota, Oregon, South Dakota, and Vermont. 

Seventeen States have more than 10 percent of program allotted funds remaining: 

Alaska, Hawaii, Idaho, Indiana, Kansas, Kentucky, Maryland, Mississippi, Missouri, 

Nebraska, New Jersey, New Mexico, Ohio, South Carolina, Texas, Utah, and Wyoming. 

Eight States chose not to participate in this program: Alabama, Arizona, Connecticut, Delaware, Louisiana, Nevada, Rhode Island, and West Virginia. 

Question. If funding for the National Organic Certification Cost Share Program 

remains unobligated and/or unspent in some States at the end of fiscal year 2007, 

does USDA have the authority to make that funding available to other States? Does 

USDA plan to do so? 

Answer. Within each AMS-State cooperative agreement, there is a provision that 

gives AMS the authority to terminate agreements and redistribute unspent funds 

to other States that have exhausted funds. If States are not actively obligating 

funds and large balances remain unspent at the end of fiscal year 2007, AMS will 

exercise this authority. 

Question. What is the total funding provided in the fiscal year 2008 budget for 

the National Organic Program? Answer. The fiscal year 2008 request for Organic Standards is $3.18 million. 

EMERGING PESTS

Question. How does APHIS work to prevent things such as Emerald Ash Borers 

and Asian Longhorn Beetles from entering the United States? What improvements 

need to be made at the borders to prevent these incredibly expensive pests from entering and causing these problems? 

Answer. The Agriculture Quarantine and Inspection program protects the United 

States from the risks associated with the introduction of invasive agricultural pests 

and diseases. APHIS and the Department of Homeland Security cooperate to carry 

out this program, and fund the programs through a combination of appropriations 

and user fees. The Pest Detection program supports APHIS’ goal of safeguarding 

U.S. agricultural and environmental resources by ensuring that new introductions 

of harmful plant pests and diseases are detected as soon as possible, before they 

cause significant damage. USDA is requesting a $15 million increase in the Pest Detection program for fiscal year 2008. 

Exotic wood boring and bark beetles such as EAB and Asian longhorned beetle 

(ALB) likely entered the United States through infested solid wood packing materials such as pallets, crates, and other materials used in international shipping. 

These materials are often reused and reshipped many times throughout the world. 

Many countries have recognized the need to deal with the pest risk. APHIS worked 

with its international counterparts to develop standards for safely moving solid 

wood packing materials and implemented regulations based on the developed standards. While APHIS and affected States are still dealing with the effects of EAB and 

ALB and several other exotic forest pests already in the United States, we believe 

that the new regulation of wood packaging materials should help prevent future infestations of this type. 

Question. At what point do you make a determination that the eradication of a 

disease isn’t possible, such as in the case of citrus canker? What are the next steps 

once that determination has been made? 

Answer. Although each pest or disease situation must be analyzed separately, 

there are several factors we consider when determining whether or not eradication 

is feasible. Among these are: the availability of adequate funding and active participation from Federal, State, and industry cooperators; weather and any other environmental constraints; the potential of the pest to do significant economic damage 
107 

to agricultural or forest resources; the extent to which the pest or disease has 

spread; the availability of effective detection, diagnostic, and control technology; the 

availability of acceptable alternatives to eradication; public support for an eradication program; the disease’s public health significance; and the vectors associated 

with a disease (e.g., mosquitoes, ticks, etc.). 

Federal officials take all of these and other factors into consideration as they determine whether the eradication of a pest or disease is possible. If one or more of 

these factors change considerably during the course of an eradication effort, the 

planned course of action will be reevaluated. Prior to making any major decisions 

about discontinuing an eradication effort, Federal officials will consult with their 

State and industry cooperators, then update policies and regulations as appropriate. 

Question. Specifically for Chronic Wasting Disease, how will the requirements for 

the States change with the proposal for a match in which the Federal Government 

will pay for 60 percent of anticipated program needs, and the State will fund the 

rest? Will the State funding level need to increase? Answer. The 2008 budget proposes a reduction of about $4 million. The program 

requirements for the chronic wasting disease (CWD) herd certification program 

(HCP) will not change with the funding reduction. At the requested funding level, 

USDA anticipates the States and cooperators would contribute additional resources 

to support the efforts at current levels. 

Question. More broadly, what amount does APHIS anticipate saving by requiring 

increased State matches for APHIS activities? Is there currently a mandated match 

level for States, or is this an entirely new proposal? If a State can’t or does not provide the requested match amount, what will APHIS do then? 

Answer. The following table is provided for the record. 

[The information follows:] 

Line Item Savings 

Chronic Wasting Disease ..................................................................................................................................... $4,400 

Emerging Plant Pests—Citrus Health Response Program (Florida) ................................................................... 2,300 

Emerging Plant Pests—Asian Longhorned Beetle (NJ & NY) ............................................................................. 1,691 

Emerging Plant Pests—Glassy-Winged Sharp Shooter (California) ................................................................... 1,001 

Johne’s Disease .................................................................................................................................................... 5,005 

Noxious Weeds ...................................................................................................................................................... 300 

Total ........................................................................................................................................................ 14,697 

There is currently no mandated match level for States, nor is USDA proposing 

a mandated level. It is our goal to leverage increased participation from the States 

to maximize the benefits received from Federal dollars. 

If a State is unable to contribute the estimated amount for a particular program, 

USDA will evaluate the overall impact to program efforts and adjust future funding 

requests accordingly. 

APHIS COOPERATIVE AGREEMENTS

Question. Please provide a chart showing all cooperative agreements with States 

and other organizations to be carried out in fiscal year 2007, including total funding 

provided by Congress, and funding retained by APHIS. 

Answer. Given the timing of the full-year fiscal year 2007 appropriation, APHIS 

is currently in the process of negotiating with States and other organizations in the 

development of work plans and agreements for this year. Therefore, the requested 

information is not available at this time. This information will be provided when 

available, but not later than August 1, 2007. 

Question. Was there any input gathered from those whose responsibilities will be 

increased before this proposal was put forth to decrease funding for Johne’s disease? 

Are these activities that the States, etc. are currently undertaking, or would have 

to pick up? 

Answer. USDA has consulted with our partners in the Voluntary Bovine Johne’s 

Disease Control Program (VBJDCP), and they are aware of our request. From its 

inception, the VBJDCP has been a cooperative effort among APHIS, State departments of agriculture, and industry. States have been the main driving force of the 

VBJDCP. A large part of the Johne’s disease funds not requested in the President’s 

Budget has been used by the States to pay for producer testing and risk assessment 

fees. With a reduction in Federal funding, these costs will need to be covered by 

producers who benefit from this program. In addition, State and University partners 

would assume responsibility for continuation of the Johne’s disease demonstration 

herd projects implemented in each region. These projects focus on new and current 
108 

testing schemes and control methods to determine the most effective cost management practice options. 

APHIS will continue to provide oversight to the VBJDCP and support analysis of 

the national demonstration projects, along with continuing laboratory approval and 

licensing diagnostic tests and vaccines for commercial use. 

COMMON COMPUTING ENVIRONMENT

Question. Why is the budget for CCE decreasing this year, when needs are certainly not? 

Answer. Funding for the CCE has been comprised of Service Center Agency (FSA, 

NRCS, RD) information technology (IT) purchases through their own appropriations, 

in addition to funding provided through the CCE direct appropriation. This funding 

has been used to develop an infrastructure to support the business delivery functions of the Service Center Agency (SCA) field offices located across the country. The 

2008 budget requests that $78.5 million with an additional $12 million for CCE activities that are specific to FSA be included in the SCA salaries and expenses appropriations to meet the ongoing business delivery needs. This funding will support the 

continued IT activities of the SCAs as they jointly maintain the CCE infrastructure. 

In addition, the SCAs will continue to work with the Information Technology Services (ITS) division of the Office of the Chief Information Officer in USDA. ITS is 

funded through reimbursable agreements with the SCAs and delivers staffing and 

services to the agencies in support of the CCE. In coordination with ITS, the agencies will be able to ensure that the necessary services and staffing are available to 

maintain the infrastructure and program delivery. 

Question. Please provide a chart showing the total CCE funding, either within the 

CCE account or at the Agencies, over the past 5 years. 

Answer. A chart has been provided for the record showing the funding for the 

CCE for fiscal year 2002 through fiscal year 2006. This chart includes funding from 

the CCE direct appropriation, agency direct purchases of IT equipment and services 

for the CCE, and agency reimbursements of the OCIO-Information Technology Services (ITS) through the Working Capital Fund (WCF). These amounts paid for ITS 

operating expenses for the CCE and other IT activities, such as Geographic Information Systems (GIS). 

[The information follows:] 

CCE FUNDING 

Fiscal year 

2002 2003 2004 2005 2006 

Funding Source: 

CCE Direct Appropriation ........ $59,369,000 $133,155,000 $118,585,000 $121,577,300 $108,971,000 

Service Center Agency IT purchases for CCE (paid directly to vendors; did not 

go through WCF) ................ 29,174,241 30,924,733 30,748,000 55,413,000 30,265,009 

Total ............................... 88,543,241 164,079,733 149,333,000 176,990,300 139,236,009 

Question. Does the USDA have a solid budget estimate of the cost to replace the 

current outdated FSA computer system? 

Answer. FSA is planning to implement a long-term modernization effort known 

as MIDAS to replace its obsolete equipment. FSA anticipates submitting a business 

case for this investment to the Office of Management and Budget during March 

2007. Preliminary cost estimates indicate that this planned transition would require 

about $278 million over fiscal years 2007 through 2009. It would also have a total 

10-year lifecycle cost of $463 million unadjusted for risk and an estimated cost of 

$617 million when adjusted for risk. 

In addition to this modernization effort, further costs must be incurred to stabilize 

the FSA IT system components at field offices in the short term. These additional 

costs are estimated to be about $150 million to bring the Kansas City web-based 

system up to at least moderate reliability; about $97 million to implement likely disaster assistance and Farm Bill legislation; and nearly $29 million to replace obsolete 

field office components. Thus, estimated total costs of nearly $553 million over fiscal 

years 2007 through 2010 will be required to bring the current system up reasonable 

operating capability and to transition to a modernized system. However, the actual 

modernization component as noted above is estimated to cost about $278 million. 
109 

Question. Is an FSA replacement system part of the Farm Bill proposals submitted? If not, where will this funding come from, since it is not in the President’s 

budget? 

Answer. Funding for modernization of FSA’s information technology systems is 

not included in the Administration’s Farm Bill proposal. USDA is working with the 

Office of Management and Budget to identify an appropriate funding source for this 

investment. 

COMMODITY SUPPLEMENTAL FOOD PROGRAM

Question. How many people currently on CSFP do you estimate will lose all benefits, either by not deciding to participate in Food Stamps, or receiving fewer benefits 

under Food Stamps? 

Answer. We do not know how many current CSFP participants would not participate or potentially receive a food stamp benefit lower than the value of the CSFP 

package. We estimate that CSFP participants who opt to transition to food stamps 

will receive an average monthly benefit of $54 per person. In contrast, we project 

that the average CSFP food package for elderly people would have a retail value 

of about $44 in fiscal year 2007. 

PROPOSED LIMIT ON WIC ADMINISTRATIVE FUNDING

Question. Please explain how the proposed limit on WIC administrative funding 

will affect the activities that WIC providers are required to carry out, including nutrition education, referral services, and other important services? 

Answer. We appreciate the hard work that WIC professionals have done to create 

and operate one of our premier nutrition assistance programs. However, nutrition 

services and administration (NSA) funding continues to require a greater and greater proportion of the annual WIC appropriation. In every other sector of government—Federal, State and local—we have all had to learn to become more efficient 

within tighter administrative budgets. We believe WIC can, too. WIC State agencies 

have achieved remarkable success in controlling food costs; we have no doubt that 

the same creativity can be applied to the NSA costs without compromising important client services and program operations. 

Our proposal would provide NSA funds at the fiscal year 2006 per-person level. 

This would allow for a greater proportion of appropriated funds to be used for food 

benefits and to ensure that funding continues to be adequate to serve all eligible 

individuals who wish to participate. It is anticipated that the total appropriation 

needed for fiscal year 2008 would be reduced by approximately $145 million through 

this redirection of NSA funds to food funds. 

Question. Please outline how this proposal is different from the fiscal year 2007 

budget request. 

Answer. The current proposal is intended to provide a reduction in WIC NSA 

funding to slow its growth rather than to ‘‘cap’’ the funds available for NSA at 25 

percent as proposed in the fiscal year 2007 budget. 

Current legislation provides an amount for State agency NSA grants sufficient to 

guarantee a national administrative grant per participant (AGP). The guaranteed 

national AGP for each fiscal year is based on the prior year’s AGP, inflated by the 

State and Local Purchase Index, as required by legislation. The WIC AGP inflation 

rate from fiscal year 2006 to fiscal year 2007 was 6 percent. 

Our current proposal would reduce the AGP used to determine the proportion of 

funds made available for NSA in fiscal year 2008 rather than using the inflated fiscal year 2007 AGP level. 

Question. If this proposal is not adopted, will your request level for WIC still be 

adequate? 

Answer. USDA estimates that setting the fiscal year 2008 administrative grant 

per participant at the fiscal year 2006 level will save approximately $145 million 

through redirection of NSA funds to food funds. If this proposal is not adopted, then 

an additional $145 million would be needed in the fiscal year 2008 appropriation 

for the WIC Program in order to support average monthly participation at the anticipated level of 8.28 million. 

Question. Will the proposal regarding income limits actually save any money? Will 

this proposal, if included, require States to re-check the eligibility of all of their participants? 

Answer. USDA estimates that approximately $2 million per year will be saved by 

the proposal to limit income eligibility based on participation in Medicaid to those 

individuals whose incomes are below 250 percent of the Federal poverty guidelines. 

This will help ensure that WIC benefits are targeted to those most in need. The proposal would not require States to re-check the eligibility of all of their current par-
110 

ticipants. Rather, affected States will need to ask new WIC applicants and applicants whose prior certification has expired to show documentation of eligibility in 

a means-tested program other than Medicaid, such as the Food Stamp Program or 

Temporary Assistance for Needy Families, or to show documentation of their income 

to determine eligibility. 

Question. How many States will be affected by the income eligibility proposal, and 

how much will it cost them to re-certify all WIC participants? How many people do 

you think will have to be re-certified, and how many ineligible participants will be 

identified? 

Answer. Based on current Medicaid income eligibility levels, seven States would 

be affected: Hawaii, Maryland, Minnesota, Missouri, New Hampshire, Rhode Island 

and Vermont. The proposal would not require these States to re-certify current participants. Rather, these seven States will need to ask new WIC applicants and applicants whose prior certification has expired to show documentation of eligibility in 

a means-tested program other than Medicaid, such as the Food Stamp Program or 

Temporary Assistance for Needy Families, or to show documentation of their income 

to determine eligibility. We estimate that approximately 3,000 applicants who are 

on Medicaid in these States will have incomes above the 250 percent threshold and 

therefore no longer be eligible for benefits. 

FOOD STAMP PROGRAM LEGISLATIVE PROPOSALS

Question. How does the legislative proposal in the Food Stamp Program work to 

streamline Federal assistance programs? 

Answer. Many of the proposals work together to streamline the administration of 

the Food Stamp Program by simplifying complex policies, while at the same time 

supporting low-income working families. For example, we are proposing to exclude 

all retirement accounts and certain educational savings accounts from resources 

when determining eligibility. This simplifies the eligibility determination on the 

part of the State agencies while encouraging low-income families to save for retirement and their children’s future even if they experience a temporary need for food 

stamps. We are proposing to exclude combat related pay for military personnel. This 

proposal would make permanent a policy that has been enacted on a yearly basis 

through the budget process. This proposal makes it easier for State agencies to determine eligibility while supporting the families of service personnel fighting overseas by ensuring that they do not lose food stamps as a result of the additional deployment income. Taken as a whole, these proposals would have a significant affect 

on streamlining the administration of the Food Stamp Program. 

CENTER FOR NUTRITION POLICY AND PROMOTION

Question. Please list all cooperative agreements or contracts entered into by 

CNPP in regard to My Pyramid, including funding levels and recipients. 

Answer. Current contracts are for hosting and maintenance operations, evaluation, customer service, and refinement of tools already developed for the 

MyPyramid.gov Web site. Three cooperative agreements exist for educational purposes in support of MyPyramid and the 2005 Dietary Guidelines for Americans. No 

funds are exchanged between parties for these cooperative agreements. A list will 

be provided for the record. 

[The information follows:] 

Hosting and Maintenance Contracts (for support of website and associated databases): 

National Information Technology Center, Kansas City, KS ......................................................................... $181,000 

American Systems Corporation, Chantilly, VA ............................................................................................ 90,000 

Akamai Technologies, Cambridge, MA ........................................................................................................ 120,000 

Evaluation (for 12 month American Customer Satisfaction Index): 

ForSee Results, Ann Arbor, MI .................................................................................................................... 25,000 

Customer Service (for customer support specialist): 

Network Management Resources Consulting, Inc., Annapolis, MD ............................................................ 79,451 

Refinement of Tools (to increase usability of existing interactive tools): 

Porter Novelli, Washington, DC ................................................................................................................... 102,052 

Cooperative Agreements (To promote MyPyramid and the 2005 Dietary Guidelines for Americans): 

Tufts University, Boston, MA and Safeway, Inc., Pleasanton, CA .............................................................. ( 1 ) 

Naturally Nutrient Rich Coalition (NNRC), Chicago, IL .............................................................................. ( 1 ) 

Hispanic Communication Network (HNC), Washington, DC ....................................................................... ( 1 ) 

1 No funds were exchanged for Cooperative Agreements. 
111 

FOOD SAFETY AND INSPECTION SERVICE

Question. Will States receive the full funding level they requested in fiscal year 

2007 with the additional funding that we provided in the Joint Resolution? 

Answer. Funding levels for the States are reviewed in order to determine the 

amounts they require to perform their inspection tasks and may at times vary from 

the amount requested. However, adequate funds are available for States. 

Question. Is the President’s budget for fiscal year 2008 sufficient to provide the 

States with their full funding request in fiscal year 2008 for their State meat inspection programs? 

Answer. FSIS requests an increase of nearly $1 million for State MPI programs 

in fiscal year 2008, as stated in the amended budget explanatory notes. The fiscal 

year 2008 President’s Budget provides full funding for the State MPI programs 

based on estimated needs when the budget was proposed. FSIS will know the funding request from the States sometime after August 2007, when the States provide 

updated funding needs. 

Question. Please provide information regarding any long-term contracts FSIS has 

regarding public meeting space, including funding spent on these contracts. 

Answer. The Food Safety and Inspection Service has no long-term contracts for 

public meeting space. 

Question. Please provide information on employee performance bonuses at FSIS 

in fiscal year 2006, including the total amount of bonuses provided to GS employees, 

and the total amount of bonuses provided to SES employees. 

Answer. The Food Safety and Inspection Service’s Senior Executive Service (SES) 

performance awards for fiscal year 2006 totaled $269,362, and were paid in fiscal 

year 2007 using fiscal year 2007 funds. For fiscal year 2006, all other employees 

received a total of $2,774,926 in bonuses. 

Question. How often do processing inspectors working in combination slaughter/ 

processing plants have to perform slaughter duties because of an absence of a 

slaughter inspector due to vacancies, illness, vacations, etc.? Please describe the 

type of records the Agency keeps in such instances provide those records for the past 

2 years. 

Answer. The Food Safety and Inspection Service utilizes a variety of strategies to 

staff critical slaughter positions when absences occur due to vacancies, illnesses, and 

vacations. These strategies include utilization of relief inspectors and relief public 

health veterinarians, other-than-permanent employees, higher graded slaughter inspection personnel, and processing inspection personnel. The use of processing inspectors to cover the absence of slaughter inspectors has been policy for several decades, and is the best use of staff, as the presence of inspectors at slaughter facilities 

must be continuous. Documentation of the daily staffing strategies utilized at each 

plant is not maintained. Thus, records on the use of these staffing strategies are 

not available. 

Question. What is the current career ladder for FSIS inspection personnel? For 

the years 1996–2006, please identify the number of Agency employees by GS level 

that worked in Agency headquarters; that worked in field locations. How will the 

Agency’s implementation of RBI affect the numbers of employees in each GS level? 

Answer. FSIS’ inspection program personnel include the following primary occupations: 

—Food Inspection (slaughter), GS–5, career ladder GS–7 

—Consumer Safety Inspectors (processing), GS–8, career ladder GS–9 

—Consumer Safety Inspectors (relief positions), GS–10 

—Public Health Veterinary Medical Officers, GS–11, career ladder GS–12 

Under a more robust risk-based inspection system for meat and poultry processing, USDA will continue using the same number of inspection program personnel, spending the same amount of overall time conducting inspections. Riskbased inspection is about working smarter to protect public health by having inspection personnel spend more time in the processing plants that need assistance and 

expertise. 

A chart identifying the number of Food Safety and Inspection Service positions 

at headquarters and in field positions (1996–2006) follows: 

[The information follows:] 
112 

FOOD SAFETY AND INSPECTION SERVICE 

Actual Headquarters and Field Positions for 1996–2006 

Grade 

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 

Wash 

DC Field Wash DC Field Wash DC Field Wash DC Field Wash DC Field Wash DC Field Wash DC Field Wash DC Field Wash DC Field Wash DC Field Wash DC Field 

Senior Executive Service ... 16 5 23 1 20 1 21 .......... 21 .......... 19 2 19 2 21 .......... 26 .......... 25 1 25 1 GS–15 ............................... 44 9 45 30 45 30 57 25 51 25 52 25 51 26 59 27 60 26 59 32 58 32 GS–14 ............................... 89 44 100 48 100 48 102 49 93 46 94 46 103 58 107 72 98 72 130 87 128 85 GS–13 ............................... 212 246 215 347 215 347 248 297 232 283 248 301 221 331 228 351 208 369 293 406 240 394 GS–12 ............................... 91 956 148 939 148 939 106 935 81 874 91 883 93 889 108 960 97 1,027 117 1,058 97 1,027 GS–11 ............................... 67 387 28 463 28 463 36 406 35 345 42 329 34 384 44 304 32 280 53 260 45 253 GS–10 ............................... ....... 176 ....... 195 1 345 ....... 471 2 510 ....... 515 1 516 1 494 2 459 1 409 1 403 GS–9 ................................. 60 2,195 104 ,264 109 2,168 42 2,017 41 1,826 45 1,859 49 1,951 43 1,878 57 1,971 49 1,959 42 1,892 GS–8 ................................. 25 1,235 8 1,220 8 1,171 13 986 11 1,023 12 1,046 11 1,068 14 1,101 31 965 14 959 12 930 GS–7 ................................. 86 3,492 84 3,265 84 3,267 75 3,551 70 3,647 64 3,630 54 3,348 57 3,234 74 3,278 60 3,223 55 3,120 GS–6 ................................. 73 63 38 70 38 70 34 55 37 47 27 47 17 43 14 42 11 50 14 48 11 46 GS–5 ................................. 68 460 46 341 44 341 16 284 18 656 19 676 11 317 12 401 14 313 11 240 8 232 GS–4 ................................. 20 84 38 49 38 49 7 54 2 34 ....... 36 1 32 3 24 3 51 8 38 6 36 GS–3 ................................. 2 17 3 6 3 6 1 .......... ....... .......... ....... 21 1 20 2 19 1 1 ....... .......... ....... ..........GS–2 ................................. 2 2 ....... .......... ....... .......... ....... .......... ....... .......... ....... 1 ....... .......... ....... .......... ....... .......... ....... .......... ....... ..........GS–1 ................................. 2 1 ....... .......... ....... .......... ....... .......... ....... .......... .......Ungraded Positions ........... 2 19 2 24 1 22 1 23 ....... 23 ....... .......... ....... .......... ....... .......... ....... .......... ....... .......... ....... ..........

Total Permanent 

Positions ......... 859 9,391 882 9,262 882 9,267 759 9,153 694 9,339 713 9,417 666 8,985 713 8,907 720 8,863 834 8,720 728 8,451
113 

Question. In late October 2006, 493 beef carcasses at the Swift & Company plant 

located in Grand Island, Nebraska were inadvertently sprayed with sewage water. 

Instead of condemning the carcasses according to the provisions of 9 CFR 318.14, 

FSIS management officials instead approved a ‘‘rework’’ of the contaminated carcasses. Please explain the justification for this action. 

Answer. Under 9 CFR 318.2(d), USDA’s Food Safety and Inspection Service 

(FSIS) has historically considered offers to recondition product if it believes that an 

establishment can make the product safe for human consumption. I will provide 

more information on this particular action for the record. 

[The information follows:] 

In this case, the establishment developed an aggressive reconditioning plan based 

on relevant science, in close consultation with FSIS officials, and approved by FSIS. 

After reconditioning, extensive testing showed that, microbiologically, these carcasses had testing results equal to or better than carcasses normally processed at 

the facility. 

Question. The fiscal year 2008 budget proposal calls for the imposition of a licensing fee on all meat, poultry and egg production facilities within FSIS jurisdiction. 

Will the approximately 1000 foreign establishments that are eligible to export to the 

United States also be subject to such a licensing fee? 

Answer. No, foreign establishments eligible to export to the United States would 

not be subject to the proposed fee. USDA is recommending a fee for each Federally 

inspected establishment or official plant to partially cover the costs of USDA inspection services. 

Question. The fiscal year 2008 calls for the imposition of reinspection fees for all 

firms that are subject to failure of performance standards and/or recalls. Will foreign establishments that export to the United States be subject to reinspection fees 

when FSIS auditors find violations of U.S. standards? 

Answer. No. The proposal would not provide for charging fees to foreign establishments that export meat, poultry or egg products to the United States. FSIS may 

decertify foreign establishments, i.e., prohibit them from exporting meat, poultry or 

egg products to the United States, if it finds that they do not meet the requirements 

set forth in its regulations for imports. 

Question. What is the status of the study being conducted in Canada to justify 

less than daily inspection of processed meat and poultry products that are exported 

to the United States? 

Answer. The Canadians are continuing their study of less-than-daily inspection, 

and nothing has been submitted to USDA at this time. Once a study is completed, 

it will need to be peer reviewed and the data assessed by USDA. The Canadians 

will maintain daily inspection for any product exported to the United States until 

the study is completed and reviewed and a decision is made on how to proceed. 

Question. What is the Meat Safety Enhancement Program as it applies to meat 

imports from Australia? How does it differ from traditional inspection procedures? 

Have there been any Australian establishments approved to export meat products 

to the United States using MSEP? Are there any pending applications from any 

Australian meat establishments to use MSEP to export to the United States? If 

there are, what is the status of those applications? What criteria will FSIS use to 

make its final determination on the viability of those applications? 

Answer. Australia’s Meat Safety Enhancement Program (MSEP) is an alternative 

inspection program to Australia’s traditional slaughter inspection procedures, which 

rely solely on government-paid inspectors. MSEP differs from Australia’s traditional 

inspection approach by using both company inspectors and government-paid inspectors. It was developed by the Australian government patterned after the United 

States’ HACCP-Based Inspection Model Project (HIMP). USDA’s Food Safety and 

Inspection Service determined MSEP to be equivalent in 1999. While one MSEP establishment in Australia has applied for the ability to export its product to the 

United States, FSIS has not given approval until it completes its assessment of a 

pilot study carried out by the establishment and the Australian government and 

concurs that the food safety conditions established as part of the 1999 equivalence 

decision are being achieved. 

FSIS RISK BASED INSPECTION

Question. Please provide us an update on the FSIS announcement regarding its 

change to risk-based inspection. What is the ultimate goal of this change, and do 

you believe that FSIS has the right science and testing capabilities at this time, to 

do this safely? 

Answer. A risk-based inspection system will help USDA improve the safety of 

meat and poultry products from USDA-inspected processing establishments, and 
114 

therefore decrease the incidence of illness and deaths caused by foodborne pathogens. 

Since USDA’s Food Safety and Inspection Service (FSIS) inspection program personnel are in each plant every day, FSIS has the necessary scientific and testing 

data to institute a risk-based inspection system in processing establishments. In addition to considering the inherent risk of product, as well as its volume, FSIS will 

use seven key factors to specifically determine a plant’s ability to control risk: food 

safety recalls; verified food safety consumer complaints; noncompliance records that 

are significant to public health, enforcement actions FSIS has taken against establishments, ready-to-eat and E. coli O157:H7 sampling results, ready-to-eat Listeria 

monocytogenes control alternatives, and a plant’s Salmonella verification category. 

For more information on how FSIS will measure risk in 30 prototype processing establishments, visit the agency’s Web site at: http://www.fsis.usda.gov/Regulationsl&lPolicies/RBIlMeetingl040207/index.asp. 

Question. Do you currently have enough data on E. coli, Salmonella and Listeria 

testing, for example, to make sure that you are targeting the right plants, or are 

you still collecting it? 

Answer. The USDA’s Food Safety and Inspection Service (FSIS) has sufficient 

data to establish the plants’ ability to control risk, but the agency will continue to 

collect data on a daily basis. The data already on hand is historical, and the last 

12 months data can be used to calculate ability to control risk. The data the agency 

will collect in the future will give FSIS a snapshot of current conditions in establishments, as well as provide the agency with a measure of establishments’ ability to 

control risk that particular day. The data will allow FSIS to adjust plant inspection 

intensity in real-time, based on current data, thereby being more proactive instead 

of reactive by, for instance, increasing intensity after a recall. 

Specifically with regard to E. coli O157:H7, Listeria monocytogenes, and Salmonella sampling analysis, in calendar year 2003, FSIS conducted over 80,000 analyses of samples, and that number grew to almost 100,000 in CY 2006. These sampling data, particularly when combined with the other risk-based factors, provide 

FSIS with a very good picture of the food safety controls within regulated establishments. 

Question. Will risk-based inspection result in fewer food inspectors at processing 

facilities? 

Answer. Under a more robust risk-based inspection system for meat and poultry 

processing, USDA will continue using the same number of inspection program personnel, spending the same amount of overall time conducting inspections. Riskbased inspection is about working smarter to protect public health by having inspection personnel spend more time in the processing plants that need assistance and 

expertise. 

Question. What level of funding has been used so far to develop this program? 

Answer. FSIS has not dedicated a specific funding level for the risk-based inspection initiative. However, some of the recent expenditures for this effort include public meetings and technical summits, employee meetings, meetings with the National 

Advisory Committee on Meat and Poultry Inspection, a contract with Resolve Inc., 

and other miscellaneous items. 

Question. Please provide a detailed explanation of the evaluation FSIS will undertake of the pilot risk-based inspection program before expanding it to further plants. 

How will you measure success or failure, and what are the parameters of that determination? 

Answer. USDA’s Food Safety and Inspection Service (FSIS) intends to implement 

and review risk-based inspection for processing in a careful and deliberative manner. The perfect report card for the long-term would be a measured decrease of food 

borne disease and death. While FSIS is still in the process of developing how we 

intend to evaluate RBIS, in the near-term, FSIS will compare such measures as 

verified consumer food safety complaints, product recalls, and changes in the effectiveness of establishment risk controls between RBIS and traditionally-inspected establishments. In addition, FSIS will be interviewing inspection program personnel, 

and the USDA’s Office of Inspector General will be continuing to audit the development and implementation of RBIS. 

Question. What role is turning off the PBIS inspection task scheduler playing in 

risk-based inspection in processing? Have there been circumstances when the PBIS 

scheduler has been turned off within the past 5 years, and if so, please identify 

those circumstances and the reasons for them. 

Answer. The Food Safety and Inspection Service (FSIS) will no longer use the Performance Based Inspection System (PBIS) database scheduler in the initial 30 prototype processing locations under risk-based inspection. However, at that time, the 

agency will not discontinue the use of PBIS as a whole—only the scheduler. Proc-
115 

essing inspectors at the prototype processing locations will continue to report their 

findings into the PBIS system, and these data will be analyzed on an on-going basis. 

In 2000, FSIS allowed District Offices the option of not scheduling the inspection 

procedures to be performed in a plant on a specific day. This change recognized that 

some establishments operate seasonally, such as plants that specialize in seasonal 

or holiday meats; some operate infrequently, such as one day per week; and some 

prepare products for inspection by FSIS and by the Department of Health and 

Human Services’ Food and Drug Administration on different days. This policy saves 

inspection program personnel time, since they do not have to check a ‘‘not performed’’ box for a day when an establishment is simply not producing FSIS-inspected product. 

Question. The fiscal year 2008 budget proposal calls for the expenditure of funds 

during the last quarter of the fiscal year to cover the costs of training and relocation 

of staff when risk-based inspection in slaughter is implemented. How did the Agency arrive at those figures? Does the Agency anticipate reductions in staff when riskbased inspection in slaughter is implemented? 

Answer. The agency’s goal is to begin to implement risk-based inspection for 

young chickens at slaughter plants during the last quarter of fiscal year 2008. For 

that to happen, FSIS will need to have a final rule in place. 

Implementation of risk-based inspection in slaughter facilities is projected to require two weeks of training for Food Inspectors and one week for Consumer Safety 

Inspectors. Cost considerations include travel, per diem, supplies, and materials as 

well as backfill of frontline inspection personnel while employees are in training. 

These costs also include post-training meetings conducted by FSIS’ Technical Service Center employees to ensure consistent policy application. Other cost considerations include employee relocation expenses in accordance with Federal travel regulations. 

Risk-based inspection in processing establishments will not lead to reductions in 

the inspection program personnel workforce. Once it is implemented in the future, 

risk-based inspection for slaughter may result in a redistribution of the inspection 

workforce. 

Question. Does the Agency anticipate reductions in the overall inspection workforce as it implements both risk-based inspection in processing and slaughter? If it 

does, what role will attrition play in those reductions? Will the Agency be forced 

to reduce staffing through layoffs? 

Answer. Under a more robust risk-based inspection system for meat and poultry 

processing, USDA will continue using the same number of inspection program personnel, spending the same amount of overall time conducting inspections. 

Risk-based inspection for slaughter will likely result in a redistribution of the inspection workforce. Anyone who is employed by FSIS when risk-based inspection for 

slaughter is implemented and desires to keep working for the agency will continue 

to do so. Risk-based inspection is about working smarter to protect public health by 

having inspection personnel spend more time in the plants that need assistance and 

expertise. 

Question. What Notices and Directives has the Agency issued in preparation for 

the implementation of risk-based inspection in processing? What is the legal justification for implementing risk-based inspection in processing without the need for 

formal rulemaking or a change in existing statutes? 

Answer. As of February 27, 2007, USDA’s Food Safety and Inspection Service 

(FSIS) has not issued any directives, but will issue a directive to personnel regarding the implementation of risk-based inspection at the thirty prototype processing 

locations in order to instruct employees on how they are to perform daily tasks. In 

addition, before implementing the nationwide risk-based inspection system for processing, the agency will issue either an updated or new directive for personnel. I will 

have FSIS provide additional information explaining this rationale more thoroughly. 

[The information follows:] 

The Administrative Procedure Act (APA) (5 U.S.C. 511–599) is the law under 

which regulatory agencies, including FSIS create the rules and regulations necessary to implement and enforce the statute such as the Federal Meat Inspection 

Act, the Poultry Products Inspection Act, and the Egg Products Inspection Act. Section 553 of the APA, titled ‘‘Rule making’’ defines the procedures and specifies exemptions from rulemaking. Section 553(a) of the APA States that matters relating 

to agency management or personnel are not subject to rule making. Risk-based inspection does not place new regulatory requirements on establishments that will be 

subject to this new inspection management strategy. What risk-based inspection 

does is determine which inspection tasks are to be completed by FSIS inspectors for 

specific establishments. This is a matter of agency management, and so is not subject to rule making. 
116 

Even though rule making is not required, FSIS has engaged in, and plans to continue to engage in, a public, transparent development process in devising its new 

management strategy. The agency believes that public involvement by its stakeholders will yield the best results and the best positive effects on public health in 

the end. As FSIS gains practical insights from prototyping risk-based inspection, the 

agency plans to adapt the system to changing circumstances and its evolving understanding as to how best to manage inspection staff. 

Some of FSIS’ public participation activities used in the development of risk-based 

inspection include a two-day public listening session in October 2006, and three public sessions with the National Advisory Committee on Meat and Poultry Inspection 

to gather input. In addition, on April 2, 2007, FSIS will hold a public meeting to 

gather feedback on the proposed methodology to determine plant ability to control 

risk, and specifically how best to utilize noncompliance records. The agency will also 

hold another public meeting on April 5, 2007, to determine to how to improve attribution data. Public meetings are scheduled for April 25 and 30, 2007, to discuss how 

best to use establishment volume and establishment reported data, respectively, in 

the formulas for risk determination. 

Question. What is the status of the installation of the FSIS Automated Technology 

Suite (FACTS)? How is FACTS being used in the data collection for plants involved 

in the risk-based inspection in processing program? Please specify all the types of 

recorded data available to the Agency that will be considered in making decisions 

for risk-based inspection. For example, the Agency plans to use information on Noncompliance Records (NRs)—what specific information is available on a NR that will 

be factored into RBI decisions? 

Answer. The Food Safety and Inspection Service’s (FSIS) Automated Technology 

Suite (FACTS) applications have been incorporated into the Public Health Data 

Consolidation business case. When fully funded, this will allow FSIS to continue 

building an information technology system that is modernized to consolidate data 

into one data warehouse system and process and analyze this data through transactional systems. With this initiative FSIS will be able to gather data efficiently, 

increase data integrity and security, and expedite analysis of all FSIS data. 

The data from the processing plants that has already been gathered, along with 

risk-based inspection data to be gathered, will be stored and utilized through the 

data warehouse system described above. 

Since FSIS inspection program personnel are in each plant every day, the agency 

has the necessary data to institute an enhanced risk-based inspection system in 

processing establishments. In addition to considering the inherent risk of product, 

as well as its volume, FSIS will use seven key factors to specifically determine a 

plant’s ability to control risk: food safety recalls; verified food safety consumer complaints; noncompliance records that are significant to public health, enforcement actions FSIS has taken against establishments, ready-to-eat and E. coli O157:H7 sampling results, ready-to-eat Listeria monocytogenes control alternatives, and a plant’s 

Salmonella verification category. For more information on how FSIS will measure 

risk in 30 prototype processing establishments, visit the agency’s Web site at http:// 

www.fsis.usda.gov/Regulationsl&lPolicies/RBIlMeetingl040207/index.asp. 

FSIS FOOD INSPECTORS

Question. Please provide vacancy rates for food inspectors by district. Please provide a breakdown of FSIS inspectors and plant responsibility over the past 5 years. 

Answer. As of February 27, 2007, the inspection work force has increased by 139 

positions since the end of fiscal year 2006. These are potential new employees who 

have passed background checks, had satisfactory interviews, and have agreed to a 

start date. At any given time, the Food Safety and Inspection Service (FSIS) shows 

a vacancy rate due to a lag in hiring, attrition, difficulty in recruiting in some remote areas, difficulty in recruiting in some high income locations, and retirement. 

To meet current demand, FSIS projects that we would have 7,500 in-plant personnel 

by the end of the fiscal year. The information is provided for the record. 

[The information follows:] 

IN-PLANT OFF-LINE VACANCY DATA 1

[As of February 27, 2007] 

District Positions Employment Current Value 

Rate (percent) 

Alameda ..................................................................................................... 275.00 229.00 16.73

Denver ........................................................................................................ 278.00 253.00 8.99 
117 

IN-PLANT OFF-LINE VACANCY DATA 1—Continued 

[As of February 27, 2007] 

District Positions Employment Current Value 

Rate (percent) 

Minneapolis ................................................................................................ 185.00 167.00 9.730 

Des Moines ................................................................................................. 259.00 236.00 8.88 

Lawrence .................................................................................................... 227.00 206.00 1 9.25 

Springdale .................................................................................................. 313.00 286.00 8.63 

Dallas ......................................................................................................... 229.00 183.00 20.09 

Madison ...................................................................................................... 148.00 140.00 5.41

Chicago ...................................................................................................... 278.00 234.00 15.83 

Philadelphia ............................................................................................... 281.00 259.00 7.83 

Albany ........................................................................................................ 254.00 214.00 15.75 

Beltsville .................................................................................................... 190.00 170.00 10.53 

Raleigh ....................................................................................................... 261.00 233.00 10.73 

Atlanta ....................................................................................................... 333.00 297.00 10.81 

Jackson ....................................................................................................... 317.00 296.00 6.6296 

Total .............................................................................................. 3,828.00 3,403.00 11.10 

1 Talmadge/Aiken (T/A) plants are not included. 

ON-LINE (SLAUGHTER) VACANCY DATA 

[As of February 27, 2007] 

District Positions Employment Current Vacancy Rate 

Alameda ..................................................................................................... 209.00 175.00 16.27

Denver ........................................................................................................ 220.00 187.00 15.00 

Minneapolis ................................................................................................ 164.00 141.00 14.02 

Des Moines ................................................................................................. 413.00 373.00 9.69 

Lawrence .................................................................................................... 334.00 313.00 6.29 

Springdale .................................................................................................. 453.00 431.00 4.86 

Dallas ......................................................................................................... 337.00 309.00 8.31 

Madison ...................................................................................................... 104.00 90.00 13.46

Chicago ...................................................................................................... 169.00 141.00 16.57 

Philadelphia ............................................................................................... 142.00 126.00 11.27 

Albany ........................................................................................................ 33.00 25.00 24.24

Beltsville .................................................................................................... 275.00 255.00 7.270 

Raleigh ....................................................................................................... 504.00 456.00 9.52 

Atlanta ....................................................................................................... 509.00 450.00 11.59 

Jackson ....................................................................................................... 612.00 576.00 5.88 

Total .............................................................................................. 4,478.00 4,048.00 9.60 

Note: It is important to note that the total number of field inspection staff identified above cannot be compared with the total number of 

‘‘field staff’’ in an exhibit of FSIS’ fiscal year 2008 Explanatory Notes entitled: ‘‘Permanent Positions by Grade and Staff Year Summary –2006 

Actual and Estimated 2007 and 2008.’’ The field staff identified above relate to the inspection personnel whereas the ‘‘field staff’’ in the 

‘‘Permanent Positions by Grade and Staff Year Summary—2006 Actual and Estimated 2007 and 2008’’ exhibit relate to all FSIS staff outside 

of the Washington, D.C. area (e.g., Technical Service Center staff in Omaha, Nebraska, Financial Processing Center in Urbandale, IA, lab personnel in the three FSIS laboratories, etc.) 

INPLANT POSITION AND EMPLOYMENT FIVE YEAR HISTORY 1

On-Line Off-Line Enforcement, Investigation Analysis Officer/Compliance Officer Public Health 

Veterinariian/Veterinarian Medical 

Officer 2 Total 

Sla-07 CSI 08-10 

GS 12-13 GS 11-13 

Available Positions 

Fiscal Year 03 ................................. 3,952 3,491 189 992 8,624 

Fiscal Year 2004 ............................. 3,652 3,749 195 983 8,579 

Fiscal Year 05 ................................. 3,547 3,608 212 995 8,362 

Fiscal Year 06 ................................. 3,509 3,556 215 966 8,246 

Fiscal Year 07 2 ............................... 3,518 3,610 202 964 8,294 
118 

INPLANT POSITION AND EMPLOYMENT FIVE YEAR HISTORY 1—Continued 

On-Line Off-Line Enforcement, Investigation Analysis Officer/Compliance Officer Public Health 

Veterinariian/Veterinarian Medical Officer 2 Total Sla-07 CSI 08-10 

GS 12-13 GS 11-13 

Employment 

Fiscal Year 03 ................................. 3,310 3,226 189 838 7,563 

Fiscal Year 2004 ............................. 3,302 3,090 195 850 7,437 

Fiscal Year 2005 ............................. 3,217 3,150 188 831 7,386 

Fiscal Year 2006 ............................. 3,158 3,183 185 793 7,319 

Fiscal Year 20071A3 ........................ 3,147 3,181 183 772 7,283 

1 T/Apositions are not included.

2 Includes VMS. 

3 Current as of 2/27/2007. The end of fiscal year projected employment is 7,500. 

OTHER THAN PERMANENT—STAFF YEARS 

Years Usage 

2003 ..................................................................................................................................................................... 438 

2004 ..................................................................................................................................................................... 377 

2005 ..................................................................................................................................................................... 310 

2006 ..................................................................................................................................................................... 298 1 2007 ................................................................................................................................................................... 360 

1 Planned OTP usage. 

RISK MANAGEMENT AGENCY

Question. Is RMA developing any new products to serve regions of the country 

that currently have few, if any, options for risk management? If so, please explain 

them. 

Answer. The Risk Management Agency (RMA) has undertaken an evaluation of 

its product portfolio to identify gaps in availability, particularly with respect to underserved crops and/or regions. This evaluation found that, with few exceptions, 

crop insurance coverage is generally available for the most economically significant 

crops in the underserved regions. This result is consistent with the conclusions of 

a recent independent evaluation of RMA’s product portfolio. This suggests that RMA 

should place greater emphasis on improving currently available products to provide 

more effective risk management protection, and target efforts on the development 

of new products towards filling the few remaining gaps. RMA is currently conducting comprehensive evaluations of several crop programs to identify areas for improvement, particularly among underserved regions. 

In addition, RMA has implemented several new products, most notably Adjusted 

Gross Revenue (AGR), Adjusted Gross Revenue-Lite (AGR-Lite), and two Pasture, 

Rangeland and Forage (PRF) pilot programs. The AGR, AGR-Lite and PRF programs are particularly oriented to producers for whom traditional crop insurance 

products were either impractical, or did not provide effective risk management protection. In addition, over twenty pilot programs are currently active that pertain to 

specialty crops, including pilot programs for processing chili peppers, Hawaii Tropical Fruit, and Florida Fruit Trees. RMA also has ongoing development efforts for 

a revenue insurance product for certain specialty crops, as well as an umbrella 

weather-peril product that could provide effective coverage for certain crops with 

relatively limited market value. Additional risk management tools are developed 

through partnership agreements that impact underserved producers. These partnership agreements deal with a wide range of topics including the development and understanding of markets, pest and disease control, and water management. 

The Crop Insurance Board also accepts private sector submissions that allows persons to develop and submit for approval their own products targeted to specific risk 

management needs. 

NATIONAL ANIMAL IDENTIFICATION SYSTEM

Question. What is the status of the development of a National Animal Identification System? 
119 

Answer. The National Animal Identification System is composed of three components: premises registration, animal identification, and animal tracing. Premises 

registration is the foundation of the program. As of March 12, 2007, all 50 States, 

60 Tribes, and 2 U.S. Territories are capable of registering premises according to 

USDA standards, and approximately 378,000 locations have been registered. 

Significant progress has also been made on the second component of NAIS, animal 

identification. As of March 12, 2007, approximately 1 million Animal Identification 

Number devices have been distributed. 

The third component of the NAIS, animal tracing, is currently under development 

with the help of USDA’s industry and State partners. Industry, through private systems, and States will manage the animal tracing databases that maintain the movement records of animals. Full deployment of the Animal Trace Processing System 

is planned for the near future. 

Question. If such an animal identification system is made voluntary, what effect 

does APHIS anticipate that will have on participation? What efforts will be made 

to encourage participation? 

Answer. Participation in the NAIS is voluntary. The USDA remains committed 

to building upon our strong partnership with the States and industry to meet producers’ needs and establish a versatile system that makes sense for everyone. 

Moving forward with this voluntary approach has allowed producers the opportunity to test the program and recommend the most practical solutions for a more 

effective system. In this sense, producers themselves are playing an active role in 

helping to shape the NAIS program so that it works well for their particular needs. 

Additionally, a voluntary NAIS allows for the best price competition between service 

providers (identification device manufacturers, database providers, etc.) and leaves 

room for market applications (such as age/source/process verification) to help drive 

the system. 

To encourage participation, USDA has provided funding to facilitate development 

and implementation of an efficient system, and flexibility to adapt to producers’ operations and needs. On February 2, 2007, USDA published a request for proposals 

from nonprofit organizations that wish to enter into cooperative agreements with 

USDA to advance premises registration. USDA will make up to $6 million available, 

subject to the availability of funding, for the cooperative agreements. These cooperative agreements will support the efforts of such organizations to promote the NAIS 

and, specifically, increase participation in premises registration—the foundation of 

the program. 

INVASIVE SPECIES

Question. Please provide a list of current plant and animal invasive species, 

ranked by their threat level. What is APHIS’ short and long-term plans to deal with 

these? 

Answer. The Administration has not ranked invasive species by threat level. 

Invasive species that APHIS addresses include, but are not limited to, the programs 

focused on cattle fever tick, Mediterranean fruit fly, emerald ash borer, potato cyst 

nematode, sudden oak death, citrus diseases, brucellosis, pseudorabies, and chronic 

wasting disease. APHIS addresses each of these threats as resources allow. 

Over the long term, APHIS develops response plans for exotic pests and diseases 

that have the potential to cause significant economic or environmental damage and 

uses its safeguarding system, which involves prevention, detection, and management components, to protect U.S. agriculture. Under the Pest and Disease Exclusion 

mission area, APHIS works to prevent exotic pests such as cattle fever tick and 

Mediterranean fruit fly from entering the United States. These and other pests have 

direct pathways into the United States. APHIS takes action at U.S. borders or in 

other countries to mitigate the risks associated with them. 

Under the Monitoring and Surveillance mission area, APHIS conducts plant pest 

surveys, animal health surveillance, and other activities designed to detect exotic 

plant pests and foreign animal diseases if they are present so that we can deal with 

them quickly if needed. These programs target a changing list of high-risk plant 

pests depending on trade and travel pattern and outbreaks in other countries. These 

programs also conduct intensive monitoring and emergency preparedness efforts. 

APHIS analysts follow animal and plant health situations around the world and frequently adjust monitoring and surveillance efforts and pest and disease exclusion 

priorities to safeguard U.S. agriculture and natural resources from high-risk pests 

and diseases. 

APHIS also works to control or eradicate high priority invasive species through 

programs in the Pest and Disease Management area, including, but not limited to, 
120 

emerald ash borer, potato cyst nematode, sudden oak death, several citrus diseases, 

brucellosis, pseudorabies, and chronic wasting disease. 

AGRICULTURAL MARKETING SERVICE

Question. We have heard several reports of genetically modified material getting 

into crops intended for commercial sales, the most well-known being rice. What has 

the economic effect been of instances such as this? 

Answer. The economic effect can be reductions in seed available for planting and 

potential trade restrictions. For example, two popular long grain rice varieties can 

no longer be planted for commercial production due to the presence of genetically 

modified material. The value of certified seed of these varieties produced in 2006 

for planting in 2007 is estimated to be $39 million. 

GENETICALLY MODIFIED MATERIALS IN COMMERCIAL CROPS

Question. How is AMS, and USDA overall, working to prevent the introduction 

of genetically modified materials into crops intended for commercial sales? 

Answer. The Animal and Plant Health Inspection Service (APHIS) is involved in 

regulation of the biotechnology industry. Various measures are used in authorized 

field tests to ensure that genetically engineered organisms are confined to the test 

site. The measures include isolation distances to mitigate cross pollination with 

other crops and weedy relatives, cleaning of farm equipment to mitigate the inadvertent spread of seed, timely disposition of the field test, and post-harvest monitoring for volunteers. To ensure compliance, inspections of the test site, facilities, 

and records are conducted. Once a crop is deregulated, that crop is considered no 

different than conventional crops and may be planted without restrictions from 

APHIS. 

For organic products, regulations of AMS’ National Organic Program prohibit the 

use of genetically modified organisms in organic production. Accredited certifying 

agents review organic production and handling plans before certified organic production begins to ensure that no genetically modified organisms are used in production 

and that handling procedures protect organic products from contact with genetically 

engineered materials. Penalties are in place for intentional disregard of the regulations. 

VALUE-ADDED GRANTS

Question. Funding has been provided for Value-Added Agricultural Product Market Development Grants since the Agricultural Risk Protection Act of 2000. Ample 

time has elapsed to evaluate the effectiveness of this program. 

Please describe the types of products that have been funded. 

Answer. A wide variety of projects are funded, including value added products 

made from meat, dairy products, grains, fruits and vegetables, oilseeds, and renewable energy sources. Grant funds totaling $150,000 were used as working capital for 

the start up phase of a new tilapia production facility where the fish will be raised 

and processed into fillets. Other types of products include wine, compost made from 

diary waste, wind energy, soy-flour, identity-preserved yogurt, dehydrated apple 

slices, and branded cuts of beef. 

Question. Are these products becoming marketable and sustainable? 

Answer. Information about the long-term sustainability became available early 

this year from a study that the University of Missouri has done. The study indicates 

that approximately 60 percent of the projects funded resulted in a marketable product. 

Question. What are the outcome measures that are being used to determine the 

success of this program? 

Answer. Several measures evaluating the program are in place, including the 

number of jobs created, the increase in producer revenue due to the project, the increase in customer base due to the project, and the sustainability of the business 

receiving the grant. 

Question. How many grants and how much funding has been provided to energyrelated projects? 

Answer. Since 2001, 155 grants have been made for energy-related projects, totaling $25.2 million. 

Question. How successful are these energy-related projects and how do you define 

success? 

Answer. We define the success of energy-related projects in the same way as for 

other project types—we consider any project that resulted in a marketable product 

to be successful. We estimate that approximately 48 percent of energy related 
121 

projects resulted in a marketable product. This compares to 60 percent success in 

projects over all for the value added program. 

QUESTIONS SUBMITTED BY SENATOR TOM HARKIN

AGRICULTURE QUARANTINE AND INSPECTION

Question. In 2002, agriculture inspectors who protect our Nation from invasive 

species and pests at ports of entry were transferred from USDA to the Department 

of Homeland Security (DHS). Consequently, now USDA is responsible for creating 

the policy for agriculture inspections at ports of entry but DHS is responsible for 

the implementation of that policy. 

Secretary Johanns, can you tell me how much control USDA still has over the agriculture inspectors at ports of entry? 

Answer. In order to fulfill the requirements of the Homeland Security Act of 2002, 

USDA and DHS entered into a memorandum of agreement (MOA) which specified 

the roles of the Animal and Plant Health Inspection Service (APHIS) and the Customs and Border Protection (CBP). Through this MOA, CBP conducts the majority 

of the front line activities. APHIS provides training, risk assessment, and technical 

support. 

Question. A Government Accountability Office (GAO) report that came out last 

year noted that agriculture inspectors’ morale is low, their rates of interception of 

potentially harmful material is low, and that there are fewer canine units performing inspections. Can USDA do anything to improve these problems, or is this 

responsibility now entirely in the hands of DHS? 

Answer. After the issues were highlighted by GAO, the Animal and Plant Health 

Inspection Service within USDA and the Customs and Border Protection within 

DHS instituted quarterly face-to-face meetings. These meetings occur at both the 

technical level and managerial level. These meetings ensure transparency and are 

a forum for addressing present and future issues. 

Question. What would be the positive and negative impacts in transferring these 

inspectors back to USDA from DHS? 

Answer. The USDA supports the President’s decision to transfer inspectors from 

the USDA to DHS. This decision allowed for the creation of a consolidated border 

inspection organization which provides information sharing, streamlined services, 

cross-training among specialists, and innovative techniques that were not possible 

when border inspection was the responsibility of three separate agencies. Rather 

than limiting agricultural inspection to a relatively small cadre of specialized inspectors, DHS greatly expanded the number of inspectors who can screen air passengers 

and vehicles at land border crossings for prohibited agricultural products. 

U.S. FOREIGN FOOD ASSISTANCE

Question. As a result of continuing food crises in Africa and elsewhere, Congress 

has been obliged to provide additional emergency funding for Title II international 

food aid above and beyond appropriated levels for the last several years. 

Why has the Administration been unwilling to acknowledge that increased demand for emergency food assistance has persisted, and not requested funding above 

the recent levels of $1.2 billion for Title II in the fiscal 2008 budget proposal? 

Answer. The 2008 budget request reflects a careful prioritization among the competing demands for international humanitarian assistance. It is also important to 

understand that emergency food needs are difficult to predict in advance, especially 

given the complex nature of evolving, rapidly changing conflicts and the unpredictability of rainy seasons in drought-prone areas. 

Nevertheless, the 2008 budget does support our commitment to addressing the 

most severe and critical emergency food aid needs. And should unanticipated needs 

arise, the Bill Emerson Humanitarian Trust is available to ensure we can respond 

to them. 

Question. The USDA policy with respect to the Bill Emerson Humanitarian Trust, 

at least as indicated in the budget summary document for fiscal 2008, is that up 

to 500,000 tons of food is available annually for unanticipated emergency food assistance. Since the Emerson Trust now has commodity reserves of about 800,000 

tons, that would last less than 2 years. When does the Administration plan to ask 

for funds to replenish the Trust? 

Answer. The Trust currently holds 915,000 metric tons of wheat and $107 million 

of cash. Based on a current price of hard red winter wheat of about $216 per metric 

ton, that cash equates to approximately 495,000 metric tons of wheat. That amount, 

combined with the 915,000 metric tons of wheat held in the Trust, provides a total 
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tonnage of just over 1.4 million metric tons. Wheat is not the only commodity that 

might be needed in an emergency, of course, but because it is used so frequently 

in overseas feeding programs, it provides a good illustration of the level of the 

Trust’s resources. 

At this time, the Administration is not planning to request funds to replenish the 

Trust. However, in 2 recent years, $20 million was transferred annually from the 

Public Law 480 program to the Commodity Credit Corporation as reimbursement 

for commodities previously released from the Trust, and those funds were, in turn, 

assigned to the Trust. The Administration may consider future transfers of Public 

Law 480 funds that can be used to replenish the Trust, but current statutory authorities preclude annual reimbursement and replenishment above the $20 million 

level. 

CROP INSURANCE

Question. Wouldn’t the Department’s request to utilize mandatory funds to cover 

data mining and computer hardware costs cover some of the same costs that the 

user fee proposal would pay for? 

Answer. No. The data mining operation is conducted on separate IT systems than 

those that would be funded through the user fee proposal. The existing IT system 

used by the Risk Management Agency (RMA) is outdated and is not capable of conducting the data mining activities. Consequently, RMA contracts with Tarleton 

State University to perform the data warehousing and data mining activities mandated by Congress. 

NATIONAL VETERINARY MEDICAL SERVICES ACT

Question. In 2003 Congress passed the National Veterinary Medical Services Act 

to address the shortage of large animal veterinarians across the country. Four years 

later the regulations have yet to be issued for this program even though Congress 

has appropriated $1 million for the program. At last year’s agriculture appropriations hearing, you said the regulations would be done in 18 months. 

When can we expect to see USDA release the regulations for this program? 

Answer. We plan to publish a Final Rule delegating the National Veterinary Medical Services Act program to CSREES in the Federal Register on March 19, 2007. 

Although there are additional administrative steps that must be completed prior to 

the distribution of funds, a framework for the program has been developed by 

CSREES. 

CONSERVATION SECURITY PROGRAM

Question. As part of the Continuing Resolution for fiscal year 2007, it is my understanding that the CSP includes a funding cap that will result in farmers and 

ranchers receiving a pro-rated reduced payment for contract modifications, which 

they are required to complete despite reduced payment. 

How much of a reduction from the contract level will producers have to accept? 

Is there consideration of giving farmers the option of delaying their compliance with 

the modified contract if the Federal Government is not living up to its side of the 

bargain to make payment? If a farmer receives a partial CSP payment this year, 

will USDA pay the rest of the balance next year (or out of any supplemental funding 

provided in fiscal year 2007)? 

Answer. Unmodified contracts and those that were modified but did not exceed 

their 2006 payment level, are fully funded in 2007. Participants with 2007 contract 

obligations that exceeded their 2006 level will receive just over half of the amount 

above what they received in 2006. 

If the producer is not in compliance with the modified contract, the State Conservationist has the flexibility, on a case by case basis, to make adjustments to the 

participant’s contract. 

CSP is annually funded and payments will be made up to the level of funding 

made available by Congress. 

APPROPRIATE TECHNOLOGY TRANSFER FOR RURAL AREAS

Question. In 1985, Congress authorized the implementation of a sustainable agriculture information service, Appropriate Technology Transfer for Rural Areas 

(ATTRA), to provide technical assistance and information to farmers, ranchers, extension agents, educators and others involved in sustainable agriculture. ATTRA 

now supports more than 20 agricultural specialists working in six locations across 

the Nation. I strongly urge USDA to not consider ATTRA an earmark given it was 

authorized in the 1985 farm bill. 
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What will USDA do to ensure ATTRA’s funding level remains intact for fiscal year 

2007? 

Answer. Under the first Continuing Resolution $936,000 was obligated in 2007 for ATTRA compared to about $2.5 million that was provided in 2006. The revised Continuing Resolution reduced funding for rural cooperative development grants and no 

further funding was provided for ATTRA. No funding is included in the 2008 budget 

request for ATTRA, although the budget request does include funding for similar 

competitive grants. 

QUESTIONS SUBMITTED BY SENATOR BYRON L. DORGAN

ARS RESEARCH FUNDING

Question. Secretary Johanns, in your statement you describe how the President’s 

fiscal year 2008 budget request for USDA meets the challenges of the agricultural 

community by ‘‘funding our highest, most important priorities.’’ That is why I was 

disappointed to see harsh cuts to important agricultural research across the country, 

particularly in North Dakota. 

The President’s fiscal year 2008 budget cuts research at the Fargo and Mandan 

ARS Centers. These cuts include research into wheat and barley scab, sclerotinia— 

a white mold disease that wilts or rots broadleaf crops, and precision agriculture. 

Can you please explain why these research programs are singled out for cuts in 

the fiscal year 2008 budget? 

Answer. The 2008 Budget for ARS proposes to discontinue funding for a number 

of research projects added by Congress that provide mostly localized benefits and 

do not have a nationwide impact. Doing so will enable the Department to focus limited resources on higher priority research and on addressing important national 

goals such as emerging and exotic diseases of plants and animals, renewable energy 

and obesity. 

NATIONAL ANIMAL HEALTH LABORATORY NETWORK FUNDING

Question. The National Animal Health Laboratory Network (NAHLN) was established to create a greater infrastructure that enabled a rapid and adequate response 

to animal health emergencies. In addition to protecting animal health and the agriculture industries, these labs also play an important role in protecting public health. 

The Network was started with 12 ‘‘pilot labs’’ around the country, and has since 

been expanded to include diagnostic labs from virtually every State. My State of 

North Dakota is a full partner in the network and is certified to respond in four 

areas, including avian influenza (AI), exotic Newcastle disease (END), foot and 

mouth disease (FMD), and classical swine fever (CSF). 

Of the funding provided for the NAHLN, some goes to maintain the 12 pilot labs, 

and the rest is distributed to some of the remaining diagnostic labs. It appears that 

there are inadequate resources going into the NAHLN to adequately fund all participating labs or support the infrastructure that was created. 

Will the President’s fiscal year 2008 budget request for NAHLN support some operating or structural costs of each participating diagnostic lab (as supported by the 

American Veterinary Medical Association, the American Association of Veterinary 

Laboratory Diagnosticians, and the National Institute for Animal Agriculture)? 

Answer. The NAHLN is a cooperative effort between the Animal and Plant Health 

Inspection Service (APHIS) and the Cooperative State Research, Education, and Extension Service (CSREES). CSREES provides infrastructure support to the 12 

NAHLN pilot labs, while APHIS provides infrastructure support to other laboratories in the network as funds become available. 

APHIS’ fiscal year 2008 budget request will support upgrading three laboratories 

to biosafety level (BSL)-3 requirements. The agency is currently conducting disease 

risk assessments to determine the highest priority labs for the upgrade. The assessment will determine those areas that have the greatest risk of the introduction of 

a disease for which diagnostics would require this level of bio-security. 

QUESTIONS SUBMITTED BY SENATOR RICHARD J. DURBIN

FRESH FRUIT AND VEGETABLE PROGRAM IN SCHOOLS

Question. With the President’s Budget request, how many new States will be able 

to join the Fresh Fruit and Vegetable Snack Program this year? 

Answer. The Department is not proposing to expand the Fresh Fruit and Vegetable Program. Instead, our Farm Bill proposal would increase mandatory spending 
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for fruits and vegetables in the National School Lunch and School Breakfast Programs by $500 million over 10 years. In addition, the Farm Bill proposal would increase section 32 spending on fruits and vegetables by $2.75 billion over 10 years, 

some of which would likely go to schools. The Department considered a range of approaches to increase the availability of fruits and vegetables in schools, and ultimately selected this approach because it has the potential to increase fruit and vegetable access to the greatest number of school children. 

The Administration is committed to increasing fruit and vegetable consumption, 

given their importance to health and the specific recommendations of the Dietary 

Guidelines for Americans. Increased funding for fruits and vegetables in the school 

programs will help support the Administration’s implementation of the 2005 Dietary 

Guidelines for Americans in the more than 31 million lunches served every school 

day. 

Question. Is there a set of selection criteria at USDA for admittance to the program? 

Answer. Almost all of the States currently participating in the Fresh Fruit and 

Vegetable Program were designated by Congress. Since the Department is not proposing to expand the Fresh Fruit and Vegetable Program, we have not developed 

selection criteria for additional States. 

Question. Which States are poised to be accepted to the program soonest? 

Answer. The Department is aware that a number of additional States have expressed interest in participating in the Fresh Fruit and Vegetable Program. The 

program has been well received by students and by State and local school administrators in those places where it currently operates. However, we believe that the 

policy emphasis is best placed on our Farm Bill proposals. The Administration’s 

Farm Bill proposals have the potential to increase fruit and vegetable access to 

school children in every State. 

BROADBAND AND DISTANCE LEARNING AND TELEMEDICINE FUNDING

Question. The President’s Budget decreases funding for the set of broadband programs housed at USDA Rural Utilities Service (RUS). The budget proposes to cut 

the Distance Learning, Telemedicine, and Broadband Program from $85 million in 

2006 (actual) to $31 million (fiscal year 2008 Budget). Grants are cut from $70 million in fiscal year 2006 (actual) to $25 million (fiscal year 2008 Budget). Total direct 

loan levels are decreased from $1.155 billion in fiscal year 2007 (estimated) to $300 

million (fiscal year 2008 Budget). Direct loans for distance learning and telemedicine are eliminated entirely, from a level of $156 million in fiscal year 2007 (estimated). 

Can you explain the reasons why funding levels for these programs were decreased? 

Answer. The distance learning and telemedicine program has received only a few 

applications for loans since the program was established a number of years ago. The 

2008 budget maintains the grant portion of the program at its current level of about 

$25 million although it does not include funding for other broadband grant programs for which about $20 million is available for 2007. The 2008 budget also includes funding for $300 million in broadband loans which is expected to be enough 

to meet the needs of those rural communities that have no or only limited access 

to broadband services. 

Question. How do these decreases fit within the President’s stated policy objective 

of making broadband universal and affordable by 2007? 

Answer. USDA is providing a sufficient level of funding to meet the expected demand for loans. Moreover, program regulations are being revised to focus on areas 

that do not already have existing broadband providers. These revisions are expected 

to improve the performance of meeting the President’s goal of universal and affordable service budget. 

Question. Are there alternative funding streams or mechanisms in the President’s 

Budget that make up for these decreased funding levels? 

Answer. Currently the USDA’s telecommunication loan programs finance technology that supports Broadband ready capabilities. Further, the Administration’s 

2007 Farm Bill proposal addresses the need for enhancing rural infrastructure by 

providing an additional $500 million over 10 years. Both the broadband access and 

the distance learning and telemedicine programs are included among the programs 

that would be eligible for this funding. 

Question. Last, have you heard of Connect Kentucky’s work mapping broadband 

networks and increasing build out and demand in rural areas, and would you be 

interested in looking at ways the Department could work to facilitate similar work 

in other States and regions? 
125 

Answer. I understand that Connect Kentucky was recently recognized by the Economic Development Agency for excellence in innovation. It is a model for State-wide 

commitment for using technology to address economic opportunities and quality of 

life. Most importantly, it has an advisory board consisting of a wide range of public 

and private sector partners. I would encourage anyone with an interest in rural development to visit its website for more information. 

RURAL DEVELOPMENT HOUSING PROGRAMS

Question. The President’s Budget contains significant modifications to the rural 

housing programs run through USDA Rural Development (RD). 

Can you please provide detailed information to assure me that USDA RD’s overall 

loan activity in the area of housing would not decrease if these policy proposals were 

enacted into law? 

Answer. The 2008 budget provides for over $5 billion in housing loans, which is 

slightly higher than the amount available for 2007. In 2007 the total single family 

housing homeownership lending available was $4.7 billion ($1.1 billion for direct 

loans and $3.6 billion for guarantees). Historically, RHS has offered both direct and 

guaranteed homeownership loans. Beginning in 2008 however, RHS will only offer 

guaranteed loans. The budget provides no funding for the 502 direct single family 

housing loan program, but total lending for single family housing homeownership 

loans will be $1 million higher then in 2007 at $4.8 billion. The direction of Rural 

Development’s single family housing mortgage assistance over the last two decades 

has been towards guaranteed loans. Solely utilizing guarantees for single family 

housing mortgage is consistent with the other Federal homeownership programs. In 

fact, there are no Federal single family direct loan homeownership programs for 

urban areas. 

Furthermore, financial markets have become more efficient and increased the 

reach of mortgage credit to lower credit qualities and incomes. While there are still 

rural areas with ‘‘pockets of need’’, these areas are shrinking as improvements and 

innovations in the banking industry take hold, use of Fannie Mae and Freddie Mac 

grows, and lending through the internet have become more prevalent. Therefore, 

utilizing the private banking industry to provide this service, with a guarantee from 

the Federal Government, is a more efficient way to deliver that assistance. 

The demand for Rural Development’s single family housing guaranteed loan program has been consistently strong both among borrowers and private lenders. We 

have no reason to expect a change to this in 2008 and are confident that with the 

requested level of funding for guaranteed loans, RHS will be able to facilitate the 

dream of homeownership to more rural residents than we did in 2007. 

Question. What motivated the policy proposal of decreasing direct loan activity to 

the area of guaranteed loans—are there differentials in default rates or other operational aspects that inspired the policies? 

Answer. No other Federal agency offers direct loans for single family housing. So 

the decision was made to conform to a consistent Federal policy on the type of assistance to provide in promoting homeownership. Further, guaranteed loans have 

accounted for almost all the growth in our program activity since the mid 1990’s 

and borrowers with very low and low incomes account for 30 percent of this activity. 

Default rates for both direct and guaranteed loans have been relatively low, although this was not a factor in the decision. 

Question. Currently, what is the difference in the terms and rates offered to applicants on average through the direct loan versus the loan guarantee program, and 

would the President’s policies negatively affect RD housing loan applicants? 

Answer. In short, the difference is that interest rates on direct loans may be subsidized down to 1 percent and there are no fees, while the interest rates on guaranteed loans reflect the market rate and there is a one-time fee which is currently set 

at 2 percent and proposed to be increased to 3 percent in the 2008 budget. 

USDA recognizes that guaranteed loans are more costly to borrowers than direct 

loans and is examining alternatives for proposed legislation to provide a subsidy to 

soften the difference. Specifically to help replace the loss of assistance for mortgage 

credit from the direct loan program, the Administration expects to propose legislation to authorize a subsidized guaranteed single family housing program. 

CONSERVATION RESERVE PROGRAM

Question. In terms of conservation, the Budget proposes to eliminate new enrollments in the Conservation Reserve Program (CRP) in 2007 and 2008. The economics 

of high commodity prices will play a significant role in landowner decisions to reenroll in the program. 
126 

Given these higher prices and higher motivation not to participate in CRP as well 

as the Administration’s 2007 Farm Bill conservation recommendations, why is the 

Administration proposing no new sign ups in 2007 and 2008? 

Answer. As you point out, higher commodity prices will probably dissuade many 

landowners from participating in the CRP. For this reason, the Administration’s 

budget baseline does not assume a general sign-up for 2007 or 2008. However, continuous sign-up of high-priority buffers, wetlands and other initiatives, as well as 

the Conservation Reserve Enhancement Program, will continue and USDA encourages farmers and ranchers to consider these opportunities. We are closely monitoring interest in CRP re-enrollment, planting projections, and supply-demand situations for various commodities to determine the most appropriate future actions in 

administering the CRP. 

NRCS TECHNICAL ASSISTANCE FUNDING

Question. Also, I have been concerned to see USDA Natural Resources Conservation Service (NRCS) technical assistance (TA) funding decrease. The fiscal year 2008 

Budget proposes to cut TA from $708 million in fiscal year 2007 (estimated) and 

$727 million in fiscal year 2006 (actual) to $689 million in fiscal year 2008 (proposed). 

How is NRCS supposed to support higher program activities when its TA allocation is being cut? 

Answer. Higher priority program activities within NRCS will continue to be supported in 2008. The decrease in conservation technical assistance (CTA) that you 

reference in your question represents amounts for Congressional earmarks in the 

CTA account and reflects the realignment of the Administration’s conservation priorities. 

It should be noted that NRCS also provides technical assistance to producers 

through other discretionary programs as well as through mandatory programs authorized in the current Farm Bill. Our 2007 Farm Bill proposals significantly increase funding for conservation programs and include the technical assistance component needed to implement these programs. 

BSE SURVEILLANCE

Question. In 2004, USDA boosted BSE testing. Over a period of 18-months, a total 

of 759,000 cattle were tested and two additional cases of BSE were detected. USDA 

has relied on this data to prove that BSE is rare in the United States; however, 

USDA’s Inspector General criticized the expanded testing program. The IG noted 

that because the expanded program was voluntary, the testing might not have captured a representative sample of the Nation’s herd. 

Last year, USDA announced plans to scale back BSE testing by 90 percent and 

based its decision on the results of the expanded testing program. 

With 35 million cattle slaughtered for the U.S. food supply each year, how can 

testing only 40,000 cattle each year be sufficient to detect BSE? 

Answer. The expanded surveillance effort, which was biased toward finding the 

disease, was designed to estimate the level of disease presence in the United States 

and provide input for designing a long-term surveillance plan. USDA has now developed such a plan. USDA has the ability to detect BSE at 1 infected animal per 

1,000,000 adult cattle with a high degree of confidence. This ability far exceeds the 

international standards set by the World Organization for Animal Health (OIE). 

QUESTIONS SUBMITTED BY SENATOR BEN NELSON

DISASTER ASSISTANCE

Question. The Administration has worked to block each and every emergency disaster assistance funding legislation we have attempted in the Senate and it has consistently argued against the need for such assistance. As I look through the President’s budget proposal and the USDA budget justifications I am struck by two 

things: first, that there is practically no funding for drought and disaster assistance; 

and second, there is no funding for efforts to mitigate the devastating impacts of 

droughts and disasters. 

As such, I have to ask what the Administration proposes to do, or expects to see 

happen, with regard to the many farmers and ranchers that continue to suffer from 

drought? 

Answer. The Federal crop insurance program is intended to be, and should remain, our foremost tool to assist farmers and ranchers impacted by natural disas-
127 

ters of all types. The Administration’s budget request fully funds the Federal crop 

insurance program. 

In addition, this Administration has responded, with appropriate forms of assistance, to mitigate losses resulting from drought and other forms of disaster. However, this assistance has been crafted to specifically target producers directly impacted by adverse weather conditions. For example, the Administration developed 

the Livestock Assistance Grant Program (LAGP) which provided $50 million in 

State block grants to help livestock producers recover forage production losses due 

to drought conditions during 2006. Furthermore, I would note that the assistance 

provided by this Administration has been provided within our available resources. 

Accordingly, this Administration would strongly urge Congress to fully offset the 

cost of any ad hoc disaster assistance with commensurate reductions in other agricultural spending. 

Question. And, if the Administration is so opposed to providing emergency disaster aid why does it completely fail to provide funding to help mitigate the impacts 

from droughts and natural disasters? 

Answer. The President’s budget request for 2008 was prepared on a parallel track 

with the Administration’s 2007 Farm Bill proposals. Taken together, these two documents provide for both disaster assistance and disaster mitigation. The 2008 budget request fully funds the Federal crop insurance program which is intended to be 

the primary tool for providing disaster assistance. In addition, a key farm bill proposal would improve the counter-cyclical payment (CCP) program by basing payments on revenue rather than price. Crop prices tend to be at their highest following a disaster. Under the current design of the CCP program high commodity 

prices means that producers are not eligible to receive a CCP payment. However, 

this is precisely the time when producers need the payments the most. Producers 

cannot benefit from high commodity prices if they have no commodity to sell. Our 

farm bill proposal would correct this situation by providing an effective means of 

mitigating the financial effects of a disaster. 

USDA RENEWABLE ENERGY AND BIOFUELS INVESTMENT

Question. I applaud the Administration’s multiple investments in renewable fuels 

and biofuels in the fiscal year 2008 budget, but I am concerned that we are not 

doing enough to help this important industry progress as expeditiously as possible. 

Can you explain what the goals are for the renewable energy and biofuels investments in this budget? 

Answer. The energy goals of this budget are to expand research and development 

of potential bioenergy sources and to encourage commercialization of production facilities and infrastructure by increasing the production of renewable energy, particularly biofuels from cellulosic feedstocks. USDA will focus primarily on research and 

development of innovative processes that are cost-effective and energy efficient, and 

financial support aimed at advancing commercial applications to facilitate sufficient 

amounts of private sector investment. 

Question. What achievements can we expect to see and when can we expect to 

see them? 

Answer. Ultimately, we expect to develop and encourage the adoption of technologies for commercially viable, low cost and energy efficient production of cellulosic ethanol. This includes the development of commercially-viable, value-added 

co-products. This achievement will be reached when cellulosic energy is a vital component of the Nation’s energy production as was highlighted by the ‘‘20 in 10’’ initiative in the President’s State of the Union address. Even though commercial viability 

of cellulosic ethanol may be several years off, the Department has already achieved 

numerous advances that will contribute to this ultimate goal. Included in these advancements are innovations in cellulosic feedstock development and research into 

energy conversion techniques. 

Question. In what ways do the various proposals for renewable fuels complement 

each other—both within the USDA budget and across budgets with other agencies 

such as the Department of Energy? 

Answer. USDA has the scientific expertise for conducting and administering research programs relating to all aspects of crop production, including post harvest 

usage of crops. Consequently, it is ideally suited to address these aspects of advancing the Nation’s biofuel industry. Moreover, USDA’s Rural Development mission 

area has the experience and capacity to provide financial support for a wide range 

of business and infrastructure projects that will be needed to encourage private sector investments in the industry. There are a number of other Federal agencies that 

have expertise to offer, most notably the Department of Energy (DOE) for its research capacities. To avoid duplication and ensure coordination, USDA, DOE and 
128 

other Federal agencies are participating in the statutorily established Biomass Research and Development Board to coordinate activities. 

Question. Can you further explain how the USDA and DOE budgets work together 

to make sure we are advancing our biofuels industry in the most efficient and timely manner, without unnecessary duplication or conflict? 

Answer. USDA and DOE are working together through the Biomass Research and 

Development Board and the USDA Energy Council. The Administration’s Farm Bill 

proposes that this relationship be strengthened by moving the authority for USDA’s 

existing renewable energy and energy efficiency loan and grant program, which is 

a stand alone authority contained in the 2002 Farm Bill, into the Biomass Research 

and Development Act of 2000, which established the Biomass Research and Development Board and contains the authority for the Biomass Research and Development program that received funding under Section 9008 of the 2002 Farm Bill. 

Additionally, DOE and USDA will lead an interagency effort to prepare a detailed 

multi-year interagency coordination plan (MYICP). The MYICP will aim to improve 

the efficient use of resources by minimizing duplication of effort and defining clear 

roles and responsibilities for each agency and program. The MYICP will define a 

realistic long-term vision for achieving public policy goals through biomass utilization. 

Question. With regard to the production of cellulosic ethanol: do you feel that we 

(both Congress and the Administration) are doing enough to make sure that not 

only are we advancing the production of cellulosic ethanol, but that we are also 

keeping up on a parallel track the advancement of the on-farm production of a diverse range of biomass feedstocks—such as, developing the infrastructure and 

logistical components for harvesting, transporting, storing and handling these potentially bulky feedstocks? 

Answer. Production of cellulosic ethanol is at an early stage of development. New 

technologies will have a significant influence on the types of infrastructure and 

other related needs for commercial production. These technologies will likely affect 

even the location of production facilities. Consequently, while USDA is aware of various infrastructure and environmental issues relating to ethanol production, it is too 

early to know what the funding needs to address these issues may be. However, 

USDA does have research activities underway that are looking into the issues of 

harvesting, transportation, and storage of the feedstocks. 

Question. Where in this budget are the Administration’s investments in this important part of the cellulosic ethanol production chain? 

Answer. There are a number of USDA programs that are available to support a 

cellulosic energy industry. Possible programs include The Renewable Energy and 

Energy Efficient loan and grant program, Business and Industry guaranteed loan 

program, and the Value Added Producer Grant program can be used to finance renewable energy related activities. In most cases, these programs serve a multitude 

of purposes and funding for celluloic industry needs is not specifically targeted for 

this purpose. 

RURAL DEVELOPMENT GUARANTEED LENDING

Question. Can you further explain the Administration’s focus for rural development funding on guaranteed business and industry loans versus other programs 

such as the rural business grants, etc.? 

Answer. In general, loans and loan guarantees are effective in providing support 

for rural infrastructure and they are less costly to the Government than grants. 

Rural Development intends to re-focus its limited resources on programs that have 

more potential for encouraging private sector investments and that would reach a 

broader range of rural communities. However, there is a role for the limited use of 

grants for such things as market surveys and technical assistance as well as demonstration projects. 

Question. Do you have any data or other information that supports concentrating 

funding on the loans instead of the grants? 

Answer. The 2008 budget contains information on the Government’s cost for various loan programs. For example, it shows that the $43.2 million in budget authority for business and industry loan guarantees will support about $1 billion in private sector financing. Further, the Administration’s 2007 Farm Bill proposal indicates that $210 million in budget authority will support $2.17 billion in guaranteed 

loans. It also indicates that the Administration proposes that the loan limit for renewable energy loans for cellulosic facilities be increased to $100 million. If the 

same amount of budget authority were used to finance such facilities, only a small 

fraction of projects could be financed unless the grant funds are used only for specific purposes that encourage private sector financing. 
129 

Question. Certainly many of the witnesses at a recent rural development hearing 

before the Senate Ag Committee raised concerns about an over-emphasis on loans 

instead of grants for rural communities, especially when compared with how we provide funding to urban communities. Do you have any information or explanation for 

this discrepancy? 

Answer. There is no denying the fact that certain needs for both rural and urban 

communities require mostly Federal funding, for example roads or rental housing 

projects. Minimizing the use of grant funds allows Rural Development to provide 

funding to more communities. For example, the 2008 budget proposes to reduce the 

interest rate on Water and Waste Disposal loans and reducing the amount of grants. 

This proposal is expected to provide more assistance to most rural communities at 

no additional cost to the Government. 

COMMODITY SUPPLEMENTAL FOOD PROGRAM

Question. The Administration again proposes cutting the Commodity Supplemental Food Program (CSFP) this year because it has concluded that the CSFP program is duplicative of other nutrition programs. This is the exact opposite of what 

I am hearing from folks in Nebraska, specifically as it relates to elderly recipients 

and the supplemental nature of the products this program provides. 

What support do you have for the conclusion that this is a duplicative program? 

Answer. The CSFP does not duplicate other programs in every respect. However, 

there is significant overlap between the CSFP eligible populations of women, infants 

and pre school children and those of the Special Supplemental Nutrition Program 

for Women, Infants and Children (WIC). There is also significant overlap between 

the CSFP eligible elderly population and that of the Food Stamp Program. In addition, low-income elderly persons have access to the Emergency Food Assistance Program and programs administered by the Administration on Aging. Our priority is 

to fund the Food Stamp Program, WIC, and the Emergency Food Assistance Program (TEFAP) because they are nationally available, including in the communities 

served by CSFP. I will ask the agency to provide some additional details on this. 

[The information follows:] 

CSFP was created in January 1969 to assist nutritionally at-risk women, infants, 

and pre school children by providing commodities in specific amounts judged necessary for their health. WIC was enacted in September 1972 serving a very similar 

purpose through provision of coupons that could be redeemed at food retailers for 

supplemental food. WIC soon became the preeminent program serving this population, currently reaching over 8 million participants in an average month in fiscal 

year 2006, while CSFP WIC-type participation is about 40,000. WIC provides eligible participants better nutrition education, more active referrals to needed health 

care resources, and higher supplemental food benefits than the CSFP. 

The Food Stamp Program is the Nation’s primary domestic nutrition assistance 

program for low-income households including the elderly. The Food Stamp Program 

is a mandatory program available in all jurisdictions. It is designed to provide lowincome households with adequate resources to buy a nutritious, low-cost diet. Because the CSFP operates in limited areas, some low-income elderly have access to 

nutrition assistance through commodities and/or Food Stamps, while most others 

must rely on Food Stamps, TEFAP and Administration on Aging programs for such 

help. 

Ensuring adequate funding for programs that have the scope and reach necessary 

to provide access to eligible people wherever they may reside is a better and more 

equitable use of scarce resources than to allocate them to programs that cannot provide access to many areas of the country. For this reason, the Administration has 

placed a priority on funding the Food Stamp Program, WIC, and other nationallyavailable programs, such as the Administration on Aging programs for seniors and 

the Emergency Food Assistance Program (TEFAP), which provide benefits to eligible 

people wherever they may live, including communities currently served by CSFP. 

All seniors over age 60 are eligible for both congregate and home-delivered nutrition 

assistance provided by one of 655 Area Agencies on Aging, which are funded 

through the Administration on Aging in the Department of Health and Human 

Services. In addition to the Administration on Aging programs for seniors, low-income individuals of any age have access to TEFAP. 

Question. How is it duplicative, particularly with regard to the specific components of CSFP compared to Food Stamps and WIC; i.e. where do those programs 

provide the food packages and items to needy and elderly people? 

Answer. It is duplicative in that there are other, nationally available nutrition assistance programs that serve the same or similar demographics. In the few areas 

where CSFP is available, there is significant overlap between the eligible popu-
130 

lations and areas of operation of CSFP and the Special Supplemental Nutrition Program (WIC), and for elderly eligibles, CSFP and the Food Stamp Program. Both the 

Food Stamp Program and WIC are available nationwide. Benefits in the Food 

Stamp Program provide low-income households with adequate resources to buy a 

nutritious, low-cost diet. 

Question. Does the Administration have any idea of how many people will not be 

served or by how much they will lose support? 

Answer. Most of the current CSFP participants will be able to switch over to food 

stamps and/or WIC. Spending for WIC food benefits would be as much, or more, 

than CSFP benefits; and for the elderly, the average elderly food stamp benefit purchases about 50 percent more than the retail value of the CSFP benefit. There 

would be some current CSFP recipients who would not qualify for either of these 

programs and who would need to go to TEFAP and/or the Agency on Aging programs. I have asked staff to provide more specifics. 

[The information follows:] 

Recent program reporting data show that about 463,000 individuals participated 

in CSFP in 2006—40,000 women, infants, and pre school children, and 423,000 elderly, persons 60 years of age or older. The Department estimates that a substantial 

portion of the women, infants and children who participate in CSFP will be eligible 

for WIC. The two groups of CSFP participants that are not eligible for the WIC program are children between the ages of 5 and 6 and certain women who are 6 to 

12 months post-partum. 

Based on the circumstances and experiences of all low-income elderly, we believe 

about two-thirds of the projected 423,000 elderly CSFP participants will be eligible 

for food stamps. Compared to CSFP benefits, food stamp benefits are more advantageous for elderly persons because they often have medical conditions that limit 

their food choices. Also, food stamps allow them to select foods appropriate to their 

preparation abilities and cultural preferences, both a challenge to meet via commodity distribution, where food selection is more limited than at food stamp retailers. 

In addition to food stamps, all seniors over age 60 are eligible for both congregate 

and home-delivered nutrition assistance provided by one of 655 Area Agencies on 

Aging, which are funded through the Administration on Aging in the Department 

of Health and Human Services. Low-income individuals of any age also have access 

to the Emergency Food Assistance Program and other government and private nonprofit programs that offer nutrition assistance. 

U.S. AGRICULTURAL TRADE

Question. Finally, below are two common assumptions or perceptions that many 

believe help drive farm policy development. I have a few questions that correspond 

to these assumptions, and I would welcome answers to the questions that include 

any information or compilation of information (reports, charts, graphs, etc.) that address each: 

Increased net agricultural exports through trade agreements focusing on greater 

market access are assumed to have been successful and that they hold the greatest 

promise for U.S. agriculture. 

Has USDA developed a year-by-year analysis for the U.S. agricultural net balance 

of trade for the years 1975–2006—including the trade balance in both nominal 

terms, and in inflation adjusted 2006 dollar terms, as well as highlighting specific 

years when significant agricultural trade agreements have been passed? Please provide. 

Answer. A table showing the U.S. agricultural trade balance from fiscal year 1975 

to fiscal year 2006 will be submitted for the record. The trade balance is shown in 

nominal terms and real terms, using the GDP deflator based on 2000, as reported 

in the 2007 Economic Report of the President. In general, the agricultural trade balance has reflected the U.S. exchange rate, growing when the dollar was weak, such 

as in the early 1980s and early 1990s, but shrinking when the dollar appreciated, 

such as in the mid-1980s and in the early 2000s. Imports have been growing rapidly 

over the past decade, and do not seem to be strongly influenced by the value of the 

dollar. Exports have increased significantly the past few years, reflecting higher 

commodity prices and a weaker dollar. 

The change in the agricultural trade surplus does not correspond with the implementation of a particular free trade agreement (FTA) for several reasons. FTAs are, 

by design, implemented slowly over a transition period to expressly avoid major 

trade disruptions. The U.S.-Canada FTA began in 1989, and U.S. exports increased 

by $4 billion that year. But the NAFTA with Mexico began in 1994, and U.S. exports stayed about the same as in 1993. However, when viewed over the longer 
131 

term, data show that the value of U.S. agricultural exports to Canada have increased by 119 percent and to Mexico by 181 percent since implementation of 

NAFTA. In addition, Canada and Mexico are now more important markets for U.S. 

agriculture than they were before NAFTA. In 1993, Canada and Mexico combined 

accounted for about 21 percent of total U.S. agricultural exports. By 2006, that percentage had risen to 32 percent. 

Exports in any 1 year are more influenced by changes in world commodity prices 

and global economic growth than by FTAs. Imports are more influenced by economic 

growth in the United States, which translates into greater purchasing power for 

U.S. consumers and greater demand for imported goods. 

[The information follows:] 

VALUE OF U.S. AGRICULTURAL TRADE BY FISCAL YEAR 

[In billions of dollars] 

Year Exports Imports Trade Balance GDP deflator 

2000=100 

Trade Balance 

in 2000 $ 

1975 ................................................. 21.82 9.44 12.38 38.0 32.58 

1976 ................................................. 22.74 10.49 12.25 40.2 30.48 

1977 ................................................. 23.97 13.36 10.61 42.8 24.80 

1978 ................................................. 27.29 13.89 13.40 45.8 29.27 

1979 ................................................. 31.98 16.19 15.79 49.5 31.91 

1980 ................................................. 40.47 17.29 23.18 54.0 42.92 

1981 ................................................. 43.78 17.34 26.44 59.1 44.75 

1982 ................................................. 39.10 15.46 23.64 62.7 37.70 

1983 ................................................. 34.77 16.28 18.49 65.2 28.36 

1984 ................................................. 38.03 18.91 19.12 67.7 28.24 

1985 ................................................. 31.20 19.74 11.46 69.7 16.44 

1986 ................................................. 26.31 20.88 5.43 71.3 7.61 

1987 ................................................. 27.88 20.65 7.23 73.2 9.87 

1988 ................................................. 35.32 21.01 14.30 75.7 18.89 

1989 ................................................. 39.67 21.57 18.10 78.6 23.03 

1990 ................................................. 40.35 22.71 17.64 81.6 21.62 

1991 ................................................. 37.86 22.74 15.13 84.4 17.93 

1992 ................................................. 42.55 24.50 18.05 86.4 20.89 

1993 ................................................. 43.06 24.60 18.46 88.4 20.88 

1994 ................................................. 43.89 26.56 17.33 90.3 19.19 

1995 ................................................. 54.61 29.79 24.82 92.1 26.95 

1996 ................................................. 59.79 32.44 27.34 93.9 29.12 

1997 ................................................. 57.31 35.65 21.65 95.4 22.70 

1998 ................................................. 53.66 36.83 16.83 96.5 17.44 

1999 ................................................. 49.12 37.29 11.83 97.9 12.08 

2000 ................................................. 50.76 38.86 11.90 100.0 11.90 

2001 ................................................. 52.72 39.03 13.69 102.4 13.37 

2002 ................................................. 53.32 40.95 12.37 104.2 11.87 

2003 ................................................. 56.01 45.68 10.33 106.4 9.71 

2004 ................................................. 62.41 52.66 9.75 109.4 8.91 

2005 ................................................. 62.52 57.74 4.78 112.7 4.24 

2006 ................................................. 68.72 64.03 4.70 115.8 4.06 

October-September fiscal year. 

Source: U.S. Bureau of the Census; Economic Report of the President for GDP deflator 

Question. Has USDA developed an equivalent analysis and graph for only the food 

portion of the U.S. agricultural balance of trade, since the commonly published agricultural trade balance includes forest and other non-food items. Please provide. 

Answer. There is no commonly accepted definition of ‘‘food’’ for purposes of analyzing U.S. agricultural trade. For example, the Department of Commerce includes 

fish and fish products in its definition of food trade, but USDA does not include fish 

in its official U.S. agricultural trade figures. 

Tables will be provided for the record that show one breakdown of food trade, including fish. In general, practically all U.S. agricultural imports are food, under this 

definition. The share of food in U.S. agricultural exports has been growing, as exports have diversified into many more products such as fruits, vegetables, meats, 

and processed foods. 

[The information follows:] 
132 

U.S. AGRICULTURAL IMPORTS 

[In billions of dollars] 

Cal. yrs 

1989 1990 1991 1992 1993 1994 1995 1996 

All processed foods ................................................................................. 19.304 20.399 20.426 21.557 21.630 23.588 24.768 27.556 

Grain mill products ........................................................................ 1.217 1.240 1.328 1.658 1.608 1.962 2.194 2.666 Sugar & confections ...................................................................... 1.862 2.188 2.091 2.142 2.059 2.088 2.330 3.101 Preserved fruits & vegetables ....................................................... 2.326 2.589 2.404 2.623 2.414 2.597 2.658 3.118 Dairy products ................................................................................ .740 .783 .702 .782 .768 .855 1.060 1.227 Meat products ................................................................................ 2.597 3.016 2.999 2.758 2.915 2.799 2.486 2.474 Fish and seafood ........................................................................... 5.381 5.169 5.604 5.617 5.761 6.545 6.691 6.607 Bakery products ............................................................................. .343 .347 .381 .422 .473 .546 .603 .660 Miscellaneous foods ....................................................................... 1.337 1.358 1.488 1.622 1.781 1.967 2.150 2.395 Beverages ....................................................................................... 3.501 3.708 3.429 3.934 3.852 4.229 4.595 5.308 

Unprocessed foods .................................................................................. 2.843 3.341 3.472 3.449 3.795 4.027 4.460 5.032 

Fruits, nuts, vegetables ................................................................. 72.795 73.286 73.425 73.395 73.665 73.921 4.405 4.961 Fish and seafood ........................................................................... .048 .055 .047 .054 .130 .106 .055 .072 

TOTAL FOOD IMPORTS ................................................................ 22.146 23.740 23.899 25.006 25.424 27.615 29.228 32.589 TOTAL NONFOOD IMPORTS ......................................................... 5.161 4.403 4.628 5.458 5.598 6.060 7.773 7.602 

Source: U.S. Census Bureau. 

U.S. AGRICULTURAL IMPORTS—CONTINUED 

[In billions of dollars] 

Cal. yrs. 

1997 1998 1999 2000 2001 2002 2003 2004 2005 

All processed foods .................................................... 30.072 31.858 34.549 36.600 37.024 37.807 42.465 47.067 51.029 

Grain mill products ........................................... 2.768 2.715 2.546 2.557 2.369 2.275 2.577 3.298 3.408 Sugar & confections ......................................... 3.119 3.189 2.947 2.818 2.982 3.378 4.283 4.450 5.027 Preserved fruits & vegetables .......................... 3.279 3.250 3.852 3.834 3.624 3.219 3.740 4.068 4.487 Dairy products ................................................... 1.164 1.398 1.456 1.529 1.642 1.575 1.740 2.027 2.224 Meat products ................................................... 2.825 3.044 3.477 3.992 4.447 4.443 4.618 5.858 5.895 
133 

Fish and seafood .............................................. 7.626 8.025 8.872 9.593 9.268 9.356 9.914 10.056 10.625 Bakery products ................................................ .711 .799 .921 1.032 1.124 .821 .878 .929 1.007 Miscellaneous foods .......................................... 2.650 2.998 3.160 3.189 3.098 3.295 3.521 4.114 4.578 Beverages .......................................................... 5.929 6.441 7.318 8.056 8.472 9.445 11.194 12.265 13.780 

Unprocessed foods ..................................................... 5.173 5.878 6.289 6.631 7.351 8.775 9.968 11.235 12.444 

Fruits, nuts, vegetables .................................... 5.093 5.808 6.239 6.279 6.880 8.074 8.928 10.070 11.097 Fish and seafood .............................................. .080 .071 .050 .351 .470 .700 1.040 1.165 1.347 

TOTAL FOOD IMPORTS .................................. 35.246 37.737 40.838 43.231 44.375 46.581 52.433 58.302 63.473 TOTAL NONFOOD IMPORTS ............................ 8.609 7.254 5.756 5.688 4.730 5.384 5.897 6.895 7.780 

Source: U.S. Census Bureau. 

U.S. AGRICULTURAL EXPORTS 

[In billions of Dollars] 

Cal.yrs 

1989 1990 1991 1992 1993 1994 1995 1996 

All processed foods ................................................................................. 15.546 17.133 18.906 21.460 22.129 24.726 27.643 28.441 

Grain mill products ........................................................................ 5.163 4.782 5.081 5.633 5.724 6.101 6.775 6.930 Sugar & confections ...................................................................... .521 .649 .682 ,726 .822 .871 .891 .890 Preserved fruits & vegetables ....................................................... 1.423 1.771 1.966 2.210 2.294 2.580 2.869 2.960 Dairy products ................................................................................ .493 .439 .553 .832 .951 .867 ,872 .827 Meatproducts .................................................................................. 2.864 3.270 3.780 4.376 4.504 5.315 6.572 7.067 Fish and seafood ........................................................................... 2.288 2.785 3.041 3.358 2.964 3.010 3.145 2.909 Bakery products ............................................................................. .110 .190 .233 .306 .358 .389 .382 .407 Miscellaneous foods ....................................................................... 1.684 1.912 2.167 2.470 2.762 3.318 3.590 3.935 Beverages ....................................................................................... 1.000 1.335 1.405 1.549 1.751 2.276 2.545 2.517 

Unprocessed food .................................................................................... 2.861 3.877 4.131 4.462 4.788 5.517 5.579 5.884 

Fruits, nuts, vegetables ................................................................. 2.815 3.810 4.031 4.368 4.709 5.436 5.478 5.779 Fish and seafood ........................................................................... .047 ,067 .100 .094 .080 .081 .101 .105 

TOTAL FOOD EXPORTS ............................................................... 18.407 21.010 23.037 25.922 26.918 30.244 33.222 34.324 TOTAL NONFOOD EXPORTS ......................................................... 24.030 21.334 19.453 20.631 18,989 19.040 26275 28.998 

Source: U.S. Census Bureau. 
134 

U.S. AGRICULTURAL EXPORTS—CONTINUED 

[In Billions of Dollars] 

Cal. yrs. 

1997 1998 1999 2000 2001 2002 2003 2004 2005 

Ali processed foods .................................................... 29.654 28.150 27.655 28.245 30.112 26.565 28.652 28.525 32.076 

Grain mill products ........................................... 8.063 7.807 6.600 6.454 7.081 6,871 6.852 6.969 7.534 Sugar & confections ......................................... .929 .849 .884 1.041 1.230 1.052 1.119 1.238 1.307 Preserved fruits & vegetables .......................... 3.163 3.105 3.209 3.243 3.243 2.783 2.906 2.994 3.160 Dairy products ................................................... 1.048 1.008 1.029 1.076 1.192 1.047 1.131 1.642 1.788 Meatproducts .................................................... 7.021 6.552 6.644 7.202 7.533 5,096 6.034 3.937 5,400 Fish and seafood .............................................. 2.029 2.642 2.651 2.894 2.606 2.629 2.898 3.112 2.909 Bakery products ................................................ .446 .459 .456 .466 .489 .386 .385 .429 .478 Miscellaneous foods .......................................... 3.762 3.912 3.799 3.662 3.717 4.018 4.501 5,111 6.029 Beverages .......................................................... 2.613 2.429 2.394 2.451 2.732 2.705 3.097 3.306 3.270 

Unprocessed food ....................................................... 6.007 5.951 5.790 6.238 6.261 7.257 7.894 9.149 10.633 

Fruits, nuts, vegetables .................................... 5.878 5.676 5.544 5.984 5.973 6.763 7.328 8.405 9.744 Fish and seafood .............................................. .130 .275 .246 .254 .288 .494 .566 .744 .889 

TOTAL FOOD EXPORTS .................................. 35.662 34.101 33.445 34.483 36.373 33.822 36.547 37.674 42.709 TOTAL NONFOOD EXPORTS ........................... 24.228 19.956 17.821 19.668 20.467 22.392 26.012 27.352 24.249 

Source: U.S. Census Bureau. 
135 

Question. It is generally assumed that approximately one-third of all U.S. farm 

production is exported. According to some analysts, however, 8 percent of the farm 

value of U.S. agricultural production is exported, and the ‘‘one-third’’ figure is largely based on processed food value at the export/import points, not farm-gate value, 

which arguably skews the data. 

Has USDA analyzed and tabulated data showing the proportion of total farm cash receipts ($239.0 billion in 2005) that have been exported, based on farm value for 

the years 1975 to 2006? Please provide. 

Answer. There are several ways to measure the importance of trade to the agricultural sector, and none is perfect. A typical approach is to compare the value of 

exports to the value of agricultural production, or to farm cash receipts. One shortcoming of this method is that exports are valued at the point of export, which includes the value of farm-to-port transportation and other costs. It is also difficult 

to measure the value of processed products at the farm gate, which account for a 

large share of U.S. agricultural exports. Another factor affecting export share that 

is not captured in this measure is the increasing amount of corn, soybeans, and 

other feeds that are exported indirectly in the form of meat rather than directly. 

USDA’s Economic Research Service uses two methods to examine the share of 

production that is exported. One approach is based on volume weights, and the 

other is based on dollar values. 

Information reported by ERS using these two methods, will be supplied for the 

record. Data are not available before 1980. 

[The information follows:] 

EXPORT SHARES OF U.S. AGRICULTURAL PRODUCTION 

Measure 1980–84 1990–94 1999 2002 

Percent of production: 

Volume-based ...................................................... 29.2 23.1 22.8 21.9 

Value-based ......................................................... 21.9 16.8 16.7 17.7 

Both the volume and value measures include primary livestock and crop commodities as well as major processed food products. Each measure has advantages. The 

volume-based measure reduces the variations due to product prices, while the value 

measure better reflects product quality, such as differences between a pound of 

steak and a pound of hamburger. 

To make volume- and value-based export shares comparable, the measures include only products for which both production and export volumes are available. 

Products excluded for this reason are mostly minor and include greenhouse and 

nursery products, seeds, cattle, hides and skins, and animal fats. 

The export share of U.S. agricultural production, based on volume, has averaged 

22 percent since 1996, reflecting the high weight of exported food and feed grains, 

oilseeds and oilseed products, cotton, and tobacco relative to their total harvested 

weight. However, this overall export share masks differences in trends between livestock products and crops and crop products. The export share of U.S. livestock products rose from 3 percent in the 1980s to more than 10 percent in recent years, while 

the export share of crops and crop products fell from over 30 percent to 23 percent 

during the same period. Behind these contrasting trends has been the increase in 

U.S. livestock and poultry production and the corresponding feed requirements that 

have diminished feed grains available for export. 

The export share of U.S. agricultural products, based on values, averaged 17 percent from 1998 to 2002, 5 percentage points lower than the volume-based average. 

The lower value-based measure reflects the lower aggregate value of livestock exports relative to their farm production value. The historical movement of the two 

export share measures shows no consistent pattern—about half the time they move 

in the same direction and the other half not. For example, the volume-based share 

declined from 23 percent in 2001 to 22 percent in 2002, while the value-based share 

rose from 17 to 18 percent. 

QUESTIONS SUBMITTED BY SENATOR JACK REED

PROGRESS IMPLEMENTING LOCAL FOOD PURCHASE PROVISION

Question. Section 4303 of the 2002 Farm Bill allows school districts to pursue a 

local food purchasing preference. 

Can you tell me about USDA’s progress in implementing the provision? 
136 

Answer. This Farm Bill provision authorized funds to be requested to encourage 

schools to purchase locally produced foods and to provide grants and technical assistance for projects that improve access to local foods from small farmers and support school garden programs. This provision has not been funded. Nonetheless, I 

know that the Food and Nutrition Service has done quite a bit to encourage local 

purchases anyway. I will ask staff to provide more details on this. 

[The information follows:] 

Regarding implementation of section 4303 of the 2002 Farm Bill, the Conference 

Report that accompanied the Farm Bill indicated that this provision was not intended to permit State or local geographic preferences, or to circumvent Federal procurement requirements. School districts participating in the National School Lunch 

and School Breakfast Programs are prohibited by government-wide regulation from 

applying a geographic preference in their procurements. 

Although no funds have been appropriated to carry out Section 4303, USDA has 

supported farm to school initiatives. In 1997, the Food and Nutrition Service established a ‘‘farm to school’’ initiative which is based on the cooperation of Federal, 

State, and local governments, as well as local farm and educational organizations. 

The initiative encourages schools to purchase locally grown fruits and vegetables. 

As part of this initiative, USDA has created two publications, which are posted on 

our web site, called Eat Smart-Farm Fresh! A Guide to Buying and Serving LocallyGrown Produce in School Meals and Small Farms/School Meals Initiative: a Stepby-Step Guide on How to Bring Small Farms and Local Schools Together. These 

publications provide practical tips in a handbook format on how school food service 

personnel can purchase products from local farmers. 

Questions. If it is USDA’s position that Congress’s guidance in Section 4303 is inadequate to authorize farm to school initiatives and other local food purchasing programs, what language would you recommend that Congress include in the next 

Farm Bill to make clear its intent to authorize and encourage programs? 

Answer. Current statutory authority does not unduly restrict farm to school and 

local food purchasing initiatives. Although school districts participating in the National School Lunch and School Breakfast Programs are prohibited by governmentwide regulation from applying a geographic preference in their procurements, school 

districts may tailor their procurement specifications to maximize full and open competition and obtain high quality fresh produce for their school meal programs, in 

many instances from local producers. Consequently, we do not believe any change 

to current law is necessary to further authorize or encourage farm to school initiatives. 

The Department is supportive of farm to school initiatives, and believes that these 

initiatives can be successful within the framework of current law and regulations 

and free and open competition for contracts. 

QUESTIONS SUBMITTED BY SENATOR ROBERT F. BENNETT

RENTAL ASSISTANCE

Question. Mr. Secretary, the budget proposes changing the length of rental assistance contracts to a term of 1 year. Prior to fiscal 2007, those contracts were generally longer in length. The fiscal 2007 budget proposed a reduction to 2 years, and 

now the fiscal 2008 budget proposes renewing contracts for 1 year. 

Can you please explain the rationale behind this change? 

Answer. Other Federal housing programs offering rental assistance provide annual renewals, for instance the Department is aware of similar assistance offered 

by the department of Housing and Urban Development. The budget change will not 

affect the cost of the program, but the change in contract terms will impact the distribution of budget authority during the transition period. 

Question. Would this change improve the ability of USDA to estimate the number 

of contracts expiring in a given year? 

Answer. USDA has several tools available to assist in estimating the number of 

contracts expiring in a given year. However, contract costs are subject to many variables, including tenant income variations, increases in operating costs (particularly 

insurance and energy costs) that result in rent increases that increase the use of 

rental assistance, and rental assistance utilization rates that vary by property. The 

effects of these variables may be more prominent on contracts with a one-year term 

than contracts with multiple years, which could spread the impact of such variables 

across a longer period of time. USDA intends to monitor closely the performance of 

these one-year contracts and is developing an analysis of these variables on rental 

assistance. 
137 

Question. If this proposal is adopted, there would be a significant amount of contracts expiring in 2008, ranging from 5-year contracts signed in 2003 to some oneyear contracts signed in 2007. 

How will this affect the budget for fiscal 2009? 

Answer. Current estimates for fiscal year 2009 indicate approximately 231,000 

rental assistance units will be up for renewal. This is 84 percent of all rental assistance units. These consist of units obligated prior to fiscal year 2004 and units obligated under contract term limits in fiscal year 2005, fiscal year 2007 and fiscal year 

2008. 

Question. Do you feel a significant amount of additional funding will be necessary 

to renew this extreme volume of contracts? 

Answer. There would be additional costs of continuing the same terms and conditions of contracts. 

Question. Do you feel that adequate funding to cover all of these contracts will 

appear in your budget proposal for next year? 

Answer. No decisions have been made for the President’s 2009 Budget. 

Question. Do you feel that Rural Development has the staff and resources needed 

to renew such a high volume of contracts in 1 year? 

Answer. The majority of the tasks associated with renewing contracts are already 

automated, and we are currently modifying documents to require minimal manual 

intervention for renewals. We believe that Rural Development has the staff and resources needed for this renewal process. 

RURAL DEVELOPMENT—DIRECT LOANS

Question. Funding for both Single Family and Multi-Family Direct Loans has 

been eliminated in your budget proposal. 

Can you please explain the basis for eliminating these programs? 

Answer. The other major Federal single family housing guarantee programs, including those operated by HUD and VA, rely on guaranteed loans. Direct loan programs are more costly to taxpayers. Based upon the fiscal year 2008 budget, the 

taxpayer’s cost for providing a direct subsidized housing loan of $100,000 would be 

$9,357. With a 3 percent guarantee fee, a guaranteed housing loan of $100,000 costs 

the taxpayer only $200. With the same cost, taxpayers can provide one direct housing loan or almost 50 guaranteed loans. For this reason, guaranteed loans have accounted for virtually all the growth in our Single Family Housing program since the 

mid 1990s. 

With regard to Multifamily Housing program, the primary reason for not requesting funds for direct loans is to concentrate on revitalization of existing portfolio. Direct loans for section 515 new construction have a subsidy rate of 45.67 percent and 

these projects also regenerate additional costs for rental assistance payments. 

Question. If adopted, what effect will these changes have on the make-up of the 

participants in single family and multi-family housing programs? Will there be people who participate in these programs now who will no longer be eligible? 

Answer. We anticipate that many customers once served by the direct housing 

loan program will be able to be served by the guaranteed program. Moreover, directing resources to our existing multifamily portfolio will protect the rent of existing 

tenants. 

RISK MANAGEMENT AGENCY CROP INSURANCE USER FEE

Question. The budget proposes the collection of a user fee from participants in the 

crop insurance program to fund the Risk Management Agency’s IT modernization 

beginning in fiscal 2009. 

Please explain how the user fee would function and who would pay the fee? 

Answer. The fee would be payable by the private sector insurance companies who 

participate in the Federal crop insurance program. The fee would be capped at $15 

million annually and would be based on a percentage of the premium written by 

the companies during the prior crop year. In this way, the companies that are the 

primary beneficiaries of the IT system would pay the larger portion of the fee. Based 

on current projections of total premiums, the fee is expected to be about one-quarter 

cent per dollar of premium. 

Question. How would this proposal, if adopted, affect future RMA IT appropriations requests? Did I understand your testimony correctly that this fee would replace the need for appropriated IT funds entirely? 

Answer. It is anticipated that the fee would eventually replace the need for appropriated funding. However, the budget proposal is designed such that the fee would 

initially supplement the annual appropriation for information technology (IT). This 

funding would be used to modernize the IT system currently in use by the Risk 
138 

Management Agency (RMA). However, once modernization is complete, the funding 

would be used for IT maintenance and would replace the need for appropriated 

funding. We anticipate that the modernization process will take about 2 years to 

complete. 

RENEWABLE ENERGY—COMMODITY PRICES

Question. The recent boom in biofuel production has caused some commodity 

prices to spike. While this has a positive effect on many agricultural economic aspects, such as farmers earning more of their income from the market, these price 

increases have also caused negative results for some. Livestock feed prices have 

climbed dramatically, putting a strain on many ranchers across the country. Also, 

higher commodity prices have had a negative impact on food aid, since fewer commodities can be purchased for the same dollar amount. 

With such a strong focus on renewable energy in both this budget and your farm 

bill proposal, how do you propose to combat the negative aspects of these new policies? 

Answer. The extraordinary price run-up that started last fall has raised costs for 

the livestock and poultry industry, along with other users of corn. The spillover has 

also led to higher prices for most other commodities and is straining fixed budgets 

for food aid. However, as often noted, the best cure for high prices is high prices. 

That is, the market is responding to the incentive of high prices by a dramatic expansion in corn acreage that will boost supplies and lead to substantial moderation 

in prices. 

There is no denying that this transition period before adjustments have occurred 

will be painful, but it should also be noted that grain prices have been very low for 

many years. In real terms, these prices have been extremely low and have made 

it difficult for farmers to cover costs without support from the Government. Consumers pay a record low share of their incomes for food in this country. Because 

of the expansion of biofuels, we do not project grain prices to fall back to very low 

levels, like the $2.00 per bushel corn of recent years. Rising productivity and response to market incentives will bring prices down in the next few years from the 

highs seen last winter. Any breakthroughs in the production of ethanol from cellulosic materials would also contribute to easing pressure on grain supplies. Given 

huge interest and new investments in research, the ability to use cellulosic feedstocks, in a cost-effective way, for ethanol production may not be far away. 

In the current environment, there are other adjustments taking place to reduce 

pressure on the livestock industry. Cattle and dairy producers are increasingly feeding distillers grains, a by-product of ethanol production. Research is underway to 

make these by-products more useable to pork and poultry feeders, as only limited 

amounts can be fed to these animals given current formulations. 

On the food aid side, higher prices are not all negative. Many, if not all, farmers 

in developing countries face low prices, frequently reflecting an urban bias. These 

farmers respond to market incentives too. The well publicized case of Mexico, where 

corn-based tortilla prices have risen sharply, also offers an encouraging lesson. 

Mexican farmers are expanding corn production, and this will help contribute greatly to rural development as much as to increasing local food supplies. 

We will continue to coordinate closely with the program agencies, USAID, FAS, 

to review commodities requested and complete market research to identify the most 

economical and effective products. Contracts are awarded based on lowest landed 

cost, so FSA must evaluate the combined commodity cost and the freight cost. The 

new award system implemented in February 2007 should help achieve some cost 

savings in all international food aid purchases. 

AGRICULTURAL DISASTER ASSISTANCE

Question. There have been many efforts in Congress to pass comprehensive disaster assistance for the nation’s farmers and ranchers dating back to 2005. I fully 

expect attempts by Members to include an agriculture disaster package in the supplemental appropriations bill Congress will soon be considering. 

In your opinion, is there a need for ag disaster, and if so, where is it needed the 

most? 

Answer. This Administration does not deny there have been times it has been necessary to provide relief to farmers and ranchers harmed by natural disasters. In 

fact, since 2005, this Administration has developed numerous ad hoc disaster assistance programs to aid producers impacted by adverse weather. However, these programs have been targeted to producers directly impacted by these extraordinary 

weather events. What this Administration has not supported are Congressional efforts to provide a multi-billion dollar, broad based, non-targeted disaster assistance 
139 

package covering a time period when producers have seen record or near record production and/or farm income levels and crop insurance losses have been at record or 

near record lows. The Administration would not support a broad disaster bill unless 

it is fully offset from other agricultural spending. 

While individual producers in certain regions of the nation have experienced crop 

losses due to adverse weather, the farm economy overall has been financially strong. 

For calendar year 2005, total crop cash receipts were $114 billion, the second highest ever. Preliminary estimates for calendar year 2006 are that total crop cash receipts will reach a record $122 billion. However, that record is expected to be shortlived as calendar year 2007 crop cash receipts are forecasted to reach nearly $134 

billion. 

For the period 2003–2005 the crop insurance loss ratio has averaged just 0.77, including a record low of 0.60 in 2005. This means that, on average, only 77 cents 

have been paid out in indemnities for each $1 of premium. And, while the loss ratio 

for the 2006 crop year is not yet finalized, current estimates place it at about 0.8. 

By comparison, during the early 1990’s the loss ratio averaged nearly 1.5. 

Question. What has USDA done to address disaster needs since the start of 2005? 

Has the money that has been obligated by the department actually made its way 

to producers? 

Answer. Throughout this period, assistance has been available under Federal 

Crop Insurance and the Noninsured Crop Disaster Assistance Program. 

In addition, in October 2005, USDA authorized the use of $250 million from Section 32 funds for crop disaster, livestock, tree, and aquaculture assistance. These 

funds are being distributed by way of five new programs; the Tree Indemnity Program (TIP), the Hurricane Indemnity Program (HIP), the Livestock Indemnity Program (LIP), and the Feed Indemnity Program (FIP); and an Aquaculture Grant Program. 

Producers in Alabama, Florida, Louisiana, Mississippi, North Carolina and Texas 

counties declared primary presidential or secretarial disaster areas in 2005 because 

of hurricanes were eligible to apply for assistance under the new programs. In general, funds under these programs have been distributed to producers. However, for 

some programs it has been necessary to delay payments until it could be determined 

if there would be a need to prorate the available funding. 

I will provide a list of further measures taken by USDA to assist farmers and 

ranchers in 2006. 

[The information follows:] 

Sign-up for programs authorized by the Emergency Agricultural Disaster Assistance Act of 2006 began on December 11, 2006. 

In August 2006, USDA authorized $780 million in assistance to help farmers and 

ranchers manage drought and weather related production challenges. This funding 

included a $50 million Livestock Assistance Grant Program for States which had 

counties which were designated as D3 or D4 on the Drought Monitor anytime between March 7 and August 31, 2006. 

In fiscal year 2006, the Farm Service Agency (FSA) provided $48 million in Emergency (EM) loan assistance. 

On July 13, 2006, USDA announced the expansion of Conservation Reserve Program (CRP) acreage eligible for emergency haying and grazing for livestock producers hit hard by drought. The expansion allows livestock producers from eligible 

counties to obtain needed hay or forage. The expanded area radiates 150 miles out 

from any county approved for emergency haying and grazing. 

USDA also reduced producers’ CRP rental payments by 10 percent, instead of the 

standard 25 percent, on CRP lands that are hayed or grazed under emergency authority in 2006. 

On July 14, 2006 USDA announced sign-up for the Emergency Forestry—Conservation Reserve Program. 

On June 29, 2006, USDA announced $11.8 million in Emergency Conservation 

Program (ECP) funding for 18 States to help producers rehabilitate land damaged 

by drought and other natural disasters. 

On June 9, 2006, USDA announced the availability of $75.7 million in Emergency 

Conservation Program (ECP) funds for victims of the 2005 hurricanes. 

On March 24, 2006, USDA announced that agricultural producers in 16 Texas 

counties adversely affected by wildfires would be eligible to receive $8.1 million in 

ECP funds. 

On March 21 2006, USDA announced that agricultural producers in six Oklahoma 

counties and 27 north Texas counties affected by wildfires could remove dry grass 

on and move cattle to CRP acreage, without facing charges for grazing value or the 

baled value of removed forage. 
140 

On March 15, 2006, USDA announced the allocation of more than $20 million in 

ECP funds to 26 states affected by drought, wildfires and other natural disasters. 

On March 3, 2006, USDA announced the allocation of $63 million in ECP funds 

to assist agricultural producers struck by hurricanes in the Gulf of Mexico region 

during calendar year 2005. 

USER FEE PROPOSALS

Question. The budget proposes user fees totaling $149 million for the Food Safety 

and Inspection Service, Animal and Plant Health Inspection Service, Grain Inspection, Packers, and Stockyards Administration and Risk Management Agency. In previous fiscal years, USDA assumed savings for these fee requests. I am pleased to 

see that this budget request does not assume savings. However, I understand that 

USDA expects to realize savings from these fees in fiscal 2009. Realizing this savings requires USDA to actively engage the Congress and affected industry to pass 

this legislation. 

Please describe, in detail, USDA’s plan for getting each user fee passed including 

discussions with industry and the authorizing committees. 

Answer. Although the budgetary treatment of proposed user fees has changed this 

year, procedures for implementing new user fees would remain the same. Generally, 

the steps for user fee implementation consist of: submitting proposed legislation to 

Congress; participating in special hearings or answering Congressional inquiries 

about the proposed fees; and engaging in the Federal rule-making process after enactment. Statutory prohibitions prevent us from lobbying for passage of new user 

fee legislation outside our communication with Congress. The rule-making process 

provides an opportunity for public input on any proposed rule. All public comments 

are evaluated and considered before a final rule is promulgated. 

GREENBOOK CHARGES

Question. I am concerned that the charges assessed to the agencies by USDA, 

known commonly as greenbook charges, have grown excessively over the last few 

years. 

Please provide, for the record, greenbook charges by category for each agency for 

fiscal year 2006, 2007, and 2008. For each category, provide an explanation of how 

the charges were assessed. 

Answer. The actual funding for fiscal year 2006 and estimated 2007 funding by 

category for greenbook charges, including an explanation of how the charges were 

assessed, is provided for the record. Estimates for fiscal year 2008 greenbook 

charges have not been decided. 

The cost breakout by agency for the greenbook charges is also provided for the 

record. The actual costs by agency for fiscal year 2007 are not yet known. 

[The information follows:] 

Department Wide Reimbursable Programs 

[USDA Agencies fiscal year 2006 Allowance and fiscal year 2007 Estimated Cost Shares] 

Fiscal year 2006 

allowance 

Fiscal year 2007 

estimate 

Agricultural Marketing Service ............................................................................................... $1,291,169 $1,392,694 

Agricultural Research Service ............................................................................................... 4,378,636 4,915,646 

Animal and Plant Health Inspection Service ........................................................................ 4,563,266 5,020,820 

Cooperative State Research, Education and Extension Service ........................................... 493,847 313,085 

Departmental Administration ................................................................................................ 181,779 250,226 

Economic Research Service ................................................................................................... 278,897 235,454 

Farm Service Agency ............................................................................................................. 5,293,884 8,175,512 

Food and Nutrition Service .................................................................................................... 1,604,131 1,103,188 

Food Safety and Inspection Service ...................................................................................... 4,584,996 4,890,378 

Foreign Agricultural Service .................................................................................................. 1,125,309 993,690 

Forest Service ........................................................................................................................ 20,141,973 21,221,635 

Grain Inspection, Packers and Stockyards Administration ................................................... 364,035 409,168 

National Agricultural Statistics Service ................................................................................ 789,616 632,371 

National Appeals Division ..................................................................................................... 80,711 49,284 

Natural Resources Conservation Service .............................................................................. 5,555,459 5,583,986 

Office of Budget and Program Analysis ............................................................................... 33,508 30,091 

Office of Chief Economist ..................................................................................................... 114,940 99,493 

Office of Civil Rights ............................................................................................................ 94,242 92,852 

Office of Communications ..................................................................................................... 66,883 49,916 
141 

Department Wide Reimbursable Programs—Continued 

[USDA Agencies fiscal year 2006 Allowance and fiscal year 2007 Estimated Cost Shares] 

Fiscal year 2006 

allowance 

Fiscal year 2007 

estimate 

Office of Executive Secretariat .............................................................................................. 10,749 9,316 

Office of General Counsel ..................................................................................................... 151,143 164,899 

Office of the Chief Financial Officer .................................................................................... 735,596 1,096,120 

Office of the Chief Information Officer ................................................................................. 5,969,036 2,832,153 

Office of the Inspector General ............................................................................................. 448,138 457,316 

Office of the Secretary .......................................................................................................... 65,775 13,314 

Risk Management Agency ..................................................................................................... 452,737 263,383 

Rural Development ................................................................................................................ 4,312,387 3,547,010 

TOTAL ......................................................................................................................... 63,182,838 63,843,000 

FINANCIAL MANAGEMENT SYSTEM

Question. The budget proposal requests an increase of almost $25 million for the 

development of a new financial management system. Implementing new IT systems 

is often very costly, especially replacing a financial system as large as USDA’s. 

How much does USDA plan to spend on the financial system implementation in 

fiscal 2007? Did this funding come from annual appropriations or from the working 

capital fund? 

Answer. USDA intends to spend $4.5 million in fiscal year 2007 for implementation activities. These funds would come from reimbursements received from USDA 

customer agencies to continue the planning and initial implementation of the Financial Management Modernization Initiative. 

Question. Does USDA plan to fund any part of the financial system in fiscal 2008 

from the working capital fund? 

Answer. The President’s fiscal year 2008 budget includes an estimate of $5.5 million in operating support for this project, to be recovered via reimbursements from 

USDA customer agencies under the Working Capital Fund. This estimate is subject 

to change as the implementation schedule and requirements gathering move forward. 

Question. Does the fiscal 2008 budget request any funding for the financial system 

from the interior appropriations subcommittee for the Forest Service? 

Answer. The fiscal year 2008 budget for the Forest Service does not request any 

funds for the financial system from the Interior Appropriations Subcommittee. We 

do not expect to begin implementation of the Forest Service into the new system 

until after fiscal year 2008. 

Question. Has USDA entered into a contract with a private company for the implementation of the new financial system? If so, please explain the terms of the contract. For example, what constitutes satisfactory completion of the system implementation by the contractor? 

Answer. USDA is currently in the acquisition process and has not entered into 

a contract. 

Question. What is the estimated total cost for development and implementation 

of the new financial system? 

Answer. The estimated cost for implementation of USDA’s new financial management system is approximately $90 million. 

Question. How much of the total development and implementation costs will be 

requested through the agriculture appropriations subcommittee? 

Answer. At this time, no final decision has been made as to the allocation of funding needed for Financial Management Modernization Initiative implementation between the Agriculture and Interior appropriations subcommittees. 

Question. How much of the total development and implementation costs will be 

requested through the interior appropriations subcommittee for the Forest Service? 

Answer. At this time, no final decision has been made as to the allocation of funding needed for Financial Management Modernization Initiative implementation between the Agriculture and Interior appropriations subcommittees. 

Question. How much of the total development and implementation costs will be 

funded through the working capital fund? 

Answer. We do not expect that development and implementation costs will be 

funded through the Working Capital Fund (WCF). We have a small amount of operating funds budgeted for the system through the WCF, but it is our aim that devel-
142 

opment and implementation funds be made available through appropriations and 

Departmental Reimbursable Program authority, if appropriate. 

Question. Once the system is implemented, how much will operations and maintenance of the financial system cost annually? 

Answer. The estimated average annual operations and maintenance cost for the 

expected life of the system, for the period fiscal year 2012 through fiscal year 2021, 

is approximately $50 million. 

Question. Will annual appropriations or the working capital fund pay for operations and maintenance costs? 

Answer. Historically USDA has used the working capital fund reimbursement 

mechanism to pay for USDA’s financial management system operations and maintenance costs. 

FSIS FUNDING

Question. The Food Safety and Inspection Service received a significant funding 

increase of more than $57 million in the fiscal 2007 joint resolution. How does FSIS 

plan to spend the additional funding? 

Answer. FSIS allocated the fiscal year 2007 increase of $62.1 million by funding 

pay costs, employee benefits and activities to strengthen the Food and Agriculture 

Defense Initiative. 

Question. How many staff will FSIS be able to hire as a result of the additional 

funding? 

Answer. FSIS is actively recruiting and hiring for positions in all of its 15 Districts and intends on filling 98 positions for slaughter services and 86 positions for 

in-plant processing in fiscal year 2007. In addition, the agency is recruiting to fill 

new positions resulting from industry growth and vacancies resulting from attrition. 

RISK BASED INSPECTION

Question. Mr. Secretary, recently the Food Safety and Inspection Service announced a plan and time table for implementing risk based inspection in meat and 

poultry plants. 

Please explain this proposal. 

Answer. Under a risk-based inspection system, the type and intensity of inspection activity at each establishment will be determined by the relative inherent risk 

of product, the volume processed, and the ability of each establishment to control 

risk. Risk-based inspection will allow USDA’s Food Safety and Inspection Service 

(FSIS) to more effectively allocate inspection resources to those processing plants 

that need them the most and carry out less intense inspection at plants with better 

risk control, while continuing daily inspection at all processing facilities. The public 

health goal of risk-based inspection is to target FSIS resources more directly at the 

greatest risks and reduce overall risks found in meat, poultry and egg products 

under agency jurisdiction. 

Question. How have industry and consumer groups reacted to this proposal? 

Answer. Most of the industry and consumer groups with whom FSIS has met believe the concept of risk-based inspection can achieve the desired goal of using FSIS 

resources more effectively. 

Question. Does FSIS have an IT system for collecting and analyzing data for risk 

based inspection? If not, why not? 

Answer. In fiscal year 2008, FSIS will use base funds to help move forward with 

information technology hardware and software improvements. The improvements 

are necessary to build a public health data infrastructure that will allow for realtime data analysis—a key element of the enhanced risk-based inspection system. 

FSIS efforts to upgrade its information technology infrastructure are expected to be 

completed in the first quarter of fiscal year 2008. The IT system will improve data 

by incorporating new inspection data generated as a consequence of planned enhancements to inspection activity. In addition, the agency will design an externalUSDA peer-reviewed, risk assessment to model the implementation of risk-based inspection in processing plants such that we can predict and respond to the public 

health outcomes of inspection activity nationwide. 

Question. How does FSIS expect risk based inspection will make meat safer for 

consumers? 

Answer. RBI will make meat safer for consumers by targeting inspection resources to high risk activities and establishments. This will help ensure that meat 

and poultry products are being more effectively inspected using state-of-the-art data 

collection techniques and analysis. 

Question. How will FSIS measure the success of the program? 
143 

Answer. USDA’s Food Safety and Inspection Service (FSIS) intends to implement 

and review risk-based inspection for processing in a careful and deliberative manner. The perfect report card for the long-term would be a measured decrease of food 

borne disease and death. While FSIS is still in the process of developing how we 

intend to evaluate RBIS, in the near-term, FSIS will compare such measures as 

verified consumer food safety complaints, product recalls, and changes in the effectiveness of establishment risk controls between RBIS and traditionally-inspected establishments. In addition, FSIS will be interviewing inspection program personnel, 

and the USDA’s Office of Inspector General will be continuing to audit the development and implementation of RBIS. 

Question. Will total inspection hours or inspection staff be reduced as a result of 

this proposal? 

Answer. Under a more robust risk-based inspection system for meat and poultry 

processing, USDA will continue using the same number of inspection program personnel, spending the same amount of time conducting inspections. Risk-based inspection is about working smarter to protect public health by having inspection personnel spend more time in the processing plants that need assistance and expertise. 

NATIONAL ANIMAL IDENTIFICATION SYSTEM

Question. Mr. Secretary, the Congress has provided over $99 million for the implementation of an animal identification system. I understand that an additional $18.7 

million has been transferred from the Commodity Credit Corporation for this purpose as well. The fiscal 2008 budget request proposes an additional $33 million to 

continue this project. If this funding is provided in fiscal 2008, the total amount 

spent on the animal identification system will be in excess of $150 million by the 

end of 2008. Unfortunately, the direction USDA plans to go with this system is still 

not clear. 

What has all this funding accomplished? 

Answer. The National Animal Identification System is composed of three components: premises registration, animal identification, and animal tracing. Premises 

registration is the foundation of the program. As of March 12, 2007, all 50 States, 

60 Tribes, and 2 U.S. Territories are capable of registering premises according to 

USDA standards, and approximately 378,000 locations have been registered. 

Significant progress has also been made on the second component of NAIS, animal 

identification. As of March 12, 2007, approximately 1 million AIN devices have been 

distributed. 

The third component of the NAIS, animal tracing, is currently under development 

with the help of USDA’s industry and State partners. Industry, through private systems, and States will manage the animal tracing databases that maintain the movement records of animals. Full deployment of the Animal Trace Processing System 

is planned for the near future. 

Question. In USDA’s opinion, how does a comprehensive animal identification system work from identification of an animal disease outbreak to resolution of the problem? 

Answer. The NAIS includes three components: premises registration, animal identification, and animal tracing. When the system is fully operational, all three of the 

NAIS components would be used together to provide a streamlined system of information in a disease situation. This information would be available to help investigate the source of a disease outbreak and identify any animals and/or locations 

in the United States that may be at risk of spreading disease. 

An example will be provided for the record. 

[The information follows:] 

A diseased animal is detected at a slaughterhouse; authorized animal health officials enter the animal’s identification number (AIN) into the National Animal Identification System (NAIS) Animal Trace Processing System (ATPS); the search will 

provide information on AIN devices distributed to a premises and animal movement 

records for that animal from the private/State animal tracing database; authorized 

animal health officials then have a listing of locations associated with the animal; 

the search will also provide the other animal identification numbers that were 

present on the premises during the time the animal in question was there. This 

helps officials identify animals that may have been exposed to the disease. Animal 

health officials can then begin an epidemiologic investigation and take precise actions to address the situation, minimize its impact on producers, and speed disease 

response efforts. 

While NAIS will not ‘‘prevent’’ the initial occurrence of a disease, it can reduce 

or prevent the spread of disease. Without this system of information, it can take 

days, weeks, and too often, months of manual searching to complete a disease inves-
144 

tigation. Moreover, the inability to quickly address an emerging animal disease can 

have negative economic and domestic/international trade implications for the livestock industry and governments. Having NAIS—a streamlined, modern information 

system—in place will not only speed up disease response but also ensure that these 

efforts are comprehensive and accurate. 

Question. How much does USDA estimate the animal identification system will 

cost when completed? Is there an end in sight to continual $33 million funding requests? 

Answer. It is projected that, once NAIS has been fully implemented, the funding 

necessary to maintain the system will be less than the funding necessary to create 

the supporting infrastructure in all States, participating Tribes, and Territories. 

However, premises information will need to be updated as changes occur throughout 

the country. Participants in the private sector will require ongoing administrative 

support and the technologies that enhance NAIS. Therefore, funding will still be 

necessary to maintain the system, to preserve security, to make any necessary upgrades, and to ensure that producers are well-informed regarding the system. 

COMMODITY SUPPLEMENTAL FOOD PROGRAM (CSFP) ELIMINATION

Question. Mr. Secretary, for the second year in a row the budget request eliminates the Commodity Supplemental Food Program, which serves the elderly and 

young women and their children in 32 States, 2 Indian reservations, and the District of Columbia. The elimination of this program results in a $107 million reduction from the fiscal 2007 joint resolution rate. Please explain why USDA chose to 

eliminate this program. 

Answer. In the Administration’s view, ensuring adequate funding for programs 

that have the scope and reach necessary to provide access to eligible people wherever they may reside is a better and more equitable use of scarce resources than 

to allocate them to programs that cannot provide access to many areas of the country. For this reason, the Administration has placed a priority on funding the Food 

Stamp Program, WIC, and other nationally-available programs which provide benefits to eligible people wherever they may live, including communities currently 

served by CSFP. 

Question. Does the budget proposal provide an alternative for all CSFP participants? 

Answer. In the Administration’s view, ensuring adequate funding for programs 

that have the scope and reach necessary to provide access to eligible people wherever they may reside is a better and more equitable use of scarce resources than 

to allocate them to programs that cannot provide access to many areas of the country. For this reason, the Administration has placed a priority on funding FSP, WIC, 

and other nationally-available programs which provide benefits to eligible people 

wherever they may live, including communities currently served by CSFP. 

Included in these programs are Federal nutrition assistance programs targeted 

specifically to seniors. These programs, administered by the Administration on 

Aging and authorized by the Older Americans Act of 1965, include congregate nutrition services and home-delivered nutrition services and are available nationwide to 

all seniors aged 60 and older. The Administration’s 2008 budget request includes 

$383 million and $181 million for these two programs, respectively. In addition, the 

2008 budget request includes $147 million for the Nutrition Services Incentive Program. Combined, the Older Americans Nutrition Programs serve about 250 million 

congregate and in-home meals to about 2.6 million older adults annually. In addition to the Administration on Aging programs for seniors, low-income individuals of 

any age have access to TEFAP. 

Question. What percentage of elderly CSFP participants are currently enrolled in 

food stamps and receive CSFP as a supplement to their monthly food stamp allotment? 

Answer. We estimate that about 20 percent of elderly CSFP participants are currently enrolled in food stamps, based on data on low-income elderly individuals we 

have used in our budget estimates. 

WIC LEGISLATIVE PROPOSALS

Question. Mr. Secretary, the budget includes a proposal to reduce state nutrition 

services and administration grants in the WIC program. Specifically, the proposal 

reduces the per participant nutrition services and administration amount paid to 

states in fiscal 2008 back to the fiscal 2006 rate. The proposal is accompanied by 

a $145 million reduction to the WIC program in the budget. Please explain why 

USDA chose to reduce the NSA grant to states. 
145 

Answer. The current proposal is intended to provide a reduction in WIC NSA 

funding to slow its growth. Further cost containment is needed to maintain the Program’s ability to serve all eligible persons expected to seek services in fiscal year 

2008, which is estimated to be approximately 8.28 million persons. WIC State agencies have been extremely successful in containing food costs. We therefore believe 

WIC State agencies can achieve similar success in containing NSA costs. 

Question. Why did USDA choose to go back to 2006 as the base year instead of 

keeping costs flat at the 2007 rate? 

Answer. The administrative expenditure per participant (AGP) is determined each 

year by inflating the prior year’s AGP by the State and Local Expenditure Index 

(SLEI). From fiscal year 1999 through fiscal year 2006, the SLEI increased 32 percent, or an average of 4.5 percent per year. The SLEI increase from fiscal year 2006 

to fiscal year 2007 is even higher at 6 percent. Over the same period, some broader 

measures of inflation (e.g., the Consumer Price Index for Urban Wage Earners and 

Clerical Workers and the Gross Domestic Product Price Index) have risen more 

slowly (21 percent and 18 percent respectively). Given that these other measures reflect a significantly lower rate of inflation than the SLEI, using 2006 as the base 

year will reduce the AGP so that it is more consistent with what would have occurred if it had grown at a rate comparable to those broader inflation indicators. 

Question. Why did USDA choose to use the budget as a vehicle for changing the 

NSA grant amount instead of asking for the change as a part of farm bill discussions with the authorizing committees? 

Answer. For the proposed NSA cost containment initiative to be effective for fiscal 

year 2008, the proposal had to be included in the fiscal year 2008 budget request. 

Question. How will this reduction impact the states ability to implement new WIC 

programs such as the revised food packages that are to be implemented at the end 

of this year? 

Answer. State agencies will be encouraged to work with Federal program staff to 

seek efficiencies in the administration of the requirements so that the reduction in 

NSA funding does not negatively impact program operations. FNS does not believe 

that the food package rule will necessitate increased staff or any other action that 

would result in major, additional administrative expenditures over the long term. 

FNS does not expect the reduction in NSA will affect the States’ ability to implement the revisions to the food packages. 

WIC MANAGEMENT INFORMATION SYSTEM FUNDING

Question. The budget request does not include funding for Management Information Systems. Please describe the current state of Management Information Systems 

in the WIC program including a discussion of states that still use paper systems 

to manage WIC caseload. 

Answer. Currently, all State agencies use automated systems to manage caseload 

and support daily operations. While the vast majority of WIC systems are electronic 

rather than paper-based, many clinics have insufficient computers to accommodate 

every workstation. Thus, in some cases participant data may be collected manually 

and later entered into a centralized system. 

Question. Why does the budget not include funding for Management Information 

Systems? 

Answer. The fiscal year 2008 budget does not request additional funding for implementation of WIC EBT. In fiscal years 2006 and 2007, $19.8 million was available for management information systems and technology needs. Assuming these 

funds are not needed to support caseload in fiscal year 2007, current funding is sufficient through fiscal year 2008 for system development and EBT initiatives. 

WIC $200 MILLION CONTINGENCY FUND

Question. The budget request proposes to increase the WIC contingency fund to 

$200 million from $125 million. Why does the contingency fund need to be increased? 

Answer. Increasing the amount of funds available in the contingency fund will 

allow the Department to ensure that adequate funds are available to support expected participation should food costs exceed projections. The Department is concerned about the potential of increased food costs in fiscal year 2008. Infant formula 

rebate savings are a significant and integral part of the WIC Program and are estimated to support the participation of over 2 million women, infants and children. 

Any erosion of these savings has serious implications for funding needs to support 

projected participation. In the past 2 to 3 years, the Department has observed a reduction in the percent discount on infant formula received by some WIC State agencies, which has led to increased formula costs. For example, twenty-seven geo-
146 

graphic State agencies have recently awarded contracts that have started in fiscal 

year 2007 or fiscal year 2008 and all but one of these State agencies received a rebate that yields a significant decrease in the discount on the wholesale cost from 

that received in its prior contract. 

WIC FOOD PACKAGE

Question. The updated WIC food package is supposed to be finalized and implemented at the end of this year. Is the Department on-time to implement the food 

package? 

Answer. Over 46,000 comments that were received on the proposed changes to the 

WIC food packages published for comment August 7, 2006 and are currently being 

analyzed. We anticipate issuing an interim final rule updating the WIC food packages in September 2007. 

RESEARCH, EDUCATION, AND ECONOMICS REORGANIZATION

Question. One of the administration’s farm bill proposals would make significant 

changes to the Research, Education, and Economics mission area within USDA. 

Specifically, CSREES and ARS would be folded into one agency. The thrust of the 

argument for this change is that it will lead to better coordinated research and end 

redundancies. 

Is that not the job of the Under Secretary? 

Answer. While the Under Secretary has a role in coordinating the efforts of the 

four REE agencies, it is important to institutionalize this coordination within the 

agencies themselves. This can best be accomplished by merging ARS and CSREES 

into a single agency with a single national program staff. 

This will help ensure that resources will be maximized and that the comparative 

strengths of our intramural and extramural system are better utilized to tackle critical problems facing agriculture. This merger will also strengthen the tie between 

USDA’s intramural research programs and the extension service. This will facilitate 

a broader dissemination of science-based technologies to farmers and ranchers. 

Question. Does he not have the authority to make ARS and CSREES operate more 

efficiently? 

Answer. While the Under Secretary has the authority to help make REE agencies 

more efficient, the current organizational structure of the mission area is a limiting 

factor. By having separate agencies with separate national program staffs, there are 

some inefficiencies that cannot be fully addressed without bringing the agencies together. The merger of ARS and CSREES will better enable the Under Secretary to 

overcome these inefficiencies. 

Question. Why don’t you use the budget process to better coordinate research? 

Answer. The REE budget process promotes research coordination across the REE 

agencies. As part of the budget formulation process, each year the Under Secretary, 

in consultation with the agency Administrators, identifies high priority issues for 

which coordinated budget requests are developed. The proposals take into consideration the current research program within each agency and identify program enhancements that are responsive to research needs and agency strengths. For example, the President’s fiscal year 2008 budget proposes complementary budget increases in bioenergy for CSREES, ARS, and ERS. Merging ARS and CSREES would 

result in one National Program staff and a single planning process for each program 

that would result in an integrated plan for the core program that capitalizes on the 

strengths of intramural and extramural research and minimizes any undesirable 

redundancies. 

Question. What steps have you taken in the fiscal 2008 budget to eliminate 

redundancies and better coordinate research among ARS and CSREES? 

Answer. For the REE fiscal 2008 budget, similar to previous years, the Under Secretary, in consultations with the agency Administrators, identified high priority 

issues for which coordinated budget requests were developed, thus promoting crossagency coordination. The Under Secretary also oversaw the development of the 

agency proposed budgets to ensure an appropriate balance across programs and 

agencies. In some cases, this involved reprogramming within the core budget. 

Throughout the fiscal year, the agencies frequently coordinate efforts on a range 

of research issues. For example, ARS and CSREES have recently developed a joint 

plan to address the Colony Collapse Disorder threatening the honey bee industry 

and production of many crops. Were ARS and CSREES to merge, there would be 

one national program staff that would routinely develop integrated program plans 

with intramural and extramural components. Such plans would inherently promote 

coordination and avoid redundancy. 
147 

Question. What specific direction has been provided to Under Secretary Buchanan 

to make certain that redundancies are eliminated and research is better coordinated? 

Answer. USDA is continually striving to maximize the efficiency and effectiveness 

of its programs. Likewise, Under Secretary Buchanan is looking for ways to make 

REE agencies more efficient and effective. Merging ARS and CSREES will help reduce redundancies and better coordinate research, thus furthering this objective. 

APHIS PROGRAM COST SHARE

Question. The President’s budget for the Animal and Plant Health Inspection 

Service requests decreases for numerous programs such as Agricultural Quarantine 

Inspection, Boll Weevil, Brucellosis, Chronic Wasting Disease, Asian Longhorned 

Beetle, Glassy-winged Sharpshooter, Johne’s Disease, Pink Bollworm, Wildlife Services Operations and Wildlife Services Methods Development. The justification for 

the funding reductions is the assumption that States or other cooperators/beneficiaries will begin paying more toward efforts to fight such plant and animal pests 

and diseases. In some cases, specific cost-share rates are indicated. 

For the record, please provide the funding contributions and cost-share rates for 

Federal vs. State/Local/Other for fiscal year 2006, and estimates for fiscal year 2007 

and fiscal year 2008. for all programs in the budget that request decreases to allow 

others to assume a larger funding portion of the program. In addition, please indicate what process and/or policies the Department uses to determine appropriate 

cost-share rates for these programs, and provide information on what indication you 

have that other State/cooperator/beneficiaries will begin paying the additional costs 

when Federal contributions are reduced. 

Answer. The following table depicts the funding contributions and cost-share rates 

for fiscal year 2006. In addition, we have provided estimates for fiscal year 2007 and 

fiscal year 2008. 

[The information follows:] 

TOTAL FUNDING: ALL SOURCES (ANNUAL) 

[Dollars in Millions] 

Federal Cooperator Total Percent Federal 

Chronic Wasting Disease: 

Fiscal year 2006 actual ...................................... $15.163 $4.473 $19.636 77.22 

Fiscal year 2007 (estimated) .............................. 13.746 9.164 22.910 60.00 

fiscal year 2008 (estimated) ............................... 10.009 11.141 21.150 47.32 

EPP-Asian Longhorned Beetle: 

Fiscal year 2006 actual ...................................... 27.322 10.434 37.756 72.36 

Fiscal year 2007 (estimated) .............................. 19.904 13.713 33.617 59.21 

Fiscal year 2008 (estimated) .............................. 18.316 15.404 33.720 54.32 

EPP-Citrus Health: 

Fiscal year 2006 actual ...................................... 21.191 39.884 61.075 34.70 

Fiscal year 2007 (estimated) .............................. 36.455 29.022 65.477 55.68 

Fiscal year 2008 (estimated) .............................. 34.409 33.368 67.777 50.77 

EPP-Glassy-Winged Sharpshooter: 

Fiscal year 2006 actual ...................................... 27.311 25.443 52.754 51.77 

Fiscal year 2007 (estimated) .............................. 24.130 25.000 49.130 49.11 

Fiscal year 2008 (estimated) .............................. 23.174 27.133 50.307 46.07 

Johne’s Disease: 

Fiscal year 2006 actual ...................................... 13.057 6.900 19.957 65.43 

Fiscal year 2007 (estimated) .............................. 12.080 7.877 19.957 60.53 

Fiscal year 2008 (estimated) .............................. 3.266 16.691 19.957 16.37 

Noxious Weeds: 

Fiscal year 2006 actual ...................................... 1.875 0.121 1.996 93.94 

Fiscal year 2007 (estimated) .............................. 1.441 0.121 1.562 92.25 

Fiscal year 2008 (estimated) .............................. 1.146 0.716 1.862 61.55 

Emergency program costs generally have been shared by APHIS and the State(s). 

These arrangements may also include local governments, industries, organizations, 

and groups that benefit from or are affected by animal and plant protection. 

Long-standing relationships between APHIS and State and industry cooperators 

usually enable an effective programmatic response to serious outbreaks. While cooperator contributions are frequently in-kind or intangible in the early stages of a program, after several years USDA expects that funding would be requested at both 
148 

the Federal and State levels, as appropriate, to ensure continued progress in controlling and/or managing the pest or disease. When requested funding is not provided, USDA evaluates the overall impact to program efforts and adjusts future 

funding requests accordingly. 

USDA believes that increased participation by all parties will facilitate improved 

planning and funding decisions by the Federal Government and its cooperators regarding plant and animal pest and disease programs. However, USDA has no predetermined rates. 

In planning with our partners, we consider factors such as the availability of 

funding to program participants; weather and any other environmental constraints; 

the potential of the pest to cause significant economic damage to agricultural or natural resources; the extent to which the pest or disease has spread; the availability 

of effective detection and control technology or availability of diagnostic tests; and, 

the availability of acceptable alternatives for controlling and managing the pest or 

disease. 

CROSS-CUTTING TRADE NEGOTIATIONS AND BIOTECHNOLOGY RESOURCES

Question. What is the basis for the funding increase proposed for fiscal year 2008? 

Answer. As the usage of biotechnology, both domestically and internationally, has 

expanded in recent years, the Department has recognized the need to increase its 

oversight and regulatory activities in this area. The requested funding increase 

would allow for the expansion of regulatory and trade strategies for specialty crops 

and transgenic animals, and improved communication materials for both domestic 

and international markets. 

Question. Specifically, how will the funds for ‘‘cross-cutting trade negotiations and 

biotechnology resources’’ be used? 

Answer. Cross-cutting trade and biotechnology funding would be used to conduct: 

quantitative analyses and studies needed to support increasingly complex compliance activities; expand a project to develop a regulatory and trade strategy for specialty crops; increase regulatory activity in the area of transgenic animals—domestically, in international markets, and in international standard setting organizations; 

and increase outreach activities for both domestic and international markets. These 

projects would involve multiple USDA agencies. 

Question. Please discuss specific results achieved using these funds in the past? 

Answer. The Foreign Agricultural Service has used this funding to support U.S. 

trade policy objectives for agricultural biotechnology that include expanding market 

access through negotiation and coalition building initiatives. The funds support 

USDA bilateral and multi-lateral negotiating efforts by providing the means to 

sponsor technical and policy level exchanges (e.g., during the Korea and Malaysia 

FTA negotiations, Vietnam WTO accession negotiations, etc.), and to support the 

U.S. WTO challenge of the EU moratorium on agricultural biotechnology approvals. 

The funds also have helped to support U.S. coalition building efforts to address overly restrictive interpretations of the Cartagena Protocol. U.S. outreach efforts center 

around an array of USDA sponsored workshops hosted in multiple foras, including 

the Asia Pacific Economic Council and North American Biotechnology Initiative, to 

raise awareness of the importance of sound regulatory systems. Initiatives undertaken using these funds are aimed at increasing market access for U.S. agricultural 

trade and fostering implementation of policies that are transparent and based on 

sound science through coalition building, global public diplomacy, the advancement 

of science-based regulation and in accordance with international obligations. 

The Animal and Plant Health Inspection Service has used the funds to focus on 

two areas. First, to strengthen Federal-State partnerships, APHIS’ Biotechnology 

Regulatory Services supported the pilot State inspection project, designed and began 

developing an on-line biotechnology training module for State regulatory officials 

and others, and conducted outreach to State regulators. Second, APHIS implemented recommendations from the Office of the Inspector General to enhance compliance and inspection activities, and funded select biotechnology inspections. 

The Cooperative State Research, Education, and Extension Service used the funds 

to support the initial phases of the Specialty Crops Regulatory Initiative (SCRI), an 

effort by a diverse group of public and private-sector stakeholders to establish an 

entity that can assist developers of biotechnology-derived specialty crops to complete 

the existing regulatory process. During 2006–2007, a consultant for the SCRI planning group began development of a business plan and structure for SCRI, as well 

as a roadmap for phased implementation of the SCRI program. 

Question. Why should the funds be appropriated to the Office of the Secretary instead to specific agencies? 
149 

Answer. Because of the cross-cutting nature of these activities, which can involve 

a number of different USDA agencies, the Department proposed several years ago 

that the funding be provided to the Office of the Secretary. This approach allows 

the funding to be allocated in response to emerging issues to whatever agency or 

agencies have the appropriate expertise and knowledge to address them. In addition, having a central fund helps in the coordination of these activities within the 

Department and avoids duplication in agencies’ efforts. 

OFFICE OF THE SECRETARY, PROVINCIAL RECONSTRUCTION TEAMS

Question. How would the funding be allocated between Iraq and Afghanistan? Answer. USDA estimates that $5.3 million will be used to support PRT activities in Afghanistan and $7.2 million will be used to support PRT activities and related 

technical assistance in Iraq. These estimates are subject to change as conditions and 

opportunities dictate. 

Question. For each country, please explain what activities the members of the 

PRT will be involved in. 

Answer. In Iraq, USDA’s advisors serving with the PRTs will work to support a 

market-based approach to agribusiness; improve livestock health and animal production; improve the production of dryland agriculture, especially wheat yields and 

crop diversification; and increase the production and processing of horticultural 

crops. 

In Afghanistan, USDA will address many of the same issues, and will also continue efforts to improve irrigation and farm water use efficiency; promote post-harvest storage for improved nutrition; stimulate tree production, reforestation, and revegetation; and reestablish production of high-value horticultural crops. 

Question. How will you measure success? 

Answer. USDA’s PRT advisors rely on funding from USAID and the military to 

carry out specific reconstruction projects. In designing projects, each advisor will establish metrics to measure success. In the long-term, success will be evident in improved crop yields, increased irrigated land under cultivation, and greater food 

stores in periods of seasonal need. 

Question. How will you ensure these funds are used effectively? 

Answer. USDA has instituted programmatic and administrative controls in field 

offices as well as Washington-based offices. USDA coordinated closely with other 

U.S. Government, Iraqi, and Afghan agencies to ensure that programs are designed 

to meet the specific needs of the end users. 

Question. How much of the requested funding will go into the field? 

Answer. USDA estimates that of the $12.5 million requested for these activities 

in Iraq and Afghanistan, 76 percent or approximately $9.5 million will be used to 

cover in-country staff salaries, operations, and technical assistance/capacity building 

activities. 

Funding that is not used in country covers items that are essential for the administration and conduct of these activities. They include the costs for such things as 

recruitment and selection, medical and security clearances, supplies and equipment 

(e.g., satellite phones), travel for both recruitment interviews and deployment to the 

countries, and associated administrative costs of FAS, which administers these activities on behalf of the Department. 

Question. Will any of the requested funding go to the State Department and/or 

Defense Department? Is so, for what? 

Answer. USDA anticipates that approximately $200,000 will be transferred to the 

State Department to cover fiscal year 2008 International Cooperative Administrative Support Services (ICASS) charges related to USDA activities in Afghanistan. 

However, we do not anticipate that USDA will be assessed fiscal year 2008 ICASS 

charges for USDA activities in Iraq. 

AGRICULTURAL RESEARCH SERVICE, BUILDINGS AND FACILITIES

Question. How much will the new facility in Athens, Georgia cost to construct, furnish, and equip? 

Answer. The latest design and construction estimate is $207 million—$16 million 

for design in fiscal year 2008 and $191 million for construction. Equipment necessary for the facility is included in the total construction cost. 

Question. Please describe the process used to determine that this facility is necessary? 

Answer. Avian Influenza is a continuing problem in Asia where millions of poultry 

have been killed to protect both the industry and the consumers, and where over 

150 humans have died from infection after direct contact with sick birds. Avian influenza and other viral diseases of poultry, such as NewCastle disease that recently 
150 

devastated the poultry industry in the Southwest require new technologies to understand the origin and spread of the disease, their rapid detection and their control 

through vaccines and novel management approaches. A leading laboratory in the 

world to conduct research on such poultry diseases is the USDA Southeast Poultry 

Research Laboratory in Athens, Georgia. The high containment laboratory is housed 

in outdated facilities that make it difficult to meet the needs of a modern bio-containment facility. Clearly, a new facility is critical to the protection of humans as 

well as poultry. The proposed new, modernized facility will meet the long term 

needs for bio-containment laboratory and animal space. It will enable scientists to 

more adequately address the emerging/exotic poultry diseases which threaten not 

only the Nation’s poultry industry but potentially the health of hundreds of thousands of Americans. This new facility would consolidate existing facilities in Athens, 

Georgia, and East Lansing, Michigan, some of which were constructed as early as 

1939. 

Question. How will ARS manage this construction project to make sure it is on 

budget and on time? 

Answer. ARS has experience managing projects of this complexity and scope as 

evidenced by the successful implementation of the Ames Modernization Project. The 

engineering and contract management responsibilities and oversight will be handled 

by the ARS Facilities Division (FD). All detailed planning, design, scheduling and 

day-to-day construction inspection will be achieved through contracts with architectengineering firms with oversight provided by the FD. Rigorous quality assurance 

measures will be instituted and lessons learned from the Ames Modernization 

Project related to bio- containment construction will be incorporated into the management strategy to ensure budget, schedule, and quality issues are adequately addressed. 

Question. Are all ARS facilities currently in good repair? Do they meet all applicable state and Federal codes? Do they pose any threat to human health or safety? 

Please provide information, including an estimated cost, for each location where repairs are necessary to bring the facility into compliance. 

Answer. In response to Executive Order 13327, Real Property Asset Management, 

ARS is in the process of implementing a Facility Asset Management program that 

will capture accurate repair and modernization needs—information not currently 

available. A private firm specializing in documenting facility condition was hired to 

support our efforts by sampling facility condition, analyzing ARS replacement values, and providing estimates of repair needs based upon sampling results and industry metrics. Based upon this analysis it has been determined that the ARS facility portfolio is considered to be in ‘‘fair’’ condition with an average condition index 

of 0.90 out of 1.0, and total deferred maintenance needs estimated at $317 million. 

All human health or safety issues are handled immediately utilizing existing 

funding resources. All non-threatening code issues are addressed as funds become 

available. 

Question. Please provide an update on the status of the Anacostia Waterfront Corporation’s Riverwalk project along the perimeter of the U.S. National Arboretum. 

Answer. The U.S. National Arboretum (USNA) has contracted with a landscape 

architecture firm to develop a conceptual plan for improvements to and development 

of the USNA property adjacent to the Anacostia River water front. The plan includes access to the Anacostia River, a tram stop on the flood plain area, and considerable improvements to the entire Asian Collections. Portions of this area will become accessible and a new parking lot, as well as orientation and restroom facilities 

are planned. The USNA has met with the National Park Service to coordinate longrange plans which were then incorporated into a revised USNA Master Plan that 

was approved by the National Capital Planning Commission and the U. S. Commission on Fine Arts. 

USDA OVERSEAS ACTIVITIES

Question. Please provide information on the activities of USDA in the Middle 

East, Southwest Asia, India, Afghanistan, Pakistan, and East Africa. 

Answer. The requested information will be provided for the record. 

[The information follows:] 

Middle East and Southwest Asia.—With funding from the Department of State 

under the Middle East Partnership Initiative (MEPI), USDA is implementing 

projects supporting Free Trade Agreements (FTAs), Trade and Investment Framework Agreements (TIFAs), and WTO Accession for selected countries in the North 

Africa and the Gulf Region. Activities include technical assistance in food safety and 

food defense, animal health, plant health, and environmental considerations in 

these areas. 
151 

In Egypt, USDA and USAID are actively engaged in capacity building programs 

in cooperation with Egyptian Ministries. A main effort is to develop a biosafety regulatory system. Other U.S.-Egyptian capacity building efforts include U.S. interagency and Egyptian science and technology collaboration and training on sanitary 

and phytosanitary (SPS) standards. 

The Cochran Fellowship Program has trained 163 fellows from Southwest Asia 

and Middle Eastern countries since 1999. Recent programs include training in food 

safety, agricultural extension, grain procurement and poultry management. The 

Norman E. Borlaug International Agricultural Science and Technology Fellows Program (Borlaug Fellows Program) conducts faculty and scientist exchange programs 

with developing countries. During fiscal years 2004–2007, the Borlaug Fellows program included eight participants from the Middle East and 12 from Southwest Asia. 

India.—USDA is the lead agency on the U.S.-India Agricultural Knowledge Initiative (AKI), a 3-year public/private sector Presidential Initiative. Support for this initiative comes from USDA and across the U.S. Government, resulting in a large 

number of successful activities in four focus areas: (1) university capacity building; 

(2) biotechnology; (3) food processing and marketing; and (4) water resource management. For example, USDA is currently supporting four Animal and Plant Health 

Inspection Service (APHIS) technicians in India working on pre-clearance of mangoes. USDA is hosting two workshops on food safety regulations in Mumbai and 

Bangalore, with an upcoming workshop on biotechnology for the public and private 

sector and scientists. In addition, USDA worked with the National Association of 

State Universities and Land Grant Colleges to fund small seed grants to foster university-to-university collaboration. 

With funds from USAID, USDA is providing training and technical assistance to 

the Government of India on rural electrification and alternative financing models. 

The Cochran Fellowship Program has trained 97 Indians since 2000. Under the 

India-U.S. Agriculture Knowledge Initiative, the Cochran Program will train 12 individuals per year from 2006 through 2008. 

Afghanistan.—USDA’s primary technical assistance initiatives in Afghanistan address a range of issues, including livestock health, SPS standards, agricultural extension, conservation of biodiversity, rangelands and watersheds management, and 

capacity building in information technology and communications. Under the Provincial Reconstruction Team (PRT) program, USDA has deployed and supported 36 agricultural advisors from nine USDA agencies on 9-month assignments. The advisors’ 

activities focus on projects that rehabilitate a province’s agricultural infrastructure, 

both physical and institutional. In 2007, USDA is providing seven advisors for 

PRTs. 

The Cochran Fellowship Program has trained 14 Afghans since 2004 in the areas 

of small business entrepreneurship and animal disease diagnosis. The Cochran Program is currently planning programs for fiscal year 2007 and fiscal year 2008 in 

the areas of animal health and agricultural extension. 

Pakistan.—Under a reimbursable agreement, since 2006 USDA has had two staff 

members detailed to USAID/Pakistan, working on the 4-year, $200 million Pakistan 

Earthquake Reconstruction Program. USDA staff lead a 10-person team spread 

across four locations in Pakistan. The teams focus on construction, training, capacity 

building, and the rehabilitation of livelihoods (agriculture and markets). The Cochran Program has trained 20 Fellows from Pakistan since 2000 in the areas of feed 

manufacturing, grain procurement, cotton classification, cooperative development, 

biotechnology and wheat milling. 

East Africa.—In 2007, USDA led an Agribusiness Trade and Investment Mission 

to East Africa. Participant countries included Burundi, Ethiopia, Kenya, Rwanda, 

Tanzania, Uganda and Zambia. The Mission’s objectives were to promote U.S.-Africa 

agribusiness cooperation, trade, and investment. Under the Africa Growth and Opportunities Act (AGOA) USDA is implementing an SPS program that includes capacity building in plant and animal health and food safety systems for the East Africa region. This program specifically helps the following East African countries: 

Kenya, Ethiopia, Rwanda, Uganda, and Tanzania. The Cochran Fellowship Program 

has trained 207 fellows from East Africa; Cochran expects to train a total of 20– 

25 participants from these countries in fiscal year 2007. The Borlaug Fellows program on Women in Science has supported six scholars from Kenya and five from 

Uganda. 

USDA has also provided food assistance to various countries in these regions as 

follows: 
152 

USDA FOOD AID ACTIVITIES IN SELECTED COUNTRIES IN FISCAL YEAR 2006 AND FISCAL 

YEAR 2007 

[Dollars in millions] 

Country Activity Value 

Afghanistan ......................................................... School feeding ....................................................................... $26.2 

Afghanistan ......................................................... Agricultural development ...................................................... 12.7 

Afghanistan ......................................................... Agricultural and rural development ...................................... 10.4 

Afghanistan ......................................................... Agricultural and rural development ...................................... 9.5 

Bangladesh ......................................................... School feeding and food processing improvements ............. 4.4 

Bangladesh ......................................................... School feeding ....................................................................... 7.4 

Ethiopia ............................................................... Support for poverty alleviation programs ............................. 6.3 

Jordan .................................................................. Agricultural development, natural resource management, 

and income supplements for the poor.

20.0 

Kenya ................................................................... School feeding ....................................................................... 18.1 

Kenya ................................................................... Dairy development ................................................................. 7.8 

Kenya ................................................................... Rural development and improvement in financing system 9.1 

Lebanon ............................................................... Agricultural development and food security ......................... 9.2 

Mozambique ........................................................ Agricultural development ...................................................... 12.7 

Mozambique ........................................................ School feeding ....................................................................... 4.4 

Mozambique ........................................................ Rural development and HIV/AIDS education and prevention 8.4 

Pakistan .............................................................. School feeding and food processing improvement ............... 8.1 

Pakistan .............................................................. School feeding ....................................................................... 7.0 

Pakistan .............................................................. Relief for earthquake victims ............................................... 11.9 

Sri Lanka ............................................................. School feeding ....................................................................... 0.2 

Sri Lanka ............................................................. Agricultural development and de-mining ............................. 10.7 

Tanzania .............................................................. Agricultural development ...................................................... 6.8 

Yemen ................................................................. Rural development ................................................................ 11.6 

FOOD SAFETY RESEARCH

Question. Please provide an overview on all food safety research being conducted 

through ARS and CSREES. 

Answer. The information is submitted for the record. 

[The information follows:] 

ARS food safety research focuses on finding ways to assess and control potentially 

harmful food contaminants. These activities are conducted through 4 program components: microbial pathogens; chemical contaminants; mycotoxins and plant toxins. 

Research is designed to yield science-based knowledge on the safe production, storage, processing and handling of plant and animal products, and on the detection and 

control of toxin-producing and/or pathogenic bacteria and fungi, parasites, chemical 

contaminants, mycotoxins, plant toxins and biosecurity. This knowledge will assist 

regulatory agencies and the food industry in reducing the incidence of foodborne illnesses. ARS research also assists defense related agencies. 

The research program is directed towards improving public health, which is inline with other countries. Research accomplishments are measured by the development, transfer and implementation of new technologies to Federal agencies and the 

private sector. Since food-safety and -security are global issues, research also involves both national and international collaborations. 

The program’s role in bioterrorism related research is to establish methods to protect ‘‘at-risk’’ foods; strengthen and expand laboratory preparedness; and develop 

rapid and confirmatory laboratory methods to analyze suspect foods for ‘‘select 

agents,’’ toxins and chemical contaminants. 

Research is coordinated to meet the needs of USDA–FSIS; DHHS–FDA and the 

CDC, EPA and the DHS. The Program collaborates with the FDA, CDC, DHS, and 

fellow USDA agencies CSREES, ERS and FSIS on a wide variety of issues. 

A detailed 2006–2010 Action Plan outlining the ARS Food Safety Research Program is available at: http://www.ars.usda.gov/research/programs/programs.htm?nplcode=108&docid=278 

The Food Safety Program has a long history of accomplishments for its major 

stakeholders and customers. The 5-year Accomplishment Report is available at: 

http://www.ars.usda.gov/research/programs/programs.htm?nplcode=108&docid=7589 

Recent areas of accomplishment include: 

—Sensing technologies that enable detection of fecal contamination on animal carcasses and produce, helping lower the incidence of E. coli 0157:H7. 
153 

—Giving cattle an oral dose of sodium chlorate prior to slaughter holds promise 

as an effective intervention to kill E. coli in live cattle. 

—Rapid, sensitive and inexpensive assays for detecting pathogens and chemical 

residues, for example dioxins in food. 

Among the food safety research goals for the coming 5-years are: 

—Understanding the epidemiology and ecology of pathogens in the farm environment through production and processing. 

—Development of intervention strategies to control pathogens in animal and 

produce production and processing. 

—Identification of factors responsible for mediating antibiotic resistance in 

foodborne and other bacteria. 

—Genomics to understand the differences between pathogens and non-pathogens, 

and identify factors that encode for variations in virulence. 

—Development and validation of methodologies and rapid screening tests, including on-line methods, to detect fungal and plant toxins. 

The Food Safety Program involves 10 major laboratories and approximately 250 

scientists. The total budget for fiscal year 2007 is $105.2 million. 

CSREES’ competitively funded food safety research programs are presently focusing on a few areas of interest to U.S. agriculture and consumers, including microbial 

contamination of fresh produce which is minimally processed prior to consumption. 

Bacterial pathogens E. coli and Salmonella are emphasized in this area as they have 

been particularly problematic. Contamination of seafood with viruses and Vibrio 

bacteria, Campylobacter and Salmonella bacteria in poultry and swine, and epidemiological approaches to development of on-farm mitigation measures and analysis 

of critical control points are also focus areas for the Agency this year. Also funded 

are competitively awarded projects which couple research, education, and extension 

activities with focus on education, certification, and training of industry, retail personnel, and consumers. Integrated food safety projects also include emphasis in 

analysis of microbial contamination of fruits, vegetables, dairy, meat and poultry 

with subsequent information exchange through formal and informal educational settings. 

Funded projects cover a wide variety of food safety issues; however, all maintain 

a scope of funding that relies on producing real-world answers to problems facing 

the food production, processing, distribution and regulatory communities as well as 

consumers. Priority areas align with CSREES mission and relevant goals, and demonstrate relevance to U.S. agriculture. Priorities are assessed annually to ensure 

food safety programs are able to respond to emerging issues. It is estimated that 

$23 million of CSREES funds in fiscal year 2006, fiscal year 2007, and fiscal year 

2008 support food safety research. 

QUESTIONS SUBMITTED BY SENATOR ROBERT C. BYRD

NATURAL RESOURCES CONSERVATION SERVICE

Question. Could you please provide the committee with information regarding 

plans by the Department to close agency field offices across the country, including 

the possible reorganization of these offices within each State? The committee is 

aware that some States are currently operating with a deficit in funding and one 

of the options apparently being discussed to address these deficits is the reorganization of field offices in these states. I have been informed that NRCS in West Virginia, for example, could have a loss in workforce to address the deficit in our state. 

I have heard concerns from my constituents that a NRCS office in Hamlin, West 

Virginia, could be closed which will result in a loss of services to constituents in 

southern West Virginia. 

Answer. In the face of constrained discretionary funding levels, NRCS has taken 

appropriate management steps to ensure that NRCS operates within its budget. As 

part of this effort, a central point of focus has been to ensure that there is the right 

number of offices in the right places. NRCS has not prescribed specific office moves 

or consolidation from Washington, DC. Instead, NRCS leadership believes that local 

agency staff, including the State Conservationist, know the State and local needs 

better than anyone. State Conservationists have to manage and work within a budget allocation each year. As a result, states are working with local partners, stakeholders, and constituents to develop plans that work to the betterment of each locale. Consistent with the Department’s policy of keeping Congress informed of its 

activities, NRCS will notify Congress of office closures as appropriate. 
154 

RURAL DEVELOPMENT

Question. Could you please provide the committee with information regarding 

plans by the Department to close agency field offices across the country, including 

the possible reorganization of these offices within each State? The committee is 

aware that some states are currently operating with a deficit in funding and one 

of the options apparently being discussed to address these deficits is the reorganization of field offices in these states. I have heard concerns from my constituents that 

it is possible that Rural Development offices could be closed or reorganized in West 

Virginia which will result in a loss of services to my constituents. 

Answer. The Rural Development State Directors have developed their reorganization plans for National Office consideration. While some employees will be working 

at a different office location, we are making every effort to minimize the disruption 

to staff. Rural Development is not proposing a Reduction-in-Force and all employees 

will be offered a position at their current grade and pay level. We are also seeking 

Voluntary Early Retirement Authority which could be of interest to those employees 

who are several years short of being eligible for regular retirement. 

Since the State plans are currently being reviewed, we do not know the number 

of offices to be closed or that will operate on a part-time basis. RD will keep the 

committee informed of its plans. It is RD’s intent that the reorganization be completed by March, 2008. 

Our intent is to train staff so that they are knowledgeable in all Rural Development programs in order to provide better customer. We anticipate no reduction in 

services and plan to continue to provide comprehensive access to our programs. 

FARM SERVICE AGENCY

Question. Could you please provide the committee with information regarding 

plans by the Department to close agency field offices across the country, including 

the possible reorganization of these offices within each State? The committee is 

aware that some states are currently operating with a deficit in funding and one 

of the options apparently being discussed to address these deficits is the reorganization of field offices in these States. I have heard concerns from my constituents that 

it is possible that Farm Service Agency offices could be closed or reorganized in 

West Virginia which will result in a loss of services to my constituents. 

Answer. As competition and accountability for limited resources continue to increase, we want to ensure we are still providing our customers with the efficient, 

accurate and timely service they deserve. Our FSA State Executive Directors (SEDs) 

are conducting independent, local-level reviews of the efficiency and effectiveness of 

the FSA office structure in their State. In each State, the SED and State Committee 

have formed a review committee to develop proposals for the optimum network of 

FSA facilities, staffing, training, and technology for their State within existing budgetary resources and staffing ceilings. FSA is committed to meeting the needs of 

farmers and ranchers in the 21st century, and our hope is to wisely invest in our 

employees, technology and equipment. 

There is no comprehensive national plan or formula for identifying the optimum 

network of FSA offices. Each State will submit recommendations to FSA’s Deputy 

Administrator for Field Operations for review. If a State’s plan proposes office closures or consolidations, we will strictly and faithfully follow the congressional and 

public notification procedures as required and outlined in Public Law 110–5. If a 

State recommends that any of our offices be closed or consolidated, we will hold public meetings in that county with area farmers, ranchers, and stakeholders within 30 

days of headquarters concurrence with the plan. We will notify Congress of the 

Agency’s intent to close offices 120 days prior to closure. 

QUESTION SUBMITTED BY SENATOR ARLEN SPECTER

COMMODITY SUPPLEMENTAL FOOD PROGRAM

Question. The Commodity Supplemental Food Program (CSFP) provides 6.4 million food packages to over 500,000 mothers, infants, children, and primarily low-income seniors—in fiscal year 2005, 15,575 households in PA received CSFP packages. 

CSFP food packages are delivered monthly, and provide $20 worth of food including 

cheese, milk, and canned fruits and vegetables. In his fiscal year 2008 budget request, as in his fiscal year 2007 request, the President eliminated this program, 

stating that Food Stamps and the WIC program could meet the needs of CSFP recipients. Congress provided $112 million in fiscal year 2006 and has maintained 

that level in the fiscal year 2007 Continuing Resolution. Seniors, who represent 90 
155 

percent of CSFP recipients, are not eligible for the WIC program, and many of these 

seniors are also not eligible for food stamps, or are only eligible to receive $10 per 

month in food stamp benefits. Additionally, for seniors with disabilities, the CSFP 

program meets a vital need by bringing food directly to their homes. How does the 

Department plan to meet the needs of many of these seniors who depend on the 

CSFP program and who will not be eligible to receive any benefits, or will receive 

reduced benefits, from the Food Stamp program? 

Answer. Elderly participants who are leaving the CSFP upon termination of its 

funding and who are not already receiving food stamp benefits would be eligible to 

receive a transitional benefit worth $20 per month, ending in the first month following enrollment in the Food Stamp Program under normal program rules, or 6 

months, whichever occurs first. Based on the information we have about the characteristics of all elderly food stamp participants, the average monthly food stamp benefit for an elderly person living alone was $70 per month in 2005. The percentage 

of food stamp households with elderly that received the maximum benefit (14.1 percent) was nearly as large as the percentage that received the minimum benefit of 

$10 (15.5 percent). Using information on the financial circumstances of low-income 

elderly, we estimate that CSFP participants transitioning to food stamps will receive an average monthly benefit of $54 per person. 

Elderly CSFP participants who are ineligible for food stamps will be treated no 

differently than anyone else living in similar circumstances who is currently unable 

to participate in the CSFP due to its limited availability. Former CSFP participants 

will have access to the Emergency Food Assistance Program and other government 

and private non-profit programs that offer community-based food assistance opportunities. 

Included in these programs are Federal nutrition assistance programs targeted 

specifically to seniors. These programs, administered by the Administration on 

Aging and authorized by the Older Americans Act of 1965, include congregate nutrition services and home-delivered nutrition services. The Administration’s 2008 

budget request includes $383 million and $181 million for these two programs, respectively. In addition, the 2008 budget request includes $147 million for the Nutrition Services Incentive Program. Combined, the Older Americans Nutrition Programs serve about 250 million congregate and in-home meals to about 2.6 million 

older adults annually. 

FSIS IT INFRASTRUCTURE

Question. It is my understanding that USDA’s Food Safety and Inspection Service 

is initiating a major change in its inspection program in order to allocate Agency 

resources according to risk. In order to determine risk on an ongoing basis, the 

Agency will need to analyze a significant amount of data from a wide variety of diverse sources. Please detail the level of funding for information technology infrastructure for FSIS for fiscal year 2008 and compare this funding to 1) previous funding for information technology for FSIS for the past 3 fiscal years, and 2) information technology infrastructure funding for other agencies in the Department. 

Answer. A chart detailing the funding for information technology infrastructure 

for USDA by mission area, for the previous 3 fiscal years, is provided for the record. 

[The information follows:] 

INFORMATION TECHNOLOGY INVESTMENTS BY AGENCY 

[Dollars in Millions] 

Agency 

Fiscal Year 

2002 Actual 2006 Actual 2007 Estimate 2008 Budget 

Farm and Foreign Agricultural Services: 

Foreign Agricultural Service ................................ $23.3 $23.1 $29.9 $26.2 

Farm Service Agency ........................................... 237.6 263.6 270.4 303.0 

Risk Management Agency ................................... 17.6 20.4 21.7 30.7 

Subtotal, FFAS ................................................. 278.5 307.2 322.0 359.9 

Food Nutrition and Consumer Services: Food and Nutrition Service ........................................................... 52.2 593.8 605.3 641.2 

Food Safety: Food Safety and Inspection Service ........ 39.6 43.4 40.2 38.2 

Natural Resources and Environment: 

Natural Resources Conservation Service ............. 71.8 102.3 104.4 71.6 
156 

INFORMATION TECHNOLOGY INVESTMENTS BY AGENCY—Continued 

[Dollars in Millions] 

Agency 

Fiscal Year 

2002 Actual 2006 Actual 2007 Estimate 2008 Budget 

Forest Service ...................................................... 411.2 396.7 410.0 407.1 

Subtotal, NRE .................................................. 483.0 499.0 514.3 478.7 

Research, Education and Economics: 

Agricultural Research Service ............................. 37.4 52.2 59.1 39.3 

Cooperative State Research, Education & Extension Service ..................................................... 10.0 9.7 10.8 10.8 

Economic Research Service ................................. 7.1 7.3 6.1 6.3 

National Agricultural Statistics Service .............. 23.5 24.1 24.3 24.8 

Subtotal, REE .................................................. 78.0 93.2 100.3 81.3 

Rural Development: Rural Development ....................... 108.5 119.9 137.5 138.1 

Marketing and Regulatory Programs: 

Agricultural Marketing Service ............................ 18.1 35.8 35.2 48.3 

Animal and Plant Health Inspection Service ...... 75.1 81.7 73,7 76.2 

Grain Inspection, Packers & Stockyards Administration ........................................................... 6.9 12.6 12.3 10.7 

Subtotal, MRP ................................................. 100.0 130.0 121.2 135.2 

Office of the Chief Financial Officer: Office of the 

Chief Financial Officer ............................................. 83.4 99.5 188.7 118.8 

Office of the Chief Information Officer: 

Office of the Chief Information Officer ............... 145.0 62.2 54.0 30.2 

Common Computing Environment ....................... 179.9 128.3 217.8 ( /1/ ) 

Subtotal, OCIO ................................................. 324.9 190.4 271.8 30.2 

Staff Offices ................................................................. 45.7 44.7 56.5 69.7 

Total, Information Technology Investments ......... 1,593.9 2,121.0 ,357.9 2,091.3 

1 Fiscal year 2008 President’s Budget includes funding for CCE in FSA, RD, and NRCS. 

Question. Is the current level of funding sufficient for FSIS’ data analysis needs 

for the Agency’s new risk-based inspection initiative? 

Answer. The Food Safety and Inspection Service’s fiscal year 2008 budget request 

includes sufficient funding for hardware and software application needs, which includes the agency’s needs for risk-based inspection in processing. 

QUESTIONS SUBMITTED BY SENATOR CHRISTOPHER S. BOND

LOAN PROGRAM DELINQUENCY RATES

Question. For the geopolitical districts (States, Congressional districts) involved in 

each Federally declared disaster during the past 5 years, please provide a table 

showing the delinquency rates of participants in all USDA loan programs for each 

of the past 5 years. 

Please clearly indicate in which of the past 5 years the disaster affecting that district was declared and what the nature of the disaster was. 

Answer. I have asked my staff to prepare the available data. 

[The information follows:] 
157 

EMERGENCY DISASTER DESIGNATIONS APPROVED/PROCESSED BY EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH, PECD 

[Final totals for fiscal year 2002] 

State Abbrev Name PRE-Primary PRE-Contiguous ADM-Primary ADM-Contiguous SEC-Primary SEC-Contiguous PRE ADM SEC 

AL ............................................ Alabama .............. 19 35 ........................ ........................ ........................ 7 54 ........................ 7 AK ............................................ Alaska ................. 6 15 ........................ ........................ ........................ ........................ 21 ........................ ........................AZ ............................................ Arizona ................ 4 11 ........................ ........................ 20 10 15 ........................ 30 AR ............................................ Arkansas ............. 20 69 9 29 6 26 89 38 32 CA ............................................ California ............ ........................ 1 ........................ ........................ 10 49 1 ........................ 59 CO ............................................ Colorado .............. 59 9 ........................ ........................ 62 61 68 ........................ 123 CT ............................................ Connecticut ......... ........................ ........................ ........................ ........................ ........................ 10 ........................ ........................ 10 DE ............................................ Delaware ............. ........................ ........................ ........................ ........................ ........................ 1 ........................ ........................ 1 FL ............................................. Florida ................. 4 3 ........................ ........................ ........................ ........................ 7 ........................ ........................GA ............................................ Georgia ................ ........................ 5 2 10 25 86 5 12 111 HI ............................................. Hawaii ................. ........................ ........................ 1 ........................ ........................ ........................ ........................ 1 ........................ID ............................................. Idaho ................... ........................ ........................ ........................ ........................ 10 47 ........................ ........................ 57 IL ............................................. Illinois ................. 106 129 ........................ ........................ ........................ 9 235 ........................ 9 IN ............................................. Indiana ................ 72 112 5 22 6 34 184 27 40 IA ............................................. Iowa ..................... 21 26 ........................ ........................ 8 29 47 ........................ 37 KS ............................................ Kansas ................ 35 40 ........................ 6 75 135 75 6 210 KY ............................................ Kentucky .............. 86 157 ........................ 2 ........................ 19 243 2 19 LA ............................................ Louisiana ............. 15 15 ........................ 2 32 26 30 2 58 ME ........................................... Maine .................. ........................ ........................ 1 ........................ 27 5 ........................ 1 32 MD ........................................... Maryland ............. 3 7 1 ........................ ........................ 8 10 1 8 MA ........................................... Massachusetts .... ........................ ........................ ........................ ........................ 7 12 ........................ ........................ 19 MI ............................................ Michigan ............. 7 14 ........................ 1 107 59 21 1 166 MN ........................................... Minnesota ............ 26 70 ........................ ........................ 15 36 96 ........................ 51 MS ........................................... Mississippi .......... 21 38 6 15 21 43 59 21 64 MO ........................................... Missouri ............... 142 283 ........................ 1 14 51 425 1 65 MT ............................................ Montana .............. 5 10 ........................ ........................ 56 24 15 ........................ 80 NE ............................................ Nebraska ............. 1 5 9 35 104 125 6 44 229 NV ............................................ Nevada ................ ........................ ........................ ........................ ........................ 1 15 ........................ ........................ 16 NH ............................................ New Hampshire ... ........................ 2 ........................ ........................ ........................ 11 2 ........................ 11 NJ ............................................. New Jersey ........... ........................ ........................ ........................ ........................ ........................ ........................ ........................ ........................ ........................NM ........................................... New Mexico ......... ........................ 10 ........................ ........................ 38 24 10 ........................ 62 NY ............................................ New York ............. 56 15 1 4 54 106 71 5 160 NC ............................................ North Carolina ..... ........................ 8 ........................ ........................ 60 53 8 ........................ 113 ND ............................................ North Dakota ....... 10 35 ........................ ........................ 83 39 45 ........................ 122 OH ............................................ Ohio ..................... ........................ 10 ........................ 2 43 95 10 2 138 
158 

EMERGENCY DISASTER DESIGNATIONS APPROVED/PROCESSED BY EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH, PECD—Continued 

[Final totals for fiscal year 2002] 

State Abbrev Name PRE-Primary PRE-Contiguous ADM-Primary ADM-Contiguous SEC-Primary SEC-Contiguous PRE ADM SEC 

OK ............................................ Oklahoma ............ 48 37 1 4 105 28 85 5 133 OR ............................................ Oregon ................. 5 9 ........................ ........................ 7 26 14 ........................ 33 PA ............................................ Pennsylvania ....... ........................ 7 ........................ ........................ 46 36 7 ........................ 82 RI ............................................. Rhode Island ....... ........................ ........................ ........................ ........................ ........................ 4 ........................ ........................ 4 SC ............................................ South Carolina .... ........................ ........................ ........................ ........................ 46 11 ........................ ........................ 57 SD ............................................ South Dakota ...... ........................ 1 ........................ ........................ 55 54 1 ........................ 109 TN ............................................ Tennessee ............ 36 72 7 20 27 77 108 27 104 TX ............................................ Texas ................... 67 215 6 34 69 300 282 40 369 UT ............................................ Utah .................... ........................ 7 ........................ ........................ 53 11 7 ........................ 64 VT ............................................ Vermont ............... 4 15 ........................ ........................ 11 16 19 ........................ 27 VA ............................................ Virginia ................ 25 86 ........................ ........................ 14 80 111 ........................ 94 WA ........................................... Washington ......... ........................ ........................ 1 6 17 43 ........................ 7 60 WV ........................................... West Virginia ....... 11 41 ........................ ........................ ........................ 7 52 ........................ 7 WI ............................................ Wisconsin ............ 27 51 9 34 ........................ 6 78 43 6 WY ........................................... Wyoming .............. ........................ 4 ........................ ........................ 29 41 4 ........................ 70 

TOTALS ....................... ............................. 941 1,679 59 227 1,363 1,995 2,620 286 3,358 TOTALS ....................... 6,264 

PRE=Presidental, ADM=FSA Administrator, SEC=Sectretarial. 

EMERGENCY DISASTER DESIGNATIONS APPROVED/PROCESSED BY EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH, PECD 

[Preliminary totals for fiscal year 2003] 

State Abbrev Name PRE-Primary PRE-Contiguous ADM-Primary ADM-Contiguous SEC-Primary SEC-Contiguous PRE ADM SEC 

AL ............................................ Alabama .............. 69 68 ........................ 4 67 49 137 4 116 AK ............................................ Alaska ................. 11 18 ........................ ........................ ........................ ........................ 29 ........................ ........................AZ ............................................ Arizona ................ 1 6 ........................ ........................ 16 9 7 ........................ 25 AR ............................................ Arkansas ............. 41 75 28 72 93 48 116 100 141 CA ............................................ California ............ ........................ ........................ ........................ ........................ 52 74 ........................ ........................ 126 CO ............................................ Colorado .............. 29 28 ........................ 3 6 26 57 3 32 CT ............................................ Connecticut ......... 8 7 ........................ 8 8 13 15 8 21 DE ............................................ Delaware ............. 7 8 ........................ 1 3 7 15 1 10 
159 

FL ............................................. Florida ................. 10 20 ........................ 2 12 23 30 2 35 GA ............................................ Georgia ................ ........................ 32 4 13 270 67 32 17 337 HI ............................................. Hawaii ................. ........................ ........................ ........................ ........................ 1 ........................ ........................ ........................ 1 ID ............................................. Idaho ................... ........................ ........................ ........................ ........................ 24 35 ........................ ........................ 59 IL ............................................. Illinois ................. 16 46 ........................ 4 65 66 62 4 131 IN ............................................. Indiana ................ 67 87 ........................ ........................ 74 51 154 ........................ 125 IA ............................................. Iowa ..................... ........................ 4 2 11 21 34 4 13 55 KS ............................................ Kansas ................ 15 50 ........................ 5 63 66 65 5 129 KY ............................................ Kentucky .............. 119 157 ........................ 6 120 61 276 6 181 LA ............................................ Louisiana ............. 86 118 2 11 63 51 204 13 114 ME ........................................... Maine .................. 12 11 ........................ ........................ 16 2 23 ........................ 18 MD ........................................... Maryland ............. 44 52 ........................ ........................ 21 12 96 ........................ 33 MA ........................................... Massachusetts .... 14 14 10 3 12 12 28 13 24 MI ............................................ Michigan ............. 14 14 2 11 33 25 28 13 58 MN ........................................... Minnesota ............ ........................ ........................ 10 31 6 22 ........................ 41 28 MS ........................................... Mississippi .......... 57 114 ........................ 6 82 50 171 6 132 MO ........................................... Missouri ............... 75 73 ........................ 9 29 59 148 9 88 MT ............................................ Montana .............. ........................ ........................ ........................ ........................ 2 3 ........................ ........................ 5 NE ............................................ Nebraska ............. 19 52 21 62 53 17 71 83 70 NV ............................................ Nevada ................ ........................ ........................ ........................ ........................ 34 6 ........................ ........................ 40 NH ............................................ New Hampshire ... 7 15 ........................ 3 10 ........................ 22 3 10NJ ............................................. New Jersey ........... 26 22 8 12 19 20 48 20 39 NM ........................................... New Mexico ......... ........................ 3 ........................ ........................ ........................ 17 3 ........................ 17 NY ............................................ New York ............. 133 95 9 39 81 82 228 48 163 NC ............................................ North Carolina ..... 76 76 1 5 44 79 152 6 123 ND ............................................ North Dakota ....... 1 6 ........................ ........................ ........................ ........................ 7 ........................ ........................OH ............................................ Ohio ..................... 76 181 21 28 158 24 257 49 182 OK ............................................ Oklahoma ............ 41 77 1 5 75 47 118 6 122 OR ............................................ Oregon ................. ........................ ........................ ........................ ........................ 14 38 ........................ ........................ 52 PA ............................................ Pennsylvania ....... 50 111 ........................ 6 59 49 161 6 108 RI ............................................. Rhode Island ....... 2 6 ........................ 3 5 ........................ 8 3 5SC ............................................ South Carolina .... 6 15 ........................ ........................ 46 25 21 ........................ 71 SD ............................................ South Dakota ...... ........................ 5 9 18 8 31 5 27 39 TN ............................................ Tennessee ............ 120 179 3 9 108 149 299 12 257 TX ............................................ Texas ................... 91 212 1 9 163 222 303 10 385 UT ............................................ Utah .................... ........................ ........................ ........................ ........................ 29 8 ........................ ........................ 37 VT ............................................ Vermont ............... 4 16 ........................ 2 6 20 20 2 26 VA ............................................ Virginia ................ 139 166 15 48 105 144 305 63 249 WA ........................................... Washington ......... ........................ ........................ ........................ ........................ 34 86 ........................ ........................ 120 WV ........................................... West Virginia ....... 79 119 ........................ 12 51 54 198 12 105 
160 

EMERGENCY DISASTER DESIGNATIONS APPROVED/PROCESSED BY EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH, PECD—Continued 

[Preliminary totals for fiscal year 2003] 

State Abbrev Name PRE-Primary PRE-Contiguous ADM-Primary ADM-Contiguous SEC-Primary SEC-Contiguous PRE ADM SEC 

WI ............................................ Wisconsin ............ ........................ ........................ 4 16 41 35 ........................ 20 76 WY ........................................... Wyoming .............. ........................ 3 ........................ ........................ 7 11 3 ........................ 18 

TOTALS ....................... ............................. 1,565 2,361 151 477 2,309 2,029 3,926 628 4,338 GRAND TOTAL ............. 8,892 

PRE=Presidental, ADM=FSA Administrator, SEC=Sectretarial. 

EMERGENCY DISASTER DESIGNATIONS APPROVED/PROCESSED BY EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH, PECD 

[Preliminary totals for fiscal year 2004] 

State Abbrev Name PRE-Primary PRE-Contiguous ADM-Primary ADM-Contiguous SEC-Primary SEC-Contiguous PRE ADM SEC 

AL ............................................ Alabama .............. 67 44 ........................ ........................ ........................ 5 111 ........................ 5 AK ............................................ Alaska ................. ........................ ........................ ........................ ........................ ........................ ........................ ........................ ........................ ........................AZ ............................................ Arizona ................ ........................ 2 ........................ ........................ ........................ 9 2 ........................ 9 AR ............................................ Arkansas ............. 28 35 14 29 55 83 63 43 138 CA ............................................ California ............ 8 18 ........................ ........................ 40 181 26 ........................ 221 CO ............................................ Colorado .............. ........................ 2 ........................ 2 49 71 2 2 120 CT ............................................ Connecticut ......... 7 8 ........................ ........................ 8 9 15 ........................ 17 DE ............................................ Delaware ............. ........................ 2 ........................ ........................ ........................ 3 2 ........................ 3 FL ............................................. Florida ................. 174 117 ........................ ........................ ........................ 9 291 ........................ 9 GA ............................................ Georgia ................ 124 157 ........................ ........................ 87 37 281 ........................ 124 HI ............................................. Hawaii ................. ........................ ........................ 3 ........................ 7 2 ........................ 3 9 ID ............................................. Idaho ................... ........................ 7 ........................ ........................ 33 63 7 ........................ 96 IL ............................................. Illinois ................. 4 40 ........................ 5 42 53 44 5 95 IN ............................................. Indiana ................ 89 104 ........................ ........................ 30 34 193 ........................ 64 IA ............................................. Iowa ..................... 77 83 ........................ 9 72 74 160 9 146 KS ............................................ Kansas ................ 31 77 ........................ 2 129 103 108 2 232 KY ............................................ Kentucky .............. 105 92 1 6 ........................ 23 197 7 23 LA ............................................ Louisiana ............. 17 30 1 6 49 38 47 7 87 ME ........................................... Maine .................. 25 23 ........................ ........................ 4 9 48 ........................ 13 MD ........................................... Maryland ............. ........................ 11 ........................ ........................ ........................ ........................ 11 ........................ ........................MA ........................................... Massachusetts .... 17 15 ........................ ........................ 10 13 32 ........................ 23 
161 

MI ............................................ Michigan ............. 23 31 1 5 126 90 54 6 216 MN ........................................... Minnesota ............ ........................ 15 5 25 65 59 15 30 124 MS ........................................... Mississippi .......... 23 35 3 10 ........................ 11 58 13 11 MO ........................................... Missouri ............... 37 43 ........................ 5 78 81 80 5 159 MT ............................................ Montana .............. ........................ 4 ........................ ........................ 46 45 4 ........................ 91 NE ............................................ Nebraska ............. 39 61 17 50 61 99 100 67 160 NV ............................................ Nevada ................ 1 7 ........................ ........................ 17 13 8 ........................ 30 NH ............................................ New Hampshire ... 8 15 ........................ ........................ ........................ 6 23 ........................ 6 NJ ............................................. New Jersey ........... 2 12 ........................ ........................ 16 3 14 ........................ 19 NM ........................................... New Mexico ......... ........................ ........................ ........................ ........................ 32 20 ........................ ........................ 52 NY ............................................ New York ............. 18 62 7 20 55 101 80 27 156 NC ............................................ North Carolina ..... 86 79 ........................ 1 6 29 165 1 35 ND ............................................ North Dakota ....... 27 32 ........................ 4 82 44 59 4 126 OH ............................................ Ohio ..................... 72 130 ........................ ........................ 46 77 202 ........................ 123 OK ............................................ Oklahoma ............ ........................ 7 ........................ 1 ........................ 34 7 1 34 OR ............................................ Oregon ................. 30 10 ........................ ........................ 12 44 40 ........................ 56 PA ............................................ Pennsylvania ....... 70 102 2 14 1 19 172 16 20 RI ............................................. Rhode Island ....... ........................ 7 ........................ ........................ ........................ 6 7 ........................ 6 SC ............................................ South Carolina .... 22 57 ........................ ........................ 8 20 79 ........................ 28 SD ............................................ South Dakota ...... 9 21 ........................ 6 74 70 30 6 144 TN ............................................ Tennessee ............ ........................ 35 ........................ ........................ 12 32 35 ........................ 44 TX ............................................ Texas ................... ........................ 5 6 41 82 432 5 47 514 UT ............................................ Utah .................... ........................ ........................ ........................ ........................ 20 30 ........................ ........................ 50 VT ............................................ Vermont ............... 7 17 ........................ ........................ ........................ 4 24 ........................ 4 VA ............................................ Virginia ................ 22 64 2 6 9 50 86 8 59 WA ........................................... Washington ......... 15 18 ........................ ........................ 29 45 33 ........................ 74 WV ........................................... West Virginia ....... 84 124 ........................ 2 ........................ 4 208 2 4 WI ............................................ Wisconsin ............ 44 44 39 161 59 38 88 200 97 WY ........................................... Wyoming .............. ........................ ........................ ........................ 2 14 37 ........................ 2 51 

TOTALS ....................... ............................. 1,412 1,904 101 412 1,565 2,362 3,316 513 3,927 GRAND TOTAL ............. 7,756 

PRE=Presidental, ADM=FSA Administrator, SEC=Sectretarial. 
162 

EMERGENCY DISASTER DESIGNATIONS APPROVED/PROCESSED BY EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH, PECD 

[Final totals for fiscal year 2005] 

State Abbrev Name PRE-Primary PRE-Contiguous ADM-Primary ADM-Contiguous SEC-Primary SEC-Contiguous PRE ADM SEC 

AL ............................................ Alabama .............. 53 95 ........................ 10 ........................ 21 148 10 21 AK ............................................ Alaska ................. 3 5 ........................ ........................ ........................ ........................ 8 ........................ ........................AZ ............................................ Arizona ................ 15 18 3 6 ........................ 3 33 9 3 AR ............................................ Arkansas ............. 0 6 ........................ 2 40 56 6 2 96 CA ............................................ California ............ 15 18 1 5 49 146 33 6 195 CO ............................................ Colorado .............. 0 5 ........................ ........................ 5 23 5 ........................ 28 CT ............................................ Connecticut ......... 0 4 ........................ ........................ 4 9 4 ........................ 13 DE ............................................ Delaware ............. 1 2 ........................ ........................ ........................ ........................ 3 ........................ ........................FL ............................................. Florida ................. 30 62 ........................ 1 ........................ 4 92 1 4 GA ............................................ Georgia ................ 0 27 22 77 32 49 27 99 81 HI ............................................. Hawaii ................. 1 ........................ 4 ........................ ........................ ........................ 1 4 ........................ID ............................................. Idaho ................... 1 6 ........................ ........................ 11 37 7 ........................ 48 IL ............................................. Illinois ................. 16 24 ........................ ........................ 93 27 40 ........................ 120 IN ............................................. Indiana ................ 136 45 20 16 ........................ 24 181 36 24 IA ............................................. Iowa ..................... 0 6 ........................ 1 16 27 6 1 43 KS ............................................ Kansas ................ 41 35 ........................ 3 19 101 76 3 120 KY ............................................ Kentucky .............. 30 82 ........................ 10 ........................ 24 112 10 24 LA ............................................ Louisiana ............. 54 83 1 6 ........................ 20 137 7 20 ME ........................................... Maine .................. 13 11 ........................ ........................ 2 6 24 ........................ 8 MD ........................................... Maryland ............. 0 2 ........................ ........................ ........................ ........................ 2 ........................ ........................MA ........................................... Massachusetts .... 0 3 3 5 2 8 3 8 10 MI ............................................ Michigan ............. 0 3 27 25 94 41 3 52 135 MN ........................................... Minnesota ............ 7 19 ........................ ........................ 65 82 26 ........................ 147 MS ........................................... Mississippi .......... 74 70 11 44 69 49 144 55 118 MO ........................................... Missouri ............... 0 13 ........................ 1 112 20 13 1 132 MT ............................................ Montana .............. 0 1 ........................ ........................ 43 49 1 ........................ 92 NE ............................................ Nebraska ............. 11 26 12 32 30 54 37 44 84 NV ............................................ Nevada ................ 2 12 ........................ 3 19 13 14 3 32 NH ............................................ New Hampshire ... 0 5 ........................ 2 ........................ ........................ 5 2 ........................NJ ............................................. New Jersey ........... 14 30 ........................ ........................ 4 11 44 ........................ 15 NM ........................................... New Mexico ......... 0 10 ........................ ........................ 1 14 10 ........................ 15 NY ............................................ New York ............. 48 113 7 23 65 105 161 30 170 NC ............................................ North Carolina ..... 0 26 ........................ ........................ ........................ 7 26 ........................ 7 ND ............................................ North Dakota ....... 26 49 ........................ ........................ 14 23 75 ........................ 37 OH ............................................ Ohio ..................... 79 59 6 24 108 82 138 30 190 
163 

OK ............................................ Oklahoma ............ 0 10 ........................ ........................ 60 41 10 ........................ 101 OR ............................................ Oregon ................. 0 1 ........................ ........................ 5 26 1 ........................ 31 PA ............................................ Pennsylvania ....... 11 50 ........................ 2 ........................ 18 61 2 18 RI ............................................. Rhode Island ....... 0 ........................ ........................ ........................ ........................ ........................ 0 ........................ ........................SC ............................................ South Carolina .... 28 12 ........................ ........................ ........................ 1 40 ........................ 1 SD ............................................ South Dakota ...... 7 22 ........................ 3 3 26 29 3 29 TN ............................................ Tennessee ............ 15 47 1 4 30 69 62 5 99 TX ............................................ Texas ................... 22 35 3 21 96 579 57 24 675 UT ............................................ Utah .................... 10 31 1 5 2 17 41 6 19 VT ............................................ Vermont ............... ........................ 1 ........................ ........................ ........................ 6 1 ........................ 6 VA ............................................ Virginia ................ 10 13 ........................ ........................ 2 8 23 ........................ 10 WA ........................................... Washington ......... 0 2 ........................ ........................ 9 27 2 ........................ 36 WV ........................................... West Virginia ....... 6 20 ........................ 4 ........................ 19 26 4 19 WI ............................................ Wisconsin ............ 0 ........................ ........................ ........................ 16 58 0 ........................ 74 WY ........................................... Wyoming .............. 1 5 ........................ 3 5 12 6 3 17 

TOTALS ....................... ............................. 780 1,224 122 338 1,125 2,042 2,004 460 3,167 GRAND TOTAL ............. 5,631 

PRE=Presidental, ADM=FSA Administrator, SEC=Sectretarial. 

EMERGENCY DISASTER DESIGNATIONS APPROVED/PROCESSED BY THE DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES), PECD 

[Final totals for fiscal year 2006] 

State Abbrev Name PRE-Primary PRE-Contiguous ADM-Primary ADM-Contiguous SEC-Primary SEC-Contiguous PRE ADM SEC 

AL ............................................ Alabama .............. ........................ ........................ ........................ 2 67 103 ........................ 2 170 AK ............................................ Alaska ................. 1 3 ........................ ........................ ........................ ........................ 4 ........................ ........................AZ ............................................ Arizona ................ 6 14 ........................ ........................ 14 10 20 ........................ 24 AR ............................................ Arkansas ............. 7 29 23 72 98 113 36 95 211 CA ............................................ California ............ 48 54 ........................ ........................ 55 97 102 ........................ 152 CO ............................................ Colorado .............. ........................ 5 ........................ ........................ 79 187 5 ........................ 266 CT ............................................ Connecticut ......... 5 14 1 5 16 17 19 6 33 DE ............................................ Delaware ............. 1 4 ........................ ........................ ........................ 2 5 ........................ 2 FL ............................................. Florida ................. 17 35 ........................ ........................ ........................ 15 52 ........................ 15 GA ............................................ Georgia ................ ........................ 6 7 36 267 57 6 43 324 HI ............................................. Hawaii ................. 2 ........................ 2 ........................ 2 ........................ 2 2 2 ID ............................................. Idaho ................... 1 9 ........................ ........................ ........................ 12 10 ........................ 12 IL ............................................. Illinois ................. 6 22 ........................ ........................ 5 33 28 ........................ 38 
164 

EMERGENCY DISASTER DESIGNATIONS APPROVED/PROCESSED BY THE DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES), PECD— 

Continued 

[Final totals for fiscal year 2006] 

State Abbrev Name PRE-Primary PRE-Contiguous ADM-Primary ADM-Contiguous SEC-Primary SEC-Contiguous PRE ADM SEC 

IN ............................................. Indiana ................ 2 5 5 15 24 47 7 20 71 IA ............................................. Iowa ..................... ........................ 2 2 12 24 68 2 14 92 KS ............................................ Kansas ................ 24 48 ........................ ........................ 12 109 72 ........................ 121 KY ............................................ Kentucky .............. 2 23 ........................ ........................ 109 43 25 ........................ 152 LA ............................................ Louisiana ............. 8 32 ........................ ........................ 40 41 40 ........................ 81 ME ........................................... Maine .................. 1 4 ........................ ........................ ........................ 2 5 ........................ 2 MD ........................................... Maryland ............. 3 24 ........................ ........................ ........................ 6 27 ........................ 6 MA ........................................... Massachusetts .... 12 17 1 3 13 27 29 4 40 MI ............................................ Michigan ............. ........................ 2 ........................ ........................ 74 79 2 ........................ 153 MN ........................................... Minnesota ............ 18 40 1 6 36 37 58 7 73 MS ........................................... Mississippi .......... ........................ 4 ........................ ........................ 166 28 4 ........................ 194 MO ........................................... Missouri ............... 48 155 ........................ 12 ........................ 17 203 12 17 MT ............................................ Montana .............. ........................ 7 4 18 3 25 7 22 28 NE ............................................ Nebraska ............. 29 35 ........................ ........................ 98 136 64 ........................ 234 NV ............................................ Nevada ................ 6 16 ........................ ........................ ........................ 13 22 ........................ 13 NH ............................................ New Hampshire ... 13 20 ........................ ........................ 10 7 33 ........................ 17 NJ ............................................. New Jersey ........... 3 15 ........................ ........................ 36 12 18 ........................ 48 NM ........................................... New Mexico ......... 15 34 ........................ ........................ 31 31 49 ........................ 62 NY ............................................ New York ............. 21 59 3 18 93 267 80 21 360 NC ............................................ North Carolina ..... 10 22 ........................ ........................ ........................ 33 32 ........................ 33 ND ............................................ North Dakota ....... 35 50 ........................ 4 90 38 85 4 128 OH ............................................ Ohio ..................... 9 24 ........................ ........................ ........................ 19 33 ........................ 19 OK ............................................ Oklahoma ............ 29 73 1 11 154 55 102 12 209 OR ............................................ Oregon ................. 20 26 ........................ ........................ 10 61 46 ........................ 71 PA ............................................ Pennsylvania ....... 28 96 ........................ ........................ 23 60 124 ........................ 83 RI ............................................. Rhode Island ....... ........................ 6 ........................ ........................ 5 12 6 ........................ 17 SC ............................................ South Carolina .... 7 7 ........................ 4 ........................ 18 14 4 18 SD ............................................ South Dakota ...... 32 44 3 13 94 156 76 16 250 TN ............................................ Tennessee ............ 15 51 2 15 42 153 66 17 195 TX ............................................ Texas ................... 33 123 2 9 342 1,252 156 11 1,594 UT ............................................ Utah .................... ........................ 1 ........................ ........................ 1 12 1 ........................ 13 VT ............................................ Vermont ............... ........................ 12 ........................ ........................ 14 25 12 ........................ 39 VA ............................................ Virginia ................ 37 68 ........................ ........................ 51 142 105 ........................ 193 
165 

WA ........................................... Washington ......... 11 13 ........................ ........................ 28 42 24 ........................ 70 WV ........................................... West Virginia ....... ........................ 5 ........................ ........................ 29 30 5 ........................ 59 WI ............................................ Wisconsin ............ ........................ ........................ 3 12 46 98 ........................ 15 144 WY ........................................... Wyoming .............. ........................ 1 ........................ ........................ ........................ 14 1 ........................ 14 

TOTALS ....................... ............................. 565 1,359 60 267 2,301 3,861 1,924 327 6,162 GRAND TOTAL ............. 8,413 

PRE=Presidental, ADM=FSA Administrator, SEC=Sectretarial. 
166 

This data represents the dollar delinquency rate for all geographic counties, 

whether or not there was any loan activity in those counties. Data is as of December 

31 in order to correspond to calendar year Presidential and Secretarial disaster declarations. For the year of the disaster declaration, primary counties are highlighted 

in red and contiguous counties in yellow. This data represents a snapshot on a particular day. In some instances, the delinquencies identified may be resolved within 

days as producers sell their crop and apply the proceeds to their loans 
167 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES) 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

ALABAMA ..................................................................................................................................... AUTAUGA .............................. ........................ ........................ ........................ .01 .08 ALABAMA ..................................................................................................................................... BALDWIN ............................... ........................ .36 2.89 3.02 .99 ALABAMA ..................................................................................................................................... BARBOUR ............................. ........................ ........................ ........................ 1.47 .04 ALABAMA ..................................................................................................................................... BIBB ..................................... ........................ ........................ ........................ ........................ 13.38 ALABAMA ..................................................................................................................................... BLOUNT ................................ 2.55 1.47 1.65 1.15 9.29 ALABAMA ..................................................................................................................................... BULLOCK .............................. ........................ ........................ ........................ ........................ 12.85 ALABAMA ..................................................................................................................................... BUTLER ................................. ........................ .76 5.90 3.25 ........................ALABAMA ..................................................................................................................................... CALHOUN .............................. ........................ ........................ ........................ 1.34 .70 ALABAMA ..................................................................................................................................... CHAMBERS ........................... ........................ ........................ 1.17 .92 ........................ALABAMA ..................................................................................................................................... CHEROKEE ............................ .12 2.29 .84 ........................ 1.04 ALABAMA ..................................................................................................................................... CHILTON ............................... ........................ ........................ 2.30 1.98 16.72 ALABAMA ..................................................................................................................................... CHOCTAW ............................. 100.00 62.66 33.12 25.45 8.34 ALABAMA ..................................................................................................................................... CLARKE ................................. ........................ ........................ ........................ ........................ ........................ALABAMA ..................................................................................................................................... CLAY ..................................... .77 .98 2.99 ........................ ........................ALABAMA ..................................................................................................................................... CLEBURNE ............................ 36.33 4.77 7.68 4.76 2.88 ALABAMA ..................................................................................................................................... COFFEE ................................. ........................ .68 1.35 .33 .27 ALABAMA ..................................................................................................................................... COLBERT .............................. .28 ........................ ........................ 3.50 2.42 ALABAMA ..................................................................................................................................... CONECUH ............................. 4.33 3.79 1.14 5.13 ........................ALABAMA ..................................................................................................................................... COOSA .................................. ........................ ........................ ........................ ........................ ........................ALABAMA ..................................................................................................................................... COVINGTON ........................... ........................ ........................ ........................ .29 ........................ALABAMA ..................................................................................................................................... CRENSHAW ........................... ........................ ........................ ........................ ........................ ........................ALABAMA ..................................................................................................................................... CULLMAN .............................. ........................ 8.60 4.18 1.99 1.72 ALABAMA ..................................................................................................................................... DALE ..................................... ........................ 2.96 ........................ ........................ ........................ALABAMA ..................................................................................................................................... DALLAS ................................. 1.01 1.05 4.01 .62 .65 ALABAMA ..................................................................................................................................... DE KALB ............................... 7.15 2.33 5.49 3.86 2.80 ALABAMA ..................................................................................................................................... ELMORE ................................ ........................ 10.38 1.49 1.20 .64 ALABAMA ..................................................................................................................................... ESCAMBIA ............................. 1.72 .38 ........................ 4.17 4.00 ALABAMA ..................................................................................................................................... ETOWAH ................................ 2.22 2.18 .93 14.89 7.83 ALABAMA ..................................................................................................................................... FAYETTE ................................ ........................ ........................ ........................ 3.08 3.75 ALABAMA ..................................................................................................................................... FRANKLIN .............................. 1.01 .92 .84 .94 1.18 ALABAMA ..................................................................................................................................... GENEVA ................................ 2.81 4.15 3.73 3.77 3.58 ALABAMA ..................................................................................................................................... GREENE ................................ 1.86 .94 1.28 1.89 5.83 ALABAMA ..................................................................................................................................... HALE ..................................... 7.16 15.01 7.92 6.29 .73 ALABAMA ..................................................................................................................................... HENRY .................................. ........................ ........................ 2.58 4.29 1.61 ALABAMA ..................................................................................................................................... HOUSTON .............................. ........................ 7.73 5.22 4.10 2.63 
168 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

ALABAMA ..................................................................................................................................... JACKSON ............................... 5.22 7.37 9.79 8.19 5.49 ALABAMA ..................................................................................................................................... JEFFERSON ........................... ........................ ........................ 10.86 ........................ ........................ALABAMA ..................................................................................................................................... LAMAR .................................. ........................ ........................ ........................ 3.30 2.91 ALABAMA ..................................................................................................................................... LAUDERDALE ........................ 1.25 .81 12.12 11.75 8.91 ALABAMA ..................................................................................................................................... LAWRENCE ............................ 11.42 9.59 7.31 5.25 4.20 ALABAMA ..................................................................................................................................... LEE ....................................... ........................ ........................ 15.54 ........................ ........................ALABAMA ..................................................................................................................................... LIMESTONE ........................... 2.51 1.05 .66 2.30 .10 ALABAMA ..................................................................................................................................... LOWNDES .............................. 15.00 17.36 16.71 14.30 14.66 ALABAMA ..................................................................................................................................... MACON ................................. 4.93 ........................ 8.92 ........................ ........................ALABAMA ..................................................................................................................................... MADISON .............................. 2.39 .65 1.40 2.13 .17 ALABAMA ..................................................................................................................................... MARENGO ............................. 3.21 3.78 2.87 1.73 1.57 ALABAMA ..................................................................................................................................... MARION ................................ ........................ ........................ 5.36 ........................ .57 ALABAMA ..................................................................................................................................... MARSHALL ............................ .02 .97 2.42 .03 8.02 ALABAMA ..................................................................................................................................... MOBILE ................................. ........................ 1.32 ........................ 14.97 ........................ALABAMA ..................................................................................................................................... MONROE ............................... 1.49 1.39 2.23 1.49 1.13 ALABAMA ..................................................................................................................................... MONTGOMERY ...................... .13 .20 2.30 ........................ 4.37 ALABAMA ..................................................................................................................................... MORGAN ............................... ........................ ........................ ........................ ........................ .29 ALABAMA ..................................................................................................................................... PERRY .................................. 11.51 10.92 3.92 5.46 1.29 ALABAMA ..................................................................................................................................... PICKENS ............................... 3.79 3.76 1.60 1.93 .59 ALABAMA ..................................................................................................................................... PIKE ...................................... ........................ ........................ ........................ ........................ 18.73 ALABAMA ..................................................................................................................................... RANDOLPH ............................ .28 .12 .33 .07 ........................ALABAMA ..................................................................................................................................... RUSSELL ............................... ........................ ........................ ........................ ........................ ........................ALABAMA ..................................................................................................................................... SHELBY ................................. ........................ ........................ ........................ 8.48 6.54 ALABAMA ..................................................................................................................................... ST. CLAIR ............................. ........................ ........................ ........................ ........................ ........................ALABAMA ..................................................................................................................................... SUMTER ................................ 10.43 4.20 4.93 8.01 8.21 ALABAMA ..................................................................................................................................... TALLADEGA ........................... 1.83 ........................ ........................ ........................ 2.14 ALABAMA ..................................................................................................................................... TALLAPOOSA ......................... ........................ 2.24 ........................ ........................ 2.44 ALABAMA ..................................................................................................................................... TUSCALOOSA ........................ 1.08 .62 3.82 .18 ........................ALABAMA ..................................................................................................................................... WALKER ................................ ........................ ........................ ........................ ........................ ........................ALABAMA ..................................................................................................................................... WASHINGTON ........................ ........................ ........................ ........................ ........................ 3.16 ALABAMA ..................................................................................................................................... WILCOX ................................. 2.12 ........................ 1.93 .31 ........................ALABAMA ..................................................................................................................................... WINSTON ............................... ........................ ........................ .27 1.79 1.76 ALASKA ........................................................................................................................................ ALEUTIANS E BOROUGH ....... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ ALEUTIANS W CENSUS A ...... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ ANCHORAGE BOROUGH ........ ........................ ........................ ........................ ........................ ........................
169 

ALASKA ........................................................................................................................................ BETHEL CENSUS AREA ......... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ BRISTOL BAY BOROUGH ....... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ DENALI BOROUGH ................ ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ DILLINGHAM CENSUS A ........ ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ FAIRBANKS NORTH STAR ...... 11.75 10.74 8.53 11.32 5.82 ALASKA ........................................................................................................................................ HAINES BOROUGH ................ ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ JUNEAU ................................. .17 1.33 1.40 8.95 5.50 ALASKA ........................................................................................................................................ KENAI PENINSULA ................. 4.12 ........................ ........................ ........................ 15.99 ALASKA ........................................................................................................................................ KETCHIKAN GATEWAY ........... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ KODIAK ISL. BOROUGH ......... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ LAKE & PENINSULA .............. ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ MATANUSKA-SUSITNA ........... 14.53 10.61 7.19 4.15 3.89 ALASKA ........................................................................................................................................ NOME CENSUS AREA ............ ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ NORTH SLOPE BOROUGH ..... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ NORTHWEST ARCTIC ............. ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ PRINCE OF WALES ................ ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ SITKA BOROUGH ................... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ SKAGWAY-YAKUTAT-ANGO .... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ SOUTHEAST FAIRBANKS ........ ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ VALDEZ-CORDOVA ................ ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ WADE-HAMPTON ................... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ WRANGELL-PETERSBURG ..... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ YAKUTAT ............................... ........................ ........................ ........................ ........................ ........................ALASKA ........................................................................................................................................ YUKON-KOYUKUK .................. ........................ ........................ ........................ ........................ ........................ARIZONA ...................................................................................................................................... APACHE,S ............................. 38.25 32.21 23.82 10.62 8.74 ARIZONA ...................................................................................................................................... COCHISE ............................... 19.73 20.85 20.15 14.46 22.17 ARIZONA ...................................................................................................................................... COCONINO ............................ ........................ ........................ 11.99 10.45 15.54 ARIZONA ...................................................................................................................................... GILA ...................................... 86.80 72.30 63.01 44.74 ........................ARIZONA ...................................................................................................................................... GRAHAM ............................... 18.78 8.77 5.11 33.36 31.82 ARIZONA ...................................................................................................................................... GREENLEE ............................ ........................ ........................ ........................ ........................ 19.31 ARIZONA ...................................................................................................................................... LA PAZ .................................. ........................ ........................ 4.61 ........................ 19.71 ARIZONA ...................................................................................................................................... MARICOPA ............................ 21.63 48.43 39.07 66.94 62.73 ARIZONA ...................................................................................................................................... MOHAVE ................................ 9.17 1.49 9.28 8.05 9.44 ARIZONA ...................................................................................................................................... NAVAJO,S .............................. 70.65 32.30 80.77 76.52 58.92 ARIZONA ...................................................................................................................................... PIMA ..................................... 54.40 100.00 47.09 43.44 45.98 ARIZONA ...................................................................................................................................... PINAL .................................... 24.87 23.21 3.46 19.13 13.15 ARIZONA ...................................................................................................................................... SANTA CRUZ ......................... ........................ ........................ ........................ ........................ ........................ARIZONA ...................................................................................................................................... YAVAPAI ................................ ........................ 80.69 78.00 76.27 71.46 ARIZONA ...................................................................................................................................... YUMA .................................... ........................ ........................ ........................ .13 11.30 ARKANSAS ................................................................................................................................... ARKANSAS ............................ 6.38 8.46 5.92 7.33 8.45 
170 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

ARKANSAS ................................................................................................................................... ASHLEY ................................. 15.50 26.88 22.61 30.67 32.25 ARKANSAS ................................................................................................................................... BAXTER ................................. .04 .03 .18 .07 ........................ARKANSAS ................................................................................................................................... BENTON ................................ 5.16 9.05 6.22 4.90 8.93 ARKANSAS ................................................................................................................................... BOONE .................................. ........................ ........................ .10 .01 .03 ARKANSAS ................................................................................................................................... BRADLEY .............................. 44.57 44.07 48.42 51.24 39.29 ARKANSAS ................................................................................................................................... CALHOUN .............................. 57.07 53.37 46.60 38.11 23.28 ARKANSAS ................................................................................................................................... CARROLL .............................. 1.74 1.67 1.52 .96 .50 ARKANSAS ................................................................................................................................... CHICOT ................................. 30.48 25.83 24.66 20.40 26.57 ARKANSAS ................................................................................................................................... CLARK ................................... .14 15.56 14.32 1.39 3.03 ARKANSAS ................................................................................................................................... CLAY ..................................... .57 7.53 2.66 3.22 .04 ARKANSAS ................................................................................................................................... CLEBURNE ............................ 1.50 .83 .88 1.12 1.88 ARKANSAS ................................................................................................................................... CLEVELAND ........................... ........................ ........................ ........................ ........................ ........................ARKANSAS ................................................................................................................................... COLUMBIA ............................ ........................ ........................ ........................ 25.19 20.54 ARKANSAS ................................................................................................................................... CONWAY ............................... 3.72 4.01 4.60 3.33 3.10 ARKANSAS ................................................................................................................................... CRAIGHEAD ........................... 2.18 3.06 .88 6.90 4.34 ARKANSAS ................................................................................................................................... CRAWFORD ........................... 2.36 .76 3.86 2.48 2.53 ARKANSAS ................................................................................................................................... CRITTENDEN ......................... 25.94 35.00 37.17 30.91 31.61 ARKANSAS ................................................................................................................................... CROSS .................................. 22.11 10.77 20.66 11.07 9.75 ARKANSAS ................................................................................................................................... DALLAS ................................. 9.09 ........................ ........................ .38 6.19 ARKANSAS ................................................................................................................................... DESHA .................................. 4.25 2.69 5.72 7.53 4.99 ARKANSAS ................................................................................................................................... DREW .................................... 19.45 4.28 2.29 14.55 10.97 ARKANSAS ................................................................................................................................... FAULKNER ............................. 26.65 20.50 14.94 1.10 4.57 ARKANSAS ................................................................................................................................... FRANKLIN .............................. .85 .76 .37 2.40 2.24 ARKANSAS ................................................................................................................................... FULTON ................................. 4.65 1.70 2.57 1.38 1.41 ARKANSAS ................................................................................................................................... GARLAND .............................. 19.47 ........................ ........................ .25 ........................ARKANSAS ................................................................................................................................... GRANT .................................. ........................ 6.00 57.29 57.50 59.97 ARKANSAS ................................................................................................................................... GREENE ................................ ........................ .18 3.20 9.74 16.34 ARKANSAS ................................................................................................................................... HEMPSTEAD .......................... .42 2.88 4.13 2.72 1.18 ARKANSAS ................................................................................................................................... HOT SPRING ......................... 2.45 ........................ ........................ .21 .04 ARKANSAS ................................................................................................................................... HOWARD ............................... 21.67 21.65 18.48 15.12 13.28 ARKANSAS ................................................................................................................................... INDEPENDENCE .................... 4.49 3.47 4.46 1.74 2.08 ARKANSAS ................................................................................................................................... IZARD ................................... .78 1.12 .89 8.44 7.17 ARKANSAS ................................................................................................................................... JACKSON ............................... 8.03 5.39 4.12 12.11 18.23 ARKANSAS ................................................................................................................................... JEFFERSON ........................... 17.66 17.57 18.59 20.55 15.71 ARKANSAS ................................................................................................................................... JOHNSON .............................. .73 .33 .34 .21 .22 
171 

ARKANSAS ................................................................................................................................... LAFAYETTE ............................ 7.14 6.68 8.55 10.98 8.83 ARKANSAS ................................................................................................................................... LAWRENCE ............................ .27 .25 ........................ .02 13.38 ARKANSAS ................................................................................................................................... LEE ....................................... 21.15 21.84 20.10 24.83 25.61 ARKANSAS ................................................................................................................................... LINCOLN ............................... 44.89 44.62 33.82 25.54 20.05 ARKANSAS ................................................................................................................................... LITTLE RIVER ........................ 5.63 15.13 21.42 19.06 15.89 ARKANSAS ................................................................................................................................... LOGAN .................................. 8.47 5.33 5.11 .29 1.15 ARKANSAS ................................................................................................................................... LONOKE ................................ 8.93 7.39 5.63 4.52 5.72 ARKANSAS ................................................................................................................................... MADISON .............................. .14 .13 5.67 13.10 10.00 ARKANSAS ................................................................................................................................... MARION ................................ ........................ ........................ 10.70 11.33 9.53 ARKANSAS ................................................................................................................................... MILLER ................................. 3.55 1.89 5.62 3.94 3.58 ARKANSAS ................................................................................................................................... MISSISSIPPI .......................... 2.31 2.45 4.66 3.31 5.75 ARKANSAS ................................................................................................................................... MONROE ............................... 12.17 11.97 20.02 22.42 29.36 ARKANSAS ................................................................................................................................... MONTGOMERY ...................... 8.29 6.87 6.85 5.95 2.79 ARKANSAS ................................................................................................................................... NEVADA ................................ 23.13 24.92 19.65 17.26 17.57 ARKANSAS ................................................................................................................................... NEWTON ................................ ........................ ........................ ........................ ........................ ........................ARKANSAS ................................................................................................................................... OUACHITA ............................. 1.26 41.07 19.28 10.29 5.70 ARKANSAS ................................................................................................................................... PERRY .................................. ........................ ........................ .93 ........................ ........................ARKANSAS ................................................................................................................................... PHILLIPS ............................... 36.77 35.21 33.13 34.06 33.43 ARKANSAS ................................................................................................................................... PIKE ...................................... 1.71 12.05 11.79 6.83 12.35 ARKANSAS ................................................................................................................................... POINSETT .............................. 2.14 3.80 7.08 10.69 10.39 ARKANSAS ................................................................................................................................... POLK ..................................... 2.38 1.79 1.26 .64 2.02 ARKANSAS ................................................................................................................................... POPE ..................................... 5.60 4.28 2.38 .69 .32 ARKANSAS ................................................................................................................................... PRAIRIE ................................ 11.70 10.77 6.50 5.63 2.71 ARKANSAS ................................................................................................................................... PULASKI ................................ 1.91 1.79 1.54 3.08 19.15 ARKANSAS ................................................................................................................................... RANDOLPH ............................ 6.76 8.20 7.49 4.69 3.96 ARKANSAS ................................................................................................................................... SALINE .................................. ........................ 5.45 2.74 ........................ ........................ARKANSAS ................................................................................................................................... SCOTT ................................... 2.38 1.68 .05 ........................ ........................ARKANSAS ................................................................................................................................... SEARCY ................................ 3.40 2.42 2.58 4.63 .22 ARKANSAS ................................................................................................................................... SEBASTIAN ............................ ........................ 2.04 1.19 .24 ........................ARKANSAS ................................................................................................................................... SEVIER .................................. 2.82 1.94 4.65 4.53 3.72 ARKANSAS ................................................................................................................................... SHARP .................................. .11 .87 1.43 1.45 1.39 ARKANSAS ................................................................................................................................... ST. FRANCIS ......................... 15.12 5.17 5.64 5.14 5.17 ARKANSAS ................................................................................................................................... STONE ................................... .80 .60 1.78 1.56 .40 ARKANSAS ................................................................................................................................... UNION ................................... 18.71 12.14 9.31 8.02 6.78 ARKANSAS ................................................................................................................................... VAN BUREN .......................... 2.48 8.03 6.57 6.09 5.76 ARKANSAS ................................................................................................................................... WASHINGTON ........................ 3.63 2.05 1.07 1.12 9.48 ARKANSAS ................................................................................................................................... WHITE ................................... 4.47 4.63 7.18 9.68 9.84 ARKANSAS ................................................................................................................................... WOODRUFF ........................... 21.91 21.26 21.96 18.11 17.66 ARKANSAS ................................................................................................................................... YELL ..................................... .14 .16 .28 .11 .42 CALIFORNIA ................................................................................................................................. ALAMEDA .............................. ........................ ........................ ........................ 12.00 53.62 
172 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

CALIFORNIA ................................................................................................................................. ALPINE .................................. ........................ ........................ ........................ ........................ ........................CALIFORNIA ................................................................................................................................. AMADOR ............................... 2.63 2.72 .31 ........................ 4.39 CALIFORNIA ................................................................................................................................. BUTTE ................................... 10.64 18.08 12.49 20.14 17.14 CALIFORNIA ................................................................................................................................. CALAVERAS ........................... 63.73 94.84 14.25 5.74 ........................CALIFORNIA ................................................................................................................................. COLUSA ................................ 34.86 4.66 4.29 4.30 6.96 CALIFORNIA ................................................................................................................................. CONTRA COSTA .................... ........................ ........................ ........................ ........................ ........................CALIFORNIA ................................................................................................................................. DEL NORTE ........................... ........................ 3.49 .27 2.07 5.24 CALIFORNIA ................................................................................................................................. EL DORADO .......................... ........................ 42.31 39.25 17.24 25.00 CALIFORNIA ................................................................................................................................. FRESNO ................................ 17.78 15.64 28.52 26.82 24.26 CALIFORNIA ................................................................................................................................. GLENN .................................. 3.77 5.26 8.07 9.15 7.96 CALIFORNIA ................................................................................................................................. HUMBOLDT ........................... 5.93 6.53 13.11 21.56 35.17 CALIFORNIA ................................................................................................................................. IMPERIAL .............................. ........................ 1.06 24.81 26.92 15.59 CALIFORNIA ................................................................................................................................. INYO ..................................... ........................ ........................ ........................ .60 .91 CALIFORNIA ................................................................................................................................. KERN .................................... 1.47 59.46 65.12 61.27 56.85 CALIFORNIA ................................................................................................................................. KINGS ................................... ........................ .12 11.20 7.33 4.63 CALIFORNIA ................................................................................................................................. LAKE ..................................... 8.81 6.83 15.08 22.35 29.56 CALIFORNIA ................................................................................................................................. LASSEN ................................. 67.08 70.99 65.40 60.13 60.49 CALIFORNIA ................................................................................................................................. LOS ANGELES ....................... ........................ ........................ 100.00 ........................ 86.33 CALIFORNIA ................................................................................................................................. MADERA ................................ 19.78 19.90 18.28 19.58 22.25 CALIFORNIA ................................................................................................................................. MARIN ................................... 1.33 10.56 10.65 10.19 1.93 CALIFORNIA ................................................................................................................................. MARIPOSA ............................. 4.80 ........................ ........................ 41.10 37.81 CALIFORNIA ................................................................................................................................. MENDOCINO .......................... 30.00 22.87 23.54 24.44 14.60 CALIFORNIA ................................................................................................................................. MERCED ............................... 47.89 44.13 38.33 35.29 34.20 CALIFORNIA ................................................................................................................................. MODOC ................................. 15.23 15.67 13.55 13.22 12.67 CALIFORNIA ................................................................................................................................. MONO ................................... ........................ ........................ ........................ ........................ ........................CALIFORNIA ................................................................................................................................. MONTEREY ............................ 17.58 10.66 8.86 23.70 25.28 CALIFORNIA ................................................................................................................................. NAPA ..................................... ........................ ........................ ........................ ........................ ........................CALIFORNIA ................................................................................................................................. NEVADA ................................ 19.56 16.30 9.44 ........................ 8.21 CALIFORNIA ................................................................................................................................. ORANGE ................................ 88.96 77.59 18.78 17.18 ........................CALIFORNIA ................................................................................................................................. PLACER ................................. 7.03 15.72 19.99 23.63 21.49 CALIFORNIA ................................................................................................................................. PLUMAS ................................ ........................ ........................ ........................ ........................ ........................CALIFORNIA ................................................................................................................................. RIVERSIDE ............................ 6.20 2.32 3.89 21.51 54.80 CALIFORNIA ................................................................................................................................. SACRAMENTO ....................... 37.68 32.57 23.28 21.42 12.25 CALIFORNIA ................................................................................................................................. SAN BENITO .......................... 93.48 91.52 90.98 90.90 93.89 CALIFORNIA ................................................................................................................................. SAN BERNARDINO ................ 76.77 24.07 32.32 30.76 28.85 
173 

CALIFORNIA ................................................................................................................................. SAN DIEGO ........................... 20.95 20.23 57.61 53.98 60.50 CALIFORNIA ................................................................................................................................. SAN FRANCISCO ................... ........................ ........................ ........................ ........................ ........................CALIFORNIA ................................................................................................................................. SAN JOAQUIN ........................ 12.16 13.75 18.73 18.16 20.46 CALIFORNIA ................................................................................................................................. SAN LUIS OBISPO ................. 45.47 42.65 29.58 27.78 25.90 CALIFORNIA ................................................................................................................................. SAN MATEO .......................... ........................ ........................ ........................ ........................ ........................CALIFORNIA ................................................................................................................................. SANTA BARBARA .................. 20.12 8.14 15.11 ........................ 3.62 CALIFORNIA ................................................................................................................................. SANTA CLARA ....................... 82.53 78.46 79.50 78.30 77.80 CALIFORNIA ................................................................................................................................. SANTA CRUZ ......................... 7.83 13.98 9.94 9.32 7.10 CALIFORNIA ................................................................................................................................. SHASTA ................................. ........................ ........................ .70 ........................ .70 CALIFORNIA ................................................................................................................................. SIERRA ................................. ........................ ........................ ........................ .41 ........................CALIFORNIA ................................................................................................................................. SISKIYOU .............................. 1.97 1.95 11.05 9.46 7.22 CALIFORNIA ................................................................................................................................. SOLANO ................................ 6.57 ........................ ........................ ........................ 1.64 CALIFORNIA ................................................................................................................................. SONOMA ............................... 18.00 62.28 74.25 64.65 39.72 CALIFORNIA ................................................................................................................................. STANISLAUS .......................... 2.20 2.66 6.76 6.08 5.67 CALIFORNIA ................................................................................................................................. SUTTER ................................. 2.94 3.06 2.04 5.92 5.82 CALIFORNIA ................................................................................................................................. TEHAMA ................................ 13.24 11.06 11.88 14.10 7.58 CALIFORNIA ................................................................................................................................. TRINITY ................................. ........................ ........................ ........................ ........................ ........................CALIFORNIA ................................................................................................................................. TULARE ................................. 4.65 7.12 9.56 11.84 10.82 CALIFORNIA ................................................................................................................................. TUOLUMNE ............................ ........................ ........................ ........................ ........................ ........................CALIFORNIA ................................................................................................................................. VENTURA .............................. 72.04 75.51 74.61 73.49 70.47 CALIFORNIA ................................................................................................................................. YOLO ..................................... 1.13 .21 8.95 6.90 3.98 CALIFORNIA ................................................................................................................................. YUBA .................................... .45 .04 1.46 .77 2.28 COLORADO .................................................................................................................................. ADAMS .................................. 4.76 6.91 11.81 3.56 3.57 COLORADO .................................................................................................................................. ALAMOSA .............................. 1.75 2.68 3.68 9.87 6.29 COLORADO .................................................................................................................................. ARAPAHOE ............................ 6.87 16.63 17.91 18.69 ........................COLORADO .................................................................................................................................. ARCHULETA .......................... 4.05 1.60 2.45 1.05 .55 COLORADO .................................................................................................................................. BACA .................................... 10.15 15.86 15.64 9.69 26.44 COLORADO .................................................................................................................................. BENT ..................................... .32 19.41 23.31 14.88 11.26 COLORADO .................................................................................................................................. BOULDER .............................. 3.87 ........................ 1.43 7.54 ........................COLORADO .................................................................................................................................. BROOMFIELD ........................ ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. CHAFFEE ............................... ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. CHEYENNE ............................ ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. CLEAR CREEK ....................... ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. CONEJOS ............................... 7.54 9.09 5.98 7.20 21.36 COLORADO .................................................................................................................................. COSTILLA .............................. 3.35 3.33 2.12 1.07 7.88 COLORADO .................................................................................................................................. CROWLEY .............................. ........................ ........................ ........................ ........................ 15.82 COLORADO .................................................................................................................................. CUSTER ................................ ........................ ........................ ........................ ........................ 34.64 COLORADO .................................................................................................................................. DELTA ................................... ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. DENVER ................................ 99.61 99.81 100.00 3.88 ........................COLORADO .................................................................................................................................. DOLORES .............................. ........................ 2.32 .26 ........................ ........................
174 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

COLORADO .................................................................................................................................. DOUGLAS .............................. 14.10 .80 2.25 ........................ ........................COLORADO .................................................................................................................................. EAGLE ................................... ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. EL PASO ............................... 18.70 15.84 12.11 9.83 12.27 COLORADO .................................................................................................................................. ELBERT ................................. .83 2.87 2.54 1.57 3.12 COLORADO .................................................................................................................................. FREMONT .............................. ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. GARFIELD .............................. 9.61 ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. GILPIN ................................... ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. GRAND .................................. ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. GUNNISON ............................ ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. HINSDALE ............................. ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. HUERFANO ............................ ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. JACKSON ............................... ........................ ........................ ........................ ........................ 8.57 COLORADO .................................................................................................................................. JEFFERSON ........................... ........................ ........................ 15.04 7.82 ........................COLORADO .................................................................................................................................. KIOWA ................................... 2.81 1.48 ........................ ........................ ........................COLORADO .................................................................................................................................. KIT CARSON .......................... .98 1.07 1.75 ........................ ........................COLORADO .................................................................................................................................. LA PLATA .............................. 6.13 .31 ........................ .15 1.83 COLORADO .................................................................................................................................. LAKE ..................................... ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. LARIMER ............................... ........................ ........................ ........................ 11.69 13.31 COLORADO .................................................................................................................................. LAS ANIMAS .......................... 12.68 12.23 16.56 15.52 4.72 COLORADO .................................................................................................................................. LINCOLN ............................... 1.43 .27 .49 .06 1.28 COLORADO .................................................................................................................................. LOGAN .................................. 7.90 10.79 6.67 10.08 4.62 COLORADO .................................................................................................................................. MESA .................................... 2.69 ........................ 1.06 20.00 10.50 COLORADO .................................................................................................................................. MINERAL ............................... ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. MOFFAT ................................. ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. MONTEZUMA ......................... 3.45 .89 .91 1.69 3.76 COLORADO .................................................................................................................................. MONTROSE ........................... ........................ ........................ ........................ 2.22 1.21COLORADO .................................................................................................................................. MORGAN ............................... 10.75 13.76 16.19 15.85 12.72 COLORADO .................................................................................................................................. OTERO .................................. 3.49 .93 .94 37.90 39.62 COLORADO .................................................................................................................................. OURAY .................................. ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. PARK ..................................... ........................ ........................ ........................ ........................ .29 COLORADO .................................................................................................................................. PHILLIPS ............................... ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. PITKIN ................................... ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. PROWERS ............................. 22.38 21.52 19.77 22.56 29.61 COLORADO .................................................................................................................................. PUEBLO ................................ .33 ........................ ........................ .01 5.74 COLORADO .................................................................................................................................. RIO BLANCO ......................... ........................ ........................ ........................ ........................ ........................
175 

COLORADO .................................................................................................................................. RIO GRANDE ......................... ........................ .22 .95 2.40 .50 COLORADO .................................................................................................................................. ROUTT ................................... ........................ ........................ 8.97 ........................ 8.95 COLORADO .................................................................................................................................. SAGUACHE ............................ .83 8.63 8.11 12.61 8.01 COLORADO .................................................................................................................................. SAN JUAN ............................. ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. SAN MIGUEL ......................... ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. SEDGWICK ............................ ........................ 3.85 3.71 4.46 9.29 COLORADO .................................................................................................................................. SUMMIT ................................ ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. TELLER ................................. ........................ ........................ ........................ ........................ ........................COLORADO .................................................................................................................................. WASHINGTON ........................ 6.53 4.31 3.00 4.12 6.35 COLORADO .................................................................................................................................. WELD .................................... 17.81 13.03 15.04 12.70 14.09 COLORADO .................................................................................................................................. YUMA .................................... .06 16.40 13.01 13.12 9.98 CONNECTICUT ............................................................................................................................. FAIRFIELD ............................. ........................ ........................ 59.10 38.25 19.18 CONNECTICUT ............................................................................................................................. HARTFORD, PT ...................... 1.87 ........................ ........................ 9.54 28.30 CONNECTICUT ............................................................................................................................. LITCHFIELD ........................... .09 ........................ 17.49 12.73 12.07 CONNECTICUT ............................................................................................................................. MIDDLESEX,S ........................ ........................ ........................ 33.81 32.51 38.51 CONNECTICUT ............................................................................................................................. NEW HAVEN, NE ................... ........................ ........................ 100.00 ........................ ........................CONNECTICUT ............................................................................................................................. NEW LONDON ....................... ........................ .68 30.59 25.51 23.40 CONNECTICUT ............................................................................................................................. TOLLAND ............................... 15.02 26.65 27.26 23.94 18.46 CONNECTICUT ............................................................................................................................. WINDHAM .............................. 7.56 3.39 2.72 5.89 2.23 DELAWARE ................................................................................................................................... KENT ..................................... ........................ ........................ 10.54 3.89 1.30 DELAWARE ................................................................................................................................... NEW CASTLE ......................... 45.75 45.23 43.45 35.88 17.07 DELAWARE ................................................................................................................................... SUSSEX ................................. 66.24 75.39 41.44 37.24 32.17 FLORIDA ...................................................................................................................................... ALACHUA .............................. ........................ ........................ .51 ........................ 7.50 FLORIDA ...................................................................................................................................... BAKER .................................. 91.38 90.51 89.90 62.60 38.06 FLORIDA ...................................................................................................................................... BAY ....................................... ........................ ........................ ........................ 89.94 2.00 FLORIDA ...................................................................................................................................... BRADFORD ............................ ........................ ........................ 23.64 ........................ ........................FLORIDA ...................................................................................................................................... BREVARD .............................. ........................ ........................ ........................ ........................ 4.32 FLORIDA ...................................................................................................................................... BROWARD ............................. ........................ ........................ ........................ .58 .28 FLORIDA ...................................................................................................................................... CALHOUN .............................. ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... CHARLOTTE ........................... 82.38 83.18 84.04 66.58 48.92 FLORIDA ...................................................................................................................................... CITRUS ................................. ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... CLAY ..................................... ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... COLLIER ................................ ........................ ........................ 14.15 ........................ 38.59 FLORIDA ...................................................................................................................................... COLUMBIA ............................ .23 ........................ 6.00 8.14 4.04 FLORIDA ...................................................................................................................................... DADE .................................... 3.16 6.02 4.35 5.67 10.85 FLORIDA ...................................................................................................................................... DE SOTO ............................... ........................ ........................ .13 ........................ ........................FLORIDA ...................................................................................................................................... DIXIE ..................................... ........................ 22.24 11.78 11.13 10.33 FLORIDA ...................................................................................................................................... DUVAL ................................... ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... ESCAMBIA ............................. ........................ ........................ ........................ ........................ 8.93 FLORIDA ...................................................................................................................................... FLAGLER ............................... ........................ ........................ ........................ 1.74 2.80 
176 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

FLORIDA ...................................................................................................................................... FRANKLIN .............................. ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... GADSDEN .............................. 25.89 .06 ........................ ........................ ........................FLORIDA ...................................................................................................................................... GILCHRIST ............................ ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... GLADES ................................. ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... GULF ..................................... ........................ .02 ........................ ........................ ........................FLORIDA ...................................................................................................................................... HAMILTON ............................. ........................ 2.61 22.96 24.19 30.87 FLORIDA ...................................................................................................................................... HARDEE ................................ ........................ ........................ 3.87 26.75 78.32 FLORIDA ...................................................................................................................................... HENDRY ................................ ........................ ........................ ........................ ........................ 100.00 FLORIDA ...................................................................................................................................... HERNANDO ........................... ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... HIGHLANDS ........................... .50 8.05 .41 25.94 24.27 FLORIDA ...................................................................................................................................... HILLSBOROUGH .................... 13.54 11.52 17.24 17.60 14.79 FLORIDA ...................................................................................................................................... HOLMES ................................ .47 1.31 3.94 4.30 7.79 FLORIDA ...................................................................................................................................... INDIAN RIVER ....................... 8.04 6.59 7.15 32.98 21.50 FLORIDA ...................................................................................................................................... JACKSON ............................... .40 .15 .95 16.95 45.45 FLORIDA ...................................................................................................................................... JEFFERSON ........................... ........................ ........................ ........................ 2.16 ........................FLORIDA ...................................................................................................................................... LAFAYETTE ............................ ........................ ........................ ........................ .03 .03 FLORIDA ...................................................................................................................................... LAKE ..................................... 2.34 .19 46.71 48.20 8.04 FLORIDA ...................................................................................................................................... LEE ....................................... ........................ ........................ ........................ 30.00 34.64 FLORIDA ...................................................................................................................................... LEON ..................................... ........................ 12.42 ........................ ........................ ........................FLORIDA ...................................................................................................................................... LEVY ..................................... 6.22 6.20 4.54 1.84 2.12 FLORIDA ...................................................................................................................................... LIBERTY ................................ ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... MADISON .............................. 28.22 25.02 17.62 14.66 27.68 FLORIDA ...................................................................................................................................... MANATEE .............................. 10.77 9.21 67.33 31.69 18.33 FLORIDA ...................................................................................................................................... MARION ................................ ........................ 77.13 67.14 89.48 92.16 FLORIDA ...................................................................................................................................... MARTIN ................................. ........................ 7.94 15.46 6.03 ........................FLORIDA ...................................................................................................................................... MONROE ............................... ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... NASSAU ................................ ........................ ........................ 100.00 85.72 52.93 FLORIDA ...................................................................................................................................... OKALOOSA ............................ ........................ ........................ ........................ 9.41 8.85 FLORIDA ...................................................................................................................................... OKEECHOBEE ........................ 8.56 7.86 8.48 2.76 1.35 FLORIDA ...................................................................................................................................... ORANGE ................................ ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... OSCEOLA .............................. ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... PALM BEACH ........................ 45.43 38.52 44.41 38.49 31.62 FLORIDA ...................................................................................................................................... PASCO .................................. ........................ ........................ ........................ 51.76 48.64 FLORIDA ...................................................................................................................................... PINELLAS .............................. ........................ 14.34 ........................ ........................ ........................FLORIDA ...................................................................................................................................... POLK ..................................... 9.55 15.82 15.42 15.47 10.72 
177 

FLORIDA ...................................................................................................................................... PUTNAM ................................ ........................ .08 .92 15.48 9.97 FLORIDA ...................................................................................................................................... SANTA ROSA ......................... .57 ........................ ........................ ........................ 4.40 FLORIDA ...................................................................................................................................... SARASOTA ............................. ........................ 99.43 85.87 82.99 79.72 FLORIDA ...................................................................................................................................... SEMINOLE ............................. ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... ST. JOHNS ............................. ........................ ........................ 1.01 2.44 ........................FLORIDA ...................................................................................................................................... ST. LUCIE ............................. ........................ ........................ ........................ 50.18 67.13 FLORIDA ...................................................................................................................................... SUMTER ................................ ........................ ........................ ........................ ........................ .32 FLORIDA ...................................................................................................................................... SUWANNEE ........................... 58.17 18.15 13.07 6.70 6.07 FLORIDA ...................................................................................................................................... TAYLOR ................................. ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... UNION ................................... 16.91 15.15 13.98 14.67 84.13 FLORIDA ...................................................................................................................................... VOLUSIA ................................ .08 3.31 11.61 11.79 7.76 FLORIDA ...................................................................................................................................... WAKULLA .............................. ........................ ........................ ........................ ........................ ........................FLORIDA ...................................................................................................................................... WALTON ................................ .22 22.30 20.02 17.83 21.76 FLORIDA ...................................................................................................................................... WASHINGTON ........................ ........................ ........................ ........................ .42 25.12 GEORGIA ...................................................................................................................................... APPLING ................................ 1.43 6.62 2.38 .23 .35 GEORGIA ...................................................................................................................................... ATKINSON ............................. ........................ ........................ .43 11.44 18.75 GEORGIA ...................................................................................................................................... BACON .................................. 2.68 4.16 5.55 10.59 15.18 GEORGIA ...................................................................................................................................... BAKER .................................. 3.84 3.09 2.28 2.26 20.79 GEORGIA ...................................................................................................................................... BALDWIN ............................... 49.10 52.55 46.90 24.18 19.74 GEORGIA ...................................................................................................................................... BANKS .................................. 63.49 69.48 65.46 40.84 31.57 GEORGIA ...................................................................................................................................... BARROW ............................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... BARTOW ................................ ........................ ........................ ........................ 3.90 10.17 GEORGIA ...................................................................................................................................... BEN HILL .............................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... BERRIEN ............................... 4.12 1.99 3.22 4.29 5.20 GEORGIA ...................................................................................................................................... BIBB ..................................... ........................ .47 ........................ 4.51 ........................GEORGIA ...................................................................................................................................... BLECKLEY ............................. 30.33 6.91 15.89 7.97 9.54 GEORGIA ...................................................................................................................................... BRANTLEY ............................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... BROOKS ................................ 19.91 18.07 17.73 12.57 10.22 GEORGIA ...................................................................................................................................... BRYAN .................................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... BULLOCH .............................. 4.59 8.67 5.20 3.52 1.55 GEORGIA ...................................................................................................................................... BURKE .................................. 11.45 11.05 8.60 5.34 4.12 GEORGIA ...................................................................................................................................... BUTTS ................................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... CALHOUN .............................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... CAMDEN ............................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... CANDLER .............................. ........................ ........................ 50.19 ........................ 66.70 GEORGIA ...................................................................................................................................... CARROLL .............................. .05 57.07 56.06 54.55 54.25 GEORGIA ...................................................................................................................................... CATOOSA .............................. ........................ 14.93 ........................ ........................ ........................GEORGIA ...................................................................................................................................... CHARLTON ............................ ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... CHATHAM .............................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... CHATTAHOOCHEE .................. ........................ ........................ ........................ ........................ ........................
178 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

GEORGIA ...................................................................................................................................... CHATTOOGA .......................... 1.14 6.12 14.44 5.96 6.46 GEORGIA ...................................................................................................................................... CHEROKEE ............................ 21.68 ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... CLARKE ................................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... CLAY ..................................... 100.00 25.14 14.24 22.93 11.21 GEORGIA ...................................................................................................................................... CLAYTON ............................... ........................ ........................ ........................ 100.00 ........................GEORGIA ...................................................................................................................................... CLINCH ................................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... COBB .................................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... COFFEE ................................. 15.54 12.15 8.45 6.68 5.46 GEORGIA ...................................................................................................................................... COLQUITT .............................. 16.99 10.43 17.56 13.89 22.68 GEORGIA ...................................................................................................................................... COLUMBIA ............................ ........................ ........................ 5.97 .45 ........................GEORGIA ...................................................................................................................................... COOK .................................... 10.93 6.37 6.97 5.96 10.60 GEORGIA ...................................................................................................................................... COWETA ................................ ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... CRAWFORD ........................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... CRISP ................................... 2.38 3.56 1.82 .87 ........................GEORGIA ...................................................................................................................................... DADE .................................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... DAWSON ............................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... DECATUR .............................. 11.88 16.67 12.67 28.27 19.58 GEORGIA ...................................................................................................................................... DEKALB ................................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... DODGE .................................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... DOOLY .................................. 1.11 .72 4.03 5.44 3.53 GEORGIA ...................................................................................................................................... DOUGHERTY .......................... ........................ ........................ 45.24 28.54 ........................GEORGIA ...................................................................................................................................... DOUGLAS .............................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... EARLY ................................... 7.21 .06 .37 ........................ ........................GEORGIA ...................................................................................................................................... ECHOLS ................................ 6.03 2.84 11.93 9.51 ........................GEORGIA ...................................................................................................................................... EFFINGHAM ........................... ........................ ........................ 26.70 24.03 ........................GEORGIA ...................................................................................................................................... ELBERT ................................. ........................ ........................ ........................ .03 5.38 GEORGIA ...................................................................................................................................... EMANUEL .............................. ........................ ........................ .94 .79 .42 GEORGIA ...................................................................................................................................... EVANS ................................... ........................ ........................ 53.79 4.56 ........................GEORGIA ...................................................................................................................................... FANNIN ................................. ........................ 12.89 10.23 1.91 ........................GEORGIA ...................................................................................................................................... FAYETTE ................................ ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... FLOYD ................................... 3.62 3.27 ........................ 8.99 3.27 GEORGIA ...................................................................................................................................... FORSYTH ............................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... FRANKLIN .............................. ........................ ........................ .33 9.65 5.86 GEORGIA ...................................................................................................................................... FULTON ................................. 98.52 98.87 99.15 99.35 99.52 GEORGIA ...................................................................................................................................... GILMER ................................. .63 .24 3.23 8.21 3.55 
179 

GEORGIA ...................................................................................................................................... GLASCOCK ............................ ........................ 26.52 ........................ ........................ ........................GEORGIA ...................................................................................................................................... GLYNN .................................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... GORDON ............................... .16 .36 3.23 1.40 11.72 GEORGIA ...................................................................................................................................... GRADY .................................. ........................ 15.24 23.35 21.85 50.79 GEORGIA ...................................................................................................................................... GREENE ................................ 13.02 10.61 7.33 6.48 6.89 GEORGIA ...................................................................................................................................... GWINNETT ............................. ........................ 98.62 97.55 96.35 95.03 GEORGIA ...................................................................................................................................... HABERSHAM ......................... ........................ ........................ 1.35 ........................ ........................GEORGIA ...................................................................................................................................... HALL ..................................... 8.30 10.01 7.97 11.21 4.66 GEORGIA ...................................................................................................................................... HANCOCK .............................. 21.80 4.02 3.14 2.21 .36 GEORGIA ...................................................................................................................................... HARALSON ............................ .90 ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... HARRIS ................................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... HART ..................................... ........................ ........................ .90 .51 1.35 GEORGIA ...................................................................................................................................... HEARD .................................. ........................ ........................ ........................ 14.57 12.28 GEORGIA ...................................................................................................................................... HENRY .................................. ........................ .42 3.27 ........................ ........................GEORGIA ...................................................................................................................................... HOUSTON .............................. 32.71 23.83 22.09 25.46 19.14 GEORGIA ...................................................................................................................................... IRWIN .................................... 14.60 22.38 21.54 23.70 23.42 GEORGIA ...................................................................................................................................... JACKSON ............................... ........................ ........................ 7.05 20.92 16.96 GEORGIA ...................................................................................................................................... JASPER ................................. ........................ ........................ ........................ 3.83 ........................GEORGIA ...................................................................................................................................... JEFF DAVIS ........................... 11.80 9.50 6.16 2.56 4.19 GEORGIA ...................................................................................................................................... JEFFERSON ........................... 9.97 10.15 9.07 7.38 6.82 GEORGIA ...................................................................................................................................... JENKINS ................................ ........................ 1.55 .45 4.69 ........................GEORGIA ...................................................................................................................................... JOHNSON .............................. .96 .53 .77 .20 .17 GEORGIA ...................................................................................................................................... JONES ................................... ........................ ........................ 2.09 7.31 ........................GEORGIA ...................................................................................................................................... LAMAR .................................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... LANIER .................................. ........................ 2.24 31.23 13.44 .78 GEORGIA ...................................................................................................................................... LAURENS .............................. 17.10 22.00 5.21 18.69 14.73 GEORGIA ...................................................................................................................................... LEE ....................................... 14.98 12.72 16.89 21.29 12.65 GEORGIA ...................................................................................................................................... LIBERTY ................................ ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... LINCOLN ............................... ........................ ........................ ........................ .01 1.28 GEORGIA ...................................................................................................................................... LONG .................................... 31.53 26.81 22.15 17.41 16.69 GEORGIA ...................................................................................................................................... LOWNDES .............................. 48.04 46.15 40.30 41.42 26.99 GEORGIA ...................................................................................................................................... LUMPKIN ............................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... MACON ................................. 11.05 9.07 20.71 18.11 17.20 GEORGIA ...................................................................................................................................... MADISON .............................. 3.20 1.58 .13 .25 1.59 GEORGIA ...................................................................................................................................... MARION ................................ ........................ ........................ 3.97 ........................ 1.87 GEORGIA ...................................................................................................................................... MCDUFFIE ............................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... MCINTOSH ............................ ........................ ........................ ........................ 100.00 100.00 GEORGIA ...................................................................................................................................... MERIWETHER ........................ ........................ ........................ 2.79 ........................ ........................GEORGIA ...................................................................................................................................... MILLER ................................. ........................ 1.60 1.49 1.32 10.11 GEORGIA ...................................................................................................................................... MITCHELL ............................. 10.23 12.08 11.79 6.76 6.49 
180 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

GEORGIA ...................................................................................................................................... MONROE ............................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... MONTGOMERY ...................... ........................ 39.77 1.88 8.51 ........................GEORGIA ...................................................................................................................................... MORGAN ............................... ........................ ........................ .60 .21 4.25 GEORGIA ...................................................................................................................................... MURRAY ............................... ........................ ........................ ........................ ........................ 16.05 GEORGIA ...................................................................................................................................... MUSCOGEE ........................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... NEWTON ................................ ........................ ........................ 4.38 ........................ ........................GEORGIA ...................................................................................................................................... OCONEE ................................ 1.46 1.42 1.84 1.37 3.97 GEORGIA ...................................................................................................................................... OGLETHORPE ........................ ........................ ........................ ........................ 3.99 1.39 GEORGIA ...................................................................................................................................... PAULDING ............................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... PEACH .................................. ........................ ........................ 12.08 13.97 15.25 GEORGIA ...................................................................................................................................... PICKENS ............................... 53.92 64.55 61.68 46.72 44.07 GEORGIA ...................................................................................................................................... PIERCE ................................. 10.71 18.52 16.41 18.53 24.41 GEORGIA ...................................................................................................................................... PIKE ...................................... 52.89 46.56 39.13 35.93 29.41 GEORGIA ...................................................................................................................................... POLK ..................................... ........................ 33.01 24.02 24.27 15.33 GEORGIA ...................................................................................................................................... PULASKI ................................ .87 2.81 7.25 6.21 8.12 GEORGIA ...................................................................................................................................... PUTNAM ................................ 7.54 5.69 3.44 3.77 10.80 GEORGIA ...................................................................................................................................... QUITMAN ............................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... RABUN .................................. 3.96 3.07 2.82 ........................ ........................GEORGIA ...................................................................................................................................... RANDOLPH ............................ ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... RICHMOND ............................ ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... ROCKDALE ............................ ........................ ........................ ........................ ........................ 100.00 GEORGIA ...................................................................................................................................... SCHLEY ................................. 42.67 64.10 46.02 39.05 32.36 GEORGIA ...................................................................................................................................... SCREVEN .............................. 9.25 15.38 14.77 14.02 9.09 GEORGIA ...................................................................................................................................... SEMINOLE ............................. 6.30 4.79 7.89 39.12 55.39 GEORGIA ...................................................................................................................................... SPALDING ............................. ........................ .89 1.18 1.12 .93 GEORGIA ...................................................................................................................................... STEPHENS ............................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... STEWART .............................. ........................ ........................ ........................ 20.27 ........................GEORGIA ...................................................................................................................................... SUMTER ................................ 23.77 25.12 25.06 22.57 25.58 GEORGIA ...................................................................................................................................... TALBOT ................................. 76.12 51.52 24.65 ........................ ........................GEORGIA ...................................................................................................................................... TALIAFERRO .......................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... TATTNALL .............................. 4.62 7.65 7.55 33.24 38.38 GEORGIA ...................................................................................................................................... TAYLOR ................................. 7.47 4.83 3.86 3.70 7.00 GEORGIA ...................................................................................................................................... TELFAIR ................................ 4.73 3.80 2.97 3.53 2.77 GEORGIA ...................................................................................................................................... TERRELL ............................... 8.93 6.81 3.29 6.10 3.62 GEORGIA ...................................................................................................................................... THOMAS ................................ 20.58 21.90 19.49 15.46 13.48 
181 

GEORGIA ...................................................................................................................................... TIFT ....................................... 22.67 22.13 22.20 29.22 27.01 GEORGIA ...................................................................................................................................... TOOMBS ................................ ........................ ........................ ........................ ........................ .19 GEORGIA ...................................................................................................................................... TOWNS .................................. ........................ ........................ ........................ 4.80 ........................GEORGIA ...................................................................................................................................... TREUTLEN ............................. 35.50 22.44 22.01 15.71 7.18 GEORGIA ...................................................................................................................................... TROUP .................................. 6.91 8.24 8.16 ........................ 3.03 GEORGIA ...................................................................................................................................... TURNER ................................ 1.13 1.19 8.89 11.63 11.82 GEORGIA ...................................................................................................................................... TWIGGS ................................. 1.14 ........................ ........................ ........................ 4.41 GEORGIA ...................................................................................................................................... UNION ................................... .10 8.36 .25 .17 8.67 GEORGIA ...................................................................................................................................... UPSON .................................. ........................ ........................ 27.54 13.85 ........................GEORGIA ...................................................................................................................................... WALKER ................................ 7.39 3.42 9.45 1.22 .10 GEORGIA ...................................................................................................................................... WALTON ................................ ........................ 8.54 ........................ 39.05 40.38 GEORGIA ...................................................................................................................................... WARE .................................... 2.05 1.16 1.71 .07 5.60 GEORGIA ...................................................................................................................................... WARREN ............................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... WASHINGTON ........................ ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... WAYNE .................................. 12.41 9.07 9.21 8.38 5.82 GEORGIA ...................................................................................................................................... WEBSTER .............................. ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... WHEELER .............................. 1.59 ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... WHITE ................................... ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... WHITFIELD ............................ ........................ ........................ ........................ ........................ ........................GEORGIA ...................................................................................................................................... WILCOX ................................. 5.39 2.20 .69 1.52 1.15 GEORGIA ...................................................................................................................................... WILKES ................................. 7.17 28.99 10.94 61.06 46.06 GEORGIA ...................................................................................................................................... WILKINSON ............................ ........................ 25.63 ........................ ........................ ........................GEORGIA ...................................................................................................................................... WORTH .................................. 36.87 33.03 29.62 25.26 23.94 GUAM .......................................................................................................................................... AGANA .................................. 3.27 2.16 14.54 20.50 21.57 HAWAII ......................................................................................................................................... AMERICAN SAMOA ................ 2.10 1.23 ........................ ........................ ........................HAWAII ......................................................................................................................................... HAWAII, E. (HILO) ................. 13.25 10.53 6.28 8.08 6.72 HAWAII ......................................................................................................................................... HONOLULU ............................ 39.48 32.20 30.25 29.07 23.75 HAWAII ......................................................................................................................................... KALAWAO .............................. ........................ ........................ ........................ ........................ ........................HAWAII ......................................................................................................................................... KAUAI .................................... 4.93 8.88 7.60 9.31 7.30 HAWAII ......................................................................................................................................... MAUI ..................................... 1.23 6.87 7.40 8.34 5.79 IDAHO .......................................................................................................................................... ADA ....................................... 4.66 6.10 6.40 8.43 4.99 IDAHO .......................................................................................................................................... ADAMS .................................. ........................ ........................ ........................ ........................ ........................IDAHO .......................................................................................................................................... BANNOCK .............................. .73 .46 .52 ........................ 2.72 IDAHO .......................................................................................................................................... BEAR LAKE ........................... 1.37 .42 ........................ .22 .25 IDAHO .......................................................................................................................................... BENEWAH ............................. 4.19 ........................ ........................ ........................ ........................IDAHO .......................................................................................................................................... BINGHAM .............................. ........................ ........................ ........................ ........................ ........................IDAHO .......................................................................................................................................... BLAINE .................................. ........................ ........................ ........................ 2.58 1.32 IDAHO .......................................................................................................................................... BOISE ................................... ........................ ........................ ........................ ........................ ........................IDAHO .......................................................................................................................................... BONNER ................................ ........................ ........................ ........................ ........................ 2.59 IDAHO .......................................................................................................................................... BONNEVILLE ......................... 4.06 2.86 7.71 3.52 3.01 
182 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

IDAHO .......................................................................................................................................... BOUNDARY ........................... ........................ ........................ 3.68 2.92 1.57 IDAHO .......................................................................................................................................... BUTTE ................................... 1.13 .33 5.69 6.95 3.78 IDAHO .......................................................................................................................................... CAMAS .................................. ........................ ........................ ........................ ........................ ........................IDAHO .......................................................................................................................................... CANYON ................................ 3.74 8.78 5.06 7.86 8.69 IDAHO .......................................................................................................................................... CARIBOU ............................... 4.57 2.37 2.20 1.03 .18 IDAHO .......................................................................................................................................... CASSIA .................................. 4.37 2.29 1.62 1.89 4.03 IDAHO .......................................................................................................................................... CLARK ................................... ........................ ........................ ........................ 23.47 15.30 IDAHO .......................................................................................................................................... CLEARWATER ........................ ........................ ........................ ........................ ........................ ........................IDAHO .......................................................................................................................................... ELMORE ................................ 1.43 .13 11.21 4.54 3.04 IDAHO .......................................................................................................................................... FRANKLIN .............................. ........................ .39 .24 .65 .52 IDAHO .......................................................................................................................................... FREMONT .............................. 3.03 .33 33.61 22.54 48.12 IDAHO .......................................................................................................................................... GEM ...................................... .73 1.30 .87 6.40 4.53 IDAHO .......................................................................................................................................... GOODING .............................. 1.10 .77 ........................ 14.49 13.69 IDAHO .......................................................................................................................................... IDAHO ................................... 30.46 28.86 12.02 9.75 6.98 IDAHO .......................................................................................................................................... JEFFERSON ........................... 3.56 1.16 2.08 1.24 1.84 IDAHO .......................................................................................................................................... JEROME ................................ 2.48 ........................ 2.15 1.05 1.64 IDAHO .......................................................................................................................................... KOOTENAI ............................. .01 ........................ 3.74 .07 ........................IDAHO .......................................................................................................................................... LATAH ................................... 2.87 ........................ 7.16 30.93 42.19 IDAHO .......................................................................................................................................... LEMHI ................................... 19.91 24.18 19.33 9.17 4.82 IDAHO .......................................................................................................................................... LEWIS ................................... 14.85 13.49 12.55 13.71 20.62 IDAHO .......................................................................................................................................... LINCOLN ............................... ........................ ........................ .60 1.59 .88 IDAHO .......................................................................................................................................... MADISON .............................. 3.50 4.06 14.15 13.08 2.71 IDAHO .......................................................................................................................................... MINIDOKA ............................. 14.28 13.96 11.21 9.37 13.80 IDAHO .......................................................................................................................................... NEZ PERCE ........................... ........................ 2.00 .10 .48 .43 IDAHO .......................................................................................................................................... NORTH CUSTER .................... ........................ 6.14 2.78 .58 1.23 IDAHO .......................................................................................................................................... ONEIDA ................................. .73 .16 1.16 25.53 27.09 IDAHO .......................................................................................................................................... OWYHEE ................................ 11.47 7.72 8.11 12.97 8.28 IDAHO .......................................................................................................................................... PAYETTE ............................... ........................ .52 32.41 24.66 8.36 IDAHO .......................................................................................................................................... POWER .................................. .07 2.88 6.48 4.98 .51 IDAHO .......................................................................................................................................... SHOSHONE ............................ ........................ ........................ ........................ ........................ ........................IDAHO .......................................................................................................................................... TETON ................................... 5.31 ........................ ........................ ........................ ........................IDAHO .......................................................................................................................................... TWIN FALLS .......................... 1.21 .63 .46 .13 .66 IDAHO .......................................................................................................................................... VALLEY ................................. ........................ ........................ ........................ 45.81 11.76 IDAHO .......................................................................................................................................... WASHINGTON ........................ 1.10 2.37 1.11 3.85 2.01 ILLINOIS ....................................................................................................................................... ADAMS .................................. .28 ........................ 1.13 3.86 2.99 
183 

ILLINOIS ....................................................................................................................................... ALEXANDER .......................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... BOND .................................... .21 .14 .12 ........................ ........................ILLINOIS ....................................................................................................................................... BOONE .................................. ........................ ........................ ........................ 7.32 6.91 ILLINOIS ....................................................................................................................................... BROWN ................................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... BUREAU ................................ ........................ ........................ .69 1.06 4.03 ILLINOIS ....................................................................................................................................... CALHOUN .............................. 6.44 6.02 ........................ ........................ ........................ILLINOIS ....................................................................................................................................... CARROLL .............................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... CASS ..................................... 5.16 4.73 ........................ 23.87 16.04 ILLINOIS ....................................................................................................................................... CHAMPAIGN .......................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... CHRISTIAN ............................ ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... CLARK ................................... 5.82 5.86 6.35 3.36 2.38 ILLINOIS ....................................................................................................................................... CLAY ..................................... ........................ ........................ ........................ .22 ........................ILLINOIS ....................................................................................................................................... CLINTON ............................... ........................ ........................ .63 1.25 .92 ILLINOIS ....................................................................................................................................... COLES ................................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... COOK .................................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... CRAWFORD ........................... ........................ ........................ ........................ 3.97 .96 ILLINOIS ....................................................................................................................................... CUMBERLAND ....................... ........................ 6.31 4.95 4.01 1.27 ILLINOIS ....................................................................................................................................... DEKALB ................................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... DEWITT ................................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... DOUGLAS .............................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... DUPAGE ................................ ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... EDGAR .................................. .54 .51 .21 .17 ........................ILLINOIS ....................................................................................................................................... EDWARDS ............................. ........................ .47 1.08 .79 .75 ILLINOIS ....................................................................................................................................... EFFINGHAM ........................... 12.56 11.73 11.01 8.40 7.85 ILLINOIS ....................................................................................................................................... FAYETTE ................................ .26 ........................ .07 4.27 4.62 ILLINOIS ....................................................................................................................................... FORD .................................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... FRANKLIN .............................. ........................ 7.85 4.11 14.89 14.87 ILLINOIS ....................................................................................................................................... FULTON ................................. .72 2.98 12.62 13.09 9.99 ILLINOIS ....................................................................................................................................... GALLATIN .............................. 10.00 8.92 6.84 8.97 8.50 ILLINOIS ....................................................................................................................................... GREENE ................................ 2.46 2.53 2.83 .71 .91 ILLINOIS ....................................................................................................................................... GRUNDY ................................ ........................ ........................ ........................ .78 ........................ILLINOIS ....................................................................................................................................... HAMILTON ............................. .89 .04 .22 .30 .31 ILLINOIS ....................................................................................................................................... HANCOCK .............................. ........................ .86 .33 .13 .03 ILLINOIS ....................................................................................................................................... HARDIN ................................. 8.94 ........................ 2.35 5.44 7.12 ILLINOIS ....................................................................................................................................... HENDERSON ......................... ........................ ........................ ........................ 3.51 4.60 ILLINOIS ....................................................................................................................................... HENRY .................................. ........................ ........................ ........................ ........................ 1.00 ILLINOIS ....................................................................................................................................... IR0QUOIS .............................. 1.44 .64 .87 .45 .48 ILLINOIS ....................................................................................................................................... JACKSON ............................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... JASPER ................................. ........................ ........................ ........................ 3.12 2.52 ILLINOIS ....................................................................................................................................... JEFFERSON ........................... ........................ ........................ ........................ ........................ ........................
184 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

ILLINOIS ....................................................................................................................................... JERSEY ................................. ........................ 1.82 1.22 .15 4.64 ILLINOIS ....................................................................................................................................... JO DAVIESS ........................... .13 ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... JOHNSON .............................. .26 7.40 .56 .76 2.60 ILLINOIS ....................................................................................................................................... KANE ..................................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... KANKAKEE ............................. .86 .77 .16 .87 .14 ILLINOIS ....................................................................................................................................... KENDALL ............................... 4.32 .75 .40 4.94 13.20 ILLINOIS ....................................................................................................................................... KNOX .................................... .56 .28 .85 .76 1.52 ILLINOIS ....................................................................................................................................... LA SALLE .............................. .03 ........................ .07 .04 .05 ILLINOIS ....................................................................................................................................... LAKE ..................................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... LAWRENCE ............................ 1.24 1.26 1.17 4.21 1.05 ILLINOIS ....................................................................................................................................... LEE ....................................... ........................ ........................ 1.74 1.12 .42 ILLINOIS ....................................................................................................................................... LIVINGSTON .......................... .22 .25 .47 .48 .40 ILLINOIS ....................................................................................................................................... LOGAN .................................. ........................ ........................ .13 .18 1.46 ILLINOIS ....................................................................................................................................... MACON ................................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... MACOUPIN ............................ .18 1.78 .60 .59 .92 ILLINOIS ....................................................................................................................................... MADISON .............................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... MARION ................................ .37 1.80 1.52 1.32 1.00 ILLINOIS ....................................................................................................................................... MARSHALL ............................ ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... MASON .................................. ........................ ........................ .63 ........................ ........................ILLINOIS ....................................................................................................................................... MASSAC ................................ 4.13 8.45 5.32 3.19 9.47 ILLINOIS ....................................................................................................................................... MCDONOUGH ........................ 1.42 1.45 1.43 1.25 2.06 ILLINOIS ....................................................................................................................................... MCHENRY ............................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... MCLEAN ................................ ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... MENARD ............................... ........................ ........................ ........................ 14.57 ........................ILLINOIS ....................................................................................................................................... MERCER ............................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... MONROE ............................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... MONTGOMERY ...................... 6.88 6.80 6.21 5.52 31.88 ILLINOIS ....................................................................................................................................... MORGAN ............................... ........................ ........................ ........................ .34 .31 ILLINOIS ....................................................................................................................................... MOULTRIE ............................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... OGLE ..................................... 8.25 7.11 6.97 11.93 10.32 ILLINOIS ....................................................................................................................................... PEORIA ................................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... PERRY .................................. 2.78 3.14 1.80 ........................ ........................ILLINOIS ....................................................................................................................................... PIATT .................................... ........................ ........................ ........................ 4.38 ........................ILLINOIS ....................................................................................................................................... PIKE ...................................... ........................ ........................ ........................ 1.61 1.55 ILLINOIS ....................................................................................................................................... POPE ..................................... ........................ ........................ ........................ ........................ ........................
185 

ILLINOIS ....................................................................................................................................... PULASKI ................................ 3.09 5.63 3.88 1.83 1.38 ILLINOIS ....................................................................................................................................... PUTNAM ................................ ........................ ........................ ........................ ........................ .47 ILLINOIS ....................................................................................................................................... RANDOLPH ............................ ........................ 2.40 2.04 ........................ 4.51 ILLINOIS ....................................................................................................................................... RICHLAND ............................. 1.05 .71 .76 .83 1.01 ILLINOIS ....................................................................................................................................... ROCK ISLAND ....................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... SALINE .................................. 4.33 4.76 3.78 4.96 7.00 ILLINOIS ....................................................................................................................................... SANGAMON ........................... ........................ ........................ 3.08 7.74 6.52 ILLINOIS ....................................................................................................................................... SCHUYLER ............................ ........................ ........................ ........................ 4.70 ........................ILLINOIS ....................................................................................................................................... SCOTT ................................... ........................ 60.17 57.25 38.54 29.62 ILLINOIS ....................................................................................................................................... SHELBY ................................. ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... ST. CLAIR ............................. ........................ ........................ ........................ 8.25 9.10 ILLINOIS ....................................................................................................................................... STARK ................................... ........................ ........................ ........................ ........................ ........................ILLINOIS ....................................................................................................................................... STEPHENSON ........................ .23 .76 1.11 1.09 .70 ILLINOIS ....................................................................................................................................... TAZEWELL ............................. ........................ ........................ ........................ 1.21 ........................ILLINOIS ....................................................................................................................................... UNION ................................... 10.11 11.83 7.76 4.80 3.67 ILLINOIS ....................................................................................................................................... VERMILION ............................ 2.04 1.96 1.80 1.33 1.24 ILLINOIS ....................................................................................................................................... WABASH ................................ 1.66 1.43 1.59 .36 ........................ILLINOIS ....................................................................................................................................... WARREN ............................... ........................ ........................ ........................ .05 ........................ILLINOIS ....................................................................................................................................... WASHINGTON ........................ ........................ ........................ .02 ........................ ........................ILLINOIS ....................................................................................................................................... WAYNE .................................. .46 .16 .06 ........................ 1.41 ILLINOIS ....................................................................................................................................... WHITE ................................... ........................ 3.41 5.02 3.51 ........................ILLINOIS ....................................................................................................................................... WHITESIDE ............................ ........................ ........................ ........................ 2.29 1.70 ILLINOIS ....................................................................................................................................... WILL ...................................... 10.67 8.83 7.84 7.21 6.62 ILLINOIS ....................................................................................................................................... WILLIAMSON ......................... ........................ 3.67 .98 1.22 ........................ILLINOIS ....................................................................................................................................... WINNEBAGO .......................... ........................ ........................ 30.31 ........................ ........................ILLINOIS ....................................................................................................................................... WOODFORD ........................... ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... ADAMS .................................. ........................ ........................ ........................ ........................ 5.95 INDIANA ....................................................................................................................................... ALLEN ................................... ........................ ........................ 3.52 4.88 17.24 INDIANA ....................................................................................................................................... BARTHOLOMEW ..................... .79 .34 .42 ........................ .51 INDIANA ....................................................................................................................................... BENTON ................................ ........................ ........................ ........................ 9.25 11.57 INDIANA ....................................................................................................................................... BLACKFORD .......................... ........................ .19 ........................ ........................ ........................INDIANA ....................................................................................................................................... BOONE .................................. ........................ 9.82 7.19 8.48 11.60 INDIANA ....................................................................................................................................... BROWN ................................. ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... CARROLL .............................. .05 ........................ .13 .49 .15 INDIANA ....................................................................................................................................... CASS ..................................... .13 .73 ........................ ........................ .83 INDIANA ....................................................................................................................................... CLARK ................................... ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... CLAY ..................................... ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... CLINTON ............................... 2.71 5.09 3.25 8.94 33.67 INDIANA ....................................................................................................................................... CRAWFORD ........................... ........................ ........................ ........................ ........................ 71.69 INDIANA ....................................................................................................................................... DAVIESS ................................ ........................ ........................ ........................ ........................ .06 
186 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

INDIANA ....................................................................................................................................... DEARBORN ........................... ........................ ........................ 8.39 60.49 57.14 INDIANA ....................................................................................................................................... DECATUR .............................. .81 2.79 2.65 1.41 1.87 INDIANA ....................................................................................................................................... DEKALB ................................. .25 .13 3.63 .33 9.60 INDIANA ....................................................................................................................................... DELAWARE ............................ 1.69 ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... DUBOIS ................................. ........................ ........................ ........................ ........................ 13.21 INDIANA ....................................................................................................................................... ELKHART ............................... 2.05 ........................ 21.49 20.58 19.71 INDIANA ....................................................................................................................................... FAYETTE ................................ 9.19 10.12 14.66 13.58 11.25 INDIANA ....................................................................................................................................... FLOYD ................................... ........................ ........................ 41.47 34.85 30.94 INDIANA ....................................................................................................................................... FOUNTAIN ............................. 7.06 5.35 4.77 26.61 22.59 INDIANA ....................................................................................................................................... FRANKLIN .............................. ........................ ........................ ........................ 49.50 36.17 INDIANA ....................................................................................................................................... FULTON ................................. 1.98 2.37 1.14 .35 2.14 INDIANA ....................................................................................................................................... GIBSON ................................. ........................ 11.25 1.58 .24 55.09 INDIANA ....................................................................................................................................... GRANT .................................. ........................ ........................ ........................ .24 .23 INDIANA ....................................................................................................................................... GREENE ................................ ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... HAMILTON ............................. ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... HANCOCK .............................. 5.08 7.38 6.32 6.37 .24 INDIANA ....................................................................................................................................... HARRISON ............................. .50 .69 .59 .63 .28 INDIANA ....................................................................................................................................... HENDRICKS ........................... ........................ ........................ ........................ ........................ 1.01 INDIANA ....................................................................................................................................... HENRY .................................. 6.22 5.47 5.48 11.98 14.43 INDIANA ....................................................................................................................................... HOWARD ............................... ........................ ........................ ........................ 19.37 16.74 INDIANA ....................................................................................................................................... HUNTINGTON ......................... ........................ ........................ ........................ ........................ .03 INDIANA ....................................................................................................................................... JACKSON ............................... 1.48 1.63 .90 7.22 6.65 INDIANA ....................................................................................................................................... JASPER ................................. .51 2.26 4.14 8.02 2.69 INDIANA ....................................................................................................................................... JAY ........................................ 13.78 10.19 7.81 4.62 1.33 INDIANA ....................................................................................................................................... JEFFERSON ........................... 8.93 11.21 10.76 11.91 11.53 INDIANA ....................................................................................................................................... JENNINGS .............................. 5.87 5.07 4.65 27.66 24.23 INDIANA ....................................................................................................................................... JOHNSON .............................. ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... KNOX .................................... 3.50 ........................ .01 ........................ ........................INDIANA ....................................................................................................................................... KOSCIUSKO ........................... 2.63 2.45 3.80 2.92 2.77 INDIANA ....................................................................................................................................... LAGRANGE ............................ .18 ........................ ........................ ........................ 1.45 INDIANA ....................................................................................................................................... LAKE ..................................... 11.66 7.03 6.08 3.00 2.73 INDIANA ....................................................................................................................................... LAPORTE ............................... 10.63 14.47 8.01 8.01 5.82 INDIANA ....................................................................................................................................... LAWRENCE ............................ .28 .31 .20 6.83 5.59 INDIANA ....................................................................................................................................... MADISON .............................. ........................ ........................ ........................ 9.88 8.14 INDIANA ....................................................................................................................................... MARION ................................ ........................ ........................ ........................ ........................ ........................
187 

INDIANA ....................................................................................................................................... MARSHALL ............................ 2.71 14.33 11.08 11.09 10.18 INDIANA ....................................................................................................................................... MARTIN ................................. ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... MIAMI ................................... 3.33 2.79 2.48 1.52 5.36 INDIANA ....................................................................................................................................... MONROE ............................... ........................ 100.00 ........................ 100.00 100.00 INDIANA ....................................................................................................................................... MONTGOMERY ...................... 1.28 .87 3.07 6.25 3.66 INDIANA ....................................................................................................................................... MORGAN ............................... ........................ ........................ ........................ 2.18 ........................INDIANA ....................................................................................................................................... NEWTON ................................ 4.77 1.85 5.47 2.43 3.34 INDIANA ....................................................................................................................................... NOBLE .................................. 2.98 .75 .13 3.34 ........................INDIANA ....................................................................................................................................... OHIO ..................................... ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... ORANGE ................................ ........................ ........................ ........................ 8.62 63.76 INDIANA ....................................................................................................................................... OWEN .................................... ........................ ........................ .92 35.60 41.18 INDIANA ....................................................................................................................................... PARKE ................................... 14.40 5.34 4.15 2.62 12.94 INDIANA ....................................................................................................................................... PERRY .................................. ........................ .38 ........................ 8.17 ........................INDIANA ....................................................................................................................................... PIKE ...................................... ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... PORTER ................................ ........................ .20 6.22 14.10 8.36 INDIANA ....................................................................................................................................... POSEY ................................... ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... PULASKI ................................ 6.16 8.12 7.12 11.70 8.71 INDIANA ....................................................................................................................................... PUTNAM ................................ 2.71 ........................ ........................ 45.38 49.07 INDIANA ....................................................................................................................................... RANDOLPH ............................ ........................ ........................ ........................ ........................ .87 INDIANA ....................................................................................................................................... RIPLEY .................................. ........................ 1.14 15.32 3.41 .89 INDIANA ....................................................................................................................................... RUSH .................................... .20 14.84 12.99 7.99 7.44 INDIANA ....................................................................................................................................... SCOTT ................................... 49.49 48.17 ........................ .07 .18 INDIANA ....................................................................................................................................... SHELBY ................................. ........................ ........................ .30 .60 .12 INDIANA ....................................................................................................................................... SPENCER .............................. .90 .12 .36 ........................ .14 INDIANA ....................................................................................................................................... ST. JOSEPH ........................... 2.11 13.88 11.22 12.28 14.48 INDIANA ....................................................................................................................................... STARKE ................................. 1.54 6.60 4.23 8.38 9.01 INDIANA ....................................................................................................................................... STEUBEN .............................. ........................ ........................ ........................ ........................ 2.92 INDIANA ....................................................................................................................................... SULLIVAN .............................. 2.51 1.45 .73 ........................ ........................INDIANA ....................................................................................................................................... SWITZERLAND ....................... 22.38 17.80 14.81 13.70 34.26 INDIANA ....................................................................................................................................... TIPPECANOE ......................... 3.89 2.84 21.70 12.16 23.34 INDIANA ....................................................................................................................................... TIPTON .................................. ........................ ........................ ........................ ........................ 28.35 INDIANA ....................................................................................................................................... UNION ................................... ........................ ........................ .30 ........................ 3.20 INDIANA ....................................................................................................................................... VANDERBURGH ..................... ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... VERMILLION .......................... ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... VIGO ..................................... ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... WABASH ................................ ........................ .74 .87 1.29 1.11 INDIANA ....................................................................................................................................... WARREN ............................... ........................ ........................ ........................ 1.01 ........................INDIANA ....................................................................................................................................... WARRICK .............................. 35.82 35.33 47.95 43.27 40.09 INDIANA ....................................................................................................................................... WASHINGTON ........................ ........................ ........................ .31 2.25 1.79 INDIANA ....................................................................................................................................... WAYNE .................................. 20.70 ........................ ........................ 4.54 34.66 
188 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

INDIANA ....................................................................................................................................... WELLS ................................... ........................ ........................ ........................ ........................ ........................INDIANA ....................................................................................................................................... WHITE ................................... ........................ ........................ ........................ 15.39 13.91 INDIANA ....................................................................................................................................... WHITLEY ............................... 1.62 1.13 ........................ 1.02 .17 IOWA ............................................................................................................................................ ADAIR ................................... 2.60 2.78 2.56 ........................ 5.23 IOWA ............................................................................................................................................ ADAMS .................................. ........................ .18 ........................ ........................ ........................IOWA ............................................................................................................................................ ALLAMAKEE ........................... ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ APPANOOSE .......................... .14 .16 ........................ .28 7.53 IOWA ............................................................................................................................................ AUDUBON ............................. ........................ ........................ .08 ........................ .02 IOWA ............................................................................................................................................ BENTON ................................ 4.61 3.52 2.51 2.83 3.17 IOWA ............................................................................................................................................ BLACK HAWK ........................ ........................ 12.18 7.91 ........................ ........................IOWA ............................................................................................................................................ BOONE .................................. ........................ .70 1.09 .96 .57 IOWA ............................................................................................................................................ BREMER ............................... ........................ ........................ ........................ ........................ .30 IOWA ............................................................................................................................................ BUCHANAN ........................... 3.06 2.91 3.17 3.14 2.98 IOWA ............................................................................................................................................ BUENA VISTA ........................ 3.56 1.51 2.59 1.22 1.09 IOWA ............................................................................................................................................ BUTLER ................................. 1.55 1.66 1.65 1.43 2.47 IOWA ............................................................................................................................................ CALHOUN .............................. ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ CARROLL .............................. .07 .06 .09 .17 .36 IOWA ............................................................................................................................................ CASS ..................................... 12.49 11.46 12.53 12.75 10.59 IOWA ............................................................................................................................................ CEDAR .................................. 1.11 1.32 .87 .69 .41 IOWA ............................................................................................................................................ CERRO GORDO ..................... 8.96 9.21 4.81 4.39 4.62 IOWA ............................................................................................................................................ CHEROKEE ............................ ........................ ........................ ........................ ........................ .83 IOWA ............................................................................................................................................ CHICKASAW .......................... 3.72 3.84 5.34 3.50 4.49 IOWA ............................................................................................................................................ CLARKE ................................. .02 .02 .01 .02 .44 IOWA ............................................................................................................................................ CLAY ..................................... ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ CLAYTON ............................... ........................ 1.08 ........................ ........................ ........................IOWA ............................................................................................................................................ CLINTON ............................... .01 ........................ ........................ .02 .18 IOWA ............................................................................................................................................ CRAWFORD ........................... ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ DALLAS ................................. ........................ 6.07 4.21 2.35 ........................IOWA ............................................................................................................................................ DAVIS .................................... .49 1.96 3.66 2.25 1.29 IOWA ............................................................................................................................................ DECATUR .............................. .07 .06 .05 .14 .13 IOWA ............................................................................................................................................ DELAWARE ............................ ........................ ........................ .37 .02 .25 IOWA ............................................................................................................................................ DES MOINES ......................... .66 ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ DICKINSON ............................ ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ DUBUQUE ............................. .10 1.04 1.00 3.36 3.62 IOWA ............................................................................................................................................ EMMET .................................. .35 ........................ ........................ ........................ ........................
189 

IOWA ............................................................................................................................................ FAYETTE ................................ .89 1.19 .88 .94 1.06 IOWA ............................................................................................................................................ FLOYD ................................... ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ FRANKLIN .............................. ........................ ........................ 1.23 12.54 .27 IOWA ............................................................................................................................................ FREMONT .............................. ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ GREENE ................................ 14.16 13.12 10.23 7.75 5.73 IOWA ............................................................................................................................................ GRUNDY ................................ 2.16 1.74 ........................ ........................ ........................IOWA ............................................................................................................................................ GUTHRIE ............................... ........................ .29 .38 .24 1.66 IOWA ............................................................................................................................................ HAMILTON ............................. 45.51 40.07 29.90 32.63 28.80 IOWA ............................................................................................................................................ HANCOCK .............................. ........................ 3.73 2.83 2.47 1.93 IOWA ............................................................................................................................................ HARDIN ................................. ........................ ........................ 3.42 1.95 .46 IOWA ............................................................................................................................................ HARRISON ............................. ........................ .21 1.59 1.33 1.55 IOWA ............................................................................................................................................ HENRY .................................. 8.39 11.46 2.23 2.22 5.69 IOWA ............................................................................................................................................ HOWARD ............................... ........................ ........................ ........................ .05 .27 IOWA ............................................................................................................................................ HUMBOLDT ........................... .35 ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ IDA ........................................ .01 .03 ........................ ........................ ........................IOWA ............................................................................................................................................ IOWA ..................................... .85 2.25 1.45 1.95 1.36 IOWA ............................................................................................................................................ JACKSON ............................... .78 3.69 3.84 3.59 3.05 IOWA ............................................................................................................................................ JASPER ................................. .28 ........................ ........................ .06 ........................IOWA ............................................................................................................................................ JEFFERSON ........................... 1.49 1.41 1.29 .68 1.73 IOWA ............................................................................................................................................ JOHNSON .............................. 3.91 3.78 2.88 .03 15.34 IOWA ............................................................................................................................................ JONES ................................... 2.00 2.37 1.58 .78 .14 IOWA ............................................................................................................................................ KEOKUK ................................ ........................ ........................ ........................ ........................ .18 IOWA ............................................................................................................................................ KOSSUTH .............................. .75 ........................ ........................ ........................ 1.10 IOWA ............................................................................................................................................ LEE ....................................... ........................ ........................ .72 .07 10.65 IOWA ............................................................................................................................................ LINN ...................................... ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ LOUISA .................................. ........................ ........................ ........................ ........................ .02 IOWA ............................................................................................................................................ LUCAS ................................... 3.06 3.03 2.79 3.11 2.57 IOWA ............................................................................................................................................ LYON ..................................... ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ MADISON .............................. 7.52 40.71 32.88 29.41 18.51 IOWA ............................................................................................................................................ MAHASKA .............................. ........................ 1.32 1.16 .93 .83 IOWA ............................................................................................................................................ MARION ................................ ........................ .12 2.22 .13 .09 IOWA ............................................................................................................................................ MARSHALL ............................ ........................ ........................ ........................ .05 5.01 IOWA ............................................................................................................................................ MILLS .................................... 6.76 5.44 3.66 1.34 1.95 IOWA ............................................................................................................................................ MITCHELL ............................. 1.82 2.57 1.30 9.44 5.67 IOWA ............................................................................................................................................ MONONA ............................... .13 ........................ .10 ........................ .85 IOWA ............................................................................................................................................ MONROE ............................... .02 .13 1.31 .37 .39 IOWA ............................................................................................................................................ MONTGOMERY ...................... 1.92 6.87 1.91 1.75 1.71 IOWA ............................................................................................................................................ MUSCATINE ........................... ........................ .69 ........................ .26 .14 IOWA ............................................................................................................................................ O’BRIEN ................................ 1.50 ........................ 4.87 ........................ ........................IOWA ............................................................................................................................................ OSCEOLA .............................. .31 .78 .88 1.08 1.21 
190 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

IOWA ............................................................................................................................................ PAGE ..................................... .65 .49 .61 .75 1.38 IOWA ............................................................................................................................................ PALO ALTO ............................ .05 ........................ ........................ .04 ........................IOWA ............................................................................................................................................ PLYMOUTH ............................ .02 .58 .79 4.59 3.84 IOWA ............................................................................................................................................ POCAHONTAS ........................ ........................ ........................ ........................ .03 3.48 IOWA ............................................................................................................................................ POLK ..................................... 17.55 15.65 17.04 5.45 2.57 IOWA ............................................................................................................................................ POTTAWATTAMIE ................... 4.57 4.39 5.44 4.77 2.97 IOWA ............................................................................................................................................ POWESHIEK ........................... ........................ ........................ ........................ 1.23 1.00 IOWA ............................................................................................................................................ RINGGOLD ............................. ........................ ........................ ........................ .02 .46 IOWA ............................................................................................................................................ SAC ....................................... .55 .61 .96 1.06 5.40 IOWA ............................................................................................................................................ SCOTT ................................... ........................ ........................ ........................ .19 ........................IOWA ............................................................................................................................................ SHELBY ................................. .55 ........................ .11 ........................ .21 IOWA ............................................................................................................................................ SIOUX ................................... ........................ .74 ........................ ........................ .94 IOWA ............................................................................................................................................ STORY ................................... ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ TAMA .................................... 3.10 3.19 1.51 1.96 .68 IOWA ............................................................................................................................................ TAYLOR ................................. 22.04 25.04 25.46 22.78 28.09 IOWA ............................................................................................................................................ UNION ................................... 8.41 6.66 6.18 5.75 5.43 IOWA ............................................................................................................................................ VAN BUREN .......................... .36 .33 .37 .75 .74 IOWA ............................................................................................................................................ WAPELLO .............................. .28 ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ WARREN ............................... ........................ ........................ ........................ ........................ 3.44 IOWA ............................................................................................................................................ WASHINGTON ........................ .79 .11 .15 4.30 .67 IOWA ............................................................................................................................................ WAYNE .................................. ........................ ........................ .23 ........................ 2.59 IOWA ............................................................................................................................................ WEBSTER .............................. ........................ ........................ ........................ ........................ ........................IOWA ............................................................................................................................................ WINNEBAGO .......................... 1.22 1.10 4.05 2.45 1.48 IOWA ............................................................................................................................................ WINNESHIEK ......................... ........................ ........................ ........................ 2.19 1.09 IOWA ............................................................................................................................................ WOODBURY ........................... ........................ ........................ ........................ ........................ 1.65 IOWA ............................................................................................................................................ WORTH .................................. .56 ........................ .24 ........................ ........................IOWA ............................................................................................................................................ WRIGHT ................................. ........................ ........................ ........................ ........................ 1.00 KANSAS ....................................................................................................................................... ALLEN ................................... ........................ 2.57 7.08 22.93 35.46 KANSAS ....................................................................................................................................... ANDERSON ............................ 1.11 ........................ ........................ .07 ........................KANSAS ....................................................................................................................................... ATCHISON ............................. 1.37 1.15 1.39 3.36 2.86 KANSAS ....................................................................................................................................... BARBER ................................ .05 .92 1.50 1.10 .48 KANSAS ....................................................................................................................................... BARTON ................................ .70 .27 .54 .75 .54 KANSAS ....................................................................................................................................... BOURBON ............................. ........................ ........................ ........................ ........................ ........................KANSAS ....................................................................................................................................... BROWN ................................. .15 ........................ .18 ........................ 1.01 KANSAS ....................................................................................................................................... BUTLER ................................. ........................ ........................ ........................ .18 .32 
191 

KANSAS ....................................................................................................................................... CHASE .................................. ........................ ........................ ........................ ........................ ........................KANSAS ....................................................................................................................................... CHAUTAUQUA ........................ 2.75 1.87 .43 ........................ .99 KANSAS ....................................................................................................................................... CHEROKEE ............................ ........................ 3.57 3.16 ........................ ........................KANSAS ....................................................................................................................................... CHEYENNE ............................ 6.41 4.80 4.92 3.22 2.40 KANSAS ....................................................................................................................................... CLARK ................................... ........................ ........................ ........................ 2.40 ........................KANSAS ....................................................................................................................................... CLAY ..................................... .14 .16 .37 .15 .01 KANSAS ....................................................................................................................................... CLOUD .................................. 1.55 2.30 7.39 7.74 7.42 KANSAS ....................................................................................................................................... COFFEY ................................. 20.01 17.26 3.51 2.64 3.12 KANSAS ....................................................................................................................................... COMANCHE ........................... .84 2.02 1.06 2.74 3.71 KANSAS ....................................................................................................................................... COWLEY ................................ ........................ ........................ ........................ 2.99 .01 KANSAS ....................................................................................................................................... CRAWFORD ........................... .49 ........................ ........................ .73 .38 KANSAS ....................................................................................................................................... DECATUR .............................. 4.43 3.99 3.12 2.45 2.27 KANSAS ....................................................................................................................................... DICKINSON ............................ 3.15 1.90 5.32 3.67 3.13 KANSAS ....................................................................................................................................... DONIPHAN ............................. ........................ ........................ ........................ .92 ........................KANSAS ....................................................................................................................................... DOUGLAS .............................. ........................ ........................ ........................ ........................ 1.34 KANSAS ....................................................................................................................................... EDWARDS ............................. 1.65 1.78 2.31 1.81 4.78 KANSAS ....................................................................................................................................... ELK ....................................... 1.26 3.26 2.15 2.88 2.24 KANSAS ....................................................................................................................................... ELLIS .................................... .74 .25 1.37 1.32 .94 KANSAS ....................................................................................................................................... ELLSWORTH .......................... .42 .42 .29 .27 .09 KANSAS ....................................................................................................................................... FINNEY .................................. 1.27 1.99 2.38 .60 .84 KANSAS ....................................................................................................................................... FORD .................................... 3.03 3.79 2.78 1.34 3.55 KANSAS ....................................................................................................................................... FRANKLIN .............................. ........................ .33 1.19 5.15 3.33 KANSAS ....................................................................................................................................... GEARY .................................. 1.97 ........................ ........................ ........................ .64 KANSAS ....................................................................................................................................... GOVE .................................... 6.15 6.20 5.36 15.28 12.10 KANSAS ....................................................................................................................................... GRAHAM ............................... .45 .89 .54 .49 .33 KANSAS ....................................................................................................................................... GRANT .................................. ........................ .22 11.29 8.45 16.01 KANSAS ....................................................................................................................................... GRAY .................................... .25 .41 .10 3.36 1.14 KANSAS ....................................................................................................................................... GREELEY ............................... 2.40 2.14 3.44 1.78 1.75 KANSAS ....................................................................................................................................... GREENWOOD ......................... ........................ ........................ 14.56 29.21 27.27 KANSAS ....................................................................................................................................... HAMILTON ............................. .93 ........................ ........................ ........................ .10 KANSAS ....................................................................................................................................... HARPER ................................ .37 .93 .97 1.25 1.07 KANSAS ....................................................................................................................................... HARVEY ................................ ........................ ........................ ........................ ........................ 1.24 KANSAS ....................................................................................................................................... HASKELL ............................... 4.48 3.83 3.50 19.58 2.60 KANSAS ....................................................................................................................................... HODGEMAN ........................... .36 .27 2.71 3.98 2.12 KANSAS ....................................................................................................................................... JACKSON ............................... ........................ 1.07 ........................ 1.20 ........................KANSAS ....................................................................................................................................... JEFFERSON ........................... .45 ........................ ........................ ........................ .16 KANSAS ....................................................................................................................................... JEWELL ................................. 2.43 2.30 2.49 2.24 2.36 KANSAS ....................................................................................................................................... JOHNSON .............................. ........................ ........................ ........................ ........................ ........................KANSAS ....................................................................................................................................... KEARNY ................................ 1.47 1.06 .98 1.25 1.11 KANSAS ....................................................................................................................................... KINGMAN .............................. 3.31 2.55 3.81 5.39 4.74 
192 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

KANSAS ....................................................................................................................................... KIOWA ................................... 2.33 ........................ 2.13 1.15 1.36 KANSAS ....................................................................................................................................... LABETTE ............................... .72 .87 1.01 .95 .82 KANSAS ....................................................................................................................................... LANE ..................................... .39 .84 .90 .75 .85 KANSAS ....................................................................................................................................... LEAVENWORTH ...................... 23.78 18.46 15.55 12.73 9.82 KANSAS ....................................................................................................................................... LINCOLN ............................... .10 .47 .77 1.18 1.48 KANSAS ....................................................................................................................................... LINN ...................................... ........................ ........................ .18 18.21 15.95 KANSAS ....................................................................................................................................... LOGAN .................................. 2.91 .69 2.15 2.73 .61 KANSAS ....................................................................................................................................... LYON ..................................... ........................ ........................ ........................ .52 .18 KANSAS ....................................................................................................................................... MARION ................................ ........................ 2.23 1.07 1.52 .37 KANSAS ....................................................................................................................................... MARSHALL ............................ 1.13 1.85 1.21 1.78 2.08 KANSAS ....................................................................................................................................... MCPHERSON ......................... 2.91 3.19 2.56 4.04 5.57 KANSAS ....................................................................................................................................... MEADE .................................. .32 .86 .72 .79 2.27 KANSAS ....................................................................................................................................... MIAMI ................................... 9.28 10.80 8.66 6.62 6.56 KANSAS ....................................................................................................................................... MITCHELL ............................. ........................ ........................ ........................ ........................ .53 KANSAS ....................................................................................................................................... MONTGOMERY ...................... .46 1.09 6.43 7.64 7.74 KANSAS ....................................................................................................................................... MORRIS ................................ ........................ ........................ 5.18 5.19 5.52 KANSAS ....................................................................................................................................... MORTON ............................... 1.68 1.05 1.76 1.09 .03 KANSAS ....................................................................................................................................... NEMAHA ................................ .05 .06 .06 .06 .15 KANSAS ....................................................................................................................................... NEOSHO ................................ ........................ .90 19.53 13.85 1.57 KANSAS ....................................................................................................................................... NESS ..................................... 1.82 .80 .63 .74 .79 KANSAS ....................................................................................................................................... NORTON ................................ 1.12 .96 .99 1.03 1.12 KANSAS ....................................................................................................................................... OSAGE .................................. ........................ ........................ ........................ 32.62 31.65 KANSAS ....................................................................................................................................... OSBORNE .............................. .30 .32 2.33 .95 .82 KANSAS ....................................................................................................................................... OTTAWA ................................ ........................ ........................ ........................ ........................ ........................KANSAS ....................................................................................................................................... PAWNEE ................................ .32 .85 ........................ ........................ ........................KANSAS ....................................................................................................................................... PHILLIPS ............................... .63 .18 .70 .56 .57 KANSAS ....................................................................................................................................... POTTAWATOMIE ..................... .28 1.15 .99 1.92 2.11 KANSAS ....................................................................................................................................... PRATT ................................... .91 .39 2.97 1.59 2.90 KANSAS ....................................................................................................................................... RAWLINS ............................... ........................ ........................ 3.55 1.61 1.66 KANSAS ....................................................................................................................................... RENO .................................... .60 .35 .33 1.02 5.37 KANSAS ....................................................................................................................................... REPUBLIC ............................. 2.12 2.34 1.92 2.13 1.56 KANSAS ....................................................................................................................................... RICE ..................................... .51 1.57 2.00 2.71 2.41 KANSAS ....................................................................................................................................... RILEY .................................... ........................ .74 9.64 12.09 9.53 KANSAS ....................................................................................................................................... ROOKS .................................. 3.21 3.33 3.76 1.62 3.44 KANSAS ....................................................................................................................................... RUSH .................................... 2.61 .18 .27 ........................ .32 
193 

KANSAS ....................................................................................................................................... RUSSELL ............................... 2.95 .22 .10 .92 1.14 KANSAS ....................................................................................................................................... SALINE .................................. 8.89 9.11 ........................ 7.88 7.50 KANSAS ....................................................................................................................................... SCOTT ................................... .68 2.62 2.60 .74 .07 KANSAS ....................................................................................................................................... SEDGWICK ............................ .16 .86 .51 .24 1.19 KANSAS ....................................................................................................................................... SEWARD ................................ 4.57 2.49 10.64 34.22 34.73 KANSAS ....................................................................................................................................... SHAWNEE .............................. ........................ ........................ 2.52 ........................ ........................KANSAS ....................................................................................................................................... SHERIDAN ............................. .47 .65 .79 1.14 1.24 KANSAS ....................................................................................................................................... SHERMAN ............................. 5.73 4.45 11.27 6.33 6.99 KANSAS ....................................................................................................................................... SMITH ................................... .35 .76 .33 .48 .32 KANSAS ....................................................................................................................................... STAFFORD ............................. 4.70 1.36 1.07 .40 2.77 KANSAS ....................................................................................................................................... STANTON ............................... 1.37 .63 .82 3.98 .81 KANSAS ....................................................................................................................................... STEVENS ............................... 1.57 5.29 2.75 8.67 3.74 KANSAS ....................................................................................................................................... SUMNER ............................... 1.18 1.97 3.65 3.94 5.10 KANSAS ....................................................................................................................................... THOMAS ................................ 2.82 2.94 3.40 .28 .15 KANSAS ....................................................................................................................................... TREGO .................................. 5.06 6.49 1.44 1.38 .41 KANSAS ....................................................................................................................................... WABAUNSEE ......................... ........................ ........................ ........................ .75 .77KANSAS ....................................................................................................................................... WALLACE .............................. .17 ........................ .66 5.85 3.33 KANSAS ....................................................................................................................................... WASHINGTON ........................ 2.42 1.93 2.75 2.60 1.97 KANSAS ....................................................................................................................................... WICHITA ................................ 5.52 3.74 3.26 3.88 3.62 KANSAS ....................................................................................................................................... WILSON ................................. 1.97 1.02 .32 5.90 6.18 KANSAS ....................................................................................................................................... WOODSON ............................. ........................ ........................ ........................ 4.54 2.48 KANSAS ....................................................................................................................................... WYANDOTTE .......................... ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... ADAIR ................................... .03 .11 .39 .10 .16 KENTUCKY ................................................................................................................................... ALLEN ................................... .63 .55 .10 .16 .02 KENTUCKY ................................................................................................................................... ANDERSON ............................ ........................ .51 ........................ ........................ ........................KENTUCKY ................................................................................................................................... BALLARD ............................... ........................ .48 .33 4.39 1.99 KENTUCKY ................................................................................................................................... BARREN ................................ 7.01 7.16 6.65 6.71 3.91 KENTUCKY ................................................................................................................................... BATH ..................................... 3.47 3.45 3.25 3.06 .95 KENTUCKY ................................................................................................................................... BELL ..................................... ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... BOONE .................................. ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... BOURBON ............................. ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... BOYD .................................... ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... BOYLE ................................... .25 .23 ........................ .80 .19 KENTUCKY ................................................................................................................................... BRACKEN .............................. ........................ ........................ .16 5.13 3.22 KENTUCKY ................................................................................................................................... BREATHITT ............................ 3.30 ........................ 15.87 4.37 3.38 KENTUCKY ................................................................................................................................... BRECKINRIDGE ..................... .10 .11 .39 .51 .37 KENTUCKY ................................................................................................................................... BULLITT ................................ ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... BUTLER ................................. ........................ ........................ ........................ ........................ .21 KENTUCKY ................................................................................................................................... CALDWELL ............................ ........................ ........................ ........................ .27 3.16 KENTUCKY ................................................................................................................................... CALLOWAY ............................ 1.62 .10 2.51 .15 ........................
194 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

KENTUCKY ................................................................................................................................... CAMPBELL ............................ ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... CARLISLE .............................. .15 ........................ ........................ ........................ 1.43 KENTUCKY ................................................................................................................................... CARROLL .............................. 26.22 23.52 24.66 21.13 17.81 KENTUCKY ................................................................................................................................... CARTER ................................ 3.38 .14 ........................ ........................ 1.79 KENTUCKY ................................................................................................................................... CASEY ................................... 34.07 29.06 26.41 30.61 17.18 KENTUCKY ................................................................................................................................... CHRISTIAN ............................ 2.92 2.44 2.19 .87 1.04 KENTUCKY ................................................................................................................................... CLARK ................................... .11 ........................ ........................ .47 .35 KENTUCKY ................................................................................................................................... CLAY ..................................... 10.10 7.56 10.91 8.72 16.83 KENTUCKY ................................................................................................................................... CLINTON ............................... .34 2.59 2.41 2.19 7.95 KENTUCKY ................................................................................................................................... CRITTENDEN ......................... .45 3.03 2.18 .18 36.71 KENTUCKY ................................................................................................................................... CUMBERLAND ....................... 16.22 19.38 18.40 14.34 11.44 KENTUCKY ................................................................................................................................... DAVIESS ................................ ........................ 29.99 29.32 35.96 35.57 KENTUCKY ................................................................................................................................... EDMONSON ........................... 4.71 .87 .01 2.31 3.19 KENTUCKY ................................................................................................................................... ELLIOTT ................................. ........................ 22.40 20.76 14.57 7.74 KENTUCKY ................................................................................................................................... ESTILL ................................... .17 .29 ........................ ........................ 3.97 KENTUCKY ................................................................................................................................... FAYETTE ................................ 1.25 ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... FLEMING ............................... 1.40 1.17 .94 .70 1.00 KENTUCKY ................................................................................................................................... FLOYD ................................... ........................ ........................ ........................ 9.26 21.44 KENTUCKY ................................................................................................................................... FRANKLIN .............................. ........................ ........................ ........................ .03 ........................KENTUCKY ................................................................................................................................... FULTON ................................. ........................ 2.60 2.85 1.14 ........................KENTUCKY ................................................................................................................................... GALLATIN .............................. 20.52 17.35 15.70 13.72 12.31 KENTUCKY ................................................................................................................................... GARRARD .............................. .08 ........................ ........................ ........................ .92 KENTUCKY ................................................................................................................................... GRANT .................................. 2.22 1.09 ........................ ........................ ........................KENTUCKY ................................................................................................................................... GRAVES ................................ .61 .26 .24 .28 4.01 KENTUCKY ................................................................................................................................... GRAYSON .............................. ........................ .84 .54 .61 .32 KENTUCKY ................................................................................................................................... GREEN .................................. ........................ .78 ........................ .04 1.59 KENTUCKY ................................................................................................................................... GREENUP .............................. 1.80 4.05 1.49 4.37 2.15 KENTUCKY ................................................................................................................................... HANCOCK .............................. ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... HARDIN ................................. ........................ .27 ........................ .09 .27 KENTUCKY ................................................................................................................................... HARLAN ................................ 100.00 100.00 100.00 77.76 ........................KENTUCKY ................................................................................................................................... HARRISON ............................. 1.40 1.21 1.64 1.65 1.51 KENTUCKY ................................................................................................................................... HART ..................................... 1.00 .97 .96 1.00 .67 KENTUCKY ................................................................................................................................... HENDERSON ......................... ........................ ........................ ........................ 2.68 ........................KENTUCKY ................................................................................................................................... HENRY .................................. 5.73 7.97 6.99 5.82 6.46 KENTUCKY ................................................................................................................................... HICKMAN .............................. ........................ .59 ........................ ........................ 1.28 
195 

KENTUCKY ................................................................................................................................... HOPKINS ............................... ........................ 10.92 7.94 ........................ ........................KENTUCKY ................................................................................................................................... JACKSON ............................... .05 2.10 2.24 2.40 .57 KENTUCKY ................................................................................................................................... JEFFERSON ........................... .18 ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... JESSAMINE ............................ 5.55 1.88 .18 ........................ ........................KENTUCKY ................................................................................................................................... JOHNSON .............................. 1.52 .96 1.82 1.13 .89 KENTUCKY ................................................................................................................................... KENTON ................................ 3.41 ........................ ........................ 4.05 ........................KENTUCKY ................................................................................................................................... KNOTT ................................... ........................ ........................ ........................ .50 35.41 KENTUCKY ................................................................................................................................... KNOX .................................... ........................ ........................ ........................ ........................ 2.50 KENTUCKY ................................................................................................................................... LARUE ................................... ........................ 14.05 15.79 16.53 13.70 KENTUCKY ................................................................................................................................... LAUREL ................................. ........................ ........................ 1.32 2.17 1.20 KENTUCKY ................................................................................................................................... LAWRENCE ............................ 3.27 1.81 1.03 ........................ 17.97 KENTUCKY ................................................................................................................................... LEE ....................................... ........................ ........................ ........................ ........................ .77 KENTUCKY ................................................................................................................................... LESLIE .................................. ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... LETCHER ............................... ........................ ........................ 17.19 52.76 17.20 KENTUCKY ................................................................................................................................... LEWIS ................................... .14 1.54 .86 ........................ ........................KENTUCKY ................................................................................................................................... LINCOLN ............................... 3.01 2.48 4.73 3.79 12.35 KENTUCKY ................................................................................................................................... LIVINGSTON .......................... ........................ .74 .60 4.14 3.96 KENTUCKY ................................................................................................................................... LOGAN .................................. 1.74 2.75 1.65 .78 .53 KENTUCKY ................................................................................................................................... LYON ..................................... ........................ ........................ ........................ ........................ 6.06 KENTUCKY ................................................................................................................................... MADISON .............................. .92 ........................ ........................ .72 2.91 KENTUCKY ................................................................................................................................... MAGOFFIN ............................. ........................ 7.88 16.78 10.57 6.09 KENTUCKY ................................................................................................................................... MARION ................................ .22 .03 .30 ........................ 1.98 KENTUCKY ................................................................................................................................... MARSHALL ............................ ........................ 26.70 11.32 6.50 ........................KENTUCKY ................................................................................................................................... MARTIN ................................. ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... MASON .................................. 4.58 3.05 1.54 6.32 6.00 KENTUCKY ................................................................................................................................... MCCRACKEN ......................... ........................ ........................ ........................ .33 .14 KENTUCKY ................................................................................................................................... MCCREARY ........................... 13.59 7.38 ........................ ........................ ........................KENTUCKY ................................................................................................................................... MCLEAN ................................ ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... MEADE .................................. ........................ 1.21 .20 .07 ........................KENTUCKY ................................................................................................................................... MENIFEE ............................... .11 5.53 5.54 3.79 3.82 KENTUCKY ................................................................................................................................... MERCER ............................... ........................ ........................ 1.84 1.08 1.70 KENTUCKY ................................................................................................................................... METCALFE ............................. ........................ ........................ ........................ ........................ 5.79 KENTUCKY ................................................................................................................................... MONROE ............................... ........................ 2.57 3.23 1.88 1.51 KENTUCKY ................................................................................................................................... MONTGOMERY ...................... ........................ 1.30 1.16 2.49 .40 KENTUCKY ................................................................................................................................... MORGAN ............................... .16 .30 .60 .68 9.20 KENTUCKY ................................................................................................................................... MUHLENBERG ....................... ........................ 3.37 ........................ ........................ ........................KENTUCKY ................................................................................................................................... NELSON ................................ 2.31 2.54 2.27 20.61 20.92 KENTUCKY ................................................................................................................................... NICHOLAS ............................. .33 3.27 2.97 2.84 1.82 KENTUCKY ................................................................................................................................... OHIO ..................................... ........................ ........................ ........................ .03 ........................KENTUCKY ................................................................................................................................... OLDHAM ................................ ........................ ........................ 1.48 .88 ........................
196 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

KENTUCKY ................................................................................................................................... OWEN .................................... 27.76 20.59 15.15 11.82 10.09 KENTUCKY ................................................................................................................................... OWSLEY ................................ 3.11 ........................ 35.67 27.86 22.70 KENTUCKY ................................................................................................................................... PENDLETON .......................... 5.61 4.87 2.40 .90 ........................KENTUCKY ................................................................................................................................... PERRY .................................. 50.62 15.53 10.13 17.77 13.61 KENTUCKY ................................................................................................................................... PIKE ...................................... ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... POWELL ................................ ........................ .01 .58 .14 ........................KENTUCKY ................................................................................................................................... PULASKI ................................ .79 .49 .65 1.05 .40 KENTUCKY ................................................................................................................................... ROBERTSON .......................... 6.17 5.29 10.34 8.36 8.22 KENTUCKY ................................................................................................................................... ROCKCASTLE ........................ 2.32 1.80 1.33 1.16 1.01 KENTUCKY ................................................................................................................................... ROWAN ................................. .33 3.49 ........................ ........................ ........................KENTUCKY ................................................................................................................................... RUSSELL ............................... 6.13 4.77 4.31 3.45 3.14 KENTUCKY ................................................................................................................................... SCOTT ................................... ........................ ........................ ........................ ........................ 6.30 KENTUCKY ................................................................................................................................... SHELBY ................................. .40 .48 .64 2.05 14.96 KENTUCKY ................................................................................................................................... SIMPSON ............................... 8.13 11.20 3.43 11.23 9.54 KENTUCKY ................................................................................................................................... SPENCER .............................. ........................ 3.98 5.31 .83 ........................KENTUCKY ................................................................................................................................... TAYLOR ................................. ........................ ........................ .73 .62 1.05 KENTUCKY ................................................................................................................................... TODD .................................... .66 .48 .29 .18 .39 KENTUCKY ................................................................................................................................... TRIGG ................................... 15.17 32.97 32.54 30.58 1.05 KENTUCKY ................................................................................................................................... TRIMBLE ............................... ........................ ........................ .61 .04 ........................KENTUCKY ................................................................................................................................... UNION ................................... ........................ ........................ ........................ ........................ 2.53 KENTUCKY ................................................................................................................................... WARREN ............................... 6.99 7.14 7.17 5.32 3.59 KENTUCKY ................................................................................................................................... WASHINGTON ........................ 3.99 4.96 4.28 4.27 3.68 KENTUCKY ................................................................................................................................... WAYNE .................................. .40 .04 .06 .09 ........................KENTUCKY ................................................................................................................................... WEBSTER .............................. ........................ ........................ ........................ 8.61 1.59 KENTUCKY ................................................................................................................................... WHITLEY ............................... ........................ ........................ ........................ ........................ ........................KENTUCKY ................................................................................................................................... WOLFE .................................. 2.76 2.85 2.32 1.14 .72 KENTUCKY ................................................................................................................................... WOODFORD ........................... ........................ 3.86 2.66 1.67 1.84 LOUISIANA ................................................................................................................................... ACADIA ................................. 25.99 36.66 24.63 14.01 15.20 LOUISIANA ................................................................................................................................... ALLEN ................................... 25.86 18.36 16.26 11.41 7.05 LOUISIANA ................................................................................................................................... ASCENSION ........................... ........................ ........................ ........................ 79.45 78.82 LOUISIANA ................................................................................................................................... ASSUMPTION ......................... ........................ ........................ .69 ........................ ........................LOUISIANA ................................................................................................................................... AVOYELLES ........................... 15.16 19.11 10.01 12.75 11.09 LOUISIANA ................................................................................................................................... BEAUREGARD ....................... ........................ ........................ 7.94 3.81 66.56 LOUISIANA ................................................................................................................................... BIENVILLE ............................. ........................ ........................ ........................ ........................ ........................LOUISIANA ................................................................................................................................... BOSSIER ............................... 9.13 9.66 27.68 15.89 19.41 
197 

LOUISIANA ................................................................................................................................... CADDO .................................. .60 5.61 20.13 19.70 17.89 LOUISIANA ................................................................................................................................... CALCASIEU ........................... 63.06 52.62 59.44 45.12 52.20 LOUISIANA ................................................................................................................................... CALDWELL ............................ .16 1.78 1.62 1.18 3.26 LOUISIANA ................................................................................................................................... CAMERON ............................. ........................ ........................ ........................ ........................ ........................LOUISIANA ................................................................................................................................... CATAHOULA .......................... 11.54 12.34 10.28 11.03 11.07 LOUISIANA ................................................................................................................................... CLAIBORNE ........................... ........................ ........................ ........................ ........................ 9.08 LOUISIANA ................................................................................................................................... CONCORDIA .......................... 17.62 17.90 17.72 16.00 17.79 LOUISIANA ................................................................................................................................... DE SOTO ............................... 35.54 31.87 29.26 22.72 16.34 LOUISIANA ................................................................................................................................... EAST BATON ROUGE ............. ........................ ........................ 37.10 29.84 23.11 LOUISIANA ................................................................................................................................... EAST CARROLL ..................... 15.81 21.92 20.87 19.07 15.71 LOUISIANA ................................................................................................................................... EAST FELICIANA .................... ........................ ........................ ........................ ........................ ........................LOUISIANA ................................................................................................................................... EVANGELINE ......................... .49 2.69 .49 44.67 59.04 LOUISIANA ................................................................................................................................... FRANKLIN .............................. 21.38 22.94 25.74 26.39 28.61 LOUISIANA ................................................................................................................................... GRANT .................................. 8.78 7.41 6.61 6.98 61.45 LOUISIANA ................................................................................................................................... IBERIA .................................. 19.46 19.57 19.72 27.57 31.92 LOUISIANA ................................................................................................................................... IBERVILLE ............................. 17.74 15.44 19.66 23.98 18.03 LOUISIANA ................................................................................................................................... JACKSON ............................... ........................ ........................ ........................ ........................ ........................LOUISIANA ................................................................................................................................... JEFFERSON ........................... ........................ ........................ ........................ ........................ ........................LOUISIANA ................................................................................................................................... JEFFERSON DAVIS ................. 5.12 5.16 2.20 2.16 1.27 LOUISIANA ................................................................................................................................... LA SALLE .............................. ........................ 71.56 53.22 22.51 70.55 LOUISIANA ................................................................................................................................... LAFAYETTE ............................ ........................ ........................ 12.78 16.65 11.12 LOUISIANA ................................................................................................................................... LAFOURCHE .......................... ........................ ........................ 6.40 16.06 25.44 LOUISIANA ................................................................................................................................... LINCOLN ............................... ........................ .65 1.34 3.66 ........................LOUISIANA ................................................................................................................................... LIVINGSTON .......................... .21 3.22 ........................ ........................ ........................LOUISIANA ................................................................................................................................... MADISON .............................. 13.32 9.59 6.62 6.76 5.13 LOUISIANA ................................................................................................................................... MOREHOUSE ......................... 15.31 14.39 15.09 14.07 12.06 LOUISIANA ................................................................................................................................... NATCHITOCHES ..................... 8.62 9.53 8.21 26.06 88.68 LOUISIANA ................................................................................................................................... ORLEANS .............................. ........................ ........................ ........................ ........................ ........................LOUISIANA ................................................................................................................................... OUACHITA ............................. 47.64 43.12 42.41 17.52 37.71 LOUISIANA ................................................................................................................................... PLAQUEMINES ....................... .11 .19 ........................ 1.20 20.90 LOUISIANA ................................................................................................................................... POINTE COUPEE ................... 16.14 17.21 20.79 16.72 26.96 LOUISIANA ................................................................................................................................... RAPIDES ............................... 13.27 18.28 21.95 28.31 28.89 LOUISIANA ................................................................................................................................... RED RIVER ........................... ........................ ........................ ........................ ........................ 25.11 LOUISIANA ................................................................................................................................... RICHLAND ............................. 25.48 26.91 27.74 27.03 33.13 LOUISIANA ................................................................................................................................... SABINE ................................. 4.59 5.55 5.09 27.05 52.37 LOUISIANA ................................................................................................................................... ST. BERNARD ....................... ........................ ........................ 6.11 2.27 1.41 LOUISIANA ................................................................................................................................... ST. CHARLES ........................ ........................ 8.29 ........................ ........................ ........................LOUISIANA ................................................................................................................................... ST. HELENA .......................... 22.98 46.15 24.14 19.24 22.41 LOUISIANA ................................................................................................................................... ST. JAMES ............................. 6.18 7.47 ........................ ........................ ........................LOUISIANA ................................................................................................................................... ST. JOHN THE BAPTIST ......... ........................ ........................ ........................ ........................ ........................
198 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

LOUISIANA ................................................................................................................................... ST. LANDRY .......................... 8.94 13.93 13.10 21.90 17.72 LOUISIANA ................................................................................................................................... ST. MARTIN ........................... 2.29 6.78 10.21 11.82 20.14 LOUISIANA ................................................................................................................................... ST. MARY .............................. 25.47 7.71 3.13 .84 7.10 LOUISIANA ................................................................................................................................... ST. TAMMANY ....................... ........................ ........................ ........................ ........................ ........................LOUISIANA ................................................................................................................................... TANGIPAHOA ......................... 11.16 13.28 11.80 10.15 7.81 LOUISIANA ................................................................................................................................... TENSAS ................................. 38.51 35.93 31.49 31.20 26.90 LOUISIANA ................................................................................................................................... TERREBONNE ........................ ........................ ........................ ........................ ........................ ........................LOUISIANA ................................................................................................................................... UNION ................................... .16 1.86 1.70 1.72 6.02 LOUISIANA ................................................................................................................................... VERMILION ............................ 9.45 11.92 9.61 16.97 17.69 LOUISIANA ................................................................................................................................... VERNON ................................ 31.16 6.35 35.00 4.14 29.59 LOUISIANA ................................................................................................................................... WASHINGTON ........................ .17 1.10 2.09 4.39 .85 LOUISIANA ................................................................................................................................... WEBSTER .............................. ........................ ........................ ........................ ........................ ........................LOUISIANA ................................................................................................................................... WEST BATON ROUGE ............ ........................ ........................ .54 .53 ........................LOUISIANA ................................................................................................................................... WEST CARROLL .................... 20.00 18.17 19.49 20.37 18.54 LOUISIANA ................................................................................................................................... WEST FELICIANA ................... ........................ ........................ ........................ ........................ ........................LOUISIANA ................................................................................................................................... WINN ..................................... ........................ ........................ ........................ ........................ ........................MAINE .......................................................................................................................................... ANDROSCOGGIN .................... 1.51 1.76 2.00 ........................ ........................MAINE .......................................................................................................................................... AROOSTOOK, PT .................... 17.81 18.33 15.98 15.32 20.08 MAINE .......................................................................................................................................... CUMBERLAND, PT ................. ........................ ........................ ........................ ........................ ........................MAINE .......................................................................................................................................... FRANKLIN .............................. 2.79 ........................ 21.15 20.10 14.09 MAINE .......................................................................................................................................... HANCOCK, PT ....................... .84 2.07 4.59 7.82 7.02 MAINE .......................................................................................................................................... KENNEBEC, PT ...................... 4.66 4.18 3.69 9.55 12.96 MAINE .......................................................................................................................................... KNOX .................................... 26.50 15.58 11.13 16.53 12.56 MAINE .......................................................................................................................................... LINCOLN ............................... ........................ ........................ 3.69 4.25 29.51 MAINE .......................................................................................................................................... OXFORD ................................ 11.11 8.52 8.53 6.02 5.09 MAINE .......................................................................................................................................... PENOBSCOT, PT .................... 12.81 14.06 11.72 12.09 10.20 MAINE .......................................................................................................................................... PISCATAQUIS ........................ ........................ ........................ ........................ 10.13 8.89 MAINE .......................................................................................................................................... SAGADAHOC .......................... ........................ ........................ 1.12 2.13 ........................MAINE .......................................................................................................................................... SOMERSET ............................ 2.11 1.71 2.16 3.14 1.41 MAINE .......................................................................................................................................... WALDO, PT ............................ ........................ 15.76 ........................ ........................ 5.82 MAINE .......................................................................................................................................... WASHINGTON, PT .................. 8.21 31.97 18.56 11.35 15.79 MAINE .......................................................................................................................................... YORK .................................... 11.18 6.49 3.12 1.78 ........................MARYLAND .................................................................................................................................. ALLEGANY ............................. ........................ ........................ ........................ ........................ ........................MARYLAND .................................................................................................................................. ANNE ARUNDEL .................... ........................ ........................ ........................ ........................ ........................MARYLAND .................................................................................................................................. BALTIMORE ........................... ........................ ........................ ........................ ........................ ........................
199 

MARYLAND .................................................................................................................................. BALTIMORE CITY .................. ........................ ........................ ........................ ........................ ........................MARYLAND .................................................................................................................................. CALVERT ............................... ........................ ........................ ........................ ........................ ........................MARYLAND .................................................................................................................................. CAROLINE ............................. ........................ 4.47 3.31 8.26 9.26 MARYLAND .................................................................................................................................. CARROLL .............................. .81 .16 3.05 .75 1.26 MARYLAND .................................................................................................................................. CECIL .................................... ........................ 1.53 ........................ ........................ ........................MARYLAND .................................................................................................................................. CHARLES .............................. 24.08 20.03 18.60 15.89 15.01 MARYLAND .................................................................................................................................. DORCHESTER ........................ ........................ ........................ 25.21 15.76 10.71 MARYLAND .................................................................................................................................. FREDERICK ........................... 31.03 21.14 20.05 13.63 13.31 MARYLAND .................................................................................................................................. GARRETT ............................... 2.78 2.37 4.57 3.76 1.69 MARYLAND .................................................................................................................................. HARFORD .............................. ........................ 5.58 4.96 2.29 2.23 MARYLAND .................................................................................................................................. HOWARD ............................... ........................ ........................ 8.74 5.50 5.59 MARYLAND .................................................................................................................................. KENT ..................................... 9.31 13.07 2.95 5.42 2.62 MARYLAND .................................................................................................................................. MONTGOMERY ...................... 21.51 16.75 10.98 10.45 8.77 MARYLAND .................................................................................................................................. PRINCE GEORGE’S ................ 30.65 28.06 25.35 23.64 21.96 MARYLAND .................................................................................................................................. QUEEN ANNE’S ..................... 56.91 5.46 4.04 1.30 ........................MARYLAND .................................................................................................................................. SOMERSET ............................ 25.28 15.70 38.89 34.76 38.54 MARYLAND .................................................................................................................................. ST. MARY’S ........................... ........................ ........................ 21.45 10.97 5.23 MARYLAND .................................................................................................................................. TALBOT ................................. ........................ ........................ 22.00 8.23 19.21 MARYLAND .................................................................................................................................. WASHINGTON ........................ 1.32 .98 6.14 7.27 8.65 MARYLAND .................................................................................................................................. WICOMICO ............................ 2.57 ........................ 38.30 42.74 29.85 MARYLAND .................................................................................................................................. WORCESTER ......................... 36.13 49.04 39.25 33.72 31.81 MASSACHUSETTS ......................................................................................................................... BARNSTABLE ........................ 13.50 10.40 8.42 6.83 5.65 MASSACHUSETTS ......................................................................................................................... BERKSHIRE ........................... 8.88 9.73 10.30 10.24 13.20 MASSACHUSETTS ......................................................................................................................... BRISTOL ................................ 11.75 8.40 7.64 9.76 12.54 MASSACHUSETTS ......................................................................................................................... DUKES .................................. ........................ ........................ ........................ ........................ 8.77 MASSACHUSETTS ......................................................................................................................... ESSEX ................................... 24.58 19.91 18.38 19.66 19.19 MASSACHUSETTS ......................................................................................................................... FRANKLIN, PT ....................... 11.68 17.14 18.80 16.18 16.34 MASSACHUSETTS ......................................................................................................................... HAMPDEN, PT ....................... 4.41 4.96 2.21 1.87 3.59 MASSACHUSETTS ......................................................................................................................... HAMPSHIRE .......................... 35.99 36.23 34.86 33.76 29.96 MASSACHUSETTS ......................................................................................................................... MIDDLESEX ........................... 26.85 27.18 24.75 18.47 17.95 MASSACHUSETTS ......................................................................................................................... NANTUCKET .......................... ........................ ........................ 13.89 ........................ ........................MASSACHUSETTS ......................................................................................................................... NORFOLK .............................. 25.61 34.21 18.64 7.81 4.73 MASSACHUSETTS ......................................................................................................................... PLYMOUTH, PT ...................... 9.30 8.78 9.11 6.85 5.15 MASSACHUSETTS ......................................................................................................................... SUFFOLK ............................... ........................ ........................ ........................ ........................ ........................MASSACHUSETTS ......................................................................................................................... WORCESTER, PT ................... 16.42 24.50 24.11 24.76 21.57 MICHIGAN .................................................................................................................................... ALCONA ................................ 2.58 .65 .55 ........................ .82 MICHIGAN .................................................................................................................................... ALGER ................................... 1.40 .95 ........................ ........................ 1.80 MICHIGAN .................................................................................................................................... ALLEGAN ............................... 1.19 ........................ 6.53 ........................ .31 MICHIGAN .................................................................................................................................... ALPENA ................................. 1.84 1.37 .55 1.39 1.95 MICHIGAN .................................................................................................................................... ANTRIM ................................. ........................ .12 ........................ .24 ........................
200 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

MICHIGAN .................................................................................................................................... ARENAC ................................ ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... BARAGA ................................ ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... BARRY .................................. ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... BAY ....................................... 8.97 9.65 13.41 8.94 8.89 MICHIGAN .................................................................................................................................... BENZIE ................................. ........................ ........................ ........................ 20.40 21.77 MICHIGAN .................................................................................................................................... BERRIEN ............................... 4.35 3.79 2.76 1.34 3.34 MICHIGAN .................................................................................................................................... BRANCH ................................ 2.81 .77 3.50 .80 ........................MICHIGAN .................................................................................................................................... CALHOUN .............................. 11.55 6.77 5.13 3.75 11.15 MICHIGAN .................................................................................................................................... CASS ..................................... 5.78 5.23 7.22 1.78 1.22 MICHIGAN .................................................................................................................................... CHARLEVOIX ......................... ........................ 79.34 77.04 65.98 52.52 MICHIGAN .................................................................................................................................... CHEBOYGAN ......................... 1.51 1.70 .93 .03 ........................MICHIGAN .................................................................................................................................... CHIPPEWA ............................. .54 .57 1.25 .54 1.06 MICHIGAN .................................................................................................................................... CLARE ................................... ........................ 1.13 ........................ ........................ ........................MICHIGAN .................................................................................................................................... CLINTON ............................... ........................ ........................ ........................ .19 ........................MICHIGAN .................................................................................................................................... CRAWFORD ........................... ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... DELTA ................................... .76 14.97 15.57 12.46 10.36 MICHIGAN .................................................................................................................................... DICKINSON ............................ ........................ ........................ 5.02 ........................ ........................MICHIGAN .................................................................................................................................... EATON ................................... ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... EMMET .................................. ........................ ........................ 38.71 29.93 26.63 MICHIGAN .................................................................................................................................... GENESEE .............................. ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... GLADWIN ............................... 15.11 10.98 10.47 8.33 7.47 MICHIGAN .................................................................................................................................... GOGEBIC ............................... ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... GRAND TRAVERSE ................ 2.01 ........................ 1.18 ........................ 1.73 MICHIGAN .................................................................................................................................... GRATIOT ................................ 2.47 2.54 3.29 2.85 3.50 MICHIGAN .................................................................................................................................... HILLSDALE ............................ 1.86 6.44 5.60 4.38 4.26 MICHIGAN .................................................................................................................................... HOUGHTON ........................... ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... HURON .................................. ........................ ........................ .55 .13 .31 MICHIGAN .................................................................................................................................... INGHAM ................................ 8.56 7.29 2.29 2.00 42.89 MICHIGAN .................................................................................................................................... IONIA .................................... 6.29 1.55 2.00 ........................ .64 MICHIGAN .................................................................................................................................... IOSCO ................................... ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... IRON ..................................... 4.85 1.55 36.38 61.81 22.52 MICHIGAN .................................................................................................................................... ISABELLA .............................. .64 ........................ .15 1.17 ........................MICHIGAN .................................................................................................................................... JACKSON ............................... 5.38 3.61 3.31 .82 1.02 MICHIGAN .................................................................................................................................... KALAMAZOO .......................... 11.95 4.27 2.18 2.22 .15 MICHIGAN .................................................................................................................................... KALKASKA ............................. ........................ ........................ ........................ .82 6.16 
201 

MICHIGAN .................................................................................................................................... KENT ..................................... .25 7.26 9.33 2.66 70.03 MICHIGAN .................................................................................................................................... KEWEENAW ........................... ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... LAKE ..................................... ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... LAPEER ................................. 4.61 7.78 5.15 4.58 4.25 MICHIGAN .................................................................................................................................... LEELANAU ............................. .30 .42 ........................ ........................ .56 MICHIGAN .................................................................................................................................... LENAWEE .............................. 7.30 6.97 6.38 6.89 4.92 MICHIGAN .................................................................................................................................... LIVINGSTON .......................... ........................ ........................ 4.84 .30 ........................MICHIGAN .................................................................................................................................... LUCE ..................................... ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... MACKINAC ............................ 2.40 ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... MACOMB ............................... ........................ ........................ 6.77 ........................ ........................MICHIGAN .................................................................................................................................... MANISTEE ............................. ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... MARQUETTE .......................... ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... MASON .................................. 1.36 1.59 1.63 1.55 1.88 MICHIGAN .................................................................................................................................... MECOSTA .............................. 6.72 6.64 .37 ........................ ........................MICHIGAN .................................................................................................................................... MENOMINEE .......................... .15 2.58 5.32 3.69 2.34 MICHIGAN .................................................................................................................................... MIDLAND ............................... ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... MISSAUKEE ........................... ........................ 22.87 21.02 20.24 17.76 MICHIGAN .................................................................................................................................... MONROE ............................... ........................ ........................ ........................ .06 39.39 MICHIGAN .................................................................................................................................... MONTCALM ........................... 2.70 2.81 1.43 1.20 1.87 MICHIGAN .................................................................................................................................... MONTMORENCY .................... 1.66 2.24 ........................ ........................ .39 MICHIGAN .................................................................................................................................... MUSKEGON ........................... ........................ ........................ ........................ 3.52 1.11 MICHIGAN .................................................................................................................................... NEWAYGO ............................. ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... OAKLAND .............................. 7.95 ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... OCEANA ................................ 8.98 16.79 14.20 10.08 15.24 MICHIGAN .................................................................................................................................... OGEMAW ............................... ........................ .07 ........................ ........................ ........................MICHIGAN .................................................................................................................................... ONTONAGON ......................... 7.46 5.66 1.00 26.06 24.56 MICHIGAN .................................................................................................................................... OSCEOLA .............................. 3.56 2.04 1.27 ........................ ........................MICHIGAN .................................................................................................................................... OSCODA ................................ ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... OTSEGO ................................ ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... OTTAWA ................................ ........................ 1.69 .66 .58 .53 MICHIGAN .................................................................................................................................... PRESQUE ISLE ...................... 7.70 3.69 4.60 5.18 4.84 MICHIGAN .................................................................................................................................... ROSCOMMON ........................ ........................ ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... SAGINAW ............................... .16 ........................ .04 2.36 2.21 MICHIGAN .................................................................................................................................... SANILAC ................................ 4.68 4.47 4.32 4.03 4.19 MICHIGAN .................................................................................................................................... SCHOOLCRAFT ...................... .73 ........................ ........................ ........................ ........................MICHIGAN .................................................................................................................................... SHIAWASSEE ......................... 5.65 5.30 5.86 1.21 ........................MICHIGAN .................................................................................................................................... ST. CLAIR ............................. ........................ ........................ ........................ 30.78 28.40 MICHIGAN .................................................................................................................................... ST. JOSEPH ........................... 2.49 2.94 2.12 2.43 3.63 MICHIGAN .................................................................................................................................... TUSCOLA ............................... 4.02 4.04 3.95 4.29 4.59 MICHIGAN .................................................................................................................................... VAN BUREN .......................... ........................ ........................ .76 2.03 5.99 
202 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

MICHIGAN .................................................................................................................................... WASHTENAW ......................... 2.59 2.91 2.89 2.45 1.53 MICHIGAN .................................................................................................................................... WAYNE .................................. .55 .52 .44 .32 ........................MICHIGAN .................................................................................................................................... WEXFORD .............................. ........................ ........................ ........................ 25.85 51.85 MINNESOTA ................................................................................................................................. AITKIN ................................... 6.78 6.30 10.32 9.88 22.35 MINNESOTA ................................................................................................................................. ANOKA .................................. ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. BECKER ................................ .61 .80 .59 11.26 10.95 MINNESOTA ................................................................................................................................. BELTRAMI ............................. 4.25 .16 ........................ .38 4.80 MINNESOTA ................................................................................................................................. BENTON ................................ .64 .66 2.54 1.55 1.23 MINNESOTA ................................................................................................................................. BIG STONE ............................ ........................ ........................ 2.03 ........................ .58 MINNESOTA ................................................................................................................................. BLUE EARTH ......................... .15 .20 ........................ ........................ .07 MINNESOTA ................................................................................................................................. BROWN ................................. .96 .92 1.84 1.54 1.54 MINNESOTA ................................................................................................................................. CARLTON .............................. 3.05 3.08 3.14 2.26 ........................MINNESOTA ................................................................................................................................. CARVER ................................ .51 ........................ .61 .01 .85 MINNESOTA ................................................................................................................................. CASS ..................................... 8.79 4.55 6.14 8.55 10.30 MINNESOTA ................................................................................................................................. CHIPPEWA ............................. ........................ ........................ .78 2.73 2.25 MINNESOTA ................................................................................................................................. CHISAGO ............................... ........................ ........................ .71 24.58 32.28 MINNESOTA ................................................................................................................................. CLAY ..................................... 3.03 5.44 4.51 3.88 8.01 MINNESOTA ................................................................................................................................. CLEARWATER ........................ .68 .28 2.38 3.42 5.62 MINNESOTA ................................................................................................................................. COOK .................................... ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. COTTONWOOD ....................... 3.16 3.39 5.32 2.77 2.18 MINNESOTA ................................................................................................................................. CROW WING .......................... ........................ 2.34 4.86 1.51 5.85 MINNESOTA ................................................................................................................................. DAKOTA ................................. ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. DODGE .................................. 1.10 .01 .07 ........................ ........................MINNESOTA ................................................................................................................................. DOUGLAS .............................. 3.38 3.08 3.88 1.07 2.53 MINNESOTA ................................................................................................................................. FARIBAULT ............................ ........................ ........................ ........................ ........................ .09 MINNESOTA ................................................................................................................................. FILLMORE ............................. .24 .11 .06 .77 3.50 MINNESOTA ................................................................................................................................. FREEBORN ............................ ........................ ........................ ........................ ........................ 1.20 MINNESOTA ................................................................................................................................. GOODHUE ............................. ........................ 3.83 3.25 1.80 .99 MINNESOTA ................................................................................................................................. GRANT .................................. .47 .44 11.19 .09 1.11 MINNESOTA ................................................................................................................................. HENNEPIN ............................. ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. HOUSTON .............................. ........................ ........................ .25 1.01 16.03 MINNESOTA ................................................................................................................................. HUBBARD ............................. ........................ ........................ 10.51 2.87 2.17 MINNESOTA ................................................................................................................................. ISANTI ................................... 2.63 2.70 ........................ 3.08 ........................MINNESOTA ................................................................................................................................. ITASCA .................................. ........................ ........................ ........................ 1.59 13.49 MINNESOTA ................................................................................................................................. JACKSON ............................... 2.45 2.36 2.48 1.77 .39 
203 

MINNESOTA ................................................................................................................................. KANABEC .............................. .26 .06 1.92 2.17 28.92 MINNESOTA ................................................................................................................................. KANDIYOHI ............................ ........................ .39 .97 4.95 4.59 MINNESOTA ................................................................................................................................. KITTSON ................................ .36 .17 .14 1.45 6.70 MINNESOTA ................................................................................................................................. KOOCHICHING ....................... 1.56 .72 1.37 1.09 .58 MINNESOTA ................................................................................................................................. LAC QUI PARLE .................... 1.26 ........................ .01 .11 .86 MINNESOTA ................................................................................................................................. LAKE ..................................... ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. LAKE OF THE WOODS ........... 6.11 8.25 7.90 11.78 11.00 MINNESOTA ................................................................................................................................. LE SUEUR ............................. ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. LINCOLN ............................... .87 .64 .10 1.97 2.49 MINNESOTA ................................................................................................................................. LYON ..................................... 4.42 5.01 6.87 6.88 4.66 MINNESOTA ................................................................................................................................. MAHNOMEN, S ...................... .11 .60 3.82 4.20 4.38 MINNESOTA ................................................................................................................................. MARSHALL,W ........................ .33 .42 1.13 1.13 2.63 MINNESOTA ................................................................................................................................. MARTIN ................................. .28 .03 .20 .32 .59 MINNESOTA ................................................................................................................................. MCLEOD ................................ .55 .36 .65 .20 4.93 MINNESOTA ................................................................................................................................. MEEKER ................................ 10.10 7.44 6.93 6.52 5.68 MINNESOTA ................................................................................................................................. MILLE LACS .......................... ........................ ........................ ........................ .99 2.71MINNESOTA ................................................................................................................................. MORRISON ............................ 3.09 1.96 6.00 4.44 6.29 MINNESOTA ................................................................................................................................. MOWER ................................. ........................ ........................ ........................ 3.93 5.92 MINNESOTA ................................................................................................................................. MURRAY ............................... 1.33 1.20 2.11 1.81 2.44 MINNESOTA ................................................................................................................................. NICOLLET .............................. .43 .41 .49 .53 .42 MINNESOTA ................................................................................................................................. NOBLES ................................ 2.73 2.73 3.73 4.31 4.19 MINNESOTA ................................................................................................................................. NORMAN ............................... .21 ........................ .28 .43 2.40 MINNESOTA ................................................................................................................................. OLMSTED .............................. ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. PENNINGTON ......................... .32 .86 1.20 1.14 1.80 MINNESOTA ................................................................................................................................. PINE ...................................... 5.82 7.36 3.33 1.29 .39 MINNESOTA ................................................................................................................................. PIPESTONE ............................ 1.28 1.34 1.39 2.89 3.70 MINNESOTA ................................................................................................................................. POPE ..................................... 1.28 .94 .60 13.95 12.36 MINNESOTA ................................................................................................................................. RAMSEY ................................ ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. RED LAKE ............................. .72 .54 .18 .11 .88 MINNESOTA ................................................................................................................................. REDWOOD ............................. 1.47 2.09 1.87 1.40 1.42 MINNESOTA ................................................................................................................................. RENVILLE .............................. 6.42 6.70 9.08 10.10 8.57 MINNESOTA ................................................................................................................................. RICE ..................................... ........................ ........................ ........................ ........................ .37 MINNESOTA ................................................................................................................................. ROCK .................................... ........................ ........................ ........................ ........................ 3.46 MINNESOTA ................................................................................................................................. ROSEAU ................................ 3.48 4.31 5.99 7.01 8.65 MINNESOTA ................................................................................................................................. SCOTT ................................... ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. SHERBURNE ......................... ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. SIBLEY .................................. 2.18 1.58 3.00 3.83 4.42 MINNESOTA ................................................................................................................................. ST. LOUIS, S ......................... .18 ........................ 1.06 .82 .57 MINNESOTA ................................................................................................................................. STEARNS ............................... .14 .68 .07 .26 .33 MINNESOTA ................................................................................................................................. STEELE ................................. ........................ ........................ ........................ ........................ ........................
204 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

MINNESOTA ................................................................................................................................. STEVENS ............................... ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. SWIFT .................................... .63 .62 1.39 1.31 1.83 MINNESOTA ................................................................................................................................. TODD .................................... .74 .53 4.74 3.79 3.03 MINNESOTA ................................................................................................................................. TRAVERSE ............................. ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. WABASHA .............................. 1.98 2.86 2.89 1.99 .51 MINNESOTA ................................................................................................................................. WADENA ................................ .84 5.55 6.31 19.55 21.18 MINNESOTA ................................................................................................................................. WASECA ................................ ........................ ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. WASHINGTON ........................ 22.76 7.86 ........................ ........................ ........................MINNESOTA ................................................................................................................................. WATONWAN ........................... .85 .41 ........................ .07 ........................MINNESOTA ................................................................................................................................. WEST OTTER TAIL ................. .83 .43 1.41 2.50 2.12 MINNESOTA ................................................................................................................................. WEST POLK ........................... .06 .81 .92 .91 1.39 MINNESOTA ................................................................................................................................. WILKIN .................................. ........................ .01 .02 ........................ .02 MINNESOTA ................................................................................................................................. WINONA ................................ .98 .08 5.15 7.52 7.37 MINNESOTA ................................................................................................................................. WRIGHT ................................. .26 ........................ ........................ ........................ ........................MINNESOTA ................................................................................................................................. YELLOW MEDICINE ............... .03 .05 1.31 .49 1.10 MISSISSIPPI ................................................................................................................................. ADAMS .................................. ........................ ........................ 4.15 10.99 10.71 MISSISSIPPI ................................................................................................................................. ALCORN ................................ .23 .38 .16 .13 1.25 MISSISSIPPI ................................................................................................................................. AMITE ................................... 18.85 19.52 14.11 7.96 9.83 MISSISSIPPI ................................................................................................................................. ATTALA .................................. ........................ .68 7.75 8.64 5.90 MISSISSIPPI ................................................................................................................................. BENTON ................................ 24.12 18.35 16.33 25.70 30.75 MISSISSIPPI ................................................................................................................................. BOLIVAR ............................... 54.54 61.68 61.76 57.79 56.13 MISSISSIPPI ................................................................................................................................. CALHOUN .............................. .64 6.09 9.04 8.10 8.71 MISSISSIPPI ................................................................................................................................. CARROLL .............................. ........................ .27 .44 6.90 34.08 MISSISSIPPI ................................................................................................................................. CHICKASAW .......................... 11.33 11.69 12.10 12.22 9.59 MISSISSIPPI ................................................................................................................................. CHOCTAW ............................. 21.55 17.82 14.35 10.74 5.58 MISSISSIPPI ................................................................................................................................. CLAIBORNE ........................... 9.00 8.88 13.45 11.64 25.27 MISSISSIPPI ................................................................................................................................. CLARKE ................................. ........................ ........................ 1.05 3.23 .65 MISSISSIPPI ................................................................................................................................. CLAY ..................................... 26.91 25.88 23.45 12.83 8.46 MISSISSIPPI ................................................................................................................................. COAHOMA ............................. 42.43 44.60 50.31 44.68 38.84 MISSISSIPPI ................................................................................................................................. COPIAH ................................. ........................ ........................ 23.45 20.20 16.73 MISSISSIPPI ................................................................................................................................. COVINGTON ........................... ........................ 7.19 5.78 4.35 5.54 MISSISSIPPI ................................................................................................................................. DESOTO ................................ 29.20 73.04 67.61 60.75 61.15 MISSISSIPPI ................................................................................................................................. FOREST ................................. ........................ ........................ ........................ 49.45 45.67 MISSISSIPPI ................................................................................................................................. FRANKLIN .............................. ........................ ........................ 1.19 ........................ 6.78 MISSISSIPPI ................................................................................................................................. GEORGE ................................ ........................ 78.65 82.44 85.35 84.61 
205 

MISSISSIPPI ................................................................................................................................. GREENE ................................ ........................ 2.39 2.32 2.90 4.00 MISSISSIPPI ................................................................................................................................. GRENADA .............................. 12.92 .63 .60 .54 .43 MISSISSIPPI ................................................................................................................................. HANCOCK .............................. ........................ 5.46 ........................ 7.93 20.95 MISSISSIPPI ................................................................................................................................. HARRISON ............................. ........................ ........................ ........................ ........................ 54.70 MISSISSIPPI ................................................................................................................................. HINDS ................................... ........................ .95 15.65 17.22 7.05 MISSISSIPPI ................................................................................................................................. HOLMES ................................ 23.32 28.84 29.61 26.42 22.83 MISSISSIPPI ................................................................................................................................. HUMPHREYS ......................... 27.74 28.93 36.34 56.13 59.23 MISSISSIPPI ................................................................................................................................. ISSAQUENA ........................... 21.64 19.49 36.02 38.65 29.16 MISSISSIPPI ................................................................................................................................. ITAWAMBA ............................ ........................ ........................ 34.45 31.14 45.42 MISSISSIPPI ................................................................................................................................. JACKSON ............................... ........................ ........................ ........................ ........................ ........................MISSISSIPPI ................................................................................................................................. JASPER ................................. .17 .53 1.89 2.91 1.31 MISSISSIPPI ................................................................................................................................. JEFFERSON ........................... ........................ .44 4.31 2.98 2.67 MISSISSIPPI ................................................................................................................................. JEFFERSON DAVIS ................. 15.64 30.19 36.39 38.96 35.29 MISSISSIPPI ................................................................................................................................. JONES ................................... 3.40 3.95 6.48 2.96 22.73 MISSISSIPPI ................................................................................................................................. KEMPER ................................ 2.58 3.17 3.48 3.13 4.58 MISSISSIPPI ................................................................................................................................. LAFAYETTE ............................ ........................ ........................ 1.87 37.11 24.23 MISSISSIPPI ................................................................................................................................. LAMAR .................................. 23.99 23.89 21.55 24.79 27.74 MISSISSIPPI ................................................................................................................................. LAUDERDALE ........................ 45.03 43.37 43.43 35.08 49.68 MISSISSIPPI ................................................................................................................................. LAWRENCE ............................ ........................ ........................ ........................ ........................ .04 MISSISSIPPI ................................................................................................................................. LEAKE ................................... 29.19 26.36 26.77 37.45 41.38 MISSISSIPPI ................................................................................................................................. LEE ....................................... .11 ........................ ........................ ........................ ........................MISSISSIPPI ................................................................................................................................. LEFLORE ............................... 76.86 75.74 70.95 67.95 64.77 MISSISSIPPI ................................................................................................................................. LINCOLN ............................... ........................ ........................ 3.14 2.55 18.28 MISSISSIPPI ................................................................................................................................. LOWNDES .............................. 2.58 3.29 2.74 1.50 .77 MISSISSIPPI ................................................................................................................................. MADISON .............................. 4.83 7.14 20.99 19.08 15.00 MISSISSIPPI ................................................................................................................................. MARION ................................ 30.58 23.88 23.59 23.17 17.91 MISSISSIPPI ................................................................................................................................. MARSHALL ............................ 62.67 60.50 68.86 63.73 55.63 MISSISSIPPI ................................................................................................................................. MONROE ............................... 11.51 12.96 11.17 15.91 13.37 MISSISSIPPI ................................................................................................................................. MONTGOMERY ...................... ........................ .89 2.09 3.71 3.32 MISSISSIPPI ................................................................................................................................. NESHOBA .............................. ........................ .07 ........................ 1.31 1.25 MISSISSIPPI ................................................................................................................................. NEWTON ................................ 6.78 .05 2.79 5.66 13.07 MISSISSIPPI ................................................................................................................................. NOXUBEE .............................. 26.94 28.75 23.83 24.78 20.83 MISSISSIPPI ................................................................................................................................. OKTIBBEHA ........................... 11.17 6.54 5.45 3.24 1.19 MISSISSIPPI ................................................................................................................................. PANOLA ................................. 11.21 12.82 50.82 47.23 43.01 MISSISSIPPI ................................................................................................................................. PEARL RIVER ........................ 39.53 46.29 51.06 55.69 62.82 MISSISSIPPI ................................................................................................................................. PERRY .................................. ........................ .14 .18 1.02 ........................MISSISSIPPI ................................................................................................................................. PIKE ...................................... 38.10 44.52 45.87 42.44 40.89 MISSISSIPPI ................................................................................................................................. PONTOTOC ............................ .21 .14 1.91 9.42 15.39 MISSISSIPPI ................................................................................................................................. PRENTISS .............................. ........................ 6.66 5.58 4.38 3.97 MISSISSIPPI ................................................................................................................................. QUITMAN ............................... 52.65 48.94 50.07 44.71 39.25 
206 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

MISSISSIPPI ................................................................................................................................. RANKIN ................................. 67.35 65.85 54.37 51.65 54.04 MISSISSIPPI ................................................................................................................................. SCOTT ................................... 6.57 5.90 7.09 4.90 21.02 MISSISSIPPI ................................................................................................................................. SHARKEY .............................. 72.34 78.58 78.90 70.64 70.95 MISSISSIPPI ................................................................................................................................. SIMPSON ............................... 53.02 48.00 51.34 54.39 50.89 MISSISSIPPI ................................................................................................................................. SMITH ................................... 10.31 15.64 10.88 8.96 8.90 MISSISSIPPI ................................................................................................................................. STONE ................................... 2.37 62.82 59.21 58.47 58.94 MISSISSIPPI ................................................................................................................................. SUNFLOWER .......................... 58.82 61.08 57.47 50.55 56.04 MISSISSIPPI ................................................................................................................................. TALLAHATCHIE ...................... 26.90 28.06 23.92 21.89 22.51 MISSISSIPPI ................................................................................................................................. TATE ..................................... 29.10 37.93 51.55 47.39 51.07 MISSISSIPPI ................................................................................................................................. TIPPAH .................................. 10.25 8.51 8.60 16.31 12.47 MISSISSIPPI ................................................................................................................................. TISHOMINGO ......................... 45.32 50.16 41.78 33.36 29.77 MISSISSIPPI ................................................................................................................................. TUNICA ................................. 55.31 57.64 52.72 48.74 49.60 MISSISSIPPI ................................................................................................................................. UNION ................................... 8.98 8.63 7.91 7.14 6.01 MISSISSIPPI ................................................................................................................................. WALTHALL ............................. 5.38 23.08 23.30 24.17 26.76 MISSISSIPPI ................................................................................................................................. WARREN ............................... 22.83 21.01 20.20 27.98 21.97 MISSISSIPPI ................................................................................................................................. WASHINGTON ........................ 55.50 56.92 47.24 63.73 60.91 MISSISSIPPI ................................................................................................................................. WAYNE .................................. ........................ .51 2.01 1.00 2.62 MISSISSIPPI ................................................................................................................................. WEBSTER .............................. .90 .58 .01 1.67 ........................MISSISSIPPI ................................................................................................................................. WILKINSON ............................ .49 ........................ ........................ 3.33 14.58 MISSISSIPPI ................................................................................................................................. WINSTON ............................... ........................ .08 2.34 1.91 1.12 MISSISSIPPI ................................................................................................................................. YALOBUSHA .......................... 5.98 7.15 6.51 4.01 3.66 MISSISSIPPI ................................................................................................................................. YAZOO .................................. 15.67 16.37 21.37 30.08 32.13 MISSOURI .................................................................................................................................... ADAIR ................................... .67 ........................ .06 ........................ .20 MISSOURI .................................................................................................................................... ANDREW ............................... ........................ ........................ .16 2.08 2.06 MISSOURI .................................................................................................................................... ATCHISON ............................. ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... AUDRAIN ............................... ........................ ........................ ........................ .22 1.13 MISSOURI .................................................................................................................................... BARRY .................................. .44 .21 ........................ ........................ ........................MISSOURI .................................................................................................................................... BARTON ................................ .24 .06 .01 .60 .80 MISSOURI .................................................................................................................................... BATES ................................... 11.69 9.86 8.58 6.23 5.00 MISSOURI .................................................................................................................................... BENTON ................................ ........................ ........................ ........................ .67 1.04 MISSOURI .................................................................................................................................... BOLLINGER ........................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... BOONE .................................. ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... BUCHANAN ........................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... BUTLER ................................. 8.89 7.96 8.01 12.41 9.86 MISSOURI .................................................................................................................................... CALDWELL ............................ ........................ ........................ .19 .13 ........................
207 

MISSOURI .................................................................................................................................... CALLAWAY ............................ ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... CAMDEN ............................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... CAPE GIRARDEAU ................. .39 .25 ........................ 1.34 .29 MISSOURI .................................................................................................................................... CARROLL .............................. ........................ .35 .03 ........................ 1.48 MISSOURI .................................................................................................................................... CARTER ................................ ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... CASS ..................................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... CEDAR .................................. ........................ 13.99 15.20 7.57 9.97 MISSOURI .................................................................................................................................... CHARITON ............................. ........................ ........................ ........................ ........................ .11 MISSOURI .................................................................................................................................... CHRISTIAN ............................ ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... CLARK ................................... 1.26 1.96 .90 1.30 .45 MISSOURI .................................................................................................................................... CLAY ..................................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... CLINTON ............................... ........................ 1.27 ........................ .82 ........................MISSOURI .................................................................................................................................... COLE ..................................... .98 .87 1.15 2.36 ........................MISSOURI .................................................................................................................................... COOPER ................................ .07 ........................ .10 ........................ ........................MISSOURI .................................................................................................................................... CRAWFORD ........................... ........................ ........................ ........................ .75 ........................MISSOURI .................................................................................................................................... DADE .................................... ........................ .41 ........................ ........................ .66 MISSOURI .................................................................................................................................... DALLAS ................................. 12.82 8.40 6.31 5.90 24.55 MISSOURI .................................................................................................................................... DAVIESS ................................ ........................ ........................ 9.14 7.29 6.19 MISSOURI .................................................................................................................................... DEKALB ................................. 1.13 1.17 1.76 .72 .15 MISSOURI .................................................................................................................................... DENT ..................................... ........................ ........................ ........................ 1.57 ........................MISSOURI .................................................................................................................................... DOUGLAS .............................. 1.91 .80 .10 .04 1.05 MISSOURI .................................................................................................................................... DUNKLIN ............................... .32 .02 1.02 1.93 .72 MISSOURI .................................................................................................................................... FRANKLIN .............................. .28 .33 ........................ ........................ ........................MISSOURI .................................................................................................................................... GASCONADE .......................... .50 .26 2.61 ........................ ........................MISSOURI .................................................................................................................................... GENTRY ................................ ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... GREENE ................................ .41 .31 ........................ ........................ ........................MISSOURI .................................................................................................................................... GRUNDY ................................ ........................ ........................ ........................ ........................ .39 MISSOURI .................................................................................................................................... HARRISON ............................. ........................ ........................ ........................ 7.51 5.06 MISSOURI .................................................................................................................................... HENRY .................................. 5.63 21.55 12.92 12.36 10.55 MISSOURI .................................................................................................................................... HICKORY ............................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... HOLT ..................................... 1.02 1.02 1.09 .25 1.28 MISSOURI .................................................................................................................................... HOWARD ............................... .30 .09 ........................ ........................ ........................MISSOURI .................................................................................................................................... HOWELL ................................ 9.34 .20 .20 ........................ .20 MISSOURI .................................................................................................................................... IRON ..................................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... JACKSON ............................... ........................ ........................ 23.38 22.15 11.85 MISSOURI .................................................................................................................................... JASPER ................................. ........................ ........................ ........................ .43 .22 MISSOURI .................................................................................................................................... JEFFERSON ........................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... JOHNSON .............................. 23.09 23.23 23.32 19.78 16.14 MISSOURI .................................................................................................................................... KNOX .................................... 7.88 2.63 3.31 1.70 6.81 MISSOURI .................................................................................................................................... LACLEDE ............................... 2.20 2.17 4.68 8.28 5.21 
208 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

MISSOURI .................................................................................................................................... LAFAYETTE ............................ .25 .27 ........................ .52 ........................MISSOURI .................................................................................................................................... LAWRENCE ............................ ........................ .30 .42 .14 7.99 MISSOURI .................................................................................................................................... LEWIS ................................... .43 4.33 7.09 5.64 3.52 MISSOURI .................................................................................................................................... LINCOLN ............................... 1.35 ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... LINN ...................................... .04 .03 .46 .39 ........................MISSOURI .................................................................................................................................... LIVINGSTON .......................... 3.86 3.04 3.10 3.18 2.58 MISSOURI .................................................................................................................................... MACON ................................. 1.20 .95 .41 1.86 .57 MISSOURI .................................................................................................................................... MADISON .............................. ........................ ........................ ........................ .02 5.86 MISSOURI .................................................................................................................................... MARIES ................................. .62 1.10 ........................ ........................ ........................MISSOURI .................................................................................................................................... MARION ................................ ........................ 2.62 ........................ ........................ ........................MISSOURI .................................................................................................................................... MCDONALD ........................... ........................ ........................ ........................ 12.72 9.54 MISSOURI .................................................................................................................................... MERCER ............................... ........................ ........................ ........................ .01 2.98 MISSOURI .................................................................................................................................... MILLER ................................. 1.35 2.15 2.83 1.78 9.40 MISSOURI .................................................................................................................................... MISSISSIPPI .......................... 5.39 5.64 7.74 12.63 6.17 MISSOURI .................................................................................................................................... MONITEAU ............................. 9.44 ........................ 2.19 13.69 10.81 MISSOURI .................................................................................................................................... MONROE ............................... 1.47 1.33 .48 3.76 ........................MISSOURI .................................................................................................................................... MONTGOMERY ...................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... MORGAN ............................... ........................ .59 .58 ........................ ........................MISSOURI .................................................................................................................................... NEW MADRID ........................ .33 .20 5.73 6.40 5.61 MISSOURI .................................................................................................................................... NEWTON ................................ 2.64 ........................ 2.45 1.55 .43 MISSOURI .................................................................................................................................... NODAWAY ............................. .04 ........................ .03 .40 .27 MISSOURI .................................................................................................................................... OREGON ................................ 1.78 .63 ........................ .24 5.41 MISSOURI .................................................................................................................................... OSAGE .................................. 1.74 1.22 .70 .79 1.28 MISSOURI .................................................................................................................................... OZARK .................................. 1.47 1.96 9.54 7.79 7.36 MISSOURI .................................................................................................................................... PEMISCOT ............................. 12.97 13.35 11.36 12.77 9.35 MISSOURI .................................................................................................................................... PERRY .................................. 2.34 ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... PETTIS .................................. ........................ ........................ .15 .17 .06 MISSOURI .................................................................................................................................... PHELPS ................................. .55 ........................ ........................ .01 ........................MISSOURI .................................................................................................................................... PIKE ...................................... ........................ .29 ........................ 1.16 .17 MISSOURI .................................................................................................................................... PLATTE .................................. ........................ ........................ ........................ 3.43 ........................MISSOURI .................................................................................................................................... POLK ..................................... 1.08 .17 ........................ ........................ 1.50 MISSOURI .................................................................................................................................... PULASKI ................................ ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... PUTNAM ................................ 4.62 .30 .25 .55 11.98 MISSOURI .................................................................................................................................... RALLS ................................... ........................ ........................ .25 .30 ........................MISSOURI .................................................................................................................................... RANDOLPH ............................ .01 ........................ ........................ ........................ 1.52 
209 

MISSOURI .................................................................................................................................... RAY ....................................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... REYNOLDS ............................ ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... RIPLEY .................................. .74 .70 .54 .28 .08 MISSOURI .................................................................................................................................... SALINE .................................. .02 .12 .64 .90 1.26 MISSOURI .................................................................................................................................... SCHUYLER ............................ .13 ........................ .74 1.06 8.55 MISSOURI .................................................................................................................................... SCOTLAND ............................ ........................ 2.89 ........................ .37 .12 MISSOURI .................................................................................................................................... SCOTT ................................... ........................ .19 32.64 ........................ ........................MISSOURI .................................................................................................................................... SHANNON .............................. 3.59 ........................ 9.00 .40 .41 MISSOURI .................................................................................................................................... SHELBY ................................. .22 ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... ST LOUIS CITY ...................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... ST. CHARLES ........................ ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... ST. CLAIR ............................. 3.61 5.73 5.96 7.69 7.08 MISSOURI .................................................................................................................................... ST. FRANCOIS ....................... ........................ .20 ........................ ........................ ........................MISSOURI .................................................................................................................................... ST. LOUIS ............................. ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... STE. GENEVIEVE ................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... STODDARD ............................ 1.30 1.19 .86 .66 1.18 MISSOURI .................................................................................................................................... STONE ................................... ........................ .28 .27 1.38 ........................MISSOURI .................................................................................................................................... SULLIVAN .............................. ........................ ........................ ........................ ........................ .15 MISSOURI .................................................................................................................................... TANEY ................................... ........................ ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... TEXAS ................................... .04 .20 .20 .18 .78 MISSOURI .................................................................................................................................... VERNON ................................ .21 31.45 24.13 14.72 12.03 MISSOURI .................................................................................................................................... WARREN ............................... 3.81 ........................ ........................ ........................ ........................MISSOURI .................................................................................................................................... WASHINGTON ........................ ........................ ........................ ........................ 2.14 ........................MISSOURI .................................................................................................................................... WAYNE .................................. ........................ ........................ ........................ 13.91 3.66 MISSOURI .................................................................................................................................... WEBSTER .............................. 1.22 .35 .11 14.84 13.38 MISSOURI .................................................................................................................................... WORTH .................................. ........................ ........................ ........................ .86 ........................MISSOURI .................................................................................................................................... WRIGHT ................................. 4.06 2.69 1.44 1.16 .05 MONTANA .................................................................................................................................... BEAVERHEAD ........................ ........................ ........................ ........................ 1.67 1.45MONTANA .................................................................................................................................... BIG HORN ............................. 15.98 18.39 22.98 24.15 20.84 MONTANA .................................................................................................................................... BLAINE .................................. 40.00 38.09 37.02 37.85 32.28 MONTANA .................................................................................................................................... BROADWATER ....................... 1.95 ........................ 62.56 58.47 53.05 MONTANA .................................................................................................................................... CARBON ................................ 43.20 12.63 11.52 18.21 18.47 MONTANA .................................................................................................................................... CARTER ................................ 4.96 5.58 18.72 14.03 12.52 MONTANA .................................................................................................................................... CASCADE .............................. .54 ........................ .76 .30 .22 MONTANA .................................................................................................................................... CHOUTEAU ............................ .94 .66 .55 1.26 1.41 MONTANA .................................................................................................................................... CUSTER ................................ .08 .09 .33 .97 .27 MONTANA .................................................................................................................................... DANIELS ................................ 5.01 4.43 6.77 7.18 7.05 MONTANA .................................................................................................................................... DAWSON ............................... .14 4.85 3.45 1.76 1.36 MONTANA .................................................................................................................................... DEER LODGE ........................ .07 ........................ ........................ .14 .51 MONTANA .................................................................................................................................... FALLON ................................. 1.69 1.50 1.47 .95 1.32 
210 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

MONTANA .................................................................................................................................... FERGUS ................................ 1.58 .35 1.70 2.30 2.88 MONTANA .................................................................................................................................... FLATHEAD ............................. ........................ 7.14 9.81 23.99 21.19 MONTANA .................................................................................................................................... GALLATIN .............................. .81 ........................ ........................ ........................ ........................MONTANA .................................................................................................................................... GARFIELD .............................. 35.40 19.14 50.87 44.82 35.03 MONTANA .................................................................................................................................... GLACIER ............................... ........................ ........................ ........................ ........................ 11.63 MONTANA .................................................................................................................................... GOLDEN VALLEY ................... ........................ ........................ ........................ .86 ........................MONTANA .................................................................................................................................... GRANITE ............................... ........................ ........................ ........................ ........................ 1.11 MONTANA .................................................................................................................................... HILL ...................................... 1.09 1.19 ........................ 1.58 2.72 MONTANA .................................................................................................................................... JEFFERSON ........................... ........................ ........................ ........................ ........................ ........................MONTANA .................................................................................................................................... JUDITH BASIN ....................... ........................ .22 ........................ ........................ ........................MONTANA .................................................................................................................................... LAKE ..................................... ........................ ........................ ........................ ........................ ........................MONTANA .................................................................................................................................... LEWIS AND CLARK ................ ........................ ........................ ........................ ........................ ........................MONTANA .................................................................................................................................... LIBERTY ................................ 1.30 3.32 ........................ ........................ 5.07 MONTANA .................................................................................................................................... LINCOLN ............................... 9.25 8.83 8.25 7.96 6.99 MONTANA .................................................................................................................................... MADISON .............................. ........................ ........................ ........................ .23 1.24 MONTANA .................................................................................................................................... MCCONE ............................... .96 1.39 1.16 1.62 2.52 MONTANA .................................................................................................................................... MEAGHER ............................. ........................ ........................ .55 ........................ 1.72 MONTANA .................................................................................................................................... MINERAL ............................... ........................ ........................ ........................ ........................ ........................MONTANA .................................................................................................................................... MISSOULA ............................. ........................ ........................ ........................ ........................ .55 MONTANA .................................................................................................................................... MUSSELSHELL ...................... ........................ ........................ 32.28 3.02 1.22 MONTANA .................................................................................................................................... PARK ..................................... 21.11 18.82 13.87 12.10 10.47 MONTANA .................................................................................................................................... PETROLEUM .......................... ........................ ........................ ........................ ........................ ........................MONTANA .................................................................................................................................... PHILLIPS ............................... 10.84 9.07 6.54 6.00 9.33 MONTANA .................................................................................................................................... PONDERA .............................. 3.86 2.93 2.67 1.92 1.12 MONTANA .................................................................................................................................... POWDER RIVER .................... ........................ 2.68 1.76 3.47 .51 MONTANA .................................................................................................................................... POWELL ................................ .51 5.27 5.22 2.88 2.94 MONTANA .................................................................................................................................... PRAIRIE ................................ ........................ ........................ ........................ 6.82 1.93 MONTANA .................................................................................................................................... RAVALLI ................................ 12.09 5.59 ........................ 6.84 2.20 MONTANA .................................................................................................................................... RICHLAND ............................. 1.96 5.61 11.20 12.69 7.92 MONTANA .................................................................................................................................... ROOSEVELT ........................... .27 ........................ ........................ ........................ 7.22 MONTANA .................................................................................................................................... ROSEBUD .............................. .69 ........................ 1.18 .20 2.03 MONTANA .................................................................................................................................... SANDERS .............................. 9.31 7.13 22.95 12.48 7.97 MONTANA .................................................................................................................................... SHERIDAN ............................. ........................ .27 .06 ........................ ........................MONTANA .................................................................................................................................... SILVER BOW ......................... ........................ ........................ ........................ ........................ ........................MONTANA .................................................................................................................................... STILLWATER .......................... 6.02 15.91 15.15 14.07 10.75 
211 

MONTANA .................................................................................................................................... SWEET GRASS ...................... 3.54 1.01 2.93 2.14 .28 MONTANA .................................................................................................................................... TETON ................................... 15.20 25.81 24.27 4.10 4.06 MONTANA .................................................................................................................................... TOOLE ................................... .23 .30 .35 .43 .22 MONTANA .................................................................................................................................... TREASURE ............................ ........................ 26.91 24.22 11.38 ........................MONTANA .................................................................................................................................... VALLEY ................................. 17.32 19.80 20.87 19.95 17.15 MONTANA .................................................................................................................................... WHEATLAND .......................... ........................ ........................ ........................ 1.76 ........................MONTANA .................................................................................................................................... WIBAUX ................................. .04 ........................ .62 1.24 .14 MONTANA .................................................................................................................................... YELLOWSTONE ...................... 21.61 20.18 16.67 13.40 9.39 NEBRASKA ................................................................................................................................... ADAMS .................................. .42 .47 .52 .76 .50 NEBRASKA ................................................................................................................................... ANTELOPE ............................. ........................ ........................ ........................ .29 .25 NEBRASKA ................................................................................................................................... ARTHUR ................................ ........................ ........................ ........................ ........................ ........................NEBRASKA ................................................................................................................................... BANNER ................................ ........................ ........................ ........................ ........................ ........................NEBRASKA ................................................................................................................................... BLAINE .................................. 11.81 ........................ ........................ ........................ ........................NEBRASKA ................................................................................................................................... BOONE .................................. .05 ........................ ........................ 1.01 3.62 NEBRASKA ................................................................................................................................... BOX BUTTE ........................... ........................ ........................ .09 ........................ .23NEBRASKA ................................................................................................................................... BOYD .................................... 1.15 1.20 2.52 1.64 2.57 NEBRASKA ................................................................................................................................... BROWN ................................. ........................ ........................ ........................ ........................ .12 NEBRASKA ................................................................................................................................... BUFFALO ............................... 1.36 2.77 15.84 14.24 19.72 NEBRASKA ................................................................................................................................... BURT .................................... .39 .39 9.33 12.06 7.38 NEBRASKA ................................................................................................................................... BUTLER ................................. .13 4.60 .09 .03 .63 NEBRASKA ................................................................................................................................... CASS ..................................... ........................ ........................ .25 .79 .39 NEBRASKA ................................................................................................................................... CEDAR .................................. .67 .30 .20 .02 .04 NEBRASKA ................................................................................................................................... CHASE .................................. 7.44 .68 .32 2.35 2.03 NEBRASKA ................................................................................................................................... CHERRY ................................ .55 .84 .49 .38 1.02 NEBRASKA ................................................................................................................................... CHEYENNE ............................ 1.59 2.98 1.50 5.19 4.90 NEBRASKA ................................................................................................................................... CLAY ..................................... 1.00 1.25 .27 .92 14.32 NEBRASKA ................................................................................................................................... COLFAX ................................. .10 .31 .57 6.96 2.53 NEBRASKA ................................................................................................................................... CUMING ................................ .33 .30 .30 .34 .33 NEBRASKA ................................................................................................................................... CUSTER ................................ 5.99 5.20 .34 2.32 2.10 NEBRASKA ................................................................................................................................... DAKOTA ................................. ........................ ........................ ........................ ........................ ........................NEBRASKA ................................................................................................................................... DAWES .................................. ........................ 1.58 .42 ........................ .47 NEBRASKA ................................................................................................................................... DAWSON ............................... .04 .05 1.50 .79 1.03 NEBRASKA ................................................................................................................................... DEUEL ................................... ........................ ........................ ........................ ........................ ........................NEBRASKA ................................................................................................................................... DIXON ................................... ........................ ........................ ........................ ........................ .39 NEBRASKA ................................................................................................................................... DODGE .................................. .51 .45 3.16 2.83 2.65 NEBRASKA ................................................................................................................................... DOUGLAS .............................. ........................ ........................ ........................ ........................ ........................NEBRASKA ................................................................................................................................... DUNDY .................................. ........................ ........................ 4.11 17.06 5.79 NEBRASKA ................................................................................................................................... FILLMORE ............................. .79 ........................ ........................ ........................ .77 NEBRASKA ................................................................................................................................... FRANKLIN .............................. 1.36 ........................ .07 .66 5.90 NEBRASKA ................................................................................................................................... FRONTIER ............................. 1.14 .95 2.01 4.21 2.02 
212 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

NEBRASKA ................................................................................................................................... FURNAS ................................ .56 3.49 3.42 3.46 3.63 NEBRASKA ................................................................................................................................... GAGE .................................... .13 .07 .07 .67 .38 NEBRASKA ................................................................................................................................... GARDEN ................................ ........................ ........................ ........................ ........................ ........................NEBRASKA ................................................................................................................................... GARFIELD .............................. 1.11 ........................ 4.02 30.23 31.15 NEBRASKA ................................................................................................................................... GOSPER ................................ ........................ ........................ ........................ 1.28 .41 NEBRASKA ................................................................................................................................... GRANT .................................. ........................ ........................ ........................ ........................ ........................NEBRASKA ................................................................................................................................... GREELEY ............................... .87 .77 .75 .69 11.38 NEBRASKA ................................................................................................................................... HALL ..................................... ........................ .27 1.10 13.11 11.59 NEBRASKA ................................................................................................................................... HAMILTON ............................. .24 ........................ .70 .49 .16 NEBRASKA ................................................................................................................................... HARLAN ................................ .70 ........................ .57 7.66 2.10 NEBRASKA ................................................................................................................................... HAYES ................................... 16.68 15.19 14.26 8.22 7.15 NEBRASKA ................................................................................................................................... HITCHCOCK ........................... ........................ 9.03 16.46 14.05 12.63 NEBRASKA ................................................................................................................................... HOLT ..................................... .12 ........................ .45 .09 .06 NEBRASKA ................................................................................................................................... HOOKER ................................ ........................ ........................ ........................ ........................ ........................NEBRASKA ................................................................................................................................... HOWARD ............................... 1.88 .29 .46 3.24 1.01 NEBRASKA ................................................................................................................................... JEFFERSON ........................... ........................ .36 13.10 14.09 16.90 NEBRASKA ................................................................................................................................... JOHNSON .............................. 1.08 .33 1.31 1.14 .51 NEBRASKA ................................................................................................................................... KEARNEY .............................. ........................ ........................ ........................ ........................ 2.66 NEBRASKA ................................................................................................................................... KEITH .................................... ........................ ........................ ........................ 4.64 ........................NEBRASKA ................................................................................................................................... KEYA PAHA ........................... .49 ........................ 4.06 6.90 3.02 NEBRASKA ................................................................................................................................... KIMBALL ............................... ........................ .79 .49 13.56 .60 NEBRASKA ................................................................................................................................... KNOX .................................... 1.89 1.38 1.13 1.10 2.90 NEBRASKA ................................................................................................................................... LANCASTER ........................... ........................ .06 ........................ .41 .33 NEBRASKA ................................................................................................................................... LINCOLN ............................... 1.72 1.40 .70 1.55 3.33 NEBRASKA ................................................................................................................................... LOGAN .................................. ........................ ........................ ........................ ........................ 2.03 NEBRASKA ................................................................................................................................... LOUP ..................................... 2.19 .15 ........................ ........................ ........................NEBRASKA ................................................................................................................................... MADISON .............................. ........................ ........................ .15 ........................ ........................NEBRASKA ................................................................................................................................... MCPHERSON ......................... ........................ ........................ ........................ ........................ ........................NEBRASKA ................................................................................................................................... MERRICK .............................. 3.09 3.64 4.89 8.04 6.56 NEBRASKA ................................................................................................................................... MORRILL ............................... 21.95 18.30 17.96 15.57 14.30 NEBRASKA ................................................................................................................................... NANCE .................................. .68 .10 .24 .25 .23 NEBRASKA ................................................................................................................................... NEMAHA ................................ .79 .68 .84 .83 2.84 NEBRASKA ................................................................................................................................... NUCKOLLS ............................ 2.59 2.32 6.45 6.12 11.10 NEBRASKA ................................................................................................................................... OTOE ..................................... .76 .79 .73 .82 9.64 NEBRASKA ................................................................................................................................... PAWNEE ................................ .35 2.27 .89 .88 2.25 
213 

NEBRASKA ................................................................................................................................... PERKINS ............................... ........................ ........................ .11 .04 .12 NEBRASKA ................................................................................................................................... PHELPS ................................. 1.53 2.38 3.99 6.57 8.44 NEBRASKA ................................................................................................................................... PIERCE ................................. .64 1.19 .60 1.67 .90 NEBRASKA ................................................................................................................................... PLATTE .................................. .72 .70 .89 1.02 .09 NEBRASKA ................................................................................................................................... POLK ..................................... .06 ........................ ........................ .65 3.44 NEBRASKA ................................................................................................................................... RED WILLOW ......................... 3.03 1.97 .95 1.68 2.26 NEBRASKA ................................................................................................................................... RICHARDSON ........................ .49 .54 1.79 .97 1.55 NEBRASKA ................................................................................................................................... ROCK .................................... 1.58 2.10 1.64 4.60 16.59 NEBRASKA ................................................................................................................................... SALINE .................................. .52 .52 .98 .89 1.25 NEBRASKA ................................................................................................................................... SARPY ................................... ........................ ........................ ........................ .45 .35 NEBRASKA ................................................................................................................................... SAUNDERS ............................ .28 .22 ........................ .82 .69 NEBRASKA ................................................................................................................................... SCOTTS BLUFF ...................... 16.20 18.17 16.03 16.82 15.09 NEBRASKA ................................................................................................................................... SEWARD ................................ ........................ .16 .14 ........................ 1.07 NEBRASKA ................................................................................................................................... SHERIDAN ............................. 4.40 1.73 1.26 .87 .07 NEBRASKA ................................................................................................................................... SHERMAN ............................. 3.12 1.51 1.01 .94 16.82 NEBRASKA ................................................................................................................................... SIOUX, S1/2 .......................... 1.92 .35 ........................ .32 1.39 NEBRASKA ................................................................................................................................... STANTON ............................... 2.68 .21 8.93 6.62 6.33 NEBRASKA ................................................................................................................................... THAYER ................................. .51 .50 4.62 5.42 3.46 NEBRASKA ................................................................................................................................... THOMAS ................................ ........................ 5.42 4.65 19.72 34.47 NEBRASKA ................................................................................................................................... THURSTON ............................ .28 ........................ 10.10 6.31 6.64 NEBRASKA ................................................................................................................................... VALLEY ................................. 3.59 2.79 .42 .40 .60 NEBRASKA ................................................................................................................................... WASHINGTON ........................ .03 .01 .11 .93 2.47 NEBRASKA ................................................................................................................................... WAYNE .................................. 1.65 14.61 14.73 16.56 12.93 NEBRASKA ................................................................................................................................... WEBSTER .............................. ........................ ........................ .35 .22 1.46 NEBRASKA ................................................................................................................................... WHEELER .............................. .08 ........................ ........................ ........................ .96 NEBRASKA ................................................................................................................................... YORK .................................... 5.39 3.81 3.39 3.56 7.07 NEVADA ....................................................................................................................................... CARSON CITY ....................... ........................ ........................ ........................ ........................ ........................NEVADA ....................................................................................................................................... CHURCHILL ........................... 2.13 14.53 ........................ ........................ ........................NEVADA ....................................................................................................................................... CLARK ................................... ........................ .01 .81 ........................ ........................NEVADA ....................................................................................................................................... DOUGLAS .............................. ........................ ........................ ........................ ........................ ........................NEVADA ....................................................................................................................................... ELKO ..................................... 20.36 7.29 13.63 6.27 6.41 NEVADA ....................................................................................................................................... ESMERALDA .......................... ........................ ........................ ........................ ........................ ........................NEVADA ....................................................................................................................................... EUREKA ................................ .20 24.81 17.02 12.39 11.28 NEVADA ....................................................................................................................................... HUMBOLDT ........................... 15.59 19.47 6.83 9.72 6.05 NEVADA ....................................................................................................................................... LANDER ................................ 2.06 ........................ ........................ ........................ ........................NEVADA ....................................................................................................................................... LINCOLN ............................... 24.31 ........................ ........................ ........................ 74.44 NEVADA ....................................................................................................................................... LYON ..................................... ........................ ........................ 3.55 .98 ........................NEVADA ....................................................................................................................................... MINERAL ............................... ........................ ........................ 22.34 6.29 ........................NEVADA ....................................................................................................................................... NYE,NW ................................. ........................ .53 ........................ 30.90 28.93 NEVADA ....................................................................................................................................... PERSHING ............................. .54 ........................ ........................ .33 ........................
214 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

NEVADA ....................................................................................................................................... STOREY ................................. ........................ ........................ ........................ ........................ ........................NEVADA ....................................................................................................................................... WASHOE ................................ 70.07 68.04 63.04 58.07 54.38 NEVADA ....................................................................................................................................... WHITE PINE .......................... ........................ ........................ ........................ ........................ ........................NEW HAMPSHIRE ......................................................................................................................... BELKNAP ............................... 2.68 .88 .91 1.59 2.67 NEW HAMPSHIRE ......................................................................................................................... CARROLL .............................. 2.61 ........................ ........................ 3.03 ........................NEW HAMPSHIRE ......................................................................................................................... CHESHIRE ............................. ........................ .07 ........................ .06 ........................NEW HAMPSHIRE ......................................................................................................................... COOS .................................... 4.40 6.40 6.46 8.17 7.54 NEW HAMPSHIRE ......................................................................................................................... GRAFTON .............................. ........................ 3.59 4.04 4.72 3.95 NEW HAMPSHIRE ......................................................................................................................... HILLSBOROUGH .................... .89 ........................ ........................ ........................ ........................NEW HAMPSHIRE ......................................................................................................................... MERRIMACK .......................... .29 ........................ ........................ ........................ ........................NEW HAMPSHIRE ......................................................................................................................... ROCKINGHAM ........................ .04 ........................ ........................ .02 .52 NEW HAMPSHIRE ......................................................................................................................... STRAFFORD ........................... 4.61 4.19 4.38 3.73 3.58 NEW HAMPSHIRE ......................................................................................................................... SULLIVAN .............................. ........................ .35 ........................ 4.43 1.56 NEW JERSEY ................................................................................................................................ ATLANTIC .............................. 8.36 25.38 30.29 31.23 28.26 NEW JERSEY ................................................................................................................................ BERGEN ................................ ........................ ........................ ........................ ........................ ........................NEW JERSEY ................................................................................................................................ BURLINGTON ......................... 34.19 29.72 25.86 24.93 26.37 NEW JERSEY ................................................................................................................................ CAMDEN ............................... ........................ 43.62 43.43 29.95 26.95 NEW JERSEY ................................................................................................................................ CAPE MAY ............................ ........................ 16.01 80.06 79.93 79.95 NEW JERSEY ................................................................................................................................ CUMBERLAND ....................... 37.81 35.00 40.14 38.70 42.37 NEW JERSEY ................................................................................................................................ ESSEX ................................... ........................ ........................ ........................ ........................ ........................NEW JERSEY ................................................................................................................................ GLOUCESTER ........................ 58.84 67.47 57.78 55.76 53.93 NEW JERSEY ................................................................................................................................ HUDSON ................................ ........................ ........................ ........................ ........................ ........................NEW JERSEY ................................................................................................................................ HUNTERDON ......................... 2.46 4.89 11.12 9.30 13.31 NEW JERSEY ................................................................................................................................ MERCER ............................... ........................ ........................ ........................ 100.00 ........................NEW JERSEY ................................................................................................................................ MIDDLESEX ........................... 82.88 82.86 82.68 82.66 56.49 NEW JERSEY ................................................................................................................................ MONMOUTH .......................... 56.77 75.28 74.72 74.00 59.26 NEW JERSEY ................................................................................................................................ MORRIS ................................ ........................ 1.98 ........................ ........................ 10.28 NEW JERSEY ................................................................................................................................ OCEAN .................................. ........................ 90.95 ........................ ........................ 9.43 NEW JERSEY ................................................................................................................................ PASSAIC ................................ ........................ ........................ ........................ ........................ ........................NEW JERSEY ................................................................................................................................ SALEM .................................. 48.91 49.26 53.50 46.95 49.33 NEW JERSEY ................................................................................................................................ SOMERSET ............................ ........................ .74 40.11 35.87 25.40 NEW JERSEY ................................................................................................................................ SUSSEX ................................. 3.77 1.71 ........................ ........................ ........................NEW JERSEY ................................................................................................................................ UNION ................................... ........................ ........................ ........................ ........................ ........................NEW JERSEY ................................................................................................................................ WARREN ............................... 5.11 4.41 4.24 5.28 4.12 NEW MEXICO ............................................................................................................................... BERNALILLO WEST ................ 41.39 27.29 15.81 1.20 ........................
215 

NEW MEXICO ............................................................................................................................... CATRON ................................ 7.28 5.13 6.78 3.70 3.15 NEW MEXICO ............................................................................................................................... CHAVES ................................ 31.80 26.59 21.63 18.16 17.87 NEW MEXICO ............................................................................................................................... CIBOLA ................................. 47.44 74.12 72.48 68.32 65.66 NEW MEXICO ............................................................................................................................... COLFAX ................................. ........................ 1.99 ........................ ........................ ........................NEW MEXICO ............................................................................................................................... CURRY .................................. 4.45 4.19 7.58 11.91 10.09 NEW MEXICO ............................................................................................................................... DEBACA ................................ ........................ ........................ ........................ .96 ........................NEW MEXICO ............................................................................................................................... DONA ANA ............................ 9.27 9.11 7.80 5.96 .65 NEW MEXICO ............................................................................................................................... EDDY .................................... 28.85 19.77 13.65 14.74 9.74 NEW MEXICO ............................................................................................................................... GRANT .................................. 28.41 23.42 18.45 18.04 10.15 NEW MEXICO ............................................................................................................................... GUADALUPE .......................... ........................ ........................ ........................ ........................ ........................NEW MEXICO ............................................................................................................................... HARDING, PT ........................ ........................ ........................ ........................ ........................ ........................NEW MEXICO ............................................................................................................................... HIDALGO ............................... 16.29 17.69 22.09 23.80 8.57 NEW MEXICO ............................................................................................................................... LEA ....................................... 17.67 15.88 14.62 8.52 8.12 NEW MEXICO ............................................................................................................................... LINCOLN ............................... 1.76 2.52 14.11 13.10 11.09 NEW MEXICO ............................................................................................................................... LOS ALAMOS ......................... ........................ ........................ ........................ ........................ ........................NEW MEXICO ............................................................................................................................... LUNA ..................................... 3.87 6.65 6.84 3.84 2.51 NEW MEXICO ............................................................................................................................... MCKINLEY ............................. 8.99 11.57 15.15 26.61 20.31 NEW MEXICO ............................................................................................................................... MORA .................................... ........................ .26 .17 .87 1.40 NEW MEXICO ............................................................................................................................... OTERO, PT ............................ 27.20 23.35 25.27 13.59 13.43 NEW MEXICO ............................................................................................................................... QUAY .................................... ........................ .34 2.08 2.21 1.73 NEW MEXICO ............................................................................................................................... RIO ARRIBA .......................... 9.39 17.54 15.79 12.09 10.74 NEW MEXICO ............................................................................................................................... ROOSEVELT ........................... 21.77 22.28 26.80 21.02 18.83 NEW MEXICO ............................................................................................................................... SAN JUAN ............................. 45.80 42.09 33.05 9.10 3.37 NEW MEXICO ............................................................................................................................... SAN MIGUEL ......................... .15 44.63 32.06 37.85 45.32 NEW MEXICO ............................................................................................................................... SANDOVAL ............................ 6.49 7.84 4.99 .37 .11 NEW MEXICO ............................................................................................................................... SANTA FE, N ......................... 9.56 21.99 11.72 7.26 ........................NEW MEXICO ............................................................................................................................... SIERRA ................................. 27.37 19.38 17.14 16.70 14.75 NEW MEXICO ............................................................................................................................... SOCORRO ............................. 30.24 31.48 24.60 20.72 19.54 NEW MEXICO ............................................................................................................................... TAOS ..................................... ........................ ........................ 2.75 4.02 3.15 NEW MEXICO ............................................................................................................................... TORRANCE ............................ 2.33 25.76 22.26 21.53 21.58 NEW MEXICO ............................................................................................................................... UNION ................................... 4.21 2.79 1.51 ........................ 11.38 NEW MEXICO ............................................................................................................................... VALENCIA, WEST ................... 8.20 6.63 9.57 2.27 2.06 NEW YORK ................................................................................................................................... ALBANY ................................. 1.62 2.82 8.40 ........................ ........................NEW YORK ................................................................................................................................... ALLEGANY ............................. 12.98 11.53 10.78 9.24 4.83 NEW YORK ................................................................................................................................... BRONX .................................. ........................ ........................ ........................ ........................ ........................NEW YORK ................................................................................................................................... BROOME ............................... ........................ ........................ 2.65 1.62 .03 NEW YORK ................................................................................................................................... CATTARAUGUS ...................... .89 5.00 10.69 12.42 21.44 NEW YORK ................................................................................................................................... CAYUGA ................................ 17.87 15.49 16.56 18.46 16.03 NEW YORK ................................................................................................................................... CHAUTAUQUA ........................ 5.96 9.56 7.83 8.59 8.62 NEW YORK ................................................................................................................................... CHEMUNG ............................. ........................ 1.69 6.35 ........................ ........................
216 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

NEW YORK ................................................................................................................................... CHENANGO ........................... 6.18 5.41 4.45 12.21 20.02 NEW YORK ................................................................................................................................... CLINTON ............................... 4.35 ........................ 27.49 39.16 31.95 NEW YORK ................................................................................................................................... COLUMBIA ............................ 3.49 7.00 5.12 5.88 6.96 NEW YORK ................................................................................................................................... CORTLAND ............................ 2.26 1.51 2.26 .93 1.18 NEW YORK ................................................................................................................................... DELAWARE ............................ 14.31 14.68 15.85 17.22 26.81 NEW YORK ................................................................................................................................... DUTCHESS ............................ ........................ 26.31 32.60 45.68 50.85 NEW YORK ................................................................................................................................... ERIE ...................................... 7.06 7.08 9.73 13.82 16.84 NEW YORK ................................................................................................................................... ESSEX ................................... ........................ ........................ ........................ 7.99 ........................NEW YORK ................................................................................................................................... FRANKLIN .............................. 21.37 27.43 25.49 27.46 26.41 NEW YORK ................................................................................................................................... FULTON ................................. ........................ .43 .45 1.15 .33 NEW YORK ................................................................................................................................... GENESEE .............................. 10.59 27.01 22.99 14.99 13.03 NEW YORK ................................................................................................................................... GREENE ................................ 7.40 ........................ ........................ ........................ ........................NEW YORK ................................................................................................................................... HAMILTON ............................. ........................ ........................ ........................ ........................ ........................NEW YORK ................................................................................................................................... HERKIMER ............................ 4.12 4.91 4.99 5.98 4.76 NEW YORK ................................................................................................................................... JEFFERSON ........................... 4.68 6.41 7.75 7.55 16.84 NEW YORK ................................................................................................................................... KINGS ................................... ........................ ........................ ........................ ........................ ........................NEW YORK ................................................................................................................................... LEWIS ................................... 11.05 9.29 8.62 9.91 26.21 NEW YORK ................................................................................................................................... LIVINGSTON .......................... 32.63 34.53 36.79 36.03 36.47 NEW YORK ................................................................................................................................... MADISON .............................. 10.01 11.85 12.42 10.81 7.55 NEW YORK ................................................................................................................................... MONROE ............................... 4.09 11.20 11.13 14.80 24.48 NEW YORK ................................................................................................................................... MONTGOMERY ...................... 2.28 2.93 1.41 5.95 5.01 NEW YORK ................................................................................................................................... NASSAU ................................ ........................ ........................ ........................ ........................ ........................NEW YORK ................................................................................................................................... NEW YORK ............................ ........................ ........................ ........................ ........................ ........................NEW YORK ................................................................................................................................... NIAGARA ............................... 2.08 2.50 1.83 8.02 13.21 NEW YORK ................................................................................................................................... ONEIDA ................................. 1.23 5.77 6.12 19.98 17.48 NEW YORK ................................................................................................................................... ONONDAGA ........................... 10.50 19.57 10.99 14.55 11.22 NEW YORK ................................................................................................................................... ONTARIO ............................... 12.78 14.43 19.41 24.70 26.16 NEW YORK ................................................................................................................................... ORANGE ................................ 14.63 10.60 33.45 35.43 44.92 NEW YORK ................................................................................................................................... ORLEANS .............................. 29.28 27.80 27.84 19.57 26.08 NEW YORK ................................................................................................................................... OSWEGO ............................... 44.08 29.59 24.34 22.63 21.86 NEW YORK ................................................................................................................................... OTSEGO ................................ 1.99 2.54 6.26 6.01 10.50 NEW YORK ................................................................................................................................... PUTNAM ................................ ........................ ........................ ........................ ........................ ........................NEW YORK ................................................................................................................................... QUEENS ................................ ........................ ........................ ........................ ........................ ........................NEW YORK ................................................................................................................................... RENSSELAER ........................ ........................ 5.76 5.22 15.09 10.58 NEW YORK ................................................................................................................................... RICHMOND ............................ ........................ ........................ ........................ ........................ ........................
217 

NEW YORK ................................................................................................................................... ROCKLAND ............................ ........................ ........................ ........................ ........................ ........................NEW YORK ................................................................................................................................... SARATOGA ............................ 45.25 25.64 23.63 21.92 19.44 NEW YORK ................................................................................................................................... SCHENECTADY ...................... ........................ 19.34 .51 ........................ ........................NEW YORK ................................................................................................................................... SCHOHARIE ........................... 1.84 2.36 5.47 4.83 3.95 NEW YORK ................................................................................................................................... SCHUYLER ............................ .24 ........................ 1.21 2.07 11.63 NEW YORK ................................................................................................................................... SENECA ................................ 2.07 2.68 5.46 3.99 2.41 NEW YORK ................................................................................................................................... ST. LAWRENCE ..................... 13.13 13.57 13.70 14.19 14.31 NEW YORK ................................................................................................................................... STEUBEN .............................. 5.06 8.08 6.14 23.87 26.88 NEW YORK ................................................................................................................................... SUFFOLK ............................... 1.13 ........................ ........................ ........................ 2.94 NEW YORK ................................................................................................................................... SULLIVAN .............................. 2.52 1.73 ........................ ........................ ........................NEW YORK ................................................................................................................................... TIOGA .................................... 15.93 13.11 8.66 6.97 7.63 NEW YORK ................................................................................................................................... TOMPKINS ............................. 11.80 10.05 19.50 8.86 8.20 NEW YORK ................................................................................................................................... ULSTER ................................. 33.51 40.62 43.30 37.21 37.05 NEW YORK ................................................................................................................................... WARREN ............................... ........................ ........................ ........................ ........................ ........................NEW YORK ................................................................................................................................... WASHINGTON ........................ 16.95 12.25 21.58 20.32 21.81 NEW YORK ................................................................................................................................... WAYNE .................................. 15.42 13.07 11.53 14.13 10.98 NEW YORK ................................................................................................................................... WESTCHESTER ...................... 48.51 49.68 54.19 60.25 67.02 NEW YORK ................................................................................................................................... WYOMING .............................. 5.72 6.48 6.59 6.61 19.97 NEW YORK ................................................................................................................................... YATES ................................... 10.87 9.81 8.01 7.92 8.44 NORTH CAROLINA ........................................................................................................................ ALAMANCE ............................ ........................ ........................ 1.76 2.55 ........................NORTH CAROLINA ........................................................................................................................ ALEXANDER .......................... ........................ ........................ ........................ 2.88 ........................NORTH CAROLINA ........................................................................................................................ ALLEGHANY ........................... 19.48 19.37 20.35 17.24 14.44 NORTH CAROLINA ........................................................................................................................ ANSON .................................. ........................ 4.49 2.71 18.84 15.56 NORTH CAROLINA ........................................................................................................................ ASHE ..................................... 19.84 17.74 9.33 8.39 2.97 NORTH CAROLINA ........................................................................................................................ AVERY ................................... 4.18 3.63 3.63 5.92 5.48 NORTH CAROLINA ........................................................................................................................ BEAUFORT ............................ 5.23 6.59 8.54 6.89 14.71 NORTH CAROLINA ........................................................................................................................ BERTIE .................................. .40 ........................ 3.12 5.47 12.50 NORTH CAROLINA ........................................................................................................................ BLADEN ................................ 19.96 26.55 24.50 21.61 23.95 NORTH CAROLINA ........................................................................................................................ BRUNSWICK .......................... ........................ ........................ 21.28 12.44 12.33 NORTH CAROLINA ........................................................................................................................ BUNCOMBE ........................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ BURKE .................................. ........................ 5.06 ........................ 36.56 31.82 NORTH CAROLINA ........................................................................................................................ CABARRUS ............................ ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ CALDWELL ............................ ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ CAMDEN ............................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ CARTERET ............................. ........................ ........................ ........................ ........................ 45.63 NORTH CAROLINA ........................................................................................................................ CASWELL .............................. 22.78 26.68 27.53 23.50 22.43 NORTH CAROLINA ........................................................................................................................ CATAWBA .............................. 64.17 61.04 ........................ 1.69 ........................NORTH CAROLINA ........................................................................................................................ CHATHAM .............................. 1.04 .41 .96 7.23 3.43 NORTH CAROLINA ........................................................................................................................ CHEROKEE ............................ ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ CHOWAN ............................... .33 ........................ 3.99 ........................ ........................
218 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

NORTH CAROLINA ........................................................................................................................ CLAY ..................................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ CLEVELAND ........................... 1.18 .15 2.86 ........................ .91 NORTH CAROLINA ........................................................................................................................ COLUMBUS ........................... 8.57 9.51 6.02 2.75 2.33 NORTH CAROLINA ........................................................................................................................ CRAVEN ................................ 13.86 16.78 11.51 20.12 19.10 NORTH CAROLINA ........................................................................................................................ CUMBERLAND ....................... ........................ 5.91 23.90 11.36 32.80 NORTH CAROLINA ........................................................................................................................ CURRITUCK ........................... ........................ ........................ ........................ ........................ 7.62 NORTH CAROLINA ........................................................................................................................ DARE .................................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ DAVIDSON ............................. ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ DAVIE .................................... ........................ 23.14 ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ DUPLIN ................................. 2.07 2.01 3.44 2.84 2.49 NORTH CAROLINA ........................................................................................................................ DURHAM ............................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ EDGECOMBE ......................... 7.20 8.25 10.58 10.74 15.96 NORTH CAROLINA ........................................................................................................................ FORSYTH ............................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ FRANKLIN .............................. ........................ ........................ 3.13 ........................ 12.98NORTH CAROLINA ........................................................................................................................ GASTON ................................ ........................ ........................ 99.41 100.00 100.00 NORTH CAROLINA ........................................................................................................................ GATES ................................... 4.02 7.73 6.89 6.24 7.98 NORTH CAROLINA ........................................................................................................................ GRAHAM ............................... ........................ ........................ ........................ 98.17 97.97NORTH CAROLINA ........................................................................................................................ GRANVILLE ............................ ........................ 56.27 57.08 41.42 41.78 NORTH CAROLINA ........................................................................................................................ GREENE ................................ 10.28 14.61 14.52 11.20 9.73 NORTH CAROLINA ........................................................................................................................ GUILFORD ............................. ........................ ........................ ........................ 1.08 ........................NORTH CAROLINA ........................................................................................................................ HALIFAX ................................ 30.11 26.19 24.47 38.17 43.81 NORTH CAROLINA ........................................................................................................................ HARNETT ............................... ........................ ........................ ........................ 25.76 28.24 NORTH CAROLINA ........................................................................................................................ HAYWOOD ............................. .61 ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ HENDERSON ......................... 62.67 60.55 52.17 44.97 35.67 NORTH CAROLINA ........................................................................................................................ HERTFORD ............................ 23.37 20.01 16.94 16.40 18.74 NORTH CAROLINA ........................................................................................................................ HOKE .................................... ........................ ........................ ........................ 11.56 11.63 NORTH CAROLINA ........................................................................................................................ HYDE .................................... 17.32 11.51 9.02 2.69 3.34 NORTH CAROLINA ........................................................................................................................ IREDELL ................................ ........................ ........................ ........................ .89 .14 NORTH CAROLINA ........................................................................................................................ JACKSON ............................... ........................ 1.70 ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ JOHNSTON ............................. 7.61 11.13 13.08 17.13 21.65 NORTH CAROLINA ........................................................................................................................ JONES ................................... 4.55 16.72 9.39 ........................ ........................NORTH CAROLINA ........................................................................................................................ LEE ....................................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ LENOIR ................................. 5.16 4.53 5.27 2.52 1.55 NORTH CAROLINA ........................................................................................................................ LINCOLN ............................... ........................ ........................ ........................ ........................ 18.22 NORTH CAROLINA ........................................................................................................................ MACON ................................. ........................ ........................ ........................ ........................ ........................
219 

NORTH CAROLINA ........................................................................................................................ MADISON .............................. 7.78 15.24 13.19 9.55 9.91 NORTH CAROLINA ........................................................................................................................ MARTIN ................................. 8.92 8.38 7.77 7.18 12.18 NORTH CAROLINA ........................................................................................................................ MCDOWELL ........................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ MECKLENBURG ..................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ MITCHELL ............................. ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ MONTGOMERY ...................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ MOORE ................................. ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ NASH .................................... 2.36 1.04 1.53 7.34 6.45 NORTH CAROLINA ........................................................................................................................ NEW HANOVER ..................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ NORTHAMPTON ..................... 17.11 14.57 21.63 26.68 31.55 NORTH CAROLINA ........................................................................................................................ ONSLOW ................................ 6.50 7.58 9.05 53.65 53.67 NORTH CAROLINA ........................................................................................................................ ORANGE ................................ 82.77 69.64 69.25 67.44 56.28 NORTH CAROLINA ........................................................................................................................ PAMLICO ............................... .91 32.13 6.56 11.73 11.04 NORTH CAROLINA ........................................................................................................................ PASQUOTANK ........................ .81 .68 7.21 .86 .69 NORTH CAROLINA ........................................................................................................................ PENDER ................................ 72.13 73.16 71.62 74.00 70.98 NORTH CAROLINA ........................................................................................................................ PERQUIMANS ........................ .32 .71 .97 ........................ ........................NORTH CAROLINA ........................................................................................................................ PERSON ................................ 31.78 29.28 29.14 25.31 23.54 NORTH CAROLINA ........................................................................................................................ PITT ...................................... 49.09 45.86 40.08 40.08 39.76 NORTH CAROLINA ........................................................................................................................ POLK ..................................... 8.52 ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ RANDOLPH ............................ ........................ ........................ 5.15 2.55 2.54 NORTH CAROLINA ........................................................................................................................ RICHMOND ............................ ........................ ........................ ........................ .03 ........................NORTH CAROLINA ........................................................................................................................ ROBESON .............................. 30.76 54.99 49.62 45.28 42.21 NORTH CAROLINA ........................................................................................................................ ROCKINGHAM ........................ 6.33 8.13 .75 .37 28.84 NORTH CAROLINA ........................................................................................................................ ROWAN ................................. 10.09 ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ RUTHERFORD ........................ ........................ ........................ ........................ 3.05 ........................NORTH CAROLINA ........................................................................................................................ SAMPSON .............................. 12.67 9.76 9.26 42.47 47.85 NORTH CAROLINA ........................................................................................................................ SCOTLAND ............................ ........................ ........................ 84.80 69.78 36.99 NORTH CAROLINA ........................................................................................................................ STANLY ................................. ........................ ........................ ........................ ........................ 4.37 NORTH CAROLINA ........................................................................................................................ STOKES ................................. ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ SURRY .................................. .47 ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ SWAIN ................................... ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ TRANSYLVANIA ...................... 72.66 71.39 71.38 70.37 69.91 NORTH CAROLINA ........................................................................................................................ TYRRELL ............................... 10.26 3.74 9.79 56.96 55.82 NORTH CAROLINA ........................................................................................................................ UNION ................................... 25.12 57.71 20.36 16.83 28.02 NORTH CAROLINA ........................................................................................................................ VANCE .................................. ........................ ........................ 17.09 14.02 15.30 NORTH CAROLINA ........................................................................................................................ WAKE .................................... ........................ 27.46 32.17 25.91 32.42 NORTH CAROLINA ........................................................................................................................ WARREN ............................... 22.33 29.11 23.04 24.36 53.96 NORTH CAROLINA ........................................................................................................................ WASHINGTON ........................ 14.61 17.52 6.66 3.41 7.43 NORTH CAROLINA ........................................................................................................................ WATAUGA .............................. ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ WAYNE .................................. ........................ 5.08 3.55 6.77 8.29 
220 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

NORTH CAROLINA ........................................................................................................................ WILKES ................................. 1.78 1.60 2.27 2.22 2.63 NORTH CAROLINA ........................................................................................................................ WILSON ................................. 7.63 7.36 .18 .32 1.33 NORTH CAROLINA ........................................................................................................................ YADKIN ................................. ........................ ........................ ........................ ........................ ........................NORTH CAROLINA ........................................................................................................................ YANCEY ................................ ........................ .48 1.35 ........................ 1.12 NORTH DAKOTA ........................................................................................................................... ADAMS .................................. 6.20 5.65 4.26 4.30 4.64 NORTH DAKOTA ........................................................................................................................... BARNES ................................ ........................ ........................ 3.97 2.98 2.36 NORTH DAKOTA ........................................................................................................................... BENSON ................................ 1.53 3.18 2.75 4.24 4.44 NORTH DAKOTA ........................................................................................................................... BILLINGS ............................... 4.37 .63 .14 1.75 1.29 NORTH DAKOTA ........................................................................................................................... BOTTINEAU ........................... 2.04 1.63 2.75 2.68 3.25 NORTH DAKOTA ........................................................................................................................... BOWMAN ............................... ........................ ........................ .85 .20 .58 NORTH DAKOTA ........................................................................................................................... BURKE .................................. ........................ ........................ .50 ........................ .45 NORTH DAKOTA ........................................................................................................................... BURLEIGH ............................. .31 3.06 1.93 1.51 2.14 NORTH DAKOTA ........................................................................................................................... CASS ..................................... 2.24 .86 ........................ .11 .57 NORTH DAKOTA ........................................................................................................................... CAVALIER .............................. .34 .37 .08 .08 .30 NORTH DAKOTA ........................................................................................................................... CORSON SD, PT .................... .09 ........................ ........................ .28 3.56 NORTH DAKOTA ........................................................................................................................... DICKEY ................................. ........................ ........................ ........................ 1.88 .45NORTH DAKOTA ........................................................................................................................... DIVIDE .................................. .58 .16 .53 .33 1.50 NORTH DAKOTA ........................................................................................................................... DUNN, PT .............................. 51.09 48.57 43.23 39.54 36.15 NORTH DAKOTA ........................................................................................................................... EDDY .................................... .18 5.97 4.09 2.13 3.16 NORTH DAKOTA ........................................................................................................................... EMMONS ............................... .88 1.35 1.06 1.07 3.06 NORTH DAKOTA ........................................................................................................................... FOSTER ................................. ........................ ........................ 10.74 8.71 7.48 NORTH DAKOTA ........................................................................................................................... GOLDEN VALLEY ................... 1.92 .54 1.04 .12 1.14 NORTH DAKOTA ........................................................................................................................... GRAND FORKS ...................... .37 ........................ .54 3.45 2.94 NORTH DAKOTA ........................................................................................................................... GRANT .................................. 1.86 1.00 1.04 1.74 1.59 NORTH DAKOTA ........................................................................................................................... GRIGGS ................................. ........................ ........................ 2.49 .53 2.76 NORTH DAKOTA ........................................................................................................................... HETTINGER ........................... .35 1.49 .74 1.89 3.45 NORTH DAKOTA ........................................................................................................................... KIDDER ................................. .69 3.00 4.09 1.90 4.81 NORTH DAKOTA ........................................................................................................................... LAMOURE .............................. ........................ ........................ ........................ .53 .20 NORTH DAKOTA ........................................................................................................................... LOGAN .................................. .37 1.34 .45 .56 .64 NORTH DAKOTA ........................................................................................................................... MCHENRY ............................. 1.54 1.62 2.29 2.23 1.78 NORTH DAKOTA ........................................................................................................................... MCINTOSH ............................ 1.19 .63 .49 1.01 1.72 NORTH DAKOTA ........................................................................................................................... MCKENZIE, PT ...................... 23.90 22.20 20.71 19.44 17.73 NORTH DAKOTA ........................................................................................................................... MCLEAN, PT .......................... 22.21 19.26 16.05 12.37 13.14 NORTH DAKOTA ........................................................................................................................... MERCER, PT ......................... 56.65 52.20 45.12 37.57 32.15 NORTH DAKOTA ........................................................................................................................... MORTON ............................... 2.09 1.83 1.76 1.66 2.81 
221 

NORTH DAKOTA ........................................................................................................................... MOUNTRAIL, PT .................... 41.43 42.29 42.97 39.96 35.83 NORTH DAKOTA ........................................................................................................................... NELSON ................................ ........................ ........................ ........................ ........................ .53 NORTH DAKOTA ........................................................................................................................... OLIVER .................................. 2.53 8.08 6.22 6.07 1.95 NORTH DAKOTA ........................................................................................................................... PEMBINA ............................... 5.29 6.43 5.87 6.87 6.74 NORTH DAKOTA ........................................................................................................................... PIERCE ................................. 1.47 1.11 1.22 .88 .37 NORTH DAKOTA ........................................................................................................................... RAMSEY ................................ ........................ ........................ .12 .09 4.61 NORTH DAKOTA ........................................................................................................................... RANSOM ............................... ........................ ........................ ........................ .10 .72 NORTH DAKOTA ........................................................................................................................... RENVILLE .............................. ........................ .05 .02 2.31 1.62 NORTH DAKOTA ........................................................................................................................... RICHLAND ............................. .38 ........................ ........................ 3.13 4.18 NORTH DAKOTA ........................................................................................................................... ROLETTE ............................... 3.42 1.56 6.09 3.98 21.21 NORTH DAKOTA ........................................................................................................................... SARGENT .............................. 1.55 .54 .46 .27 1.92 NORTH DAKOTA ........................................................................................................................... SHERIDAN ............................. 14.57 15.73 11.29 12.88 7.01 NORTH DAKOTA ........................................................................................................................... SIOUX ................................... 20.53 24.96 26.89 26.74 33.27 NORTH DAKOTA ........................................................................................................................... SLOPE ................................... .02 ........................ .51 ........................ .36 NORTH DAKOTA ........................................................................................................................... STARK ................................... 2.56 .59 3.82 2.52 2.73 NORTH DAKOTA ........................................................................................................................... STEELE ................................. ........................ ........................ ........................ .13 .18 NORTH DAKOTA ........................................................................................................................... STUTSMAN ............................ 1.18 2.33 7.43 3.45 2.19 NORTH DAKOTA ........................................................................................................................... TOWNER ................................ 5.25 4.72 3.34 4.17 8.69 NORTH DAKOTA ........................................................................................................................... TRAILL .................................. .56 .25 ........................ .05 4.60 NORTH DAKOTA ........................................................................................................................... WALSH .................................. 3.51 2.85 2.77 3.70 3.93 NORTH DAKOTA ........................................................................................................................... WARD .................................... 2.54 2.45 3.70 6.02 3.70 NORTH DAKOTA ........................................................................................................................... WELLS ................................... .82 .38 ........................ 5.43 4.97 NORTH DAKOTA ........................................................................................................................... WILLIAMS .............................. 5.83 5.37 8.36 8.66 9.58 OHIO ............................................................................................................................................ ADAMS .................................. .39 .96 1.58 1.39 1.92 OHIO ............................................................................................................................................ ALLEN ................................... ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ ASHLAND .............................. .99 1.59 1.91 .91 3.03 OHIO ............................................................................................................................................ ASHTABULA ........................... 14.35 8.09 6.89 9.02 2.40 OHIO ............................................................................................................................................ ATHENS ................................. ........................ ........................ 18.03 6.20 1.52 OHIO ............................................................................................................................................ AUGLAIZE .............................. ........................ 1.16 29.35 23.07 21.58 OHIO ............................................................................................................................................ BELMONT .............................. 17.86 17.73 18.38 18.85 20.79 OHIO ............................................................................................................................................ BROWN ................................. 7.74 .31 7.88 .71 .22 OHIO ............................................................................................................................................ BUTLER ................................. ........................ ........................ ........................ 19.36 17.59 OHIO ............................................................................................................................................ CARROLL .............................. 8.14 7.13 6.97 6.42 2.79 OHIO ............................................................................................................................................ CHAMPAIGN .......................... .55 .04 ........................ ........................ .97 OHIO ............................................................................................................................................ CLARK ................................... 1.14 1.06 1.08 1.24 1.35 OHIO ............................................................................................................................................ CLERMONT ............................ ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ CLINTON ............................... 1.14 .27 2.54 .82 .29 OHIO ............................................................................................................................................ COLUMBIANA ........................ .19 .04 .37 4.29 3.30 OHIO ............................................................................................................................................ COSHOCTON ......................... ........................ ........................ ........................ ........................ .85 OHIO ............................................................................................................................................ CRAWFORD ........................... ........................ ........................ .61 ........................ 41.02 
222 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

OHIO ............................................................................................................................................ CUYAHOGA ............................ ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ DARKE .................................. 5.21 4.71 10.05 17.04 15.07 OHIO ............................................................................................................................................ DEFIANCE ............................. .23 .36 ........................ ........................ ........................OHIO ............................................................................................................................................ DELAWARE ............................ 42.59 39.65 29.84 44.80 37.91 OHIO ............................................................................................................................................ ERIE ...................................... ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ FAIRFIELD ............................. 1.49 5.05 5.23 7.54 11.16 OHIO ............................................................................................................................................ FAYETTE ................................ 9.43 9.13 7.55 8.14 4.14 OHIO ............................................................................................................................................ FRANKLIN .............................. ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ FULTON ................................. ........................ ........................ ........................ 2.20 1.56 OHIO ............................................................................................................................................ GALLIA .................................. 47.94 72.71 21.20 42.88 39.03 OHIO ............................................................................................................................................ GEAUGA ................................ ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ GREENE ................................ 7.58 5.53 8.02 15.31 12.55 OHIO ............................................................................................................................................ GUERNSEY ............................ .84 ........................ ........................ ........................ .06 OHIO ............................................................................................................................................ HAMILTON ............................. ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ HANCOCK .............................. ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ HARDIN ................................. ........................ ........................ ........................ ........................ .56 OHIO ............................................................................................................................................ HARRISON ............................. ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ HENRY .................................. ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ HIGHLAND ............................. ........................ ........................ .11 .08 .08 OHIO ............................................................................................................................................ HOCKING ............................... ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ HOLMES ................................ ........................ ........................ ........................ ........................ 3.60 OHIO ............................................................................................................................................ HURON .................................. ........................ 4.54 4.48 13.43 10.01 OHIO ............................................................................................................................................ JACKSON ............................... ........................ ........................ 40.48 32.43 32.67 OHIO ............................................................................................................................................ JEFFERSON ........................... ........................ ........................ 11.33 5.17 ........................OHIO ............................................................................................................................................ KNOX .................................... 6.23 4.63 6.57 4.78 5.46 OHIO ............................................................................................................................................ LAKE ..................................... ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ LAWRENCE ............................ .30 ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ LICKING ................................ ........................ ........................ 1.21 7.19 4.60 OHIO ............................................................................................................................................ LOGAN .................................. 1.11 56.54 42.11 38.42 38.54 OHIO ............................................................................................................................................ LORAIN ................................. .35 1.79 1.27 12.47 11.49 OHIO ............................................................................................................................................ LUCAS ................................... ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ MADISON .............................. ........................ ........................ ........................ .15 .09 OHIO ............................................................................................................................................ MAHONING ............................ ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ MARION ................................ ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ MEDINA ................................. 19.43 .75 .67 .58 .60 
223 

OHIO ............................................................................................................................................ MEIGS ................................... 19.79 19.80 20.15 8.77 8.13 OHIO ............................................................................................................................................ MERCER ............................... 26.96 33.16 50.46 42.32 40.86 OHIO ............................................................................................................................................ MIAMI ................................... ........................ 2.72 2.62 1.69 3.99 OHIO ............................................................................................................................................ MONROE ............................... ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ MONTGOMERY ...................... ........................ ........................ 19.11 13.76 9.16 OHIO ............................................................................................................................................ MORGAN ............................... 18.49 11.58 8.28 3.25 2.36 OHIO ............................................................................................................................................ MORROW .............................. .29 .74 .92 1.78 .44 OHIO ............................................................................................................................................ MUSKINGUM ......................... 9.47 ........................ ........................ .07 .45 OHIO ............................................................................................................................................ NOBLE .................................. ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ OTTAWA ................................ .88 .96 .59 .86 .36 OHIO ............................................................................................................................................ PAULDING ............................. ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ PERRY .................................. ........................ ........................ 5.19 8.97 1.58 OHIO ............................................................................................................................................ PICKAWAY ............................. 27.21 25.00 23.90 23.09 35.35 OHIO ............................................................................................................................................ PIKE ...................................... ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ PORTAGE .............................. ........................ ........................ 3.31 3.07 .33 OHIO ............................................................................................................................................ PREBLE ................................. 1.28 .96 1.56 11.30 11.93 OHIO ............................................................................................................................................ PUTNAM ................................ ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ RICHLAND ............................. .37 ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ ROSS .................................... ........................ ........................ ........................ 9.91 9.36 OHIO ............................................................................................................................................ SANDUSKY ............................ ........................ ........................ .95 19.59 18.18 OHIO ............................................................................................................................................ SCIOTO ................................. ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ SENECA ................................ .72 .07 .08 .08 .07 OHIO ............................................................................................................................................ SHELBY ................................. ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ STARK ................................... ........................ ........................ ........................ 7.61 13.89 OHIO ............................................................................................................................................ SUMMIT ................................ ........................ ........................ 4.67 ........................ 17.39 OHIO ............................................................................................................................................ TRUMBULL ............................ 2.05 .88 1.62 2.21 1.95 OHIO ............................................................................................................................................ TUSCARAWAS ........................ .93 ........................ 12.65 28.39 46.16 OHIO ............................................................................................................................................ UNION ................................... ........................ ........................ ........................ ........................ 58.35 OHIO ............................................................................................................................................ VAN WERT ............................ ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ VINTON ................................. ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ WARREN ............................... ........................ ........................ ........................ ........................ ........................OHIO ............................................................................................................................................ WASHINGTON ........................ ........................ 35.66 13.06 8.06 47.60 OHIO ............................................................................................................................................ WAYNE .................................. 1.38 ........................ .63 ........................ 5.52 OHIO ............................................................................................................................................ WILLIAMS .............................. ........................ ........................ ........................ ........................ 2.93 OHIO ............................................................................................................................................ WOOD ................................... 5.22 5.93 8.55 ........................ ........................OHIO ............................................................................................................................................ WYANDOT .............................. ........................ ........................ ........................ ........................ ........................OKLAHOMA .................................................................................................................................. ADAIR ................................... 1.13 6.57 4.90 2.79 2.13 OKLAHOMA .................................................................................................................................. ALFALFA ................................ ........................ .43 .23 8.50 6.62 OKLAHOMA .................................................................................................................................. ATOKA ................................... 1.99 10.84 11.11 10.21 64.02 OKLAHOMA .................................................................................................................................. BEAVER ................................ 1.13 2.00 3.92 8.36 8.10 
224 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

OKLAHOMA .................................................................................................................................. BECKHAM ............................. 5.89 7.31 6.57 4.99 5.81 OKLAHOMA .................................................................................................................................. BLAINE .................................. 7.43 6.46 6.62 6.12 9.42 OKLAHOMA .................................................................................................................................. BRYAN .................................. 4.01 5.96 9.22 10.34 15.21 OKLAHOMA .................................................................................................................................. CADDO .................................. 4.97 4.71 6.70 14.94 13.66 OKLAHOMA .................................................................................................................................. CANADIAN ............................. 4.81 .50 1.64 1.86 6.11 OKLAHOMA .................................................................................................................................. CARTER ................................ 1.13 .13 2.89 1.33 .57 OKLAHOMA .................................................................................................................................. CHEROKEE ............................ 1.08 1.24 1.60 2.92 2.01 OKLAHOMA .................................................................................................................................. CHOCTAW ............................. 16.45 11.87 11.11 26.33 26.90 OKLAHOMA .................................................................................................................................. CIMARRON ............................ 6.54 4.55 3.88 4.46 3.40 OKLAHOMA .................................................................................................................................. CLEVELAND ........................... 33.81 25.05 16.25 5.86 4.76 OKLAHOMA .................................................................................................................................. COAL ..................................... 1.64 .84 2.15 17.12 16.06 OKLAHOMA .................................................................................................................................. COMANCHE ........................... 2.42 .75 1.10 7.56 9.06 OKLAHOMA .................................................................................................................................. COTTON ................................ 5.65 1.77 3.15 25.87 28.04 OKLAHOMA .................................................................................................................................. CRAIG ................................... .19 15.06 14.74 12.33 12.71 OKLAHOMA .................................................................................................................................. CREEK .................................. 1.14 .48 ........................ .91 ........................OKLAHOMA .................................................................................................................................. CUSTER ................................ 9.77 4.80 5.12 4.64 2.63 OKLAHOMA .................................................................................................................................. DELAWARE ............................ 7.25 5.69 5.23 13.23 12.47 OKLAHOMA .................................................................................................................................. DEWEY .................................. 8.78 7.93 7.25 5.85 5.34 OKLAHOMA .................................................................................................................................. ELLIS .................................... 8.99 7.63 3.82 4.01 2.89 OKLAHOMA .................................................................................................................................. GARFIELD .............................. 1.49 2.98 2.25 .91 2.50 OKLAHOMA .................................................................................................................................. GARVIN ................................. 7.44 2.77 5.40 4.86 7.83 OKLAHOMA .................................................................................................................................. GRADY .................................. 2.07 2.60 3.09 3.25 2.36 OKLAHOMA .................................................................................................................................. GRANT .................................. 2.76 3.31 8.90 10.30 9.06 OKLAHOMA .................................................................................................................................. GREER .................................. 5.65 7.94 11.10 5.49 6.13 OKLAHOMA .................................................................................................................................. HARMON ............................... 4.74 4.07 4.68 4.89 3.83 OKLAHOMA .................................................................................................................................. HARPER ................................ 14.81 10.95 7.11 3.38 1.93 OKLAHOMA .................................................................................................................................. HASKELL ............................... .42 .27 1.40 2.09 2.28 OKLAHOMA .................................................................................................................................. HUGHES ................................ 15.62 20.21 23.58 33.96 31.70 OKLAHOMA .................................................................................................................................. JACKSON ............................... 5.49 4.27 5.13 4.07 3.96 OKLAHOMA .................................................................................................................................. JEFFERSON ........................... 4.59 13.05 16.28 17.55 11.63 OKLAHOMA .................................................................................................................................. JOHNSTON ............................. 5.80 5.68 5.97 7.89 10.48 OKLAHOMA .................................................................................................................................. KAY ....................................... 1.49 1.40 4.28 2.80 3.65 OKLAHOMA .................................................................................................................................. KINGFISHER .......................... 4.35 3.97 4.14 7.16 6.71 OKLAHOMA .................................................................................................................................. KIOWA ................................... 7.72 5.06 5.14 5.52 11.07 OKLAHOMA .................................................................................................................................. LATIMER ............................... .91 .12 18.81 20.40 14.81 
225 

OKLAHOMA .................................................................................................................................. LE FLORE .............................. 6.82 6.23 4.50 6.12 7.86 OKLAHOMA .................................................................................................................................. LINCOLN ............................... 12.61 10.43 7.66 5.37 7.46 OKLAHOMA .................................................................................................................................. LOGAN .................................. 2.74 7.83 6.43 6.51 8.46 OKLAHOMA .................................................................................................................................. LOVE ..................................... 2.44 .75 3.13 4.51 3.95 OKLAHOMA .................................................................................................................................. MAJOR .................................. 1.85 1.91 1.26 2.00 5.73 OKLAHOMA .................................................................................................................................. MARSHALL ............................ 5.97 5.85 6.54 7.35 59.81 OKLAHOMA .................................................................................................................................. MAYES .................................. 8.37 8.78 10.76 10.65 9.74 OKLAHOMA .................................................................................................................................. MCCLAIN ............................... 7.90 5.02 19.72 20.89 28.12 OKLAHOMA .................................................................................................................................. MCCURTAIN .......................... 3.61 3.48 1.60 4.97 20.27 OKLAHOMA .................................................................................................................................. MCINTOSH ............................ 3.62 4.54 3.83 4.43 3.44 OKLAHOMA .................................................................................................................................. MURRAY ............................... 3.72 3.52 15.78 5.31 12.68 OKLAHOMA .................................................................................................................................. MUSKOGEE ........................... 12.03 11.28 12.42 11.88 18.79 OKLAHOMA .................................................................................................................................. NOBLE .................................. .75 .66 1.37 1.11 .82 OKLAHOMA .................................................................................................................................. NOWATA ................................ .77 .48 5.67 2.74 1.60 OKLAHOMA .................................................................................................................................. OKFUSKEE ............................. 4.65 14.32 14.52 28.27 30.72 OKLAHOMA .................................................................................................................................. OKLAHOMA ............................ 28.45 26.88 21.71 20.80 49.90 OKLAHOMA .................................................................................................................................. OKMULGEE ............................ 9.62 8.78 6.66 7.10 5.09 OKLAHOMA .................................................................................................................................. OSAGE .................................. 4.60 8.00 9.55 11.18 12.26 OKLAHOMA .................................................................................................................................. OTTAWA ................................ 4.86 5.81 11.63 11.32 10.88 OKLAHOMA .................................................................................................................................. PAWNEE ................................ 22.19 23.28 10.45 11.16 8.38 OKLAHOMA .................................................................................................................................. PAYNE ................................... 13.94 20.18 22.05 29.37 23.08 OKLAHOMA .................................................................................................................................. PITTSBURG ........................... 3.63 6.85 6.90 5.91 6.92 OKLAHOMA .................................................................................................................................. PONTOTOC ............................ 2.47 4.68 7.90 16.31 16.78 OKLAHOMA .................................................................................................................................. POTTAWATOMIE ..................... .50 9.57 16.40 17.94 17.07 OKLAHOMA .................................................................................................................................. PUSHMATAHA ........................ 29.48 31.94 33.57 30.18 34.34 OKLAHOMA .................................................................................................................................. ROGER MILLS ....................... ........................ 1.65 2.45 1.52 2.33 OKLAHOMA .................................................................................................................................. ROGERS ................................ 10.27 11.75 15.84 14.89 16.82 OKLAHOMA .................................................................................................................................. SEMINOLE ............................. .72 1.03 1.66 5.07 2.79 OKLAHOMA .................................................................................................................................. SEQUOYAH ............................ 5.45 5.97 5.35 6.40 7.16 OKLAHOMA .................................................................................................................................. STEPHENS ............................. .50 .70 4.35 3.91 4.62 OKLAHOMA .................................................................................................................................. TEXAS ................................... 8.91 15.36 11.51 9.29 14.75 OKLAHOMA .................................................................................................................................. TILLMAN ................................ 3.04 3.61 2.02 2.41 3.61 OKLAHOMA .................................................................................................................................. TULSA ................................... 8.46 12.40 12.70 13.81 8.01 OKLAHOMA .................................................................................................................................. WAGONER ............................. 15.27 11.78 10.46 16.72 14.33 OKLAHOMA .................................................................................................................................. WASHINGTON ........................ .25 1.18 .15 ........................ ........................OKLAHOMA .................................................................................................................................. WASHITA ............................... 12.23 3.45 2.78 3.31 10.97 OKLAHOMA .................................................................................................................................. WOODS ................................. .18 3.11 3.68 4.80 8.51 OKLAHOMA .................................................................................................................................. WOODWARD .......................... ........................ ........................ ........................ ........................ 42.50 OREGON ...................................................................................................................................... BAKER .................................. 5.41 4.17 3.92 1.90 3.65 OREGON ...................................................................................................................................... BENTON ................................ 4.47 6.76 3.26 1.73 2.73 
226 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

OREGON ...................................................................................................................................... CLACKAMAS .......................... 7.67 9.05 13.39 4.19 3.33 OREGON ...................................................................................................................................... CLATSOP ............................... 56.61 52.21 36.87 29.98 24.91 OREGON ...................................................................................................................................... COLUMBIA ............................ 9.91 7.41 7.01 10.21 8.79 OREGON ...................................................................................................................................... COOS .................................... 2.28 2.01 2.32 5.64 7.90 OREGON ...................................................................................................................................... CROOK .................................. 11.86 4.57 ........................ ........................ 4.29 OREGON ...................................................................................................................................... CURRY .................................. 4.41 1.49 1.09 2.32 2.60 OREGON ...................................................................................................................................... DESCHUTES .......................... 6.46 ........................ 6.79 5.73 .77 OREGON ...................................................................................................................................... DOUGLAS .............................. .79 1.15 .85 4.13 3.02 OREGON ...................................................................................................................................... GILLIAM ................................ 7.47 9.53 3.70 8.74 9.11 OREGON ...................................................................................................................................... GRANT .................................. .05 .47 .13 ........................ 3.69 OREGON ...................................................................................................................................... HARNEY ................................ 4.07 6.11 7.56 4.59 4.29 OREGON ...................................................................................................................................... HOOD RIVER ......................... .44 .43 9.39 23.38 20.31 OREGON ...................................................................................................................................... JACKSON ............................... 3.03 4.40 3.02 19.39 15.32 OREGON ...................................................................................................................................... JEFFERSON ........................... ........................ ........................ 11.12 10.12 8.78 OREGON ...................................................................................................................................... JOSEPHINE ............................ ........................ ........................ ........................ ........................ ........................OREGON ...................................................................................................................................... KLAMATH .............................. .07 .50 10.22 9.30 6.65 OREGON ...................................................................................................................................... LAKE ..................................... .45 1.31 3.79 4.00 .41 OREGON ...................................................................................................................................... LANE ..................................... 1.88 2.63 1.96 11.74 10.68 OREGON ...................................................................................................................................... LINCOLN ............................... ........................ ........................ ........................ ........................ ........................OREGON ...................................................................................................................................... LINN ...................................... 4.72 5.63 5.52 3.24 3.90 OREGON ...................................................................................................................................... MALHEUR .............................. 5.69 4.62 4.13 4.48 5.31 OREGON ...................................................................................................................................... MARION ................................ 5.83 3.12 2.58 2.89 3.95 OREGON ...................................................................................................................................... MORROW .............................. ........................ 2.66 ........................ ........................ ........................OREGON ...................................................................................................................................... MULTNOMAH ......................... ........................ ........................ ........................ ........................ ........................OREGON ...................................................................................................................................... POLK ..................................... 1.61 .80 .87 3.00 1.51 OREGON ...................................................................................................................................... SHERMAN ............................. 4.28 1.75 21.84 16.45 14.88 OREGON ...................................................................................................................................... TILLAMOOK ........................... ........................ ........................ ........................ .47 .50 OREGON ...................................................................................................................................... UMATILLA .............................. 1.76 2.25 3.25 3.37 4.49 OREGON ...................................................................................................................................... UNION ................................... 16.18 13.93 2.71 2.07 2.81 OREGON ...................................................................................................................................... WALLOWA .............................. .41 3.03 1.75 1.97 3.77 OREGON ...................................................................................................................................... WASCO .................................. ........................ .11 ........................ .76 .05 OREGON ...................................................................................................................................... WASHINGTON ........................ .59 .75 .71 .74 .77 OREGON ...................................................................................................................................... WHEELER .............................. ........................ ........................ ........................ ........................ ........................OREGON ...................................................................................................................................... YAMHILL ............................... 26.59 33.67 22.97 17.20 12.51 PENNSYLVANIA ............................................................................................................................ ADAMS .................................. .55 1.64 3.07 19.39 2.53 
227 

PENNSYLVANIA ............................................................................................................................ ALLEGHENY ........................... ........................ ........................ ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ ARMSTRONG ......................... 17.64 23.54 38.84 6.95 4.60 PENNSYLVANIA ............................................................................................................................ BEAVER ................................ ........................ ........................ 8.33 ........................ ........................PENNSYLVANIA ............................................................................................................................ BEDFORD .............................. .19 .20 .21 .18 .34 PENNSYLVANIA ............................................................................................................................ BERKS .................................. 7.34 10.54 11.05 15.82 12.61 PENNSYLVANIA ............................................................................................................................ BLAIR .................................... .67 ........................ ........................ 1.07 .07 PENNSYLVANIA ............................................................................................................................ BRADFORD ............................ .25 .34 .55 1.44 1.96 PENNSYLVANIA ............................................................................................................................ BUCKS .................................. ........................ ........................ 10.04 15.11 8.29 PENNSYLVANIA ............................................................................................................................ BUTLER ................................. .08 4.33 3.21 1.17 1.53 PENNSYLVANIA ............................................................................................................................ CAMBRIA .............................. 2.50 3.09 2.86 5.97 7.93 PENNSYLVANIA ............................................................................................................................ CAMERON ............................. ........................ ........................ ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ CARBON ................................ ........................ ........................ ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ CENTRE ................................ .13 .15 .07 .43 .91 PENNSYLVANIA ............................................................................................................................ CHESTER .............................. 11.27 8.46 9.56 11.30 11.22 PENNSYLVANIA ............................................................................................................................ CLARION ............................... 4.67 6.15 5.71 11.55 7.92 PENNSYLVANIA ............................................................................................................................ CLEARFIELD .......................... 3.90 3.06 5.58 1.64 2.25 PENNSYLVANIA ............................................................................................................................ CLINTON ............................... .27 ........................ 1.40 .54 .79 PENNSYLVANIA ............................................................................................................................ COLUMBIA ............................ 13.89 19.78 11.96 11.39 13.72 PENNSYLVANIA ............................................................................................................................ CRAWFORD ........................... 4.22 2.61 .88 .25 4.41 PENNSYLVANIA ............................................................................................................................ CUMBERLAND ....................... 4.40 2.29 4.25 2.78 2.14 PENNSYLVANIA ............................................................................................................................ DAUPHIN ............................... ........................ .42 ........................ .43 2.69 PENNSYLVANIA ............................................................................................................................ DELAWARE ............................ ........................ ........................ ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ ELK ....................................... 92.80 90.74 89.88 88.51 86.62 PENNSYLVANIA ............................................................................................................................ ERIE ...................................... .29 .19 1.99 2.36 2.26 PENNSYLVANIA ............................................................................................................................ FAYETTE ................................ 1.19 ........................ .08 ........................ 3.68 PENNSYLVANIA ............................................................................................................................ FOREST ................................. ........................ ........................ ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ FRANKLIN .............................. .70 .75 21.02 11.97 14.58 PENNSYLVANIA ............................................................................................................................ FULTON ................................. .33 .38 .31 5.98 6.04 PENNSYLVANIA ............................................................................................................................ GREENE ................................ ........................ ........................ 7.06 5.18 4.26 PENNSYLVANIA ............................................................................................................................ HUNTINGDON ........................ .53 .31 .87 .91 1.69 PENNSYLVANIA ............................................................................................................................ INDIANA ................................ ........................ 3.41 12.39 10.16 12.30 PENNSYLVANIA ............................................................................................................................ JEFFERSON ........................... ........................ ........................ 1.02 1.47 ........................PENNSYLVANIA ............................................................................................................................ JUNIATA ................................ 2.23 5.33 1.67 1.35 .55 PENNSYLVANIA ............................................................................................................................ LACKAWANNA ........................ ........................ ........................ ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ LANCASTER ........................... 1.43 .95 3.16 3.45 2.80 PENNSYLVANIA ............................................................................................................................ LAWRENCE ............................ 13.75 9.96 10.89 10.10 14.42 PENNSYLVANIA ............................................................................................................................ LEBANON .............................. 15.25 13.01 5.75 3.65 9.15 PENNSYLVANIA ............................................................................................................................ LEHIGH ................................. 1.15 ........................ ........................ .01 ........................PENNSYLVANIA ............................................................................................................................ LUZERNE .............................. ........................ 10.85 5.90 21.20 17.29 PENNSYLVANIA ............................................................................................................................ LYCOMING ............................ 2.83 7.15 1.13 .48 2.27 
228 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

PENNSYLVANIA ............................................................................................................................ MCKEAN ................................ ........................ ........................ ........................ ........................ .03 PENNSYLVANIA ............................................................................................................................ MERCER ............................... 6.65 6.40 5.15 8.10 3.01 PENNSYLVANIA ............................................................................................................................ MIFFLIN ................................. 1.66 .67 5.64 4.95 4.54 PENNSYLVANIA ............................................................................................................................ MONROE ............................... ........................ ........................ ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ MONTGOMERY ...................... 28.67 30.01 32.24 28.30 33.57 PENNSYLVANIA ............................................................................................................................ MONTOUR ............................. ........................ ........................ 2.48 .80 1.58 PENNSYLVANIA ............................................................................................................................ NORTHAMPTON ..................... 72.55 73.70 84.03 48.17 42.22 PENNSYLVANIA ............................................................................................................................ NORTHUMBERLAND .............. 3.97 3.17 1.05 .58 4.80 PENNSYLVANIA ............................................................................................................................ PERRY .................................. 5.23 4.53 1.19 ........................ .58 PENNSYLVANIA ............................................................................................................................ PHILADELPHIA ....................... ........................ ........................ ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ PIKE ...................................... ........................ ........................ ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ POTTER ................................. .04 ........................ ........................ 1.23 1.99 PENNSYLVANIA ............................................................................................................................ SCHUYLKILL .......................... 2.57 1.56 1.27 2.86 .17 PENNSYLVANIA ............................................................................................................................ SNYDER ................................ 2.63 2.85 4.95 4.72 3.47 PENNSYLVANIA ............................................................................................................................ SOMERSET ............................ 1.78 .55 .09 ........................ .02 PENNSYLVANIA ............................................................................................................................ SULLIVAN .............................. ........................ 2.66 ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ SUSQUEHANNA ..................... ........................ .29 .31 9.23 7.06 PENNSYLVANIA ............................................................................................................................ TIOGA .................................... .21 .66 6.07 5.25 7.24 PENNSYLVANIA ............................................................................................................................ UNION ................................... ........................ 2.00 1.52 1.53 1.99 PENNSYLVANIA ............................................................................................................................ VENANGO .............................. 5.49 3.86 2.47 .40 ........................PENNSYLVANIA ............................................................................................................................ WARREN ............................... .01 ........................ ........................ ........................ 2.89 PENNSYLVANIA ............................................................................................................................ WASHINGTON ........................ 8.13 5.13 8.51 1.92 .99 PENNSYLVANIA ............................................................................................................................ WAYNE .................................. 1.34 34.98 19.69 15.77 19.82 PENNSYLVANIA ............................................................................................................................ WESTMORELAND ................... 17.19 19.44 15.13 11.07 8.10 PENNSYLVANIA ............................................................................................................................ WYOMING .............................. ........................ ........................ ........................ ........................ ........................PENNSYLVANIA ............................................................................................................................ YORK .................................... .06 ........................ 4.83 4.33 16.28 PUERTO RICO .............................................................................................................................. ADJUNTAS ............................. 27.19 25.23 23.03 20.81 18.03 PUERTO RICO .............................................................................................................................. AGUADILLA ............................ 82.23 80.72 75.99 66.63 60.99 PUERTO RICO .............................................................................................................................. BARRANQUITAS ..................... 16.12 13.82 15.33 15.35 14.34 PUERTO RICO .............................................................................................................................. BAYAMON ............................. 67.93 62.64 60.00 57.92 59.70 PUERTO RICO .............................................................................................................................. CAGUAS ................................ 30.39 26.63 20.94 15.71 14.91 PUERTO RICO .............................................................................................................................. CAMUY .................................. 45.93 37.67 31.24 24.49 23.60 PUERTO RICO .............................................................................................................................. CIALES .................................. 48.26 45.99 38.05 32.76 24.59 PUERTO RICO .............................................................................................................................. COAMO ................................. 28.66 24.99 21.65 17.19 12.28 PUERTO RICO .............................................................................................................................. COROZAL .............................. 22.12 17.24 14.77 13.37 17.01 
229 

PUERTO RICO .............................................................................................................................. FAJARDO ............................... 47.25 50.10 44.53 39.49 36.05 PUERTO RICO .............................................................................................................................. GUAYAMA .............................. 48.71 48.91 46.65 44.69 43.21 PUERTO RICO .............................................................................................................................. HUMACAO ............................. 28.15 23.76 22.62 22.91 20.16 PUERTO RICO .............................................................................................................................. JAYUYA ................................. 7.08 8.25 7.47 7.61 9.90 PUERTO RICO .............................................................................................................................. JUANA DIAZ .......................... 20.75 18.93 21.95 27.88 26.87 PUERTO RICO .............................................................................................................................. LARES ................................... 25.14 23.69 21.38 20.04 17.21 PUERTO RICO .............................................................................................................................. MAYAGUEZ ............................ 13.88 12.57 12.07 12.03 12.05 PUERTO RICO .............................................................................................................................. MOROVIS .............................. 43.02 39.79 38.43 31.53 25.85 PUERTO RICO .............................................................................................................................. RIO GRANDE ......................... 22.78 20.71 15.63 12.24 9.76 PUERTO RICO .............................................................................................................................. SAN GERMAN ........................ 41.89 37.19 34.89 33.26 31.61 PUERTO RICO .............................................................................................................................. SAN LORENZO ...................... 19.95 26.07 17.89 11.34 9.17 PUERTO RICO .............................................................................................................................. SAN SEBASTIAN .................... 24.51 22.49 21.44 21.47 24.55 PUERTO RICO .............................................................................................................................. UTUADO ................................ 15.45 13.16 11.66 10.28 10.85 PUERTO RICO .............................................................................................................................. YAUCO .................................. 35.83 31.87 26.73 22.77 17.73 RHODE ISLAND ............................................................................................................................ BRISTOL ................................ 38.13 2.96 ........................ 11.20 ........................RHODE ISLAND ............................................................................................................................ KENT ..................................... 34.74 29.11 25.94 22.42 19.75 RHODE ISLAND ............................................................................................................................ NEWPORT .............................. 30.40 25.20 22.76 23.11 24.62 RHODE ISLAND ............................................................................................................................ PROVIDENCE ......................... 7.70 5.64 4.20 2.26 8.40 RHODE ISLAND ............................................................................................................................ WASHINGTON ........................ 1.67 5.20 1.58 1.97 8.34 SOUTH CAROLINA ........................................................................................................................ ABBEVILLE ............................ ........................ 1.82 1.76 1.41 ........................SOUTH CAROLINA ........................................................................................................................ AIKEN .................................... ........................ ........................ 6.75 9.81 4.90 SOUTH CAROLINA ........................................................................................................................ ALLENDALE ........................... ........................ ........................ 1.66 1.75 4.21 SOUTH CAROLINA ........................................................................................................................ ANDERSON ............................ 10.74 33.49 20.30 1.41 1.21 SOUTH CAROLINA ........................................................................................................................ BAMBERG ............................. ........................ .72 ........................ .46 1.79 SOUTH CAROLINA ........................................................................................................................ BARNWELL ............................ 47.59 52.40 48.94 49.41 48.54 SOUTH CAROLINA ........................................................................................................................ BEAUFORT ............................ 58.85 98.22 98.17 98.16 98.10 SOUTH CAROLINA ........................................................................................................................ BERKELEY ............................. ........................ ........................ 10.70 5.70 4.56 SOUTH CAROLINA ........................................................................................................................ CALHOUN .............................. 24.53 20.48 16.97 13.62 14.31 SOUTH CAROLINA ........................................................................................................................ CHARLESTON ........................ 21.55 28.16 15.76 19.03 14.25 SOUTH CAROLINA ........................................................................................................................ CHEROKEE ............................ 5.61 ........................ 4.64 ........................ ........................SOUTH CAROLINA ........................................................................................................................ CHESTER .............................. ........................ ........................ 3.47 ........................ 11.34 SOUTH CAROLINA ........................................................................................................................ CHESTERFIELD ...................... .32 ........................ .68 .72 1.43 SOUTH CAROLINA ........................................................................................................................ CLARENDON .......................... 4.76 19.57 16.33 14.60 12.91 SOUTH CAROLINA ........................................................................................................................ COLLETON ............................. 21.81 19.87 17.73 17.72 14.46 SOUTH CAROLINA ........................................................................................................................ DARLINGTON ......................... 4.23 4.60 3.60 3.02 3.83 SOUTH CAROLINA ........................................................................................................................ DILLON .................................. 1.69 1.16 1.43 1.38 1.15 SOUTH CAROLINA ........................................................................................................................ DORCHESTER ........................ .94 1.08 16.02 9.73 9.48 SOUTH CAROLINA ........................................................................................................................ EDGEFIELD ............................ ........................ 72.07 67.44 71.54 73.57 SOUTH CAROLINA ........................................................................................................................ FAIRFIELD ............................. ........................ ........................ ........................ ........................ ........................SOUTH CAROLINA ........................................................................................................................ FLORENCE ............................ 21.28 20.73 28.95 27.39 25.67 
230 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

SOUTH CAROLINA ........................................................................................................................ GEORGETOWN ....................... 5.65 ........................ 3.54 3.07 6.09 SOUTH CAROLINA ........................................................................................................................ GREENVILLE .......................... ........................ ........................ 2.03 ........................ ........................SOUTH CAROLINA ........................................................................................................................ GREENWOOD ......................... 14.47 11.76 10.16 9.46 5.07 SOUTH CAROLINA ........................................................................................................................ HAMPTON .............................. ........................ ........................ 14.95 55.76 66.83 SOUTH CAROLINA ........................................................................................................................ HORRY .................................. ........................ .13 .18 .09 1.21 SOUTH CAROLINA ........................................................................................................................ JASPER ................................. 64.42 80.66 79.83 79.36 74.86 SOUTH CAROLINA ........................................................................................................................ KERSHAW .............................. ........................ ........................ ........................ ........................ ........................SOUTH CAROLINA ........................................................................................................................ LANCASTER ........................... ........................ ........................ ........................ ........................ ........................SOUTH CAROLINA ........................................................................................................................ LAURENS .............................. ........................ 11.08 19.07 10.73 13.37 SOUTH CAROLINA ........................................................................................................................ LEE ....................................... 1.13 1.55 9.39 7.89 6.58 SOUTH CAROLINA ........................................................................................................................ LEXINGTON ........................... 1.80 1.93 3.36 1.26 4.09 SOUTH CAROLINA ........................................................................................................................ MARION ................................ 16.65 16.55 24.16 21.06 14.25 SOUTH CAROLINA ........................................................................................................................ MARLBORO ........................... 5.35 5.23 4.60 2.99 9.00 SOUTH CAROLINA ........................................................................................................................ MCCORMICK ......................... ........................ ........................ ........................ 12.75 ........................SOUTH CAROLINA ........................................................................................................................ NEWBERRY ........................... 1.10 .60 6.56 3.21 1.97 SOUTH CAROLINA ........................................................................................................................ OCONEE ................................ 8.39 12.57 23.55 45.06 43.43 SOUTH CAROLINA ........................................................................................................................ ORANGEBURG ....................... 5.13 8.43 7.06 4.91 4.25 SOUTH CAROLINA ........................................................................................................................ PICKENS ............................... ........................ ........................ ........................ .14 ........................SOUTH CAROLINA ........................................................................................................................ RICHLAND ............................. ........................ 10.35 ........................ 1.79 18.54 SOUTH CAROLINA ........................................................................................................................ SALUDA ................................. 1.80 1.23 2.51 1.92 3.18 SOUTH CAROLINA ........................................................................................................................ SPARTANBURG ...................... 23.15 20.69 5.13 3.22 1.90 SOUTH CAROLINA ........................................................................................................................ SUMTER ................................ 7.83 6.16 4.10 4.56 6.65 SOUTH CAROLINA ........................................................................................................................ UNION ................................... ........................ ........................ ........................ ........................ ........................SOUTH CAROLINA ........................................................................................................................ WILLIAMSBURG ..................... 15.95 17.11 19.87 17.91 15.60 SOUTH CAROLINA ........................................................................................................................ YORK .................................... .54 .45 ........................ ........................ ........................SOUTH DAKOTA ........................................................................................................................... AURORA ................................ 3.05 2.37 1.81 1.60 1.24 SOUTH DAKOTA ........................................................................................................................... BEADLE ................................. .56 .80 .87 7.14 13.03 SOUTH DAKOTA ........................................................................................................................... BENNETT ............................... .39 .53 .49 .06 .43 SOUTH DAKOTA ........................................................................................................................... BON HOMME ......................... 2.20 1.59 3.03 .86 .18 SOUTH DAKOTA ........................................................................................................................... BROOKINGS .......................... .27 .66 .19 .34 .17 SOUTH DAKOTA ........................................................................................................................... BROWN ................................. .07 .08 .07 .07 .24 SOUTH DAKOTA ........................................................................................................................... BRULE .................................. ........................ ........................ .56 .01 .68 SOUTH DAKOTA ........................................................................................................................... BUFFALO ............................... ........................ ........................ .11 .46 .08 SOUTH DAKOTA ........................................................................................................................... BUTTE ................................... ........................ .03 ........................ .06 1.74 SOUTH DAKOTA ........................................................................................................................... CAMPBELL ............................ .13 .13 .09 .08 8.74 
231 

SOUTH DAKOTA ........................................................................................................................... CHARLES MIX ....................... 2.46 2.71 2.68 2.48 2.82 SOUTH DAKOTA ........................................................................................................................... CLARK ................................... ........................ .02 .01 .63 2.48 SOUTH DAKOTA ........................................................................................................................... CLAY ..................................... .12 .14 .12 ........................ .74 SOUTH DAKOTA ........................................................................................................................... CODINGTON .......................... 1.24 1.63 1.59 .51 4.25 SOUTH DAKOTA ........................................................................................................................... CUSTER ................................ .36 ........................ ........................ ........................ ........................SOUTH DAKOTA ........................................................................................................................... DAVISON ............................... 18.27 15.31 26.96 23.40 19.72 SOUTH DAKOTA ........................................................................................................................... DAY ....................................... 1.08 .33 6.58 2.52 .90 SOUTH DAKOTA ........................................................................................................................... DEUEL ................................... 1.91 .31 .24 .65 .20 SOUTH DAKOTA ........................................................................................................................... DEWEY .................................. 5.45 6.77 4.99 4.76 4.12 SOUTH DAKOTA ........................................................................................................................... DOUGLAS .............................. .05 .38 .09 .01 ........................SOUTH DAKOTA ........................................................................................................................... EDMUNDS ............................. .17 ........................ .02 1.37 1.40 SOUTH DAKOTA ........................................................................................................................... FALL RIVER ........................... .24 ........................ ........................ ........................ .39 SOUTH DAKOTA ........................................................................................................................... FAULK ................................... .04 .06 ........................ .06 .03 SOUTH DAKOTA ........................................................................................................................... GRANT .................................. .42 .44 .11 ........................ .93 SOUTH DAKOTA ........................................................................................................................... GREGORY .............................. .82 .86 .78 .72 3.29 SOUTH DAKOTA ........................................................................................................................... HAAKON ................................ .67 .47 .25 1.06 .30 SOUTH DAKOTA ........................................................................................................................... HAMLIN ................................. .93 .94 .79 .64 1.82 SOUTH DAKOTA ........................................................................................................................... HAND .................................... .18 .50 .23 1.05 1.78 SOUTH DAKOTA ........................................................................................................................... HANSON ................................ ........................ ........................ .10 ........................ .47 SOUTH DAKOTA ........................................................................................................................... HARDING ............................... .36 ........................ ........................ ........................ 3.49 SOUTH DAKOTA ........................................................................................................................... HUGHES ................................ ........................ .03 ........................ ........................ .01 SOUTH DAKOTA ........................................................................................................................... HUTCHINSON ........................ ........................ .02 ........................ ........................ ........................SOUTH DAKOTA ........................................................................................................................... HYDE .................................... .26 ........................ .24 .39 1.31 SOUTH DAKOTA ........................................................................................................................... JACKSON ............................... 1.31 1.21 1.05 .57 .70 SOUTH DAKOTA ........................................................................................................................... JERAULD ............................... .05 .06 .04 .32 .10 SOUTH DAKOTA ........................................................................................................................... JONES ................................... .61 .71 .60 .70 ........................SOUTH DAKOTA ........................................................................................................................... KINGSBURY ........................... .82 .34 .13 .03 1.87 SOUTH DAKOTA ........................................................................................................................... LAKE ..................................... ........................ .47 .40 .40 .28 SOUTH DAKOTA ........................................................................................................................... LAWRENCE ............................ ........................ ........................ ........................ ........................ ........................SOUTH DAKOTA ........................................................................................................................... LINCOLN ............................... ........................ ........................ ........................ ........................ ........................SOUTH DAKOTA ........................................................................................................................... LYMAN .................................. .77 ........................ ........................ ........................ 4.41SOUTH DAKOTA ........................................................................................................................... MARSHALL ............................ .11 1.39 1.02 .83 1.25 SOUTH DAKOTA ........................................................................................................................... MCCOOK ............................... ........................ 15.58 3.88 2.72 1.72 SOUTH DAKOTA ........................................................................................................................... MCPHERSON ......................... ........................ ........................ .93 1.07 .71 SOUTH DAKOTA ........................................................................................................................... MEADE .................................. ........................ ........................ ........................ ........................ ........................SOUTH DAKOTA ........................................................................................................................... MELLETTE,W ......................... ........................ 1.62 1.70 1.69 ........................SOUTH DAKOTA ........................................................................................................................... MINER ................................... ........................ .18 .26 6.22 3.97 SOUTH DAKOTA ........................................................................................................................... MINNEHAHA .......................... ........................ ........................ ........................ .54 .37 SOUTH DAKOTA ........................................................................................................................... MOODY ................................. .04 ........................ ........................ .22 ........................SOUTH DAKOTA ........................................................................................................................... PENNINGTON ......................... ........................ ........................ ........................ .09 ........................
232 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

SOUTH DAKOTA ........................................................................................................................... PERKINS ............................... .27 .15 .22 .66 1.17 SOUTH DAKOTA ........................................................................................................................... POTTER ................................. 1.01 .90 .68 .51 .16 SOUTH DAKOTA ........................................................................................................................... ROBERTS .............................. .18 ........................ ........................ .31 1.03 SOUTH DAKOTA ........................................................................................................................... SANBORN .............................. ........................ ........................ .71 ........................ ........................SOUTH DAKOTA ........................................................................................................................... SHANNON, PT WEST ............. ........................ ........................ ........................ .10 .10 SOUTH DAKOTA ........................................................................................................................... SPINK .................................... 2.83 .73 .71 4.47 4.03 SOUTH DAKOTA ........................................................................................................................... STANLEY ............................... .21 ........................ .43 ........................ ........................SOUTH DAKOTA ........................................................................................................................... SULLY ................................... .59 ........................ ........................ ........................ 39.81 SOUTH DAKOTA ........................................................................................................................... TODD .................................... ........................ .94 .82 .77 .68 SOUTH DAKOTA ........................................................................................................................... TRIPP .................................... 2.05 2.30 2.73 4.82 3.46 SOUTH DAKOTA ........................................................................................................................... TURNER ................................ .03 ........................ .47 ........................ .12 SOUTH DAKOTA ........................................................................................................................... UNION ................................... .57 1.24 1.73 .21 ........................SOUTH DAKOTA ........................................................................................................................... WALWORTH ........................... 16.12 13.62 10.14 10.01 13.28 SOUTH DAKOTA ........................................................................................................................... YANKTON .............................. .08 .14 .08 2.42 1.76 SOUTH DAKOTA ........................................................................................................................... ZIEBACH ............................... ........................ ........................ ........................ ........................ 19.65 TENNESSEE ................................................................................................................................. ANDERSON ............................ ........................ ........................ ........................ ........................ ........................TENNESSEE ................................................................................................................................. BEDFORD .............................. 5.06 .73 .68 .67 6.97 TENNESSEE ................................................................................................................................. BENTON ................................ ........................ ........................ 3.55 .87 ........................TENNESSEE ................................................................................................................................. BLEDSOE .............................. 12.10 10.76 9.02 6.96 7.20 TENNESSEE ................................................................................................................................. BLOUNT ................................ ........................ ........................ 8.55 9.96 1.30 TENNESSEE ................................................................................................................................. BRADLEY .............................. 13.65 9.96 8.70 14.16 10.29 TENNESSEE ................................................................................................................................. CAMPBELL ............................ ........................ ........................ ........................ 5.04 6.10 TENNESSEE ................................................................................................................................. CANNON ................................ 5.00 1.80 .85 ........................ ........................TENNESSEE ................................................................................................................................. CARROLL .............................. .07 4.31 6.99 4.39 20.45 TENNESSEE ................................................................................................................................. CARTER ................................ 43.56 ........................ ........................ ........................ ........................TENNESSEE ................................................................................................................................. CHEATHAM ............................ 21.19 15.92 34.26 25.99 43.80 TENNESSEE ................................................................................................................................. CHESTER .............................. 3.75 2.44 1.55 .80 .66 TENNESSEE ................................................................................................................................. CLAIBORNE ........................... 1.99 18.28 22.10 21.90 20.40 TENNESSEE ................................................................................................................................. CLAY ..................................... ........................ ........................ .26 1.64 .95 TENNESSEE ................................................................................................................................. COCKE .................................. ........................ 7.44 3.37 .10 7.00 TENNESSEE ................................................................................................................................. COFFEE ................................. 6.24 4.79 3.99 5.43 3.62 TENNESSEE ................................................................................................................................. CROCKETT ............................ 6.59 6.12 5.36 4.75 4.94 TENNESSEE ................................................................................................................................. CUMBERLAND ....................... 8.91 14.43 4.67 6.02 1.75 TENNESSEE ................................................................................................................................. DAVIDSON ............................. ........................ ........................ 100.00 ........................ ........................TENNESSEE ................................................................................................................................. DECATUR .............................. 1.86 1.92 4.39 4.62 3.46 
233 

TENNESSEE ................................................................................................................................. DEKALB ................................. 1.95 11.01 9.42 7.66 6.99 TENNESSEE ................................................................................................................................. DICKSON ............................... 5.27 4.66 7.66 12.14 3.62 TENNESSEE ................................................................................................................................. DYER .................................... 1.31 5.56 6.76 6.07 4.76 TENNESSEE ................................................................................................................................. FAYETTE ................................ 2.21 2.92 3.90 4.10 6.11 TENNESSEE ................................................................................................................................. FENTRESS ............................. 20.51 20.06 22.24 14.34 9.48 TENNESSEE ................................................................................................................................. FRANKLIN .............................. 8.10 6.41 5.50 3.80 3.53 TENNESSEE ................................................................................................................................. GIBSON ................................. .59 .86 .01 .01 ........................TENNESSEE ................................................................................................................................. GILES .................................... 7.57 5.06 6.41 9.43 3.34 TENNESSEE ................................................................................................................................. GRAINGER ............................. 1.35 ........................ 6.52 4.16 1.37 TENNESSEE ................................................................................................................................. GREENE ................................ 10.25 15.03 24.69 24.69 20.52 TENNESSEE ................................................................................................................................. GRUNDY ................................ 4.94 4.11 3.37 2.54 9.59 TENNESSEE ................................................................................................................................. HAMBLEN .............................. 7.39 ........................ ........................ ........................ 34.92 TENNESSEE ................................................................................................................................. HAMILTON ............................. 57.11 49.55 21.85 6.52 39.20 TENNESSEE ................................................................................................................................. HANCOCK .............................. ........................ 13.40 13.37 10.33 10.71 TENNESSEE ................................................................................................................................. HARDEMAN ........................... 1.91 .01 .58 2.71 3.23 TENNESSEE ................................................................................................................................. HARDIN ................................. ........................ ........................ ........................ .42 2.24 TENNESSEE ................................................................................................................................. HAWKINS ............................... 9.81 .04 .13 .05 .09 TENNESSEE ................................................................................................................................. HAYWOOD ............................. 5.40 5.82 11.03 15.19 11.73 TENNESSEE ................................................................................................................................. HENDERSON ......................... 10.27 11.06 5.05 1.80 7.87 TENNESSEE ................................................................................................................................. HENRY .................................. 4.90 6.00 10.17 5.47 11.26 TENNESSEE ................................................................................................................................. HICKMAN .............................. 2.95 ........................ 6.71 3.30 .12 TENNESSEE ................................................................................................................................. HOUSTON .............................. .24 ........................ .55 .49 ........................TENNESSEE ................................................................................................................................. HUMPHREYS ......................... 9.19 6.83 .87 2.08 1.71 TENNESSEE ................................................................................................................................. JACKSON ............................... 7.82 7.66 .23 .19 5.83 TENNESSEE ................................................................................................................................. JEFFERSON ........................... 3.68 3.36 2.57 6.12 7.16 TENNESSEE ................................................................................................................................. JOHNSON .............................. ........................ 1.88 ........................ .03 .64 TENNESSEE ................................................................................................................................. KNOX .................................... 15.79 13.89 .31 .30 .46 TENNESSEE ................................................................................................................................. LAKE ..................................... ........................ ........................ 3.34 3.17 2.81 TENNESSEE ................................................................................................................................. LAUDERDALE ........................ 8.65 6.41 4.88 7.17 9.67 TENNESSEE ................................................................................................................................. LAWRENCE ............................ 5.58 6.65 2.59 2.40 5.08 TENNESSEE ................................................................................................................................. LEWIS ................................... ........................ .12 .08 .04 .04 TENNESSEE ................................................................................................................................. LINCOLN ............................... 1.73 8.36 5.78 4.01 2.74 TENNESSEE ................................................................................................................................. LOUDON ................................ ........................ .25 14.68 9.47 5.75 TENNESSEE ................................................................................................................................. MACON ................................. ........................ .60 .80 .53 .59 TENNESSEE ................................................................................................................................. MADISON .............................. 7.28 10.27 8.02 5.08 4.70 TENNESSEE ................................................................................................................................. MARION ................................ 3.21 1.29 1.57 1.04 4.58 TENNESSEE ................................................................................................................................. MARSHALL ............................ 20.32 18.48 14.78 12.91 5.67 TENNESSEE ................................................................................................................................. MAURY .................................. 6.95 7.40 9.09 6.41 4.45 TENNESSEE ................................................................................................................................. MCMINN ................................ 26.67 22.99 7.09 5.28 20.76 TENNESSEE ................................................................................................................................. MCNAIRY .............................. .53 6.19 4.04 2.88 3.08 
234 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

TENNESSEE ................................................................................................................................. MEIGS ................................... ........................ ........................ ........................ .59 2.73 TENNESSEE ................................................................................................................................. MONROE ............................... 4.93 1.61 1.00 4.50 11.18 TENNESSEE ................................................................................................................................. MONTGOMERY ...................... 3.51 4.18 5.76 15.52 12.88 TENNESSEE ................................................................................................................................. MOORE ................................. ........................ ........................ ........................ 1.85 ........................TENNESSEE ................................................................................................................................. MORGAN ............................... 1.60 18.03 9.97 6.59 2.35 TENNESSEE ................................................................................................................................. OBION ................................... .37 .36 ........................ .32 .23 TENNESSEE ................................................................................................................................. OVERTON .............................. 13.91 12.13 9.58 8.26 8.29 TENNESSEE ................................................................................................................................. PERRY .................................. ........................ ........................ ........................ ........................ ........................TENNESSEE ................................................................................................................................. PICKETT ................................ 1.31 8.64 1.28 .21 ........................TENNESSEE ................................................................................................................................. POLK ..................................... 4.01 2.33 .82 ........................ ........................TENNESSEE ................................................................................................................................. PUTNAM ................................ ........................ 2.81 65.22 64.18 61.32 TENNESSEE ................................................................................................................................. RHEA .................................... 1.26 1.23 2.96 1.89 ........................TENNESSEE ................................................................................................................................. ROANE .................................. 8.55 6.06 5.82 6.27 3.18 TENNESSEE ................................................................................................................................. ROBERTSON .......................... 6.41 8.13 8.74 8.28 4.83 TENNESSEE ................................................................................................................................. RUTHERFORD ........................ .41 .21 .65 2.51 9.70 TENNESSEE ................................................................................................................................. SCOTT ................................... ........................ ........................ ........................ 1.92 2.24 TENNESSEE ................................................................................................................................. SEQUATCHIE ......................... ........................ ........................ ........................ 17.16 16.69 TENNESSEE ................................................................................................................................. SEVIER .................................. ........................ ........................ ........................ 3.36 ........................TENNESSEE ................................................................................................................................. SHELBY ................................. 4.12 3.89 4.40 3.85 7.47 TENNESSEE ................................................................................................................................. SMITH ................................... 2.05 ........................ 2.35 2.35 1.71 TENNESSEE ................................................................................................................................. STEWART .............................. 2.73 1.94 2.44 2.01 2.59 TENNESSEE ................................................................................................................................. SULLIVAN .............................. 32.40 25.75 22.98 18.37 14.99 TENNESSEE ................................................................................................................................. SUMNER ............................... 7.75 4.99 2.44 1.44 1.45 TENNESSEE ................................................................................................................................. TIPTON .................................. ........................ 3.97 2.31 3.84 5.89 TENNESSEE ................................................................................................................................. TROUSDALE .......................... ........................ ........................ ........................ ........................ ........................TENNESSEE ................................................................................................................................. UNICOI .................................. ........................ ........................ ........................ ........................ ........................TENNESSEE ................................................................................................................................. UNION ................................... ........................ ........................ 2.64 .36 1.06 TENNESSEE ................................................................................................................................. VAN BUREN .......................... 2.62 2.44 1.12 2.10 72.06 TENNESSEE ................................................................................................................................. WARREN ............................... 4.65 3.93 4.51 2.52 7.05 TENNESSEE ................................................................................................................................. WASHINGTON ........................ 4.75 4.00 1.82 .68 .55 TENNESSEE ................................................................................................................................. WAYNE .................................. .09 1.02 1.21 .06 2.06 TENNESSEE ................................................................................................................................. WEAKLEY .............................. 2.74 2.13 .87 2.00 3.07 TENNESSEE ................................................................................................................................. WHITE ................................... .90 2.66 3.79 1.49 1.43 TENNESSEE ................................................................................................................................. WILLIAMSON ......................... 2.53 3.00 3.89 1.99 1.26 TENNESSEE ................................................................................................................................. WILSON ................................. ........................ .09 3.44 1.95 2.16 
235 

TEXAS .......................................................................................................................................... ANDERSON ............................ 40.46 42.48 38.24 39.01 22.33 TEXAS .......................................................................................................................................... ANDREWS ............................. ........................ ........................ 64.50 77.41 65.46 TEXAS .......................................................................................................................................... ANGELINA ............................. 22.56 4.85 5.59 3.50 76.24 TEXAS .......................................................................................................................................... ARANSAS .............................. 100.00 100.00 100.00 100.00 100.00 TEXAS .......................................................................................................................................... ARCHER ................................ 3.26 3.60 6.07 1.76 7.13 TEXAS .......................................................................................................................................... ARMSTRONG ......................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... ATASCOSA ............................. .45 .37 38.04 31.00 35.68 TEXAS .......................................................................................................................................... AUSTIN .................................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... BAILEY .................................. 7.69 13.47 13.84 24.04 26.00 TEXAS .......................................................................................................................................... BANDERA .............................. ........................ ........................ 96.81 74.62 70.47 TEXAS .......................................................................................................................................... BASTROP .............................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... BAYLOR ................................ 10.15 ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... BEE ....................................... 22.76 31.12 38.52 41.03 36.51 TEXAS .......................................................................................................................................... BELL ..................................... 37.60 10.68 59.72 55.38 43.71 TEXAS .......................................................................................................................................... BEXAR .................................. ........................ 7.37 9.55 26.53 13.06 TEXAS .......................................................................................................................................... BLANCO ................................ ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... BORDEN ................................ .01 1.13 3.52 2.47 2.00 TEXAS .......................................................................................................................................... BOSQUE ................................ ........................ 1.26 ........................ ........................ 27.83 TEXAS .......................................................................................................................................... BOWIE ................................... 1.65 2.63 4.12 2.20 2.03 TEXAS .......................................................................................................................................... BRAZORIA ............................. 42.03 67.46 33.71 55.82 60.22 TEXAS .......................................................................................................................................... BRAZOS ................................ 73.25 81.70 99.55 97.54 95.36 TEXAS .......................................................................................................................................... BREWSTER ............................ ........................ ........................ ........................ 39.23 17.21 TEXAS .......................................................................................................................................... BRISCOE ............................... ........................ 1.02 .11 ........................ 7.39 TEXAS .......................................................................................................................................... BROOKS ................................ 17.07 16.28 41.66 59.75 50.39 TEXAS .......................................................................................................................................... BROWN ................................. ........................ 22.29 21.34 18.59 27.51 TEXAS .......................................................................................................................................... BURLESON ............................ ........................ .54 ........................ 5.49 ........................TEXAS .......................................................................................................................................... BURNET ................................ ........................ ........................ ........................ 99.99 100.00 TEXAS .......................................................................................................................................... CALDWELL ............................ ........................ 33.10 25.34 52.02 48.78 TEXAS .......................................................................................................................................... CALHOUN .............................. 31.39 33.33 31.55 32.77 30.14 TEXAS .......................................................................................................................................... CALLAHAN ............................. 2.98 2.92 .24 4.36 3.33 TEXAS .......................................................................................................................................... CAMERON ............................. 38.59 49.93 56.50 65.93 63.10 TEXAS .......................................................................................................................................... CAMP .................................... ........................ ........................ 17.40 10.58 12.05 TEXAS .......................................................................................................................................... CARSON ................................ ........................ ........................ 27.86 38.54 23.64 TEXAS .......................................................................................................................................... CASS ..................................... .67 .14 .15 ........................ .20 TEXAS .......................................................................................................................................... CASTRO ................................ 10.91 31.06 44.72 39.96 42.84 TEXAS .......................................................................................................................................... CHAMBERS ........................... 64.40 58.70 60.40 89.81 81.48 TEXAS .......................................................................................................................................... CHEROKEE ............................ 3.99 28.21 25.54 32.76 37.21 TEXAS .......................................................................................................................................... CHILDRESS ........................... 24.31 20.08 16.16 14.79 16.51 TEXAS .......................................................................................................................................... CLAY ..................................... 2.25 1.07 4.10 7.18 8.80 TEXAS .......................................................................................................................................... COCHRAN ............................. 19.75 37.43 34.17 33.93 29.05 
236 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

TEXAS .......................................................................................................................................... COKE .................................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... COLEMAN .............................. 80.53 74.72 74.34 62.35 60.90 TEXAS .......................................................................................................................................... COLLIN .................................. 4.76 4.65 .80 .65 3.99 TEXAS .......................................................................................................................................... COLLINGSWORTH .................. 22.57 16.82 12.46 10.21 6.33 TEXAS .......................................................................................................................................... COLORADO ............................ ........................ ........................ ........................ ........................ 16.94 TEXAS .......................................................................................................................................... COMAL .................................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... COMANCHE ........................... 52.33 63.18 62.11 56.87 49.95 TEXAS .......................................................................................................................................... CONCHO ............................... ........................ ........................ ........................ 25.81 43.42 TEXAS .......................................................................................................................................... COOKE .................................. ........................ ........................ ........................ ........................ 41.59 TEXAS .......................................................................................................................................... CORYELL ............................... 10.88 59.99 57.20 66.72 59.84 TEXAS .......................................................................................................................................... COTTLE ................................. 35.29 33.76 33.56 33.61 31.43 TEXAS .......................................................................................................................................... CRANE .................................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... CROCKETT ............................ ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... CROSBY ................................ 13.41 20.71 21.81 21.16 20.42 TEXAS .......................................................................................................................................... CULBERSON .......................... ........................ ........................ ........................ ........................ 62.15 TEXAS .......................................................................................................................................... DALLAM ................................ 3.14 2.45 8.04 6.51 3.28 TEXAS .......................................................................................................................................... DALLAS ................................. ........................ 4.35 ........................ 17.46 15.63 TEXAS .......................................................................................................................................... DAWSON ............................... 14.72 27.05 36.64 47.28 51.79 TEXAS .......................................................................................................................................... DEAF SMITH .......................... ........................ 3.71 7.91 13.09 28.31 TEXAS .......................................................................................................................................... DELTA ................................... 6.18 4.06 2.39 5.49 5.33 TEXAS .......................................................................................................................................... DENTON ................................ ........................ ........................ 71.01 68.13 49.36 TEXAS .......................................................................................................................................... DEWITT ................................. ........................ ........................ 4.00 24.69 30.21 TEXAS .......................................................................................................................................... DICKENS ............................... 34.01 33.91 35.10 37.23 50.97 TEXAS .......................................................................................................................................... DIMMIT ................................. 95.24 94.05 65.45 61.16 64.74 TEXAS .......................................................................................................................................... DONLEY ................................ ........................ 3.44 5.20 5.20 13.78 TEXAS .......................................................................................................................................... DUVAL ................................... 17.71 21.60 24.99 32.58 19.98 TEXAS .......................................................................................................................................... EASTLAND ............................. 38.53 37.27 31.22 32.52 24.37 TEXAS .......................................................................................................................................... ECTOR .................................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... EDWARDS ............................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... EL PASO ............................... 36.27 45.16 46.78 46.96 45.39 TEXAS .......................................................................................................................................... ELLIS .................................... 7.27 26.14 47.05 42.37 39.77 TEXAS .......................................................................................................................................... ERATH ................................... 40.03 48.82 44.12 39.49 37.00 TEXAS .......................................................................................................................................... FALLS .................................... 24.72 26.44 36.14 50.05 61.25 TEXAS .......................................................................................................................................... FANNIN ................................. 7.11 9.77 13.98 31.68 32.18 TEXAS .......................................................................................................................................... FAYETTE ................................ ........................ ........................ ........................ 65.69 34.85 
237 

TEXAS .......................................................................................................................................... FISHER .................................. 1.12 3.74 4.58 12.90 13.70 TEXAS .......................................................................................................................................... FLOYD ................................... 9.43 7.04 11.87 16.39 15.79 TEXAS .......................................................................................................................................... FOARD .................................. 30.72 34.26 43.43 48.08 48.51 TEXAS .......................................................................................................................................... FORT BEND ........................... ........................ 2.30 3.93 ........................ ........................TEXAS .......................................................................................................................................... FRANKLIN .............................. 2.57 1.17 2.24 1.24 5.75 TEXAS .......................................................................................................................................... FREESTONE ........................... 10.55 11.60 17.96 33.73 40.06 TEXAS .......................................................................................................................................... FRIO ...................................... 66.56 70.09 63.32 66.32 64.85 TEXAS .......................................................................................................................................... GAINES ................................. 1.33 2.05 5.16 13.75 15.07 TEXAS .......................................................................................................................................... GALVESTON ........................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... GARZA .................................. .51 ........................ .14 3.22 .29 TEXAS .......................................................................................................................................... GILLESPIE ............................. ........................ ........................ ........................ 1.08 10.03 TEXAS .......................................................................................................................................... GLASSCOCK .......................... 18.32 15.40 13.81 11.48 13.26 TEXAS .......................................................................................................................................... GOLIAD ................................. ........................ ........................ 64.24 80.19 47.58 TEXAS .......................................................................................................................................... GONZALES ............................ .05 3.86 11.91 18.30 30.41 TEXAS .......................................................................................................................................... GRAY .................................... ........................ 3.10 ........................ ........................ .73 TEXAS .......................................................................................................................................... GRAYSON .............................. ........................ 44.36 35.21 38.81 27.93 TEXAS .......................................................................................................................................... GREGG .................................. 28.04 21.67 3.63 2.22 2.39 TEXAS .......................................................................................................................................... GRIMES ................................. 5.37 ........................ ........................ .03 2.17 TEXAS .......................................................................................................................................... GUADALUPE .......................... .30 .94 3.01 3.37 2.06 TEXAS .......................................................................................................................................... HALE ..................................... 2.15 14.31 16.18 23.58 24.31 TEXAS .......................................................................................................................................... HALL ..................................... 2.46 6.51 4.80 7.22 5.31 TEXAS .......................................................................................................................................... HAMILTON ............................. ........................ 23.36 16.12 21.51 40.02 TEXAS .......................................................................................................................................... HANSFORD ............................ ........................ ........................ 21.23 13.93 4.41 TEXAS .......................................................................................................................................... HARDEMAN ........................... 14.68 20.18 20.63 18.11 14.03 TEXAS .......................................................................................................................................... HARDIN ................................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... HARRIS ................................. ........................ 14.79 14.78 11.52 10.82 TEXAS .......................................................................................................................................... HARRISON ............................. 28.32 16.28 10.68 2.17 25.18 TEXAS .......................................................................................................................................... HARTLEY ............................... ........................ 12.51 12.60 6.02 4.97 TEXAS .......................................................................................................................................... HASKELL ............................... 13.34 9.29 24.13 34.22 32.38 TEXAS .......................................................................................................................................... HAYS ..................................... 34.03 39.83 35.54 31.99 28.04 TEXAS .......................................................................................................................................... HEMPHILL ............................. ........................ ........................ .57 4.09 ........................TEXAS .......................................................................................................................................... HENDERSON ......................... 39.34 33.15 30.24 29.68 24.58 TEXAS .......................................................................................................................................... HIDALGO ............................... 34.44 49.30 59.09 57.00 53.27 TEXAS .......................................................................................................................................... HILL ...................................... 1.75 6.26 13.55 18.84 17.31 TEXAS .......................................................................................................................................... HOCKLEY .............................. 15.47 29.09 37.91 35.76 34.53 TEXAS .......................................................................................................................................... HOOD .................................... ........................ 31.54 34.90 81.74 81.56 TEXAS .......................................................................................................................................... HOPKINS ............................... .21 4.28 4.18 12.89 13.61 TEXAS .......................................................................................................................................... HOUSTON .............................. 65.09 52.43 63.44 64.72 61.69 TEXAS .......................................................................................................................................... HOWARD ............................... 21.34 28.71 29.59 25.88 29.17 TEXAS .......................................................................................................................................... HUDSPETH ............................ 16.27 45.67 38.02 37.10 38.82 
238 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

TEXAS .......................................................................................................................................... HUNT .................................... .82 1.61 .72 .52 ........................TEXAS .......................................................................................................................................... HUTCHINSON ........................ ........................ 2.06 ........................ 21.37 ........................TEXAS .......................................................................................................................................... IRION .................................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... JACK ..................................... ........................ ........................ ........................ ........................ 97.01 TEXAS .......................................................................................................................................... JACKSON ............................... 17.78 21.02 23.58 28.14 34.50 TEXAS .......................................................................................................................................... JASPER ................................. .40 11.89 78.13 78.14 69.37 TEXAS .......................................................................................................................................... JEFF DAVIS ........................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... JEFFERSON ........................... 27.30 81.72 76.04 69.32 78.38 TEXAS .......................................................................................................................................... JIM HOGG ............................. 95.59 91.55 90.22 84.79 62.29 TEXAS .......................................................................................................................................... JIM WELLS ............................ 14.30 24.02 30.25 24.66 22.56 TEXAS .......................................................................................................................................... JOHNSON .............................. 2.71 25.30 22.05 25.60 23.21 TEXAS .......................................................................................................................................... JONES ................................... 14.62 14.26 20.66 22.03 21.84 TEXAS .......................................................................................................................................... KARNES ................................ 7.28 22.04 18.88 19.44 27.45 TEXAS .......................................................................................................................................... KAUFMAN .............................. 21.96 30.57 30.83 47.37 44.00 TEXAS .......................................................................................................................................... KENDALL ............................... ........................ ........................ ........................ 44.34 44.17 TEXAS .......................................................................................................................................... KENEDY ................................ ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... KENT ..................................... 13.72 10.23 14.80 37.78 17.36 TEXAS .......................................................................................................................................... KERR .................................... ........................ 23.72 66.30 100.00 100.00 TEXAS .......................................................................................................................................... KIMBLE ................................. ........................ 1.54 2.77 .84 1.69 TEXAS .......................................................................................................................................... KING ..................................... 8.43 6.46 ........................ ........................ ........................TEXAS .......................................................................................................................................... KINNEY ................................. 4.58 ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... KLEBERG .............................. 47.29 61.82 55.74 56.88 53.05 TEXAS .......................................................................................................................................... KNOX .................................... .48 10.41 11.13 8.10 14.53 TEXAS .......................................................................................................................................... LA SALLE .............................. ........................ ........................ ........................ 34.39 36.12 TEXAS .......................................................................................................................................... LAMAR .................................. .92 2.78 3.07 8.36 10.36 TEXAS .......................................................................................................................................... LAMB .................................... 12.88 41.98 46.54 55.04 60.54 TEXAS .......................................................................................................................................... LAMPASAS ............................ ........................ 44.95 38.58 34.71 29.70 TEXAS .......................................................................................................................................... LAVACA ................................. ........................ ........................ 40.22 35.26 92.16 TEXAS .......................................................................................................................................... LEE ....................................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... LEON ..................................... ........................ 33.17 41.82 52.02 64.37 TEXAS .......................................................................................................................................... LIBERTY ................................ ........................ 19.39 13.84 11.20 47.24 TEXAS .......................................................................................................................................... LIMESTONE ........................... 32.70 36.71 41.62 35.58 39.12 TEXAS .......................................................................................................................................... LIPSCOMB ............................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... LIVE OAK .............................. 20.64 16.69 24.17 21.51 21.03 TEXAS .......................................................................................................................................... LLANO ................................... ........................ ........................ ........................ ........................ ........................
239 

TEXAS .......................................................................................................................................... LOVING ................................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... LUBBOCK .............................. .43 5.98 7.80 14.60 13.72 TEXAS .......................................................................................................................................... LYNN ..................................... .38 1.21 5.47 9.51 8.84 TEXAS .......................................................................................................................................... MADISON .............................. 76.09 ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... MARION ................................ 22.95 27.47 21.73 18.47 16.61 TEXAS .......................................................................................................................................... MARTIN ................................. 6.67 20.48 26.28 29.88 47.24 TEXAS .......................................................................................................................................... MASON .................................. 44.31 40.97 32.75 40.35 34.68 TEXAS .......................................................................................................................................... MATAGORDA ......................... 17.97 23.69 16.90 17.67 17.64 TEXAS .......................................................................................................................................... MAVERICK ............................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... MCCULLOCH ......................... ........................ 8.23 4.73 10.30 17.20 TEXAS .......................................................................................................................................... MCLENNAN ........................... ........................ 4.92 3.30 11.19 11.21 TEXAS .......................................................................................................................................... MCMULLEN ........................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... MEDINA ................................. ........................ ........................ 19.75 51.30 41.71 TEXAS .......................................................................................................................................... MENARD ............................... ........................ 16.87 20.61 13.73 30.59 TEXAS .......................................................................................................................................... MIDLAND ............................... 19.53 22.33 17.83 28.02 26.38 TEXAS .......................................................................................................................................... MILAM ................................... 6.39 18.48 31.72 26.87 32.20 TEXAS .......................................................................................................................................... MILLS .................................... 97.12 97.56 67.92 69.82 66.43 TEXAS .......................................................................................................................................... MITCHELL ............................. 2.86 3.25 8.08 20.16 16.17 TEXAS .......................................................................................................................................... MONTAGUE ........................... 26.86 9.52 4.68 12.02 5.65 TEXAS .......................................................................................................................................... MONTGOMERY ...................... 29.73 28.25 6.68 86.92 37.36 TEXAS .......................................................................................................................................... MOORE ................................. 44.71 28.06 24.56 9.49 18.05 TEXAS .......................................................................................................................................... MORRIS ................................ 37.70 22.23 11.28 7.88 ........................TEXAS .......................................................................................................................................... MOTLEY ................................ ........................ ........................ ........................ ........................ 13.39 TEXAS .......................................................................................................................................... NACOGDOCHES ..................... 29.94 33.24 34.25 33.33 33.30 TEXAS .......................................................................................................................................... NAVARRO .............................. 55.20 43.68 59.73 32.31 51.08 TEXAS .......................................................................................................................................... NEWTON ................................ 54.30 54.38 48.23 40.69 36.06 TEXAS .......................................................................................................................................... NOLAN .................................. 8.71 5.74 19.48 31.23 27.88 TEXAS .......................................................................................................................................... NUECES ................................ 17.21 19.71 16.38 24.20 21.53 TEXAS .......................................................................................................................................... OCHILTREE ........................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... OLDHAM ................................ ........................ 22.37 21.58 20.07 23.34 TEXAS .......................................................................................................................................... ORANGE ................................ 31.06 8.09 9.37 21.93 .68 TEXAS .......................................................................................................................................... PALO PINTO .......................... ........................ 97.64 97.54 70.26 61.54 TEXAS .......................................................................................................................................... PANOLA ................................. 49.64 35.62 35.60 33.34 31.61 TEXAS .......................................................................................................................................... PARKER ................................ 27.80 15.93 15.27 5.97 29.53 TEXAS .......................................................................................................................................... PARMER ................................ 1.24 2.23 14.28 15.69 14.80 TEXAS .......................................................................................................................................... PECOS .................................. ........................ 2.83 1.46 18.97 18.45 TEXAS .......................................................................................................................................... POLK ..................................... 43.71 45.33 42.63 39.55 55.69 TEXAS .......................................................................................................................................... POTTER ................................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... PRESIDIO .............................. 43.37 35.14 28.08 17.18 38.90 TEXAS .......................................................................................................................................... RAINS ................................... ........................ 1.39 9.25 6.99 31.62 
240 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

TEXAS .......................................................................................................................................... RANDALL ............................... ........................ ........................ ........................ 18.87 28.88 TEXAS .......................................................................................................................................... REAGAN ................................ 24.84 24.99 26.01 31.87 30.62 TEXAS .......................................................................................................................................... REAL ..................................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... RED RIVER ........................... 8.68 8.17 9.29 22.46 18.69 TEXAS .......................................................................................................................................... REEVES ................................. 22.29 31.03 23.89 21.63 40.08 TEXAS .......................................................................................................................................... REFUGIO ............................... 6.74 14.18 11.17 10.47 9.77 TEXAS .......................................................................................................................................... ROBERTS .............................. ........................ ........................ 24.22 14.88 13.65 TEXAS .......................................................................................................................................... ROBERTSON .......................... 3.97 17.47 21.59 27.45 26.48 TEXAS .......................................................................................................................................... ROCKWALL ............................ 31.20 37.40 57.82 59.18 53.32 TEXAS .......................................................................................................................................... RUNNELS .............................. 5.38 14.83 23.18 28.89 28.01 TEXAS .......................................................................................................................................... RUSK .................................... 3.26 20.15 34.57 30.62 29.82 TEXAS .......................................................................................................................................... SABINE ................................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... SAN AUGUSTINE ................... ........................ 1.17 .87 14.46 13.01 TEXAS .......................................................................................................................................... SAN JACINTO ........................ ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... SAN PATRICIO ....................... 13.01 12.91 24.38 17.91 14.56 TEXAS .......................................................................................................................................... SAN SABA ............................. 47.77 35.39 28.28 33.45 23.72 TEXAS .......................................................................................................................................... SCHLEICHER ......................... .82 18.01 15.36 11.75 12.95 TEXAS .......................................................................................................................................... SCURRY ................................ ........................ 3.58 8.69 5.54 3.46 TEXAS .......................................................................................................................................... SHACKELFORD ...................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... SHELBY ................................. 19.56 24.00 20.77 22.37 17.91 TEXAS .......................................................................................................................................... SHERMAN ............................. 2.25 ........................ 54.85 32.83 35.45 TEXAS .......................................................................................................................................... SMITH ................................... ........................ ........................ 27.61 27.99 52.67 TEXAS .......................................................................................................................................... SOMERVELL .......................... ........................ ........................ 3.00 ........................ ........................TEXAS .......................................................................................................................................... STARR ................................... 29.20 53.83 36.97 36.39 35.95 TEXAS .......................................................................................................................................... STEPHENS ............................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... STERLING .............................. ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... STONEWALL .......................... 1.84 2.14 .95 12.04 12.18 TEXAS .......................................................................................................................................... SUTTON ................................. 20.31 20.59 13.82 9.71 10.32 TEXAS .......................................................................................................................................... SWISHER ............................... 1.83 2.59 3.83 4.21 8.06 TEXAS .......................................................................................................................................... TARRANT ............................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... TAYLOR ................................. .23 1.27 .15 .10 .07 TEXAS .......................................................................................................................................... TERRELL ............................... ........................ ........................ ........................ ........................ 14.25 TEXAS .......................................................................................................................................... TERRY ................................... 6.22 5.92 6.77 12.24 11.69 TEXAS .......................................................................................................................................... THROCKMORTON ................... ........................ 41.43 35.93 30.39 14.63 TEXAS .......................................................................................................................................... TITUS .................................... ........................ ........................ ........................ .70 .43 
241 

TEXAS .......................................................................................................................................... TOM GREEN .......................... 16.22 10.26 14.25 12.17 13.77 TEXAS .......................................................................................................................................... TRAVIS .................................. ........................ ........................ 99.57 91.45 88.31 TEXAS .......................................................................................................................................... TRINITY ................................. 40.71 42.22 46.99 41.74 38.02 TEXAS .......................................................................................................................................... TYLER ................................... 27.70 24.35 20.29 16.41 14.35 TEXAS .......................................................................................................................................... UPSHUR ................................ ........................ .47 ........................ ........................ 26.27 TEXAS .......................................................................................................................................... UPTON .................................. 5.13 2.19 9.09 12.91 25.42 TEXAS .......................................................................................................................................... UVALDE ................................. 1.06 ........................ 22.36 24.62 35.92 TEXAS .......................................................................................................................................... VAL VERDE ........................... ........................ 5.68 ........................ ........................ ........................TEXAS .......................................................................................................................................... VAN ZANDT ........................... 2.81 31.40 25.37 41.51 43.15 TEXAS .......................................................................................................................................... VICTORIA .............................. 40.58 30.21 21.97 38.73 30.34 TEXAS .......................................................................................................................................... WALKER ................................ ........................ ........................ 2.78 2.75 .76 TEXAS .......................................................................................................................................... WALLER ................................ .95 ........................ ........................ 99.29 24.85 TEXAS .......................................................................................................................................... WARD .................................... ........................ ........................ .44 .53 ........................TEXAS .......................................................................................................................................... WASHINGTON ........................ ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... WEBB .................................... ........................ ........................ 35.76 34.50 33.55 TEXAS .......................................................................................................................................... WHARTON ............................. 12.15 16.91 15.20 22.47 23.36 TEXAS .......................................................................................................................................... WHEELER .............................. ........................ 31.49 28.03 20.67 27.88 TEXAS .......................................................................................................................................... WICHITA ................................ ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... WILBARGER .......................... 6.58 9.23 14.66 13.72 14.49 TEXAS .......................................................................................................................................... WILLACY ............................... 53.11 47.35 37.49 32.25 33.08 TEXAS .......................................................................................................................................... WILLIAMSON ......................... 68.13 69.02 63.64 70.94 54.50 TEXAS .......................................................................................................................................... WILSON ................................. 27.75 43.71 54.61 55.44 51.59 TEXAS .......................................................................................................................................... WINKLER ............................... ........................ ........................ ........................ ........................ ........................TEXAS .......................................................................................................................................... WISE ..................................... ........................ ........................ 59.90 14.39 75.05 TEXAS .......................................................................................................................................... WOOD ................................... 3.35 1.49 2.61 4.67 58.36 TEXAS .......................................................................................................................................... YOAKUM ................................ 7.26 9.36 9.94 19.08 17.62 TEXAS .......................................................................................................................................... YOUNG .................................. ........................ ........................ ........................ ........................ 39.62 TEXAS .......................................................................................................................................... ZAPATA ................................. ........................ 38.30 42.45 36.44 30.93 TEXAS .......................................................................................................................................... ZAVALA ................................. 10.79 ........................ 29.48 62.95 54.87 UTAH ........................................................................................................................................... BEAVER ................................ .23 ........................ ........................ 1.47 .80 UTAH ........................................................................................................................................... BOX ELDER ........................... 5.58 1.60 9.87 10.85 12.25 UTAH ........................................................................................................................................... CACHE .................................. 4.61 2.03 2.34 3.36 1.64 UTAH ........................................................................................................................................... CARBON ................................ ........................ .29 ........................ ........................ ........................UTAH ........................................................................................................................................... DAGGETT ............................... ........................ .28 8.48 5.77 3.64 UTAH ........................................................................................................................................... DAVIS .................................... ........................ ........................ ........................ ........................ ........................UTAH ........................................................................................................................................... DUCHESNE ............................ ........................ 2.77 .18 .02 .14 UTAH ........................................................................................................................................... EMERY .................................. ........................ .35 .69 .33 ........................UTAH ........................................................................................................................................... GARFIELD .............................. .17 .12 .98 1.61 1.62 UTAH ........................................................................................................................................... GRAND,E ............................... ........................ 3.75 2.70 3.44 ........................UTAH ........................................................................................................................................... IRON ..................................... 4.88 ........................ 1.68 .75 ........................
242 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

UTAH ........................................................................................................................................... JUAB ..................................... .84 .81 .57 .64 .56 UTAH ........................................................................................................................................... KANE ..................................... ........................ 2.18 1.52 2.60 2.17 UTAH ........................................................................................................................................... MILLARD ............................... .90 .73 2.20 5.97 6.01 UTAH ........................................................................................................................................... MORGAN ............................... ........................ ........................ ........................ ........................ ........................UTAH ........................................................................................................................................... PIUTE .................................... .71 .13 1.78 2.07 3.78 UTAH ........................................................................................................................................... RICH ..................................... ........................ ........................ 1.94 2.16 1.71 UTAH ........................................................................................................................................... SALT LAKE ............................ ........................ ........................ .59 ........................ ........................UTAH ........................................................................................................................................... SAN JUAN ............................. .11 .10 .03 ........................ .04 UTAH ........................................................................................................................................... SANPETE ............................... .65 1.26 1.25 .69 1.39 UTAH ........................................................................................................................................... SEVIER .................................. 2.61 2.08 .46 1.25 3.45 UTAH ........................................................................................................................................... SUMMIT ................................ .12 .24 ........................ ........................ 1.33 UTAH ........................................................................................................................................... TOOELE ................................. 2.18 1.25 ........................ ........................ ........................UTAH ........................................................................................................................................... UINTAH ................................. .49 .03 .50 .18 .15 UTAH ........................................................................................................................................... UTAH ..................................... 2.39 .16 .32 1.41 .91 UTAH ........................................................................................................................................... WASATCH .............................. ........................ ........................ ........................ ........................ ........................UTAH ........................................................................................................................................... WASHINGTON ........................ ........................ ........................ ........................ 1.61 3.08 UTAH ........................................................................................................................................... WAYNE .................................. .91 .77 4.27 4.02 4.36 UTAH ........................................................................................................................................... WEBER .................................. ........................ ........................ ........................ ........................ ........................VERMONT .................................................................................................................................... ADDISON ............................... 4.00 6.23 8.61 9.57 8.24 VERMONT .................................................................................................................................... BENNINGTON ........................ ........................ ........................ ........................ ........................ 22.65 VERMONT .................................................................................................................................... CALEDONIA ........................... 13.93 12.49 13.63 11.62 12.33 VERMONT .................................................................................................................................... CHITTENDEN ......................... ........................ .98 ........................ ........................ 1.33VERMONT .................................................................................................................................... ESSEX ................................... ........................ ........................ ........................ 1.78 .98 VERMONT .................................................................................................................................... FRANKLIN .............................. 1.87 6.05 6.40 5.92 6.79 VERMONT .................................................................................................................................... GRAND ISLE .......................... ........................ ........................ ........................ 1.20 1.63 VERMONT .................................................................................................................................... LAMOILLE .............................. ........................ 2.73 ........................ 7.43 8.28 VERMONT .................................................................................................................................... ORANGE ................................ ........................ ........................ 3.73 3.22 2.95 VERMONT .................................................................................................................................... ORLEANS .............................. .02 .13 ........................ ........................ .05 VERMONT .................................................................................................................................... RUTLAND .............................. 2.26 2.93 .33 2.22 4.85 VERMONT .................................................................................................................................... WASHINGTON ........................ ........................ 4.66 2.18 ........................ ........................VERMONT .................................................................................................................................... WINDHAM .............................. .39 4.48 2.45 4.32 3.48 VERMONT .................................................................................................................................... WINDSOR .............................. 23.76 20.36 22.63 16.35 18.89 VIRGIN ISLANDS .......................................................................................................................... ST. CROIX ............................. 37.62 32.24 26.64 21.58 18.75 VIRGIN ISLANDS .......................................................................................................................... ST. JOHN ............................... ........................ ........................ ........................ ........................ ........................VIRGIN ISLANDS .......................................................................................................................... ST. THOMAS .......................... ........................ ........................ .53 ........................ ........................
243 

VIRGINIA ...................................................................................................................................... ACCOMACK ........................... 3.31 2.36 5.05 11.24 7.93 VIRGINIA ...................................................................................................................................... ALBEMARLE .......................... 1.73 ........................ 3.68 ........................ ........................VIRGINIA ...................................................................................................................................... ALEXANDRIA CITY ................. ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... ALLEGHANY ........................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... AMELIA ................................. 4.09 8.93 6.81 11.27 5.86 VIRGINIA ...................................................................................................................................... AMHERST .............................. 2.96 5.14 2.59 .67 ........................VIRGINIA ...................................................................................................................................... APPOMATTOX ........................ 6.01 3.33 35.11 31.30 26.85 VIRGINIA ...................................................................................................................................... ARLINGTON ........................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... AUGUSTA .............................. 1.26 .36 6.06 8.74 20.50 VIRGINIA ...................................................................................................................................... BATH ..................................... ........................ ........................ 100.00 87.63 76.36 VIRGINIA ...................................................................................................................................... BEDFORD .............................. 1.90 ........................ 1.39 1.58 10.00 VIRGINIA ...................................................................................................................................... BEDFORD CITY ..................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... BLAND .................................. ........................ ........................ ........................ 2.02 ........................VIRGINIA ...................................................................................................................................... BOTETOURT .......................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... BRISTOL ................................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... BRUNSWICK .......................... .83 .44 1.84 2.24 11.75 VIRGINIA ...................................................................................................................................... BUCHANAN ........................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... BUCKINGHAM ........................ .18 ........................ 10.04 .85 .44 VIRGINIA ...................................................................................................................................... BUENA VISTA ........................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... CAMPBELL ............................ .20 3.14 .34 .84 4.47 VIRGINIA ...................................................................................................................................... CAROLINE ............................. ........................ 2.29 2.15 20.64 19.29 VIRGINIA ...................................................................................................................................... CARROLL .............................. ........................ ........................ ........................ .96 1.95 VIRGINIA ...................................................................................................................................... CHARLES CITY ...................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... CHARLOTTE ........................... 1.62 1.52 ........................ ........................ ........................VIRGINIA ...................................................................................................................................... CHARLOTTESVILLE CITY ........ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... CHESAPEAKE ........................ 63.71 61.72 56.41 48.77 46.53 VIRGINIA ...................................................................................................................................... CHESTERFIELD ...................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... CLARKE ................................. ........................ ........................ 2.60 1.32 10.38 VIRGINIA ...................................................................................................................................... COLONIAL HEIGHTS .............. ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... COURTLAND .......................... 14.07 15.34 16.64 18.29 19.52 VIRGINIA ...................................................................................................................................... COVINGTON ........................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... CRAIG ................................... 9.82 ........................ 5.48 6.21 5.95 VIRGINIA ...................................................................................................................................... CULPEPER ............................ 28.72 24.06 17.24 14.64 10.60 VIRGINIA ...................................................................................................................................... CUMBERLAND ....................... .57 .31 1.24 2.17 5.48 VIRGINIA ...................................................................................................................................... DANVILLE .............................. ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... DICKENSON ........................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... DINWIDDIE ............................ 67.18 76.61 72.65 71.87 71.01 VIRGINIA ...................................................................................................................................... EMPORIA ............................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... ESSEX ................................... 1.15 4.61 2.76 1.98 1.47 VIRGINIA ...................................................................................................................................... FAIRFAX ................................ ........................ ........................ ........................ ........................ ........................
244 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

VIRGINIA ...................................................................................................................................... FAIRFAX CITY ........................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... FALLS CHURCH ..................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... FAUQUIER ............................. 2.36 .18 .17 8.25 4.89 VIRGINIA ...................................................................................................................................... FLOYD ................................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... FLUVANNA ............................. ........................ ........................ 3.41 3.97 15.29 VIRGINIA ...................................................................................................................................... FRANKLIN .............................. 6.03 9.81 11.81 10.54 24.45 VIRGINIA ...................................................................................................................................... FRANKLIN CITY ..................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... FREDERICK ........................... 2.19 7.53 7.06 6.52 5.00 VIRGINIA ...................................................................................................................................... FREDERICKSBURG ................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... GALAX ................................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... GILES .................................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... GLOUCESTER ........................ 10.27 8.81 11.80 ........................ ........................VIRGINIA ...................................................................................................................................... GOOCHLAND ......................... .30 .35 .61 .79 ........................VIRGINIA ...................................................................................................................................... GRAYSON .............................. 5.80 3.56 1.77 .28 ........................VIRGINIA ...................................................................................................................................... GREENE ................................ 3.10 ........................ ........................ 9.05 ........................VIRGINIA ...................................................................................................................................... GREENSVILLE ........................ ........................ 12.82 1.72 ........................ 5.89 VIRGINIA ...................................................................................................................................... HALIFAX ................................ 4.45 3.84 5.76 7.27 18.31 VIRGINIA ...................................................................................................................................... HAMPTON .............................. ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... HANOVER .............................. 2.98 1.63 2.03 8.15 6.48 VIRGINIA ...................................................................................................................................... HARRISONBURG .................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... HENRICO ............................... 8.13 ........................ 9.34 ........................ ........................VIRGINIA ...................................................................................................................................... HENRY .................................. 24.81 20.54 17.03 13.13 13.56 VIRGINIA ...................................................................................................................................... HIGHLAND ............................. ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... HOPEWELL ............................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... ISLE OF WIGHT ..................... 1.85 7.32 10.33 4.57 11.68 VIRGINIA ...................................................................................................................................... JAMES CITY .......................... 21.38 20.65 19.63 18.81 18.13 VIRGINIA ...................................................................................................................................... KING AND QUEEN ................. 8.40 6.37 5.10 20.22 16.10 VIRGINIA ...................................................................................................................................... KING GEORGE ....................... ........................ 1.01 18.53 9.26 11.30 VIRGINIA ...................................................................................................................................... KING WILLIAM ....................... ........................ ........................ 4.89 ........................ ........................VIRGINIA ...................................................................................................................................... LANCASTER ........................... ........................ ........................ ........................ 44.04 68.26 VIRGINIA ...................................................................................................................................... LEE ....................................... .58 ........................ .13 ........................ ........................VIRGINIA ...................................................................................................................................... LEXINGTON ........................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... LOUDOUN .............................. 4.78 ........................ ........................ 14.22 16.94 VIRGINIA ...................................................................................................................................... LOUISA .................................. 2.80 ........................ ........................ 5.73 ........................VIRGINIA ...................................................................................................................................... LUNENBURG ......................... ........................ .67 .71 .55 1.18 
245 

VIRGINIA ...................................................................................................................................... LYNCHBURG ......................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... MADISON .............................. 11.76 7.78 14.81 4.80 8.34 VIRGINIA ...................................................................................................................................... MANASSA PARK CITY ............ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... MANASSAS ............................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... MARTINSVILLE ...................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... MATHEWS ............................. ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... MECKLENBURG ..................... .69 12.73 12.12 9.78 8.26 VIRGINIA ...................................................................................................................................... MIDDLESEX ........................... 16.15 7.61 6.73 6.07 .06 VIRGINIA ...................................................................................................................................... MONTGOMERY ...................... ........................ ........................ ........................ 2.15 ........................VIRGINIA ...................................................................................................................................... NELSON ................................ ........................ ........................ 1.76 ........................ ........................VIRGINIA ...................................................................................................................................... NEW KENT ............................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... NEWPORT NEWS ................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... NORFOLK CITY ...................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... NORTHAMPTON ..................... 7.22 15.64 19.20 12.02 1.99 VIRGINIA ...................................................................................................................................... NORTHUMBERLAND .............. 90.62 90.22 90.22 89.72 88.58 VIRGINIA ...................................................................................................................................... NORTON ................................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... NOTTOWAY ............................ .79 ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... ORANGE ................................ 1.65 ........................ ........................ ........................ 8.17 VIRGINIA ...................................................................................................................................... PAGE ..................................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... PATRICK ................................ 4.32 .37 ........................ .76 .78 VIRGINIA ...................................................................................................................................... PETERSBURG ........................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... PITTSYLVANIA ....................... 5.84 6.05 5.89 3.79 1.14 VIRGINIA ...................................................................................................................................... POQUASON ............................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... PORTSMOUTH CITY ............... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... POWHATAN ............................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... PRINCE EDWARD .................. ........................ 8.51 2.91 ........................ ........................VIRGINIA ...................................................................................................................................... PRINCE GEORGE ................... 3.03 19.99 5.02 2.94 3.67 VIRGINIA ...................................................................................................................................... PRINCE WILLIAM ................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... PULASKI ................................ 71.12 72.07 70.96 69.47 48.43 VIRGINIA ...................................................................................................................................... RADFORD .............................. ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... RAPPAHANNOCK ................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... RICHMOND ............................ 8.44 5.56 1.12 10.91 16.45 VIRGINIA ...................................................................................................................................... RICHMOND CITY ................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... ROANOKE .............................. ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... ROANOKE CITY ..................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... ROCKBRIDGE ........................ .89 2.29 .45 .96 5.18 VIRGINIA ...................................................................................................................................... ROCKINGHAM ........................ 1.38 1.29 .57 ........................ 3.08 VIRGINIA ...................................................................................................................................... RUSSELL ............................... ........................ ........................ 1.06 1.25 .40 VIRGINIA ...................................................................................................................................... SALEM .................................. ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... SCOTT ................................... 31.38 29.03 21.91 21.64 18.60 
246 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

VIRGINIA ...................................................................................................................................... SHENANDOAH ....................... 1.02 1.28 2.46 4.30 1.22 VIRGINIA ...................................................................................................................................... SMYTH .................................. ........................ 38.87 34.67 31.11 22.97 VIRGINIA ...................................................................................................................................... SPOTSYLVANIA ...................... 45.60 32.38 25.52 2.66 2.80 VIRGINIA ...................................................................................................................................... STAFFORD ............................. ........................ ........................ 2.01 2.66 ........................VIRGINIA ...................................................................................................................................... STAUNTON ............................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... SUFFOLK ............................... 7.04 2.08 2.31 9.47 8.24 VIRGINIA ...................................................................................................................................... SURRY .................................. 9.50 4.73 5.72 5.06 .07 VIRGINIA ...................................................................................................................................... SUSSEX ................................. 11.71 11.49 3.87 6.40 3.36 VIRGINIA ...................................................................................................................................... TAZEWELL ............................. ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... VIRGINIA BEACH (CITY ......... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... WARREN ............................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... WASHINGTON ........................ ........................ 3.83 3.25 4.71 2.14 VIRGINIA ...................................................................................................................................... WAYNESBORO ....................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... WESTMORELAND ................... 13.10 7.58 19.94 1.26 8.60 VIRGINIA ...................................................................................................................................... WILLIAMSBURG ..................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... WINCHESTER ........................ ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... WISE ..................................... ........................ ........................ ........................ ........................ ........................VIRGINIA ...................................................................................................................................... WYTHE .................................. 36.09 29.32 27.37 21.51 18.52 VIRGINIA ...................................................................................................................................... YORK .................................... ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... ADAMS .................................. 7.30 11.35 15.57 18.73 10.65 WASHINGTON ............................................................................................................................... ASOTIN .................................. ........................ ........................ 100.00 ........................ ........................WASHINGTON ............................................................................................................................... BENTON ................................ 1.68 2.32 4.27 5.39 3.68 WASHINGTON ............................................................................................................................... CHELAN ................................ 2.42 3.47 3.07 2.56 6.03 WASHINGTON ............................................................................................................................... CLALLAM ............................... ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... CLARK ................................... ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... COLUMBIA ............................ ........................ ........................ 2.94 ........................ ........................WASHINGTON ............................................................................................................................... COWLITZ ............................... ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... DOUGLAS .............................. 1.60 3.41 4.09 4.43 4.20 WASHINGTON ............................................................................................................................... FERRY ................................... 35.65 34.59 36.55 32.98 41.27 WASHINGTON ............................................................................................................................... FRANKLIN .............................. 4.19 17.04 10.24 10.86 6.74 WASHINGTON ............................................................................................................................... GARFIELD .............................. 1.18 4.77 ........................ ........................ ........................WASHINGTON ............................................................................................................................... GRANT, N .............................. 1.00 2.00 2.21 2.33 2.09 WASHINGTON ............................................................................................................................... GRAYS HARBOR .................... ........................ .15 ........................ ........................ .93 WASHINGTON ............................................................................................................................... ISLAND .................................. ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... JEFFERSON ........................... ........................ ........................ 25.25 ........................ .35
247 

WASHINGTON ............................................................................................................................... KING ..................................... ........................ ........................ 8.35 ........................ 4.04 WASHINGTON ............................................................................................................................... KITSAP .................................. ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... KITTITAS ................................ .03 .64 .63 9.99 9.62 WASHINGTON ............................................................................................................................... KLICKITAT ............................. .21 .40 .29 .29 15.28 WASHINGTON ............................................................................................................................... LEWIS ................................... 21.84 19.92 34.06 28.02 21.59 WASHINGTON ............................................................................................................................... LINCOLN ............................... 1.54 1.78 .93 .66 .22 WASHINGTON ............................................................................................................................... MASON .................................. ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... OKANOGAN ............................ 14.55 13.39 15.21 12.62 12.77 WASHINGTON ............................................................................................................................... PACIFIC ................................. 3.54 2.16 1.75 1.31 .98 WASHINGTON ............................................................................................................................... PEND OREILLE ...................... ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... PIERCE ................................. ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... SAN JUAN ............................. ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... SKAGIT .................................. 14.22 13.15 19.79 21.50 19.50 WASHINGTON ............................................................................................................................... SKAMANIA ............................. ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... SNOHOMISH .......................... ........................ ........................ ........................ ........................ .69 WASHINGTON ............................................................................................................................... SPOKANE .............................. 6.01 1.99 2.29 8.09 5.34 WASHINGTON ............................................................................................................................... STEVENS ............................... 3.62 .64 11.65 9.28 10.21 WASHINGTON ............................................................................................................................... THURSTON ............................ ........................ ........................ ........................ ........................ ........................WASHINGTON ............................................................................................................................... WAHKIAKUM .......................... ........................ ........................ 17.21 13.77 10.96 WASHINGTON ............................................................................................................................... WALLA WALLA ....................... 4.32 3.42 2.92 4.62 7.06 WASHINGTON ............................................................................................................................... WHATCOM ............................. 4.30 2.42 3.43 2.45 3.71 WASHINGTON ............................................................................................................................... WHITMAN .............................. 1.91 1.54 6.51 4.54 2.86 WASHINGTON ............................................................................................................................... YAKIMA ................................. 6.28 8.04 6.78 6.70 5.05 WEST VIRGINIA ............................................................................................................................ BARBOUR ............................. .20 .12 4.77 4.25 8.04 WEST VIRGINIA ............................................................................................................................ BERKELEY ............................. 6.35 42.59 37.20 41.43 22.99 WEST VIRGINIA ............................................................................................................................ BOONE .................................. ........................ ........................ ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ BRAXTON .............................. 1.01 1.58 1.77 14.37 12.31 WEST VIRGINIA ............................................................................................................................ BROOKE ................................ 4.12 13.19 ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ CABELL ................................. 4.24 1.21 9.68 8.65 6.08 WEST VIRGINIA ............................................................................................................................ CALHOUN .............................. .93 1.02 .65 1.05 2.37 WEST VIRGINIA ............................................................................................................................ CLAY ..................................... 1.86 .54 ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ DODDRIDGE .......................... .29 10.23 7.24 8.40 4.99 WEST VIRGINIA ............................................................................................................................ FAYETTE ................................ 3.65 12.96 29.85 31.48 11.83 WEST VIRGINIA ............................................................................................................................ GILMER ................................. 1.84 .77 2.08 2.93 18.68 WEST VIRGINIA ............................................................................................................................ GRANT .................................. 1.44 1.88 1.01 .36 .03 WEST VIRGINIA ............................................................................................................................ GREENBRIER ........................ 11.65 12.61 10.12 8.75 6.99 WEST VIRGINIA ............................................................................................................................ HAMPSHIRE .......................... 9.69 9.54 7.27 7.10 1.96 WEST VIRGINIA ............................................................................................................................ HANCOCK .............................. 16.16 9.42 ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ HARDY .................................. 1.26 .24 .04 1.79 2.96 WEST VIRGINIA ............................................................................................................................ HARRISON ............................. 5.81 6.06 9.81 7.79 7.55 
248 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

WEST VIRGINIA ............................................................................................................................ JACKSON ............................... 1.23 .69 .24 .07 ........................WEST VIRGINIA ............................................................................................................................ JEFFERSON ........................... 10.24 8.26 6.36 10.29 3.37 WEST VIRGINIA ............................................................................................................................ KANAWHA .............................. ........................ ........................ ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ LEWIS ................................... .51 18.01 14.41 16.15 22.58 WEST VIRGINIA ............................................................................................................................ LINCOLN ............................... 4.11 1.64 6.69 8.65 3.67 WEST VIRGINIA ............................................................................................................................ LOGAN .................................. ........................ ........................ ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ MARION ................................ 1.48 8.86 4.81 2.45 ........................WEST VIRGINIA ............................................................................................................................ MARSHALL ............................ 10.11 12.10 9.53 8.49 8.20 WEST VIRGINIA ............................................................................................................................ MARSHALL ............................ ........................ ........................ ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ MASON .................................. 3.33 6.00 9.15 10.39 8.78 WEST VIRGINIA ............................................................................................................................ MCDOWELL ........................... 28.81 24.36 18.97 13.37 7.47 WEST VIRGINIA ............................................................................................................................ MERCER ............................... 8.92 10.65 10.32 9.32 6.70 WEST VIRGINIA ............................................................................................................................ MINERAL ............................... 1.84 ........................ ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ MINGO .................................. ........................ ........................ ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ MONONGALIA ........................ ........................ .20 .22 .12 ........................WEST VIRGINIA ............................................................................................................................ MONROE ............................... 13.21 14.04 9.98 8.84 7.78 WEST VIRGINIA ............................................................................................................................ MORGAN ............................... 6.83 2.91 6.49 2.43 ........................WEST VIRGINIA ............................................................................................................................ NICHOLAS ............................. 3.30 1.02 .17 .36 1.45 WEST VIRGINIA ............................................................................................................................ PENDLETON .......................... 1.90 .76 1.13 1.25 .02 WEST VIRGINIA ............................................................................................................................ PLEASANTS ........................... ........................ ........................ ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ POCAHONTAS ........................ ........................ .09 .55 1.12 1.26 WEST VIRGINIA ............................................................................................................................ PRESTON .............................. 1.22 5.47 1.94 9.33 8.96 WEST VIRGINIA ............................................................................................................................ PUTNAM ................................ .18 3.47 5.09 5.87 4.04 WEST VIRGINIA ............................................................................................................................ RALEIGH ............................... 25.55 22.09 20.78 20.47 17.08 WEST VIRGINIA ............................................................................................................................ RANDOLPH ............................ .19 ........................ 3.49 .15 ........................WEST VIRGINIA ............................................................................................................................ RITCHIE ................................ 1.72 .67 14.10 1.31 9.21 WEST VIRGINIA ............................................................................................................................ ROANE .................................. 1.12 1.00 1.06 1.26 6.30 WEST VIRGINIA ............................................................................................................................ SUMMERS ............................. 15.57 9.47 7.77 6.25 7.00 WEST VIRGINIA ............................................................................................................................ TAYLOR ................................. ........................ 1.15 .94 2.91 .87 WEST VIRGINIA ............................................................................................................................ TUCKER ................................ ........................ ........................ ........................ ........................ ........................WEST VIRGINIA ............................................................................................................................ TYLER ................................... ........................ ........................ ........................ ........................ .09 WEST VIRGINIA ............................................................................................................................ UPSHUR ................................ 5.84 14.17 11.22 10.22 15.91 WEST VIRGINIA ............................................................................................................................ WAYNE .................................. ........................ ........................ ........................ 4.70 ........................WEST VIRGINIA ............................................................................................................................ WEBSTER .............................. 2.01 1.41 ........................ 3.49 2.44 WEST VIRGINIA ............................................................................................................................ WETZEL ................................. ........................ ........................ ........................ 4.01 2.93 
249 

WEST VIRGINIA ............................................................................................................................ WIRT ..................................... ........................ .70 2.09 3.05 5.28 WEST VIRGINIA ............................................................................................................................ WOOD ................................... ........................ 17.00 15.91 35.87 29.28 WEST VIRGINIA ............................................................................................................................ WYOMING .............................. 20.44 22.44 10.96 4.80 ........................WISCONSIN .................................................................................................................................. ADAMS .................................. ........................ ........................ ........................ ........................ ........................WISCONSIN .................................................................................................................................. ASHLAND .............................. .20 3.10 3.74 3.47 7.27 WISCONSIN .................................................................................................................................. BARRON ................................ 2.16 ........................ .24 2.09 .35 WISCONSIN .................................................................................................................................. BAYFIELD .............................. .31 .28 1.75 .94 2.94 WISCONSIN .................................................................................................................................. BROWN ................................. .20 .21 3.22 3.76 1.74 WISCONSIN .................................................................................................................................. BUFFALO ............................... ........................ .42 .51 ........................ ........................WISCONSIN .................................................................................................................................. BURNETT .............................. ........................ .38 1.34 .48 ........................WISCONSIN .................................................................................................................................. CALUMET .............................. 1.05 ........................ ........................ 4.41 1.16 WISCONSIN .................................................................................................................................. CHIPPEWA ............................. 1.35 .71 5.69 6.09 3.92 WISCONSIN .................................................................................................................................. CLARK ................................... .55 .51 .84 1.06 .85 WISCONSIN .................................................................................................................................. COLUMBIA ............................ 4.11 1.58 2.54 1.70 2.91 WISCONSIN .................................................................................................................................. CRAWFORD ........................... .31 ........................ ........................ .30 .16 WISCONSIN .................................................................................................................................. DANE .................................... ........................ .82 .71 1.35 9.23 WISCONSIN .................................................................................................................................. DODGE .................................. 3.84 3.47 3.49 6.21 3.37 WISCONSIN .................................................................................................................................. DOOR .................................... ........................ ........................ ........................ 1.43 .61 WISCONSIN .................................................................................................................................. DOUGLAS .............................. .36 ........................ .41 5.50 2.31 WISCONSIN .................................................................................................................................. DUNN .................................... 1.09 4.13 5.26 9.56 8.23 WISCONSIN .................................................................................................................................. EAU CLAIRE .......................... 8.31 ........................ 2.21 1.12 2.31 WISCONSIN .................................................................................................................................. FLORENCE ............................ 11.97 7.08 1.41 ........................ ........................WISCONSIN .................................................................................................................................. FOND DU LAC ....................... 1.79 2.30 3.56 6.26 4.65 WISCONSIN .................................................................................................................................. FOREST ................................. ........................ ........................ ........................ ........................ ........................WISCONSIN .................................................................................................................................. GRANT .................................. .07 .88 1.07 2.28 1.03 WISCONSIN .................................................................................................................................. GREEN .................................. .37 1.67 4.27 3.71 4.35 WISCONSIN .................................................................................................................................. GREEN LAKE ......................... .39 .28 .20 1.37 .98 WISCONSIN .................................................................................................................................. IOWA ..................................... .61 .01 ........................ .50 1.97 WISCONSIN .................................................................................................................................. IRON ..................................... ........................ ........................ ........................ ........................ 1.01 WISCONSIN .................................................................................................................................. JACKSON ............................... ........................ ........................ ........................ ........................ ........................WISCONSIN .................................................................................................................................. JEFFERSON ........................... .19 .06 ........................ .12 1.12 WISCONSIN .................................................................................................................................. JUNEAU ................................. 1.56 .18 .18 .97 ........................WISCONSIN .................................................................................................................................. KENOSHA .............................. ........................ ........................ ........................ ........................ ........................WISCONSIN .................................................................................................................................. KEWAUNEE ............................ 2.85 2.96 2.69 2.44 3.60 WISCONSIN .................................................................................................................................. LA CROSSE ........................... ........................ ........................ ........................ .41 1.42 WISCONSIN .................................................................................................................................. LAFAYETTE ............................ .47 .34 .57 .42 .64 WISCONSIN .................................................................................................................................. LANGLADE ............................. .65 4.62 2.65 3.45 2.62 WISCONSIN .................................................................................................................................. LINCOLN ............................... ........................ ........................ 1.99 ........................ ........................WISCONSIN .................................................................................................................................. MANITOWOC .......................... .04 .34 .28 .12 .15 WISCONSIN .................................................................................................................................. MARATHON ........................... .14 2.14 1.04 2.74 7.32 
250 

DIRECT LOAN PROGRAM DELINQUENCIES (ALL LOAN TYPES)—Continued 

STATE NAME COUNTY NAME DELQ RATE 12/31/06 DELQ RATE 12/31/05 DELQ RATE 12/31/04 DELQ RATE 12/31/03 DELQ RATE 12/31/02 

WISCONSIN .................................................................................................................................. MARINETTE ........................... 5.84 5.46 3.94 3.52 4.03 WISCONSIN .................................................................................................................................. MARQUETTE .......................... 2.77 ........................ ........................ 11.20 2.25 WISCONSIN .................................................................................................................................. MENOMINEE .......................... ........................ ........................ ........................ ........................ ........................WISCONSIN .................................................................................................................................. MILWAUKEE .......................... ........................ ........................ ........................ ........................ ........................WISCONSIN .................................................................................................................................. MONROE ............................... .03 .91 1.48 .56 .27 WISCONSIN .................................................................................................................................. OCONTO ................................ 1.69 2.07 .66 1.38 1.20 WISCONSIN .................................................................................................................................. ONEIDA ................................. ........................ ........................ ........................ ........................ ........................WISCONSIN .................................................................................................................................. OUTAGAMIE ........................... .85 1.37 2.40 .94 .69 WISCONSIN .................................................................................................................................. OZAUKEE .............................. ........................ ........................ 6.58 2.42 ........................WISCONSIN .................................................................................................................................. PEPIN .................................... .58 ........................ ........................ ........................ 6.28 WISCONSIN .................................................................................................................................. PIERCE ................................. 2.44 2.28 1.11 ........................ .29 WISCONSIN .................................................................................................................................. POLK ..................................... 1.78 .69 .52 .21 .35 WISCONSIN .................................................................................................................................. PORTAGE .............................. 1.46 1.44 .63 .40 1.68 WISCONSIN .................................................................................................................................. PRICE ................................... .24 1.02 1.41 .43 ........................WISCONSIN .................................................................................................................................. RACINE ................................. 3.55 ........................ ........................ ........................ ........................WISCONSIN .................................................................................................................................. RICHLAND ............................. 1.47 .75 1.15 .76 1.00 WISCONSIN .................................................................................................................................. ROCK .................................... .40 4.61 7.76 5.99 8.24 WISCONSIN .................................................................................................................................. RUSK .................................... .54 ........................ 2.63 1.59 7.86 WISCONSIN .................................................................................................................................. SAUK ..................................... 1.55 2.74 3.22 2.23 4.12 WISCONSIN .................................................................................................................................. SAWYER ................................ ........................ ........................ 1.27 ........................ ........................WISCONSIN .................................................................................................................................. SHAWANO ............................. 2.21 1.95 1.96 2.47 .60 WISCONSIN .................................................................................................................................. SHEBOYGAN .......................... ........................ 4.56 3.46 1.11 1.02 WISCONSIN .................................................................................................................................. ST. CROIX ............................. .01 .28 ........................ .95 .50 WISCONSIN .................................................................................................................................. TAYLOR ................................. ........................ .03 .71 .77 .69 WISCONSIN .................................................................................................................................. TREMPEALEAU ...................... 2.29 2.29 1.90 1.74 1.88 WISCONSIN .................................................................................................................................. VERNON ................................ .17 .41 .34 .47 1.34 WISCONSIN .................................................................................................................................. VILAS .................................... ........................ ........................ ........................ ........................ 5.67 WISCONSIN .................................................................................................................................. WALWORTH ........................... ........................ ........................ 1.08 1.61 .27 WISCONSIN .................................................................................................................................. WASHBURN ........................... .22 ........................ .33 ........................ ........................WISCONSIN .................................................................................................................................. WASHINGTON ........................ .03 ........................ ........................ 7.00 5.56 WISCONSIN .................................................................................................................................. WAUKESHA ............................ ........................ ........................ ........................ ........................ ........................WISCONSIN .................................................................................................................................. WAUPACA .............................. ........................ ........................ ........................ .96 1.98 WISCONSIN .................................................................................................................................. WAUSHARA ........................... ........................ ........................ ........................ ........................ 1.00 WISCONSIN .................................................................................................................................. WINNEBAGO .......................... ........................ ........................ .82 ........................ 12.93 WISCONSIN .................................................................................................................................. WOOD ................................... 1.44 1.06 .84 .33 3.32 
251 

WYOMING .................................................................................................................................... ALBANY ................................. ........................ .30 ........................ ........................ 7.86 WYOMING .................................................................................................................................... BIG HORN, SOUTHERN ......... 2.82 8.53 7.08 6.89 18.84 WYOMING .................................................................................................................................... CAMPBELL ............................ 43.00 25.88 21.15 4.87 ........................WYOMING .................................................................................................................................... CARBON ................................ 1.23 ........................ .48 7.38 5.93 WYOMING .................................................................................................................................... CONVERSE ............................ ........................ ........................ ........................ ........................ ........................WYOMING .................................................................................................................................... CROOK .................................. ........................ ........................ ........................ ........................ ........................WYOMING .................................................................................................................................... FREMONT .............................. 10.62 14.63 13.63 14.11 12.15 WYOMING .................................................................................................................................... GOSHEN ................................ 6.54 11.37 9.51 7.25 5.40 WYOMING .................................................................................................................................... HOT SPRINGS ....................... 16.64 14.96 12.87 10.20 9.51 WYOMING .................................................................................................................................... JOHNSON .............................. ........................ ........................ ........................ ........................ ........................WYOMING .................................................................................................................................... LARAMIE ............................... 13.77 18.56 15.62 14.36 10.50 WYOMING .................................................................................................................................... LINCOLN ............................... ........................ ........................ 1.87 ........................ 4.13 WYOMING .................................................................................................................................... NATRONA .............................. .33 .19 ........................ ........................ ........................WYOMING .................................................................................................................................... NIOBRARA ............................. ........................ ........................ ........................ ........................ ........................WYOMING .................................................................................................................................... PARK ..................................... ........................ ........................ .21 2.00 2.27 WYOMING .................................................................................................................................... PLATTE .................................. 5.94 6.06 4.54 8.68 7.66 WYOMING .................................................................................................................................... SHERIDAN ............................. ........................ ........................ ........................ ........................ ........................WYOMING .................................................................................................................................... SUBLETTE ............................. 100.00 65.30 70.56 ........................ 6.48 WYOMING .................................................................................................................................... SWEETWATER ........................ 5.59 ........................ 12.60 ........................ ........................WYOMING .................................................................................................................................... TETON ................................... ........................ ........................ ........................ ........................ ........................WYOMING .................................................................................................................................... UINTA .................................... 20.12 13.49 7.44 1.96 1.99 WYOMING .................................................................................................................................... WASHAKIE ............................. 2.12 1.42 2.35 ........................ 3.95 WYOMING .................................................................................................................................... WESTON ................................ ........................ ........................ ........................ 8.37 ........................

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE 

Year State County Date FEMA No Incident Type 

2002 ..................................................................... Alabama .................................... Barbour ...................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Bibb ........................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Blount ........................................ 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Calhoun ..................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Cherokee .................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Cleburne .................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Cullman ..................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Dale ........................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... DeKalb ....................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Etowah ....................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Fayette ....................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 
252 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2002 ..................................................................... Alabama .................................... Franklin ..................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Greene ....................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Hale ........................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Henry ......................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Houston ..................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Jefferson .................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Lamar ........................................ 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Lawrence ................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Marion ....................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Marshall .................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Morgan ...................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Pickens ...................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Shelby ........................................ 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... St. Clair ..................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Talladega ................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Tuscaloosa ................................. 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Walker ........................................ 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alabama .................................... Winston ...................................... 11/14/02 ........... FEMA–1442–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Alaska ........................................ Aniak, Crooked Creek ................ 6/26/02 ............. FEMA–1423–DR ........ Flooding 2002 ..................................................................... Alaska ........................................ Chignik Bay area ...................... 12/04/02 ........... FEMA–1445–DR ........ Severe Winter Storms, Flooding, Coastal Erosion 

and Tidal Surge 

2002 ..................................................................... Alaska ........................................ Delta Greely Regional Educational Attendance Area. 11/08/02 ........... FEMA–1440–DR ........ Earthquake 2002 ..................................................................... Alaska ........................................ Ekwok and New Stuyahok in the 

Southwest Region REAA.

6/26/02 ............. FEMA–1423–DR ........ Flooding 

2002 ..................................................................... Alaska ........................................ Fairbanks North Star Borough .. 6/26/02 ............. FEMA–1423–DR ........ Flooding 2002 ..................................................................... Alaska ........................................ Fairbanks North Star Borough .. 11/08/02 ........... FEMA–1440–DR ........ Earthquake 2002 ..................................................................... Alaska ........................................ Kenai Peninsula Borough .......... 12/04/02 ........... FEMA–1445–DR ........ Severe Winter Storms, Flooding, Coastal Erosion 

and Tidal Surge 

2002 ..................................................................... Alaska ........................................ Kodiak Island Borough .............. 12/04/02 ........... FEMA–1445–DR ........ Severe Winter Storms, Flooding, Coastal Erosion 

and Tidal Surge 

2002 ..................................................................... Alaska ........................................ Kwethluk in the Lower 

Kuskokwim REAA.

6/26/02 ............. FEMA–1423–DR ........ Flooding 

2002 ..................................................................... Alaska ........................................ McGrath and Lime Village in 

the Iditarod REAA.

6/26/02 ............. FEMA–1423–DR ........ Flooding 
253 

2002 ..................................................................... Alaska ........................................ Red Devil and Sleetmute in the 

Kuspuk REAA.

6/26/02 ............. FEMA–1423–DR ........ Flooding 

2002 ..................................................................... Arizona ....................................... Apache ....................................... 6/25/02 ............. FEMA–1422–DR ........ Wildfires 2002 ..................................................................... Arizona ....................................... Coconino .................................... 6/25/02 ............. FEMA–1422–DR ........ Wildfires 2002 ..................................................................... Arizona ....................................... Fort Apache Indian Reservation 6/25/02 ............. FEMA–1422–DR ........ Wildfires 2002 ..................................................................... Arizona ....................................... Gila ............................................ 6/25/02 ............. FEMA–1422–DR ........ Wildfires 2002 ..................................................................... Arizona ....................................... Navajo ....................................... 6/25/02 ............. FEMA–1422–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Adams ....................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Alamosa ..................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Arapahoe ................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Archuleta ................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Baca .......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Bent ........................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Boulder ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Broomfield City and County ...... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Chaffee ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Cheyenne ................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Clear Creek ................................ 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Conejos ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Costilla ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Crowley ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Custer ........................................ 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Delta .......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Denver City and County ............ 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Dolores ....................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Douglas ..................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Eagle ......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... El Paso ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Elbert ......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Fremont ..................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Garfield ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Gilpin ......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Grand ......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Gunnison ................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Hinsdale .................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Huerfano .................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Jackson ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Jefferson .................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Kiowa ......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Kit Carson ................................. 6/19/02 ............. FEMA–1421–DR ........ Wildfires 
254 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2002 ..................................................................... Colorado .................................... La Plata ..................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Lake ........................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Larimer ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Las Animas ............................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Lincoln ....................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Mesa .......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Mineral ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Moffat ........................................ 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Montezuma ................................ 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Montrose .................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Otero .......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Ouray ......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Park ........................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Pitkin ......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Pueblo ........................................ 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Rio Blanco ................................. 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Rio Grande ................................ 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Routt .......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Saguache ................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... San Juan ................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... San Miguel ................................ 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Southern Ute Reservation ......... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Summit ...................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Teller .......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Ute Mountain Reservation ......... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Washington ................................ 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Weld ........................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Colorado .................................... Yuma ......................................... 6/19/02 ............. FEMA–1421–DR ........ Wildfires 2002 ..................................................................... Federated States of Micronesia Chuuk State .............................. 7/11/02 ............. FEMA–1427 .............. Tropical Storm Chata’an, including flooding, 

mudslides and landslides 

2002 ..................................................................... Guam ......................................... Territory of Guam ...................... 7/06/02 ............. FEMA–1426–DR ........ Typhoon Chata’an 2002 ..................................................................... Guam ......................................... Territory of Guam ...................... 12/08/02 ........... FEMA–1446–DR ........ Super Typhoon Pongsona 2002 ..................................................................... Illinois ........................................ Adams ....................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Alexander ................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Bond .......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Brown ........................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 
255 

2002 ..................................................................... Illinois ........................................ Calhoun ..................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Cass .......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Champaign ................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Christian .................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Clark .......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Clay ........................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Clinton ....................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Coles .......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Crawford .................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Cumberland ............................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ De Witt ...................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Douglas ..................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Edgar ......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Edwards ..................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Effingham .................................. 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Fayette ....................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Ford ........................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Franklin ..................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Fulton ........................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Gallatin ...................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Greene ....................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Hamilton .................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Hancock ..................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Hardin ........................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Iroquois ...................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Jackson ...................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Jasper ........................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Jefferson .................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Jersey ......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Johnson ...................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Lawrence ................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Logan ......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Macon ........................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Macoupin ................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Madison ..................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Marion ....................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Mason ........................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Massac ...................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ McDonough ................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Menard ...................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 
256 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2002 ..................................................................... Illinois ........................................ Monroe ....................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Montgomery ............................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Morgan ...................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Moultrie ..................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Perry .......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Piatt ........................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Pike ............................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Pope ........................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Pulaski ....................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Randolph ................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Richland .................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Saline ........................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Sangamon ................................. 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Schuyler ..................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Scott .......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Shelby ........................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ St. Clair ..................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Union ......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Vermilion ................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Wabash ...................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Washington, ............................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Wayne ........................................ 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ White ......................................... 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Illinois ........................................ Williamson ................................. 5/21/02 ............. FEMA–1416–DR ........ Severe Storms, Tornadoes, and Flooding 2002 ..................................................................... Indiana ...................................... Martin ........................................ 6/13/02 ............. FEMA–1418–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Indiana ...................................... Bartholomew .............................. 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Blackford ................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Brown ........................................ 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Daviess ...................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Dearborn .................................... 6/13/02 ............. FEMA–1418–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Indiana ...................................... Dearborn .................................... 6/13/02 ............. FEMA–1418–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Indiana ...................................... Decatur ...................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Delaware .................................... 9/25/02 ............. FEMA–1433–DR.2002 ..................................................................... Indiana ...................................... Fayette ....................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Franklin ..................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Gibson ....................................... 6/13/02 ............. FEMA–1418–DR ........ Severe Storms, Tornadoes and Flooding 
257 

2002 ..................................................................... Indiana ...................................... Gibson ....................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Grant ......................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Greene ....................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Hamilton .................................... 6/13/02 ............. FEMA–1418–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Indiana ...................................... Hamilton .................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Hancock ..................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Hendricks ................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Henry ......................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Jay ............................................. 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Johnson ...................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Knox ........................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Lawrence ................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Madison ..................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Marion ....................................... 6/13/02 ............. FEMA–1418–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Indiana ...................................... Marion ....................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Monroe ....................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Morgan ...................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Orange ....................................... 6/13/02 ............. FEMA–1418–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Indiana ...................................... Owen .......................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Pike ............................................ 6/13/02 ............. FEMA–1418–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Indiana ...................................... Pike ............................................ 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Posey ......................................... 6/13/02 ............. FEMA–1418–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Indiana ...................................... Posey ......................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Randolph ................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Rush .......................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Shelby ........................................ 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Sullivan ..................................... 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Tipton ........................................ 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Vanderburg ................................ 9/25/02 ............. FEMA–1433–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Indiana ...................................... Vigo ........................................... 6/13/02 ............. FEMA–1418–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Iowa ........................................... Allamakee .................................. 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Benton ....................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Buchanan .................................. 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Cedar ......................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Clayton ...................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Clinton ....................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Delaware .................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Des Moines ................................ 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Dubuque .................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Fayette ....................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 
258 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2002 ..................................................................... Iowa ........................................... Henry ......................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Iowa ........................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Jackson ...................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Johnson ...................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Jones .......................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Lee ............................................. 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Linn ........................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Louisa ........................................ 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Muscatine .................................. 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Scott .......................................... 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Iowa ........................................... Winneshiek ................................ 6/19/02 ............. FEMA–1420–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kansas ....................................... Allen .......................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Anderson .................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Barber ........................................ 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Bourbon ..................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Butler ......................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Chautauqua ............................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Coffey ........................................ 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Cowley ....................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Crawford .................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Douglas ..................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Elk ............................................. 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Franklin ..................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Greenwood ................................. 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Labette ...................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Linn ........................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Miami ........................................ 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Montgomery ............................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Neosho ....................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Osage ........................................ 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Sumner ...................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Wilson ........................................ 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kansas ....................................... Woodson .................................... 2/06/02 ............. FEMA–1402–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Kentucky .................................... Bath ........................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Bell ............................................ 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Bourbon ..................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 
259 

2002 ..................................................................... Kentucky .................................... Boyd ........................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Breckinridge .............................. 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Carter ........................................ 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Clay ........................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Crittenden .................................. 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Fleming ...................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Floyd .......................................... 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Grayson ...................................... 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Greenup ..................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Hancock ..................................... 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Hardin ........................................ 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Harlan ........................................ 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Henderson .................................. 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Hopkins ...................................... 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Knox ........................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Laurel ........................................ 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Laurel ........................................ 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Lawrence ................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Leslie ......................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Letcher ....................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Letcher ....................................... 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Lewis ......................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Marion ....................................... 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Martin ........................................ 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... McCreary .................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... McLean ...................................... 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Meade ........................................ 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Menifee ...................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Montgomery ............................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Morgan ...................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Nicholas ..................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Ohio ........................................... 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Perry .......................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Pike ............................................ 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Rockcastle ................................. 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Rowan ........................................ 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Kentucky .................................... Union ......................................... 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Webster ...................................... 5/07/02 ............. FEMA–1414–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Kentucky .................................... Whitley ....................................... 4/04/02 ............. FEMA–1407–DR ........ Severe Storms and Flooding 2002 ..................................................................... Louisiana ................................... Acadia ....................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 
260 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2002 ..................................................................... Louisiana ................................... Allen .......................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Ascension .................................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Assumption ................................ 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Avoyelles .................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Beauregard ................................ 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Calcasieu ................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Cameron .................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... East Baton Rouge ..................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... East Feliciana ........................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Evangeline ................................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Iberia ......................................... 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... Iberia ......................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Iberville ...................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Jefferson .................................... 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... Jefferson .................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Jefferson Davis .......................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Lafayette .................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Lafourche ................................... 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... Lafourche ................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Livingston .................................. 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... Livingston .................................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Orleans ...................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Orleans, ..................................... 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... Plaquemines .............................. 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... Plaquemines .............................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Pointe Coupee ........................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Rapides ..................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... St. Bernard ................................ 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... St. Bernard ................................ 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... St. Charles ................................ 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... St. Charles ................................ 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... St. Helena .................................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... St. James ................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... St. John the Baptist .................. 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... St. John the Baptist .................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... St. Landry .................................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 
261 

2002 ..................................................................... Louisiana ................................... St. Martin .................................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... St. Mary ..................................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... St. Tammany ............................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... St.Tammany ............................... 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... Tangipahoa ................................ 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... Tangipahoa ................................ 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Terrebonne ................................. 9/27/02 ............. FEMA–1435–DR ........ Tropical Storm Isidore 2002 ..................................................................... Louisiana ................................... Terrebonne ................................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Vermillion .................................. 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... Washington ................................ 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Louisiana ................................... West Baton Rouge ..................... 10/03/02 ........... FEMA–1437–DR ........ Hurricane Lili 2002 ..................................................................... Maryland .................................... Calvert ....................................... 5/01/02 ............. FEMA–1409–DR ........ Tornado 2002 ..................................................................... Maryland .................................... Charles ...................................... 5/01/02 ............. FEMA–1409–DR ........ Tornado 2002 ..................................................................... Maryland .................................... Dorchester ................................. 5/01/02 ............. FEMA–1409–DR ........ Tornado 2002 ..................................................................... Minnesota .................................. Becker ........................................ 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Minnesota .................................. Beltrami ..................................... 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Minnesota .................................. Clay ........................................... 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Minnesota .................................. Clearwater ................................. 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Minnesota .................................. Itasca ........................................ 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Minnesota .................................. Kittson ....................................... 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Minnesota .................................. McLeod ...................................... 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Minnesota .................................. Pennington ................................ 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Minnesota .................................. Polk ............................................ 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Minnesota .................................. Roseau ....................................... 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Minnesota .................................. Wright ........................................ 6/14/02 ............. FEMA–1419–DR ........ Severe Storms, Flooding and Tornadoes 2002 ..................................................................... Mississippi ................................ Amite ......................................... 10/01/02 ........... FEMA–1436 .............. Tropical Storm Isidore 2002 ..................................................................... Mississippi ................................ Clay ........................................... 11/14/02 ........... FEMA–1443–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Mississippi ................................ Hancock ..................................... 10/01/02 ........... FEMA–1436 .............. Tropical Storm Isidore 2002 ..................................................................... Mississippi ................................ Harrison ..................................... 10/01/02 ........... FEMA–1436 .............. Tropical Storm Isidore 2002 ..................................................................... Mississippi ................................ Jackson ...................................... 10/01/02 ........... FEMA–1436 .............. Tropical Storm Isidore 2002 ..................................................................... Mississippi ................................ Lowndes ..................................... 11/14/02 ........... FEMA–1443–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Mississippi ................................ Monroe ....................................... 11/14/02 ........... FEMA–1443–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Mississippi ................................ Noxubee ..................................... 11/14/02 ........... FEMA–1443–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Mississippi ................................ Oktibbeha .................................. 11/14/02 ........... FEMA–1443–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Mississippi ................................ Pearl River ................................. 10/01/02 ........... FEMA–1436 .............. Tropical Storm Isidore 2002 ..................................................................... Mississippi ................................ Pike ............................................ 10/01/02 ........... FEMA–1436 .............. Tropical Storm Isidore 2002 ..................................................................... Mississippi ................................ Stone ......................................... 10/01/02 ........... FEMA–1436 .............. Tropical Storm Isidore 2002 ..................................................................... Missouri ..................................... Adair .......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Audrain ...................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Barton ........................................ 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 
262 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2002 ..................................................................... Missouri ..................................... Bates ......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Benton ....................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Bollinger .................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Boone ......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Buchanan .................................. 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Butler ......................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Caldwell ..................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Cape Girardeau ......................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Carroll ........................................ 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Carter ........................................ 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Cass .......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Cedar ......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Chariton ..................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Clair ........................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Clark .......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Clay ........................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Clinton ....................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Cooper ....................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Crawford .................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Daviess ...................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Dent ........................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Douglas ..................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Dunklin ...................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Grundy ....................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Henry ......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Howard ...................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Howell ........................................ 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Iron ............................................ 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Jackson ...................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Jefferson .................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Johnson ...................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Knox ........................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Lafayette .................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Lewis ......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Linn ........................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Livingston .................................. 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 
263 

2002 ..................................................................... Missouri ..................................... Macon ........................................ 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Madison ..................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Marion ....................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Monroe ....................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Morgan ...................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Oregon ....................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Ozark ......................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Perry .......................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Pettis ......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Platte ......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Ralls .......................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Randolph ................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Ray ............................................ 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Reynolds .................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Ripley ......................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Saline ........................................ 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Scotland .................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Shannon .................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Shelby ........................................ 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... St Francois ................................ 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... St Geneieve ............................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... St. Sullivan ................................ 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Stoddard .................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Texas ......................................... 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Missouri ..................................... Vernon ....................................... 2/06/02 ............. FEMA–1403–DR ........ Severe Winter Ice Storm 2002 ..................................................................... Missouri ..................................... Wayne ........................................ 5/06/02 ............. FEMA–1412–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... New York ................................... Clinton ....................................... 5/16/02 ............. FEMA–1415–DR ........ Earthquake 2002 ..................................................................... New York ................................... Essex ......................................... 5/16/02 ............. FEMA–1415–DR ........ Earthquake 2002 ..................................................................... Northern Mariana Islands ......... Island of Rota ........................... 12/11/02 ........... FEMA–1447–DR ........ Super Typhoon Pongsona 2002 ..................................................................... Ohio ........................................... Cuyahoga ................................... 11/18/02 ........... FEMA–1444–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Ohio ........................................... Hancock ..................................... 11/18/02 ........... FEMA–1444–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Ohio ........................................... Ottawa ....................................... 11/18/02 ........... FEMA–1444–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Ohio ........................................... Paulding .................................... 11/18/02 ........... FEMA–1444–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Ohio ........................................... Putnam ...................................... 11/18/02 ........... FEMA–1444–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Ohio ........................................... Seneca ....................................... 11/18/02 ........... FEMA–1444–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Ohio ........................................... Summit ...................................... 11/18/02 ........... FEMA–1444–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Ohio ........................................... Van Wert .................................... 11/18/02 ........... FEMA–1444–DR ........ Severe Storms and Tornadoes 2002 ..................................................................... Oklahoma .................................. Alfalfa ........................................ 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Beaver ....................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Beckham .................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 
264 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2002 ..................................................................... Oklahoma .................................. Blaine ........................................ 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Caddo ........................................ 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Canadian ................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Cimarron .................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Cleveland ................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Comanche .................................. 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Creek ......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Custer ........................................ 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Dewey ........................................ 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Ellis ........................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Garfield ...................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Garvin ........................................ 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Grady ......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Grant ......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Greer .......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Harmon ...................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Harper ........................................ 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Jackson ...................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Kay ............................................. 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Kingfisher .................................. 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Kiowa ......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Lincoln ....................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Logan ......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Major ......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. McClain ..................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Mills ........................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Noble ......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Nowata ...................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Oklahoma .................................. 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Osage ........................................ 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Pawnee ...................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Payne ......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Pottawatomie ............................. 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Roger ......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Rogers ....................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Stephens .................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 
265 

2002 ..................................................................... Oklahoma .................................. Texas ......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Tillman ...................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Tulsa .......................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Washington ................................ 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Washita ..................................... 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Woods ........................................ 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Oklahoma .................................. Woodward .................................. 2/01/02 ............. FEMA–1401–DR ........ Ice Storm 2002 ..................................................................... Tennessee .................................. and ............................................ 4/05/02 ............. FEMA–1408–DR ........ Severe Storms and Flooding 2002 ..................................................................... Tennessee .................................. Anderson .................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Bedford ...................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Bledsoe ...................................... 4/05/02 ............. FEMA–1408–DR ........ Severe Storms and Flooding 2002 ..................................................................... Tennessee .................................. Bledsoe ...................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Blount ........................................ 4/05/02 ............. FEMA–1408–DR ........ Severe Storms and Flooding 2002 ..................................................................... Tennessee .................................. Carroll ........................................ 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Claiborne ................................... 4/05/02 ............. FEMA–1408–DR ........ Severe Storms and Flooding 2002 ..................................................................... Tennessee .................................. Cocke ......................................... 4/05/02 ............. FEMA–1408–DR ........ Severe Storms and Flooding 2002 ..................................................................... Tennessee .................................. Coffee ........................................ 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Crockett ..................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Cumberland ............................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Fentress ..................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Gibson ....................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Hancock ..................................... 4/05/02 ............. FEMA–1408–DR ........ Severe Storms and Flooding 2002 ..................................................................... Tennessee .................................. Hawkins ..................................... 4/05/02 ............. FEMA–1408–DR ........ Severe Storms and Flooding 2002 ..................................................................... Tennessee .................................. Henderson .................................. 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Loudon ....................................... 4/05/02 ............. FEMA–1408–DR ........ Severe Storms and Flooding 2002 ..................................................................... Tennessee .................................. Madison ..................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Marshall .................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Montgomery ............................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Morgan ...................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Roane ........................................ 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Rutherford ................................. 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Scott .......................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Sevier ......................................... 4/05/02 ............. FEMA–1408–DR ........ Severe Storms and Flooding 2002 ..................................................................... Tennessee .................................. Sumner ...................................... 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Tipton ........................................ 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Tennessee .................................. Van Buren ................................. 11/13/02 ........... FEMA–1441–DR ........ Severe Storms, Tornadoes and Flooding 2002 ..................................................................... Texas ......................................... Bexar ......................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Aransas ..................................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Atascosa .................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Bandera ..................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 
266 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2002 ..................................................................... Texas ......................................... Bee ............................................ 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Blanco ....................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Brazoria ..................................... 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... Brazoria ..................................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Brown ........................................ 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Burnet ........................................ 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Caldwell ..................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Calhoun ..................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Callahan .................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Cameron .................................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Coleman .................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Comal ........................................ 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... DeWitt ........................................ 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Dimmit ....................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Duval ......................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Eastland .................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Fort Bend ................................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Frio ............................................ 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Frio ............................................ 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... Galveston ................................... 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... Gillespie ..................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Goliad ........................................ 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Gonzales .................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Guadalupe ................................. 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Hardin ........................................ 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Harris ......................................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Hays ........................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Jasper ........................................ 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Jefferson .................................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Jim Wells ................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Jim Wells ................................... 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... Jim Wells ................................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Karnes ....................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Kendall ...................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Kerr ............................................ 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Kleberg ...................................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 
267 

2002 ..................................................................... Texas ......................................... La Salle ..................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... La Salle ..................................... 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... Liberty ........................................ 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Live Oak .................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Live Oak .................................... 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... Matagorda ................................. 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... McMullen ................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Medina ....................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Montgomery ............................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Nueces ....................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Nueces ....................................... 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... Nueces ....................................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Orange ....................................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Real ........................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... San Jacinto ................................ 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... San Patricio ............................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... San Patricio ............................... 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... San Patricio ............................... 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Taylor ......................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Travis ......................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Uvalde ....................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Victoria ...................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Walker ........................................ 11/05/02 ........... FEMA–1439–DR ........ severe storms, tornadoes, and flooding 2002 ..................................................................... Texas ......................................... Webb .......................................... 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... Wharton ..................................... 9/26/02 ............. FEMA–1434–DR ........ Tropical Storm Fay 2002 ..................................................................... Texas ......................................... Wilson ........................................ 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Texas ......................................... Zavala ....................................... 7/04/02 ............. FEMA–1425–DR ........ Severe Storms and Flooding 2002 ..................................................................... Vermont ..................................... Caledonia .................................. 7/12/02 ............. FEMA–1428–DR ........ Severe storms and flooding 2002 ..................................................................... Vermont ..................................... Franklin ..................................... 7/12/02 ............. FEMA–1428–DR ........ Severe storms and flooding 2002 ..................................................................... Vermont ..................................... Lamoille ..................................... 7/12/02 ............. FEMA–1428–DR ........ Severe storms and flooding 2002 ..................................................................... Vermont ..................................... Orleans ...................................... 7/12/02 ............. FEMA–1428–DR ........ Severe storms and flooding 2002 ..................................................................... Virginia ...................................... Buchanan .................................. 5/05/02 ............. FEMA–1411–DR ........ Severe Storms and Tornado 2002 ..................................................................... Virginia ...................................... city of Norton ............................ 4/02/02 ............. FEMA–1406–DR ........ Severe Storms and Flooding 2002 ..................................................................... Virginia ...................................... Dickenson .................................. 4/02/02 ............. FEMA–1406–DR ........ Severe Storms and Flooding 2002 ..................................................................... Virginia ...................................... Lee ............................................. 4/02/02 ............. FEMA–1406–DR ........ Severe Storms and Flooding 2002 ..................................................................... Virginia ...................................... Russell ....................................... 4/02/02 ............. FEMA–1406–DR ........ Severe Storms and Flooding 2002 ..................................................................... Virginia ...................................... Scott .......................................... 4/02/02 ............. FEMA–1406–DR ........ Severe Storms and Flooding 2002 ..................................................................... Virginia ...................................... Smyth ........................................ 4/02/02 ............. FEMA–1406–DR ........ Severe Storms and Flooding 2002 ..................................................................... Virginia ...................................... Tazewell ..................................... 4/02/02 ............. FEMA–1406–DR ........ Severe Storms and Flooding 2002 ..................................................................... Virginia ...................................... Tazewell ..................................... 5/05/02 ............. FEMA–1411–DR ........ Severe Storms and Tornado 
268 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2002 ..................................................................... Virginia ...................................... Washington ................................ 4/02/02 ............. FEMA–1406–DR ........ Severe Storms and Flooding 2002 ..................................................................... Virginia ...................................... Wise ........................................... 4/02/02 ............. FEMA–1406–DR ........ Severe Storms and Flooding 2002 ..................................................................... West Virginia ............................. McDowell ................................... 5/05/02 ............. FEMA–1410–DR ........ Severe Storms, Flooding, and Landslides 2002 ..................................................................... West Virginia ............................. Mercer ........................................ 5/05/02 ............. FEMA–1410–DR ........ Severe Storms, Flooding, and Landslides 2002 ..................................................................... West Virginia ............................. Mingo ......................................... 5/05/02 ............. FEMA–1410–DR ........ Severe Storms, Flooding, and Landslides 2002 ..................................................................... West Virginia ............................. Wyoming .................................... 5/05/02 ............. FEMA–1410–DR ........ Severe Storms, Flooding, and Landslides 2002 ..................................................................... Wisconsin .................................. Barron ........................................ 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Burnett ...................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Chippewa ................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Clark .......................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Dunn .......................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Langlade .................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Lincoln ....................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Marathon ................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Polk ............................................ 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Portage ...................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Price .......................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Rusk .......................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Sawyer ....................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Shawano .................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. St. Croix ..................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Taylor ......................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Washburn .................................. 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Waupaca .................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2002 ..................................................................... Wisconsin .................................. Wood .......................................... 9/10/02 ............. FEMA–1432–DR ........ Severe storms, tornadoes and flooding 2003 ..................................................................... Alabama .................................... Baldwin ..................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Bibb ........................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Blount ........................................ 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Calhoun ..................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Clarke ........................................ 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Colbert ....................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Cullman ..................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... DeKalb ....................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Escambia ................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Etowah ....................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Jackson ...................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 
269 

2003 ..................................................................... Alabama .................................... Jefferson .................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Madison ..................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Marshall .................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Mobile ........................................ 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Monroe ....................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Morgan ...................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Shelby ........................................ 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... St.Clair ...................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Talladega ................................... 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Tuscaloosa ................................. 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Walker ........................................ 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alabama .................................... Washington ................................ 5/12/03 ............. FEMA–1466–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Alaska ........................................ Kenai Peninsula Borough .......... 4/26/03 ............. FEMA–1461–DR ........ Severe winter storm, including high winds and 

freezing temperatures 

2003 ..................................................................... Alaska ........................................ Matanuska-Susitna Borough ..... 4/26/03 ............. FEMA–1461–DR ........ Severe winter storm, including high winds and 

freezing temperatures 

2003 ..................................................................... Alaska ........................................ Municipality of Anchorage ........ 4/26/03 ............. FEMA–1461–DR ........ Severe winter storm, including high winds and 

freezing temperatures 

2003 ..................................................................... American Samoa ....................... The Island of Tutuila ................ 6/06/03 ............. FEMA–1473–DR ........ Heavy Rainfall, Flooding, Landslides, and 

Mudslides 

2003 ..................................................................... Arkansas .................................... Benton ....................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Chicot ........................................ 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Cleburne .................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Columbia ................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Conway ...................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Craighead .................................. 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Crittenden .................................. 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Cross ......................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Faulkner ..................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Fulton ........................................ 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Jackson ...................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Lonoke ....................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Nevada ...................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Perry .......................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Phillips ...................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Poinsett ..................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... St. Francis ................................. 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... White ......................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Arkansas .................................... Woodruff .................................... 6/06/03 ............. FEMA–1472–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... California ................................... Los Angeles ............................... 10/27/03 ........... FEMA–1498–DR ........ Wildfires 
270 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... California ................................... Riverside .................................... 10/27/03 ........... FEMA–1498–DR ........ Wildfires 2003 ..................................................................... California ................................... San Bernardino ......................... 10/27/03 ........... FEMA–1498–DR ........ Wildfires 2003 ..................................................................... California ................................... San Diego .................................. 10/27/03 ........... FEMA–1498–DR ........ Wildfires 2003 ..................................................................... California ................................... Ventura ...................................... 10/27/03 ........... FEMA–1498–DR ........ Wildfires 2003 ..................................................................... Commonwealth of Puerto Rico .. Aibonito ..................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Arroyo ......................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Cabo Rojo .................................. 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Can?vanas ................................. 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Fajardo ...................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Guμnica .................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Guayama ................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Juana Diaz ................................. 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Lajas .......................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Loiza .......................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Luquillo ...................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Maunabo .................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Naguabo .................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Naranjito .................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Patillas ...................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Rφo Grande ............................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 
271 

2003 ..................................................................... Commonwealth of Puerto Rico .. Salinas ...................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Santa Isabel .............................. 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Toa Baja .................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Yabucoa ..................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Commonwealth of Puerto Rico .. Yauco ......................................... 11/21/03 ........... FEMA–1501–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2003 ..................................................................... Delaware .................................... New Castle ................................ 9/23/03 ............. FEMA–1495–DR ........ Tropical Storm Henri 2003 ..................................................................... Delware ...................................... Kent ........................................... 9/20/03 ............. FEMA–1494–DR ........ Hurricane Isabel 2003 ..................................................................... Delware ...................................... New Castle ................................ 9/20/03 ............. FEMA–1494–DR ........ Hurricane Isabel 2003 ..................................................................... Delware ...................................... Sussex ....................................... 9/20/03 ............. FEMA–1494–DR ........ Hurricane Isabel 2003 ..................................................................... District of Columbia .................. District of Columbia .................. 9/20/03 ............. FEMA–1493–DR ........ Hurricane Isabel 2003 ..................................................................... Federated States of Micronesia Island of Eauripik ..................... 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Federated States of Micronesia Island of Elato .......................... 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Federated States of Micronesia Island of Fais ............................ 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Federated States of Micronesia Island of Faraulap .................... 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Federated States of Micronesia Island of Ifalik .......................... 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Federated States of Micronesia Lamotrek .................................... 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Federated States of Micronesia Namonuito Atoll ......................... 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Federated States of Micronesia Satawal ..................................... 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Federated States of Micronesia the Hall Islands ........................ 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Federated States of Micronesia Ulithi .......................................... 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Federated States of Micronesia Western Islands within Chuuk 

State.

12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 

2003 ..................................................................... Federated States of Micronesia Woleai within Yap State ........... 12/19/03 ........... FEMA–1504–DR ........ Typhoon Lupit 2003 ..................................................................... Florida ....................................... Miami-Dade County ................... 4/25/03 ............. FEMA–1460–DR ........ Severe storms and tornadoes 2003 ..................................................................... Illinois ........................................ Adams ....................................... 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Alexander ................................... 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Brown ........................................ 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Fulton ........................................ 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Hancock ..................................... 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Mason ........................................ 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Massac ...................................... 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Pope ........................................... 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Pulaski ....................................... 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Schuyler ..................................... 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Tazewell ..................................... 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 
272 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... Illinois ........................................ Union ......................................... 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Illinois ........................................ Woodford .................................... 5/15/03 ............. FEMA–1469–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Indiana ...................................... Adams ....................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Allen .......................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Benton ....................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Blackford ................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Blackford ................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Boone ......................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Boone ......................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Carroll ........................................ 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Cass .......................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Clay ........................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Clay ........................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Clinton ....................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Delaware .................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Delaware .................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Fountain .................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Fulton ........................................ 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Grant ......................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Grant ......................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Greene ....................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Hamilton .................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Hamilton .................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Hancock ..................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Hancock ..................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Hendricks ................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Henry ......................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Henry ......................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Howard ...................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Huntington ................................. 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Jasper ........................................ 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Jay ............................................. 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Jay ............................................. 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Johnson ...................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Kosciusko ................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Lake ........................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 
273 

2003 ..................................................................... Indiana ...................................... Madison ..................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Madison ..................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Marion ....................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Marion ....................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Miami ........................................ 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Monroe ....................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Montgomery ............................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Montgomery ............................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Morgan ...................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Morgan ...................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Newton ....................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Noble ......................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Owen .......................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Parke ......................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Porter ......................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Pulaski ....................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Putnam ...................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Randolph ................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Randolph ................................... 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Shelby ........................................ 9/05/03 ............. FEMA–1487–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Tippecanoe ................................ 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Tipton ........................................ 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Vanderburgh .............................. 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Vigo ........................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Wabash ...................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Warren ....................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Wayne ........................................ 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Wells .......................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... White ......................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Indiana ...................................... Whitley ....................................... 7/11/03 ............. FEMA–1476–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kansas ....................................... Allen .......................................... 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kansas ....................................... Cherokee .................................... 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kansas ....................................... Crawford .................................... 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kansas ....................................... Haskell ....................................... 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kansas ....................................... Labette ...................................... 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kansas ....................................... Leavenworth .............................. 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kansas ....................................... Meade ........................................ 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kansas ....................................... Miami ........................................ 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kansas ....................................... Neosho ....................................... 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kansas ....................................... Seward ....................................... 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 
274 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... Kansas ....................................... Wyandotte .................................. 5/06/03 ............. FEMA–1462–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Kentucky .................................... Anderson .................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Boyd ........................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Boyd ........................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Boyle .......................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Breathitt .................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Breathitt .................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Breckenridge .............................. 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Bullitt ........................................ 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Caldwell ..................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Carter ........................................ 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Carter ........................................ 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Carter ........................................ 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Clarke ........................................ 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Clay ........................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Crittenden .................................. 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Elliott ......................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 
275 

2003 ..................................................................... Kentucky .................................... Elliott ......................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Estill .......................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Fayette ....................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Fleming ...................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Floyd .......................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Floyd .......................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Garrard ...................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Graves ....................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Grayson ...................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Greenup ..................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Greenup ..................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Greenup ..................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Hardin ........................................ 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Harlan ........................................ 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Hart ........................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Henderson .................................. 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Hopkins ...................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Jefferson .................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 
276 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... Kentucky .................................... Jessamine .................................. 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Johnson ...................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Johnson ...................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Knott .......................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Knott .......................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Knox ........................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Knox ........................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Larue ......................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Lawrence ................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Lawrence ................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Leslie ......................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Leslie ......................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Letcher ....................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Letcher ....................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Lewis ......................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 
277 

2003 ..................................................................... Kentucky .................................... Lewis ......................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Lewis ......................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Madison ..................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Magoffin .................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Martin ........................................ 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Martin ........................................ 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Mason ........................................ 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... McLean ...................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Meade ........................................ 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Mercer ........................................ 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Nelson ........................................ 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Owsley ....................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Owsley ....................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Owsley ....................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Perry .......................................... 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 

2003 ..................................................................... Kentucky .................................... Perry .......................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Perry .......................................... 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Pike ............................................ 3/14/03 ............. FEMA–1454–DR ........ Severe winter ice and snow storms, heavy rain, 

flooding, tornadoes, and mud and rock slides 
278 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... Kentucky .................................... Pike ............................................ 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Rowan ........................................ 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Rowan ........................................ 7/02/03 ............. FEMA–1475–DR ........ Severe Storms, Flooding, Mud and Rock Slides, 

and Tornadoes 

2003 ..................................................................... Kentucky .................................... Union ......................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Washington ................................ 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Webster ...................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Kentucky .................................... Woodford .................................... 6/03/03 ............. FEMA–1471–DR ........ Severe storms, flooding, mud and rock slides, 

and tornadoes 

2003 ..................................................................... Maryland .................................... Allegany ..................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Anne .......................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Anne’s ........................................ 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Arundel ...................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Baltimore ................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Calvert ....................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Caroline ..................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Carroll ........................................ 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Cecil .......................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Charles ...................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... City of Baltimore ....................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Dorchester ................................. 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Frederick .................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Garrett ....................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... George’s ..................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Harford ...................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Howard ...................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Kent ........................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Mary’s ........................................ 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Montgomery ............................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Prince ........................................ 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Queen ........................................ 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 
279 

2003 ..................................................................... Maryland .................................... Somerset .................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... St ............................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Talbot ........................................ 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Washington ................................ 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Wicomico ................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Maryland .................................... Worcester ................................... 9/18/03 ............. FEMA–1492–DR ........ Hurricane Isabel 2003 ..................................................................... Mississippi ................................ Amite ......................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Attala ......................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Calhoun ..................................... 5/23/03 ............. FEMA–1470–DR ........ Severe Storms, Tornadoes and High Winds 2003 ..................................................................... Mississippi ................................ Chickasaw ................................. 5/23/03 ............. FEMA–1470–DR ........ Severe Storms, Tornadoes and High Winds 2003 ..................................................................... Mississippi ................................ Claiborne ................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Clarke ........................................ 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Clay ........................................... 5/23/03 ............. FEMA–1470–DR ........ Severe Storms, Tornadoes and High Winds 2003 ..................................................................... Mississippi ................................ Copiah ....................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Davis ......................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Franklin ..................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Hinds ......................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Holmes ....................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Issaquena .................................. 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Itawamba .................................. 5/23/03 ............. FEMA–1470–DR ........ Severe Storms, Tornadoes and High Winds 2003 ..................................................................... Mississippi ................................ Jasper ........................................ 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Jefferson .................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Jefferson .................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Kemper ...................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Lauderdale ................................. 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Lawrence ................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Leake ......................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Lee ............................................. 5/23/03 ............. FEMA–1470–DR ........ Severe Storms, Tornadoes and High Winds 2003 ..................................................................... Mississippi ................................ Lincoln ....................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Lowndes ..................................... 5/23/03 ............. FEMA–1470–DR ........ Severe Storms, Tornadoes and High Winds 2003 ..................................................................... Mississippi ................................ Madison ..................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Marion ....................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Monroe ....................................... 5/23/03 ............. FEMA–1470–DR ........ Severe Storms, Tornadoes and High Winds 2003 ..................................................................... Mississippi ................................ Neshoba ..................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Newton ....................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Pearl .......................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Pike ............................................ 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Pontotoc ..................................... 5/23/03 ............. FEMA–1470–DR ........ Severe Storms, Tornadoes and High Winds 2003 ..................................................................... Mississippi ................................ Rankin ....................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ River .......................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 
280 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... Mississippi ................................ Scott .......................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Simpson ..................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Smith ......................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Walthall ..................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Warren ....................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Wayne ........................................ 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Mississippi ................................ Webster ...................................... 5/23/03 ............. FEMA–1470–DR ........ Severe Storms, Tornadoes and High Winds 2003 ..................................................................... Mississippi ................................ Yazoo ......................................... 4/23/03 ............. FEMA–1459–DR ........ Severe Storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Barry .......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Barton ........................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Bates ......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Benton ....................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Bollinger .................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Buchanan .................................. 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Camden ..................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Cape .......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Cass .......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Cedar ......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Christian .................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Clair ........................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Clay ........................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Clinton ....................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Cooper ....................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Crawford .................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Dade .......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Dallas ........................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Dent ........................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Douglas ..................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Francois ..................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Franklin ..................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Gasconade ................................. 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Genevieve .................................. 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Girardeau ................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Greene ....................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Henry ......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Hickory ....................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 
281 

2003 ..................................................................... Missouri ..................................... Iron ............................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Jackson ...................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Jasper ........................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Jefferson .................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Johnson ...................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Knox ........................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Laclede ...................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Lafayette .................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Lawrence ................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Louis .......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Marion ....................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... McDonald ................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Miller ......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Monroe ....................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Morgan ...................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Newton ....................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Osage ........................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Perry .......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Pettis ......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Phelps ........................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Platte ......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Polk ............................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Pulaski ....................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Ray ............................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Saint .......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Saint .......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Sainte ........................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Saline ........................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Scott .......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... St ............................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Stoddard .................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Stone ......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Taney ......................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Vernon ....................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Washington ................................ 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Missouri ..................................... Webster ...................................... 5/06/03 ............. FEMA–1463–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... New York ................................... Allegany ..................................... 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Cattaraugus .............................. 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Cayuga ...................................... 5/12/03 ............. FEMA–1467–DR ........ Ice Storm 2003 ..................................................................... New York ................................... Chemung ................................... 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 
282 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... New York ................................... Columbia ................................... 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Delaware .................................... 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Fulton ........................................ 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Greene ....................................... 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Livingston .................................. 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Monroe ....................................... 5/12/03 ............. FEMA–1467–DR ........ Ice Storm 2003 ..................................................................... New York ................................... Montgomery ............................... 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Oneida ....................................... 5/12/03 ............. FEMA–1467–DR ........ Ice Storm 2003 ..................................................................... New York ................................... Onondaga .................................. 5/12/03 ............. FEMA–1467–DR ........ Ice Storm 2003 ..................................................................... New York ................................... Ontario ....................................... 5/12/03 ............. FEMA–1467–DR ........ Ice Storm 2003 ..................................................................... New York ................................... Ontario ....................................... 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Oswego ...................................... 5/12/03 ............. FEMA–1467–DR ........ Ice Storm 2003 ..................................................................... New York ................................... Rensselaer ................................. 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Schuyler ..................................... 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Seneca ....................................... 5/12/03 ............. FEMA–1467–DR ........ Ice Storm 2003 ..................................................................... New York ................................... Steuben ..................................... 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... New York ................................... Wayne ........................................ 5/12/03 ............. FEMA–1467–DR ........ Ice Storm 2003 ..................................................................... New York ................................... Yates ......................................... 8/29/03 ............. FEMA–1486–DR ........ Severe Storms, Flooding, and Tornadoes 2003 ..................................................................... North Carolina ........................... Beaufort ..................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Bertie ......................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Bladen ....................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Brunswick .................................. 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Camden ..................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Carteret ..................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Chowan ...................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Columbus .................................. 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Craven ....................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Cumberland ............................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Currituck .................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Dare ........................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Davidson .................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Duplin ........................................ 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Durham ...................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Edgecombe ................................ 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Franklin ..................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Gates ......................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 
283 

2003 ..................................................................... North Carolina ........................... Granville .................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Greene ....................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Halifax ....................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Hanover ..................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Harnett ...................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Hertford ..................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Hyde ........................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Johnston .................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Jones .......................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Lenoir ......................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Martin ........................................ 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Nash .......................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... New ............................................ 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Northampton .............................. 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Onslow ....................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Pamlico ...................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Pasquotank ................................ 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Pender ....................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Perquimans ............................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Person ........................................ 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Pitt ............................................. 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Robeson ..................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Sampson .................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Tyrrell ......................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Vance ......................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Wake .......................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Warren ....................................... 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Washington ................................ 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Wayne ........................................ 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... North Carolina ........................... Wilson ........................................ 9/18/03 ............. FEMA–1490–DR ........ Hurricane Isabel 2003 ..................................................................... Ohio ........................................... Adams ....................................... 3/14/03 ............. FEMA–1453–DR ........ Severe Winter Storm 2003 ..................................................................... Ohio ........................................... Auglaize ..................................... 7/15/03 ............. FEMA–1478–DR ........ Severe Storms and Flooding 2003 ..................................................................... Ohio ........................................... Carroll ........................................ 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Columbiana ............................... 7/15/03 ............. FEMA–1478–DR ........ Severe Storms and Flooding 2003 ..................................................................... Ohio ........................................... Columbiana ............................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Crawford .................................... 7/15/03 ............. FEMA–1478–DR ........ Severe Storms and Flooding 2003 ..................................................................... Ohio ........................................... Cuyahoga ................................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 
284 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... Ohio ........................................... Darke ......................................... 7/15/03 ............. FEMA–1478–DR ........ Severe Storms and Flooding 2003 ..................................................................... Ohio ........................................... Franklin ..................................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Jackson ...................................... 3/14/03 ............. FEMA–1453–DR ........ Severe Winter Storm 2003 ..................................................................... Ohio ........................................... Jefferson .................................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Lawrence ................................... 3/14/03 ............. FEMA–1453–DR ........ Severe Winter Storm 2003 ..................................................................... Ohio ........................................... Logan ......................................... 7/15/03 ............. FEMA–1478–DR ........ Severe Storms and Flooding 2003 ..................................................................... Ohio ........................................... Mahoning ................................... 7/15/03 ............. FEMA–1478–DR ........ Severe Storms and Flooding 2003 ..................................................................... Ohio ........................................... Mahoning ................................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Medina ....................................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Mercer ........................................ 7/15/03 ............. FEMA–1478–DR ........ Severe Storms and Flooding 2003 ..................................................................... Ohio ........................................... Pike ............................................ 3/14/03 ............. FEMA–1453–DR ........ Severe Winter Storm 2003 ..................................................................... Ohio ........................................... Pike ............................................ 7/15/03 ............. FEMA–1478–DR ........ Severe Storms and Flooding 2003 ..................................................................... Ohio ........................................... Portage ...................................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Richland .................................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Scioto ......................................... 3/14/03 ............. FEMA–1453–DR ........ Severe Winter Storm 2003 ..................................................................... Ohio ........................................... Shelby ........................................ 7/15/03 ............. FEMA–1478–DR ........ Severe Storms and Flooding 2003 ..................................................................... Ohio ........................................... Stark .......................................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Summit ...................................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Trumbull .................................... 8/01/03 ............. FEMA–1484–DR ........ Tornadoes, Flooding, Severe Storms, and High 

Winds 

2003 ..................................................................... Ohio ........................................... Van Wert .................................... 7/15/03 ............. FEMA–1478–DR ........ Severe Storms and Flooding 2003 ..................................................................... Oklahoma .................................. Canadian ................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Carter ........................................ 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Cherokee .................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Cleveland ................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Creek ......................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Delaware .................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Garvin ........................................ 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 
285 

2003 ..................................................................... Oklahoma .................................. Grady ......................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Kay ............................................. 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Kingfisher .................................. 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Lincoln ....................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Logan ......................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. McClain ..................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Mills ........................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Muskogee ................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Nowata ...................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Okfuskee .................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Oklahoma .................................. 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Okmulgee ................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Osage ........................................ 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Pontotoc ..................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Pottawatomie ............................. 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Roger ......................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Seminole .................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Texas ......................................... 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Oklahoma .................................. Washington ................................ 5/10/03 ............. FEMA–1465–DR ........ Severe storms and tornadoes 2003 ..................................................................... Pennsylvania ............................. Blair ........................................... 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Pennsylvania ............................. Chester ...................................... 9/26/03 ............. FEMA–1497–DR ........ Tropical Storms Henri and Isabel, and related 

severe storms and flooding 

2003 ..................................................................... Pennsylvania ............................. Crawford .................................... 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Pennsylvania ............................. Lackawanna .............................. 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Pennsylvania ............................. Lawrence ................................... 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Pennsylvania ............................. McKean ...................................... 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Pennsylvania ............................. Mercer ........................................ 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Pennsylvania ............................. Potter ......................................... 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Pennsylvania ............................. Tioga .......................................... 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Pennsylvania ............................. Venango ..................................... 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Pennsylvania ............................. Warren ....................................... 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Pennsylvania ............................. Wayne ........................................ 8/23/03 ............. FEMA–1485–DR ........ Severe Storms, Tornadoes, and Flooding 2003 ..................................................................... Tennessee .................................. Anderson .................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Bedford ...................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Benton ....................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Bledsoe ...................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Blount ........................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Bradley ...................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Cannon ...................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Carroll ........................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 
286 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... Tennessee .................................. Cheatham .................................. 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Chester ...................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Cocke ......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Coffee ........................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Crockett ..................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Cumberland ............................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Davidson .................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Decatur ...................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. DeKalb ....................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Dickson ...................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Dyer ........................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Fayette ....................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Fayette ....................................... 7/29/03 ............. FEMA–1482–DR ........ Severe storms, high winds, and heavy rain 2003 ..................................................................... Tennessee .................................. Gibson ....................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Giles .......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Hamilton .................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Hardeman .................................. 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Hardin ........................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Haywood .................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Henderson .................................. 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Henry ......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Hickman .................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Houston ..................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Humphreys ................................. 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Jefferson .................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Knox ........................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Lake ........................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Lauderdale ................................. 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Lawrence ................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Lewis ......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Lincoln ....................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Loudon ....................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Macon ........................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Madison ..................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Marion ....................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Marshall .................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 
287 

2003 ..................................................................... Tennessee .................................. Maury ......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. McMinn ...................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Meigs ......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Monroe ....................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Montgomery ............................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Obion ......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Perry .......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Polk ............................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Rhea .......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Roane ........................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Robertson .................................. 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Rutherford ................................. 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Sequatchie ................................. 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Sevier ......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Shelby ........................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Shelby ........................................ 7/29/03 ............. FEMA–1482–DR ........ Severe storms, high winds, and heavy rain 2003 ..................................................................... Tennessee .................................. Smith ......................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Stewart ...................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Tipton ........................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Trousdale ................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Warren ....................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Wayne ........................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Weakley ...................................... 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Williamson ................................. 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Tennessee .................................. Wilson ........................................ 5/08/03 ............. FEMA–1464–DR ........ Severe storms, tornadoes, and flooding 2003 ..................................................................... Texas ......................................... Aransas ..................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Atascosa .................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Bee ............................................ 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Brazoria ..................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Calhoun ..................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... DeWitt ........................................ 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Frio ............................................ 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Galveston ................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Goliad ........................................ 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Jackson ...................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Karnes ....................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Live Oak .................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Matagorda ................................. 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... McMullen ................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Refugio ...................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 
288 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... Texas ......................................... San Patricio ............................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Victoria ...................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Texas ......................................... Zavala ....................................... 7/17/03 ............. FEMA–1479–DR ........ Hurricane Claudette 2003 ..................................................................... Virginia ...................................... Accomack .................................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Albemarle .................................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Amelia ....................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Amherst ..................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Appomattox ................................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Arlington .................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Augusta ..................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Bedford ...................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Bland ......................................... 12/09/03 ........... FEMA–1502–DR ........ Severe Storms and Flooding 2003 ..................................................................... Virginia ...................................... Brunswick .................................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Buchanan .................................. 3/27/03 ............. FEMA–1458–DR ........ Severe winter storm, record/near-record snowfall, heavy rain, flooding, and mudslides 2003 ..................................................................... Virginia ...................................... Buchanan .................................. 12/09/03 ........... FEMA–1502–DR ........ Severe Storms and Flooding 2003 ..................................................................... Virginia ...................................... Buckingham .............................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Campbell ................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Caroline ..................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Charles City ............................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Charlotte .................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Chesterfield ............................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Alexandria ...................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Bedford .......................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Buena ............................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Charlottesville ............... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Chesapeake ................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Colonial Heights ............ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Danville ......................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Emporia ......................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Fairfax ........................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Falls Church .................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Franklin ......................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Fredericksburg ............... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Galax ............................. 12/09/03 ........... FEMA–1502–DR ........ Severe Storms and Flooding 2003 ..................................................................... Virginia ...................................... City of Hampton ........................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 
289 

2003 ..................................................................... Virginia ...................................... City of Harrisonburg .................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Hopewell ........................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Lynchburg ...................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Manassas ...................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Manassas Park .............. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Newport ......................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of News .............................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Norfolk ........................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Norton ............................ 3/27/03 ............. FEMA–1458–DR ........ Severe winter storm, record/near-record snowfall, heavy rain, flooding, and mudslides 2003 ..................................................................... Virginia ...................................... City of Petersburg ..................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Poquoson ....................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Portsmouth .................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Richmond ...................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Roanoke ......................... 3/27/03 ............. FEMA–1458–DR ........ Severe winter storm, record/near-record snowfall, heavy rain, flooding, and mudslides 2003 ..................................................................... Virginia ...................................... City of Salem ............................ 3/27/03 ............. FEMA–1458–DR ........ Severe winter storm, record/near-record snowfall, heavy rain, flooding, and mudslides 2003 ..................................................................... Virginia ...................................... City of Staunton ........................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Suffolk ........................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Virginia Beach ............... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Vista .............................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Waynesboro .................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Williamsburg ................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... City of Winchester ..................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Clarke ........................................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Culpeper .................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Cumberland ............................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Dickenson .................................. 3/27/03 ............. FEMA–1458–DR ........ Severe winter storm, record/near-record snowfall, heavy rain, flooding, and mudslides 2003 ..................................................................... Virginia ...................................... Dinwiddie ................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Essex ......................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Fairfax ....................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Fauquier .................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Fluvanna .................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Frederick .................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Giles .......................................... 12/09/03 ........... FEMA–1502–DR ........ Severe Storms and Flooding 2003 ..................................................................... Virginia ...................................... Gloucester .................................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Goochland .................................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Greene ....................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 
290 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... Virginia ...................................... Greensville ................................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Halifax ....................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Hanover ..................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Henrico ...................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Isle of Wight .............................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... James City ................................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... King and Queen ........................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... King George ............................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... King William .............................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Lancaster ................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Loudoun ..................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Louisa ........................................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Lunenburg ................................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Madison ..................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Mathews .................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Mecklenburg .............................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Middlesex ................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Montgomery ............................... 3/27/03 ............. FEMA–1458–DR ........ Severe winter storm, record/near-record snowfall, heavy rain, flooding, and mudslides 2003 ..................................................................... Virginia ...................................... Nelson ........................................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... New Kent ................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Northampton .............................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Northumberland ......................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Nottoway .................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Orange ....................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Page .......................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Pittsylvania ................................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Powhatan ................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Prince Edward ........................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Prince George ............................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Prince William ........................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Rappahannock ........................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Richmond .................................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Rockbridge ................................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Rockingham ............................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 
291 

2003 ..................................................................... Virginia ...................................... Russell ....................................... 3/27/03 ............. FEMA–1458–DR ........ Severe winter storm, record/near-record snowfall, heavy rain, flooding, and mudslides 2003 ..................................................................... Virginia ...................................... Shenandoah ............................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Smyth ........................................ 12/09/03 ........... FEMA–1502–DR ........ Severe Storms and Flooding 2003 ..................................................................... Virginia ...................................... Southampton ............................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Spotsylvania .............................. 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Stafford ..................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Surry .......................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Sussex ....................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Tazewell ..................................... 3/27/03 ............. FEMA–1458–DR ........ Severe winter storm, record/near-record snowfall, heavy rain, flooding, and mudslides 2003 ..................................................................... Virginia ...................................... Tazewell ..................................... 12/09/03 ........... FEMA–1502–DR ........ Severe Storms and Flooding 2003 ..................................................................... Virginia ...................................... Warren ....................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Westmoreland ............................ 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Virginia ...................................... Wise ........................................... 3/27/03 ............. FEMA–1458–DR ........ Severe winter storm, record/near-record snowfall, heavy rain, flooding, and mudslides 2003 ..................................................................... Virginia ...................................... York ........................................... 9/18/03 ............. FEMA–1491–DR ........ Hurricane Isabel 2003 ..................................................................... Washington ................................ Chelan ....................................... 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Clallam ...................................... 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Grays ......................................... 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Harbor ........................................ 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Island ........................................ 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Jefferson .................................... 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Juan ........................................... 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ King ........................................... 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Kitsap ........................................ 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Mason ........................................ 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Okanogan .................................. 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Pierce ......................................... 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ San ............................................ 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Skagit ........................................ 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Snohomish ................................. 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Thurston .................................... 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... Washington ................................ Whatcom .................................... 11/07/03 ........... FEMA–1499–DR ........ Severe Storms and Flooding 2003 ..................................................................... West Virginia ............................. Berkeley ..................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Boone ......................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Boone ......................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Braxton ...................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Cabel ......................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 
292 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2003 ..................................................................... West Virginia ............................. Cabell ........................................ 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Cabell ........................................ 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Calhoun ..................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Calhoun ..................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Clay ........................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Doddridge .................................. 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Fayette ....................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Fayette ....................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Gilmer ........................................ 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Greenbrier .................................. 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Greenbrier .................................. 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Harrison ..................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Jackson ...................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Kanawha .................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Kanawha .................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Kanawha .................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Lewis ......................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Lincoln ....................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Lincoln ....................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Lincoln ....................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Logan ......................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Logan ......................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Marion ....................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Mason ........................................ 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Mason ........................................ 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. McDowell ................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. McDowell ................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 
293 

2003 ..................................................................... West Virginia ............................. McDowell ................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Mercer ........................................ 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Mercer ........................................ 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Mingo ......................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Mingo ......................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Monongalia ................................ 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Monroe ....................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Nicholas ..................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Nicholas ..................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Nicholas ..................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Preston ...................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Putman ...................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Putnam ...................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Raleigh ...................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Raleigh ...................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Roane ........................................ 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Summers ................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Taylor ......................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Upshur ....................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Wayne ........................................ 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Wayne ........................................ 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Wayne ........................................ 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Webster ...................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Webster ...................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Wetzel ........................................ 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Wyoming .................................... 3/14/03 ............. FEMA–1455–DR ........ Severe Winter Storm, Record/Near Record Snow, 

Heavy Rains, Flooding and Landslides 

2003 ..................................................................... West Virginia ............................. Wyoming .................................... 6/21/03 ............. FEMA–1474–DR ........ Severe Storms, Flooding, and Landslides 2003 ..................................................................... West Virginia ............................. Wyoming .................................... 11/21/03 ........... FEMA–1500–DR ........ Severe Storms, Flooding, and Landslides 2004 ..................................................................... Alabama .................................... Autauga ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Baldwin ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Barbour ...................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 
294 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Alabama .................................... Bibb ........................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Blount ........................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Bullock ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Butler ......................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Calhoun ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Chambers .................................. 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Chilton ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Choctaw ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Clarke ........................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Clay ........................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Coffee ........................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Colbert ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Coosa ......................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Conecuh ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Covington .................................. 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Crenshaw ................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Cullman ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Dale ........................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Dallas ........................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... DeKalb ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Elmore ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Escambia ................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Etowah ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Fayette ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Franklin ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Geneva ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Greene ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Hale ........................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Henry ......................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Houston ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Jackson ...................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Jefferson .................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Lamar ........................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Lauderdale ................................. 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Lawrence ................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Lee ............................................. 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 
295 

2004 ..................................................................... Alabama .................................... Limestone .................................. 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Lowndes ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Macon ........................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Madison ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Marengo ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Marshall .................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Marion ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Mobile ........................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Monroe ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Montgomery ............................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Morgan ...................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Perry .......................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Pickens ...................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Pike ............................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Randolph ................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Russell ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Shelby ........................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... St. Clair ..................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Sumter ....................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Talladega ................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Tallapoosa ................................. 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Tuscaloosa ................................. 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Walker ........................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Washington ................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Wilcox ........................................ 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... Alabama .................................... Winston ...................................... 9/15/04 ............. FEMA–1549–DR ........ Hurricane Ivan 2004 ..................................................................... American Samoa ....................... Island of Tutuila ....................... 1/13/04 ............. FEMA–1506–DR ........ High Winds, High Surf and Heavy Rainfall Associated With Tropical Cyclone Heta 2004 ..................................................................... American Samoa ....................... The Manu’a Islands .................. 1/13/04 ............. FEMA–1506–DR ........ High Winds, High Surf and Heavy Rainfall Associated With Tropical Cyclone Heta 2004 ..................................................................... California ................................... San Luis Obispo ........................ 1/13/04 ............. FEMA–1505–DR ........ Earthquake 2004 ..................................................................... Florida ....................................... Alachua ..................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Baker ......................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Bradford .................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Brevard ...................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Charlotte .................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Citrus ......................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Clay ........................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Columbia ................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... DeSoto ....................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 
296 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Florida ....................................... Dixie ........................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Duval ......................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Flagler ....................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Gilchrist ..................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Glades ....................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Hamilton .................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Hardee ....................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Hendry ....................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Hernando ................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Highlands .................................. 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Hillsborough .............................. 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Indian River ............................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Jefferson .................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Lafayette .................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Lake ........................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Levy ........................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Madison ..................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Manatee ..................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Marion ....................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Martin ........................................ 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Nassau ...................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Okeechobee ................................ 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Orange ....................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Osceola ...................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Palm Beach ............................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Pasco ......................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Pinellas ...................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Polk ............................................ 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Putnam ...................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... St. Johns .................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... St. Lucie .................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Sarasota .................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Seminole .................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Sumter ....................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Suwannee .................................. 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Taylor ......................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 
297 

2004 ..................................................................... Florida ....................................... Union ......................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Volusia ....................................... 9/26/04 ............. FEMA–1561–DR ........ Hurricane Jeanne 2004 ..................................................................... Florida ....................................... Bay ............................................ 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Brevard ...................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Calhoun ..................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Clay ........................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Citrus ......................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Duval ......................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Escambia ................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Flagler ....................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Franklin ..................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Gadsden .................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Gulf ............................................ 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Highlands .................................. 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Holmes ....................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Indian River ............................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Jackson ...................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Lake ........................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Lee ............................................. 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Leon ........................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Liberty ........................................ 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Manatee ..................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Marion ....................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Martin ........................................ 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Okaloosa .................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Okeechobee ................................ 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Osceola ...................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Orange ....................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Palm Beach ............................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Pasco ......................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Polk ............................................ 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Santa Rosa ................................ 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Seminole .................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... St. Johns .................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... St. Lucie .................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Taylor ......................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Volusia ....................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Wakulla ...................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Walton ....................................... 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 2004 ..................................................................... Florida ....................................... Washington ................................ 9/16/04 ............. FEMA–1551–DR ........ Hurricane Ivan 
298 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Florida ....................................... Alachua ..................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Baker ......................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Bradford .................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Brevard ...................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Broward ..................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Charlotte .................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Citrus ......................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Clay ........................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Columbia ................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... DeSoto ....................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Dixie ........................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Duval ......................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Flagler ....................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Gilchrist ..................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Glades ....................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Hardee ....................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Hendry ....................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Hernando ................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Highlands .................................. 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Hillsborough .............................. 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Indian River ............................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Lake ........................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Lee ............................................. 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Levy ........................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Manatee ..................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Marion ....................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Martin ........................................ 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Miami-Dade ............................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Nassau ...................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Okeechobee ................................ 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Orange ....................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Osceola ...................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Palm Beach ............................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Pasco ......................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Pinellas ...................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Polk ............................................ 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 
299 

2004 ..................................................................... Florida ....................................... Putnam ...................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Sarasota .................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Seminole .................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... St. Johns .................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... St. Lucie .................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Sumter ....................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Suwannee .................................. 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Union ......................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Volusia ....................................... 9/04/04 ............. FEMA–1545–DR ........ Hurricane Frances 2004 ..................................................................... Florida ....................................... Brevard ...................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Charlotte .................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Collier ........................................ 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... DeSoto ....................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Dixie ........................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Duval ......................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Flagler ....................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Glades ....................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Hardee ....................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Hendry ....................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Highlands .................................. 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Indian River ............................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Lake ........................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Lee ............................................. 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Levy ........................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Manatee ..................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Monroe ....................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Okeechobee ................................ 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Orange ....................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Osceola ...................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Pasco ......................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Polk ............................................ 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... St. Johns .................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Sarasota .................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Seminole .................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Florida ....................................... Volusia ....................................... 8/13/04 ............. FEMA–1539–DR ........ Tropical Storm Bonnie and Hurricane Charley 2004 ..................................................................... Georgia ...................................... Carroll ........................................ 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Cherokee .................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Clayton ...................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Cobb .......................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Dade .......................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 
300 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Georgia ...................................... Dawson ...................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... DeKalb ....................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Early .......................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Forsyth ....................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Franklin ..................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Fulton ........................................ 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Gilmer ........................................ 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Heard ......................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Madison ..................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Miller ......................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Pickens ...................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Rabun ........................................ 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Towns ........................................ 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Union ......................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... White ......................................... 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Georgia ...................................... Wilkes ........................................ 9/18/04 ............. FEMA–1554–DR ........ Hurricane Ivan 2004 ..................................................................... Illinois ........................................ Kankakee ................................... 4/23/04 ............. FEMA–1513–DR ........ Severe Storms and Tornadoes 2004 ..................................................................... Illinois ........................................ LaSalle ....................................... 4/23/04 ............. FEMA–1513–DR ........ Severe Storms and Tornadoes 2004 ..................................................................... Illinois ........................................ Putnam ...................................... 4/23/04 ............. FEMA–1513–DR ........ Severe Storms and Tornadoes 2004 ..................................................................... Illinois ........................................ Will ............................................ 4/23/04 ............. FEMA–1513–DR ........ Severe Storms and Tornadoes 2004 ..................................................................... Indiana ...................................... Adams ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Allen .......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Benton ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Boone ......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Brown ........................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Carroll ........................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Cass .......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Clark .......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Clay ........................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Clinton ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Crawford .................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Dearborn .................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Decatur ...................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... DeKalb ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Delaware .................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Dubois ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 
301 

2004 ..................................................................... Indiana ...................................... Floyd .......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Fountain .................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Franklin ..................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Fulton ........................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Gibson ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Grant ......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Greene ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Hamilton .................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Hancock ..................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Harrison ..................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Hendricks ................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Henry ......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Howard ...................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Huntington ................................. 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Jackson ...................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Jasper ........................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Jefferson .................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Jennings .................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Johnson ...................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Kosciusko ................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Lake ........................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Lawrence ................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Madison ..................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Marion ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Martin ........................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Miami ........................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Monroe ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Montgomery ............................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Morgan ...................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Newton ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Noble ......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Ohio ........................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Orange ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Owen .......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Perry .......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Pike ............................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Putnam ...................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Ripley ......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Scott .......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Shelby ........................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 
302 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Indiana ...................................... Spencer ...................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Switzerland ................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Tippecanoe ................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Tipton ........................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Vanderburgh .............................. 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Wabash ...................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Warren ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Warrick ...................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Washington ................................ 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Wells .......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... White ......................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Indiana ...................................... Whitley ....................................... 6/03/04 ............. FEMA–1520–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Adair .......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Adams ....................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Allamakee .................................. 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Appanoose ................................. 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Audubon .................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Benton ....................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Black Hawk ............................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Boone ......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Bremer ....................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Buchanan .................................. 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Buena Vista ............................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Butler ......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Calhoun ..................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Cass .......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Cedar ......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Cerro Gordo ............................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Chickasaw ................................. 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Clay ........................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Clayton ...................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Clinton ....................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Dallas ........................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Davis ......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Delaware .................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Des Moines ................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 
303 

2004 ..................................................................... Iowa ........................................... Dubuque .................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Fayette ....................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Floyd .......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Franklin ..................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Greene ....................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Grundy ....................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Guthrie ....................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Hamilton .................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Hancock ..................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Henry ......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Hardin ........................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Howard ...................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Humboldt ................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Iowa ........................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Jackson ...................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Jasper ........................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Jones .......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Johnson ...................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Kossuth ...................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Linn ........................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Louisa ........................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Lucas ......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Madison ..................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Marshall .................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Mitchell ...................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Monroe ....................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Montgomery ............................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Muscatine .................................. 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Palo Alto .................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Pocahontas ................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Polk ............................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Pottawattamie ........................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Poweshiek .................................. 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Sac ............................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Scott .......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Shelby ........................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Story .......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Tama ......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Wapello ...................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Warren ....................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 
304 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Iowa ........................................... Washington ................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Wayne ........................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Webster ...................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Winnebago ................................. 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Winneshiek ................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Worth ......................................... 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Iowa ........................................... Wright ........................................ 5/25/04 ............. FEMA–1518–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Kentucky .................................... Bell ............................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Bourbon ..................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Boyd ........................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Boyle .......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Breathitt .................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Breckinridge .............................. 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Bullitt ........................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Butler ......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Caldwell ..................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Carroll ........................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Carter ........................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Casey ......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Christian .................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Clark .......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 
305 

2004 ..................................................................... Kentucky .................................... Clay ........................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Crittenden .................................. 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Edmonson .................................. 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Elliott ......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Estill .......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Fayette ....................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Floyd .......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Franklin ..................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Garrard ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Grayson ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Greenup ..................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Hardin ........................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Harlan ........................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Hart ........................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Henderson .................................. 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Henry ......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Hopkins ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Jackson ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Jefferson .................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Jessamine .................................. 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 
306 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Kentucky .................................... Johnson ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Knott .......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Knox ........................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Laurel ........................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Lawrence ................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Lee ............................................. 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Leslie ......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Letcher ....................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Lincoln ....................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Madison ..................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Magoffin .................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Martin ........................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... McLean ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Menifee ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Montgomery ............................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Morgan ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Muhlenberg ................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Ohio ........................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 
307 

2004 ..................................................................... Kentucky .................................... Oldham ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Owen .......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Owsley ....................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Perry .......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Pike ............................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Powell ........................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Pulaski ....................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Rockcastle ................................. 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Rowan ........................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Scott .......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Shelby ........................................ 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Spencer ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Trimble ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Union ......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Webster ...................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Whitely ....................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Wolfe .......................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Kentucky .................................... Woodford .................................... 6/10/04 ............. FEMA–1523–DR ........ Severe Storms, Tornadoes, Flooding, and 

Mudslides 

2004 ..................................................................... Louisiana ................................... Jefferson .................................... 9/15/04 ............. FEMA–1548–DR ........ Hurricane Ivan 2004 ..................................................................... Louisiana ................................... Lafourche ................................... 9/15/04 ............. FEMA–1548–DR ........ Hurricane Ivan 2004 ..................................................................... Louisiana ................................... Orleans ...................................... 9/15/04 ............. FEMA–1548–DR ........ Hurricane Ivan 2004 ..................................................................... Louisiana ................................... Plaquemines .............................. 9/15/04 ............. FEMA–1548–DR ........ Hurricane Ivan 
308 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Louisiana ................................... St. Bernard ................................ 9/15/04 ............. FEMA–1548–DR ........ Hurricane Ivan 2004 ..................................................................... Louisiana ................................... St. Charles ................................ 9/15/04 ............. FEMA–1548–DR ........ Hurricane Ivan 2004 ..................................................................... Louisiana ................................... St. Tammany ............................. 9/15/04 ............. FEMA–1548–DR ........ Hurricane Ivan 2004 ..................................................................... Louisiana ................................... Terrebonne ................................. 9/15/04 ............. FEMA–1548–DR ........ Hurricane Ivan 2004 ..................................................................... Louisiana ................................... Acadia ....................................... 6/08/04 ............. FEMA–1521–DR ........ Severe Storms and Flooding 2004 ..................................................................... Louisiana ................................... Iberville ...................................... 6/08/04 ............. FEMA–1521–DR ........ Severe Storms and Flooding 2004 ..................................................................... Louisiana ................................... Jefferson Davis .......................... 6/08/04 ............. FEMA–1521–DR ........ Severe Storms and Flooding 2004 ..................................................................... Louisiana ................................... Lafayette .................................... 6/08/04 ............. FEMA–1521–DR ........ Severe Storms and Flooding 2004 ..................................................................... Louisiana ................................... Livingston .................................. 6/08/04 ............. FEMA–1521–DR ........ Severe Storms and Flooding 2004 ..................................................................... Louisiana ................................... Pointe Coupee ........................... 6/08/04 ............. FEMA–1521–DR ........ Severe Storms and Flooding 2004 ..................................................................... Louisiana ................................... St. Landry .................................. 6/08/04 ............. FEMA–1521–DR ........ Severe Storms and Flooding 2004 ..................................................................... Louisiana ................................... St. Martin .................................. 6/08/04 ............. FEMA–1521–DR ........ Severe Storms and Flooding 2004 ..................................................................... Louisiana ................................... West Baton Rouge ..................... 6/08/04 ............. FEMA–1521–DR ........ Severe Storms and Flooding 2004 ..................................................................... Massachusetts .......................... Essex ......................................... 4/21/04 ............. FEMA–1512–DR ........ Severe Winter Storms 2004 ..................................................................... Massachusetts .......................... Middlesex ................................... 4/21/04 ............. FEMA–1512–DR ........ Severe Winter Storms 2004 ..................................................................... Massachusetts .......................... Norfolk ....................................... 4/21/04 ............. FEMA–1512–DR ........ Severe Winter Storms 2004 ..................................................................... Massachusetts .......................... Suffolk ....................................... 4/21/04 ............. FEMA–1512–DR ........ Severe Winter Storms 2004 ..................................................................... Massachusetts .......................... Worcester ................................... 4/21/04 ............. FEMA–1512–DR ........ Severe Winter Storms 2004 ..................................................................... Michigan .................................... Barry .......................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Berrien ....................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Cass .......................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Eaton ......................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Genesee ..................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Gladwin ..................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Ingham ...................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Ionia .......................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Jackson ...................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Kent ........................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Livingston .................................. 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Macomb ..................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Mecosta ..................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Muskegon .................................. 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Oakland ..................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Ottawa ....................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Saginaw ..................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Sanilac ...................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 
309 

2004 ..................................................................... Michigan .................................... Shiawassee ................................ 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... St. Clair ..................................... 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... St. Joseph .................................. 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Washtenaw ................................ 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Michigan .................................... Wayne ........................................ 6/30/04 ............. FEMA–1527–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Minnesota .................................. Dodge ........................................ 10/07/04 ........... FEMA–1569–DR ........ Severe Storms and Flooding 2004 ..................................................................... Minnesota .................................. Faribault .................................... 10/07/04 ........... FEMA–1569–DR ........ Severe Storms and Flooding 2004 ..................................................................... Minnesota .................................. Freeborn ..................................... 10/07/04 ........... FEMA–1569–DR ........ Severe Storms and Flooding 2004 ..................................................................... Minnesota .................................. Martin ........................................ 10/07/04 ........... FEMA–1569–DR ........ Severe Storms and Flooding 2004 ..................................................................... Minnesota .................................. Mower ........................................ 10/07/04 ........... FEMA–1569–DR ........ Severe Storms and Flooding 2004 ..................................................................... Minnesota .................................. Olmsted ..................................... 10/07/04 ........... FEMA–1569–DR ........ Severe Storms and Flooding 2004 ..................................................................... Minnesota .................................. Steele ......................................... 10/07/04 ........... FEMA–1569–DR ........ Severe Storms and Flooding 2004 ..................................................................... Mississippi ................................ Clarke ........................................ 9/15/04 ............. FEMA–1550–DR ........ Hurricane Ivan 2004 ..................................................................... Mississippi ................................ George ....................................... 9/15/04 ............. FEMA–1550–DR ........ Hurricane Ivan 2004 ..................................................................... Mississippi ................................ Hancock ..................................... 9/15/04 ............. FEMA–1550–DR ........ Hurricane Ivan 2004 ..................................................................... Mississippi ................................ Harrison ..................................... 9/15/04 ............. FEMA–1550–DR ........ Hurricane Ivan 2004 ..................................................................... Mississippi ................................ Jackson ...................................... 9/15/04 ............. FEMA–1550–DR ........ Hurricane Ivan 2004 ..................................................................... Mississippi ................................ Lauderdale ................................. 9/15/04 ............. FEMA–1550–DR ........ Hurricane Ivan 2004 ..................................................................... Mississippi ................................ Perry .......................................... 9/15/04 ............. FEMA–1550–DR ........ Hurricane Ivan 2004 ..................................................................... Mississippi ................................ Stone ......................................... 9/15/04 ............. FEMA–1550–DR ........ Hurricane Ivan 2004 ..................................................................... Mississippi ................................ Wayne ........................................ 9/15/04 ............. FEMA–1550–DR ........ Hurricane Ivan 2004 ..................................................................... Missouri ..................................... Adair .......................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Andrew ....................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Bates ......................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Benton ....................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Buchanan .................................. 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Caldwell ..................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Carroll ........................................ 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Cass .......................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Cedar ......................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Chariton ..................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Clay ........................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Clinton ....................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Daviess ...................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... DeKalb ....................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Gentry ........................................ 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Grundy ....................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Harrison ..................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Henry ......................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Hickory ....................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 
310 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Missouri ..................................... Jackson ...................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Johnson ...................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Knox ........................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Linn ........................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Livingston .................................. 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Macon ........................................ 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Mercer ........................................ 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Monroe ....................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Nodaway .................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Platte ......................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Polk ............................................ 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Randolph ................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Ray ............................................ 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Shelby ........................................ 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... St.-Clair ..................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Sullivan ..................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Vernon ....................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Missouri ..................................... Worth ......................................... 6/10/04 ............. FEMA–1524–DR ........ Severe storms, tornadoes, and flooding 2004 ..................................................................... Nebraska ................................... Adams ....................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Buffalo ....................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Butler ......................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Cass .......................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Clay ........................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Dodge ........................................ 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Douglas ..................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Fillmore ...................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Franklin ..................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Gage .......................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Hall ............................................ 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Hamilton .................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Jefferson .................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Johnson ...................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Kearney ...................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Lancaster ................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Nuckolls ..................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Otoe ........................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 
311 

2004 ..................................................................... Nebraska ................................... Pawnee ...................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Saline ........................................ 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Sarpy ......................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Saunders ................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Seward ....................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Thayer ........................................ 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Washington ................................ 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... Webster ...................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Nebraska ................................... York ........................................... 5/23/04 ............. FEMA–1517–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... New Jersey ................................. Hunterdon .................................. 10/01/04 ........... FEMA–1563–DR ........ Tropical Depression Ivan 2004 ..................................................................... New Jersey ................................. Mercer ........................................ 10/01/04 ........... FEMA–1563–DR ........ Tropical Depression Ivan 2004 ..................................................................... New Jersey ................................. Sussex ....................................... 10/01/04 ........... FEMA–1563–DR ........ Tropical Depression Ivan 2004 ..................................................................... New Jersey ................................. Warren ....................................... 10/01/04 ........... FEMA–1563–DR ........ Tropical Depression Ivan 2004 ..................................................................... New Jersey ................................. Burlington .................................. 7/16/04 ............. FEMA–1530–DR ........ Severe Storms and Flooding 2004 ..................................................................... New Jersey ................................. Camden ..................................... 7/16/04 ............. FEMA–1530–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Broome ...................................... 10/01/04 ........... FEMA–1565–DR ........ Tropical Depression Ivan 2004 ..................................................................... New York ................................... Chenango .................................. 10/01/04 ........... FEMA–1565–DR ........ Tropical Depression Ivan 2004 ..................................................................... New York ................................... Delaware .................................... 10/01/04 ........... FEMA–1565–DR ........ Tropical Depression Ivan 2004 ..................................................................... New York ................................... Orange ....................................... 10/01/04 ........... FEMA–1565–DR ........ Tropical Depression Ivan 2004 ..................................................................... New York ................................... Sullivan ..................................... 10/01/04 ........... FEMA–1565–DR ........ Tropical Depression Ivan 2004 ..................................................................... New York ................................... Ulster ......................................... 10/01/04 ........... FEMA–1565–DR ........ Tropical Depression Ivan 2004 ..................................................................... New York ................................... Allegany ..................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Broome ...................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Cattaraugus .............................. 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Madison ..................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Monroe ....................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Niagara ...................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Oneida ....................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Onondaga .................................. 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Orange ....................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Orleans ...................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Steuben ..................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Sullivan ..................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Ulster ......................................... 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... New York ................................... Wayne ........................................ 10/01/04 ........... FEMA–1564–DR ........ Severe Storms and Flooding 2004 ..................................................................... North Carolina ........................... Alamance ................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Alleghany ................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Ashe ........................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Avery .......................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Buncombe .................................. 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 
312 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... North Carolina ........................... Burke ......................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Caldwell ..................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Caswell ...................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Davidson .................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Forsyth ....................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Graham ...................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Guilford ...................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Haywood .................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Henderson .................................. 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Jackson ...................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Macon ........................................ 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Madison ..................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... McDowell ................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Mitchell ...................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Polk ............................................ 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Randolph ................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Rockingham ............................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Rutherford ................................. 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Stokes ........................................ 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Swain ......................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Transylvania .............................. 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Watauga .................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Wilkes ........................................ 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Yancey ....................................... 9/18/04 ............. FEMA–1553–DR ........ Hurricane Ivan 2004 ..................................................................... North Carolina ........................... Alleghany ................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Alexander ................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Ashe ........................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Avery .......................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Bladen ....................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Buncombe .................................. 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Burke ......................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Cabarrus .................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Caldwell ..................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Catawba .................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Cleveland ................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Columbus .................................. 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 
313 

2004 ..................................................................... North Carolina ........................... Cumberland ............................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Gaston ....................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Haywood .................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Henderson .................................. 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Jackson ...................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Hoke ........................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Iredell ........................................ 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Lincoln ....................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Madison ..................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... McDowell ................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Mecklenburg .............................. 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Mitchell ...................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Polk ............................................ 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Robeson ..................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Rutherford ................................. 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Scotland .................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Transylvania .............................. 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Union ......................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Watauga .................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Wilkes ........................................ 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... North Carolina ........................... Yancey ....................................... 9/10/04 ............. FEMA–1546–DR ........ Tropical Storm Frances 2004 ..................................................................... Northern Mariana Islands ......... Rota ........................................... 8/26/04 ............. FEMA–1541–DR ........ Flooding, High Surf, Storm Surge, and High 

Winds as a result of Super Typhoon Chaba 

2004 ..................................................................... Northern Mariana Islands ......... Saipan ....................................... 8/26/04 ............. FEMA–1541–DR ........ Flooding, High Surf, Storm Surge, and High 

Winds as a result of Super Typhoon Chaba 

2004 ..................................................................... Northern Mariana Islands ......... Tinian ........................................ 8/26/04 ............. FEMA–1541–DR ........ Flooding, High Surf, Storm Surge, and High 

Winds as a result of Super Typhoon Chaba 

2004 ..................................................................... Northern Mariana Islands ......... Rota ........................................... 7/29/04 ............. FEMA–1532–DR ........ Flooding, High Surf, High Winds, and Wind– 

DRiven Rain associated with Typhoon Tingting 

2004 ..................................................................... Northern Mariana Islands ......... Saipan ....................................... 7/29/04 ............. FEMA–1532–DR ........ Flooding, High Surf, High Winds, and Wind– 

DRiven Rain associated with Typhoon Tingting 

2004 ..................................................................... Northern Mariana Islands ......... Tinian ........................................ 7/29/04 ............. FEMA–1532–DR ........ Flooding, High Surf, High Winds, and Wind– 

DRiven Rain associated with Typhoon Tingting 

2004 ..................................................................... Ohio ........................................... Athens ....................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Belmont ..................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Carroll ........................................ 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Columbiana ............................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 
314 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Ohio ........................................... Gallia ......................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Guernsey .................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Harrison ..................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Jefferson .................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Lawrence ................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Mahoning ................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Meigs ......................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Monroe ....................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Morgan ...................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Muskingum ................................ 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Noble ......................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Perry .......................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Stark .......................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Trumbull .................................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Tuscarawas ............................... 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Vinton ........................................ 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Washington ................................ 9/19/04 ............. FEMA–1556–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Athens ....................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Carroll ........................................ 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Columbiana ............................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Crawford .................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Cuyahoga ................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Delaware .................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Geauga ...................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Guernsey .................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Harrison ..................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Hocking ...................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Holmes ....................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Licking ....................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Logan ......................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Lorain ........................................ 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Mahoning ................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Medina ....................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Noble ......................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Perry .......................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Portage ...................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 
315 

2004 ..................................................................... Ohio ........................................... Richland .................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Stark .......................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Summit ...................................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Tuscarawas ............................... 6/03/04 ............. FEMA–1519–DR ........ Severe Storms and Flooding 2004 ..................................................................... Ohio ........................................... Belmont ..................................... 1/26/04 ............. FEMA–1507–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2004 ..................................................................... Ohio ........................................... Franklin ..................................... 1/26/04 ............. FEMA–1507–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2004 ..................................................................... Ohio ........................................... Jefferson .................................... 1/26/04 ............. FEMA–1507–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2004 ..................................................................... Ohio ........................................... Licking ....................................... 1/26/04 ............. FEMA–1507–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2004 ..................................................................... Ohio ........................................... Morgan ...................................... 1/26/04 ............. FEMA–1507–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2004 ..................................................................... Ohio ........................................... Ross ........................................... 1/26/04 ............. FEMA–1507–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2004 ..................................................................... Ohio ........................................... Tuscarawas ............................... 1/26/04 ............. FEMA–1507–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2004 ..................................................................... Ohio ........................................... Washington ................................ 1/26/04 ............. FEMA–1507–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2004 ..................................................................... Pennsylvania ............................. Allegheny ................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Armstrong .................................. 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Beaver ....................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Bedford ...................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Blair ........................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Bradford .................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Bucks ......................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Butler ......................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Cameron .................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Carbon ....................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Centre ........................................ 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Chester ...................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Clarion ....................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Clearfield ................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Clinton ....................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Columbia ................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Crawford .................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Cumberland ............................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Dauphin ..................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Delaware .................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 
316 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Pennsylvania ............................. Elk ............................................. 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Franklin ..................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Fulton ........................................ 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Green ......................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Huntingdon ................................ 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Indiana ...................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Jefferson .................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Juniata ....................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Lackawanna .............................. 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Lawrence ................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Lebanon ..................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Lehigh ........................................ 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Luzerne ...................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Lycoming ................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Mifflin ........................................ 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Monroe ....................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Montgomery ............................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Montour ..................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Northampton .............................. 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Northumberland ......................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Perry .......................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Philadelphia .............................. 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Pike ............................................ 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Potter ......................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Schuylkill ................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Snyder ........................................ 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Somerset .................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Sullivan ..................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Susquehanna ............................. 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Tioga .......................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Union ......................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Washington ................................ 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Wayne ........................................ 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Westmoreland ............................ 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. Wyoming .................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 2004 ..................................................................... Pennsylvania ............................. York ........................................... 9/19/04 ............. FEMA–1557–DR ........ Tropical Depression Ivan 
317 

2004 ..................................................................... Pennsylvania ............................. Beaver ....................................... 9/19/04 ............. FEMA–1555–DR ........ Severe Storms and Flooding associated with 

Tropical Depression Frances 

2004 ..................................................................... Pennsylvania ............................. Bedford ...................................... 9/19/04 ............. FEMA–1555–DR ........ Severe Storms and Flooding associated with 

Tropical Depression Frances 

2004 ..................................................................... Pennsylvania ............................. Blair ........................................... 9/19/04 ............. FEMA–1555–DR ........ Severe Storms and Flooding associated with 

Tropical Depression Frances 

2004 ..................................................................... Pennsylvania ............................. Butler ......................................... 9/19/04 ............. FEMA–1555–DR ........ Severe Storms and Flooding associated with 

Tropical Depression Frances 

2004 ..................................................................... Pennsylvania ............................. Crawford .................................... 9/19/04 ............. FEMA–1555–DR ........ Severe Storms and Flooding associated with 

Tropical Depression Frances 

2004 ..................................................................... Pennsylvania ............................. Erie ............................................ 9/19/04 ............. FEMA–1555–DR ........ Severe Storms and Flooding associated with 

Tropical Depression Frances 

2004 ..................................................................... Pennsylvania ............................. Huntingdon ................................ 9/19/04 ............. FEMA–1555–DR ........ Severe Storms and Flooding associated with 

Tropical Depression Frances 

2004 ..................................................................... Pennsylvania ............................. Lawrence ................................... 9/19/04 ............. FEMA–1555–DR ........ Severe Storms and Flooding associated with 

Tropical Depression Frances 

2004 ..................................................................... Pennsylvania ............................. Warren ....................................... 9/19/04 ............. FEMA–1555–DR ........ Severe Storms and Flooding associated with 

Tropical Depression Frances 

2004 ..................................................................... Pennsylvania ............................. Washington ................................ 9/19/04 ............. FEMA–1555–DR ........ Severe Storms and Flooding associated with 

Tropical Depression Frances 

2004 ..................................................................... Pennsylvania ............................. Delaware .................................... 8/06/04 ............. FEMA–1538–DR ........ Severe Storms and Flooding 2004 ..................................................................... Pennsylvania ............................. Montgomery ............................... 8/06/04 ............. FEMA–1538–DR ........ Severe Storms and Flooding 2004 ..................................................................... Pennsylvania ............................. Philadelphia .............................. 8/06/04 ............. FEMA–1538–DR ........ Severe Storms and Flooding 2004 ..................................................................... Puerto Rico ................................ Aguada ...................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Aguadilla ................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Aguas ........................................ 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Buenas ...................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Aibonito ..................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Aoasco ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Arecibo ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Arroyo ......................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 
318 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Puerto Rico ................................ Barceloneta ............................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Barranquitas ............................. 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Bayamon .................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Caguas ...................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Camuy ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Canovanas ................................. 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Carolina ..................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Cataoo ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Cayey ......................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Ceiba ......................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Ciales ........................................ 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Cidra .......................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Coamo ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Comeroo ..................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Corozal ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Dorado ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Fajardo ...................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Florida ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 
319 

2004 ..................................................................... Puerto Rico ................................ Guayama ................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Gurabo ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Hatillo ........................................ 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Humacao ................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Isabela ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Juana Doaz ................................ 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Juncos ........................................ 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Lares .......................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Las Piedras ............................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Looza ......................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Manato ...................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Maunabo .................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Moca .......................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Morovis ...................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Naguabo .................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Naranjito .................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Orocovis ..................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Patillas ...................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Quebradillas .............................. 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Rincon ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 
320 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Puerto Rico ................................ Roo Grande ................................ 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Salinas ...................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ San Lorenzo ............................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ San Sebastian ........................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Santa Isabel .............................. 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Toa Alta ..................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Toa Baja .................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Utuado ....................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Vega Alta ................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Vega Baja .................................. 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Villalba ...................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Vieques ...................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... Puerto Rico ................................ Yabucoa ..................................... 9/17/04 ............. FEMA–1552–DR ........ Tropical Storm Jeanne and resulting landslides 

and mudslides 

2004 ..................................................................... South Carolina .......................... Berkeley ..................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Calhoun ..................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Charleston ................................. 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Cherokee .................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Chester ...................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Chesterfield ............................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Clarendon .................................. 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Darlington .................................. 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Dillon ......................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Fairfield ..................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 
321 

2004 ..................................................................... South Carolina .......................... Florence ..................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Georgetown ................................ 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Greenville ................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Horry .......................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Kershaw ..................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Lancaster ................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Lee ............................................. 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Lexington ................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Marion ....................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Marlboro .................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Newberry .................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Oconee ....................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Pickens ...................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Richland .................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Spartanburg .............................. 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Sumter ....................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... Williamsburg ............................. 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... South Carolina .......................... York ........................................... 10/07/04 ........... FEMA–1566–DR ........ Tropical Storm Frances 2004 ..................................................................... Virginia ...................................... Alleghany ................................... 10/18/04 ........... FEMA–1570–DR ........ Severe Storms and Flooding from the remnants 

of Hurricane Jeanne 

2004 ..................................................................... Virginia ...................................... Botetourt .................................... 10/18/04 ........... FEMA–1570–DR ........ Severe Storms and Flooding from the remnants 

of Hurricane Jeanne 

2004 ..................................................................... Virginia ...................................... Craig .......................................... 10/18/04 ........... FEMA–1570–DR ........ Severe Storms and Flooding from the remnants 

of Hurricane Jeanne 

2004 ..................................................................... Virginia ...................................... Floyd .......................................... 10/18/04 ........... FEMA–1570–DR ........ Severe Storms and Flooding from the remnants 

of Hurricane Jeanne 

2004 ..................................................................... Virginia ...................................... Giles .......................................... 10/18/04 ........... FEMA–1570–DR ........ Severe Storms and Flooding from the remnants 

of Hurricane Jeanne 

2004 ..................................................................... Virginia ...................................... Montgomery ............................... 10/18/04 ........... FEMA–1570–DR ........ Severe Storms and Flooding from the remnants 

of Hurricane Jeanne 

2004 ..................................................................... Virginia ...................................... Patrick ....................................... 10/18/04 ........... FEMA–1570–DR ........ Severe Storms and Flooding from the remnants 

of Hurricane Jeanne 

2004 ..................................................................... Virginia ...................................... Roanoke ..................................... 10/18/04 ........... FEMA–1570–DR ........ Severe Storms and Flooding from the remnants 

of Hurricane Jeanne 

2004 ..................................................................... Virginia ...................................... Chesterfield ............................... 9/03/04 ............. FEMA–1544–DR ........ Severe Storms, Flooding and Tornadoes associated with Tropical Depression Gaston 2004 ..................................................................... Virginia ...................................... Dinwiddie ................................... 9/03/04 ............. FEMA–1544–DR ........ Severe Storms, Flooding and Tornadoes associated with Tropical Depression Gaston 2004 ..................................................................... Virginia ...................................... Hanover ..................................... 9/03/04 ............. FEMA–1544–DR ........ Severe Storms, Flooding and Tornadoes associated with Tropical Depression Gaston 
322 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2004 ..................................................................... Virginia ...................................... Henrico ...................................... 9/03/04 ............. FEMA–1544–DR ........ Severe Storms, Flooding and Tornadoes associated with Tropical Depression Gaston 2004 ..................................................................... Virginia ...................................... Prince George ............................ 9/03/04 ............. FEMA–1544–DR ........ Severe Storms, Flooding and Tornadoes associated with Tropical Depression Gaston 2004 ..................................................................... Virginia ...................................... Buchanan .................................. 6/15/04 ............. FEMA–1525–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Virginia ...................................... Lee ............................................. 6/15/04 ............. FEMA–1525–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Virginia ...................................... Russell ....................................... 6/15/04 ............. FEMA–1525–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... Virginia ...................................... Tazewell ..................................... 6/15/04 ............. FEMA–1525–DR ........ Severe Storms, Tornadoes, and Flooding 2004 ..................................................................... West Virginia ............................. Berkeley ..................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Brooke ........................................ 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Cabell ........................................ 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Hancock ..................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Jackson ...................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Kanawha .................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Lincoln ....................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Logan ......................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Marshall .................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Mason ........................................ 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Mingo ......................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Morgan ...................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Ohio ........................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Pleasants ................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Tyler ........................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Wayne ........................................ 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Wetzel ........................................ 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Wirt ............................................ 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Wood .......................................... 9/20/04 ............. FEMA–1558–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Fayette ....................................... 8/06/04 ............. FEMA–1536–DR ........ Severe Storms, Flooding, and Tornadoes 2004 ..................................................................... West Virginia ............................. Lincoln ....................................... 8/06/04 ............. FEMA–1536–DR ........ Severe Storms, Flooding, and Tornadoes 2004 ..................................................................... West Virginia ............................. Logan ......................................... 8/06/04 ............. FEMA–1536–DR ........ Severe Storms, Flooding, and Tornadoes 2004 ..................................................................... West Virginia ............................. Mingo ......................................... 8/06/04 ............. FEMA–1536–DR ........ Severe Storms, Flooding, and Tornadoes 2004 ..................................................................... West Virginia ............................. Boone ......................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Braxton ...................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Cabell ........................................ 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Calhoun ..................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Clay ........................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 
323 

2004 ..................................................................... West Virginia ............................. Fayette ....................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Gilmer ........................................ 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Jackson ...................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Kanawha .................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Lewis ......................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Lincoln ....................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Logan ......................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Mason ........................................ 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. McDowell ................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Mercer ........................................ 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Mingo ......................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Nicholas ..................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Putnam ...................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Raleigh ...................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Roane ........................................ 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Wayne ........................................ 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Webster ...................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Wirt ............................................ 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... West Virginia ............................. Wyoming .................................... 6/07/04 ............. FEMA–1522–DR ........ Severe Storms, Flooding and Landslides 2004 ..................................................................... Wisconsin .................................. Clark .......................................... 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Columbia ................................... 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Crawford .................................... 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Dodge ........................................ 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Fond du Lac .............................. 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Grant ......................................... 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Green Lake ................................ 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Jefferson .................................... 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Kenosha ..................................... 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Ozaukee ..................................... 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Vernon ....................................... 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2004 ..................................................................... Wisconsin .................................. Winnebago ................................. 6/19/04 ............. FEMA–1526–DR ........ Severe Storms and Flooding 2005 ..................................................................... Alabama .................................... Baldwin ..................................... 7/10/05 ............. FEMA–1593–DR ........ Hurricane Dennis 2005 ..................................................................... Alabama .................................... Baldwin ..................................... 8/29/05 ............. FEMA–1605–DR ........ Hurricane Katrina 2005 ..................................................................... Alabama .................................... Escambia ................................... 7/10/05 ............. FEMA–1593–DR ........ Hurricane Dennis 2005 ..................................................................... Alabama .................................... Greene ....................................... 8/29/05 ............. FEMA–1605–DR ........ Hurricane Katrina 2005 ..................................................................... Alabama .................................... Hale ........................................... 8/29/05 ............. FEMA–1605–DR ........ Hurricane Katrina 2005 ..................................................................... Alabama .................................... Marengo ..................................... 8/29/05 ............. FEMA–1605–DR ........ Hurricane Katrina 2005 ..................................................................... Alabama .................................... Mobile ........................................ 7/10/05 ............. FEMA–1593–DR ........ Hurricane Dennis 2005 ..................................................................... Alabama .................................... Mobile ........................................ 8/29/05 ............. FEMA–1605–DR ........ Hurricane Katrina 2005 ..................................................................... Alabama .................................... Pickens ...................................... 8/29/05 ............. FEMA–1605–DR ........ Hurricane Katrina 
324 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2005 ..................................................................... Alabama .................................... Tuscaloosa ................................. 8/29/05 ............. FEMA–1605–DR ........ Hurricane Katrina 2005 ..................................................................... Alabama .................................... Washington ................................ 8/29/05 ............. FEMA–1605–DR ........ Hurricane Katrina 2005 ..................................................................... California ................................... Kern ........................................... 2/04/05 ............. FEMA–1577 .............. Severe Storms, Flooding, Debris Flows, and 

Mudslides 

2005 ..................................................................... California ................................... Los Angeles ............................... 2/04/05 ............. FEMA–1577 .............. Severe Storms, Flooding, Debris Flows, and 

Mudslides 

2005 ..................................................................... California ................................... Orange ....................................... 2/04/05 ............. FEMA–1577 .............. Severe Storms, Flooding, Debris Flows, and 

Mudslides 

2005 ..................................................................... California ................................... Riverside .................................... 2/04/05 ............. FEMA–1577 .............. Severe Storms, Flooding, Debris Flows, and 

Mudslides 

2005 ..................................................................... California ................................... San Bernardino ......................... 2/04/05 ............. FEMA–1577 .............. Severe Storms, Flooding, Debris Flows, and 

Mudslides 

2005 ..................................................................... California ................................... San Diego, ................................. 2/04/05 ............. FEMA–1577 .............. Severe Storms, Flooding, Debris Flows, and 

Mudslides 

2005 ..................................................................... California ................................... Santa Barbara ........................... 2/04/05 ............. FEMA–1577 .............. Severe Storms, Flooding, Debris Flows, and 

Mudslides 

2005 ..................................................................... California ................................... Ventura ...................................... 2/04/05 ............. FEMA–1577 .............. Severe Storms, Flooding, Debris Flows, and 

Mudslides 

2005 ..................................................................... Florida ....................................... Bay ............................................ 7/10/05 ............. FEMA–1595–DR ........ Hurricane Dennis 2005 ..................................................................... Florida ....................................... Brevard ...................................... 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Broward ..................................... 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Collier ........................................ 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Dixie ........................................... 7/10/05 ............. FEMA–1595–DR ........ Hurricane Dennis 2005 ..................................................................... Florida ....................................... Escambia ................................... 7/10/05 ............. FEMA–1595–DR ........ Hurricane Dennis 2005 ..................................................................... Florida ....................................... Franklin ..................................... 7/10/05 ............. FEMA–1595–DR ........ Hurricane Dennis 2005 ..................................................................... Florida ....................................... Glades ....................................... 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Gulf ............................................ 7/10/05 ............. FEMA–1595–DR ........ Hurricane Dennis 2005 ..................................................................... Florida ....................................... Hendry ....................................... 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Indian River ............................... 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Lee ............................................. 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Martin ........................................ 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Miami-Dade ............................... 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Monroe ....................................... 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Okaloosa .................................... 7/10/05 ............. FEMA–1595–DR ........ Hurricane Dennis 2005 ..................................................................... Florida ....................................... Okeechobee ................................ 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Palm Beach ............................... 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 
325 

2005 ..................................................................... Florida ....................................... Santa Rosa ................................ 7/10/05 ............. FEMA–1595–DR ........ Hurricane Dennis 2005 ..................................................................... Florida ....................................... St. Lucie .................................... 10/24/05 ........... FEMA–1609–DR ........ Hurricane Wilma 2005 ..................................................................... Florida ....................................... Taylor ......................................... 7/10/05 ............. FEMA–1595–DR ........ Hurricane Dennis 2005 ..................................................................... Florida ....................................... Wakulla ...................................... 7/10/05 ............. FEMA–1595–DR ........ Hurricane Dennis 2005 ..................................................................... Florida ....................................... Walton ....................................... 7/10/05 ............. FEMA–1595–DR ........ Hurricane Dennis 2005 ..................................................................... Indiana ...................................... Adams ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Allen .......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Bartholomew .............................. 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Benton ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Blackford ................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Boone ......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Brown ........................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Carroll ........................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Cass .......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Clark .......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Clay ........................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Clinton ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Crawford .................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Daviess ...................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Dearborn .................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Decatur ...................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... DeKalb ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Delaware .................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Dubois ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Elkhart ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Fayette ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Floyd .......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Fountain .................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Franklin ..................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Fulton ........................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Gibson ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Grant ......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Greene ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Hamilton .................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Hancock ..................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Harrison ..................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Hendricks ................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Henry ......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Howard ...................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Huntington ................................. 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 
326 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2005 ..................................................................... Indiana ...................................... Jackson ...................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Jasper ........................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Jay ............................................. 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Jennings .................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Johnson ...................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Knox ........................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Kosciusko ................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Lake ........................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Laporte ...................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Lawrence ................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Madison ..................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Marion ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Marshall .................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Martin ........................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Miami ........................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Monroe ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Montgomery ............................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Morgan ...................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Newton ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Noble ......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Orange ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Owen .......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Parke ......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Pike ............................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Porter ......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Posey ......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Pulaski ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Putnam ...................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Randolph ................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Ripley ......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Rush .......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Scott .......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Shelby ........................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... St. Joseph .................................. 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Starke ........................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Sullivan ..................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 
327 

2005 ..................................................................... Indiana ...................................... Tippecanoe ................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Tipton ........................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Union ......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Vanderburgh .............................. 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Vanderburgh .............................. 11/08/05 ........... FEMA–1612–DR ........ Tornado and Severe Storms 2005 ..................................................................... Indiana ...................................... Vermillion .................................. 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Vigo ........................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Wabash ...................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Warren ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Warrick ...................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Warrick ...................................... 11/08/05 ........... FEMA–1612–DR ........ Tornado and Severe Storms 2005 ..................................................................... Indiana ...................................... Washington ................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Wayne ........................................ 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Wells .......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... White ......................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Indiana ...................................... Whitley ....................................... 1/21/05 ............. FEMA–1573 .............. Severe Winter Storms and Flooding 2005 ..................................................................... Kentucky .................................... Hopkins ...................................... 12/01/05 ........... FEMA–1617–DR ........ Severe Storms and Tornadoes 2005 ..................................................................... Kentucky .................................... Marshall .................................... 12/01/05 ........... FEMA–1617–DR ........ Severe Storms and Tornadoes 2005 ..................................................................... Louisiana ................................... Acadia ....................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Acadia ....................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Allen .......................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Ascension .................................. 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Ascension .................................. 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Assumption ................................ 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Beauregard ................................ 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Calcasieu ................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Calcasieu ................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Cameron .................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Cameron .................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... East Baton Rouge ..................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... East Feliciana ........................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Evangeline ................................. 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Iberia ......................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Iberia ......................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Iberville ...................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Jefferson .................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Jefferson .................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Jefferson Davies ........................ 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Jefferson Davis .......................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Lafayette .................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 
328 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2005 ..................................................................... Louisiana ................................... Lafayette .................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Lafourche ................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Lafourche ................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Livingston .................................. 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Livingston .................................. 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Orleans ...................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Plaquemines .............................. 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Plaquemines .............................. 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Pointe Coupee ........................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Sabine ....................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... St. Bernard ................................ 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... St. Charles ................................ 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... St. Helena .................................. 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... St. James ................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... St. John ..................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... St. Landry .................................. 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... St. Martin .................................. 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... St. Martin .................................. 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... St. Mary ..................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... St. Mary ..................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... St. Tammany ............................. 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Tangipahoa, Terrebonne, 

Vermilion, Washington, West Baton Rouge, and West Feliciana.

8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 

2005 ..................................................................... Louisiana ................................... Terrebonne ................................. 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Terrebonne ................................. 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Vermilion ................................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... Vermilion ................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Vernon ....................................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... Washington ................................ 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... West Baton Rouge ..................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Louisiana ................................... West Baton Rouge ..................... 9/24/05 ............. FEMA–1607–DR ........ Hurricane Rita 2005 ..................................................................... Louisiana ................................... West Feliciana ........................... 8/29/05 ............. FEMA–1603–DR ........ Hurricane Katrina 2005 ..................................................................... Massachusetts .......................... Berkshire ................................... 11/10/05 ........... FEMA–1614–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 
329 

2005 ..................................................................... Massachusetts .......................... Bristol ........................................ 11/10/05 ........... FEMA–1614–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2005 ..................................................................... Massachusetts .......................... Franklin ..................................... 11/10/05 ........... FEMA–1614–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2005 ..................................................................... Massachusetts .......................... Hampden ................................... 11/10/05 ........... FEMA–1614–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2005 ..................................................................... Massachusetts .......................... Hampshire ................................. 11/10/05 ........... FEMA–1614–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2005 ..................................................................... Massachusetts .......................... Middlesex ................................... 11/10/05 ........... FEMA–1614–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2005 ..................................................................... Massachusetts .......................... Norfolk ....................................... 11/10/05 ........... FEMA–1614–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2005 ..................................................................... Massachusetts .......................... Plymouth .................................... 11/10/05 ........... FEMA–1614–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2005 ..................................................................... Massachusetts .......................... Worcester ................................... 11/10/05 ........... FEMA–1614–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2005 ..................................................................... Mississippi ................................ Adams ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Amite ......................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Attala ......................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Choctaw ..................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Claiborne ................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Clarke ........................................ 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Copiah ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Covington .................................. 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Forrest ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Franklin ..................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ George ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Greene ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Hancock ..................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Harrison ..................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Hinds ......................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Holmes ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Humphreys ................................. 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Jackson ...................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Jasper ........................................ 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Jefferson .................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Jefferson Davis .......................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Jones .......................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Kemper ...................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Lamar ........................................ 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 
330 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2005 ..................................................................... Mississippi ................................ Lauderdale ................................. 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Lawrence ................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Leake ......................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Lincoln ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Lowndes ..................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Madison ..................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Marion ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Neshoba ..................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Newton ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Noxubee ..................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Oktibbeha .................................. 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Pearl River ................................. 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Perry .......................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Pike ............................................ 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Rankin ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Scott .......................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Simpson ..................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Smith ......................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Stone ......................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Walthall ..................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Warren ....................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Wayne ........................................ 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Wilkinson ................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Winston ...................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... Mississippi ................................ Yazoo ......................................... 8/29/05 ............. FEMA–1604–DR ........ Hurricane Katrina 2005 ..................................................................... New Hampshire ......................... Cheshire .................................... 10/26/05 ........... FEMA–1610–DR ........ Severe Storms and Floodign 2005 ..................................................................... New Hampshire ......................... Grafton ...................................... 10/26/05 ........... FEMA–1610–DR ........ Severe Storms and Floodign 2005 ..................................................................... New Hampshire ......................... Hillsborough .............................. 10/26/05 ........... FEMA–1610–DR ........ Severe Storms and Floodign 2005 ..................................................................... New Hampshire ......................... Merrimack .................................. 10/26/05 ........... FEMA–1610–DR ........ Severe Storms and Floodign 2005 ..................................................................... New Hampshire ......................... Sullivan ..................................... 10/26/05 ........... FEMA–1610–DR ........ Severe Storms and Floodign 2005 ..................................................................... New Jersey ................................. Bergen ....................................... 4/19/05 ............. FEMA–1588–DR ........ Severe Storms and Flooding 2005 ..................................................................... New Jersey ................................. Essex ......................................... 4/19/05 ............. FEMA–1588–DR ........ Severe Storms and Flooding 2005 ..................................................................... New Jersey ................................. Gloucester .................................. 4/19/05 ............. FEMA–1588–DR ........ Severe Storms and Flooding 2005 ..................................................................... New Jersey ................................. Hunterdon .................................. 4/19/05 ............. FEMA–1588–DR ........ Severe Storms and Flooding 2005 ..................................................................... New Jersey ................................. Mercer ........................................ 4/19/05 ............. FEMA–1588–DR ........ Severe Storms and Flooding 2005 ..................................................................... New Jersey ................................. Morris ........................................ 4/19/05 ............. FEMA–1588–DR ........ Severe Storms and Flooding 
331 

2005 ..................................................................... New Jersey ................................. Passaic ...................................... 4/19/05 ............. FEMA–1588–DR ........ Severe Storms and Flooding 2005 ..................................................................... New Jersey ................................. Sussex ....................................... 4/19/05 ............. FEMA–1588–DR ........ Severe Storms and Flooding 2005 ..................................................................... New Jersey ................................. Warren ....................................... 4/19/05 ............. FEMA–1588–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Broome ...................................... 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Chenango .................................. 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Cortland ..................................... 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Delaware .................................... 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Orange ....................................... 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Rensselaer ................................. 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Schenectady .............................. 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Schoharie ................................... 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Sullivan ..................................... 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Tioga .......................................... 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... New York ................................... Ulster ......................................... 4/19/05 ............. FEMA–1589–DR ........ Severe Storms and Flooding 2005 ..................................................................... Ohio ........................................... Ashland ..................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Athens ....................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Auglaize ..................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Belmont ..................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Clark .......................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Coshocton .................................. 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Crawford .................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Delaware .................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Franklin ..................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Henry ......................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Huron ......................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Jefferson .................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Logan ......................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 
332 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2005 ..................................................................... Ohio ........................................... Miami ........................................ 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Morgan ...................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Muskingum ................................ 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Pickaway .................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Pike ............................................ 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Ross ........................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Scioto ......................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Warren ....................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Washington ................................ 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Ohio ........................................... Wyandot ..................................... 2/15/05 ............. FEMA–1580 .............. Severe Winter Storms, Heavy Rains, and Flooding 2005 ..................................................................... Pennsylvania ............................. Bradford .................................... 4/14/05 ............. FEMA–1587–DR ........ Severe Storms and Flooding 2005 ..................................................................... Pennsylvania ............................. Bucks ......................................... 4/14/05 ............. FEMA–1587–DR ........ Severe Storms and Flooding 2005 ..................................................................... Pennsylvania ............................. Columbia ................................... 4/14/05 ............. FEMA–1587–DR ........ Severe Storms and Flooding 2005 ..................................................................... Pennsylvania ............................. Luzerne ...................................... 4/14/05 ............. FEMA–1587–DR ........ Severe Storms and Flooding 2005 ..................................................................... Pennsylvania ............................. Monroe ....................................... 4/14/05 ............. FEMA–1587–DR ........ Severe Storms and Flooding 2005 ..................................................................... Pennsylvania ............................. Northampton .............................. 4/14/05 ............. FEMA–1587–DR ........ Severe Storms and Flooding 2005 ..................................................................... Pennsylvania ............................. Pike ............................................ 4/14/05 ............. FEMA–1587–DR ........ Severe Storms and Flooding 2005 ..................................................................... Pennsylvania ............................. Wayne ........................................ 4/14/05 ............. FEMA–1587–DR ........ Severe Storms and Flooding 2005 ..................................................................... Pennsylvania ............................. Wyoming .................................... 4/14/05 ............. FEMA–1587–DR ........ Severe Storms and Flooding 2005 ..................................................................... Texas ......................................... Angelina .................................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Brazoria ..................................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Chambers .................................. 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Fort Bend ................................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Galveston ................................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Hardin ........................................ 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Harris ......................................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 
333 

2005 ..................................................................... Texas ......................................... Jasper ........................................ 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Jefferson .................................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Liberty ........................................ 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Montgomery ............................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Nacogdoches ............................. 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Newton ....................................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Orange ....................................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Polk ............................................ 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Sabine ....................................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... San Augustine ........................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... San Jacinto ................................ 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Shelby ........................................ 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Trinity ........................................ 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Tyler ........................................... 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Texas ......................................... Walker ........................................ 9/24/05 ............. FEMA–1606–DR ........ Hurricane Rita 2005 ..................................................................... Wyoming .................................... Campbell ................................... 8/12/05 ............. FEMA–1599–DR ........ Tornado 2006 ..................................................................... Arkansas .................................... Conway ...................................... 4/13/06 ............. FEMA–1636–DR ........ Severe Storms and Tornadoes 2006 ..................................................................... Arkansas .................................... Cross ......................................... 4/13/06 ............. FEMA–1636–DR ........ Severe Storms and Tornadoes 2006 ..................................................................... Arkansas .................................... Fulton ........................................ 4/13/06 ............. FEMA–1636–DR ........ Severe Storms and Tornadoes 2006 ..................................................................... Arkansas .................................... Greene ....................................... 4/13/06 ............. FEMA–1636–DR ........ Severe Storms and Tornadoes 2006 ..................................................................... Arkansas .................................... Lawrence ................................... 4/13/06 ............. FEMA–1636–DR ........ Severe Storms and Tornadoes 2006 ..................................................................... Arkansas .................................... Randolph ................................... 4/13/06 ............. FEMA–1636–DR ........ Severe Storms and Tornadoes 2006 ..................................................................... Arkansas .................................... White ......................................... 4/13/06 ............. FEMA–1636–DR ........ Severe Storms and Tornadoes 2006 ..................................................................... California ................................... Contra Costa ............................. 2/03/06 ............. FEMA–1628–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2006 ..................................................................... California ................................... Del Norte ................................... 2/03/06 ............. FEMA–1628–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2006 ..................................................................... California ................................... Lake ........................................... 2/03/06 ............. FEMA–1628–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2006 ..................................................................... California ................................... Marin ......................................... 2/03/06 ............. FEMA–1628–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2006 ..................................................................... California ................................... Mendocino ................................. 2/03/06 ............. FEMA–1628–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2006 ..................................................................... California ................................... Napa .......................................... 2/03/06 ............. FEMA–1628–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2006 ..................................................................... California ................................... Sacramento ............................... 2/03/06 ............. FEMA–1628–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2006 ..................................................................... California ................................... Siskiyou ..................................... 2/03/06 ............. FEMA–1628–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 
334 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2006 ..................................................................... California ................................... Solano ........................................ 2/03/06 ............. FEMA–1628–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2006 ..................................................................... California ................................... Sonoma ...................................... 2/03/06 ............. FEMA–1628–DR ........ Severe Storms, Flooding, Mudslides, and Landslides 2006 ..................................................................... Hawaii ....................................... Hawaii ....................................... 10/17/06 ........... FEMA–1664–DR ........ Earthquake 2006 ..................................................................... Hawaii ....................................... Honolulu .................................... 5/02/06 ............. FEMA–1640–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Hawaii ....................................... Kauai ......................................... 5/02/06 ............. FEMA–1640–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Illinois ........................................ Sangamon ................................. 3/28/06 ............. FEMA–1633–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Indiana ...................................... Lake ........................................... 10/06/06 ........... FEMA–1662–DR ........ Severe Storms and Flooding 2006 ..................................................................... Indiana ...................................... Vanderburgh .............................. 10/06/06 ........... FEMA–1662–DR ........ Severe Storms and Flooding 2006 ..................................................................... Indiana ...................................... Warrick ...................................... 10/06/06 ........... FEMA–1662–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Allen .......................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Beauregard ................................ 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Calcasieu ................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Caldwell ..................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Franklin ..................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Grant ......................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Jefferson Davis .......................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... LaSalle ....................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Madison ..................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Morehouse ................................. 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Natchitoches .............................. 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Richland .................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Sabine ....................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... St. Helena .................................. 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... St. Landry .................................. 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Vernon ....................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Louisiana ................................... Winn .......................................... 11/02/06 ........... FEMA–1668–DR ........ Severe Storms and Flooding 2006 ..................................................................... Maine ......................................... York ........................................... 5/25/06 ............. FEMA–1644–DR ........ Severe Storms and Flooding 2006 ..................................................................... Massachusetts .......................... Essex ......................................... 5/25/06 ............. FEMA–1642–DR ........ Severe Storms and Flooding 2006 ..................................................................... Massachusetts .......................... Middlesex ................................... 5/25/06 ............. FEMA–1642–DR ........ Severe Storms and Flooding 2006 ..................................................................... Massachusetts .......................... Suffolk ....................................... 5/25/06 ............. FEMA–1642–DR ........ Severe Storms and Flooding 2006 ..................................................................... Missouri ..................................... Andrew ....................................... 4/05/06 ............. FEMA–1635–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Benton ....................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 
335 

2006 ..................................................................... Missouri ..................................... Boone ......................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Butler ......................................... 4/05/06 ............. FEMA–1635–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Carroll ........................................ 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Cass .......................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Cedar ......................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Christian .................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Cooper ....................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Dunklin ...................................... 4/05/06 ............. FEMA–1635–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Greene ....................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Henry ......................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Hickory ....................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Iron ............................................ 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Johnson ...................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Lawrence ................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Lincoln ....................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Mississippi ................................ 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Monroe ....................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Morgan ...................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... New Madrid ............................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Newton ....................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Pemiscot .................................... 4/05/06 ............. FEMA–1635–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Perry .......................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Pettis ......................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Pettis ......................................... 4/05/06 ............. FEMA–1635–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Phelps ........................................ 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Putnam ...................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Randolph ................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Saline ........................................ 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Scott .......................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... St. Clair ..................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... St. Francois ............................... 4/05/06 ............. FEMA–1635–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Ste. Genevieve ........................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Stoddard .................................... 4/05/06 ............. FEMA–1635–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Taney ......................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Vernon ....................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Webster ...................................... 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... Missouri ..................................... Wright ........................................ 3/16/06 ............. FEMA–1631–DR ........ Severe Storms, Tornadoes, and Flooding 2006 ..................................................................... New Hampshire ......................... Belknap ..................................... 5/25/06 ............. FEMA–1643–DR ........ Severe Storms and Flooding 2006 ..................................................................... New Hampshire ......................... Carroll ........................................ 5/25/06 ............. FEMA–1643–DR ........ Severe Storms and Flooding 2006 ..................................................................... New Hampshire ......................... Hillsborough .............................. 5/25/06 ............. FEMA–1643–DR ........ Severe Storms and Flooding 
336 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2006 ..................................................................... New Hampshire ......................... Merrimack .................................. 5/25/06 ............. FEMA–1643–DR ........ Severe Storms and Flooding 2006 ..................................................................... New Hampshire ......................... Rockingham ............................... 5/25/06 ............. FEMA–1643–DR ........ Severe Storms and Flooding 2006 ..................................................................... New Hampshire ......................... Strafford .................................... 5/25/06 ............. FEMA–1643–DR ........ Severe Storms and Flooding 2006 ..................................................................... New Jersey ................................. Hunterdon .................................. 7/07/06 ............. FEMA–1653–DR ........ Severe Storms and Flooding 2006 ..................................................................... New Jersey ................................. Mercer ........................................ 7/07/06 ............. FEMA–1653–DR ........ Severe Storms and Flooding 2006 ..................................................................... New Jersey ................................. Warren ....................................... 7/07/06 ............. FEMA–1653–DR ........ Severe Storms and Flooding 2006 ..................................................................... New Mexico ................................ Dona Ana ................................... 8/30/06 ............. FEMA–1659–DR ........ Severe Storms and Flooding 2006 ..................................................................... New Mexico ................................ Otero .......................................... 8/30/06 ............. FEMA–1659–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Broome ...................................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Chenango .................................. 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Delaware .................................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Erie ............................................ 10/24/06 ........... FEMA–1665–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Genesee ..................................... 10/24/06 ........... FEMA–1665–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Herkimer .................................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Montgomery ............................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Niagara ...................................... 10/24/06 ........... FEMA–1665–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Oneida ....................................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Orange ....................................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Orleans ...................................... 10/24/06 ........... FEMA–1665–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Otsego ....................................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Schoharie ................................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Sullivan ..................................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Tioga .......................................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... New York ................................... Ulster ......................................... 7/01/06 ............. FEMA–1650–DR ........ Severe Storms and Flooding 2006 ..................................................................... Ohio ........................................... Ashtabula .................................. 8/01/06 ............. FEMA–1656–DR ........ Severe Storms, Straight Line Winds, and Flooding 2006 ..................................................................... Ohio ........................................... Cuyahoga ................................... 7/02/06 ............. FEMA–1651–DR ........ Severe Storms, Tornadoes, Straight Line Winds, 

and Flooding 

2006 ..................................................................... Ohio ........................................... Erie ............................................ 7/02/06 ............. FEMA–1651–DR ........ Severe Storms, Tornadoes, Straight Line Winds,

and Flooding 

2006 ..................................................................... Ohio ........................................... Geauga ...................................... 8/01/06 ............. FEMA–1656–DR ........ Severe Storms, Straight Line Winds, and Flooding 2006 ..................................................................... Ohio ........................................... Huron ......................................... 7/02/06 ............. FEMA–1651–DR ........ Severe Storms, Tornadoes, Straight Line Winds, 

and Flooding 

2006 ..................................................................... Ohio ........................................... Lake ........................................... 8/01/06 ............. FEMA–1656–DR ........ Severe Storms, Straight Line Winds, and Flooding 
337 

2006 ..................................................................... Ohio ........................................... Lucas ......................................... 7/02/06 ............. FEMA–1651–DR ........ Severe Storms, Tornadoes, Straight Line Winds, 

and Flooding 

2006 ..................................................................... Ohio ........................................... Sandusky ................................... 7/02/06 ............. FEMA–1651–DR ........ Severe Storms, Tornadoes, Straight Line Winds, 

and Flooding 

2006 ..................................................................... Ohio ........................................... Stark .......................................... 7/02/06 ............. FEMA–1651–DR ........ Severe Storms, Tornadoes, Straight Line Winds, 

and Flooding 

2006 ..................................................................... Oklahoma .................................. Canadian ................................... 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Cotton ........................................ 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Delaware .................................... 4/13/06 ............. FEMA–1637–DR ........ Severe Storms and Tornadoes 2006 ..................................................................... Oklahoma .................................. Garvin ........................................ 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Hughes ...................................... 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Lincoln ....................................... 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Logan ......................................... 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Mayes ........................................ 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Okfuskee .................................... 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Oklahoma .................................. 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Pottawatomie ............................. 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Seminole .................................... 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Oklahoma .................................. Stephens .................................... 1/10/06 ............. FEMA–1623–DR ........ Severe Wildfire Threat 2006 ..................................................................... Pennsylvania ............................. Berks ......................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Bradford .................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Carbon ....................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Chester ...................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Dauphin ..................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Franklin ..................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Lackawanna .............................. 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Lancaster ................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Lebanon ..................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Luzerne ...................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Monroe ....................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Montgomery ............................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Montour ..................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Pike ............................................ 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Schuylkill ................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Susquehanna ............................. 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Wayne ........................................ 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Pennsylvania ............................. Wyoming .................................... 6/30/06 ............. FEMA–1649–DR ........ Severe Storms, Flooding, and Mudslides 2006 ..................................................................... Tennessee .................................. Benton ....................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Cannon ...................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Carroll ........................................ 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 
338 

PRESIDENTIAL DISASTER DECLARATIONS WITH INDIVIDUAL ASSISTANCE—Continued 

Year State County Date FEMA No Incident Type 

2006 ..................................................................... Tennessee .................................. Cheatham .................................. 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Cumberland ............................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Davidson .................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Dickson ...................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Dyer ........................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Fayette ....................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Gibson ....................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Haywood .................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Maury ......................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Sumner ...................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Warren ....................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Tennessee .................................. Weakley ...................................... 4/05/06 ............. FEMA–1634–DR ........ Tornadoes and Severe Storms 2006 ..................................................................... Texas ......................................... Callahan .................................... 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... Cooke ......................................... 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... Eastland .................................... 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... Erath .......................................... 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... Hood .......................................... 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... Kerr ............................................ 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... Montague ................................... 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... Palo Pinto .................................. 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... Potter ......................................... 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... Tarrant ....................................... 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... Wise ........................................... 1/11/06 ............. FEMA–1624–DR ........ Extreme Wildfire Threat 2006 ..................................................................... Texas ......................................... El Paso ...................................... 8/15/06 ............. FEMA–1658–DR ........ Flooding 2006 ..................................................................... Washington ................................ Clark .......................................... 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Washington ................................ Cowlitz ....................................... 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Washington ................................ Grays Harbor ............................. 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Washington ................................ King ........................................... 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Washington ................................ Lewis ......................................... 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Washington ................................ Pierce ......................................... 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 
339 

2006 ..................................................................... Washington ................................ Skagit ........................................ 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Washington ................................ Skamania .................................. 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Washington ................................ Snohomish ................................. 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Washington ................................ Thurston .................................... 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

2006 ..................................................................... Washington ................................ Wahkiakum ................................ 12/12/06 ........... FEMA–1671–DR ........ Severe Storms, Flooding, Landslides, and 

Mudslides 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

NY ................................ Albany, Columbia, Dutchess, Niagara, Orange, Ulster. 4–15–2001 ...... 6–20–2001 ...... 10–16–2001 .... 6–17–2002 ...... S1564 .......... Albany: Hail, excessive rain; Colum- bia: Hail, high winds; Dutchess: 

Hail; Niagara: Flooding, hail; Orange: Drought; Ulster: Hail; Ulster: Hail, high winds.

6 12 

CT ................................ ........................................................ 6–03–2001 ...... 6–03–2001 ...... 10–16–2001 .... 6–17–2002 ...... S1564 .......... Hail ...................................................... .......... 2 MA ............................... ........................................................ 5–28–2001 ...... 6–20–2001 ...... 10–16–2001 .... 6–17–2002 ...... S1564 .......... Hail, high winds .................................. .......... 1 OR ................................ Jackson .......................................... 9–01–2000 ...... 4–16–2002 ...... 10–16–2001 .... 12–18–2001 .... S1565 .......... Drought ................................................ 1 ..........OR ................................ Josephine ....................................... 9–01–2000 ...... 4–16–2002 ...... 10–16–2001 .... 2–14–2002 ...... S1565 .......... Drought ................................................ 1 ..........OR ................................ Union ............................................. 9–01–2000 ...... 4–16–2002 ...... 10–16–2001 .... 6–17–2002 ...... S1565 .......... Drought ................................................ 1 4 TN ................................ Anderson, Campbell, Carroll, 

Carter, Crockett, Dyer, Giles, Greene, Hancock, Johnson, Maury, Obion, Weakley.

1–01–2001 ...... 4–16–2002 ...... 10–16–2001 .... 6–17–2002 ...... S1566 .......... Drought, excessive heat, insect infestation, hail, excessive rain, freezing conditions. 13 28 

AL ................................ ........................................................ 4–01–2001 ...... 4–16–2002 ...... 10–16–2001 .... 6–17–2002 ...... S1566 .......... Drought, insect infestation ................. .......... 2 AR ................................ ........................................................ 4–01–2001 ...... 4–16–2002 ...... 10–16–2001 .... 6–17–2002 ...... S1566 .......... Drought, insect infestation ................. .......... 1 KY ................................ ........................................................ 3–15–2001 ...... 4–16–2002 ...... 10–16–2001 .... 6–17–2002 ...... S1566 .......... Drought, insect infestation, excessive 

heat.

.......... 5 

MO ............................... ........................................................ 4–01–2001 ...... 4–16–2002 ...... 10–16–2001 .... 6–17–2002 ...... S1566 .......... Drought, insect infestation ................. .......... 1 NC ................................ ........................................................ 3–15–2001 ...... 6–15–2001 ...... 10–16–2001 .... 6–17–2002 ...... S1566 .......... Drought, excessive heat ...................... .......... 4 VA ................................ ........................................................ 1–01–2001 ...... 4–16–2002 ...... 10–16–2001 .... 6–17–2002 ...... S1566 .......... Drought, excessive heat, hail, excessive rain. .......... 5 
340 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

WA ............................... Chelan ........................................... 6–26–2001 ...... 6–27–2001 ...... 10–16–2001 .... 6–17–2002 ...... S1567 .......... Severe storms with damaging wind, 

rain, hail.

1 3 

WA ............................... Douglas, Klickitat, Walla Walla ..... 6–26–2001 ...... 6–27–2001 ...... 10–16–2001 .... 4–23–2002 ...... S1567 .......... Severe storms with damaging wind, 

rain, hail.

3 ..........

OR ................................ ........................................................ 6–26–2001 ...... 6–27–2001 ...... 10–16–2001 .... 6–17–2002 ...... S1567 .......... Severe storms with damaging wind, 

rain, hail.

.......... 4 

CA ................................ Madera ........................................... 4–04–2001 ...... 4–20–2001 ...... 10–25–2001 .... 6–25–2002 ...... S1568 .......... Freezing temperatures, hailstorms ..... 1 5 CA ................................ Mendocino ...................................... 1–01–2001 ...... 7–30–2001 ...... 10–25–2001 .... 6–25–2002 ...... S1569 .......... (1) Freezing temperatures; ..................

(2) severe heat; ...................................(3) Unseasonable rainfall; ..................(4) Drought ..........................................

1 4 

CO ................................ Eagle,Garfield, Pitkin ..................... 7–09–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1570 .......... Drought ................................................ 3 8 UT ................................ ........................................................ 7–09–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1570 .......... Drought ................................................ .......... 2 KS ................................ Atchison, Greeley, Hamilton, Jefferson, Jewell, Kearny, Kingman, Lane, Leavenworth, 

Logan, Morton, Scott, Wichita.

1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1571 .......... Drought, excessive rains, flash flooding, tornadoes, hail, repeated excessive winds. 13 28 

CO ................................ ........................................................ 1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1571 .......... Drought, excessive rains, flash flooding, tornadoes, hail, repeated excessive winds. .......... 4 MO ............................... ........................................................ 1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1571 .......... Drought, excessive rains, flash flooding, tornadoes, hail, repeated excessive winds. .......... 2 NE ................................ ........................................................ 1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1571 .......... Drought, excessive rains, flash flooding, tornadoes, hail, repeated excessive winds. .......... 2 NE ................................ Holt ................................................ 7–03–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1572 .......... Storms, hail ......................................... 1 8 OK ................................ All counties except Choctaw, 

McCurtain.

6–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1573 .......... Drought ................................................ 75 2 

AR ................................ ........................................................ 6–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1573 .......... Drought ................................................ .......... 6 CO ................................ ........................................................ 6–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1573 .......... Drought ................................................ .......... 1 KS ................................ ........................................................ 6–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1573 .......... Drought ................................................ .......... 14 MO ............................... ........................................................ 6–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1573 .......... Drought ................................................ .......... 2 NM ............................... ........................................................ 6–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1573 .......... Drought ................................................ .......... 1 
341 

TX ................................ ........................................................ 6–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1573 .......... Drought ................................................ .......... 18 OR ................................ Baker ............................................. 9–01–2000 ...... 4–25–2002 ...... 10–25–2001 .... 6–17–2002 ...... S1574 .......... Drought ................................................ 1 ..........OR ................................ Gilliam ........................................... 9–01–2000 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1574 .......... Drought ................................................ 1 2 ID ................................. ........................................................ 9–01–2000 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1574 .......... Drought ................................................ .......... 1 TX ................................ Cottle ............................................. 7–23–2001 ...... 7–23–2001 ...... 10–25–2001 .... 6–25–2002 ...... S1575 .......... Fire, excessive temperatures ............... 1 7 UT ................................ Beaver, Box Elder, Cache, Carbon, 

Davis, Emery, Iron, Juab, Kane, Millard, Morgan, Piute, Rich, San Juan, Sanpete, Sevier, Summit, Tooele, Utah, Wasatch, Washington, Wayne, Weber.

1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1576 .......... (1) Drought, Grasshopper and Mormon Cricket infestation;.

(2) Freezing temperatures, high winds 

23 6 

AZ ................................ ........................................................ 1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1576 .......... (1) Drought, Grasshopper and Mormon Cricket infestation;.

(2) Freezing temperatures, high winds 

.......... 4 

CO ................................ ........................................................ 1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1576 .......... (1) Drought, Grasshopper and Mormon Cricket infestation; Freezing 

temperatures, high winds.

.......... 5 

ID ................................. ........................................................ 1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1576 .......... (1) Drought, Grasshopper and Mormon Cricket infestation; Freezing 

temperatures, high winds.

.......... 1 

NM ............................... ........................................................ 1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1576 .......... (1) Drought, Grasshopper and Mormon Cricket infestation; Freezing 

temperatures, high winds.

.......... 1 

NV ................................ ........................................................ 1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1576 .......... (1) Drought, Grasshopper and Mormon Cricket infestation; Freezing 

temperatures, high winds.

.......... 3 

WY ............................... ........................................................ 1–01–2001 ...... 4–25–2002 ...... 10–25–2001 .... 6–25–2002 ...... S1576 .......... (1) Drought, Grasshopper and Mormon Cricket infestation;.

(2) Freezing temperatures, high winds 

.......... 3 

OR ................................ Morrow ........................................... 9–01–2000 ...... 4–29–2002 ...... 10–29–2001 .... 6–25–2002 ...... S1577 .......... Drought ................................................ 1 ..........WA ............................... ........................................................ 9–01–2000 ...... 4–29–2002 ...... 10–29–2001 .... 6–29–2002 ...... S1577 .......... Drought ................................................ .......... 1 NY ................................ Saratoga ........................................ 4–01–2001 ...... 5–28–2001 ...... 10–29–2001 .... 6–29–2002 ...... S1578 .......... Low rainfall (Drought), hail, lightning 1 8 WY ............................... Lincoln, Sweetwater ....................... 1–01–2001 ...... 5–01–2002 ...... 11–01–2001 .... 6–25–2002 ...... S1579 .......... Drought, wildfire conditions ................ 2 1 WY ............................... Big Horn, Campbell, Park, Sheridan. 1–01–2001 ...... 5–01–2002 ...... 11–01–2001 .... 1–29–2002 ...... S1579 .......... Drought, wildfire conditions ................ 4 2 WY ............................... Fremont, Hot Springs, Johnson, 

Natrona, Sublette, Washakie, Wind River Indian Reservation.

1–01–2001 ...... 5–01–2002 ...... 11–01–2001 .... 7–01–2002 ...... S1579 .......... Drought, wildfire conditions ................ 6 4 

CO ................................ ........................................................ 1–01–2001 ...... 5–01–2002 ...... 11–01–2001 .... 7–01–2002 ...... S1579 .......... Drought, wildfire conditions ................ .......... 1 ID ................................. ........................................................ 1–01–2001 ...... 5–01–2002 ...... 11–01–2001 .... 6–25–2002 ...... S1579 .......... Drought, wildfire conditions ................ .......... 1 
342 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

ID ................................. ........................................................ 1–01–2001 ...... 5–01–2002 ...... 11–01–2001 .... 7–01–2002 ...... S1579 .......... Drought, wildfire conditions ................ .......... 2 MT ................................ ........................................................ 1–01–2001 ...... 5–01–2002 ...... 11–01–2001 .... 1–29–2002 ...... S1579 .......... Drought, wildfire conditions ................ .......... 4 UT ................................ ........................................................ 1–01–2001 ...... 5–01–2002 ...... 11–01–2001 .... 6–25–2002 ...... S1579 .......... Drought, wildfire conditions ................ .......... 3 OH ................................ Brown, Clermont, Defiance, Fulton, 

Gallia, Hancock, Jackson, Ottawa, Paulding, Putnam, Vinton, Wyandot.

5–01–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2002 ...... S1580 .......... Extreme weather conditions with excessive rain, flooding, armyworms. 12 24 

IN ................................. ........................................................ 5–01–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2002 ...... S1580 .......... Extreme weather conditions with excessive rain, flooding, armyworms. .......... 2 KY ................................ ........................................................ 5–01–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2002 ...... S1580 .......... Extreme weather conditions with excessive rain, flooding, armyworms. .......... 4 WV ............................... ........................................................ 5–01–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2002 ...... S1580 .......... Extreme weather conditions with excessive rain, flooding, armyworms. .......... 2 LA ................................ Acadia, Avoyelles, Beauregard, 

Bossier, Caddo, Caldwell, Cameron, Catahoula, Concordia, De Soto, East Carroll, Evangeline, Franklin, Grant, Iberville, Jefferson Davis, La Salle, Madison, Morehouse, Natchitoches, Ouachita, Pointe Coupee, Rapides, Red River, Richland, St. Landry, St. Martin, Tensas, Vermilion, Vernon, West Baton Rouge, West Carroll.

8–27–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2001 ...... S1581 .......... Excessive rainfall, high humidity ....... 32 17 

AR ................................ ........................................................ 8–27–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2001 ...... S1581 .......... Excessive rainfall, high humidity ....... .......... 5 MS ............................... ........................................................ 8–27–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2001 ...... S1581 .......... Excessive rainfall, high humidity ....... .......... 6 TX ................................ ........................................................ 8–27–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2001 ...... S1581 .......... Excessive rainfall, high humidity ....... .......... 8 TX ................................ Bee, San Patricio ........................... 5–01–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2001 ...... S1582 .......... Drought ................................................ 2 7 WA ............................... Chelan ........................................... 6–08–2001 ...... 6–08–2001 ...... 11–02–2001 .... 7–02–2001 ...... S1583 .......... Hailstorm ............................................. 1 6 WA ............................... Lincoln ........................................... 5–21–2001 ...... 5–24–2001 ...... 11–02–2001 .... 7–02–2001 ...... S1583 .......... Freeze .................................................. 1 7 WA ............................... Asotin, Benton, Douglas, Klickitat, 

Lincoln, Stevens.

1–01–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2001 ...... S1583 .......... Drought ................................................ 6 14 

ID ................................. ........................................................ 1–01–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2001 ...... S1583 .......... Drought ................................................ .......... 1 
343 

OR ................................ ........................................................ 1–01–2001 ...... 5–02–2002 ...... 11–02–2001 .... 7–02–2001 ...... S1583 .......... Drought ................................................ .......... 7 MI ................................ Jackson, Lake, Mason, Oceana ..... 5–15–2001 ...... 5–17–2001 ...... 11–09–2001 .... 7–09–2002 ...... S1584 .......... Excessive rain, flash flooding, hail .... 4 13 MI ................................ Allegan, Berrien, Cass, Kalamazoo, 

Van Buren.

5–12–2001 ...... 5–31–2001 ...... 11–09–2001 .... 7–09–2002 ...... S1584 .......... Frost, freezing temperatures, cooler 

than normal temperatures.

5 6 

IN ................................. ........................................................ 5–12–2001 ...... 5–31–2001 ...... 11–09–2001 .... 7–09–2002 ...... S1584 .......... Frost, freezing temperatures, cooler 

than normal temperatures.

.......... 3 

TX ................................ Borden, Brown, Concho, Dimmit, 

Duval, Gaines, Mitchell, Runnels, Tom Green, Wilbarger.

1–01–2001 ...... 5–26–2002 ...... 11–26–2001 .... 7–26–2002 ...... S1585 .......... Drought ................................................ 10 40 

NM ............................... ........................................................ 1–01–2001 ...... 5–26–2002 ...... 11–26–2001 .... 7–26–2002 ...... S1585 .......... Drought ................................................ .......... 1 OK ................................ ........................................................ 1–01–2001 ...... 5–26–2002 ...... 11–26–2001 .... 7–26–2002 ...... S1585 .......... Drought ................................................ .......... 2 CA ................................ Lassen ........................................... 1–01–2001 ...... 5–29–2002 ...... 11–29–2001 .... 7–29–2002 ...... S1586 .......... Drought, excessive temperatures ........ 1 1 MI ................................ Alcona, Alger, Alpena, Antrim, 

Arenac, Bay, Benzie, Berrien, Cass, Charlevoix, Cheboygan, Chippewa, Clare, Clinton, Delta, Dickinson, Emmet, Genesee, Gladwin, Grand Traverse, Gratiot, Hillsdale, Huron, Ingham, Ionia, Iosco, Iron, Isabella, Jackson, Kalamazoo, Kalkaska, Kent, Lake, Lapeer, Leelanau, Lenawee, Livingston, Luce, Mackinac, Macomb, Manistee, Marquette, Mason, Mecosta, Menominee, Midland, Missaukee, Monroe, Montcalm, Montmorency, Muskegon, Newaygo, Oakland, Oceana, Ogemaw, Osceola, Oscoda, Otsego, Ottawa, Presque Isle, Roscommon, Saginaw, Sanilac, Schoolcraft, Shiawassee, St. Clair, St. Joseph, Tuscola, Van Buren, Washtenaw, Wayne, Wexford.

6–12–2001 ...... 8–17–2001 ...... 11–29–2001 .... 7–29–2002 ...... S1587 .......... Drought ................................................ 72 10 

IN ................................. ........................................................ 6–12–2001 ...... 8–17–2001 ...... 11–29–2001 .... 7–29–2002 ...... S1587 .......... Drought ................................................ .......... 5 OH ................................ ........................................................ 6–12–2001 ...... 8–17–2001 ...... 11–29–2001 .... 7–29–2002 ...... S1587 .......... Drought ................................................ .......... 4 WI ................................ ........................................................ 6–12–2001 ...... 8–17–2001 ...... 11–29–2001 .... 7–29–2002 ...... S1587 .......... Drought ................................................ .......... 4 
344 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

TX ................................ Glasscock, Howard, Jim Hogg, 

Kleberg, Zapata.

1–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1588 .......... Drought, excessive temperatures 

(heat), high winds, low humidity.

5 16 

TX ................................ Collingsworth ................................. 6–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1589 .......... Drought; Lightning, wildfires .............. 1 5 OK ................................ ........................................................ 6–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1589 .......... Drought; Lightning, wildfires .............. .......... 2 TX ................................ Hardeman, Maverick ...................... 1–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 7–26–2002 ...... S1590 .......... .............................................................. 2 10 TX ................................ Childress, Cottle, Hidalgo, Kent, 

Starr.

1–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1590 .......... Drought, excessive heat ...................... 5 15 

OK ................................ ........................................................ 1–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1590 .......... Drought, excessive heat ...................... .......... 2 PA ................................ Adams, Allegheny, Armstrong, 

Beaver, Bedford, Berks, Blair, Butler, Cambria, Centre, Clinton, Chester, Clarion, Clearfield, Columbia, Cumberland, Dauphin, Elk, Erie, Forest, Franklin, Fulton, Huntingdon, Indiana, Jefferson, Juniata, Lancaster, Lawrence, Lebanon, Lycoming, Mercer, Mifflin, Montour, Northumberland, Perry, Schuylkill, Snyder, Somerset, Union, Venango, Warren, Washington, Westmoreland, York.

1–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1591 .......... Drought ................................................ 44 14 

DE ................................ ........................................................ 1–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1591 .......... Drought ................................................ .......... 1 MD ............................... ........................................................ 1–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1591 .......... Drought ................................................ .......... 8 NY ................................ ........................................................ 1–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1591 .......... Drought ................................................ .......... 2 OH ................................ ........................................................ 1–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1591 .......... Drought ................................................ .......... 4 WV ............................... ........................................................ 1–01–2001 ...... 6–05–2002 ...... 12–05–2001 .... 8–05–2002 ...... S1591 .......... Drought ................................................ .......... 4 TX ................................ Austin, Burleson, Chambers, Colorado, Fort Bend, Goliad, Jefferson, Matagorda, Wharton. 8–20–2001 ...... 9–19–2001 ...... 12–13–2001 .... 8–13–2002 ...... S1592 .......... Excessive rain, flooding, flash flood- ing. 9 21 LA ................................ ........................................................ 8–20–2001 ...... 9–19–2001 ...... 12–13–2001 .... 8–13–2002 ...... S1592 .......... Excessive rain, flooding, flash flooding. .......... 1 
345 

TX ................................ Cottle ............................................. 9–20–2001 ...... 9–20–2001 ...... 12–13–2001 .... 8–13–2002 ...... S1593 .......... Excessive rain, flash flooding, hail, 

high winds.

1 7 

TX ................................ Floyd .............................................. 6–01–2001 ...... 6–05–2001 ...... 12–13–2001 .... 8–13–2002 ...... S1594 .......... Excessive rain, flash flooding, flooding, high winds, hail, lightning, 

tornado.

1 7 

TX ................................ Uvalde ............................................ 5–24–2001 ...... 5–24–2001 ...... 12–13–2001 .... 8–13–2002 ...... S1595 .......... High wind, hail ................................... 1 8 TX ................................ Wilson ............................................ 5–20–2001 ...... 5–20–2001 ...... 12–13–2001 .... 8–13–2002 ...... S1596 .......... Extreme amount of hail, high winds .. 1 5 ID ................................. Franklin, Oneida ............................ 1–01–2001 ...... 6–18–2002 ...... 12–18–2001 .... 6–25–2002 ...... S1597 .......... Drought, heat ...................................... 2 ..........ID ................................. Camas, Power ................................ 1–01–2001 ...... 6–18–2002 ...... 12–18–2001 .... 8–19–2002 ...... S1597 .......... Drought, heat ...................................... 2 6 ME ............................... Androscoggin, Cumberland, Kennebec, Lincoln, Oxford, Penobscot, Piscataquis, Sagadahoc, 

Somerset, Waldo, Washington, York.

6–01–2001 ...... 9–10–2001 ...... 12–20–2001 .... 8–20–2002 ...... S1598 .......... Armyworm infestation ......................... 12 4 

NH ................................ ........................................................ 6–01–2001 ...... 9–10–2001 ...... 12–20–2001 .... 8–20–2002 ...... S1598 .......... Armyworm infestation ......................... .......... 4 PA ................................ Erie ................................................ 7–04–2001 ...... 7–03–2002 ...... 1–03–2002 ...... 9–03–2002 ...... S1599 .......... Storms with high winds, excessive 

hail.

1 2 

NY ................................ ........................................................ 7–04–2001 ...... 7–03–2002 ...... 1–03–2002 ...... 9–03–2002 ...... S1599 .......... Storms with high winds, excessive 

hail.

.......... 1 

OH ................................ ........................................................ 7–04–2001 ...... 7–03–2002 ...... 1–03–2002 ...... 9–03–2002 ...... S1599 .......... Storms with high winds, excessive 

hail.

.......... 1 

NM ............................... Chaves, Eddy, Otero ...................... 1–01–2001 ...... 7–09–2002 ...... 1–08–2002 ...... 9–09–2002 ...... S1600 .......... Drought ................................................ 3 5 TX ................................ ........................................................ 1–01–2001 ...... 7–09–2002 ...... 1–08–2002 ...... 9–09–2002 ...... S1600 .......... Drought ................................................ .......... 5 AR ................................ Ashley, Chicot, Columbia, Desha, 

Drew, Lafayette.

8–31–2001 ...... 9–07–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1601 .......... Excessive rain ..................................... 6 10 

LA ................................ ........................................................ 8–31–2001 ...... 9–07–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1601 .......... Excessive rain ..................................... .......... 8 MS ............................... ........................................................ 8–31–2001 ...... 9–07–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1601 .......... Excessive rain ..................................... .......... 4 TN ................................ Cocke ............................................. 6–26–2001 ...... 6–26–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1602 .......... Hail, wind, flash flooding ................... 1 4 TN ................................ Rutherford ...................................... 4–01–2001 ...... 7–09–2002 ...... 1–08–2002 ...... 9–09–2002 ...... S1602 .......... Drought, insect infestation ................. 1 5 TN ................................ Morgan, Scott ................................ 3–15–2001 ...... 6–15–2001 ...... 1–08–2002 ...... 6–17–2002 ...... S1602 .......... Drought, excessive heat ...................... 2 ..........TN ................................ ........................................................ 3–15–2001 ...... 6–15–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1602 .......... Drought, excessive heat ...................... .......... 3 KY ................................ ........................................................ 3–15–2001 ...... 6–15–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1602 .......... Drought, excessive heat ...................... .......... 1 NC ................................ ........................................................ 6–26–2001 ...... 6–26–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1602 .......... Hail, wind, flash flooding ................... .......... 2 MN ............................... Cass, Crow Wing ........................... 11–15–2000 .... 6–28–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1603 .......... Heavier than normal precip, followed 

by severe cold.

2 8 

NE ................................ Buffalo, Butler, Cass, Dundy, 

Nance, Platte, Polk, Saunders, Seward, Sherman.

5–01–2001 ...... 7–09–2002 ...... 1–08–2002 ...... 9–09–2002 ...... S1604 .......... Drought, severe heat ........................... 10 26

CO ................................ ........................................................ 5–01–2001 ...... 7–09–2002 ...... 1–08–2002 ...... 9–09–2002 ...... S1604 .......... Drought, severe heat ........................... .......... 1 IA ................................. ........................................................ 5–01–2001 ...... 7–09–2002 ...... 1–08–2002 ...... 9–09–2002 ...... S1604 .......... Drought, severe heat ........................... .......... 2 
346 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

KS ................................ ........................................................ 5–01–2001 ...... 7–09–2002 ...... 1–08–2002 ...... 9–09–2002 ...... S1604 .......... Drought, severe heat ........................... .......... 2 NY ................................ Broome, Columbia, Dutchess, 

Greene, Jefferson, Lewis, Livingston, Onondaga, Sullivan, Ulster, Wyoming.

4–01–2001 ...... 7–09–2002 ...... 1–08–2002 ...... 9–09–2002 ...... S1605 .......... Columbia: Drought; Dutchess: Hail, 

High Winds; Greene: Drought∂ 

Hail, High Winds, Rain; Jefferson: Drought; Lewis: Flash Flooding, Excessive rain & Drought; Livingston: Drought; Onondaga: Hail; Sullivan: Army Cut Worms; Ulster: Hail High Winds; Wyoming: Drought.

11 22 

CT ................................ ........................................................ 7–01–2001 ...... 7–01–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1605 .......... Hail, hign winds .................................. .......... 2 MA ............................... ........................................................ 4–01–2001 ...... 7–09–2002 ...... 1–08–2002 ...... 9–09–2002 ...... S1605 .......... Hail, high winds: 07/01/01; Drought: 

04/01/01—continuing.

.......... 1 

PA ................................ ........................................................ 4–01–2001 ...... 7–09–2002 ...... 1–08–2002 ...... 9–09–2002 ...... S1605 .......... Drought: 04/01/01–05/31/01; Armyworm infestation: 07/01/01—continuing. .......... 3 NV ................................ Washoe .......................................... 5–01–2001 ...... 9–30–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1606 .......... Drought, extreme fires ........................ 1 6 CA ................................ ........................................................ 5–01–2001 ...... 9–30–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1606 .......... Drought, extreme fires ........................ .......... 5 OR ................................ ........................................................ 5–01–2001 ...... 9–30–2001 ...... 1–08–2002 ...... 9–09–2002 ...... S1606 .......... Drought, extreme fires ........................ .......... 2 NY ................................ Allegany, Cattaraugus, Chautauqua, Clinton, Essex, Niagara, Orleans, Putnam, Schuyler, 

Seneca, Wayne, Westchester.

4–01–2001 ...... 7–22–2002 ...... 1–22–2002 ...... 9–23–2002 ...... S1607 .......... Drought, army cut worms, hail ........... 12 13 

NY ................................ Dutchess, Erie, Genesee, Ulster .... 4–01–2001 ...... 7–22–2002 ...... 1–22–2002 ...... 9–23–2002 ...... S1607 .......... Drought, army cut worms, hail ........... 4 ..........PA ................................ ........................................................ 5–01–2001 ...... 7–22–2002 ...... 1–22–2002 ...... 9–23–2002 ...... S1607 .......... Drought ................................................ .......... 2 VT ................................ ........................................................ 7–09–2001 ...... 7–22–2002 ...... 1–22–2002 ...... 9–23–2002 ...... S1607 .......... Drought, Army Cut worms, hail .......... .......... 3 IN ................................. Lagrange, Perry ............................. 6–15–2001 ...... 9–09–2001 ...... 2–07–2002 ...... 10–07–2002 .... S1608 .......... Drought ................................................ 2 5 IN ................................. Benton, Clay, Elkhart, St. Joseph .. 10–24–2001 .... 10–25–2001 .... 2–07–2002 ...... 10–07–2002 .... S1608 .......... Severe storms, high winds, tornadoes, 

hail, excessive rain.

4 16 

IL ................................. ........................................................ 10–24–2001 .... 10–25–2001 .... 2–07–2002 ...... 10–07–2002 .... S1608 .......... Severe storms, high winds, tornadoes, 

hail, excessive rain.

.......... 2 

KY ................................ ........................................................ 6–15–2001 ...... 9–09–2001 ...... 2–07–2002 ...... 10–07–2002 .... S1608 .......... Drought ................................................ .......... 3 MI ................................ ........................................................ 10–24–2001 .... 10–25–2001 .... 2–07–2002 ...... 10–07–2002 .... S1608 .......... Severe storms, high winds, tornadoes, 

hail, excessive rain.

.......... 3 
347 

OH ................................ Ashland, Ashtabula, Brown, Carroll, Columbiana, Cuyahoga, 

Fulton, Geauga, Hancock, Holmes, Knox, Lake, Lucas, Mahoning, Medina, Sandusky, Seneca, Stark, Tuscarawas, Wayne, Wood, Wyandot.

5–01–2002 ...... 8–07–2002 ...... 2–07–2002 ...... 10–07–2002 .... S1609 .......... Severe drought, high temperatures .... 22 26 

KY ................................ ........................................................ 5–01–2002 ...... 8–07–2002 ...... 2–07–2002 ...... 10–07–2002 .... S1609 .......... Severe drought, high temperatures .... .......... 2 MI ................................ ........................................................ 5–01–2002 ...... 8–07–2002 ...... 2–07–2002 ...... 10–07–2002 .... S1609 .......... Severe drought, high temperatures .... .......... 3 PA ................................ ........................................................ 5–01–2002 ...... 8–07–2002 ...... 2–07–2002 ...... 10–07–2002 .... S1609 .......... Severe drought, high temperatures .... .......... 5 WV ............................... ........................................................ 5–01–2002 ...... 8–07–2002 ...... 2–07–2002 ...... 10–07–2002 .... S1609 .......... Severe drought, high temperatures .... .......... 1 GA ................................ Banks, Butts, Candler, Clayton, 

Elbert, Emanuel, Fayette, Glascock, Henry, Jackson, Jefferson, Johnson, Laurens, Madison, Oglethorpe, Tattnall, Taylor, Washington, Wilkinson.

1–01–2001 ...... 8–07–2002 ...... 2–07–2002 ...... 10–07–2002 .... S1610 .......... Drought ................................................ 19 50 

SC ................................ ........................................................ 1–01–2001 ...... 8–07–2002 ...... 2–07–2002 ...... 10–07–2002 .... S1610 .......... Drought ................................................ .......... 3 KS ................................ Chautauqua, Elk, Montgomery, 

Sumner, Reno.

1–01–2001 ...... 8–19–2002 ...... 2–19–2002 ...... 10–21–2002 .... S1611 .......... Drought, excessive rains, flash flooding, tornadoes, hail, repeatedly excessive winds. 5 14 

OK ................................ ........................................................ 1–01–2001 ...... 8–19–2002 ...... 2–19–2002 ...... 10–21–2002 .... S1611 .......... Drought, excessive rains, flash flooding, tornadoes, hail, repeatedly excessive winds. .......... 5 ND ................................ Barnes, Benson, Bottineau, Bowman, Burke, Cass, Cavalier, Divide, Eddy, Emmons, Foster, 

Grand Forks, Kidder, Logan, Mountrail, Nelson, Pembina, Pierce, Ramsey, Ransom, Renville, Richland, Rolette, Sargent, Slope, Stutsman, Towner, Traill, Walsh, Ward, Wells, Williams.

3–01–2001 ...... 8–21–2002 ...... 2–21–2002 ...... 10–21–2002 .... S1612 .......... Flooding, ground saturation, subsidence, storms, wind tornadoes, 

drought, high humidity, severe temperatures during the growing season.

32 18 

MN ............................... ........................................................ 3–01–2001 ...... 8–21–2002 ...... 2–21–2002 ...... 10–21–2002 .... S1612 .......... Flooding, ground saturation, subsidence, storms, wind tornadoes, 

drought, high humidity, severe temperatures during the growing season.

.......... 7 
348 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

MT ................................ ........................................................ 3–01–2001 ...... 8–21–2002 ...... 2–21–2002 ...... 10–21–2002 .... S1612 .......... Flooding, ground saturation, subsidence, storms, wind tornadoes, 

drought, high humidity, severe temperatures during the growing season.

.......... 4 

SD ................................ ........................................................ 3–01–2001 ...... 8–21–2002 ...... 2–21–2002 ...... 10–21–2002 .... S1612 .......... Flooding, ground saturation, subsidence, storms, wind tornadoes, 

drought, high humidity, severe temperatures during the growing season.

.......... 6 

ID ................................. Butte, Custer, Lemhi ..................... 1–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1613 .......... Drought, heat, low snow pack conditions. 3 5 MT ................................ ........................................................ 1–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1613 .......... Drought, heat, low snow pack conditions. .......... 2 CA ................................ Tehama .......................................... 4–08–2001 ...... 4–08–2001 ...... 3–01–2002 ...... 11–01–2002 .... S1614 .......... Freezing temperatures ......................... 1 3 NY ................................ Chemung, Tioga ............................ 4–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1615 .......... Drought ................................................ 2 4 PA ................................ ........................................................ 4–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1615 .......... Drought ................................................ .......... 3 NY ................................ Seneca ........................................... 10–21–2001 .... 10–21–2001 .... 3–01–2002 ...... 11–01–2002 .... S1615 .......... Hail, high winds .................................. 1 6 SC ................................ Entire State ................................... 4–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1616 .......... Drought ................................................ 46 ..........GA ................................ ........................................................ 4–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1616 .......... Drought ................................................ .......... 13 NC ................................ ........................................................ 4–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1616 .......... Drought ................................................ .......... 16 TN ................................ Claiborne, Union ............................ 7–01–2001 ...... 9–30–2001 ...... 3–01–2002 ...... 11–01–2002 .... S1617 .......... Excessive rain ..................................... 2 5 KY ................................ ........................................................ 7–01–2001 ...... 9–30–2001 ...... 3–01–2002 ...... 11–01–2002 .... S1617 .......... Excessive rain ..................................... .......... 2 TN ................................ Hamblen ........................................ 8–05–2001 ...... 8–05–2001 ...... 3–01–2002 ...... 11–01–2002 .... S1617 .......... Flooding ............................................... 1 5 TN ................................ Jefferson ........................................ 4–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1617 .......... Drought ................................................ 1 5 VA ................................ Goochland ...................................... 10–01–2000 .... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1618 .......... Drought, excessive heat ...................... 1 7 WY ............................... Albany ............................................ 1–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1619 .......... Drought, late frosts, untime rain, hail 1 2 CO ................................ ........................................................ 1–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1619 .......... Drought, late frosts, untime rain, hail .......... 2 VT ................................ Addison, Bennington, Caledonia, 

Chittenden, Orange, Orleans, Rutland, Washington.

4–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1620 .......... Drought ................................................ 8 6 

MA ............................... ........................................................ 4–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1620 .......... Drought ................................................ .......... 2 NH ................................ ........................................................ 4–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1620 .......... Drought ................................................ .......... 1 NY ................................ ........................................................ 4–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1620 .......... Drought ................................................ .......... 4 
349 

WA ............................... Yakima ........................................... 1–01–2001 ...... 9–01–2002 ...... 3–01–2002 ...... 11–01–2002 .... S1621 .......... Drought ................................................ 1 3 ME ............................... Androscoggin, Aroostook, Cumberland, Hancock, Kennebec, 

Knox, Lincoln, Oxford, Penobscot, Piscataquis, Sagadahoc, Somerset, Waldo, Washington, York.

6–01–2002 ...... 9–11–2002 ...... 3–11–2002 ...... 11–11–2002 .... S1622 .......... Drought ................................................ 15 1 

NH ................................ ........................................................ 6–01–2002 ...... 9–11–2002 ...... 3–11–2002 ...... 11–11–2002 .... S1622 .......... Drought ................................................ .......... 4 MA ............................... Franklin, Hampden, Hampshire, 

Worcester.

5–01–2000 ...... 9–22–2002 ...... 3–22–2002 ...... 11–22–2002 .... S1623 .......... Excessive rainfall, limited sunshine, 

below-average temperatures.

4 3 

CT ................................ ........................................................ 5–01–2000 ...... 9–22–2002 ...... 3–22–2002 ...... 11–22–2002 .... S1623 .......... Excessive rainfall, limited sunshine, 

below-average temperatures.

.......... 4 

NH ................................ ........................................................ 5–01–2000 ...... 9–22–2002 ...... 3–22–2002 ...... 11–22–2002 .... S1623 .......... Excessive rainfall, limited sunshine, 

below-average temperatures.

.......... 2 

RI ................................. ........................................................ 5–01–2000 ...... 9–22–2002 ...... 3–22–2002 ...... 11–22–2002 .... S1623 .......... Excessive rainfall, limited sunshine, 

below-average temperatures.

.......... 1 

VT ................................ ........................................................ 5–01–2000 ...... 9–22–2002 ...... 3–22–2002 ...... 11–22–2002 .... S1623 .......... Excessive rainfall, limited sunshine, 

below-average temperatures.

.......... 2 

MT ................................ Entire State ................................... 1–01–2002 ...... 9–27–2002 ...... 3–27–2002 ...... 11–27–2002 .... S1624 .......... Drought ................................................ 56 ..........ID ................................. ........................................................ 1–01–2002 ...... 9–27–2002 ...... 3–27–2002 ...... 11–27–2002 .... S1624 .......... Drought ................................................ .......... 8 ND ................................ ........................................................ 1–01–2002 ...... 9–27–2002 ...... 3–27–2002 ...... 11–27–2002 .... S1624 .......... Drought ................................................ .......... 6 SD ................................ ........................................................ 1–01–2002 ...... 9–27–2002 ...... 3–27–2002 ...... 11–27–2002 .... S1624 .......... Drought ................................................ .......... 2 WY ............................... ........................................................ 1–01–2002 ...... 9–27–2002 ...... 3–27–2002 ...... 11–27–2002 .... S1624 .......... Drought ................................................ .......... 6 KS ................................ Cowley ............................................ 6–01–2001 ...... 10–04–2002 .... 4–04–2002 ...... 6–25–2002 ...... S1625 .......... Drought, excessive rains, flash flooding, tornadoes, hail, repeatedly excessive winds. 1 ..........KS ................................ Edwards, Ford ................................ 6–01–2001 ...... 10–04–2002 .... 4–04–2002 ...... 12–04–2002 .... S1625 .......... Drought, excessive rains, flash flooding, tornadoes, hail, repeatedly excessive winds. 2 4 VA ................................ Prince Edward ............................... 8–01–2001 ...... 12–10–2001 .... 4–04–2002 ...... 12–04–2002 .... S1626 .......... Drought ................................................ 1 7 MA ............................... Barnstable, Bristol, Plymouth ....... 3–01–2001 ...... 10–04–2002 .... 4–04–2002 ...... 12–04–2002 .... S1627 .......... Erratic weather pattern: Record high 

temp. early spring-low rain; high temp.—June w/above ave. rain; Below normal temp.—Jul, Aug. w/ normal rain; Normal temp.—Sep. w/below norm. rain.

3 4 
350 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

RI ................................. ........................................................ 3–01–2001 ...... 10–04–2002 .... 4–04–2002 ...... 12–04–2002 .... S1627 .......... Erratic weather pattern: Record high 

temp. early spring-low rain; high temp.—June w/above ave. rain; Below normal temp.-Jul, Aug. w/ normal rain; Normal temp.—Sep. w/below norm. rain.

.......... 3 

GA ................................ Dooly .............................................. 1–01–2001 ...... 10–05–2002 .... 4–05–2002 ...... 12–05–2002 .... S1628 .......... Drought ................................................ 1 5 SD ................................ Haakon, Meade, Pennington .......... 6–01–2001 ...... 10–05–2002 .... 4–05–2002 ...... 12–05–2002 .... S1629 .......... Drought, extreme heat ........................ 3 10 CA ................................ Calaveras ....................................... 8–19–2001 ...... 9–05–2001 ...... 4–05–2002 ...... 12–05–2002 .... S1630 .......... High winds, drought, two separate 

fires.

1 5 

ID ................................. Cassia ............................................ 10–01–2001 .... 12–31–2001 .... 4–19–2002 ...... 6–25–2002 ...... S1631 .......... Drought ................................................ 1 ..........ID ................................. ........................................................ 10–01–2001 .... 12–31–2001 .... 4–19–2002 ...... 12–19–2002 .... S1631 .......... Drought ................................................ .......... 3 MS ............................... Bolivar, Calhoun, Carroll, Chickasaw, Hinds, Holmes, Itawamba, 

Jefferson Davis, Lee, Leflore, Marshall, Monroe, Noxubee, Panola, Pontotoc, Sunflower, Tallahatchie, Union, Washington.

8–15–2001 ...... 9–30–2001 ...... 4–19–2002 ...... 12–19–2002 .... S1632 .......... Excessive moisture, high humidity ..... 19 31 

MS ............................... Claiborne, Warren .......................... 8–15–2001 ...... 9–30–2001 ...... 4–19–2002 ...... 7–02–2002 ...... S1632 .......... Excessive moisture, high humidity ..... 2 ..........AL ................................ ........................................................ 8–15–2001 ...... 9–30–2001 ...... 4–19–2002 ...... 12–19–2002 .... S1632 .......... Excessive moisture, high humidity ..... .......... 5 AR ................................ ........................................................ 8–15–2001 ...... 9–30–2001 ...... 4–19–2002 ...... 12–19–2002 .... S1632 .......... Excessive moisture, high humidity ..... .......... 2 TN ................................ ........................................................ 8–15–2001 ...... 9–30–2001 ...... 4–19–2002 ...... 12–19–2002 .... S1632 .......... Excessive moisture, high humidity ..... .......... 2 IA ................................. Lucas ............................................. 10–22–2001 .... 11–01–2001 .... 4–23–2002 ...... 12–23–2002 .... S1633 .......... High winds, heavy rains, flooding ...... 1 7 IA ................................. Guthrie ........................................... 6–01–2001 ...... 10–23–2002 .... 4–23–2002 ...... 12–23–2002 .... S1634 .......... Drought ................................................ 1 6 CO ................................ Kit Carson, Phillips ....................... 9–01–2000 ...... 11–02–2002 .... 5–02–2002 ...... 1–02–2003 ...... S1635 .......... Drought ................................................ 2 5 KS ................................ ........................................................ 9–01–2000 ...... 11–02–2002 .... 5–02–2002 ...... 1–02–2003 ...... S1635 .......... Drought ................................................ .......... 1 NE ................................ ........................................................ 9–01–2000 ...... 11–02–2002 .... 5–02–2002 ...... 1–02–2003 ...... S1635 .......... Drought ................................................ .......... 2 TX ................................ Schleicher, Sutton, Zavala ............ 1–01–2001 ...... 11–02–2002 .... 5–02–2002 ...... 1–02–2003 ...... S1636 .......... Drought, excessive heat ...................... 3 5 TX ................................ ........................................................ 1–01–2001 ...... 11–02–2002 .... 5–02–2002 ...... 1–02–2003 ...... S1636 .......... Excessive heat ..................................... .......... 6 TX ................................ Garza, Lubbock, Menard, Nolan, 

Terry.

1–01–2001 ...... 11–02–2002 .... 5–02–2002 ...... 1–02–2003 ...... S1637 .......... Drought ................................................ 5 9 

TX ................................ Brooks, Callahan, Eastland, Jim 

Wells, Presidio, Stephens, Webb.

1–01–2001 ...... 11–02–2002 .... 5–02–2002 ...... 1–02–2003 ...... S1638 .......... Drought, high winds, high temperatures. 7 20 
351 

TX ................................ Loving, Pecos, Reeves ................... 1–01–2001 ...... 11–02–2002 .... 5–02–2002 ...... 1–02–2003 ...... S1639 .......... Drought, high winds ........................... 3 8 NM ............................... ........................................................ 1–01–2001 ...... 11–02–2002 .... 5–02–2002 ...... 1–02–2003 ...... S1639 .......... Drought, high winds ........................... .......... 2 ID ................................. Elmore ............................................ 10–01–2000 .... 11–10–2002 .... 5–10–2002 ...... 1–10–2003 ...... S1640 .......... Drought, insect losses (Mormon Crickets). 1 8 ID ................................. Twin Falls ...................................... 11–01–2000 .... 9–30–2001 ...... 5–10–2002 ...... 1–10–2003 ...... S1640 .......... Drought, excessive heat ...................... 1 2 NV ................................ ........................................................ 11–01–2000 .... 9–30–2001 ...... 5–10–2002 ...... 1–10–2003 ...... S1640 .......... Drought, excessive heat ...................... .......... 1 AZ ................................ All counties, except Yuma ............. 1–01–2001 ...... 11–17–2002 .... 5–17–2002 ...... 1–17–2003 ...... S1641 .......... Drought ................................................ 14 1 CA ................................ ........................................................ 1–01–2001 ...... 11–17–2002 .... 5–17–2002 ...... 1–17–2003 ...... S1641 .......... Drought ................................................ .......... 3 NV ................................ ........................................................ 1–01–2001 ...... 11–17–2002 .... 5–17–2002 ...... 1–17–2003 ...... S1641 .......... Drought ................................................ .......... 2 NM ............................... ........................................................ 1–01–2001 ...... 11–17–2002 .... 5–17–2002 ...... 1–17–2003 ...... S1641 .......... Drought ................................................ .......... 5 TX ................................ Comanche ...................................... 5–01–2001 ...... 11–24–2002 .... 5–24–2002 ...... 1–24–2003 ...... S1642 .......... Drought, heat, insects ........................ 1 5 CO ................................ Adams, Alamosa, Archuleta, Baca, 

Bent, Boulder, Chaffee, Conejos, Costilla, Crowley, Custer, Dolores, Douglas, Eagle, El Paso, Elbert, Fremont, Garfield, Grand, Hinsdale, Huerfano, Jackson, Jefferson, Kiowa, La Plata, Lake, Larimer, Las Animas, Logan, Mesa, Mineral, Montezuma, Morgan, Otero, Pitkin, Prowers, Pueblo, Rio Grande, Routt, Saguache, San Miguel, Sedgwick, Summit, Washington.

5–15–2001 ...... 11–30–2002 .... 5–30–2002 ...... 1–30–2003 ...... S1643 .......... Drought ................................................ 44 16 

KS ................................ ........................................................ 5–15–2001 ...... 11–30–2002 .... 5–30–2002 ...... 1–30–2003 ...... S1643 .......... Drought ................................................ .......... 4 NE ................................ ........................................................ 5–15–2001 ...... 11–30–2002 .... 5–30–2002 ...... 1–30–2003 ...... S1643 .......... Drought ................................................ .......... 5 NM ............................... ........................................................ 5–15–2001 ...... 11–30–2002 .... 5–30–2002 ...... 1–30–2003 ...... S1643 .......... Drought ................................................ .......... 4 OK ................................ ........................................................ 5–15–2001 ...... 11–30–2002 .... 5–30–2002 ...... 1–30–2003 ...... S1643 .......... Drought ................................................ .......... 1 NE ................................ Banner, Chase, Cheyenne, Custer, 

Dawson, Deuel, Dundy, Frontier, Hayes, Hitchcock, Keith, Kimball, Perkins, Red Willow, Scotts Bluff, Sioux.

10–01–2001 .... 11–30–2002 .... 5–30–2002 ...... 1–30–2003 ...... S1644 .......... Drought, unseasonably cold spring 

temperatures, high winds, frost.

16 17 

CO ................................ ........................................................ 10–01–2001 .... 11–30–2002 .... 5–30–2002 ...... 1–30–2003 ...... S1644 .......... Drought, unseasonably cold spring 

temperatures, high winds, frost.

.......... 5 

KS ................................ ........................................................ 10–01–2001 .... 11–30–2002 .... 5–30–2002 ...... 1–30–2003 ...... S1644 .......... Drought, unseasonably cold spring 

temperatures, high winds, frost.

.......... 3 

SD ................................ ........................................................ 10–01–2001 .... 11–30–2002 .... 5–30–2002 ...... 1–30–2003 ...... S1644 .......... Drought, unseasonably cold spring 

temperatures, high winds, frost.

.......... 1 
352 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

WY ............................... ........................................................ 10–01–2001 .... 11–30–2002 .... 5–30–2002 ...... 1–30–2003 ...... S1644 .......... Drought, unseasonably cold spring 

temperatures, high winds, frost.

.......... 3 

WY ............................... Albany, Big Horn, Campbell, Carbon, Crook, Fremont, Hot 

Springs, Johnson, Laramie, Natrona, Park, Sheridan, Washakie.

1–01–2002 ...... 12–01–2002 .... 5–31–2002 ...... 1–31–2003 ...... S1645 .......... Drought ................................................ 13 7 

CO ................................ ........................................................ 1–01–2002 ...... 12–01–2002 .... 5–31–2002 ...... 1–31–2003 ...... S1645 .......... Drought ................................................ .......... 5 MT ................................ ........................................................ 1–01–2002 ...... 12–01–2002 .... 5–31–2002 ...... 1–31–2003 ...... S1645 .......... Drought ................................................ .......... 6 NE ................................ ........................................................ 1–01–2002 ...... 12–01–2002 .... 5–31–2002 ...... 1–31–2003 ...... S1645 .......... Drought ................................................ .......... 2 SD ................................ ........................................................ 1–01–2002 ...... 12–01–2002 .... 5–31–2002 ...... 1–31–2003 ...... S1645 .......... Drought ................................................ .......... 2 TX ................................ Haskell ........................................... 1–01–2002 ...... 12–04–2002 .... 6–04–2002 ...... 2–04–2003 ...... S1646 .......... Drought, high winds, excessive heat 

(temperatures).

1 7 

GA ................................ Evans, Montgomery, Tattnall, 

Toombs.

2–28–2002 ...... 2–28–2002 ...... 6–17–2002 ...... 2–18–2003 ...... S1647 .......... Freezing weather ................................. 4 11 

NM ............................... Bernalillo, Catron, Cibola, Colfax, 

Curry, De Baca, Dona Ana, Grant, Guadalupe, Harding, Hidalgo, Lea, Lincoln, Luna, McKinley, Mora, Quay, Rio Arriba, Roosevelt, San Juan, San Miguel, Sandoval, Santa Fe, Sierra, Socorro, Taos, Torrance, Union, Valencia.

1–01–2002 ...... 12–18–2002 .... 6–17–2002 ...... 2–18–2003 ...... S1648 .......... Drought ................................................ 29 4 

WY ............................... Campbell ....................................... 1–01–2001 ...... 12–18–2002 .... 6–17–2002 ...... 2–18–2003 ...... S1649 .......... Drought ................................................ 1 5 MT ................................ ........................................................ 1–01–2001 ...... 12–18–2002 .... 6–17–2002 ...... 2–18–2003 ...... S1649 .......... Drought ................................................ .......... 1 NE ................................ Arthur, Box Butte, Franklin, Garden, Harlan, Kearney, Lincoln, 

Logan, McPherson, Morrill.

10–01–2001 .... 12–20–2003 .... 6–20–2002 ...... 2–20–2003 ...... S1650 .......... Drought, unseasonably cold spring 

temperatures, high winds, frost.

10 22 

KS ................................ ........................................................ 10–01–2001 .... 12–20–2003 .... 6–20–2002 ...... 2–20–2003 ...... S1650 .......... Drought, unseasonably cold spring 

temperatures, high winds, frost.

.......... 3 

UT ................................ Entire State ................................... 1–01–2002 ...... 1–02–2003 ...... 7–01–2002 ...... 3–03–2003 ...... S1651 .......... Drought, Mormon crickets, grasshoppers, frost, hail, high winds. 29 ..........
353 

AZ ................................ ........................................................ 1–01–2002 ...... 1–02–2003 ...... 7–01–2002 ...... 3–03–2003 ...... S1651 .......... Drought, Mormon crickets, grasshoppers, frost, hail, high winds. .......... 4 CO ................................ ........................................................ 1–01–2002 ...... 1–02–2003 ...... 7–01–2002 ...... 3–03–2003 ...... S1651 .......... Drought, Mormon crickets, grasshoppers, frost, hail, high winds. .......... 8 ID ................................. ........................................................ 1–01–2002 ...... 1–02–2003 ...... 7–01–2002 ...... 3–03–2003 ...... S1651 .......... Drought, Mormon crickets, grasshoppers, frost, hail, high winds. .......... 4 NM ............................... ........................................................ 1–01–2002 ...... 1–02–2003 ...... 7–01–2002 ...... 3–03–2003 ...... S1651 .......... Drought, Mormon crickets, grasshoppers, frost, hail, high winds. .......... 1 NV ................................ ........................................................ 1–01–2002 ...... 1–02–2003 ...... 7–01–2002 ...... 3–03–2003 ...... S1651 .......... Drought, Mormon crickets, grasshoppers, frost, hail, high winds. .......... 3 WY ............................... ........................................................ 1–01–2002 ...... 1–02–2003 ...... 7–01–2002 ...... 3–03–2003 ...... S1651 .......... Drought, Mormon crickets, grasshoppers, frost, hail, high winds. .......... 3 AZ ................................ Tohono O’Odham Nation (located 

in 3 southern AZ counties).

1–01–2001 ...... 1–12–2003 ...... 7–12–2002 ...... 3–12–2003 ...... S1652 .......... Drought ................................................ 3 ..........

VA ................................ Brunswick, Buckingham, Cumberland, Fluvanna, Louisa. 4–15–2001 ...... 1–13–2003 ...... 7–12–2002 ...... 3–12–2003 ...... S1653 .......... Drought ................................................ 5 15 NC ................................ ........................................................ 4–15–2001 ...... 1–13–2003 ...... 7–12–2002 ...... 3–12–2003 ...... S1653 .......... Drought ................................................ .......... 2 CA ................................ San Diego ...................................... 1–30–2002 ...... 3–04–2002 ...... 7–12–2002 ...... 3–12–2003 ...... S1654 .......... Fire, wind, drought, freezing conditions. 1 3 TX ................................ Willacy ........................................... 1–01–2002 ...... 1–12–2003 ...... 7–12–2002 ...... 3–12–2003 ...... S1655 .......... Drought, high winds, heat .................. 1 3 MI ................................ Allegan, Antrim, Benzie, Berrien, 

Cass, Genesee, Grand Traverse, Ingham, Ionia, Jackson, Kalamazoo, Kent, Lapeer, Leelanau, Livingston, Macomb, Manistee, Mason, Muskegon, Newaygo, Oakland, Oceana, Ottawa, St. Clair, Shiawassee, Van Buren.

4–21–2002 ...... 5–31–2002 ...... 7–15–2002 ...... 3–17–2003 ...... S1656 .......... (1) Frost, freezing temperatures, wind 

(2) Cold temperatures, hail, wet 

weather.

(3) Frost, freezing temperatures .........

26 24 

IN ................................. ........................................................ 4–21–2002 ...... 5–31–2002 ...... 7–15–2002 ...... 3–17–2003 ...... S1656 .......... (1) Frost, freezing temperatures, wind 

(2) Cold temperatures, hail, wet 

weather.

(3) Frost, freezing temperatures .........

.......... 3 

CA ................................ Glenn ............................................. 3–08–2002 ...... 3–24–2002 ...... 7–01–2002 ...... 3–03–2003 ...... S1657 .......... Freeze followed by hail ....................... 1 5 AZ ................................ Navajo Nation (located in several 

NE AZ, NW NM, and SE UT counties.

1–01–2002 ...... 1–02–2003 ...... 7–02–2002 ...... 3–03–2003 ...... S1658 .......... Drought ................................................ 3 ..........

NM ............................... Navajo Nation (located in several 

NE AZ, NW NM, and SE UT counties.

1–01–2002 ...... 1–02–2003 ...... 7–02–2002 ...... 3–03–2003 ...... S1658 .......... Drought ................................................ 6 ..........
354 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

UT ................................ Navajo Nation (located in several 

NE AZ, NW NM, and SE UT counties.

1–01–2002 ...... 1–02–2003 ...... 7–02–2002 ...... 3–03–2003 ...... S1658 .......... Drought ................................................ 1 ..........

CA ................................ Colusa ............................................ 3–08–2002 ...... 3–08–2002 ...... 7–01–2002 ...... 3–03–2003 ...... S1659 .......... Freeze, frost ......................................... 1 5 NC ................................ Alleghany, Ashe, Avery, Mitchell, 

Watauga, Yancey.

5–19–2002 ...... 5–23–2002 ...... 7–23–2002 ...... 3–24–2003 ...... S1660 .......... Abnormally low temperatures; freezes 6 7 

TN ................................ ........................................................ 5–19–2002 ...... 5–23–2002 ...... 7–23–2002 ...... 3–24–2003 ...... S1660 .......... Abnormally low temperatures; freezes .......... 3 VA ................................ ........................................................ 5–19–2002 ...... 5–23–2002 ...... 7–23–2002 ...... 3–24–2003 ...... S1660 .......... Abnormally low temperatures; freezes .......... 1 NC ................................ Alamance, Alexander, Alleghany, 

Anson, Ashe, Burke, Cabarrus, Caldwell, Caswell, Catawba, Chatham, Cleveland, Cumberland, Davidson, Davie, Durham, Forsyth, Franklin, Gaston, Granville, Guilford, Halifax, Harnett, Hoke, Iredell, Johnston, Lee, Lincoln, McDowell, Mecklenburg, Montgomery, Moore, Nash, Northampton, Orange, Person, Randolph, Richmond, Robeson, Rockingham, Rowan, Rutherford, Scotland, Stanly, Stokes, Surry, Union, Vance, Wake, Warren, Wayne, Wilkes, Wilson, Yadkin.

1–01–2002 ...... 1–23–2003 ...... 7–23–2002 ...... 3–24–2003 ...... S1661 .......... Drought ................................................ 54 18 

SC ................................ ........................................................ 1–01–2002 ...... 1–23–2003 ...... 7–23–2002 ...... 3–24–2003 ...... S1661 .......... Drought ................................................ .......... 8 TN ................................ ........................................................ 1–01–2002 ...... 1–23–2003 ...... 7–23–2002 ...... 3–24–2003 ...... S1661 .......... Drought ................................................ .......... 1 VA ................................ ........................................................ 1–01–2002 ...... 1–23–2003 ...... 7–23–2002 ...... 3–24–2003 ...... S1661 .......... Drought ................................................ .......... 11 GA ................................ Mitchell .......................................... 4–03–2002 ...... 4–03–2002 ...... 8–02–2002 ...... 4–02–2003 ...... S1662 .......... Hailstorm ............................................. 1 7 PA ................................ Erie ................................................ 5–20–2002 ...... 5–22–2002 ...... 8–07–2002 ...... 4–07–2003 ...... S1663 .......... Severe frost, freezing conditions ........ 1 2 NY ................................ ........................................................ 5–20–2002 ...... 5–22–2002 ...... 8–07–2002 ...... 4–07–2003 ...... S1663 .......... Severe frost, freezing conditions ........ .......... 1 OH ................................ ........................................................ 5–20–2002 ...... 5–22–2002 ...... 8–07–2002 ...... 4–07–2003 ...... S1663 .......... Severe frost, freezing conditions ........ .......... 1 
355 

MN ............................... Beltrami, Kittson, Koochiching, 

Lake of the Woods, Mahnomen, Marshall, Norman, Pennington, Polk, Red Lake, Roseau.

6–28–2002 ...... 2–07–2003 ...... 8–07–2002 ...... 4–07–2003 ...... S1664 .......... Excessive rainfall, flash flooding, hail 13 11 

ND ................................ ........................................................ 6–28–2002 ...... 2–07–2003 ...... 8–07–2002 ...... 4–07–2003 ...... S1664 .......... Excessive rainfall, flash flooding, hail .......... 5 VA ................................ Bedford, Orange, Rockbridge ........ 1–01–2001 ...... 2–08–2003 ...... 8–08–2002 ...... 4–08–2003 ...... S1665 .......... Drought, excessive heat ...................... 3 20 SD ................................ Aurora, Brule, Buffalo, Butte, 

Campbell, Dewey, Edmunds, Faulk, Hand, Hughes, Hyde, Lyman, Pennington, Perkins, Potter, Stanley, Sully, Ziebach, Beadle. Bennett, Brown, Charles Mix, Davison, Day, Deuel, Fall River, Gregory, Hamlin, Hanson, Hutchinson, Jerauld, Jones, Marshall, Mellette, Shannon, Spink, Todd, Tripp, Yankton, Bon Homme, Clark, Corson, Douglas, Lake, McPherson, Miner, Sanborn, Walworth, Harding, Kingsbury, McCook, Meade.

7–01–2001 ...... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1666 .......... Extreme heat, wind, late frosts, 

drought, fire.

52 12 

MN ............................... ........................................................ 7–01–2001 ...... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1666 .......... Extreme heat, wind, late frosts, 

drought, fire.

.......... 3 

MT ................................ ........................................................ 7–01–2001 ...... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1666 .......... Extreme heat, wind, late frosts, 

drought, fire.

.......... 2 

NE ................................ ........................................................ 7–01–2001 ...... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1666 .......... Extreme heat, wind, late frosts, 

drought, fire.

.......... 8 

ND ................................ ........................................................ 7–01–2001 ...... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1666 .......... Extreme heat, wind, late frosts, 

drought, fire.

.......... 8 

WY ............................... ........................................................ 7–01–2001 ...... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1666 .......... Extreme heat, wind, late frosts, 

drought, fire.

.......... 3 
356 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

KS ................................ Barber, Cheyenne, Comanche, Decatur, Edwards, Ellsworth, 

Finney, Ford, Gove, Graham, Grant, Gray, Greeley, Hamilton, Hodgeman, Jewell, Kearny, Lane, Lincoln, Logan, Meade, Morton, Norton, Osborne, Pawnee, Phillips, Rawlins, Rooks, Russell, Scott, Seward, Sheridan, Sherman, Smith, Stanton, Stevens, Thomas, Trego, Wallace, Wichita.

1–01–2002 ...... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1667 .......... Drought, frost, excessive winds .......... 40 18 

NE ................................ ........................................................ 1–01–2002 ...... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1667 .......... Drought, frost, excessive winds .......... .......... 3 OK ................................ ........................................................ 1–01–2002 ...... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1667 .......... Drought, frost, excessive winds .......... .......... 5 NE ................................ Blaine, Buffalo, Cherry, Dawes, 

Furnas, Gosper, Grant, Hooker, Phelps, Sheridan, Thomas.

10–01–2001 .... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1668 .......... Unseasonably cold spring temperatures, drought, high winds, frost, 

extreme heat, hail, grasshopper infestation.

11 21 

KS ................................ ........................................................ 10–01–2001 .... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1668 .......... Unseasonably cold spring temperatures, drought, high winds, frost, 

extreme heat, hail, grasshopper infestation.

.......... 3 

SD ................................ ........................................................ 10–01–2001 .... 2–14–2003 ...... 8–14–2002 ...... 4–14–2003 ...... S1668 .......... Unseasonably cold spring temperatures, drought, high winds, frost, 

extreme heat, hail, grasshopper infestation.

.......... 5 

CA ................................ Riverside ........................................ 2–01–2002 ...... 2–28–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1669 .......... Freezing conditions, followed by Santa 

Ana winds.

1 4 

AZ ................................ La Paz ............................................ 2–01–2002 ...... 2–28–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1669 .......... Freezing conditions, followed by Santa 

Ana winds.

.......... 1 

CA ................................ Solano ............................................ 3–06–2002 ...... 3–10–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1670 .......... Hail, extreme freezing conditions ....... 1 6 
357 

CO ................................ Arapahoe, Cheyenne, Delta, Gunnison, Lincoln, Moffat, Montrose, 

Ouray, Park, Rio Blanco, Teller, Weld, Yuma.

5–15–2001 ...... 2–16–2003 ...... 8–16–2002 ...... 4–16–2003 ...... S1643, 

Amendment 1.

Drought ................................................ 13 ..........

KS ................................ Wallace .......................................... 5–15–2001 ...... 2–16–2003 ...... 8–16–2002 ...... 4–16–2003 ...... S1643, 

Amendment 1.

Drought ................................................ .......... 1 

NE ................................ Dundy ............................................. 5–15–2001 ...... 2–16–2003 ...... 8–16–2002 ...... 4–16–2003 ...... S1643, 

Amendment 1.

Drought ................................................ .......... 1 

NY ................................ Chautauqua, Columbia, Dutchess, 

Essex, Greene, Orange, Rensselaer, Saratoga, Schenectady, Schoharie, Steuben, Ulster, Wayne, Yates.

4–06–2002 ...... 5–27–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1671 .......... Various disasters for each county including: Excessive rain, freeze, 

frost, hail, high winds, snow, wet weather.

14 24 

CT ................................ Fairfield ......................................... 4–06–2002 ...... 5–27–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1671 .......... Excessive rain, freeze, frost, hail, 

high winds, snow, wet weather.

.......... 2 

MA ............................... Litchfield ........................................ 4–06–2002 ...... 5–27–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1671 .......... Excessive rain, freeze, frost, hail, 

high winds, snow, wet weather.

.......... 1 

PA ................................ Erie, Potter, Pike, Tioga, Warren ... 4–06–2002 ...... 5–27–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1671 .......... Excessive rain, freeze, frost, hail, 

high winds, snow, wet weather.

.......... 5 

VT ................................ Addison, Bennington, Chittenden .. 4–06–2002 ...... 5–27–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1671 .......... Excessive rain, freeze, frost, hail, 

high winds, snow, wet weather.

.......... 3 

TX ................................ Duval, Live Oak ............................. 12–01–2001 .... 2–16–2003 ...... 8–16–2002 ...... 4–16–2003 ...... S1672 .......... Drought, high winds ........................... 2 10 TX ................................ Jim Wells, Kleberg ......................... 12–11–2001 .... 2–16–2003 ...... 8–16–2002 ...... 4–16–2003 ...... S1673 .......... Drought, high winds, excessive heat 

(temperatures).

2 6 

VA ................................ Grayson, Smyth, Washington ......... 5–19–2002 ...... 5–23–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1674 .......... Freeze .................................................. 3 8 NC ................................ Alleghany, Ashe, Surry ................... 5–19–2002 ...... 5–23–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1674 .......... Freeze .................................................. .......... 3 TN ................................ Johnson, Sullivan ........................... 5–19–2002 ...... 5–23–2002 ...... 8–16–2002 ...... 4–16–2003 ...... S1674 .......... Freeze .................................................. .......... 2 TX ................................ Gillespie, Karnes ............................ 1–01–2002 ...... 2–21–2003 ...... 8–20–2002 ...... 4–21–2003 ...... S1675 .......... Drought ................................................ 2 13 IA ................................. Clayton, Clinton, Delaware, Jackson, Jones, Scott. 6–03–2002 ...... 6–07–2002 ...... 8–22–2002 ...... 4–22–2003 ...... S1676 .......... Severe storms, heavy rains, flooding, flash flooding. 6 8 IL ................................. ........................................................ 6–03–2002 ...... 6–07–2002 ...... 8–22–2002 ...... 4–22–2003 ...... S1676 .......... Severe storms, heavy rains, flooding, 

flash flooding.

.......... 4 

WI ................................ ........................................................ 6–03–2002 ...... 6–07–2002 ...... 8–22–2002 ...... 4–22–2003 ...... S1676 .......... Severe storms, heavy rains, flooding, 

flash flooding.

.......... 2 
358 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

ND ................................ Adams, Barnes, Benson, Billings, 

Bottineau, Bowman, Burke, Burleigh, Cass, Cavalier, Dickey, Divide, Dunn, Eddy, Emmons, Foster, Golden Valley, Grand Forks, Grant, Griggs, Hettinger, Kidder, La Moure, Logan, McHenry, McIntosh, McKenzie, McLean, Mercer, Morton, Nelson, Oliver, Pembina, Pierce, Ramsey, Ransom, Renville, Richland, Rolette, Sargent, Sheridan, Sioux, Slope, Stark, Steele, Stutsman, Towner, Traill, Walsh, Ward, Wells.

4–01–2002 ...... 2–22–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1677 .......... Drought, fire, insects, above and 

below normal temperatures, frost, severe storms, hail, flooding, wind, crop disease.

51 2 

MN ............................... ........................................................ 4–01–2002 ...... 2–22–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1677 .......... Drought, fire, insects, above and 

below normal temperatures, frost, severe storms, hail, flooding, wind, crop disease.

.......... 7 

MT ................................ ........................................................ 4–01–2002 ...... 2–22–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1677 .......... Drought, fire, insects, above and 

below normal temperatures, frost, severe storms, hail, flooding, wind, crop disease.

.......... 5 

SD ................................ ........................................................ 4–01–2002 ...... 2–22–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1677 .......... Drought, fire, insects, above and 

below normal temperatures, frost, severe storms, hail, flooding, wind, crop disease.

.......... 8 
359 

NE ................................ Adams, Antelope, Boone, Boyd, 

Brown, Burt, Butler, Cass, Cedar, Clay, Colfax, Cuming, Dakota, Dixon, Dodge, Douglas, Fillmore, Gage, Garfield, Greeley, Hall, Hamilton, Holt, Howard, Jefferson, Johnson, Keya Paha, Knox, Lancaster, Loup, Madison, Merrick, Nance, Nemaha, Nuckolls, Otoe, Pawnee, Pierce, Platte, Polk, Richardson, Rock, Saline, Sarpy, Saunders, Seward, Sherman, Stanton, Thayer, Thurston, Valley, Washington, Wayne, Webster, Wheeler, York.

10–01–2001 .... 2–22–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1678 .......... Unseasonably cold spring temperatures, high winds, frost, extreme 

heat, hail, grasshopper infestation, drought.

56 6 

IA ................................. ........................................................ 10–01–2001 .... 2–22–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1678 .......... Unseasonably cold spring temperatures, drought, high winds, frost, 

extreme heat, hail, grasshopper infestation.

.......... 6 

KS ................................ ........................................................ 10–01–2001 .... 2–22–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1678 .......... Unseasonably cold spring temperatures, drought, high winds, frost, 

extreme heat, hail, grasshopper infestation.

.......... 8 

MO ............................... ........................................................ 10–01–2001 .... 2–22–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1678 .......... Unseasonably cold spring temperatures, drought, high winds, frost, 

extreme heat, hail, grasshopper infestation.

.......... 2 

SD ................................ ........................................................ 10–01–2001 .... 2–22–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1678 .......... Unseasonably cold spring temperatures, drought, high winds, frost, 

extreme heat, hail, grasshopper infestation.

.......... 8 
360 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: SECRETARIAL—Continued 

[Fiscal Year 2002—Secretarial Designations for Production Losses] 

State Counties requested Beginning date of disaster Ending date of disaster Approved by sec- retary Termination date Designation number Description of disaster Primary Contig- uous 

OK ................................ Alfalfa, Beaver, Beckham, Blaine, 

Caddo, Canadian, Cimarron, Comanche, Cotton, Custer, Dewey, Ellis, Garfield, Grady, Grant, Greer, Harmon, Harper, Jackson, Jefferson, Kiowa, Kingfisher, Major, Roger Mills, Stephens, Texas, Tillman, Washita, Woods, Woodward.

8–01–2001 ...... 2–23–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1679 .......... Drought ................................................ 30 9 

KS ................................ ........................................................ 8–01–2001 ...... 2–23–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1679 .......... Drought ................................................ .......... 1 TX ................................ ........................................................ 8–01–2001 ...... 2–23–2003 ...... 8–22–2002 ...... 4–22–2003 ...... S1679 .......... Drought ................................................ .......... 13 KS ................................ Crawford, Ford, Jewell, Kiowa, 

Neosho, Pratt.

5–07–2002 ...... 5–26–2002 ...... 8–22–2002 ...... 4–22–2003 ...... S1680 .......... Severe storms including, hail, high 

winds, tornadoes, excessive rain, flash flooding, flooding, lightning.

6 22 

MO ............................... ........................................................ 5–07–2002 ...... 5–26–2002 ...... 8–22–2002 ...... 4–22–2003 ...... S1680 .......... Severe storms including, hail, high 

winds, tornadoes, excessive rain, flash flooding, flooding, lightning.

.......... 3 

NE ................................ ........................................................ 5–07–2002 ...... 5–26–2002 ...... 8–22–2002 ...... 4–22–2003 ...... S1680 .......... Severe storms including, hail, high 

winds, tornadoes, excessive rain, flash flooding, flooding, lightning.

.......... 2 

WY ............................... Lincoln, Uinta ................................ 1–01–2002 ...... 3–11–2003 ...... 9–11–2002 ...... 5–12–2003 ...... S1681 .......... Drought ................................................ 2 2 ID ................................. ........................................................ 1–01–2002 ...... 3–11–2003 ...... 9–11–2002 ...... 5–12–2003 ...... S1681 .......... Drought ................................................ .......... 2 MO ............................... Adair, Bollinger,Cape Girardeau, 

Charlton, Howard, Knox, Laclede, Lafayette, Lincoln, Macon, Madison, Moniteau, Scott, Wayne.

3–01–2002 ...... 3–20–2003 ...... 9–20–2002 ...... 5–20–2003 ...... S1682 .......... Hail, tornadoes, high winds, flooding, 

unseasonably cool temperatures.

14 41 

IL ................................. ........................................................ 3–01–2002 ...... 3–20–2003 ...... 9–20–2002 ...... 5–20–2003 ...... S1682 .......... Excessive rain, flooding ...................... .......... 3 OH ................................ Auglaize, Fairfield, Morgan, 

Muskingum, Perry, Portage, Ross, Summit, Wood.

3–01–2002 ...... 5–31–2002 ...... 9–20–2002 ...... 5–20–2003 ...... S1683 .......... Frost, freeze, hail, tornado .................. 9 35 

VA ................................ Carroll ............................................ 5–19–2002 ...... 5–23–2002 ...... 9–20–2002 ...... 5–20–2003 ...... S1684 .......... Freeze, frost conditions ....................... 1 6 NC ................................ ........................................................ 5–19–2002 ...... 5–23–2002 ...... 9–20–2002 ...... 5–20–2003 ...... S1684 .......... Freeze, frost conditions ....................... .......... 1 WA ............................... Chelan, Douglas, Okanogan .......... 4–23–2002 ...... 5–07–2002 ...... 9–20–2002 ...... 5–20–2003 ...... S1685 .......... Freezing temperatures ......................... 3 8 
361 

KS ................................ Clark, Clay, Geary, Mitchell, 

Pottawatomie, Riley, Rush, Saline.

1–01–2002 ...... 3–18–2003 ...... 9–18–2002 ...... 5–19–2003 ...... S1686 .......... Drought ................................................ 8 9 

OR ................................ Wasco ............................................ 9–01–2001 ...... 3–18–2003 ...... 9–18–2002 ...... 5–19–2003 ...... S1687 .......... Drought ................................................ 1 7 WA ............................... ........................................................ 9–01–2001 ...... 3–18–2003 ...... 9–18–2002 ...... 5–19–2003 ...... S1687 .......... Drought ................................................ 1 1 NY ................................ Albany, Clinton, Erie ...................... 4–15–2002 ...... 5–22–2002 ...... 9–18–2002 ...... 5–19–2003 ...... S1688 .......... Albany: Freeze, frost, excessive rain; 

Clinton: freeze; Erie: Freeze, frost.

3 9 

VT ................................ Albany, Clinton, Erie ...................... 4–15–2002 ...... 5–22–2002 ...... 9–18–2002 ...... 5–19–2003 ...... S1688 .......... Albany: Freeze, frost, excessive rain; 

Clinton: freeze; Erie: Freeze, frost.

3 2 

TN ................................ Carter, Johnson, Lauderdale, Morgan, Scott, Shelby. 4–01–2002 ...... 3–18–2003 ...... 9–18–2002 ...... 5–19–2003 ...... S1689 .......... Flooding, frost, freeze, cold wind, low temperatures, drought, high temperatures. 6 14 AR ................................ ........................................................ 4–01–2002 ...... 3–18–2003 ...... 9–18–2002 ...... 5–19–2003 ...... S1689 .......... Flooding, frost, freeze, cold wind, low 

temperatures, drought, high temperatures.

.......... 2 

KY ................................ ........................................................ 4–01–2002 ...... 3–18–2003 ...... 9–18–2002 ...... 5–19–2003 ...... S1689 .......... Flooding, frost, freeze, cold wind, low 

temperatures, drought, high temperatures.

.......... 2 

MS ............................... ........................................................ 4–01–2002 ...... 3–18–2003 ...... 9–18–2002 ...... 5–19–2003 ...... S1689 .......... Flooding, frost, freeze, cold wind, low 

temperatures, drought, high temperatures.

.......... 2 

TX ................................ Matagorda ..................................... 2–01–2002 ...... 6–20–2002 ...... 9–26–2002 ...... 5–26–2003 ...... S1690 .......... Drought ................................................ 1 4 TX ................................ Jim Hogg ........................................ 1–01–2002 ...... 3–26–2003 ...... 9–26–2002 ...... 5–26–2003 ...... S1691 .......... Drought, high temperatures, high 

winds.

1 5 

TX ................................ Edwards ......................................... 1–01–2002 ...... 3–26–2003 ...... 9–26–2002 ...... 5–26–2003 ...... S1692 .......... Drought, excessive temperatures ........ 1 7 

TOTAL ACTIVE ........................................................ .......................... .......................... .......................... .......................... ...................... .............................................................. 1363 1995 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

VT ........................................ Essex, Franklin, Grand Isle, Lamoille, 

Windham, Windsor.

4–01–2001 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1620, 

Amendment 1.

Drought ............................................ 6 6 
362 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

TN ........................................ Dyer ........................................................... 5–10–2002 .. 5–25–2002 .. 10–21–2002 6–23–2003 .. S1689, 

Amendment 1.

Flooding ........................................... 1 3 

MO ....................................... ................................................................... 5–10–2002 .. 5–25–2002 .. 10–21–2002 6–23–2003 .. S1689, 

Amendment 1.

.......................................................... .......... 1 

OH ....................................... ENTIRE STATE ............................................ 3–01–2002 .. 4–09–2003 .. 10–09–2002 6–09–2003 .. S1693 ........ Drought ............................................ 88 ..........IN ......................................... ................................................................... 3–01–2002 .. 4–09–2003 .. 10–09–2002 6–09–2003 .. S1693 ........ Drought ............................................ .......... 10 KY ........................................ ................................................................... 3–01–2002 .. 4–09–2003 .. 10–09–2002 6–09–2003 .. S1693 ........ Drought ............................................ .......... 9 MI ........................................ ................................................................... 3–01–2002 .. 4–09–2003 .. 10–09–2002 6–09–2003 .. S1693 ........ Drought ............................................ .......... 3 PA ........................................ ................................................................... 3–01–2002 .. 4–09–2003 .. 10–09–2002 6–09–2003 .. S1693 ........ Drought ............................................ .......... 5 WV ....................................... ................................................................... 3–01–2002 .. 4–09–2003 .. 10–09–2002 6–09–2003 .. S1693 ........ Drought ............................................ .......... 12 PA ........................................ Adams, Allegheny, Armstrong, Beaver, 

Bedford, Berks, Blair, Bradford, Bucks, Butler, Cambria, Cameron, Carbon, Centre, Chester, Clearfield, Clinton, Columbia, Cumberland, Dauphin, Elk, Forest, Franklin, Fulton, Huntingdon, Indiana, Juniata, Lackawanna, Lancaster, Lawrence, Lebanon, Lehigh, Luzerne, Lycoming, McKean, Mifflin, Monroe, Montgomery, Montour, Northampton, Northumberland, Perry, Pike, Potter, Schuylkill, Snyder, Somerset, Sullivan, Susquehanna, Union, Venango, Wayne, Wyoming, York.

1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1694 ........ Drought ............................................ 54 11 

DE ........................................ ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1694 ........ Drought ............................................ .......... 1 MD ....................................... ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1694 ........ Drought ............................................ .......... 8 NJ ........................................ ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1694 ........ Drought ............................................ .......... 5 NY ........................................ ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1694 ........ Drought ............................................ .......... 9 OH ....................................... ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1694 ........ Drought ............................................ .......... 2 WV ....................................... ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1694 ........ Drought ............................................ .......... 1 
363 

GA ........................................ Entire State except for Bibb, Camden, 

Crawford, Early, Evans, Glynn, Liberty, Long, McIntosh, Peach, Tattnall, Wayne counties.

1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1695 ........ Drought ............................................ 147 10 

AL ........................................ ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1695 ........ Drought ............................................ .......... 11 FL ........................................ ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1695 ........ Drought ............................................ .......... 9 NC ....................................... ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1695 ........ Drought ............................................ .......... 4 SC ........................................ ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1695 ........ Drought ............................................ .......... 10 TN ........................................ ................................................................... 1–01–2002 .. 4–11–2003 .. 10–11–2002 6–11–2003 .. S1695 ........ Drought ............................................ .......... 4 GA ........................................ Bibb, Crawford, Early, Peach .................... 1–01–2002 .. 4/31/03 ........ 10–21–2002 6–23–2003 .. S1695, 

Amendment 1.

Drought ............................................ 4 ..........

GA ........................................ Evans ........................................................ 1–01–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1695, 

Amendment 2.

Drought ............................................ 1 ..........

OR ....................................... Gilliam, Morrow ......................................... 9–01–2000 .. 4–16–2003 .. 10–16–2002 6–16–2003 .. S1696 ........ Drought ............................................ 2 2 WA ....................................... ................................................................... 9–01–2000 .. 4–16–2003 .. 10–16–2002 6–16–2003 .. S1696 ........ Drought ............................................ .......... 1 AR ........................................ Arkansas, Clay, Craighead, Crittenden, 

Cross, Greene, Independence, Jefferson, Lawrence, Lee, Mississippi, Monroe, Poinsett, Randolph, St. Francis, Sebastian, Woodruff.

3–18–2002 .. 4–16–2003 .. 10–16–2002 6–16–2003 .. S1697 ........ Excessive rain, flooding, hail .......... 17 18 

MO ....................................... ................................................................... 3–18–2002 .. 4–16–2003 .. 10–16–2002 6–16–2003 .. S1697 ........ Excessive rain, flooding, hail .......... .......... 4 MS ....................................... ................................................................... 3–18–2002 .. 4–16–2003 .. 10–16–2002 6–16–2003 .. S1697 ........ Excessive rain, flooding, hail .......... .......... 2 OK ........................................ ................................................................... 3–18–2002 .. 4–16–2003 .. 10–16–2002 6–16–2003 .. S1697 ........ Excessive rain, flooding, hail .......... .......... 2 TN ........................................ ................................................................... 3–18–2002 .. 4–16–2003 .. 10–16–2002 6–16–2003 .. S1697 ........ Excessive rain, flooding, hail .......... .......... 4 NJ ........................................ Atlantic, Bergen, Burlington, Camden, 

Cape May, Cumberland, Essex, Gloucester, Hunterdon, Mercer, Middlesex, Monmouth, Morris, Ocean, Passaic, Salem, Somerset, Sussex, Warren.

3–04–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1698 ........ Drought, excessive temperatures .... 19 2 

DE ........................................ ................................................................... 3–04–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1698 ........ Drought, excessive temperatures .... .......... 3 NY ........................................ ................................................................... 3–04–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1698 ........ Drought, excessive temperatures .... .......... 6 DE ........................................ Entire State ............................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1699 ........ Drought, high temperatures ............ 3 ..........NJ ........................................ ................................................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1699 ........ Drought, high temperatures ............ .......... 4 PA ........................................ ................................................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1699 ........ Drought, high temperatures ............ .......... 2 
364 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

IL ......................................... Alexander, Bond, Boone, Calhoun, Clark, 

Clay, Clinton, Coles, Cook, Crawford, Cumberland, DeKalb, Dupage, Edgar, Edwards, Effingham, Fayette, Franklin, Gallatin, Greene, Grundy, Hamilton, Hardin, Jackson, Jasper, Jefferson, Jersey, Johnson, Kane, Kendall, Lake, LaSalle, Lawrence, Lee, Madison, Marion, Massac, McHenry, Monroe, Montgomery, Ogle, Perry, Piatt, Pope, Pulaski, Randolph, Richland, Saline, Scott, Shelby, St. Clair, Union, Wabash, Washington , Wayne, White, Will, Williamson.

1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1700 ........ Drought ............................................ 58 22 

IN ......................................... ................................................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1700 ........ Drought ............................................ .......... 7 KY ........................................ ................................................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1700 ........ Drought ............................................ .......... 5 MO ....................................... ................................................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1700 ........ Drought ............................................ .......... 11 WI ........................................ ................................................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1700 ........ Drought ............................................ .......... 3 MD ....................................... Anne Arundel, Baltimore, Calvert, Caroline, Carroll, Cecil, Charles, Dorchester, Frederick, Harford, Howard, 

Kent, Montgomery, Prince George’s, Queen Anne’s, St. Mary’s, Somerset, Talbot, Washington, Wicomico, Worchester.

1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1701 ........ Drought, excessive heat .................. 21 2 

DE ........................................ ................................................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1701 ........ Drought, excessive heat .................. .......... 3 PA ........................................ ................................................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1701 ........ Drought, excessive heat .................. .......... 5 VA ........................................ ................................................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1701 ........ Drought, excessive heat .................. .......... 10 WV ....................................... ................................................................... 1–01–2002 .. 4–17–2003 .. 10–17–2002 6–17–2003 .. S1701 ........ Drought, excessive heat .................. .......... 3 
365 

IN ......................................... Adams, Allen, Bartholomew, Blackford, 

Brown, Clark, Clay, Crawford, Daviess, Dearborn, Decatur, DeKalb, Delaware, Dubois, Elkhart, Fayette, Floyd, Franklin, Fulton, Gibson, Grant, Greene, Hamilton, Hancock, Harrison, Henry, Huntington, Jackson, Jay, Jefferson, Jennings, Johnson, Knox, Kosciusko, Lagrange, Lake, LaPorte, Lawrence, Madison, Marion, Marshall, Martin, Monroe, Morgan, Noble, Ohio, Orange, Owen, Perry, Pike, Porter, Posey, Randolph, Ripley, Rush, Scott, Shelby, Spencer, St. Joseph, Starke, Steuben, Sullivan , Switzerland, Tipton, Union, Vanderburg, Vermillion, Vigo, Wabash, Warrick, Washington, Wayne, Wells, Whitley.

6–01–2002 .. 8–25–2002 .. 10–18–2002 6–18–2003 .. S1702 ........ Drought ............................................ 74 13 

IL ......................................... ................................................................... 6–01–2002 .. 8–25–2002 .. 10–18–2002 6–18–2003 .. S1702 ........ Drought ............................................ .......... 11 KY ........................................ ................................................................... 6–01–2002 .. 8–25–2002 .. 10–18–2002 6–18–2003 .. S1702 ........ Drought ............................................ .......... 12 MI ........................................ ................................................................... 6–01–2002 .. 8–25–2002 .. 10–18–2002 6–18–2003 .. S1702 ........ Drought ............................................ .......... 5 AL ........................................ All counties except, Baldwin, Clarke, 

Escambia, Lamar, Marion, Mobile, Washington, Winston.

1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1703 ........ Drought ............................................ 59 7 

FL ........................................ ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1703 ........ Drought ............................................ .......... 3 MS ....................................... ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1703 ........ Drought ............................................ .......... 8 TN ........................................ ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1703 ........ Drought ............................................ .......... 6 AL ........................................ Baldwin, Clarke, Escambia, Lamar, Marion, Mobile, Washington, Winston. 1–01–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1703, Amendment 1. Drought ............................................ 8 ..........
366 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

LA ........................................ Ascension, Avoyelles, Beauregard, 

Bienville, Bossier, Caddo, Caldwell, Catahoula, Claiborne, Concordia, DeSoto, East Baton Rouge, East Feliciana, Franklin, Grant, Iberville, Jackson, Lafourche, LaSalle, Lincoln, Livingston, Natchitoches, Ouachita, Pointe Coupee, Rapides, Red River, Richland, Sabine, St. Helena, St. James, St. Landry, St. Tammany, Tangipahoa, Tensas, Terrebonne, Union, Vernon, Washington, Webster, West Baton Rouge, West Carroll, West Feliciana, Winn.

4–02–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1704 ........ Drought ............................................ 43 18 

AR ........................................ ................................................................... 4–02–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1704 ........ Drought ............................................ .......... 6 MS ....................................... ................................................................... 4–02–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1704 ........ Drought ............................................ .......... 11 TX ........................................ ................................................................... 4–02–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1704 ........ Drought ............................................ .......... 7 IA ......................................... Adams, Audubon, Cass, Clay, Decatur, 

Dickinson, Fremont, Harrison, Lyon, Mills, Monona, Montgomery, O’Brien, Page, Palo Alto, Pottawattamie, Shelby, Taylor.

9–01–2001 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1705 ........ Drought, high winds, cold spring 

temperatures, grasshopper infestation, extreme heat, hail.

18 19 

MN ....................................... ................................................................... 9–01–2001 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1705 ........ .......................................................... .......... 3 MO ....................................... ................................................................... 9–01–2001 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1705 ........ .......................................................... .......... 4 SD ........................................ ................................................................... 9–01–2001 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1705 ........ .......................................................... .......... 2 
367 

TX ........................................ Andrews, Aransas, Archer, Armstrong, 

Atascosa, Bailey, Bandera, Baylor, Bee, Bexar. Blanco, Bosque, Brewster, Briscoe, Burnet, Cameron, Carson, Castro, Clay, Cochran, Coke, Coleman, Comal, Coryell, Cottle, Crane, Crockett, Crosby, Culberson, Dallam, Dawson, Deaf Smith, DeWitt, Dickens, Dimmit, Donley, Ector, El Paso, Erath, Fisher, Floyd, Frio, Gaines, Goliad, Gonzales, Gray, Guadalupe, Hale, Hall, Hamilton, Hansford, Hartley, Hays, Hemphill, Hockley, Hood, Hudspeth, Hutchinson, Irion, Jack, Jeff Davis, Johnson, Jones, Kendall, Kenedy, Kent, Kerr, Kimble, King, Kinney, Knox, La Salle, Lamb, Lampasas, Lipscomb, Llano, Lynn, Mason, McCulloch, McMullen, Medina, Midland, Mills, Montague, Moore, Motley, Nueces, Ochiltree, Oldham, Palo Pinto, Parker, Parmer, Potter, Randall, Reagan, Real, Refugio, Roberts, San Patricio, San Saba, Scurry, Shackelford, Sherman, Somervell, Sterling, Stonewall, Swisher, Tarrant, Taylor, Terrell, Throckmorton, Travis, Upton, Uvalde, Val Verde, Ward, Wichita, Wilson, Winkler, Wise, Yoakum, Young.

1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1706 ........ Drought, excessive temperatures .... 122 58 

NM ....................................... ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1706 ........ Drought, excessive temperatures .... .......... 8 OK ........................................ ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1706 ........ Drought, excessive temperatures .... .......... 9 
368 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

VA ........................................ Appomattox, Augusta, Bedford, Bland, 

Botetourt, Buckingham, Campbell, Caroline, Craig, Cumberland, Floyd, Franklin, Goochland, Greene, Hanover, Henry, King And Queen, King George, King William, Lunenburg, Madison, Mecklenburg, Middlesex, Montgomery, Nelson, New Kent, Nottoway, Page, Pittsylvania, Powhatan, Prince William, Richmond, Rockingham, Spotsylvania, Stafford, Suffolk city, Surry, Westmoreland, Wythe.

1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1707 ........ Drought, excessive heat .................. 39 41 

MD ....................................... ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1707 ........ .......................................................... .......... 2 NC ....................................... ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1707 ........ .......................................................... .......... 8 WV ....................................... ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1707 ........ .......................................................... .......... 4 KS ........................................ Clark, Finney, Norton, Phillips, Reno, 

Rice, Rooks.

6–09–2002 .. 7–05–2002 .. 10–21–2002 6–23–2003 .. S1708 ........ Hail, high winds, tornadoes, excessive rain, flash flooding, flooding, lightning. 7 21 

NE ........................................ ................................................................... 6–09–2002 .. 7–05–2002 .. 10–21–2002 6–23–2003 .. S1708 ........ Hail, high winds, tornadoes, excessive rain, flash flooding, flooding, lightning. .......... 3 OK ........................................ ................................................................... 6–09–2002 .. 7–05–2002 .. 10–21–2002 6–23–2003 .. S1708 ........ Hail, high winds, tornadoes, excessive rain, flash flooding, flooding, lightning. .......... 2 NH ....................................... Entire State ............................................... 6–01–2001 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1709 ........ Drought ............................................ 10 ..........MA ....................................... ................................................................... 6–01–2001 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1709 ........ Drought ............................................ .......... 4 ME ....................................... ................................................................... 6–01–2001 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1709 ........ Drought ............................................ .......... 2 VT ........................................ ................................................................... 6–01–2001 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1709 ........ Drought ............................................ .......... 5 RI ......................................... Entire State ............................................... 10–01–2001 4–21–2003 .. 10–21–2002 6–23–2003 .. S1710 ........ Drought ............................................ 5 ..........CT ........................................ ................................................................... 10–01–2001 4–21–2003 .. 10–21–2002 6–23–2003 .. S1710 ........ Drought ............................................ .......... 2 MA ....................................... ................................................................... 10–01–2001 4–21–2003 .. 10–21–2002 6–23–2003 .. S1710 ........ Drought ............................................ .......... 3 KY ........................................ Entire State ............................................... 1–01–2002 .. 4–24–2003 .. 10–24–2002 6–24–2003 .. S1711 ........ Drought ............................................ .......... ..........IL ......................................... ................................................................... 1–01–2002 .. 4–24–2003 .. 10–24–2002 6–24–2003 .. S1711 ........ Drought ............................................ .......... 6 IN ......................................... ................................................................... 1–01–2002 .. 4–24–2003 .. 10–24–2002 6–24–2003 .. S1711 ........ Drought ............................................ .......... 13 
369 

MO ....................................... ................................................................... 1–01–2002 .. 4–24–2003 .. 10–24–2002 6–24–2003 .. S1711 ........ Drought ............................................ .......... 1 TN ........................................ ................................................................... 1–01–2002 .. 4–24–2003 .. 10–24–2002 6–24–2003 .. S1711 ........ Drought ............................................ .......... 14 VA ........................................ ................................................................... 1–01–2002 .. 4–24–2003 .. 10–24–2002 6–24–2003 .. S1711 ........ Drought ............................................ .......... 4 WV ....................................... ................................................................... 1–01–2002 .. 4–24–2003 .. 10–24–2002 6–24–2003 .. S1711 ........ Drought ............................................ .......... 2 SD ........................................ Custer, Jackson, Lawrence ........................ 7–01–2001 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1712 ........ Drought, extreme heat, winds, late 

frosts, fire.

3 ..........

NV ........................................ Entire State ............................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1713 ........ Drought, Mormon crickets, grasshoppers. 17 ..........CA ........................................ ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1713 ........ Drought, Mormon crickets, grasshoppers. .......... 10 ID ......................................... ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1713 ........ Drought, Mormon crickets, grasshoppers. .......... 2 OR ....................................... ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1713 ........ Drought, Mormon crickets, grasshoppers. .......... 3 NV ........................................ Entire State ............................................... 1–01–2001 .. 4–21–2003 .. 11–21–2002 6–23–2003 .. S1713, 

Amendment 1.

Severe Insect infestations ............... 17 ..........

ID ......................................... Adams, Bannock, Blaine, Boise, Bonneville, Caribou, Clark, Fremont, Gem, 

Lincoln, Owyhee, Valley, Washington.

1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1714 ........ Drought ............................................ 13 12 

MT ....................................... ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1714 ........ Drought ............................................ .......... 3 NV ........................................ ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1714 ........ Drought ............................................ .......... 1 OR ....................................... ................................................................... 1–01–2002 .. 4–21–2003 .. 10–21–2002 6–23–2003 .. S1714 ........ Drought ............................................ .......... 3 ID ......................................... Bingham, Jefferson, Madison ................... 1–01–2002 .. 6–04–2003 .. 12–04–2002 8–04–2003 .. S1714, 

Amendment 1.

Drought ............................................ 3 ..........

KS ........................................ Allen, Anderson, Atchison, Barton, Bourbon, Brown, Butler, Chase, Cherokee, 

Cloud, Coffey, Cowley, Crawford, Dickinson, Doniphan, Douglas, Ells, Ellis, Franklin, Greenwood, Harper, Harvey, Haskell, Jackson, Jefferson, Johnson, Kingman, Kiowa, Labette, Leavenworth, Line, Lyon, Marion, Marshall, McPherson, Miami, Morris, Nemaha, Neosho, Ness, Osage, Ottawa, Pratt, Reno, Republic, Rice, Sedgwick, Shawnee, Stafford, Wabaunsee, Washington, Wilson, Woodson, Wyandotte.

1–01–2002 .. 4–25–2003 .. 10–25–2002 6–25–2002 .. S1715 ........ Drought ............................................ 54 3 

MO ....................................... ................................................................... 1–01–2002 .. 4–25–2003 .. 10–25–2002 6–25–2002 .. S1715 ........ Drought ............................................ .......... 12 
370 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

OK ........................................ ................................................................... 1–01–2002 .. 4–25–2003 .. 10–25–2002 6–25–2002 .. S1715 ........ Drought ............................................ .......... 3 WY ....................................... Converse, Goshen, Niobrara, Platte, 

Sublette, Sweetwater, Weston.

1–01–2002 .. 4–28–2003 .. 10–28–2002 6–30–2003 .. S1716 ........ Drought ............................................ 7 5 

CO ....................................... ................................................................... 1–01–2002 .. 4–28–2003 .. 10–28–2002 6–30–2003 .. S1716 ........ Drought ............................................ .......... 1 NE ........................................ ................................................................... 1–01–2002 .. 4–28–2003 .. 10–28–2002 6–30–2003 .. S1716 ........ Drought ............................................ .......... 2 SD ........................................ ................................................................... 1–01–2002 .. 4–28–2003 .. 10–28–2002 6–30–2003 .. S1716 ........ Drought ............................................ .......... 4 UT ........................................ ................................................................... 1–01–2002 .. 4–28–2003 .. 10–28–2002 6–30–2003 .. S1716 ........ Drought ............................................ .......... 2 WI ........................................ Door ........................................................... 5–15–2002 .. 5–20–2002 .. 11–08–2002 7–08–2003 .. S1717 ........ Frost, freezing temperatures ........... 1 1 MN ....................................... Benton, Crow Wing, Jackson, Mille Lacs, 

Nobles, Rock.

4–01–2002 .. 7–10–2002 .. 11–15–2002 7–15–2003 .. S1718 ........ Crow Wing, Jackson, Nobles, Rock: 

Drought Benton, Mille Lacs: Heavy rain, hail, flooding, severe thunderstorms.

6 12 

IA ......................................... ................................................................... 4–01–2002 .. 7–10–2002 .. 11–15–2002 7–15–2003 .. S1718 ........ Crow Wing, Jackson, Nobles, Rock: 

Drought Benton, Mille Lacs: Heavy rain, hail, flooding, severe thunderstorms.

.......... 4 

SD ........................................ ................................................................... 4–01–2002 .. 7–10–2002 .. 11–15–2002 7–15–2003 .. S1718 ........ Crow Wing, Jackson, Nobles, Rock: 

Drought Benton, Mille Lacs: Heavy rain, hail, flooding, severe thunderstorms.

.......... 2 

NY ........................................ Albany, Allegany, Broome, Cattaraugus, 

Cayuga, Chautauqua, Chenango, Clinton, Cortland, Delaware, Erie, Essex, Franklin, Fulton, Genesee, Herkimer, Jefferson, Lewis, Livingston, Madison, Monroe, Montgomery, Niagara, Oneida, Onondaga, Ontario, Orleans, Oswego, Otsego, Rensselaer, Rockland, St. Lawrence, Saratoga, Steuben, Suffolk, Sullivan, Warren, Washington, Wayne, Wyoming, Yates.

6–01–2002 .. 5–15–2003 .. 11–15–2002 7–15–2003 .. S1719 ........ Drought ............................................ 41 15 

CT ........................................ ................................................................... 6–01–2002 .. 5–15–2003 .. 11–15–2002 7–15–2003 .. S1719 ........ Drought ............................................ .......... 4 MA ....................................... ................................................................... 6–01–2002 .. 5–15–2003 .. 11–15–2002 7–15–2003 .. S1719 ........ Drought ............................................ .......... 1 NJ ........................................ ................................................................... 6–01–2002 .. 5–15–2003 .. 11–15–2002 7–15–2003 .. S1719 ........ Drought ............................................ .......... 2 
371 

PA ........................................ ................................................................... 6–01–2002 .. 5–15–2003 .. 11–15–2002 7–15–2003 .. S1719 ........ Drought ............................................ .......... 8 VT ........................................ ................................................................... 6–01–2002 .. 5–15–2003 .. 11–15–2002 7–15–2003 .. S1719 ........ Drought ............................................ .......... 5 CA ........................................ Butte, Colusa, Fresno, Glenn, Kern, Kings, 

Los Angeles, Merced, Monterey, Napa, Orange, Plumas, Riverside, San Benito, San Bernardino, San Joaquin, San Luis Obispo, Santa Barbara, Santa Clara, Shasta, Sierra, Solano, Sonoma, Stanislaus, Tehama, Tulare, Tuolumne, Ventura, Yolo.

1–01–2002 .. 5–18–2003 .. 11–18–2002 7–18–2003 .. S1720 ........ Drought ............................................ 29 24 

AZ ........................................ ................................................................... 1–01–2002 .. 5–18–2003 .. 11–18–2002 7–18–2003 .. S1720 ........ Drought ............................................ .......... 2 NC ....................................... Avery, Bladen, Brunswick, Buncombe, 

Cherokee, Clay, Columbus, Craven, Duplin, Edgecombe, Gates, Graham, Greene, Haywood, Henderson, Jackson, Jones, Lenoir, Macon, Madison, Martin, Mitchell, Pender, Pitt, Polk, Sampson, Swain, Transylvania, Washington, Watauga, Yancey.

1–01–2002 .. 5–18–2003 .. 11–18–2002 7–18–2003 .. S1721 ........ Drought ............................................ 31 27 

GA ........................................ ................................................................... 1–01–2002 .. 5–18–2003 .. 11–18–2002 7–18–2003 .. S1721 ........ Drought ............................................ .......... 4 SC ........................................ ................................................................... 1–01–2002 .. 5–18–2003 .. 11–18–2002 7–18–2003 .. S1721 ........ Drought ............................................ .......... 6 TN ........................................ ................................................................... 1–01–2002 .. 5–18–2003 .. 11–18–2002 7–18–2003 .. S1721 ........ Drought ............................................ .......... 9 VA ........................................ ................................................................... 1–01–2002 .. 5–18–2003 .. 11–18–2002 7–18–2003 .. S1721 ........ Drought ............................................ .......... 2 NC ....................................... Bertie, Chowan, Hertford, Perquimans ..... 1–01–2002 .. 5–18–2003 .. 11–18–2002 7–18–2003 .. S1721, 

Amendment 1.

Drought ............................................ 4 1 

SD ........................................ Codington, Turner ..................................... 7–01–2001 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1722 ........ Drought ............................................ 2 1 WA ....................................... Adams ....................................................... 5–01–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1723 ........ Drought ............................................ 1 4 NY ........................................ Orleans ...................................................... 4–14–2002 .. 6–16–2002 .. 11–21–2002 7–21–2003 .. S1724 ........ Excessive rain, freeze ...................... 1 3 NY ........................................ Chemung, Columbia, Dutchess, Greene, 

Orange, Orleans, Putnam, Schenectady, Schoharie, Schuyler, Seneca, Tioga, Tompkins, Ulster, Westchester.

5–15–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1724 ........ Drought ............................................ 14 17 

CT ........................................ ................................................................... 5–15–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1724 ........ Drought ............................................ .......... 2 MA ....................................... ................................................................... 5–15–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1724 ........ Drought ............................................ .......... 1 NJ ........................................ ................................................................... 5–15–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1724 ........ Drought ............................................ .......... 3 PA ........................................ ................................................................... 5–15–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1724 ........ Drought ............................................ .......... 4 
372 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

MA ....................................... Barnstable, Berkshire, Bristol, Dukes, 

Essex, Franklin, Hampden, Hampshire, Middlesex, Norfolk, Plymouth, Worcester.

10–01–2001 5–21–2003 .. 11–21–2002 7–21–2003 .. S1725 ........ Drought ............................................ 12 2 

CT ........................................ ................................................................... 10–01–2001 5–21–2003 .. 11–21–2002 7–21–2003 .. S1725 ........ Drought ............................................ .......... 3 NY ........................................ ................................................................... 10–01–2001 5–21–2003 .. 11–21–2002 7–21–2003 .. S1725 ........ Drought ............................................ .......... 3 VT ........................................ ................................................................... 10–01–2001 5–21–2003 .. 11–21–2002 7–21–2003 .. S1725 ........ Drought ............................................ .......... 1 OR ....................................... Baker, Jefferson, Umatilla ........................ 10–01–2000 5–21–2003 .. 11–21–2002 7–21–2003 .. S1726 ........ Drought, colder than normal weather, frosts. 3 11 WA ....................................... ................................................................... 10–01–2000 5–21–2003 .. 11–21–2002 7–21–2003 .. S1726 ........ Drought, colder than normal weather, frosts. .......... 5 TN ........................................ Anderson, Bedford, Benton, Bledsoe, 

Blount, Bradley, Campbell, Cannon, Carroll, Carter, Chester, Claiborne, Clay, Coffee, Crockett, Cumberland, De Kalb, Dyer, Fentress, Franklin, Giles, Greene, Grundy, Hamilton, Hancock, Hardeman, Hardin, Hawkins, Haywood, Houston, Jackson, Jefferson, Johnson, Knox, Lake, Lauderdale, Lawrence, Lincoln, Loudon, McMinn, McNairy, Macon, Madison, Marshall, Maury, Meigs, Monroe, Moore, Obion, Overton, Pickett, Polk, Putnam, Rhea, Roane, Rutherford, Sevier, Shelby, Smith, Stewart, Sullivan, Sumner, Tipton, Trousdale, Unicoi, Union, Warren, Washington, Wayne, Weakley, Williamson, Wilson.

1–01–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1727 ........ Drought, high temperatures, high 

wind, hail.

72 23 

AL ........................................ ................................................................... 1–01–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1727 ........ Drought, high temperatures, high 

wind, hail.

.......... 4 

AR ........................................ ................................................................... 1–01–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1727 ........ Drought, high temperatures, high 

wind, hail.

.......... 2 
373 

GA ........................................ ................................................................... 1–01–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1727 ........ Drought, high temperatures, high 

wind, hail.

.......... 6 

KY ........................................ ................................................................... 1–01–2002 .. 5–21–2003 .. 11–21–2002 7–21–2003 .. S1727 ........ Drought, high temperatures, high 

wind, hail.

.......... 15 

TN ........................................ Cocke ......................................................... 1–01–2002 .. 10–18–2002 12–13–2002 8–13–2002 .. S1727, 

Amendment 1.

Drought, high temperatures, high 

wind, hail, spring flooding, late freezes.

1 ..........

WA ....................................... Franklin ..................................................... 9–01–2001 .. 5–27–2003 .. 11–27–2002 7–28–2003 .. S1728 ........ (1) Drought, High winds, excessive 

rainfall, hailstorms.

(2) Freezing weather, high winds ...

1 6 

SD ........................................ Kingsbury .................................................. 7–28–2002 .. 7–28–2002 .. 12–13–2002 8–13–2002 .. S1729 ........ Hailstorm ......................................... 1 7 CT ........................................ Entire State (8 counties) .......................... 10–01–2001 6–30–2003 .. 12–30–2002 9–01–2003 .. S1730 ........ Drought ............................................ 8 ..........ID ......................................... Bear Lake, Butte, Custer, Franklin, 

Lemhi, Oneida, Payette, Power.

1–01–2002 .. 6–30–2003 .. 12–30–2002 9–01–2003 .. S1731 ........ Drought ............................................ 8 2 

UT ........................................ ................................................................... 1–01–2002 .. 6–30–2003 .. 12–30–2002 9–01–2003 .. S1731 ........ Drought ............................................ .......... 3 KS ........................................ Meade, Rice .............................................. 8–12–2002 .. 8–13–2002 .. 12–30–2002 9–01–2003 .. S1732 ........ Hail, high winds, excessive rain, 

flash flooding, flooding.

2 10 

OK ........................................ ................................................................... 8–12–2002 .. 8–13–2002 .. 12–30–2002 9–01–2003 .. S1732 ........ Hail, high winds, excessive rain, 

flash flooding, flooding.

.......... 1 

NY ........................................ Allegany, Broome, Cattaraugus, Cayuga, 

Clinton, Dutchess, Franklin, Jefferson, Madison, Niagara, Ontario, Orange, Otsego, Putnam, Rensselaer, Schuyler, Seneca, Steuben, Tioga, Tompkins, Ulster, Wayne, Westchester, Wyoming, Yates.

4–01–2002 .. 6–30–2002 .. 12–30–2002 9–01–2003 .. S1733 ........ Various disasters: Excessive Rain, 

Flash Flooding, Flooding, Freeze, Frost , Hail, High Winds, Lightning, Tornado.

25 29 

CT ........................................ ................................................................... 4–24–2002 .. 5–31–2002 .. 12–30–2002 9–01–2003 .. S1733 ........ Various disasters: Excessive Rain, 

Freeze, Frost , Hail, High Winds.

.......... 2 

MA ....................................... ................................................................... 6–05–2002 .. 6–05–2002 .. 12–30–2002 9–01–2003 .. S1733 ........ Various disasters: Excessive Rain, 

High Winds, Lightning.

.......... 1 

NJ ........................................ ................................................................... 4–24–2002 .. 5–20–2002 .. 12–30–2002 9–01–2003 .. S1733 ........ Various disasters: Excessive 

RainFreeze, Frost.

.......... 3 

PA ........................................ ................................................................... 4–01–2002 .. 6–30–2002 .. 12–30–2002 9–01–2003 .. S1733 ........ Various disasters: Excessive Rain, 

Flash Flooding, Frost, Tornado.

.......... 8 

VT ........................................ ................................................................... 5–23–2002 .. 6–28–2002 .. 12–30–2002 9–01–2003 .. S1733 ........ Various disasters: Excessive Rain, 

Flash Flooding, High Winds, Lightning.

.......... 3 
374 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

OK ........................................ Choctaw, Creek, Haskell, Hughes, Latimer, LeFlore, McCurtain, McIntosh, 

Okfuskee, Okmulgee, Ottawa, Pittsburg, Pottawatomie, Pushmataha, Rogers, Tulsa.

5–01–2002 .. 6–30–2003 .. 12–30–2002 9–01–2003 .. S1734 ........ Drought ............................................ 16 14 

AR ........................................ ................................................................... 5–01–2002 .. 6–30–2003 .. 12–30–2002 9–01–2003 .. S1734 ........ Drought ............................................ .......... 5 MO ....................................... ................................................................... 5–01–2002 .. 6–30–2003 .. 12–30–2002 9–01–2003 .. S1734 ........ Drought ............................................ .......... 1 TX ........................................ ................................................................... 5–01–2002 .. 6–30–2003 .. 12–30–2002 9–01–2003 .. S1734 ........ Drought ............................................ .......... 3 TX ........................................ Runnels ..................................................... 1–01–2002 .. 6–30–2003 .. 12–30–2002 9–01–2003 .. S1735 ........ Drought ............................................ 1 ..........WA ....................................... Spokane ..................................................... 4–23–2002 .. 6–08–2002 .. 12–30–2002 9–01–2003 .. S1736 ........ Freezing weather ............................. 1 4 ID ......................................... ................................................................... 4–23–2002 .. 6–08–2002 .. 12–30–2002 9–01–2003 .. S1736 ........ Freezing weather ............................. .......... 3 WA ....................................... Whitman .................................................... 4–24–2002 .. 6–08–2002 .. 12–30–2002 9–01–2003 .. S1737 ........ Frost damage .................................. 1 7 ID ......................................... ................................................................... 4–24–2002 .. 6–08–2002 .. 12–30–2002 9–01–2003 .. S1737 ........ Frost damage .................................. .......... 3 LA ........................................ Beauregard, Calcasieu, Cameron, 

Catahoula, Concordia, DeSoto, East Carroll, Franklin, Grant, LaSalle, Madison, Morehouse, Natchitoches, Pointe Coupee, Red River, Richland, Tensas, Vernon, West Carroll, Winn.

9–16–2002 .. 7–15–2003 .. 1–15–2003 .. 9–15–2003 .. S1738 ........ Excessive rainfall ............................ 20 19 

AR ........................................ ................................................................... 9–16–2002 .. 7–15–2003 .. 1–15–2003 .. 9–15–2003 .. S1738 ........ Excessive rainfall ............................ .......... 3 MS ....................................... ................................................................... 9–16–2002 .. 7–15–2003 .. 1–15–2003 .. 9–15–2003 .. S1738 ........ Excessive rainfall ............................ .......... 6 TX ........................................ ................................................................... 9–16–2002 .. 7–15–2003 .. 1–15–2003 .. 9–15–2003 .. S1738 ........ Excessive rainfall ............................ .......... 5 IA ......................................... Clay, O’Brien, Sioux .................................. 9–30–2002 .. 7–15–2003 .. 1–15–2003 .. 9–15–2003 .. S1739 ........ Severe storms, including, hail and 

high winds.

3 9 

SD ........................................ Clay, O’Brien, Sioux .................................. 9–30–2002 .. 7–15–2003 .. 1–15–2003 .. 9–15–2003 .. S1739 ........ Severe storms, including, hail and 

high winds.

.......... 2 

MT ....................................... BLACKFEET NATION—(Glacier, Pondera 

Counties).

6–07–2002 .. 6–12–2002 .. 1–15–2003 .. 9–15–2003 .. S1740 ........ Heavy snow, wind, rain, blizzard 

conditions, flooding, unseasonably cold weather.

2 ..........

SC ........................................ Entire State ............................................... 4–01–2002 .. 11–30–2002 1–15–2003 .. 9–15–2003 .. S1741 ........ Drought ............................................ 46 ..........NC ....................................... Entire State ............................................... 4–01–2002 .. 11–30–2002 1–15–2003 .. 9–15–2003 .. S1741 ........ Drought ............................................ .......... 9 
375 

VA ........................................ Albemarle, Amelia, Amherst, Campbell, 

Charlotte, Chesterfield, Culpeper, Dinwiddie, Essex, Fauquier, Halifax, Henrico, Isle of Wight, Louisa, Prince George, Pulaski, Scott, Warren.

1–01–2002 .. 7–31–2003 .. 1–31–2003 .. 10–01–2003 S1742 ........ Drought, excessive heat .................. 18 12 

VA ........................................ Accomack, Alleghany, Bath, Buchanan, 

Carroll, Charles City, Clarke, Dickenson, Giles, Gloucester, Grayson, Greensville, James City, Lancaster, Lee, Mathews, Northampton, Northumberland, Orange, Patrick, Rappahannock, Roanoke, Russell, Shenandoah, Smyth, Southampton, Tazewell, Wise.

1–01–2002 .. 7–31–2003 .. 1–31–2003 .. 10–01–2003 S1743 ........ Drought, excessive heat .................. 28 9 

NC ....................................... ................................................................... 1–01–2002 .. 7–31–2003 .. 1–31–2003 .. 10–01–2003 S1743 ........ Drought, excessive heat .................. .......... 3 WV ....................................... ................................................................... 1–01–2002 .. 7–31–2003 .. 1–31–2003 .. 10–01–2003 S1743 ........ Drought, excessive heat .................. .......... 4 TN ........................................ Cheatham, Decatur, Gibson, Grainger, 

Hamblen, Henderson, Montgomery, Van Buren, White.

8–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1744 ........ Armyworms, drought, excessive 

heat, excessive rain, moisture, flooding.

9 42 

TN ........................................ Bradley, Chester, Haywood, Lauderdale, 

Madison, Marshall, Maury, McNairy, Obion, Polk, Shelby, Tipton, Weakley.

5–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1744 ........ Armyworms, excessive rain, moisture, flooding. 13 ..........

AR ........................................ ................................................................... 8–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1744 ........ Armyworms, excessive rain, moisture, flooding. .......... 2 GA ........................................ ................................................................... 8–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1744 ........ Armyworms, excessive rain, moisture, flooding. .......... 4 KY ........................................ ................................................................... 8–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1744 ........ Armyworms, excessive rain, moisture, flooding. .......... 4 KY ........................................ ................................................................... 5–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1744 ........ Armyworms, drought, excessive 

heat, excessive rain, moisture, flooding.

.......... 1 

MS ....................................... ................................................................... 8–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1744 ........ Armyworms, excessive rain, moisture, flooding. .......... 3 NC ....................................... ................................................................... 8–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1744 ........ Armyworms, excessive rain, moisture, flooding. .......... 1 
376 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

MO ....................................... Andrew, Atchison, Bates, Buchanan, 

Caldwell, Carroll, Cass, Cedar, Clinton, Daviess, DeKalb, Gentry, Grundy, Harrison, Henry, Holt, Jackson, Johnson, Linn, Livingston, Mercer, Nodaway, Platte, Putnam, Ray, Schuyler, Sullivan, Vernon, Worth.

6–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1745 ........ Drought ............................................ 29 13 

IA ......................................... ................................................................... 6–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1745 ........ Drought ............................................ .......... 2 KS ........................................ ................................................................... 6–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1745 ........ Drought ............................................ .......... 9 NE ........................................ ................................................................... 6–01–2002 .. 8–07–2003 .. 2–07–2003 .. 10–07–2003 S1745 ........ Drought ............................................ .......... 3 PA ........................................ Delaware, Fayette, Greene, Tioga, Washington. 6–01–2002 .. 8–11–2003 .. 2–11–2003 .. 10–14–2003 S1746 ........ Drought ............................................ 5 ..........NJ ........................................ ................................................................... 6–01–2002 .. 8–11–2003 .. 2–11–2003 .. 10–14–2003 S1746 ........ Drought ............................................ .......... 1 WV ....................................... ................................................................... 6–01–2002 .. 8–11–2003 .. 2–11–2003 .. 10–14–2003 S1746 ........ Drought ............................................ .......... 6 WV ....................................... Berkeley, Boone, Braxton, Brooke, Cabell, 

Calhoun, Clay, Doddridge, Gilmer, Grant, Greenbrier, Hampshire, Hancock, Harrison, Jackson, Kanawha, Lewis, Lincoln, Logan, Marshall, Mason, Mercer, Mineral, Mingo, Monroe, Morgan, Nicholas, Ohio, Pendleton, Pleasants, Pocahontas, Ritchie, Roane, Taylor, Tyler, Upshur, Wayne, Webster, Wetzel, Wirt, Wood.

1–01–2002 .. 11–19–2002 2–13–2003 .. 10–14–2003 S1747 ........ Drought ............................................ 41 12 

KY ........................................ ................................................................... 1–01–2002 .. 11–19–2002 2–13–2003 .. 10–14–2003 S1747 ........ Drought ............................................ .......... 4 OH ....................................... ................................................................... 1–01–2002 .. 11–19–2002 2–13–2003 .. 10–14–2003 S1747 ........ Drought ............................................ .......... 8 PA ........................................ ................................................................... 1–01–2002 .. 11–19–2002 2–13–2003 .. 10–14–2003 S1747 ........ Drought ............................................ .......... 1 VA ........................................ ................................................................... 1–01–2002 .. 11–19–2002 2–13–2003 .. 10–14–2003 S1747 ........ Drought ............................................ .......... 5 
377 

MS ....................................... Adams, Alcorn, Amite, Benton, Bolivar, 

Calhoun, Carroll, Chickasaw, Choctaw, Claiborne, Clay, Coahoma, Covington, De Soto, Forrest, Franklin, George, Greene, Grenada, Hancock, Harrison, Hinds, Holmes, Humphreys, Issaquena, Itawamba, Jackson, Jefferson, Jefferson Davis, Jones, Lafayette, Lawrence, Lee, Leflore, Lincoln, Lowndes, Madison, Marion, Marshall, Monroe, Newton, Noxubee, Oktibbeha, Panola, Pearl River, Perry, Pike, Pontotoc, Prentiss, Quitman, Rankin, Scott, Sharkey, Simpson, Stone, Sunflower, Tallahatchie, Tate, Tippah, Tishomingo, Tunica, Union, Walthall, Warren, Washington, Wayne, Webster, Wilkinson, Winston, Yalobusha, Yazoo.

9–26–2003 .. 8–13–2003 .. 2–13–2003 .. 10–14–2003 S1748 ........ Tropical Storm Isidore; Hurricane 

Lili.

71 11 

AL ........................................ ................................................................... 9–26–2003 .. 8–13–2003 .. 2–13–2003 .. 10–14–2003 S1748 ........ Tropical Storm Isidore; Hurricane 

Lili.

.......... 10 

AR ........................................ ................................................................... 9–26–2003 .. 8–13–2003 .. 2–13–2003 .. 10–14–2003 S1748 ........ Tropical Storm Isidore; Hurricane 

Lili.

.......... 6 

LA ........................................ ................................................................... 9–26–2003 .. 8–13–2003 .. 2–13–2003 .. 10–14–2003 S1748 ........ Tropical Storm Isidore; Hurricane 

Lili.

.......... 10 

TN ........................................ ................................................................... 9–26–2003 .. 8–13–2003 .. 2–13–2003 .. 10–14–2003 S1748 ........ Tropical Storm Isidore; Hurricane 

Lili.

.......... 5 

MS ....................................... Attala, Clarke, Copiah, Jasper, Kemper, 

Lamar, Lauderdale, Leake, Montgomery, Neshoba.

9–26–2003 .. 8–13–2003 .. 3–12–2003 .. 11–12–2003 S1748, 

Amendment 1.

Tropical Storm Isidore; Hurricane 

Lili.

11 ..........

CA ........................................ Inyo, Mono ................................................. 12–01–2001 11–25–2002 2–13–2003 .. 10–14–2003 S1749 ........ Drought, fires .................................. 2 ..........MI ........................................ (1) Alger, Baraga, Chippewa, Delta, Dickinson, Gogebic, Houghton, Iron, 

Keweenaw, Luce, Mackinaw, Marquette, Ontonagon, Houghton, Schoolcraft;.

4–01–2002 .. 8–13–2003 .. 2–13–2003 .. 10–14–2003 S1750 ........ Excessive rainfall ............................ 14 3 

MI ........................................ (2) Barry, Berrien, Branch, Calhoun, 

Cass, Eaton, Genesee, Hillsdale, Ingham, Jackson, Kalamazoo, Lenawee, Livingston, Monroe, Shiawassee, St. Joseph, Van Buren, Washtenaw, Wayne.

6–15–2002 .. 8–13–2003 .. 2–13–2003 .. 10–14–2003 S1750 ........ Drought ............................................ 19 10 
378 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

WI ........................................ ................................................................... 6–15–2002 .. 8–13–2003 .. 2–13–2003 .. 10–14–2003 S1750 ........ Excessive rainfall ............................ .......... 5 CA ........................................ Humboldt ................................................... 1–01–2002 .. 8–14–2003 .. 2–14–2003 .. 10–14–2003 S1751 ........ Drought ............................................ 1 4 OR ....................................... Coos, Crook, Curry, Grant, Union, Wheeler 9–01–2000 .. 8–14–2003 .. 2–14–2003 .. 10–14–2003 S1752 ........ Drought ............................................ 6 1 CA ........................................ ................................................................... 9–01–2000 .. 8–14–2003 .. 2–14–2003 .. 10–14–2003 S1752 ........ Drought ............................................ .......... 1 CA ........................................ Lassen ....................................................... 1–01–2002 .. 8–24–2003 .. 2–24–2003 .. 10–24–2003 S1753 ........ Drought ............................................ 1 ..........OR ....................................... Harney ....................................................... 10–01–2001 9–07–2003 .. 3–07–2003 .. 11–07–2003 S1754 ........ Drought ............................................ 1 ..........WA ....................................... Benton ....................................................... 1–01–2002 .. 7–08–2002 .. 3–12–2003 .. 11–12–2003 S1755 ........ (1) Drought, freezing temperatures, 

high winds.

(2) High winds, excessive rainfall, 

hailstorms.

1 2 

OR ....................................... ................................................................... 1–01–2002 .. 7–08–2002 .. 3–12–2003 .. 11–12–2003 S1755 ........ (1) Drought, freezing temperatures, 

high winds.

(2) High winds, excessive rainfall, 

hailstorms.

.......... 2 

TX ........................................ Uvalde ....................................................... 2–26–2002 .. 3–04–2002 .. 3–12–2003 .. 11–12–2003 S1756 ........ Freeze, high winds .......................... 1 8 TX ........................................ Lubbock ..................................................... 6–04–2002 .. 6–04–2002 .. 3–12–2003 .. 11–12–2003 S1757 ........ Excessive rain, flash flooding, ........

flooding, hail, high winds ...............

1 8 

ME ....................................... Entire State ............................................... 1–01–2002 .. 9–12–2003 .. 3–12–2003 .. 11–12–2003 S1758 ........ Drought ............................................ 16 ..........
379 

GA ........................................ Bacon, Banks, Barrow, Bartow, Ben Hill, 

Bibb, Bleckley, Brantley, Bryan, Bulloch, Burke, Butts, Calhoun, Candler, Carroll, Catoosa, Chattooga, Clarke, Clay, Clayton, Colquitt, Cook, Coweta, Crawford, Crisp, Dade, Dawson, De Kalb, Decatur, Dodge, Dooly, Dougherty, Douglas, Early, Echols, Effingham, Elbert, Emanuel, Evans, Fayette, Floyd, Forsyth, Franklin, Fulton, Glascock, Gordon, Gwinnett, Habersham, Hall, Haralson, Hart, Henry, Houston, Jackson, Jeff Davis, Jefferson, Jenkins, Johnson, Lamar, Laurens, Liberty, Long, Lowndes, Lumpkin, Macon, Madison, Marion, McDuffie, Miller, Mitchell, Monroe, Montgomery, Morgan, Murray, Oconee, Oglethorpe, Paulding, Peach, Pierce, Pike, Polk, Pulaski, Quitman, Rabun, Randolph, Rockdale, Schley, Screven, Seminole, Spalding, Stephens, Stewart, Sumter, Tattnall, Taylor, Telfair, Terrell, Thomas, Tift, Towns, Treutlen, Troup, Turner, Twiggs, Upson, Walker, Walton, Ware, Warren, Washington, Wayne, Webster, Wheeler, White, Whitfield, Wilcox, Wilkinson, Worth.

9–01–2002 .. 1–14–2003 .. 3–12–2003 .. 11–12–2003 S1759 ........ Wet, unseasonably cool fall weather. 118 40 

AL ........................................ ................................................................... 9–01–2002 .. 1–14–2003 .. 3–12–2003 .. 11–12–2003 S1759 ........ Wet, unseasonably cool fall weather. .......... 10 FL ........................................ ................................................................... 9–01–2002 .. 1–14–2003 .. 3–12–2003 .. 11–12–2003 S1759 ........ Wet, unseasonably cool fall weather. .......... 8 NC ....................................... ................................................................... 9–01–2002 .. 1–14–2003 .. 3–12–2003 .. 11–12–2003 S1759 ........ Wet, unseasonably cool fall weather. .......... 3 SC ........................................ ................................................................... 9–01–2002 .. 1–14–2003 .. 3–12–2003 .. 11–12–2003 S1759 ........ Wet, unseasonably cool fall weather. .......... 9 TN ........................................ ................................................................... 9–01–2002 .. 1–14–2003 .. 3–12–2003 .. 11–12–2003 S1759 ........ Wet, unseasonably cool fall weather. .......... 4 TN ........................................ Giles, Hardeman, Lawrence, Marion, 

Sequatchie, Wayne.

7–01–2002 .. 2–05–2003 .. 3–12–2003 .. 11–12–2003 S1760 ........ (1) Drought ......................................

(2) Excessive rain ...........................

6 18 
380 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

AL ........................................ ................................................................... 7–01–2002 .. 2–05–2003 .. 3–12–2003 .. 11–12–2003 S1760 ........ Excessive rain ................................. .......... 2 MS ....................................... ................................................................... 7–01–2002 .. 2–05–2003 .. 3–12–2003 .. 11–12–2003 S1760 ........ Excessive rain ................................. .......... 3 AZ ........................................ Yuma ......................................................... 1–01–2001 .. 9–12–2003 .. 3–12–2003 .. 11–12–2003 S1761 ........ Drought ............................................ 1 3 CA ........................................ ................................................................... 1–01–2001 .. 9–12–2003 .. 3–12–2003 .. 11–12–2003 S1761 ........ Drought ............................................ .......... 1 OR ....................................... Lake, Malheur ........................................... 9–01–2001 .. 9–21–2003 .. 3–21–2003 .. 11–21–2003 S1762 ........ Drought ............................................ 2 2 SD ........................................ Brookings, Clay ......................................... 5–01–2002 .. 12–31–2002 3–21–2003 .. 11–21–2003 S1763 ........ Drought ............................................ 2 6 CA ........................................ Del Norte, Marin ........................................ 1–01–2001 .. 9–21–2003 .. 3–21–2003 .. 11–21–2003 S1764 ........ Drought ............................................ 2 ..........VA ........................................ Highland, Chesapeake city (i) .................. 1–01–2002 .. 9–26–2003 .. 3–26–2003 .. 11–26–2003 S1765 ........ Drought, excessive heat .................. 2 ..........AR ........................................ (1) Baxter, Benton, Boone, Calhoun, Carroll, Clark, Clay, Cleburne, Cleveland, 

Columbia, Conway, Crawford, Dallas, Faulkner, Franklin, Fulton, Garland, Grant, Hempstead, Hot Spring, Howard, Izard, Johnson, Lafayette, Little River, Logan, Madison, Marion, Miller, Montgomery, Nevada, Newton, Perry, Pike, Polk, Pope, Pulaski, Saline, Scott, Searcy, Sebastian, Sevier, Sharp, Stone, Union, Van Buren, Washington, Yell.

(2) Arkansas, Ashley, Bradley, Chicot, 

Craighead, Crittenden, Cross, Desha, Drew, Greene, Independence, Jackson, Jefferson, Lawrence, Lee, Lincoln, Lonoke, Mississippi, Monroe, Ouachita, Phillips, Poinsett, Prairie, Randolph, St. Francis, White, Woodruff.

7–01–2002 .. 12–31–2002 4–03–2003 .. 12–03–2003 S1766 ........ (1) Drought ......................................

(2) Excessive rain ...........................

75 ..........

LA ........................................ ................................................................... 12–31–2002 4–03–2003 .. 12–03–2003 12–03–2003 S1766 ........ Excessive rain ................................. .......... 4 MO ....................................... ................................................................... 12–31–2002 4–03–2003 .. 12–03–2003 12–03–2003 S1766 ........ Drought ............................................ .......... 9 MS ....................................... ................................................................... 12–31–2002 4–03–2003 .. 12–03–2003 12–03–2003 S1766 ........ Excessive rain ................................. .......... 4 OK ........................................ ................................................................... 12–31–2002 4–03–2003 .. 12–03–2003 12–03–2003 S1766 ........ Drought ............................................ .......... 1 TX ........................................ ................................................................... 12–31–2002 4–03–2003 .. 12–03–2003 12–03–2003 S1766 ........ Drought ............................................ .......... 2 IL ......................................... Cass, De Witt, Mason, Moultrie, Pike, 

Stephenson, Winnebago.

6–01–2002 .. 10–09–2003 4–09–2003 .. 12–09–2003 S1767 ........ Drought ............................................ 7 23 
381 

MO ....................................... ................................................................... 6–01–2002 .. 10–09–2003 4–09–2003 .. 12–09–2003 S1767 ........ Drought ............................................ .......... 3 WI ........................................ ................................................................... 6–01–2002 .. 10–09–2003 4–09–2003 .. 12–09–2003 S1767 ........ Drought ............................................ .......... 3 TX ........................................ Bastrop, Brazos, Camp, Collin, Dallas, 

Denton, Ellis, Falls, Fayette, Freestone, Hill, Jackson, Kaufman, Lavaca, Lee, Limestone, Milam, Navarro, Rockwall, Washington, Williamson.

1–01–2002 .. 10–24–2003 4–24–2003 .. 12–26–2003 S1768 ........ Drought, excessive rain, heat ......... 21 49 

CA ........................................ Alpine, Amador, Sacramento, Yuba .......... 1–01–2001 .. 12–31–2002 4–28–2003 .. 12–29–2003 S1769 ........ Drought ............................................ 4 ..........CA ........................................ Lake ........................................................... 3–15–2002 .. 12–31–2002 4–28–2003 .. 12–29–2003 S1770 ........ Drought ............................................ 1 ..........CA ........................................ Tehama ..................................................... 12–13–2002 12–27–2002 4–30–2003 .. 12–30–2003 S1771 ........ Saturated ground, high wind .......... 1 6 CA ........................................ Sutter ........................................................ 12–13–2002 12–16–2002 4–30–2003 .. 12–30–2003 S1772 ........ Rain, wind ....................................... 1 6 CA ........................................ El Dorado, Placer ...................................... 1–01–2002 .. 12–31–2002 4–30–2003 .. 12–30–2003 S1773 ........ Drought ............................................ 2 ..........FL ........................................ Bay, Calhoun, Escambia, Gadsden, Gulf, 

Holmes, Jackson, Liberty, Okaloosa, Santa Rosa, Walton, Washington.

10–14–2002 10–29–2002 4–30–2003 .. 12–30–2003 S1774 ........ Exceptionally heavy rainfall from 

three frontal systems.

12 3 

AL ........................................ ................................................................... 10–14–2002 10–29–2002 4–30–2003 .. 12–30–2003 S1774 ........ Exceptionally heavy rainfall from 

three frontal systems.

.......... 5 

GA ........................................ ................................................................... 10–14–2002 10–29–2002 4–30–2003 .. 12–30–2003 S1774 ........ Exceptionally heavy rainfall from 

three frontal systems.

.......... 3 

TN ........................................ Fayette, Henry, Humphreys, Hickman, 

Lewis, Perry.

7–02–2002 .. 2–14–2003 .. 4–30–2003 .. 12–30–2003 S1775 ........ Drought, flooding, excessive rain ... 6 15 

KY ........................................ ................................................................... 7–02–2002 .. 2–14–2003 .. 4–30–2003 .. 12–30–2003 S1775 ........ Drought, flooding, excessive rain ... .......... 2 MS ....................................... ................................................................... 7–02–2002 .. 2–14–2003 .. 4–30–2003 .. 12–30–2003 S1775 ........ Drought, flooding, excessive rain ... .......... 2 WA ....................................... Okanogan .................................................. 5–01–2002 .. 10–30–2003 4–30–2003 .. 12–30–2003 S1776 ........ Drought ............................................ 1 7 WA ....................................... Grant, Yakima ........................................... 10–01–2001 10–30–2002 4–30–2003 .. 12–30–2003 S1777 ........ Adverse weather conditions, resulting in Western Yellow Blight. 2 12 CA ........................................ Alameda, Contra Costa, Sutter ................. 1–01–2002 .. 12–31–2002 5–01–2003 .. 1–02–2004 .. S1778 ........ Drought ............................................ 3 ..........WV ....................................... Barbour, Fayette, Hardy, Jefferson, Marion, Monongalia, Putnam, Raleigh, 

Summers, Wyoming.

1–01–2002 .. 11–19–2002 5–09–2003 .. 1–09–2004 .. S1779 ........ Drought ............................................ 10 ..........
382 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

NE ........................................ Adams, Arthur, Banner, Blaine, Box 

Butte, Boyd, Brown, Buffalo, Chase, Cherry, Cheyenne, Custer, Dawes, Dawson, Deuel, Dundy, Franklin, Frontier, Furnas, Garden, Garfield, Gosper, Grant, Greeley, Hall, Harlan, Hayes, Hitchcock, Holt, Hooker, Howard, Kearney, Keith, Keya Paha, Kimball, Lincoln, Logan, Loup, McPherson, Morrill, Nuckolls, Perkins, Phelps, Red Willow, Rock, Scotts Bluff, Sheridan, Sherman, Sioux, Thomas, Valley, Webster, Wheeler.

7–01–2002 .. 11–14–2003 5–14–2003 .. 1–14–2004 .. S1780 ........ Drought, extreme heat, grasshopper 

infestation, high winds.

53 9 

CO ....................................... ................................................................... 7–01–2002 .. 11–14–2003 5–14–2003 .. 1–14–2004 .. S1780 ........ Drought, extreme heat, grasshopper 

infestation, high winds.

.......... 5 

KS ........................................ ................................................................... 7–01–2002 .. 11–14–2003 5–14–2003 .. 1–14–2004 .. S1780 ........ Drought, extreme heat, grasshopper 

infestation, high winds.

.......... 8 

SD ........................................ ................................................................... 7–01–2002 .. 11–14–2003 5–14–2003 .. 1–14–2004 .. S1780 ........ Drought, extreme heat, grasshopper 

infestation, high winds.

.......... 7 

WY ....................................... ................................................................... 7–01–2002 .. 11–14–2003 5–14–2003 .. 1–14–2004 .. S1780 ........ Drought, extreme heat, grasshopper 

infestation, high winds.

.......... 3 

TX ........................................ Robertson, Van Zandt ............................... 1–01–2001 .. 2–12–2003 .. 5–22–2003 .. 1–22–2004 .. S1781 ........ Flooding, excessive temperatures ... 2 3 WA ....................................... Asotin, Chelan, Columbia, Douglas, Garfield, Grant, Klickitat, Lewis, Lincoln, 

Pend Oreille, Spokane, Stevens, Walla Walla, Whitman.

1–01–2002 .. 11–22–2003 5–22–2003 .. 1–22–2004 .. S1782 ........ Drought ............................................ 14 17 

ID ......................................... ................................................................... 1–01–2002 .. 11–22–2003 5–22–2003 .. 1–22–2004 .. S1782 ........ Drought ............................................ .......... 6 OR ....................................... ................................................................... 1–01–2002 .. 11–22–2003 5–22–2003 .. 1–22–2004 .. S1782 ........ Drought ............................................ .......... 7 WA ....................................... (1) Benton, Columbia, Franklin, Spokane, 

Walla Walla, Whatcom, Yakima;.

(2) Ferry, Yakima ......................................

1–01–2002 .. 11–22–2003 5–22–2003 .. 1–22–2004 .. S1783 ........ (1) Severe cold temperatures; ........

(2) Drought ......................................

8 17 

ID ......................................... ................................................................... 10–12–2002 11–06–2002 5–22–2003 .. 1–22–2004 .. S1783 ........ Severe cold ...................................... .......... 3 OR ....................................... ................................................................... 10–12–2002 11–06–2002 5–22–2003 .. 1–22–2004 .. S1783 ........ Severe cold ...................................... .......... 3 
383 

WI ........................................ Door, Kewaunee ......................................... 4–01–2002 .. 11–22–2003 5–22–2003 .. 1–22–2004 .. S1784 ........ Exceptionally cold, wet conditions 

in spring, followed by warmer and dryer conditions through the growing season.

2 2 

CA ........................................ Trinity ........................................................ 1–01–2002 .. 11–30–2002 6–03–2003 .. 2–03–2004 .. S1785 ........ Drought ............................................ 1 2 NC ....................................... Beaufort, Camden, Cartaret, Currituck, 

Hyde, New Hanover, Onslow, Pamlico, Pasquotank.

4–01–2002 .. 12–03–2003 6–03–2003 .. 2–03–2004 .. S1786 ........ (1) Excessive rainfall ......................

(2) Drought (New Hanover, Onslow 

Only).

9 15 

VA ........................................ ................................................................... 4–01–2002 .. 12–03–2003 6–03–2003 .. 2–03–2004 .. S1786 ........ Excessive rainfall ............................ .......... 3 WI ........................................ Kenosha, Racine, Rock, Walworth ............ 6–01–2002 .. 12–03–2003 6–03–2003 .. 2–03–2004 .. S1787 ........ Drought ............................................ 4 5 IL ......................................... ................................................................... 6–01–2002 .. 12–03–2003 6–03–2003 .. 2–03–2004 .. S1787 ........ Drought ............................................ .......... 4 HI ......................................... Hawaii ....................................................... 1–01–2001 .. 12–31–2002 6–03–2003 .. 2–03–2004 .. S1788 ........ Drought ............................................ 1 ..........WA ....................................... Clark, Cowlitz, Skamania, Wahkiakum ..... 6–01–2002 .. 11–30–2002 6–23–2003 .. 2–23–2004 .. S1789 ........ Cool, wet weather, followed by hot, 

dry weather.

4 4 

OR ....................................... ................................................................... 6–01–2002 .. 11–30–2002 6–23–2003 .. 2–23–2004 .. S1789 ........ Cool, wet weather, followed by hot, 

dry weather.

.......... 4 

AR ........................................ Stone ......................................................... 3–25–2003 .. 3–25–2003 .. 6–27–2003 .. 2–27–2004 .. S1790 ........ Hail .................................................. 1 6 UT ........................................ Entire State ............................................... 1–01–2003 .. 12–27–2003 6–27–2003 .. 2–27–2004 .. S1791 ........ Drought: Very low snow pack combined with low soil moisture. 29 ..........AZ ........................................ ................................................................... 1–01–2003 .. 12–27–2003 6–27–2003 .. 2–27–2004 .. S1791 ........ Drought: Very low snow pack combined with low soil moisture. .......... 4 CO ....................................... ................................................................... 1–01–2003 .. 12–27–2003 6–27–2003 .. 2–27–2004 .. S1791 ........ Drought: Very low snow pack combined with low soil moisture. .......... 8 ID ......................................... ................................................................... 1–01–2003 .. 12–27–2003 6–27–2003 .. 2–27–2004 .. S1791 ........ Drought: Very low snow pack combined with low soil moisture. .......... 4 NM ....................................... ................................................................... 1–01–2003 .. 12–27–2003 6–27–2003 .. 2–27–2004 .. S1791 ........ Drought: Very low snow pack combined with low soil moisture. .......... 1 NV ........................................ ................................................................... 1–01–2003 .. 12–27–2003 6–27–2003 .. 2–27–2004 .. S1791 ........ Drought: Very low snow pack combined with low soil moisture. .......... 3 WY ....................................... ................................................................... 1–01–2003 .. 12–27–2003 6–27–2003 .. 2–27–2004 .. S1791 ........ Drought: Very low snow pack combined with low soil moisture. .......... 3 TX ........................................ Waller ........................................................ 10–01–2002 11–30–2002 6–27–2003 .. 2–27–2004 .. S1792 ........ Excessive rain ................................. 1 6 TX ........................................ San Saba .................................................. 3–29–2003 .. 3–29–2003 .. 6–27–2003 .. 2–27–2004 .. S1793 ........ Freeze .............................................. 1 7 TX ........................................ Calhoun, Collingsworth, Concho, 

Glasscock, Hardeman, Howard, Jackson, Mitchell, Tom Green, Victoria, Wilbarger.

1–01–2002 .. 12–27–2003 6–27–2003 .. 2–27–2004 .. S1794 ........ Drought, low humidity ..................... 11 35 

OK ........................................ ................................................................... 1–01–2002 .. 12–27–2003 6–27–2003 .. 2–27–2004 .. S1794 ........ Drought, low humidity ..................... .......... 4 TX ........................................ Martin ........................................................ 1–01–2002 .. 12–27–2003 6–27–2003 .. 2–27–2004 .. S1795 ........ Drought, high winds ....................... 1 7 CA ........................................ San Diego .................................................. 11–25–2002 1–08–2003 .. 7–01–2003 .. 3–01–2004 .. S1796 ........ Damaging Santa Ana Winds ........... 1 3 
384 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

CO ....................................... Baca, Bent, Elbert, Kiowa, Lincoln, 

Prowers.

9–01–2000 .. 1–15–2004 .. 7–15–2003 .. 3–15–2004 .. S1797 ........ Drought ............................................ 6 10 

KS ........................................ ................................................................... 9–01–2000 .. 1–15–2004 .. 7–15–2003 .. 3–15–2004 .. S1797 ........ Drought ............................................ .......... 4 NM ....................................... ................................................................... 9–01–2000 .. 1–15–2004 .. 7–15–2003 .. 3–15–2004 .. S1797 ........ Drought ............................................ .......... 1 OK ........................................ ................................................................... 9–01–2000 .. 1–15–2004 .. 7–15–2003 .. 3–15–2004 .. S1797 ........ Drought ............................................ .......... 1 TX ........................................ Williamson ................................................. 7–01–2002 .. 12–31–2002 7–15–2003 .. 3–15–2004 .. S1798 ........ Excessive rain, flooding .................. 1 6 CA ........................................ Glenn ......................................................... 12–13–2002 12–27–2002 8–01–2003 .. 4–01–2004 .. S1799 ........ Rain, saturated soil, high winds .... 1 3 CA ........................................ Contra Costa ............................................. 3–16–2003 .. 5–15–2003 .. 8–06–2003 .. 4–06–2004 .. S1800 ........ (1) Hailstorm ...................................

(2) Rain ...........................................

1 

VA ........................................ Amelia ....................................................... 5–09–2003 .. 5–09–2003 .. 8–29–2003 .. 4–29–2004 .. S1801 ........ Tornado, excessive rain, large hail 1 6 OH ....................................... Adams, Allen, Ashland, Ashtabula, Athens, Auglaize, Brown, Butler, Carroll, 

Clark, Clermont, Clinton, Columbiana, Coshocton, Crawford, Cuyahoga, Darke, Delaware, Erie, Fairfield, Fayette, Franklin, Gallia, Geauga, Greene, Hamilton, Hancock, Hardin, Highland, Hocking, Holmes, Huron, Jackson, Knox, Lake, Lawrence, Licking, Logan, Lorain, Mahoning, Marion, Medina, Meigs, Mercer, Miami, Montgomery, Morgan, Morrow, Muskingum, Paulding, Perry, Pickaway, Pike, Portage, Preble, Putnam, Richland, Ross, Sandusky, Scioto, Shelby, Summit, Trumbull, Tuscarawas, Union, Van Wert, Vinton, Warren, Washington, Wyandot.

5–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1802 ........ Excessive rain, flooding, hail, high 

wind, tornado damage.

70 14 

IN ......................................... ................................................................... 5–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1802 ........ Excessive rain, flooding, hail, high 

wind, tornado damage.

.......... 8 

KY ........................................ ................................................................... 5–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1802 ........ Excessive rain, flooding, hail, high 

wind, tornado damage.

.......... 9 
385 

PA ........................................ ................................................................... 5–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1802 ........ Excessive rain, flooding, hail, high 

wind, tornado damage.

.......... 5 

WV ....................................... ................................................................... 5–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1802 ........ Excessive rain, flooding, hail, high 

wind, tornado damage.

.......... 8 

AZ ........................................ Entire State ............................................... 1–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1803 ........ Drought ............................................ 15 ..........CA ........................................ ................................................................... 1–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1803 ........ Drought ............................................ .......... 3 CO ....................................... ................................................................... 1–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1803 ........ Drought ............................................ .......... 1 NM ....................................... ................................................................... 1–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1803 ........ Drought ............................................ .......... 6 NV ........................................ ................................................................... 1–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1803 ........ Drought ............................................ .......... 2 UT ........................................ ................................................................... 1–01–2003 .. 2–29–2004 .. 8–29–2003 .. 4–29–2004 .. S1803 ........ Drought ............................................ .......... 3 CA ........................................ Merced ....................................................... 4–21–2003 .. 4–21–2003 .. 9–11–2003 .. 5–11–2004 .. S1804 ........ Hail .................................................. 1 7 VA ........................................ Campbell, Charlotte, Culpeper, Halifax, 

Page, Rappahannock, Russell, Shenandoah.

1–01–2003 .. 3–22–2004 .. 9–22–2003 .. 5–24–2004 .. S1805 ........ Excessive rainfall ............................ 8 24 

NC ....................................... Campbell, Charlotte, Culpeper, Halifax, 

Page, Rappahannock, Russell, Shenandoah.

1–01–2003 .. 3–22–2004 .. 9–22–2003 .. 5–24–2004 .. S1805 ........ Excessive rainfall ............................ .......... 3 

WV ....................................... Campbell, Charlotte, Culpeper, Halifax, 

Page, Rappahannock, Russell, Shenandoah.

1–01–2003 .. 3–22–2004 .. 9–22–2003 .. 5–24–2004 .. S1805 ........ Excessive rainfall ............................ .......... 1 

WI ........................................ Barron, Brown, Buffalo, Burnett, Chippewa, Clark, Dunn, Eau Claire, Forest, 

Florence, Jackson, Langlade, Lincoln, Marathon, Marinette, Marquette, Menominee, Oconto, Oneida, Outagamie, Pepin, Pierce, Polk, Portage, Price, Rusk, St. Croix, Sawyer, Shawano, Taylor, Vilas, Washburn, Waupaca, Wood.

7–01–2002 .. 3–22–2004 .. 9–22–2003 .. 5–24–2004 .. S1806 ........ Exceptionally cold temperatures, 

lack of snow, very deep frost, drought.

34 16 

MI ........................................ ................................................................... 7–01–2002 .. 3–22–2004 .. 9–22–2003 .. 5–24–2004 .. S1806 ........ Exceptionally cold temperatures, 

lack of snow, very deep frost, drought.

.......... 4 

MN ....................................... ................................................................... 7–01–2002 .. 3–22–2004 .. 9–22–2003 .. 5–24–2004 .. S1806 ........ Exceptionally cold temperatures, 

lack of snow, very deep frost, drought.

.......... 7 

VA ........................................ Appomattox, Augusta, Buckingham, 

Nottoway, Patrick, Pittsylvania, Prince Edward.

2–01–2003 .. 3–29–2004 .. 9–29–2003 .. 6–01–2004 .. S1807 ........ Excessive rainfall ............................ 7 21 

NC ....................................... ................................................................... 2–01–2003 .. 3–29–2004 .. 9–29–2003 .. 6–01–2004 .. S1807 ........ Excessive rainfall ............................ .......... 4 WV ....................................... ................................................................... 2–01–2003 .. 3–29–2004 .. 9–29–2003 .. 6–01–2004 .. S1807 ........ Excessive rainfall ............................ .......... 1 VA ........................................ Virginia Beach (I), Washington ................ 7–01–2002 .. 3–01–2003 .. 9–30–2003 .. 6–01–2004 .. S1808 ........ Drought ............................................ 2 7 
386 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTAL—SECRETARIAL—Continued 

[Fiscal Year 2003—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

NC ....................................... Virginia Beach (I), Washington ................ 7–01–2002 .. 3–01–2003 .. 9–30–2003 .. 6–01–2004 .. S1808 ........ Drought ............................................ .......... 1 TN ........................................ Virginia Beach (I), Washington ................ 7–01–2002 .. 3–01–2003 .. 9–30–2003 .. 6–01–2004 .. S1808 ........ Drought ............................................ .......... 2 OK ........................................ Alfalfa, Atoka, Beaver, Beckham, Blaine, 

Bryan, Caddo, Canadian, Carter, Cimarron, Cleveland, Coal., Comanche, Cotton, Creek, Custer, Dewey, Ellis, Garfield, Garvin, Grady, Grant, Greer, Harmon, Harper, Hughes, Jackson, Johnston, Kay, Kingfisher, Kiowa, L.

7–01–2003 .. 3–30–2004 .. 9–30–2003 .. 6–01–2004 .. S1809 ........ Drought ............................................ 59 10 

CO ....................................... ................................................................... 7–01–2003 .. 3–30–2004 .. 9–30–2003 .. 6–01–2004 .. S1809 ........ Drought ............................................ .......... 1 KS ........................................ ................................................................... 7–01–2003 .. 3–30–2004 .. 9–30–2003 .. 6–01–2004 .. S1809 ........ Drought ............................................ .......... 11 NM ....................................... ................................................................... 7–01–2003 .. 3–30–2004 .. 9–30–2003 .. 6–01–2004 .. S1809 ........ Drought ............................................ .......... 1 TX ........................................ ................................................................... 7–01–2003 .. 3–30–2004 .. 9–30–2003 .. 6–01–2004 .. S1809 ........ Drought ............................................ .......... 18 

TOTAL ACTIVE ........ ................................................................... ...................... ...................... ...................... ...................... ................... .......................................................... 2309 2029 
387 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

AR .................................... Arkansas, Ashley, Clay, 

Cleburne, Conway, Craighead, Crittenden, Cross, Faulkner, Greene, Hempstead, Independence, Jackson, Jefferson, Lafayette, Lawrence, Lee, Little River, Lonoke, Mississippi, Monroe, Nevada, Perry, Phillips, Poinsett, Polk, Pope, Prairie, Pulaski, Randolph, Sevier, Sharp, St. Francis, Stone, White, Woodruff.

5–01–2003 ...... 5–01–2003 ...... 10–10–2003 .... 6–10–2004 ...... S1810 .......... Excessive rain, flash flooding, hail, 

tornadoes.

36 27 

LA .................................... .................................................... 5–01–2003 ...... 5–31–2003 ...... 10–10–2003 .... 6–10–2004 ...... S1810 .......... Excessive rain, flash flooding, hail, 

tornadoes.

.......... 5 

MS ................................... .................................................... 5–01–2003 ...... 5–31–2003 ...... 10–10–2003 .... 6–10–2004 ...... S1810 .......... Excessive rain, flash flooding, hail, 

tornadoes.

.......... 4 

MO ................................... .................................................... 5–01–2003 ...... 5–31–2003 ...... 10–10–2003 .... 6–10–2004 ...... S1810 .......... Excessive rain, flash flooding, hail, 

tornadoes.

.......... 5 

OK .................................... .................................................... 5–01–2003 ...... 5–31–2003 ...... 10–10–2003 .... 6–10–2004 ...... S1810 .......... Excessive rain, flash flooding, hail, 

tornadoes.

.......... 2 

TN .................................... .................................................... 5–01–2003 ...... 5–31–2003 ...... 10–10–2003 .... 6–10–2004 ...... S1810 .......... Excessive rain, flash flooding, hail, 

tornadoes.

.......... 4 

TX .................................... .................................................... 5–01–2003 ...... 5–31–2003 ...... 10–10–2003 .... 6–10–2004 ...... S1810 .......... Excessive rain, flash flooding, hail, 

tornadoes.

.......... 1 

KS .................................... (1) Dickinson, Jewell, Republic

(2) Morton ..................................

1–01–2003 ...... 4–20–2004 ...... 10–20–2003 .... 6–21–2004 ...... S1811 .......... (1) Tornado, hail, high winds, lightning, excessive rain, flash flooding, flooding.

(2) Excessive heat, drought, high 

winds.

3 14 
388 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

CO .................................... .................................................... 1–01–2003 ...... 4–20–2004 ...... 10–20–2003 .... 6–21–2004 ...... S1811 .......... (1) Tornado, hail, high winds, lightning, excessive rain, flash flooding, flooding.

(2) Excessive heat, drought, high 

winds.

.......... 1 

NE .................................... .................................................... 1–01–2003 ...... 4–20–2004 ...... 10–20–2003 .... 6–21–2004 ...... S1811 .......... (1) Tornado, hail, high winds, lightning, excessive rain, flash flooding, flooding.

(2) Excessive heat, drought, high 

winds.

.......... 4 

OK .................................... .................................................... 1–01–2003 ...... 4–20–2004 ...... 10–20–2003 .... 6–21–2004 ...... S1811 .......... (1) Tornado, hail, high winds, lightning, excessive rain, flash flooding, flooding.

(2) Excessive heat, drought, high 

winds.

.......... 2 

CA .................................... Alameda, Contra Costa, Fresno, 

Glenn, Kern, Madera, Sacramento, San Joaquin, Tulare, Yuba.

1–01–2003 ...... 5–31–2003 ...... 10–23–2003 .... 6–23–2004 ...... S1812 .......... Excessive rain, wheat stripe rust ....... 10 30 

NV .................................... Entire State (17 counties) ......... 1–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1813 .......... Drought, insect infestation ................. 17 ..........AZ .................................... .................................................... 1–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1813 .......... Drought, insect infestation ................. .......... 1 CA .................................... .................................................... 1–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1813 .......... Drought, insect infestation ................. .......... 10 ID ..................................... .................................................... 1–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1813 .......... Drought, insect infestation ................. .......... 3 OR .................................... .................................................... 1–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1813 .......... Drought, insect infestation ................. .......... 3 UT .................................... .................................................... 1–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1813 .......... Drought, insect infestation ................. .......... 7 
389 

IA ..................................... Adair, Adams, Allamakee, Audubon, Benton, Black Hawk, 

Bremer, Buchanan, Buena Vista, Calhoun, Carroll, Cass, Cherokee, Chickasaw, Clarke, Clay, Clayton, Clinton, Crawford, Dallas, Davis, Decatur, Dickinson, Dubuque, Floyd, Franklin, Fremont, Grundy, Guthrie, Harrison, Henry, Howard, Humboldt, Ida, Jefferson, Johnson, Jones, Keokuk, Lee, Linn, Louisa, Lucas, Lyon, Madison, Marion, Mitchell, Monona, Monroe, Montgomery, O’Brien, Page, Pocahontas, Polk, Pottawattamie, Ringgold, Sac, Shelby, Story, Taylor, Union, Van Buren, Wapello, Warren, Washington, Wayne, Winnebago, Winneshiek, Worth.

7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1814 .......... .............................................................. 68 31 

IL ..................................... .................................................... 7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1814 .......... Drought, related impacts .................... .......... 7 MN ................................... .................................................... 7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1814 .......... Drought, related impacts .................... .......... 8 MO ................................... .................................................... 7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1814 .......... Drought, related impacts .................... .......... 9 NE .................................... .................................................... 7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1814 .......... Drought, related impacts .................... .......... 7 SD .................................... .................................................... 7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1814 .......... Drought, related impacts .................... .......... 2 WI .................................... .................................................... 7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1814 .......... Drought, related impacts .................... .......... 3 
390 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

MN ................................... Aitkin, Anoka, Becker, Beltrami, 

Benton, Big Stone, Carlton, Cass, Chippewa, Chisago, Clearwater, Cook, Crow Wing, Dakota, Dodge, Douglas, Faribault, Fillmore, Freeborn, Goodhue, Hennepin, Houston, Hubbard, Isanti, Itasca, Kanabec, Kandiyohi, Kittson, Lac Qui Parle, Lake, Lincoln, Mahnomen, Meeker, Mille Lacs, Morrison, Mower, Nicollet, Olmsted, Otter Tail, Pine, Pipestone, Pope, Ramsey, Red Lake, Renville, Rice, St. Louis, Scott, Sherburne, Sibley, Stearns, Steele, Swift, Todd, Traverse, Wabasha, Wadena, Waseca, Washington, Winona, Wright, Yellow Medicine.

7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1815 .......... Drought ................................................ 62 21 

IA ..................................... .................................................... 7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1815 .......... Drought ................................................ .......... 7 ND .................................... .................................................... 7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1815 .......... Drought ................................................ .......... 3 SD .................................... .................................................... 7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1815 .......... Drought ................................................ .......... 6 WI .................................... .................................................... 7–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1815 .......... Drought ................................................ .......... 10 WY ................................... Lincoln, Sublette, Sweetwater ... 1–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1816 .......... Drought ................................................ 3 4 CO .................................... .................................................... 1–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1816 .......... Drought ................................................ .......... 4 ID ..................................... .................................................... 1–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1816 .......... Drought ................................................ .......... 3 UT .................................... .................................................... 1–01–2003 ...... 4–23–2004 ...... 10–23–2003 .... 6–23–2004 ...... S1816 .......... Drought ................................................ .......... 3 CA .................................... El Dorado ................................... 4–01–2003 ...... 5–15–2003 ...... 10–30–2003 .... 6–30–2004 ...... S1817 .......... Excessive rain, hail, freezing temperatures. 1 3 CA .................................... Nevada ....................................... 3–01–2003 ...... 5–15–2003 ...... 10–30–2003 .... 6–30–2004 ...... S1817 .......... Rain, hail, freezing temperatures ....... 1 3 CA .................................... Sutter ......................................... 4–04–2003 ...... 5–09–2003 ...... 10–30–2003 .... 6–30–2004 ...... S1817 .......... Hail ...................................................... 1 2 
391 

CA .................................... Yolo ............................................ 4–01–2003 ...... 5–15–2003 ...... 10–30–2003 .... 6–30–2004 ...... S1817 .......... Freezing temperatures ......................... 1 3 NV .................................... .................................................... 3–01–2003 ...... 5–15–2003 ...... 10–30–2003 .... 6–30–2004 ...... S1817 .......... Rain, hail, freezing temperatures ....... .......... 1 NV .................................... .................................................... 4–01–2003 ...... 5–15–2003 ...... 10–30–2003 .... 6–30–2004 ...... S1817 .......... Excessive rain, hail, freezing temperatures. .......... 1 CA .................................... Butte .......................................... 3–01–2003 ...... 5–14–2003 ...... 10–30–2003 .... 6–30–2004 ...... S1818 .......... Spring rains, wheat stripe rust .......... 1 6 CA .................................... Merced ....................................... 4–01–2003 ...... 5–14–2003 ...... 10–30–2003 .... 6–30–2004 ...... S1818 .......... Spring rains, cool temperatures, 

wheat stripe rust.

1 7 

CA .................................... Solano ........................................ 4–01–2003 ...... 5–31–2003 ...... 10–30–2003 .... 6–30–2004 ...... S1818 .......... Spring rains, wheat stripe rust .......... 1 5 CA .................................... Stanislaus .................................. 4–01–2003 ...... 5–14–2003 ...... 10–30–2003 .... 6–30–2004 ...... S1818 .......... Rains, wheat stripe rust ..................... 1 3 IN ..................................... Union ......................................... 6–11–2003 ...... 6–16–2003 ...... 11–04–2003 .... 7–06–2004 ...... S1819 .......... Excessive rain, flooding ...................... 1 3 OH .................................... .................................................... 6–11–2003 ...... 6–16–2003 ...... 11–04–2003 .... 7–06–2004 ...... S1819 .......... Excessive rain, flooding ...................... .......... 2 VA .................................... Bedford, Mecklenburg, Rockingham, Scott. 1–01–2003 ...... 5–04–2004 ...... 11–04–2003 .... 7–06–2004 ...... S1820 .......... Excessive rainfall ................................ 4 20 NC .................................... Bedford, Mecklenburg, Rockingham, Scott. 1–01–2003 ...... 5–04–2004 ...... 11–04–2003 .... 7–06–2004 ...... S1820 .......... Excessive rainfall ................................ .......... 3 TN .................................... Bedford, Mecklenburg, Rockingham, Scott. 1–01–2003 ...... 5–04–2004 ...... 11–04–2003 .... 7–06–2004 ...... S1820 .......... Excessive rainfall ................................ .......... 3 WV ................................... Bedford, Mecklenburg, Rockingham, Scott. 1–01–2003 ...... 5–04–2004 ...... 11–04–2003 .... 7–06–2004 ...... S1820 .......... Excessive rainfall ................................ .......... 2 TX .................................... Lamb .......................................... 6–05–2003 ...... 6–20–2003 ...... 11–04–2003 .... 7–06–2004 ...... S1821 .......... (1) Excessive rain, hail, high winds, 

sand, static electricity;.

(2) Excessive rain, hail, high wind, 

tornado;.

1 7 

TX .................................... Calhoun, Coke, Foard, Gillespie, 

Karnes, Matagorda, Runnels, Sterling, Wharton.

1–01–2003 ...... 5–06–2004 ...... 11–04–2003 .... 7–06–2004 ...... S1822 .......... Drought ................................................ 9 36 

TX .................................... Bailey ......................................... 6–03–2003 ...... 6–20–2003 ...... 11–04–2003 .... 7–06–2004 ...... S1823 .......... Excessive rain, flash flooding, hail, 

high winds, lightning.

1 4 

NM ................................... .................................................... 6–03–2003 ...... 6–20–2003 ...... 11–04–2003 .... 7–06–2004 ...... S1823 .......... Excessive rain, flash flooding, hail, 

high winds, lightning.

.......... 2 

TX .................................... Hale ........................................... 5–20–2003 ...... 6–25–2003 ...... 11–04–2003 .... 7–06–2004 ...... S1824 .......... Flooding, hail, high winds .................. 1 7 TX .................................... Hall ............................................ 6–22–2003 ...... 6–22–2003 ...... 11–04–2003 .... 7–06–2004 ...... S1825 .......... Excessive rain, hail, high winds, 

lightning.

1 6 

NM ................................... Entire State (except Los Alamos 

County).

1–01–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1826 .......... Drought, excessive heat ...................... 32 1 

AZ .................................... .................................................... 1–01–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1826 .......... Drought, excessive heat ...................... .......... 3 CO .................................... .................................................... 1–01–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1826 .......... Drought, excessive heat ...................... .......... 7 OK .................................... .................................................... 1–01–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1826 .......... Drought, excessive heat ...................... .......... 1 TX .................................... .................................................... 1–01–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1826 .......... Drought, excessive heat ...................... .......... 16 UT .................................... .................................................... 1–01–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1826 .......... Drought, excessive heat ...................... .......... 1 
392 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

LA .................................... Acadia, Beauregard, Calcasieu, 

Cameron, Evangeline, Lafayette, Rapides, St. Landry, St. Martin.

6–01–2003 ...... 7–31–2003 ...... 11–04–2003 .... 7–06–2004 ...... S1827 .......... Excessive rain ..................................... 9 13 

TX .................................... .................................................... 6–01–2003 ...... 7–31–2003 ...... 11–04–2003 .... 7–06–2004 ...... S1827 .......... Excessive rain ..................................... .......... 2 OR .................................... Baker, Gilliam ............................ 10–01–2001 .... 5–06–2004 ...... 11–04–2003 .... 7–06–2004 ...... S1828 .......... Drought ................................................ 2 8 ID ..................................... .................................................... 10–01–2001 .... 5–06–2004 ...... 11–04–2003 .... 7–06–2004 ...... S1828 .......... Drought ................................................ .......... 2 WA ................................... .................................................... 10–01–2001 .... 5–06–2004 ...... 11–04–2003 .... 7–06–2004 ...... S1828 .......... Drought ................................................ .......... 1 TX .................................... Hockley, Lubbock ....................... 6–01–2003 ...... 6–30–2003 ...... 11–05–2003 .... 7–06–2004 ...... S1829 .......... Excessive rain, hail, high wind .......... 2 10 TX .................................... Bexar .......................................... 3–01–2003 ...... 5–27–2003 ...... 11–05–2003 .... 7–06–2004 ...... S1830 .......... Drought, high temperatures ................ 1 7 TX .................................... Crosby ........................................ 6–04–2003 ...... 6–20–2003 ...... 11–05–2003 .... 7–06–2004 ...... S1831 .......... Excessive rain, flash flooding, hail, 

high winds, lightning.

1 8 

TX .................................... Briscoe ....................................... 6–01–2003 ...... 5–06–2004 ...... 11–06–2003 .... 7–06–2004 ...... S1832 .......... Drought, high winds, static electricity, 

heat.

1 6 

TX .................................... Parmer ....................................... 5–01–2003 ...... 6–30–2003 ...... 11–06–2003 .... 7–06–2004 ...... S1833 .......... Excessive rain, hail, high winds, cool 

weather.

1 4 

NM ................................... .................................................... 5–01–2003 ...... 6–30–2003 ...... 11–06–2003 .... 7–06–2004 ...... S1833 .......... Excessive rain, hail, high winds, cool 

weather.

.......... 1 

TX .................................... Deaf Smith ................................ 6–01–2003 ...... 6–30–2003 ...... 11–06–2003 .... 7–06–2004 ...... S1834 .......... Hail, tornado ....................................... 1 5 NM ................................... .................................................... 6–01–2003 ...... 6–30–2003 ...... 11–06–2003 .... 7–06–2004 ...... S1834 .......... Hail, tornado ....................................... .......... 2 NY .................................... Seneca ....................................... 4–03–2003 ...... 4–04–2003 ...... 11–10–2003 .... 7–12–2004 ...... S1835 .......... Excessive rain, ice, high winds .......... 1 6 NY .................................... Wayne ........................................ 4–04–2003 ...... 4–04–2003 ...... 11–10–2003 .... 7–12–2004 ...... S1835 .......... Ice Storm ............................................. 1 1 IN ..................................... Bartholomew, Brown, Clark, 

Daviess, Dearborn, Decatur, Dubois, Franklin, Gibson, Jackson, Jefferson, Jennings, Knox, Martin, Monroe, Morgan, Ohio, Orange, Owen, Perry, Pike, Posey, Ripley, Scott, Spencer, Switzerland, Vanderburgh, Warrick, Washington.

4–01–2003 ...... 7–15–2003 ...... 11–13–2003 .... 7–13–2004 ...... S1836 .......... Excessive rainfall, cool temperatures 29 15 

IL ..................................... .................................................... 4–01–2003 ...... 7–15–2003 ...... 11–13–2003 .... 7–13–2004 ...... S1836 .......... Excessive rainfall, cool temperatures .......... 5 KY .................................... .................................................... 4–01–2003 ...... 7–15–2003 ...... 11–13–2003 .... 7–13–2004 ...... S1836 .......... Excessive rainfall, cool temperatures .......... 12 
393 

OH .................................... .................................................... 4–01–2003 ...... 7–15–2003 ...... 11–13–2003 .... 7–13–2004 ...... S1836 .......... Excessive rainfall, cool temperatures .......... 2 MO ................................... Andrew, Atchison, Barton, 

Bates, Benton, Buchanan, Caldwell, Carroll, Cass, Cedar, Chariton, Clay, Clinton, Cooper, Daviess , DeKalb, Gentry, Grundy, Harrison, Henry, Hickory, Holt, Jackson, Johnson, Lafayette, Linn, Livingston, Mercer, Morgan, Nodaway, Pettis, Platte, Putnam, Ray, Saline, St. Clair, Sullivan, Vernon, Worth.

1–01–2003 ...... 5–13–2004 ...... 11–13–2003 .... 7–13–2004 ...... S1837 .......... Drought ................................................ 39 13 

IA ..................................... .................................................... 1–01–2003 ...... 5–13–2004 ...... 11–13–2003 .... 7–13–2004 ...... S1837 .......... Drought ................................................ .......... 7 KS .................................... .................................................... 1–01–2003 ...... 5–13–2004 ...... 11–13–2003 .... 7–13–2004 ...... S1837 .......... Drought ................................................ .......... 9 NE .................................... .................................................... 1–01–2003 ...... 5–13–2004 ...... 11–13–2003 .... 7–13–2004 ...... S1837 .......... Drought ................................................ .......... 3 TX .................................... Cochran ..................................... 6–03–2003 ...... 6–23–2003 ...... 11–13–2003 .... 7–13–2004 ...... S1838 .......... Excessive rain, hail, high winds, 

lightning, tornado.

1 5 

NM ................................... .................................................... 6–03–2003 ...... 6–23–2003 ...... 11–13–2003 .... 7–13–2004 ...... S1838 .......... Excessive rain, hail, high winds, 

lightning, tornado.

.......... 2 

TX .................................... Motley ........................................ 6–22–2003 ...... 6–22–2003 ...... 11–13–2003 .... 7–13–2004 ...... S1839 .......... Excessive rain, hail, high winds, static electricity. 1 7 AR .................................... Lawrence .................................... 9–01–2003 ...... 9–08–2003 ...... 11–21–2003 .... 7–21–2004 ...... S1840 .......... Excessive rain, flash flooding ............. 1 5 CA .................................... Kings .......................................... 4–01–2003 ...... 5–14–2003 ...... 11–21–2003 .... 7–21–2004 ...... S1841 .......... Excessive rain, wheat stripe rust ....... 1 5 CA .................................... Tehama ...................................... 4–01–2003 ...... 5–09–2003 ...... 11–21–2003 .... 7–21–2004 ...... S1842 .......... (1) Storms ...........................................

(2) Storms with hail, extended wet 

periods, below average temperatures-causing wheat stripe rust.

1 6 

CO .................................... Alamosa, Archuletta, Chaffee, 

Conejos, Costilla, Crowley, Custer, Dolores, Fremont, Garfield, Hinsdale, Huerfano, Lake, La Plata, Las Animas Mesa, Mineral, Moffat, Montezuma, Otero, Pueblo, Rio Blanco, Rio Grande, Routt, Saguache, San Miguel.

1–31–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1843 .......... Drought, insect infestation ................. 26 17 

AZ .................................... .................................................... 1–31–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1843 .......... Drought, insect infestation ................. .......... 1 NM ................................... .................................................... 1–31–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1843 .......... Drought, insect infestation ................. .......... 5 
394 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

UT .................................... .................................................... 1–31–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1843 .......... Drought, insect infestation ................. .......... 4 WY ................................... .................................................... 1–31–2003 ...... 5–21–2004 ...... 11–21–2003 .... 7–21–2004 ...... S1843 .......... Drought, insect infestation ................. .......... 2 SD .................................... Beadle, Bennett, Bon Homme, 

Brule, Buffalo, Butte, Campbell, Charles Mix, Corson, Deuel, Dewey, Grant, Gregory, Haakon, Hamlin, Hand, Harding, Hughes, Hyde, Jackson, Jones, Meade, Mellette, Perkins, Potter, Shannon, Spink, Stanley, Sully, Todd, Tripp, Walworth, Ziebach.

1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1844 .......... Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

33 22 

MN ................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1844 .......... Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

.......... 4 

MT .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1844 .......... Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

.......... 2 

ND .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1844 .......... Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

.......... 5 

NE .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1844 .......... Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

.......... 6 

WY ................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1844 .......... Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

.......... 1 
395 

SD .................................... Brookings, Codington, Custer, 

Fall River, Faulk, Jerauld, Lyman, Pennington.

1–01–2003 ...... continuing ....... 12–11–2003 .... 8–11–2004 ...... S1844, 

Amendment 1.

Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

8 2 

MN ................................... .................................................... 1–01–2003 ...... continuing ....... 12–11–2003 .... 8–11–2004 ...... S1844, 

Amendment 1.

Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

.......... 1 

NE .................................... .................................................... 1–01–2003 ...... continuing ....... 12–11–2003 .... 8–11–2004 ...... S1844, 

Amendment 1.

Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

.......... 1 

WY ................................... .................................................... 1–01–2003 ...... continuing ....... 12–11–2003 .... 8–11–2004 ...... S1844, 

Amendment 1.

Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

.......... 2 

SD .................................... Aurora, Clark ............................. 1–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1844, 

Amendment 2.

Extreme heat, high winds, severe 

storms, significantly below normal precipitation (drought) resulting in numerous prairie and forest fires.

2 1 

NE .................................... (1) Antelope, Cedar, Cuming, 

Dixon, Madison, Stanton, Wayne.

(2) Burt, Knox ............................(3) Dakota .................................(4) Pierce ...................................

7–01–2002 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1845 .......... Drought, high temperatures, grasshopper infestation.

(2) Drought, high temperatures ..........(3)(a) Drought; (b) Continuing rain ....(4)(a) Drought, high temperatures, 

grasshopper infestation; (b) High winds.

11 3 

IA ..................................... .................................................... 7–01–2002 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1845 .......... Drought, high temperatures, grasshopper infestation.

(2) Drought, high temperatures ..........(3)(a) Drought; (b) Continuing rain ....(4)(a) Drought, high temperatures, 

grasshopper infestation; (b) High winds.

.......... 2 
396 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

OR .................................... .................................................... 7–01–2002 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1845 .......... Drought, high temperatures, grasshopper infestation.

(2) Drought, high temperatures ..........(3)(a) Drought; (b) Continuing rain ....(4)(a) Drought, high temperatures, 

grasshopper infestation; (b) High winds.

.......... 5 

ID ..................................... Bannock, Bear Lake, Benewah, 

Bingham, Blaine, Bonneville, Butte, Camas, Caribou, Cassia, Clark, Clearwater, Custer, Elmore, Franklin, Fremont, Idaho, Jefferson, Kootenai, Lemhi, Lewis, Lincoln, Madison, Nez Perce, Oneida, Owyhee, Payette, Power, Teton, Twin Falls.

1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1846 .......... (1) Drought ..........................................

(2) Frost/Freeze ...................................(3) Inadequate moisture during growing season.(4) Excessive heat ...............................(5) Insect infestation ..........................(6) Hail ................................................

30 13 

MT .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1846 .......... (1) Drought ..........................................

(2) Frost/Freeze ...................................(3) Inadequate moisture during growing season.(4) Excessive heat ...............................(5) Insect infestation ..........................(6) Hail ................................................

.......... 6 

NV .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1846 .......... (1) Drought ..........................................

(2) Frost/Freeze ...................................(3) Inadequate moisture during growing season.(4) Excessive heat ...............................(5) Insect infestation ..........................(6) Hail ................................................

.......... 2 
397 

OR .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1846 .......... (1) Drought ..........................................

(2) Frost/Freeze ...................................(3) Inadequate moisture during growing season.(4) Excessive heat ...............................(5) Insect infestation ..........................(6) Hail ................................................

.......... 2 

UT .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1846 .......... (1) Drought ..........................................

(2) Frost/Freeze ...................................(3) Inadequate moisture during growing season.(4) Excessive heat ...............................(5) Insect infestation ..........................(6) Hail ................................................

.......... 3 

WA ................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1846 .......... (1) Drought ..........................................

(2) Frost/Freeze ...................................(3) Inadequate moisture during growing season.(4) Excessive heat ...............................(5) Insect infestation ..........................(6) Hail ................................................

.......... 3 

WY ................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1846 .......... (1) Drought ..........................................

(2) Frost/Freeze ...................................(3) Inadequate moisture during growing season.(4) Excessive heat ...............................(5) Insect infestation ..........................(6) Hail ................................................

.......... 2 

MO ................................... Dunklin, New Madrid, Pemiscot, 

Stoddard.

5–04–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1847 .......... Excessive spring rainfall ..................... 4 6 

AR .................................... .................................................... 5–04–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1847 .......... Excessive spring rainfall ..................... .......... 4 KY .................................... .................................................... 5–04–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1847 .......... Excessive spring rainfall ..................... .......... 1 TN .................................... .................................................... 5–04–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1847 .......... Excessive spring rainfall ..................... .......... 2 VA .................................... Amherst, Washington ................ 4–01–2003 ...... 8–31–2003 ...... 12–02–2003 .... 8–02–2004 ...... S1848 .......... Excessive rain ..................................... 2 11 TN .................................... .................................................... 4–01–2003 ...... 8–31–2003 ...... 12–02–2003 .... 8–02–2004 ...... S1848 .......... Excessive rain ..................................... .......... 2 
398 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

MT .................................... Beaverhead, Big Horn, Blaine, 

Broadwater, Carbon, Carter, Cascade, Daniels, Dawson, Fallon, Fergus, Flathead, Gallatin, Glacier, Golden Valley, Hill, Jefferson, Judith Basin, Lake, Lewis and Clark, Liberty, Madison, Meagher, Musselshell, Park, Phillips, Rosebud, Sanders, Sheridan, Stillwater, Sweetgrass, Teton, Toole, Wheatland, Yellowstone..

1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1849 .......... Drought ................................................ 35 21 

ID ..................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1849 .......... Drought ................................................ .......... 5 ND .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1849 .......... Drought ................................................ .......... 5 SD .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1849 .......... Drought ................................................ .......... 2 WY ................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1849 .......... Drought ................................................ .......... 5 ND .................................... Adams, Barnes, Billings, 

Bottineau, Bowman, Burke, Burleigh, Cass, Cavalier, Dickey, Divide, Dunn, Emmons, Golden Valley, Grand Forks, Grant, Griggs, Hettinger, Kidder, La Moure, Logan, McHenry, McIntosh, McKenzie, McLean, Mercer, Morton, Mountrail, Oliver, Pierce, Ramsey, Ransom, Renville, Rolette, Sargent, Sheridan, Sioux, Slope, Stark, Steele, Stutsman, Towner, Traill, Walsh, Ward, Wells, Williams.

4–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1850 .......... Flooding, ground saturation, storms, 

winds, tornadoes, high humidity, dry conditions, severe temperatures.

47 6 
399 

MN ................................... .................................................... 4–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1850 .......... Flooding, ground saturation, storms, 

winds, tornadoes, high humidity, dry conditions, severe temperatures.

.......... 5 

MT .................................... .................................................... 4–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1850 .......... Flooding, ground saturation, storms, 

winds, tornadoes, high humidity, dry conditions, severe temperatures.

.......... 5 

SD .................................... .................................................... 4–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1850 .......... Flooding, ground saturation, storms, 

winds, tornadoes, high humidity, dry conditions, severe temperatures.

.......... 8 

NE .................................... Boone, Butler, Cass, Clay, 

Colfax, Dodge, Douglas, Fillmore, Gage, Hamilton, Jefferson, Johnson, Lancaster, Merrick, Nance, Nemaha, Otoe, Pawnee, Platte, Polk, Richardson, Saline, Sarpy, Saunders, Seward, Thayer, Washington, York.

7–01–2002 ...... 5–14–2004 ...... 11–14–2003 .... 7–14–2004 ...... S1851 .......... Drought, extreme heat, flooding, 

grasshopper infestation, hail, high winds, tornadoes.

28 12 

IA ..................................... .................................................... 7–01–2002 ...... 5–14–2004 ...... 11–14–2003 .... 7–14–2004 ...... S1851 .......... Drought, extreme heat, flooding, 

grasshopper infestation, hail, high winds, tornadoes.

.......... 4 

MO ................................... .................................................... 7–01–2002 ...... 5–14–2004 ...... 11–14–2003 .... 7–14–2004 ...... S1851 .......... Drought, extreme heat, flooding, 

grasshopper infestation, hail, high winds, tornadoes.

.......... 2 

KS .................................... .................................................... 7–01–2002 ...... 5–14–2004 ...... 11–14–2003 .... 7–14–2004 ...... S1851 .......... Drought, extreme heat, flooding, 

grasshopper infestation, hail, high winds, tornadoes.

.......... 6 

SC .................................... Allendale, Bamberg, Cherokee, 

Edgefield, Greenville, Pickens, Saluda, Spartanburg.

3–20–2003 ...... 11–07–2003 .... 12–09–2003 .... 8–09–2004 ...... S1852 .......... Excessive rainfall ................................ 8 16

GA .................................... .................................................... 3–20–2003 ...... 11–07–2003 .... 12–09–2003 .... 8–09–2004 ...... S1852 .......... Excessive rainfall ................................ .......... 4 NC .................................... .................................................... 3–20–2003 ...... 11–07–2003 .... 12–09–2003 .... 8–09–2004 ...... S1852 .......... Excessive rainfall ................................ .......... 5 NJ ..................................... Atlantic, Burlington, Camden, 

Cape May, Cumberland, Gloucester, Hunterdon, Mercer, Middlesex, Monmouth, Morris, Ocean, Salem, Somerset, Sussex, Warren.

1–01–2003 ...... 6–02–2004 ...... continuing ....... 8–02–2004 ...... S1853 .......... Excessive precipitation, disease, insect infestation. 16 3 

DE .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1853 .......... Excessive precipitation ........................ .......... 3 NY .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1853 .......... Excessive precipitation ........................ .......... 2 
400 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

PA .................................... .................................................... 1–01–2003 ...... 6–02–2004 ...... 12–02–2003 .... 8–02–2004 ...... S1853 .......... Excessive precipitation ........................ .......... 6 TX .................................... Wheeler ...................................... 1–01–2003 ...... 6–12–2004 ...... 12–12–2003 .... 8–12–2004 ...... S1854 .......... Drought ................................................ 1 7 CA .................................... Colusa, Sacramento .................. 7–10–2003 ...... 8–26–2003 ...... 12–19–2003 .... 8–19–2004 ...... S1855 .......... (1) Excessive rainfall ..........................

(2) Extreme heat, followed by unseasonable rainfall.

2 11 

IL ..................................... Boone, Bureau, Carroll, Clay, 

Edwards, Fayette, Franklin, Gallatin, Hamilton, Hardin, Henderson, Henry, Jackson, Jefferson, Jo Daviess, Johnson, Knox, Lake, Lee, Marion, Marshall, Massac, McHenry, Mercer, Ogle, Perry, Pope, Putnam, Randolph, Saline, St. Clair, Stark, Stephenson, Vermilion, Wabash, Washington, Wayne, White, Whiteside, Williamson, Winnebago, Woodford.

1–01–2003 ...... continuing ....... 12–19–2003 .... 8–19–2004 ...... S1856 .......... Drought ................................................ 42 28 

KY .................................... .................................................... 1–01–2003 ...... continuing ....... 12–19–2003 .... 8–19–2004 ...... S1856 .......... Drought ................................................ .......... 4 MO ................................... .................................................... 1–01–2003 ...... continuing ....... 12–19–2003 .... 8–19–2004 ...... S1856 .......... Drought ................................................ .......... 4 WI .................................... .................................................... 1–01–2003 ...... continuing ....... 12–19–2003 .... 8–19–2004 ...... S1856 .......... Drought ................................................ .......... 5 MO ................................... Audrain, Boone, Callaway, Cape 

Girardeau, Cole, Crawford, Dade, Franklin, Gasconade, Greene, Howard, Jasper, Knox, Laclede, Lawrence, Lincoln, Macon, Maries, Marion, McDonald, Miller, Moniteau, Monroe, Montgomery, Osage, Perry, Phelps, Pike, Pulaski, Ralls, Randolph, Scotland, Shelby, Warren.

6–01–2002 ...... continuing ....... 12–19–2003 .... 8–19–2004 ...... S1857 .......... Drought ................................................ 34 21 
401 

AR .................................... .................................................... 6–01–2002 ...... continuing ....... 12–19–2003 .... 8–19–2004 ...... S1857 .......... Drought ................................................ .......... 1 IL ..................................... .................................................... 6–01–2002 ...... continuing ....... 12–19–2003 .... 8–19–2004 ...... S1857 .......... Drought ................................................ .......... 7 IA ..................................... .................................................... 6–01–2002 ...... continuing ....... 12–19–2003 .... 8–19–2004 ...... S1857 .......... Drought ................................................ .......... 2 KS .................................... .................................................... 6–01–2002 ...... continuing ....... 12–19–2003 .... 8–19–2004 ...... S1857 .......... Drought ................................................ .......... 1 OK .................................... .................................................... 6–01–2002 ...... continuing ....... 12–19–2003 .... 8–19–2004 ...... S1857 .......... Drought ................................................ .......... 2 TX .................................... Floyd .......................................... 5–31–2003 ...... 6–11–2003 ...... 12–19–2003 .... 8–19–2004 ...... S1858 .......... Excessive rain, hail, high winds ......... 1 7 AR .................................... Randolph ................................... 8–03–2003 ...... 8–03–2003 ...... 1–09–2004 ...... 9–09–2004 ...... S1859 .......... Hail ...................................................... 1 4 MO ................................... .................................................... 8–03–2003 ...... 8–03–2003 ...... 1–09–2004 ...... 9–09–2004 ...... S1859 .......... Hail ...................................................... .......... 2 ID ..................................... Latah ......................................... 7–01–2003 ...... 8–02–2003 ...... 1–09–2004 ...... 9–09–2004 ...... S1860 .......... Drought ................................................ 1 4 WA ................................... .................................................... 7–01–2003 ...... 8–02–2003 ...... 1–09–2004 ...... 9–09–2004 ...... S1860 .......... Drought ................................................ .......... 1 NY .................................... Allegany, Cayuga, Columbia, 

Dutchess, Greene, Herkimer, Jefferson, Lewis, Madison, Niagara, Onondaga, Orange, Oswego, Rensselaer, Saratoga, Schuyler, Seneca, St. Lawrence, Suffolk, Tompkins, Ulster, Wayne.

4–01–2003 ...... continuing ....... 1–09–2004 ...... 9–09–2004 ...... S1861 .......... Excessive Rain, flash Flooding, cool 

temperatures.

22 30 

CT .................................... .................................................... 4–01–2003 ...... continuing ....... 1–09–2004 ...... 9–09–2004 ...... S1861 .......... Excessive Rain, flash Flooding, cool 

temperatures.

.......... 5 

MA ................................... .................................................... 4–01–2003 ...... continuing ....... 1–09–2004 ...... 9–09–2004 ...... S1861 .......... Excessive Rain, flash Flooding, cool 

temperatures.

.......... 1 

PA .................................... .................................................... 4–01–2003 ...... continuing ....... 1–09–2004 ...... 9–09–2004 ...... S1861 .......... Excessive Rain, flash Flooding, cool 

temperatures.

.......... 3 

VT .................................... .................................................... 4–01–2003 ...... continuing ....... 1–09–2004 ...... 9–09–2004 ...... S1861 .......... Excessive Rain, flash Flooding, cool 

temperatures.

.......... 1 

OR .................................... Union, Wheeler ........................... 10–01–2001 .... continuing ....... 1–09–2004 ...... 9–09–2004 ...... S1862 .......... Drought ................................................ 2 3 VA .................................... (1) Franklin, Northampton, Roanoke.

(2) Patrick .................................

1–01–2003 ...... continuing ....... 1–09–2004 ...... 9–09–2004 ...... S1863 .......... (1) Excessive rain ...............................

(2) Hurricane Isabel ............................

3 13 

NC .................................... .................................................... 1–01–2003 ...... continuing ....... 1–09–2004 ...... 9–09–2004 ...... S1863 .......... (1) Excessive rain ...............................

(2) Hurricane Isabel ............................

.......... 2 

TN .................................... Carter, Hancock, Hawkins, Jefferson, Johnson, Macon, 

Montgomery, Sullivan, Trousdale, Unicoi, Washington.

4–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1864 .......... Excessive rainfall ................................ 11 17 

KY .................................... .................................................... 4–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1864 .......... Excessive rainfall ................................ .......... 4 NC .................................... .................................................... 4–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1864 .......... Excessive rainfall ................................ .......... 6 VA .................................... .................................................... 4–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1864 .......... Excessive rainfall ................................ .......... 2 
402 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

MI .................................... Antrim, Calhoun, Ingham, Jackson, Kent, Mason, Muskegon, 

Newaygo, Ottawa.

8–01–2003 ...... 9–22–2003 ...... 1–23–2004 ...... 9–23–2004 ...... S1865 .......... Storms that produced hail, high 

winds, heavy rains.

9 24 

MI .................................... Alcona, Alger, Allegan, Alpena, 

Antrim, Arenac, Baraga, Barry, Bay, Benzie, Berrien, Calhoun, Cass, Charlevoix, Cheboygan, Chippewa, Clare, Clinton, Delta, Dickinson, Eaton, Emmet, Genesee, Gladwin, Gogebic, Grand Traverse, Gratiot, Houghton, Huron, Ingham, Ionia, Iosco, Iron, Isabella, Jackson, Kalamazoo, Kalkaska, Kent, Keweenaw, Lapeer, Leelanau, Livingston, Luce, Mackinac, Macomb, Manistee, Marquette, Mason, Mecosta, Menominee, Midland, Missaukee, Montcalm, Montmorency, Muskegon, Newaygo, Oakland, Oceana, Ogemaw, Ontonagon, Osceola, Otsego, Ottawa, Presque Isle, Saginaw, Sanilac, Schoolcraft, Shiawassee, St. Clair, St. Joseph, Tuscola, Van Buren, Washtenaw, Wayne, Wexford.

7–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1866 .......... Drought ................................................ 75 8 

IN ..................................... .................................................... 7–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1866 .......... Drought ................................................ .......... 4 WI .................................... .................................................... 7–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1866 .......... Drought ................................................ .......... 5 
403 

MI .................................... Allegan, Antrim, Benzie, Berrien, 

Cass, Charlevoix, Dickinson, Grand Traverse, Hillsdale, Huron, Ingham, Ionia, Iron, Isabella, Kalamazoo, Kent, Leelanau, Livingston, Macomb, Manistee, Mason, Menominee, Monroe, Montcalm, Muskegon, Newaygo, Oceana, Otsego, Ottawa, St. Clair, Van Buren, Wexford.

(1) 02/28/03 ....(2) 05/07/03 ....

(1) 07/21/03 ....(2) 07/21/03 ....

1–23–2004 ...... 9–23–2004 ...... S1867 .......... (1) Extreme temperature fluctuations; 

freezing rain; periods of abnormal warm weather followed by temperatures as low as 24 degrees with significant crop damage..

(2) Heavy rains, flooding, hail, high 

winds.

32 36 

IN ..................................... .................................................... (1) 02/28/03 ....

(2) 05/07/03 ....

(2) 07/21/03 ....(2) 07/21/03 ....

1–23–2004 ...... 9–23–2004 ...... S1867 .......... (1) Extreme temperature fluctuations; 

freezing rain; periods of abnormal warm weather followed by temperatures as low as 24 degrees with significant crop damage..

(2) Heavy rains, flooding, hail, high 

winds.

.......... 4 

OH .................................... .................................................... (1) 02/28/03 ....

(2)05/07/03 .....

(1) 07/21/03 ....(2)07/21/03 .....

1–23–2004 ...... 9–23–2004 ...... S1867 .......... (1) Extreme temperature fluctuations; 

freezing rain; periods of abnormal warm weather followed by temperatures as low as 24 degrees with significant crop damage..

(2) Heavy rains, flooding, hail, high 

winds.

.......... 3 

WI .................................... .................................................... (1) 02/28/03 ....

(2) 05/07/03 ....

(1) 07/21/03 ....(2) 07/21/03 ....

1–23–2004 ...... 9–23–2004 ...... S1867 .......... (1) Extreme temperature fluctuations; 

freezing rain; periods of abnormal warm weather followed by temperatures as low as 24 degrees with significant crop damage..

(2) Heavy rains, flooding, hail, high 

winds.

.......... 4 
404 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

KS .................................... Allen, Anderson, Atchison, Barber, Barton, Bourbon, Chautauqua, Cheyenne, Clay, 

Cloud, Coffey, Crawford, Decatur, Dickinson, Doniphan, Elk, Ellsworth, Finney, Ford, Geary, Graham, Grant, Gray, Hamilton, Harper, Haskell, Hodgeman, Jefferson, Jewell, Johnson, Kearny, Kingman, Kiowa, Lane, Leavenworth, Lincoln, Linn, Logan, McPherson, Marshall, Meade, Miami, Mitchell, Nemaha, Neosho, Ness, Norton, Osage, Osborne, Ottawa, Phillips, Pottawatomie, Rawlins, Reno, Republic, Rice, Riley, Rooks, Rush, Russell, Saline, Scott, Sheridan, Sherman, Smith, Stafford, Stanton, Thomas, Trego, Wabaunsee, Wallace, Washington, Wyandotte; Douglas, Edwards, Franklin, Gove, Lyon, Morris, Pawnee, Pratt.

1–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1868 .......... Drought, excessive wind, insect damage. 81 24 

CO .................................... .................................................... 1–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1868 .......... Drought, excessive wind, insect damage. .......... 4 MO ................................... .................................................... 1–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1868 .......... Drought, excessive wind, insect damage. .......... 11 NE .................................... .................................................... 1–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1868 .......... Drought, excessive wind, insect damage. .......... 13 
405 

OK .................................... .................................................... 1–01–2003 ...... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1868 .......... Drought, excessive wind, insect damage. .......... 6 OR .................................... Sherman, Wallowa ..................... 10–01–2001 .... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1869 .......... Drought ................................................ 2 5 ID ..................................... Sherman, Wallowa ..................... 10–01–2001 .... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1869 .......... Drought ................................................ .......... 3 WA ................................... Sherman, Wallowa ..................... 10–01–2001 .... continuing ....... 1–23–2004 ...... 9–23–2004 ...... S1869 .......... Drought ................................................ .......... 4 TX .................................... Brooks ........................................ 10–10–2003 .... 10–13–2003 .... 2–10–2004 ...... 10–12–2004 .... S1870 .......... Flash flooding ..................................... 1 7 TX .................................... Lavaca ....................................... 1–01–2003 ...... continuing ....... 2–10–2004 ...... 10–12–2004 .... S1871 .......... Excessive rain ..................................... 1 6 TX .................................... Wilbarger ................................... 10–10–2003 .... 10–13–2003 .... 2–10–2004 ...... 10–12–2004 .... S1872 .......... Flash flooding ..................................... 1 5 OK .................................... Jackson, Tillman ........................ 10–10–2003 .... 10–13–2003 .... 2–10–2004 ...... 10–12–2004 .... S1872 .......... Flash flooding ..................................... .......... 2 TX .................................... Knox ........................................... 1–01–2003 ...... 12–08–2003 .... 2–10–2004 ...... 10–12–2004 .... S1873 .......... Drought, high wind, excessive heat ... 1 6 TX .................................... Young ......................................... 4–05–2003 ...... 4–05–2003 ...... 2–10–2004 ...... 10–12–2004 .... S1874 .......... Hail, tornado, excessive high winds ... 1 6 TX .................................... Stephens .................................... 1–01–2003 ...... continuing ....... 2–10–2004 ...... 10–12–2004 .... S1875 .......... Drought, high winds ........................... 1 5 TX .................................... Baylor ......................................... 7–01–2003 ...... continuing ....... 2–10–2004 ...... 10–12–2004 .... S1876 .......... Drought ................................................ 1 8 TX .................................... Cottle, King ................................ 7–01–2003 ...... continuing ....... 2–10–2004 ...... 10–12–2004 .... S1877 .......... Drought, excessive temperatures 

(heat).

1 10 

TX .................................... Stonewall ................................... 1–01–2003 ...... continuing ....... 2–10–2004 ...... 10–12–2004 .... S1878 .......... Drought, excessive temperatures 

(heat).

1 7 

PA .................................... Erie ............................................ 1–01–2003 ...... 12–31–2003 .... 2–13–2004 ...... 10–13–2004 .... S1879 .......... Excessive rainfall, early frost ............. 1 2 NY .................................... .................................................... 1–01–2003 ...... 12–31–2003 .... 2–13–2004 ...... 10–13–2004 .... S1879 .......... Excessive rainfall, early frost ............. .......... 1 OH .................................... .................................................... 1–01–2003 ...... 12–31–2003 .... 2–13–2004 ...... 10–13–2004 .... S1879 .......... Excessive rainfall, early frost ............. .......... 1 OR .................................... Harney, Klamath, Malheur ......... 10–01–2001 .... continuing ....... 2–13–2004 ...... 10–13–2004 .... S1880 .......... Drought ................................................ 3 4 CA .................................... .................................................... 10–01–2001 .... continuing ....... 2–13–2004 ...... 10–13–2004 .... S1880 .......... Drought ................................................ .......... 1 ID ..................................... .................................................... 10–01–2001 .... continuing ....... 2–13–2004 ...... 10–13–2004 .... S1880 .......... Drought ................................................ .......... 1 MI .................................... Berrien, Kalamazoo, Manistee, 

Mason, Ocean, Van Buren.

8–01–2003 ...... 9–30–2003 ...... 2–13–2004 ...... 10–13–2004 .... S1881 .......... Abnormally cool, cloudy weather resulting in an increase in aphids, 

which caused mosaic virus (in vegetable crops.

6 12 

IN ..................................... Berrien, Kalamazoo, Manistee, 

Mason, Ocean, Van Buren.

8–01–2003 ...... 9–30–2003 ...... 2–13–2004 ...... 10–13–2004 .... S1881 .......... .............................................................. .......... 2 

MI .................................... Berrien, Cass, Kalamazoo, Van 

Buren.

3–01–2003 ...... 10–02–2003 .... 2–13–2004 ...... 10–13–2004 .... S1882 .......... Late spring (cool spring weather), 

combined with early freeze.

4 5 

IN ..................................... Berrien, Cass, Kalamazoo, Van 

Buren.

3–01–2003 ...... 10–02–2003 .... 2–13–2004 ...... 10–13–2004 .... S1882 .......... Late spring (cool spring weather), 

combined with early freeze.

.......... 3 
406 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

WI .................................... Adams, Ashland, Barron, 

Bayfield, Buffalo, Burnett, Calumet, Chippewa, Clark, Columbia, Crawford, Dane, Dodge, Douglas, Dunn, Eau Claire, Florence, Fond du Lac, Forest, Grant, Green, Green Lake, Iowa, Iron, Jackson, Jefferson, Juneau, Kenosha, LaCrosse, Lafayette, Langlade, Lincoln, Marquette, Milwaukee, Monroe, Oneida, Ozaukee, Pepin, Pierce, Polk, Portage, Racine, Richland, Rock, Rusk, St. Croix, Sauk, Sawyer, Trempealeau, Vernon, Vilas, Walworth, Washburn, Washington, Waukesha, Waupaca, Waushara, Winnebago, Wood.

5–01–2003 ...... 10–31–2003 .... 2–27–2004 ...... 10–27–2004 .... S1883 .......... Drought ................................................ 59 11 

IL ..................................... .................................................... 5–01–2003 ...... 10–31–2003 .... 2–27–2004 ...... 10–27–2004 .... S1883 .......... Drought ................................................ .......... 6 IA ..................................... .................................................... 5–01–2003 ...... 10–31–2003 .... 2–27–2004 ...... 10–27–2004 .... S1883 .......... Drought ................................................ .......... 3 MI .................................... .................................................... 5–01–2003 ...... 10–31–2003 .... 2–27–2004 ...... 10–27–2004 .... S1883 .......... Drought ................................................ .......... 3 MN ................................... .................................................... 5–01–2003 ...... 10–31–2003 .... 2–27–2004 ...... 10–27–2004 .... S1883 .......... Drought ................................................ .......... 10 MA ................................... Berkshire, Bristol, Franklin, 

Hampshire, Hampden, Norfolk, Plymouth.

5–01–2003 ...... 10–31–2003 .... 3–09–2004 ...... 11–09–2004 .... S1884 .......... Wet weather patterns .......................... 7 4 

CT .................................... .................................................... 5–01–2003 ...... 10–31–2003 .... 3–09–2004 ...... 11–09–2004 .... S1884 .......... Wet weather patterns .......................... .......... 2 NH .................................... .................................................... 5–01–2003 ...... 10–31–2003 .... 3–09–2004 ...... 11–09–2004 .... S1884 .......... Wet weather patterns .......................... .......... 1 RI ..................................... .................................................... 5–01–2003 ...... 10–31–2003 .... 3–09–2004 ...... 11–09–2004 .... S1884 .......... Wet weather patterns .......................... .......... 3 VT .................................... .................................................... 5–01–2003 ...... 10–31–2003 .... 3–09–2004 ...... 11–09–2004 .... S1884 .......... Wet weather patterns .......................... .......... 1 CA .................................... Fresno, Kern, Merced, Tulare ..... 1–02–2003 ...... 9–30–2003 ...... 3–09–2004 ...... 11–09–2004 .... S1885 .......... Cool weather followed by extended 

period of hot weather.

4 15 
407 

NY .................................... Albany, Cattaraugus, Chautauqua, Erie, Livingston, 

Oneida, Orleans, Saratoga, Seneca, Sullivan, Tompkins.

4–01–2003 ...... continuing ....... 3–09–2004 ...... 11–09–2004 .... S1886 .......... Various disasters for each county including: Below normal temperatures, excessive rain, flash flooding, hail, high winds. 11 12 

PA .................................... .................................................... 4–01–2003 ...... continuing ....... 3–09–2004 ...... 11–09–2004 .... S1886 .......... Various disasters for each county including: Below normal temperatures, excessive rain, flash flooding, hail, high winds. .......... 3 NY .................................... Wayne ........................................ 9–23–2003 ...... 9–23–2003 ...... 3–09–2004 ...... 11–09–2004 .... S1887 .......... Hail ...................................................... 1 4 WA ................................... (1) Clark, Cowlitz, Skamania, 

Wahkiakum.

(2) Island, San Juan, Skagit .....

5–01–2003 ...... 9–06–2003 ...... 3–09–2004 ...... 11–09–2004 .... S1888 .......... (1) Drought, excessive heat ................

(2) Drought ..........................................

7 8 

OR .................................... .................................................... 5–01–2003 ...... 9–06–2003 ...... 3–09–2004 ...... 11–09–2004 .... S1888 .......... (1) Drought, excessive heat ................

(2) Drought ..........................................

..........

CA .................................... Sutter, Yuba .............................. 8–22–2003 ...... 9–15–2003 ...... 3–11–2004 ...... 11–09–2004 .... S1889 .......... Unseasonable late summer rainfall ... 2 8 CO .................................... Cheyenne, Logan, Phillips ......... 1–01–2004 ...... continuing ....... 3–16–2004 ...... 11–16–2004 .... S1890 .......... Drought ................................................ 3 4 NE .................................... .................................................... 1–01–2004 ...... continuing ....... 3–16–2004 ...... 11–16–2004 .... S1890 .......... Drought ................................................ .......... 3 ME ................................... Aroostook, Franklin, Oxford, Penobscot. 6–01–2003 ...... continuing ....... 3–16–2004 ...... 11–16–2004 .... S1891 .......... Excessive rainfall ................................ 4 9 NH .................................... .................................................... 6–01–2003 ...... continuing ....... 3–16–2004 ...... 11–16–2004 .... S1891 .......... Excessive rainfall ................................ .......... 2 TX .................................... Hansford .................................... 6–05–2003 ...... 6–09–2003 ...... 3–16–2004 ...... 11–16–2004 .... S1892 .......... Excessive rain, flash flooding, hail, 

high winds, lightning, tornado.

1 5 

OK .................................... .................................................... 6–05–2003 ...... 6–09–2003 ...... 3–16–2004 ...... 11–16–2004 .... S1892 .......... Excessive rain, flash flooding, hail, 

high winds, lightning, tornado.

.......... 1 

WA ................................... Asotin, Chelan, Columbia, 

Douglas, Ferry, Garfield, Grays Harbor, King, Kitsap, Lewis, Lincoln, Mason, Pacific, Pend Oreille, Pierce, Spokane, Stevens, Thurston, Walla Walla, Whitman.

1–01–2003 ...... continuing ....... 3–16–2004 ...... 11–16–2004 .... S1893 .......... Drought ................................................ 20 13 

ID ..................................... .................................................... 1–01–2003 ...... continuing ....... 3–16–2004 ...... 11–16–2004 .... S1893 .......... Drought ................................................ .......... 6 OR .................................... .................................................... 1–01–2003 ...... continuing ....... 3–16–2004 ...... 11–16–2004 .... S1893 .......... Drought ................................................ .......... 2 CT .................................... Entire State ............................... 5–01–2003 ...... 9–30–2003 ...... 3–22–2004 ...... 11–22–2004 .... S1894 .......... Wet weather pattern; high rainfall, 

insect problems.

8 ..........

MA ................................... .................................................... 5–01–2003 ...... 9–30–2003 ...... 3–22–2004 ...... 11–22–2004 .... S1894 .......... Wet weather pattern; high rainfall, 

insect problems.

.......... 2 

NY .................................... .................................................... 5–01–2003 ...... 9–30–2003 ...... 3–22–2004 ...... 11–22–2004 .... S1894 .......... Wet weather pattern; high rainfall, 

insect problems.

.......... 4 
408 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

RI ..................................... .................................................... 5–01–2003 ...... 9–30–2003 ...... 3–22–2004 ...... 11–22–2004 .... S1894 .......... Wet weather pattern; high rainfall, 

insect problems.

.......... 3 

HI ..................................... Hawaii, Honolulu, Kauai, Maui .. 1–01–2003 ...... 12–31–2003 .... 3–22–2004 ...... 11–22–2004 .... S1895 .......... Drought ................................................ 4 1 OR .................................... Wasco, Washington ................... 10–01–2001 .... continuing ....... 3–22–2004 ...... 11–22–2004 .... S1896 .......... Drought ................................................ 2 8 TX .................................... Hockley ....................................... 6–30–2003 ...... continuing ....... 3–22–2004 ...... 11–22–2004 .... S1897 .......... Drought ................................................ 1 8 TX .................................... Fisher ......................................... 1–01–2003 ...... continuing ....... 3–22–2004 ...... 11–22–2004 .... S1898 .......... Drought, excessive temperatures 

(heat).

1 7 

TX .................................... Lynn ........................................... 1–01–2003 ...... continuing ....... 4–05–2004 ...... 12–06–2004 .... S1899 .......... (1) Hail, high winds ............................

(2) Drought ..........................................

1 7 

NY .................................... Erie, Livingston, Monroe, Onondaga, Ontario, Orleans, 

Oswego, Schuyler, Tompkins.

10–14–2003 .... continuing ....... 4–09–2004 ...... 12–09–2004 .... S1900 .......... Excessive rain, high winds ................. 9 20 

KS .................................... Brown ......................................... 1–01–2003 ...... continuing ....... 4–21–2004 ...... 12–21–2004 .... S1901 .......... Drought, frost, excessive wind, insect 

damage.

1 ..........

OR .................................... Morrow ....................................... 9–02–2002 ...... continuing ....... 4–21–2004 ...... 12–21–2004 .... S1902 .......... Drought ................................................ 1 ..........WA ................................... .................................................... 9–02–2002 ...... continuing ....... 4–21–2004 ...... 12–21–2004 .... S1902 .......... Drought ................................................ .......... 1 TX .................................... Robertson ................................... 10–05–2003 .... 10–09–2003 .... 4–21–2004 ...... 12–21–2004 .... S1903 .......... Excessive rain, flash flooding ............. 1 7 TX .................................... Martin ........................................ 1–01–2003 ...... 12–31–2003 .... 4–23–2004 ...... 12–23–2004 .... S1904 .......... Drought, high winds ........................... 1 7 TX .................................... Motley ........................................ 7–01–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1905 .......... Drought, high winds, static electricity 1 7 TX .................................... San Saba ................................... 10–15–2003 .... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1906 .......... Drought ................................................ 1 7 TX .................................... Mason ........................................ 10–01–2003 .... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1907 .......... Drought, high winds ........................... 1 6 TX .................................... Palo Pinto .................................. 10–01–2003 .... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1908 .......... Drought ................................................ 1 7 TX .................................... Bastrop ...................................... 3–01–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1909 .......... Drought ................................................ 1 6 TX .................................... Dickens ...................................... 8–01–2003 ...... 12–18–2003 .... 4–23–2004 ...... 12–23–2004 .... S1910 .......... Drought, excessive temperatures 

(heat).

1 8 

TX .................................... Caldwell ..................................... 3–15–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1911 .......... Drought ................................................ 1 6 TX .................................... Kent ........................................... 8–01–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1912 .......... Drought, excessive temperatures 

(heat).

1 7 

TX .................................... Montague ................................... 4–15–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1913 .......... Drought ................................................ 1 4 OK .................................... .................................................... 4–15–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1913 .......... Drought ................................................ .......... 2 TX .................................... Crane, Ector, Haskell, Loving, 

Presidio, Reeves, Ward, Winkler.

1–01–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1914 .......... Drought, high winds, excessive heat .. 8 16 

NM ................................... .................................................... 1–01–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1914 .......... Drought, high winds, excessive heat .. .......... 2 
409 

CA .................................... San Luis Obispo, Santa Barbara 4–01–2003 ...... 10–31–2003 .... 4–23–2004 ...... 12–23–2004 .... S1915 .......... (1) Insufficient winter chill hours, 

rainfall, high heat.

(2) Insufficient winter chill hours, 

cool/wet weather, extended hot spell.

2 6 

MT .................................... Blackfeet Tribe (Pondera Co.), 

Confederated Salish Kootenai Tribe (Missoula Co.), Ft. Peck Assisiboine & Sioux Tribe; (Valley Co.), Chouteau, Garfield, Granite, Mineral, Prairie, Petroleum, Pondera, Treasure.

1–01–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1916 .......... Drought ................................................ 11 ..........

ID ..................................... .................................................... 1–01–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1916 .......... Drought ................................................ .......... 2 CA .................................... Placer ......................................... 8–01–2003 ...... 10–31–2003 .... 4–23–2004 ...... 12–23–2004 .... S1917 .......... August rain, poor winter chill, high 

heat-Pistachios.

1 5 

NV .................................... .................................................... 8–01–2003 ...... 10–31–2003 .... 4–23–2004 ...... 12–23–2004 .... S1917 .......... August rain, poor winter chill, high 

heat-Pistachios.

.......... 3 

TX .................................... Crockett, Glasscock, Hardeman, 

Howard, Irion, Jones, Reagan, Upton, Williamson.

1–01–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1918 .......... Drought ................................................ 9 32 

OK .................................... .................................................... 1–01–2003 ...... continuing ....... 4–23–2004 ...... 12–23–2004 .... S1918 .......... Drought ................................................ .......... 2 NY .................................... Fulton, Montgomery, Ontario, 

Otsego.

4–01–2003 ...... continuing ....... 4–27–2004 ...... 12–27–2004 .... S1919 .......... Excessive rain, cool temperatures ...... 4 6 

TX .................................... Andrews ..................................... 1–01–2003 ...... continuing ....... 4–28–2004 ...... 12–28–2004 .... S1920 .......... Drought, high winds ........................... 1 5 NM ................................... .................................................... 1–01–2003 ...... continuing ....... 4–28–2004 ...... 12–28–2004 .... S1920 .......... Drought, high winds ........................... .......... 1 TX .................................... Donley ........................................ 9–15–2003 ...... 12–31–2003 .... 4–28–2004 ...... 12–28–2004 .... S1921 .......... Drought ................................................ 1 7 TX .................................... Shackelford, Throckmorton ........ 1–01–2003 ...... 11–25–2003 .... 4–28–2004 ...... 12–28–2004 .... S1922 .......... Drought, high winds ........................... 2 9 TX .................................... Childress .................................... 8–01–2003 ...... continuing ....... 4–28–2004 ...... 12–28–2004 .... S1923 .......... Drought, high winds ........................... 1 4 OK .................................... .................................................... 8–01–2003 ...... continuing ....... 4–28–2004 ...... 12–28–2004 .... S1923 .......... Drought, high winds ........................... .......... 1 TX .................................... Clay ............................................ 7–01–2003 ...... continuing ....... 4–28–2004 ...... 12–28–2004 .... S1924 .......... Drought ................................................ 1 4 OK .................................... .................................................... 7–01–2003 ...... continuing ....... 4–28–2004 ...... 12–28–2004 .... S1924 .......... Drought ................................................ .......... 2 TX .................................... Wise ........................................... 7–15–2003 ...... continuing ....... 4–28–2004 ...... 12–28–2004 .... S1925 .......... Drought ................................................ 1 6 NY .................................... Dutchess .................................... 9–01–2003 ...... continuing ....... 5–03–2004 ...... 12–28–2004 .... S1926 .......... Excessive rain, flooding ...................... 1 4 CT .................................... .................................................... 9–01–2003 ...... continuing ....... 5–03–2004 ...... 1–03–2005 ...... S1926 .......... Excessive rain, flooding ...................... .......... 2 MA ................................... .................................................... 9–01–2003 ...... continuing ....... 5–03–2004 ...... 1–03–2005 ...... S1926 .......... Excessive rain, flooding ...................... .......... 1 CA .................................... Placer, San Luis Obispo ............ 5–01–2003 ...... 11–15–2003 .... 5–17–2004 ...... 1–18–2005 ...... S1927 .......... (1) Unseasonable rainfall ...................

(2) Wheat stripe rust, resulting from 

unseasonable rainfall.

2 9 
410 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

NV .................................... .................................................... 5–01–2003 ...... 11–15–2003 .... 5–17–2004 ...... 1–18–2005 ...... S1927 .......... (1) Unseasonable rainfall ...................

(2) Wheat stripe rust, resulting from 

unseasonable rainfall.

.......... 3 

TX .................................... Brooks ........................................ 4–04–2004 ...... 4–04–2004 ...... 6–08–2004 ...... 2–08–2004 ...... S1928 .......... Excessive rain, flash flooding, flooding, hail, high winds. 1 7 HI ..................................... Hawaii, Honolulu, Maui ............. 12–07–2003 .... 3–26–2004 ...... 6–21–2004 ...... 2–22–2004 ...... S1929 .......... High winds, rain, flooding .................. 3 1 TX .................................... Robertson ................................... 4–10–2004 ...... 4–10–2004 ...... 6–21–2004 ...... 2–22–2004 ...... S1930 .......... Hail, high winds .................................. 1 7 NE .................................... Arthur, Banner, Chase, Cheyenne, Deuel, Dundy, Frontier, 

Garden, Hayes, Hitchcock, Keith, Kimball, Lincoln, McPherson, Morrill, Perkins, Red Willow, Scotts Bluff, Sioux.

1–01–2004 ...... continuing ....... 6–21–2004 ...... 2–22–2004 ...... S1931 .......... Drought ................................................ 19 11 

SD .................................... .................................................... 1–01–2004 ...... continuing ....... 6–21–2004 ...... 2–22–2004 ...... S1931 .......... Drought ................................................ .......... 1 WY ................................... .................................................... 1–01–2004 ...... continuing ....... 6–21–2004 ...... 2–22–2004 ...... S1931 .......... Drought ................................................ .......... 3 MA ................................... Essex, Franklin, Middlesex ........ 1–05–2004 ...... 2–20–2004 ...... 7–09–2004 ...... 3–09–2004 ...... S1932 .......... Winter damage due to abnormally cod 

weather patterns.

3 5 

NH .................................... .................................................... 1–05–2004 ...... 2–20–2004 ...... 7–09–2004 ...... 3–09–2004 ...... S1932 .......... Winter damage due to abnormally cod 

weather patterns.

.......... 3 

VT .................................... .................................................... 1–05–2004 ...... 2–20–2004 ...... 7–09–2004 ...... 3–09–2004 ...... S1932 .......... Winter damage due to abnormally cod 

weather patterns.

.......... 2 

TX .................................... Wilson ........................................ 5–13–2004 ...... 5–13–2004 ...... 7–20–2004 ...... 3–21–2004 ...... S1933 .......... Excessive rain, high winds ................. 1 5 MO ................................... Linn ............................................ 5–24–2004 ...... 5–24–2004 ...... 7–29–2004 ...... 3–29–2005 ...... S1934 .......... Severe thunderstorms w/ high winds, 

tornadoes, excessive rain, flooding, lightning, large hail.

1 6 

WA ................................... Franklin ...................................... 1–04–2004 ...... 1–07–2004 ...... 7–29–2004 ...... 3–29–2005 ...... S1935 .......... Sub-zero freezing temperatures .......... 1 6 WA ................................... Yakima ....................................... 10–29–2003 .... 1–08–2004 ...... 7–29–2004 ...... 3–29–2005 ...... S1936 .......... Adverse weather conditions; sub-zero 

freezing temperatures.

1 8 

NE .................................... Box Butte, Dawes ...................... 1–01–2004 ...... continuing ....... 7–29–2004 ...... 3–29–2005 ...... S1937 .......... Drought ................................................ 2 3 NE .................................... Sheridan .................................... 5–13–2004 ...... 5–14–2004 ...... 7–29–2004 ...... 3–29–2005 ...... S1937 .......... Freeze .................................................. 1 6 SD .................................... Fall River ................................... 1–01–2004 ...... continuing ....... 7–29–2004 ...... 3–29–2005 ...... S1937 .......... Drought ................................................ .......... 1 SD .................................... Bennett, Shannon ...................... 5–13–2004 ...... 5–14–2004 ...... 7–29–2004 ...... 3–29–2005 ...... S1937 .......... Freeze .................................................. .......... 2 
411 

CA .................................... Butte, Glenn, Yuba .................... 3–12–2004 ...... 3–15–2004 ...... 8–02–2004 ...... 4–04–2005 ...... S1938 .......... Unseasonably high temperatures, low 

humidity.

1 9 

CA .................................... Fresno ........................................ 3–01–2004 ...... 3–31–2004 ...... 8–02–2004 ...... 4–04–2005 ...... S1938 .......... Unseasonably hot weather during 

fruit bloom.

1 8 

CA .................................... Merced ....................................... 3–25–2004 ...... 3–25–2004 ...... 8–02–2004 ...... 4–04–2005 ...... S1938 .......... Windy conditions, abnormally high 

temperatures.

1 6 

CA .................................... Sutter ......................................... 3–09–2004 ...... 3–22–2004 ...... 8–02–2004 ...... 4–04–2005 ...... S1938 .......... Severe high temperatures, low humidity. 1 6 SD .................................... Bennett, Brule, Buffalo, Butte, 

Campbell, Corson, Custer, Dewey, Fall River, Gregory, Haakon, Hand, Harding, Hughes, Hyde, Jackson, Jones, Lawrence, Lyman, Meade, Mellette, Pennington, Perkins, Shannon, Stanley, Sully, Todd, Tripp, Walworth, Ziebach.

1–01–2004 ...... continuing ....... 8–06–2004 ...... 4–06–2005 ...... S1939 .......... Drought, infestation of army 

cutworms, weevils, and grasshoppers.

30 9 

MT .................................... .................................................... 1–01–2004 ...... continuing ....... 8–06–2004 ...... 4–06–2005 ...... S1939 .......... Drought, infestation of army 

cutworms, weevils, and grasshoppers.

.......... 2 

NE .................................... .................................................... 1–01–2004 ...... continuing ....... 8–06–2004 ...... 4–06–2005 ...... S1939 .......... Drought, infestation of army 

cutworms, weevils, and grasshoppers.

.......... 6 

ND .................................... .................................................... 1–01–2004 ...... continuing ....... 8–06–2004 ...... 4–06–2005 ...... S1939 .......... Drought, infestation of army 

cutworms, weevils, and grasshoppers.

.......... 5 

WY ................................... .................................................... 1–01–2004 ...... continuing ....... 8–06–2004 ...... 4–06–2005 ...... S1939 .......... Drought, infestation of army 

cutworms, weevils, and grasshoppers.

.......... 3 

SD .................................... Charles Mix ................................ 1–01–2004 ...... continuing ....... 11–23–2004 .... 7–25–2005 ...... S1939, 

Amendment 1.

Late spring killing frost, extreme 

heat, high winds, hail, severe storms, drought, insect infestation.

1 3 

NE .................................... .................................................... 1–01–2004 ...... continuing ....... 11–23–2004 .... 7–25–2005 ...... S1939, 

Amendment 1.

Late spring killing frost, extreme 

heat, high winds, hail, severe storms, drought, insect infestation.

.......... 1 
412 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

ND .................................... Adams, Billings, Bottineau, 

Bowman, Burke, Burleigh, Cavalier, Divide, Dunn, Eddy, Emmons, Foster, Golden Valley, Grand Forks, Grant, Hettinger, McHenry, McKenzie, Mercer, Morton, Mountrail, Nelson, Oliver, Pembina, Pierce, Ramsey, Ransom, Renville, Rolette, Sioux, Slope, Stark, Towner, Walsh, Ward.

1–01–2004 ...... continuing ....... 8–10–2004 ...... 4–11–2005 ...... S1940 .......... Drought, late season frost, high 

winds, flooding, ground saturation, storms, ice, snow, severe temperatures.

35 18 

MN ................................... .................................................... 1–01–2004 ...... continuing ....... 8–10–2004 ...... 4–11–2005 ...... S1940 .......... Drought, late season frost, high 

winds, flooding, ground saturation, storms, ice, snow, severe temperatures.

.......... 3 

MT .................................... .................................................... 1–01–2004 ...... continuing ....... 8–10–2004 ...... 4–11–2005 ...... S1940 .......... Drought, late season frost, high 

winds, flooding, ground saturation, storms, ice, snow, severe temperatures.

.......... 5 

SD .................................... .................................................... 1–01–2004 ...... continuing ....... 8–10–2004 ...... 4–11–2005 ...... S1940 .......... Drought, late season frost, high 

winds, flooding, ground saturation, storms, ice, snow, severe temperatures.

.......... 4 

AR .................................... Crawford, Faulkner, Greene, 

Independence, Jackson, Lawrence, Perry, Pope, Prairie, Pulaski, White, Woodruff, Yell.

4–21–2004 ...... 4–27–2004 ...... 8–11–2004 ...... 4–11–2005 ...... S1941 .......... Excessive rain, flooding ...................... 13 29 

OK .................................... Crawford, Faulkner, Greene, 

Independence, Jackson, Lawrence, Perry, Pope, Prairie, Pulaski, White, Woodruff, Yell.

4–21–2004 ...... 4–27–2004 ...... 8–11–2004 ...... 4–11–2004 ...... S1941 .......... Excessive rain, flooding ...................... .......... 2 
413 

CA .................................... Madera ....................................... 10–01–2003 .... 5–31–2004 ...... 8–11–2004 ...... 4–11–2005 ...... S1942 .......... (1) Drought ..........................................

(2)Windy conditions, abnormally high 

temperatures.

1 5 

CA .................................... Colusa ........................................ 3–12–2004 ...... 3–19–2004 ...... 8–11–2004 ...... 4–11–2005 ...... S1943 .......... Unseasonably high temperatures ....... 1 5 NY .................................... Ontario, Seneca, Steuben, 

Wayne, Yates.

12–15–2003 .... 2–17–2004 ...... 8–11–2004 ...... 4–11–2005 ...... S1944 .......... Excessive cold, significant frost ......... 5 11 

TX .................................... Lipscomb ................................... 4–11–2004 ...... 4–12–2004 ...... 8–11–2004 ...... 4–11–2005 ...... S1945 .......... Freeze .................................................. 1 3 CA .................................... Alameda ..................................... 3–01–2004 ...... continuing ....... 8–18–2004 ...... 4–18–2005 ...... S1946 .......... Drought, high winds, excessive 

[record] temperatures.

1 4 

CO .................................... Baca, Chaffee, Cheyenne, Custer, Eagle, Fremont, Garfield, 

Grand, Jackson, Kiowa, Kit Carson, Lake, Lincoln, Phillips, Pitkin, Prowers, Pueblo, Routt, Summit, Yuma.

1–01–2004 ...... continuing ....... 8–18–2004 ...... 4–18–2005 ...... S1947 .......... Drought, hail, freeze ........................... 20 22 

KS .................................... .................................................... 1–01–2004 ...... continuing ....... 8–18–2004 ...... 4–18–2005 ...... S1947 .......... Drought, hail, freeze ........................... .......... 7 NE .................................... .................................................... 1–01–2004 ...... continuing ....... 8–18–2004 ...... 4–18–2005 ...... S1947 .......... Freeze, hail .......................................... .......... 4 NM ................................... .................................................... 1–01–2004 ...... continuing ....... 8–18–2004 ...... 4–18–2005 ...... S1947 .......... Drought ................................................ .......... 1 OK .................................... .................................................... 1–01–2004 ...... continuing ....... 8–18–2004 ...... 4–18–2005 ...... S1947 .......... Drought ................................................ .......... 1 UT .................................... .................................................... 1–01–2004 ...... continuing ....... 8–18–2004 ...... 4–18–2005 ...... S1947 .......... Drought ................................................ .......... 2 WY ................................... .................................................... 1–01–2004 ...... continuing ....... 8–18–2004 ...... 4–18–2005 ...... S1947 .......... Drought ................................................ .......... 2 KS .................................... Barber, Cloud, Cowley, Decatur, 

Geary, Gove, Harper, Republic, Scott, Sumner.

4–23–2004 ...... 5–29–2004 ...... 8–20–2004 ...... 4–20–2005 ...... S1948 .......... Hail, high winds, tornadoes, excessive 

rain, flooding.

10 29 

NE .................................... .................................................... 4–23–2004 ...... 5–29–2004 ...... 8–20–2004 ...... 4–20–2005 ...... S1948 .......... Hail, high winds, tornadoes, excessive 

rain, flooding.

.......... 5 

OK .................................... .................................................... 4–23–2004 ...... 5–29–2004 ...... 8–20–2004 ...... 4–20–2005 ...... S1948 .......... Hail, high winds, tornadoes, excessive 

rain, flooding.

.......... 5 

KS .................................... Cheyenne, Decatur, Ellis, 

Finney, Gove, Graham, Grant, Greeley, Hamilton, Haskell, Hodgman, Jewell, Kearny, Lane, Logan, Mitchell, Morton, Ness, Norton, Osborne, Phillips, Rawlins, Rooks, Russell, Scott, Seward, Sheridan, Sherman, Stanton, Stevens, Trego, Thomas, Wallace, Wichita.

4–07–2004 ...... 5–15–2004 ...... 8–20–2004 ...... 4–20–2005 ...... S1949 .......... Freezing conditions, drought ............... 34 13 

CO .................................... .................................................... 4–07–2004 ...... 5–15–2004 ...... 8–20–2004 ...... 4–20–2005 ...... S1949 .......... Freezing conditions, drought ............... .......... 6 
414 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

NE .................................... .................................................... 4–07–2004 ...... 5–15–2004 ...... 8–20–2004 ...... 4–20–2005 ...... S1949 .......... Freezing conditions, drought ............... .......... 8 OK .................................... .................................................... 4–07–2004 ...... 5–15–2004 ...... 8–20–2004 ...... 4–20–2005 ...... S1949 .......... Freezing conditions, drought ............... .......... 3 OH .................................... Allen, Athens, Carroll, 

Columbiana, Coshocton, Crawford, Cuyahoga, Fayette, Greene, Guernsey, Hancock, Henry, Hocking, Holmes, Jackson, Logan, Mahoning, Medina, Noble, Perry, Tuscarawas, Union, Wayne— Ashtabula, Defiance, Delaware, Erie, Fairfield, Geauga, Lake, Licking, Logan, Lorain, Lucas, Marion, Morgan, Muskingum, Ottawa, Paulding, Portage, Sandusky, Scioto, Seneca, Summit, Van Wert, Wood, Wyandot.

5–01–2004 ...... continuing ....... 8–27–2004 ...... 4–27–2005 ...... S1950 .......... Excessive rain, high winds, flooding, 

hail, tornado—Excessive moisture.

46 69 

IN ..................................... .................................................... 5–01–2004 ...... continuing ....... 8–27–2004 ...... 4–27–2005 ...... S1950 .......... Excessive rain, high winds, flooding, 

hail, tornado—Excessive moisture.

.......... 3 

KY .................................... .................................................... 5–01–2004 ...... continuing ....... 8–27–2004 ...... 4–27–2005 ...... S1950 .......... Excessive rain, high winds, flooding, 

hail, tornado—Excessive moisture.

.......... 2 

MI .................................... .................................................... 5–01–2004 ...... continuing ....... 8–27–2004 ...... 4–27–2005 ...... S1950 .......... Excessive rain, high winds, flooding, 

hail, tornado—Excessive moisture.

.......... 2 

PA .................................... .................................................... 5–01–2004 ...... continuing ....... 8–27–2004 ...... 4–27–2005 ...... S1950 .......... Excessive rain, high winds, flooding, 

hail, tornado—Excessive moisture.

.......... 5 

WV ................................... .................................................... 5–01–2004 ...... continuing ....... 8–27–2004 ...... 4–27–2005 ...... S1950 .......... Excessive rain, high winds, flooding, 

hail, tornado—Excessive moisture.

.......... 2 

WY ................................... Big Horn, Campbell, Converse, 

Crook, Goshen, Johnson, Lincoln, Niobrara, Platte, Sheridan, Weston.

1–01–2004 ...... continuing ....... 9–07–2004 ...... 5–09–2005 ...... S1951 .......... Drought ................................................ 11 10 

ID ..................................... .................................................... 1–01–2004 ...... continuing ....... 9–07–2004 ...... 5–09–2005 ...... S1951 .......... Drought ................................................ .......... 3 
415 

MT .................................... .................................................... 1–01–2004 ...... continuing ....... 9–07–2004 ...... 5–09–2005 ...... S1951 .......... Drought ................................................ .......... 4 NE .................................... .................................................... 1–01–2004 ...... continuing ....... 9–07–2004 ...... 5–09–2005 ...... S1951 .......... Drought ................................................ .......... 3 SD .................................... .................................................... 1–01–2004 ...... continuing ....... 9–07–2004 ...... 5–09–2005 ...... S1951 .......... Drought ................................................ .......... 5 UT .................................... .................................................... 1–01–2004 ...... continuing ....... 9–07–2004 ...... 5–09–2005 ...... S1951 .......... Drought ................................................ .......... 1 ID ..................................... Contra Costa, Merced ................ 3–01–2004 ...... 4–30–2004 ...... 9/14/04 ............ 5–16–2005 ...... S1952 .......... Drought ................................................ 2 14 TX .................................... Brazos, Burleson, Robertson ..... 5–13–2004 ...... 5–13–2004 ...... 9–14–2004 ...... 5–16–2005 ...... S1953 .......... Excessive rain, flash flooding, flooding, high winds, tornado. 3 8 UT .................................... Box Elder, Cache, Carbon, 

Emery, Garfield, Grand, Iron, Juab, Kane, Millard, Piute, Rich, Salt Lake, San Juan, Sanpete, Sevier, Summit, Tooele, Washington, Wayne.

1–01–2004 ...... continuing ....... 9–14–2004 ...... 5–16–2005 ...... S1954 .......... Drought, wind, hail, heat, grasshoppers, Mormon crickets. 20 9 

AZ .................................... .................................................... 1–01–2004 ...... continuing ....... 9–14–2004 ...... 5–16–2005 ...... S1954 .......... Drought, wind, hail, heat, grasshoppers, Mormon crickets. .......... 4 CO .................................... .................................................... 1–01–2004 ...... continuing ....... 9–14–2004 ...... 5–16–2005 ...... S1954 .......... Drought, wind, hail, heat, grasshoppers, Mormon crickets. .......... 6 ID ..................................... .................................................... 1–01–2004 ...... continuing ....... 9–14–2004 ...... 5–16–2005 ...... S1954 .......... Drought, wind, hail, heat, grasshoppers, Mormon crickets. .......... 4 NV .................................... .................................................... 1–01–2004 ...... continuing ....... 9–14–2004 ...... 5–16–2005 ...... S1954 .......... Drought, wind, hail, heat, grasshoppers, Mormon crickets. .......... 3 NM ................................... .................................................... 1–01–2004 ...... continuing ....... 9–14–2004 ...... 5–16–2005 ...... S1954 .......... Drought, wind, hail, heat, grasshoppers, Mormon crickets. .......... 1 WY ................................... .................................................... 1–01–2004 ...... continuing ....... 9–14–2004 ...... 5–16–2005 ...... S1954 .......... Drought, wind, hail, heat, grasshoppers, Mormon crickets. .......... 3 TN .................................... Lauderdale ................................. 5–01–2004 ...... continuing ....... 9–17–2004 ...... 5–17–2005 ...... S1955 .......... Tornadoes, severe thunderstorms, 

strong winds, excessive rain, flooding, hail.

1 4 

AR .................................... .................................................... 5–01–2004 ...... continuing ....... 9–17–2004 ...... 5–17–2005 ...... S1955 .......... Tornadoes, severe thunderstorms, 

strong winds, excessive rain, flooding, hail.

.......... 1 
416 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

LA .................................... Acadia, Allen, Avoyelles, Beauregard, Bienville, Caldwell, 

Catahoula, Claiborne, East Carroll, East Feliciana, Evangeline, Franklin, Grant, Iberville, Jackson, Jefferson Davis, La Salle, Lafayette, Lincoln, Madison, Morehouse, Natchitoches, Ouachita, Plaquemines, Pointe Coupee, Rapides, Richland, Sabine, St. Bernard, St. Charles, St. James, St. John the Baptist, St. Landry, Tensas, Union, Vermilion, Vernon, Webster, West Baton Rouge, West Carroll.

5–01–2004 ...... 6–30–2004 ...... 9–17–2004 ...... 5–17–2005 ...... S1956 .......... Excessive rainfall ................................ 40 19 

AR .................................... .................................................... 5–01–2004 ...... 6–30–2004 ...... 9–17–2004 ...... 5–17–2005 ...... S1956 .......... Excessive rainfall ................................ .......... 5 MS ................................... .................................................... 5–01–2004 ...... 6–30–2004 ...... 9–17–2004 ...... 5–17–2005 ...... S1956 .......... Excessive rainfall ................................ .......... 7 TX .................................... .................................................... 5–01–2004 ...... 6–30–2004 ...... 9–17–2004 ...... 5–17–2005 ...... S1956 .......... Excessive rainfall ................................ .......... 3 IA ..................................... Jefferson, Lyon, O’Brien, Taylor 2–01–2004 ...... continuing ....... 9–17–2004 ...... 5–17–2005 ...... S1957 .......... Winter snow load, excessive rainfall, 

high winds, hail, tornadoes.

4 18 

MN ................................... .................................................... 2–01–2004 ...... continuing ....... 9–17–2004 ...... 5–17–2005 ...... S1957 .......... Winter snow load, excessive rainfall, 

high winds, hail, tornadoes.

.......... 2 

MO ................................... .................................................... 2–01–2004 ...... continuing ....... 9–17–2004 ...... 5–17–2005 ...... S1957 .......... Winter snow load, excessive rainfall, 

high winds, hail, tornadoes.

.......... 2 

SD .................................... .................................................... 2–01–2004 ...... continuing ....... 9–17–2004 ...... 5–17–2005 ...... S1957 .......... Winter snow load, excessive rainfall, 

high winds, hail, tornadoes.

.......... 2 

TX .................................... Briscoe ....................................... 6–21–2004 ...... 6–22–2004 ...... 9–17–2004 ...... 5–17–2005 ...... S1958 .......... Excessive rain, hail, high winds, 

lightning, tornadoes.

1 6 

AR .................................... Ashley, Bradley, Calhoun, Drew 5–01–2004 ...... 6–30–2004 ...... 9–21–2004 ...... 5–23–2005 ...... S1959 .......... Hail, high winds .................................. 4 7 LA .................................... Ashley, Bradley, Calhoun, Drew 5–01–2004 ...... 6–30–2004 ...... 9–21–2004 ...... 5–23–2005 ...... S1959 .......... Hail, high winds .................................. .......... 1 
417 

MN ................................... Lake of the Woods, Marshall, 

Roseau.

5–11–2004 ...... continuing ....... 9–21–2004 ...... 5–23–2005 ...... S1960 .......... Excessive rain, flooding ...................... 3 5 

ND .................................... .................................................... 5–11–2004 ...... continuing ....... 9–21–2004 ...... 5–23–2005 ...... S1960 .......... Excessive rain, flooding ...................... .......... 2 GA .................................... Appling, Atkinson, Bacon, 

Baker, Ben Hill, Berrien, Bibb, Bleckley, Brantley, Brooks, Bulloch, Burke, Butts, Calhoun, Camden, Charlton, Chatham, Chattahoochee, Clinch, Coffee, Colquitt, Crawford, Decatur, Dodge, Dooly, Dougherty, Echols, Emanuel, Evans, Glascock, Grady, Greene, Hancock, Harris, Henry, Houston, Jeff Davis, Jefferson, Jenkins, Johnson, Lamar, Lanier, Laurens, Lee, Long, Lowndes, Macon, Marion, Miller, Mitchell, Monroe, Montgomery, Muscogee, Peach, Pierce, Pike, Pulaski, Schley, Seminole, Spalding, Stewart, Sumter, Talbot, Taliaferro, Tattnall, Taylor, Telfair, Terrell, Thomas, Tift, Toombs, Treutlen, Turner, Twiggs, Upson, Ware, Washington, Wayne, Webster, Wheeler, Wilcox, Wilkinson, Worth.

9–04–2004 ...... 9–07–2004 ...... 9–30–2004 ...... 6–01–2005 ...... S1961 .......... Hurricane Frances ............................... 83 33 

AL .................................... .................................................... 9–04–2004 ...... 9–07–2004 ...... 9–30–2004 ...... 6–01–2005 ...... S1961 .......... Hurricane Frances ............................... .......... 5 FL ..................................... .................................................... 9–04–2004 ...... 9–07–2004 ...... 9–30–2004 ...... 6–01–2005 ...... S1961 .......... Hurricane Frances ............................... .......... 9 SC .................................... .................................................... 9–04–2004 ...... 9–07–2004 ...... 9–30–2004 ...... 6–01–2005 ...... S1961 .......... Hurricane Frances ............................... .......... 4 GA .................................... Candler, Cook, Crisp, Irwin ....... 9–04–2004 ...... 9–07–2004 ...... 10–28–2004 .... .......................... S1961, 

Amendment 1.

Hurricane Frances ............................... 4 ..........

NC .................................... Camden, Currituck, Hertford, 

New Hanover, Pender, Pasquotank.

8–14–2004 ...... 8–14–2004 ...... 9–30–2004 ...... 6–01–2005 ...... S1962 .......... Hurricane Charley ................................ 6 13 
418 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2004—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

VA .................................... .................................................... 8–14–2004 ...... 8–14–2004 ...... 9–30–2004 ...... 6–01–2005 ...... S1962 .......... Hurricane Charley ................................ .......... 4 TX .................................... Cameron .................................... 5–08–2004 ...... 5–08–2004 ...... 9–30–2004 ...... 6–01–2005 ...... S1963 .......... Excessive rain, flooding ...................... 1 2 TX .................................... Bailey ......................................... 6–16–2004 ...... 6–16–2004 ...... 9–30–2004 ...... 6–01–2005 ...... S1964 .......... Excessive rain, flash flooding, hail 

high winds, lightning.

1 4 

NM ................................... .................................................... 6–16–2004 ...... 6–16–2004 ...... 9–30–2004 ...... 6–01–2005 ...... S1964 .......... Excessive rain, flash flooding, hail 

high winds, lightning.

.......... 2 

TOTAL ACTIVE ..... .................................................... .......................... .......................... .......................... .......................... ...................... .............................................................. 1,565 2011 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

ND ................................ Barnes, Benson, Cass, Griggs, 

Kidder, LaMoure, Logan, McLean, Sheridan, Steele, Stutsman, Traill, Wells, Williams.

1–01–2004 ...... continuing ....... 1–10–2005 ...... 9–12–2005 ...... S1940, 

Amendment 1.

Drought, late season frost, high 

winds, excessive rainfall, flooding, ground saturation, early fall frost (August).

14 ..........

MN ............................... ........................................................ 1–01–2004 ...... continuing ....... 1–10–2005 ...... 9–12–2005 ...... S1940, 

Amendment 1.

.............................................................. .......... 2 

TX ................................ Zavala ............................................ 4–04–2004 ...... 5–15–2004 ...... 10–01–2004 .... 6–01–2005 ...... S1966 .......... Excessive rain, hail ............................. 1 7 NV ................................ Entire State ................................... 1–01–2004 ...... continuing ....... 10–12–2004 .... 6–13–2005 ...... S1967 .......... Drought, related insect infestations ... 17 ..........AZ ................................ ........................................................ 1–01–2004 ...... continuing ....... 10–12–2004 .... 6–13–2005 ...... S1967 .......... Drought, related insect infestations ... .......... 1 CA ................................ ........................................................ 1–01–2004 ...... continuing ....... 10–12–2004 .... 6–13–2005 ...... S1967 .......... Drought, related insect infestations ... .......... 10 ID ................................. ........................................................ 1–01–2004 ...... continuing ....... 10–12–2004 .... 6–13–2005 ...... S1967 .......... Drought, related insect infestations ... .......... 3 OR ................................ ........................................................ 1–01–2004 ...... continuing ....... 10–12–2004 .... 6–13–2005 ...... S1967 .......... Drought, related insect infestations ... .......... 3 UT ................................ ........................................................ 1–01–2004 ...... continuing ....... 10–12–2004 .... 6–13–2005 ...... S1967 .......... Drought, related insect infestations ... .......... 7 
419 

MN ............................... Aitkin, Becker, Beltrami, Carlton, 

Cass, Chippewa, Chisago, Clearwater, Cook, Crow Wing, Douglas, Hubbard, Isanti, Itasca, Kanabec, Kittson, Koochiching, Mahnomen, Marshall, Norman, Pennington, Pine, Polk, Red Lake, Roseau, St. Louis, Swift, Todd, Wadena.

8–19–2004 ...... 8–21–2004 ...... 10–12–2004 .... 6–13–2005 ...... S1968 .......... Freezing temperatures ......................... 29 18 

ND ................................ ........................................................ 8–19–2004 ...... 8–21–2004 ...... 10–12–2004 .... 6–13–2005 ...... S1968 .......... Freezing temperatures ......................... .......... 5 WI ................................ ........................................................ 8–19–2004 ...... 8–21–2004 ...... 10–12–2004 .... 6–13–2005 ...... S1968 .......... Freezing temperatures ......................... .......... 3 TX ................................ Swisher .......................................... 4–01–2003 ...... continuing ....... 10–12–2004 .... 6–13–2005 ...... S1969 .......... Drought ................................................ 1 6 CA ................................ El Dorado, Fresno, San Luis 

Obispo.

7–01–2003 ...... 6–30–2004 ...... 10–12–2004 .... 6–13–2005 ...... S1970 .......... Drought ................................................ 3 14 

NV ................................ ........................................................ 7–01–2003 ...... 6–30–2004 ...... 10–12–2004 .... 6–13–2005 ...... S1970 .......... Drought ................................................ .......... 1 KS ................................ Meade ............................................ 1–01–2004 ...... continuing ....... 10–28–2004 .... 6–28–2005 ...... S1971 .......... (1) Drought ..........................................

(2) Freezing conditions .......................

1 1 

MT ................................ Beaverhead, Big Horn, 

Broadwater, Carbon, Carter, Custer, Dawson, Fallon, Glacier, Golden Valley, Jefferson, Judith Basin, Lake, Lewis & Clark , Liberty, Madison, McCone, Meagher, Mineral, Musselshell, Park, Powder River, Powell, Prairie, Rosebud, Sanders, Silver Bow, Stillwater, Sweet Grass, Teton, Treasure, Wheatland, Wibaux, Yellowstone.

1–01–2004 ...... continuing ....... 10–28–2004 .... 6–28–2005 ...... S1972 .......... Drought ................................................ 34 18 

ID ................................. ........................................................ 1–01–2004 ...... continuing ....... 10–28–2004 .... 6–28–2005 ...... S1972 .......... Drought ................................................ .......... 6 ND ................................ ........................................................ 1–01–2004 ...... continuing ....... 10–28–2004 .... 6–28–2005 ...... S1972 .......... Drought ................................................ .......... 6 SD ................................ ........................................................ 1–01–2004 ...... continuing ....... 10–28–2004 .... 6–28–2005 ...... S1972 .......... Drought ................................................ .......... 2 WY ............................... ........................................................ 1–01–2004 ...... continuing ....... 10–28–2004 .... 6–28–2005 ...... S1972 .......... Drought ................................................ .......... 5 MT ................................ Garfield .......................................... 1–01–2004 ...... continuing ....... 2–28–2005 ...... 10–28–2005 .... S1972, 

Amendment 1.

Drought ................................................ 1 1 

NJ ................................. Bergen, Burlington, Camden, 

Ocean.

6–01–2004 ...... continuing ....... 10–28–2004 .... 6–28–2005 ...... S1973 .......... Hail, excessive rain ............................. 4 7 

NY ................................ ........................................................ 6–01–2004 ...... continuing ....... 10–28–2004 .... 6–28–2005 ...... S1973 .......... Hail, excessive rain ............................. .......... 2 PA ................................ ........................................................ 6–01–2004 ...... continuing ....... 10–28–2004 .... 6–28–2005 ...... S1973 .......... Hail, excessive rain ............................. .......... 2 
420 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

MT ................................ Carter, Fallon, Liberty, Prairie ....... 5–01–2004 ...... 6–30–2004 ...... 11–08–2004 .... 7–08–2005 ...... S1974 .......... Late Spring Frosts; Frost .................... 4 10 ND ................................ ........................................................ 5–01–2004 ...... 6–30–2004 ...... 11–08–2004 .... 7–08–2005 ...... S1974 .......... Late Spring Frosts; Frost .................... .......... 3 SD ................................ ........................................................ 5–01–2004 ...... 6–30–2004 ...... 11–08–2004 .... 7–08–2005 ...... S1974 .......... Late Spring Frosts; Frost .................... .......... 2 WY ............................... ........................................................ 5–01–2004 ...... 6–30–2004 ...... 11–08–2004 .... 7–08–2005 ...... S1974 .......... Late Spring Frosts; Frost .................... .......... 1 MT ................................ Carter ............................................. 4–01–2004 ...... continuing ....... 11–08–2004 .... 7–08–2005 ...... S1975 .......... High Winds .......................................... 1 3 SD ................................ ........................................................ 4–01–2004 ...... continuing ....... 11–08–2004 .... 7–08–2005 ...... S1975 .......... High Winds .......................................... .......... 2 WY ............................... ........................................................ 4–01–2004 ...... continuing ....... 11–08–2004 .... 7–08–2005 ...... S1975 .......... High Winds .......................................... .......... 1 TX ................................ Wilbarger ....................................... 6–02–2004 ...... 6–08–2004 ...... 11–08–2004 .... 7–08–2005 ...... S1976 .......... Excessive rain, hail, high winds ......... 1 5 OK ................................ ........................................................ 6–02–2004 ...... 6–08–2004 ...... 11–08–2004 .... 7–08–2005 ...... S1976 .......... Excessive rain, hail, high winds ......... .......... 2 TX ................................ Wise ............................................... 6–06–2004 ...... 6–11–2004 ...... 11–08–2004 .... 7–08–2005 ...... S1977 .......... Excessive rain, flash flooding, flooding, high winds, lightning. 1 6 TN ................................ Bradley, Cannon, Cocke, Giles, 

Greene, Hamblen, Hamilton, Lawrence, Lincoln, Loudon, Macon, Marion, McMinn, Meigs, Polk, Rhea, Roane, Rutherford, Sequatchie, Unicoi, Washington, Wayne.

9–01–2004 ...... continuing ....... 11–17–2004 .... 7–18–2005 ...... S1978 .......... Storm, including remnants of Hurricanes Frances and Ivan. 22 35 

AL ................................ ........................................................ 9–01–2004 ...... continuing ....... 11–17–2004 .... 7–18–2005 ...... S1978 .......... Storm, including remnants of Hurricanes Frances and Ivan. .......... 4 GA ................................ ........................................................ 9–01–2004 ...... continuing ....... 11–17–2004 .... 7–18–2005 ...... S1978 .......... Storm, including remnants of Hurricanes Frances and Ivan. .......... 6 KY ................................ ........................................................ 9–01–2004 ...... continuing ....... 11–17–2004 .... 7–18–2005 ...... S1978 .......... Storm, including remnants of Hurricanes Frances and Ivan. .......... 2 NC ................................ ........................................................ 9–01–2004 ...... continuing ....... 11–17–2004 .... 7–18–2005 ...... S1978 .......... Storm, including remnants of Hurricanes Frances and Ivan. .......... 5 WA ............................... Adams, Benton, Franklin, Grant, 

Spokane, Walla Walla, Yakima.

5–07–2004 ...... 6–30–2004 ...... 11–17–2004 .... 7–18–2005 ...... S1979 .......... Various disasters, including: Excessive rain, hail, high winds, tornado, lightning, flash flooding,. 7 13 

ID ................................. ........................................................ 5–07–2004 ...... 6–30–2004 ...... 11–17–2004 .... 7–18–2005 ...... S1979 .......... Various disasters, including: Excessive rain, hail, high winds, tornado, lightning, flash flooding,. .......... 3 
421 

OR ................................ ........................................................ 5–07–2004 ...... 6–30–2004 ...... 11–17–2004 .... 7–18–2005 ...... S1979 .......... Various disasters, including: Excessive rain, hail, high winds, tornado, lightning, flash flooding,. .......... 2 OK ................................ Grant, Kay ...................................... 4–21–2004 ...... 6–02–2004 ...... 11–17–2004 .... 7–18–2005 ...... S1980 .......... Hail, high wind ................................... 2 4 KS ................................ ........................................................ 4–21–2004 ...... 6–02–2004 ...... 11–17–2004 .... 7–18–2005 ...... S1980 .......... Hail, high wind ................................... .......... 3 NE ................................ Boyd, Brown, Holt, Keya Paha, 

Rock.

1–01–2004 ...... continuing ....... 11–17–2004 .... 7–18–2005 ...... S1981 .......... Drought ................................................ 5 7 

SD ................................ ........................................................ 1–01–2004 ...... continuing ....... 11–17–2004 .... 7–18–2005 ...... S1981 .......... Drought ................................................ .......... 4 NE ................................ Blaine, Cherry, Hayes, Hitchock, 

Thomas.

(1) 01/01/04 ....(2) 05/14/04 ....

(1) continuing(2) 05/22/04 ....

11–17–2004 .... 7–18–2005 ...... S1982 .......... (1) Drought ..........................................

(2) Frost ..............................................

1 15 

KS ................................ ........................................................ (1) 01/01/04 ....

(2) 05/14/04 ....

(1) continuing(2) 05/22/04 ....

11–17–2004 .... 7–18–2005 ...... S1982 .......... (1) Drought ..........................................

(2) Frost ..............................................

.......... 1 

SD ................................ ........................................................ (1) 01/01/04 ....

(2) 05/14/04 ....

(1) continuing(2) 05/22/04 ....

11–17–2004 .... 7–18–2005 ...... S1982 .......... (1) Drought ..........................................

(2) Frost ..............................................

.......... 4 

CA ................................ Solano, Yolo ................................... 3–01–2004 ...... 4–30–2004 ...... 11–22–2004 .... 7–22–2005 ...... S1983 .......... Record & severe, high temperatures, 

high winds.

1 7 

CA ................................ Tulare ............................................. 3–01–2004 ...... 8–31–2004 ...... 11–22–2004 .... 7–22–2005 ...... S1984 .......... Excessive heat ..................................... 1 4 MT ................................ Fallon, Liberty, Sanders ................. 7–01–2004 ...... continuing ....... 11–22–2004 .... 7–22–2005 ...... S1985 .......... Insects ................................................. 3 13 ID ................................. ........................................................ 7–01–2004 ...... continuing ....... 11–22–2004 .... 7–22–2005 ...... S1985 .......... Insects ................................................. .......... 2 ND ................................ ........................................................ 7–01–2004 ...... continuing ....... 11–22–2004 .... 7–22–2005 ...... S1985 .......... Insects ................................................. .......... 3 SD ................................ ........................................................ 7–01–2004 ...... continuing ....... 11–22–2004 .... 7–22–2005 ...... S1985 .......... Insects ................................................. .......... 1 TN ................................ Chester, McNairy, Van Buren, 

White.

5–01–2004 ...... continuing ....... 11–22–2004 .... 7–22–2005 ...... S1986 .......... Excessive rain, flooding, high winds, 

lightning, wet conditions.

4 10 

MS ............................... ........................................................ 5–01–2004 ...... continuing ....... 11–22–2004 .... 7–22–2005 ...... S1986 .......... Excessive rain, flooding, high winds, 

lightning, wet conditions.

.......... 1 

WA ............................... Spokane, Whitman ......................... 8–02–2004 ...... 8–02–2004 ...... 11–22–2004 .... 7–22–2005 ...... S1987 .......... Adverse weather: Severe thunderstorm 

with high winds, hail, lightning.

2 8 

ID ................................. ........................................................ 8–02–2004 ...... 8–02–2004 ...... 11–22–2004 .... 7–22–2005 ...... S1987 .......... Adverse weather: Severe thunderstorm 

with high winds, hail, lightning.

.......... 5 

WI ................................ Ashland, Bayfield, Door, Douglas, 

Iron, Oconto.

3–01–2004 ...... 7–03–2004 ...... 11–22–2004 .... 7–22–2005 ...... S1988 .......... Excessive rain, flooding, below normal 

temperatures.

6 12 

MI ................................ ........................................................ 3–01–2004 ...... 7–03–2004 ...... 11–22–2004 .... 7–22–2005 ...... S1988 .......... Excessive rain, flooding, below normal 

temperatures.

.......... 1 

MN ............................... ........................................................ 3–01–2004 ...... 7–03–2004 ...... 11–22–2004 .... 7–22–2005 ...... S1988 .......... Excessive rain, flooding, below normal 

temperatures.

.......... 3 

TX ................................ Hall ................................................ 8–12–2004 ...... 8–12–2004 ...... 11–23–2004 .... 7–25–2005 ...... S1989 .......... Excessive rain, hail, high winds ......... 1 6 TX ................................ Tarrant ........................................... 6–01–2004 ...... 6–09–2004 ...... 11–23–2004 .... 7–25–2005 ...... S1990 .......... Excessive rain, flash flooding, flooding, high winds, lightning. 1 6 OR ................................ Umatilla ......................................... 5–01–2004 ...... 6–15–2004 ...... 12–03–2004 .... 8–03–2005 ...... S1991 .......... Excessive rainfall, hail ........................ 1 4 WA ............................... ........................................................ 5–01–2004 ...... 6–15–2004 ...... 12–03–2004 .... 8–03–2005 ...... S1991 .......... Excessive rainfall, hail ........................ .......... 3 
422 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

SD ................................ Brookings, Codington, Hamlin ....... 1–01–2004 ...... continuing ....... 12–03–2004 .... 8–03–2005 ...... S1992 .......... Drought, cool growing season, early 

frost.

3 7 

MN ............................... ........................................................ 1–01–2004 ...... continuing ....... 12–03–2004 .... 8–03–2005 ...... S1992 .......... Drought, cool growing season, early 

frost.

.......... 2 

TX ................................ Uvalde ............................................ 6–18–2004 ...... 6–30–2004 ...... 12–03–2004 .... 8–03–2005 ...... S1993 .......... Excessive rain, flash flooding, flooding, hail. 1 8 TX ................................ Deaf Smith .................................... 8–12–2004 ...... 9–22–2004 ...... 12–03–2004 .... 8–03–2005 ...... S1994 .......... (1) Hail ................................................

(2) Excessive rain, hail .......................

1 5 

NM ............................... ........................................................ 8–12–2004 ...... 9–22–2004 ...... 12–03–2004 .... 8–03–2005 ...... S1994 .......... (1) Hail ................................................

(2) Excessive rain, hail .......................

.......... 2 

TX ................................ Austin, Washington ....................... 6–15–2004 ...... continuing ....... 12–03–2004 .... 8–03–2005 ...... S1995 .......... Excessive rain, flash flooding, flooding, hail, high winds, wind shear. 2 9 TX ................................ Culberson ....................................... 1–01–2004 ...... continuing ....... 12–03–2004 .... 8–03–2005 ...... S1996 .......... Drought ................................................ 1 3 NM ............................... ........................................................ 1–01–2004 ...... continuing ....... 12–03–2004 .... 8–03–2005 ...... S1996 .......... Drought ................................................ .......... 2 TX ................................ Bailey ............................................. 10–05–2004 .... 10–05–2004 .... 12–03–2004 .... 8–03–2005 ...... S1997 .......... Excessive rain, flash flooding, flooding, hail, high winds, lightning. 1 4 NM ............................... ........................................................ 10–05–2004 .... 10–05–2004 .... 12–03–2004 .... 8–03–2005 ...... S1997 .......... Excessive rain, flash flooding, flooding, hail, high winds, lightning. .......... 2 WY ............................... Albany, Hot Springs, Natrona, 

Washakie.

1–01–2004 ...... continuing ....... 12–03–2004 .... 8–03–2005 ...... S1998 .......... Drought ................................................ 4 1 

CO ................................ ........................................................ 1–01–2004 ...... continuing ....... 12–03–2004 .... 8–03–2005 ...... S1998 .......... Drought ................................................ .......... 2 TX ................................ Jeff Davis ....................................... 1–01–2003 ...... continuing ....... 12–06–2004 .... 8–08–2005 ...... S1999 .......... Drought, high winds, excessive temperatures. 1 6 VA ................................ Northampton .................................. 7/15/04 ............ continuing ....... 12–15–2004 .... 8–15–2005 ...... S2000 .......... Excessive Rain .................................... 1 1 TX ................................ Swisher .......................................... 6–21–2004 ...... 6–25–2004 ...... 12–15–2004 .... 8–15–2005 ...... S2001 .......... High winds, tornado ............................ 1 6 MI ................................ Isabella, Mecosta, Otsego ............. 8–19–2004 ...... 10–08–2004 .... 12–28–2004 .... 8–29–2005 ...... S2002 .......... Freeze .................................................. 3 15 MI ................................ Bay, Benzie, Grand Traverse, Isabella, Kalkaska, Lake, 

Leelanau, Manistee, Mason, Mecosta, Midland, Missaukee, Oceana, Osceola, Wexford.

7–01–2004 ...... 8–17–2004 ...... 12–28–2004 .... 8–29–2005 ...... S2003 .......... Drought ................................................ 15 13 
423 

MI ................................ Alcona, Alger, Alpena, Antrim, 

Baraga, Bay, Benzie, Berrien, Cass, Charlevoix, Cheboygan, Chippewa, Clare, Crawford, Delta, Dickinson, Emmet, Genesee, Gladwin, Gogebic, Grand Traverse, Gratiot, Hillsdale, Houghton, Huron, Ingham, Ionia, Iosco, Iron, Isabella, Jackson, Kalamazoo, Kalkaska, Kent, Keweenaw, Lake, Lapeer, Leelanau, Lenawee, Livingston, Luce, Mackinac, Macomb, Manistee, Marquette, Mason, Mecosta, Menominee, Midland, Missaukee, Monroe, Montcalm, Montmorency, Muskegon, Newaygo, Oakland, Oceana, Ogemaw, Ontonagon, Osceola, Oscoda, Otsego, Ottawa, Presque Isle, Roscommon, Saginaw, Sanilac, Schoolcraft, Shiawassee, St. Clair, St. Joseph, Tuscola, Van Buren, Washtenaw, Wayne, Wexford.

4–25–2004 ...... continuing ....... 12–28–2004 .... 8–29–2005 ...... S2004 .......... Excessive rainfall, hail, high winds, 

flooding.

76 7 

IN ................................. ........................................................ 4–25–2004 ...... continuing ....... 12–28–2004 .... 8–29–2005 ...... S2004 .......... Excessive rainfall, hail, high winds, 

flooding.

.......... 5 

OH ................................ ........................................................ 4–25–2004 ...... continuing ....... 12–28–2004 .... 8–29–2005 ...... S2004 .......... Excessive rainfall, hail, high winds, 

flooding.

.......... 3 

WI ................................ ........................................................ 4–25–2004 ...... continuing ....... 12–28–2004 .... 8–29–2005 ...... S2004 .......... Excessive rainfall, hail, high winds, 

flooding.

.......... 5 

NE ................................ Adams, Boone, Buffalo, Custer, 

Sherman, Dawson, Fillmore, Franklin, Furnas, Garfield, Gosper, Harlan, Kearney, Knox, Logan, Loup, Merrick, Nance, Nuckolls, Pawnee, Thayer, Valley, Webster, Wheeler.

1–01–2004 ...... continuing ....... 12–28–2004 .... 8–29–2005 ...... S2005 .......... Drought ................................................ 24 30 

KS ................................ ........................................................ 1–01–2004 ...... continuing ....... 12–28–2004 .... 8–29–2005 ...... S2005 .......... Drought ................................................ .......... 9 SD ................................ ........................................................ 1–01–2004 ...... continuing ....... 12–28–2004 .... 8–29–2005 ...... S2005 .......... Drought ................................................ .......... 3 
424 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

TX ................................ Presidio .......................................... 9–22–2004 ...... 9–22–2004 ...... 12–28–2004 .... 8–29–2005 ...... S2006 .......... Excessive rain, flash flooding, high 

winds.

1 3 

TX ................................ Cochran ......................................... 8–19–2004 ...... 8–19–2004 ...... 12–28–2004 .... 8–29–2005 ...... S2007 .......... Excessive rain, hail, high winds ......... 1 5 NM ............................... ........................................................ 8–19–2004 ...... 8–19–2004 ...... 12–28–2004 .... 8–29–2005 ...... S2007 .......... Excessive rain, hail, high winds ......... .......... 2 CA ................................ Tehama .......................................... 3–12–2004 ...... 3–31–2004 ...... 12–28–2004 .... 8–29–2005 ...... S2008 .......... Hot, dry, windy, weather ..................... 1 6 CO ................................ Bent, Moffat .................................. 1–01–2004 ...... continuing ....... 1–10–2005 ...... 9–12–2005 ...... S2009 .......... Bent: High winds, heavy rain Moffat: 

Drought, freeze (part).

2 7 

UT ................................ ........................................................ .......................... .......................... 1–10–2005 ...... 9–12–2005 ...... S2009 .......... Drought, freeze .................................... .......... 2 WY ............................... ........................................................ .......................... .......................... 1–10–2005 ...... 9–12–2005 ...... S2009 .......... Drought, freeze .................................... .......... 2 TX ................................ Gonzales ........................................ 11–15–2004 .... continuing ....... 1–10–2005 ...... 9–12–2005 ...... S2010 .......... Excessive rain, flooding ...................... 1 8 MS ............................... Alcorn, Amite, Bolivar, Calhoun, 

Carroll, Chickasaw, Clarke, Clay, Coahoma, Covington, George, Grenada, Hinds, Holmes, Itawamba, Jackson, Jefferson Davis, Jones, Lamar, Lauderdale, Lawrence, Lee, Marion, Monroe, Montgomery, Oktibbeha, Perry, Pike, Pontotoc, Prentiss, Quitman, Simpson, Smith, Tunica, Union, Walthall, Webster, Wilkinson.

5–01–2004 ...... 9–20–2004 ...... 1–10–2005 ...... 9–12–2005 ...... S2011 .......... Excessive rainfall, ooding, flash flooding, high winds, tornadoes, hail 

and lightning that occurred from 05/01/04–07/31/04 AND due to Hurricane Ivan 09/13/04–09/20/04 .

38 39 

AL ................................ ........................................................ 5–01–2004 ...... 10–10–2004 .... 1–10–2005 ...... 9–12–2005 ...... S2011 .......... Excessive rainfall, flooding—Hurricane Ivan. .......... 6 AR ................................ ........................................................ 5–01–2004 ...... 10–10–2004 .... 1–10–2005 ...... 9–12–2005 ...... S2011 .......... Excessive rainfall, flooding—Hurricane Ivan. .......... 5 LA ................................ ........................................................ 5–01–2004 ...... 10–10–2004 .... 1–10–2005 ...... 9–12–2005 ...... S2011 .......... Excessive rainfall, flooding—Hurricane Ivan. .......... 6 TN ................................ ........................................................ 5–01–2004 ...... 10–10–2004 .... 1–10–2005 ...... 9–12–2005 ...... S2011 .......... Excessive rainfall, flooding—Hurricane Ivan. .......... 3 TX ................................ Taylor ............................................. 10–03–2004 .... 11–18–2004 .... 1–10–2005 ...... 9–12–2005 ...... S2012 .......... Excessive rain ..................................... 1 6 TX ................................ Martin ............................................ 8–01–2004 ...... 8–31–2004 ...... 1–10–2005 ...... 9–12–2005 ...... S2013 .......... Record-breaking cool weather ............ 1 7 TX ................................ Bosque ........................................... 4–01–2004 ...... continuing ....... 1–10–2005 ...... 9–12–2005 ...... S2014 .......... Excessive rain ..................................... 1 7 
425 

TX ................................ Terrell ............................................. 7–01–2004 ...... continuing ....... 1–10–2005 ...... 9–12–2005 ...... S2015 .......... Excessive rain, flash flooding, flooding. 1 4 TX ................................ Caldwell ......................................... 10–01–2004 .... continuing ....... 1–10–2005 ...... 9–12–2005 ...... S2016 .......... Excessive rain, flash flooding ............. 1 6 TX ................................ Castro ............................................ 6–01–2004 ...... 8–31–2004 ...... 1–10–2005 ...... 9–12–2005 ...... S2017 .......... Hailstorms ........................................... 1 6 OR ................................ Coos ............................................... 1–01–2004 ...... continuing ....... 1–10–2005 ...... 9–12–2005 ...... S2018 .......... Drought ................................................ 1 2 OH ................................ Athens, Belmont, Guernsey, Harrison, Hocking, Jackson, Jefferson, Monroe, Noble, Perry, 

Scioto, Vinton, Washington.

9–08–2004 ...... 9–26–2004 ...... 1–10–2005 ...... 9–12–2005 ...... S2019 .......... Excessive rain, severe flooding, due 

to Hurricane remnants.

13 15 

KY ................................ ........................................................ 9–08–2004 ...... 9–26–2004 ...... 1–10–2005 ...... 9–12–2005 ...... S2019 .......... Excessive rain, severe flooding, due 

to Hurricane remnants.

.......... 2 

WV ............................... ........................................................ 9–08–2004 ...... 9–26–2004 ...... 1–10–2005 ...... 9–12–2005 ...... S2019 .......... Excessive rain, severe flooding, due 

to Hurricane remnants.

.......... 8 

CA ................................ Alpine, Amador, Calaveras, Inyo, 

Kings, Lake, Lassen, Mariposa, Mendocino, Mono, Monterey, Napa, Nevada, Orange, Plumas, San Benito, Santa Barbara, Santa Clara, Sierra, Sonoma, Tulare, Tuolumne, Yolo, Yuba.

1–01–2004 ...... continuing ....... 1–19–2005 ...... 9–19–2005 ...... S2020 .......... Drought ................................................ 24 29 

NV ................................ ........................................................ 1–01–2004 ...... continuing ....... 1–19–2005 ...... 9–19–2005 ...... S2020 .......... Drought ................................................ .......... 7 ID ................................. Adams, Benewah, Blaine, Camas, 

Clearwater, Kootenai, Lewis, Nez Perce, Twin Falls, Washington.

(1) 01/01/04 ....(2) 07/15/04 ....(3) 08/01/04 ....

(1) continuing(2) 09/01/04 ....(3) 09/01/04 ....

1–19–2005 ...... 9–19–2005 ...... S2021 .......... (1) Drought ..........................................

(2) Excessive Moisture, .......................(3) High winds ....................................

10 18 

MT ................................ ........................................................ (1) 01/01/04 ....

(2) 07/15/04 ....(3) 08/01/04 ....

(1) continuing(2) 09/01/04 ....(3) 09/01/04 ....

1–19–2005 ...... 9–19–2005 ...... S2021 .......... (1) Drought ..........................................

(2) Excessive Moisture, .......................(3) High winds ....................................

.......... 2 

NV ................................ ........................................................ (1) 01/01/04 ....

(2) 07/15/04 ....(3) 08/01/04 ....

(1) continuing(2) 09/01/04 ....(3) 09/01/04 ....

1–19–2005 ...... 9–19–2005 ...... S2021 .......... (1) Drought ..........................................

(2) Excessive Moisture, .......................(3) High winds ....................................

.......... 1 

OR ................................ ........................................................ (1) 01/01/04 ....

(2) 07/15/04 ....(3) 08/01/04 ....

(1) continuing(2) 09/01/04 ....(3) 09/01/04 ....

1–19–2005 ...... 9–19–2005 ...... S2021 .......... (1) Drought ..........................................

(2) Excessive Moisture, .......................(3) High winds ....................................

.......... 3 

WA ............................... ........................................................ (1) 01/01/04 ....

(2) 07/15/04 ....(3) 08/01/04 ....

(1) continuing(2) 09/01/04 ....(3) 09/01/04 ....

1–19–2005 ...... 9–19–2005 ...... S2021 .......... (1) Drought ..........................................

(2) Excessive Moisture, .......................(3) High winds ....................................

.......... 3 

ID ................................. Lincoln ........................................... 1–01–2004 ...... continuing ....... 2–09–2005 ...... 10–11–2005 .... S2021, 

Amendment 1.

Drought ................................................ 1 ..........
426 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

TX ................................ Coleman ......................................... 10–01–2004 .... continuing ....... 1–19–2005 ...... 9–19–2005 ...... S2022 .......... Excessive rain, high winds ................. 1 6 TX ................................ Gaines ............................................ 9–25–2004 ...... 9–30–2004 ...... 1–19–2005 ...... 9–19–2005 ...... S2023 .......... Excessive rain, flash flooding, high 

winds, lightning.

1 5 

NM ............................... ........................................................ 9–25–2004 ...... 9–30–2004 ...... 1–19–2005 ...... 9–19–2005 ...... S2023 .......... Excessive rain, flash flooding, high 

winds, lightning.

1 1 

TX ................................ Robertson ....................................... 11–23–2004 .... 11–23–2004 .... 1–19–2005 ...... 9–19–2005 ...... S2024 .......... Excessive rain, flash flooding, flooding, hail, high winds, tornado. 1 7 TX ................................ Hays ............................................... 10–01–2004 .... continuing ....... 1–19–2005 ...... 9–19–2005 ...... S2025 .......... Excessive rain, flash flooding ............. 1 5 TX ................................ Borden ........................................... 9–01–2004 ...... 10–15–2004 .... 1–19–2005 ...... 9–19–2005 ...... S2026 .......... Excessive rain ..................................... 1 7 TX ................................ Nolan ............................................. 10–01–2004 .... continuing ....... 1–19–2005 ...... 9–19–2005 ...... S2027 .......... Excessive rain, flash flooding ............. 1 7 TX ................................ Erath .............................................. 2–24–2004 ...... continuing ....... 1–19–2005 ...... 9–19–2005 ...... S2028 .......... Excessive rain, flooding, flash flooding, high winds, hail. 1 7 TX ................................ Howard ........................................... 10/22/04 ..........

09/25/04 ..........

10/22/04 ..........continuing .......

1–19–2005 ...... 9–19–2005 ...... S2029 .......... (1) Hail ................................................

(2) Excessive rain ...............................

1 7 

TX ................................ Dawson .......................................... 5/04/04 ............

06/19/04 ..........

continuing .......08/30/04 ..........

1–19–2005 ...... 9–19–2005 ...... S2030 .......... (1) Excessive rain ...............................

(2) Hail ................................................

1 6 

CO ................................ Huerfano, Las Animas, Rio Blanco 1–01–2004 ...... continuing ....... 2–02–2005 ...... 10–03–2005 .... S2031 .......... Drought ................................................ 3 11 NM ............................... ........................................................ 1–01–2004 ...... continuing ....... 2–02–2005 ...... 10–03–2005 .... S2031 .......... Drought ................................................ .......... 2 UT ................................ ........................................................ 1–01–2004 ...... continuing ....... 2–02–2005 ...... 10–03–2005 .... S2031 .......... Drought ................................................ .......... 1 TX ................................ Gray ............................................... 1–01–2004 ...... continuing ....... 2–02–2005 ...... 10–03–2005 .... S2032 .......... Excessive rain ..................................... 1 7 TX ................................ Hamilton ........................................ 10–13–2004 .... 10–24–2004 .... 2–02–2005 ...... 10–03–2005 .... S2033 .......... Excessive rain ..................................... 1 6 TX ................................ Hardin ............................................ 11–23–2004 .... 11–23–2004 .... 2–02–2005 ...... 10–03–2005 .... S2034 .......... Excessive rain, hail, high winds, tornado. 1 6 TX ................................ Bastrop .......................................... 10–01–2004 .... 11–24–2004 .... 2–02–2005 ...... 10–03–2005 .... S2035 .......... Excessive rain, flooding, tornado ........ 1 6 TX ................................ Garza ............................................. 10–09–2004 .... 10–09–2004 .... 2–02–2005 ...... 10–03–2005 .... S2036 .......... Hail ...................................................... 1 7 TX ................................ Coryell ............................................ 1–01–2004 ...... continuing ....... 2–02–2005 ...... 10–03–2005 .... S2037 .......... Excessive rain, flooding, hail .............. 1 5 TX ................................ Jackson .......................................... 11–20–2004 .... 111/21/04 ........ 2–02–2005 ...... 10–03–2005 .... S2038 .......... Excessive rain, flooding ...................... 1 6 TX ................................ Gillespie ......................................... 11–01–2004 .... 11–23–2004 .... 2–02–2005 ...... 10–03–2005 .... S2039 .......... Excessive rain, flooding ...................... 1 6 TX ................................ Guadalupe ..................................... 11–22–2004 .... 11–23–2004 .... 2–02–2005 ...... 10–03–2005 .... S2040 .......... Excessive rain ..................................... 1 6 TX ................................ Wharton ......................................... 11–21–2004 .... 11–28–2004 .... 2–02–2005 ...... 10–03–2005 .... S2041 .......... Excessive rain, flash flooding, flooding. 1 6 TX ................................ Newton ........................................... 11–23–2004 .... 11–24–2004 .... 2–02–2005 ...... 10–03–2005 .... S2042 .......... Flash flooding, tornadoes ................... 1 3 LA ................................ ........................................................ 11–23–2004 .... 11–24–2004 .... 2–02–2005 ...... 10–03–2005 .... S2042 .......... Flash flooding, tornadoes ................... .......... 4 TX ................................ Terry ............................................... 6–17–2004 ...... 10–05–2004 .... 2–02–2005 ...... 10–03–2005 .... S2043 .......... Hail ...................................................... 1 7 
427 

TX ................................ Wilson ............................................ 11–18–2004 .... 11–23–2004 .... 2–02–2005 ...... 10–03–2005 .... S2044 .......... Excessive rain ..................................... 1 5 TX ................................ Yoakum .......................................... 10–05–2004 .... 10–05–2004 .... 2–02–2005 ...... 10–03–2005 .... S2045 .......... Excessive rain, flash flooding, hail .... 1 4 NM ............................... ........................................................ 10–05–2004 .... 10–05–2004 .... 2–02–2005 ...... 10–03–2005 .... S2045 .......... Excessive rain, flash flooding, hail .... .......... 1 CA ................................ Placer .............................................

San Joaquin ...................................Ventura ..........................................

1–01–2004 ...... continuing ....... 2–09–2005 ...... 10–03–2005 .... S2046 .......... Drought ................................................ 3 1 

NV ................................ ........................................................ 1–01–2004 ...... continuing ....... 2–09–2005 ...... 10–11–2005 .... S2046 .......... Drought ................................................ .......... 1 GA ................................ Baker, Banks, Bartow, Calhoun, 

Catoosa, Clay, Coffee, Dade, Decatur, Dougherty, Early, Fannin, Franklin, Gilmer, Grady, Lee, Madison, Miller, Mitchell, Murray, Oconee, Randolph, Schley, Seminole, Stewart, Sumter, Terrell, Thomas, Towns, Union, Webster, Whitfield.

9–15–2005 ...... 9–17–2005 ...... 2–09–2005 ...... 10–11–2005 .... S2047 .......... Tropical Storms Frances, Ivan, Jeanne 32 42 

AL ................................ ........................................................ 9–15–2005 ...... 9–17–2005 ...... 2–09–2005 ...... 10–11–2005 .... S2047 .......... Tropical Storms Frances, Ivan, Jeanne .......... 6 FL ................................. ........................................................ 9–15–2005 ...... 9–17–2005 ...... 2–09–2005 ...... 10–11–2005 .... S2047 .......... Tropical Storms Frances, Ivan, Jeanne .......... 4 NC ................................ ........................................................ 9–15–2005 ...... 9–17–2005 ...... 2–09–2005 ...... 10–11–2005 .... S2047 .......... Tropical Storms Frances, Ivan, Jeanne .......... 2 SC ................................ ........................................................ 9–15–2005 ...... 9–17–2005 ...... 2–09–2005 ...... 10–11–2005 .... S2047 .......... Tropical Storms Frances, Ivan, Jeanne .......... 1 TN ................................ ........................................................ 9–15–2005 ...... 9–17–2005 ...... 2–09–2005 ...... 10–11–2005 .... S2047 .......... Tropical Storms Frances, Ivan, Jeanne .......... 4 NY ................................ Allegany, Cattaraugus, Chautauqua, Clinton, Columbia, 

Erie, Fulton, Genesee, Greene, Lewis, Monroe, Montgomery, Nassau, Niagara, Oneida, Ontario, Orange, Orleans, Saratoga, Schuyler, Seneca, Tompkins, Ulster, Washington, Wayne, Wyoming.

11–01–2003 .... continuing ....... 2–09–2005 ...... 10–11–2005 .... S2048 .......... (1) Multiple disasters related to severe storms, including excessive 

rain, hail, flooding, flash flooding, high winds.

(2) Freeze ............................................

25 29 

MA ............................... ........................................................ 11–01–2003 .... continuing ....... 2–09–2005 ...... 10–11–2005 .... S2048 .......... (1) Multiple disasters related to severe storms, including excessive 

rain, hail, flooding, flash flooding, high winds.

(2) Freeze ............................................

.......... 1 

NJ ................................. ........................................................ 11–01–2003 .... continuing ....... 2–09–2005 ...... 10–11–2005 .... S2048 .......... (1) Multiple disasters related to severe storms, including excessive 

rain, hail, flooding, flash flooding, high winds.

(2) Freeze ............................................

.......... 2 
428 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

PA ................................ ........................................................ 11–01–2003 .... continuing ....... 2–09–2005 ...... 10–11–2005 .... S2048 .......... (1) Multiple disasters related to severe storms, including excessive 

rain, hail, flooding, flash flooding, high winds.

(2) Freeze ............................................

.......... 5 

VT ................................ ........................................................ 11–01–2003 .... continuing ....... 2–09–2005 ...... 10–11–2005 .... S2048 .......... (1) Multiple disasters related to severe storms, including excessive 

rain, hail, flooding, flash flooding, high winds.

(2) Freeze ............................................

.......... 5 

TX ................................ Archer ............................................ 3–04–2004 ...... continuing ....... 2–09–2005 ...... 10–11–2005 .... S2049 .......... Excessive rain, flooding, high winds, 

lightning.

1 7 

TX ................................ Wichita ........................................... 3–04–2004 ...... continuing ....... 2–09–2005 ...... 10–11–2005 .... S2050 .......... Excessive rain, flash flooding, flooding, high winds, lightning, insect 

damage.

1 4 

OK ................................ ........................................................ 3–04–2004 ...... continuing ....... 2–09–2005 ...... 10–11–2005 .... S2050 .......... Excessive rain, flash flooding, flooding, high winds, lightning, insect 

damage.

.......... 2 

TX ................................ Scurry ............................................. 5–01–2004 ...... 10–31–2004 .... 2–09–2005 ...... 10–03–2005 .... S2051 .......... Excessive rain, hail, high winds, tornado. 1 7 TX ................................ Carson ........................................... 11–01–2004 .... 11–29–2004 .... 2–09–2005 ...... 10–03–2005 .... S2052 .......... Excessive rain, excessive snow, flash 

flooding.

1 8 

TX ................................ Kendall ........................................... 11–01–2004 .... 11–23–2004 .... 2–09–2005 ...... 10–03–2005 .... S2053 .......... Excessive rain, flash flooding ............. 1 6 TX ................................ Bexar .............................................. 11–19–2004 .... 11–23–2004 .... 2–09–2005 ...... 10–03–2005 .... S2054 .......... Excessive rain, flooding ...................... 1 7 TX ................................ Hudspeth ....................................... 10–15–2004 .... 10–11–2004 .... 2–09–2005 ...... 9–23–2005 ...... S2055 .......... Excessive rain ..................................... 1 4 NM ............................... ........................................................ 10–15–2004 .... 10–11–2004 .... 2–09–2005 ...... 9–24–2005 ...... S2055 .......... Excessive rain ..................................... .......... 1 TX ................................ Colorado ......................................... 11–21–2004 .... continuing ....... 2–09–2005 ...... 9–25–2005 ...... S2056 .......... Excessive rain, flooding ...................... 1 5 TX ................................ Comal ............................................ 10–01–2004 .... continuing ....... 2–09–2005 ...... 9–26–2005 ...... S2057 .......... Excessive rain, flash flooding ............. 1 5 TX ................................ Wilbarger ....................................... 11–13–2004 .... 11–22–2004 .... 2–09–2005 ...... 9–27–2005 ...... S2058 .......... Excessive rain ..................................... 1 5 OK ................................ ........................................................ 11–13–2004 .... 11–22–2004 .... 2–09–2005 ...... 9–28–2005 ...... S2058 .......... Excessive rain ..................................... .......... 2 WI ................................ Calumet, Clark, Door, Kewaunee, 

Manitowoc, Marinette, Milwaukee, Oconto, Waukesha, Waupaca.

3–01–2004 ...... 10–08–2004 .... 2–09–2005 ...... 9–29–2005 ...... S2059 .......... Excessive rain, flooding, fol. By dry 

spell, early frost.

10 24 
429 

MI ................................ ........................................................ 3–01–2004 ...... 10–08–2004 .... 2–09–2005 ...... 9–30–2005 ...... S2059 .......... Excessive rain, flooding, fol. By dry 

spell, early frost.

.......... 2 

CA ................................ Humboldt ....................................... 3–01–2004 ...... continuing ....... 2–24–2005 ...... 10–24–2005 .... S2060 .......... Drought ................................................ 1 4 NY ................................ Herkimer, Ontario, Otsego ............. 5–01–2004 ...... 10–10–2004 .... 2–24–2005 ...... 10–24–2005 .... S2061 .......... Excessive rain, flash Flooding, flooding. 3 16 CA ................................ Solano ............................................ 3–01–2004 ...... 9–23–2004 ...... 2–24–2005 ...... 10–24–2005 .... S2062 .......... Extremely low precipitation (Drought), 

warm spring temperatures, dry north winds.

1 5 

CA ................................ San Luis Obispo ............................ 4–23–2004 ...... 8–25–2004 ...... 2–24–2005 ...... 10–24–2005 .... S2063 .......... Extreme prolonged heat; Subsequent 

fruit drop, through 08/25/04.

1 4 

CA ................................ Marin ............................................. 1–01–2004 ...... continuing ....... 2–24–2005 ...... 10–24–2005 .... S2064 .......... Sporadic rain, high winds, excessive 

heat, unseasonable summer winds.

1 1 

NY ................................ Broome, Chemung, Chenango, Columbia, Cortland, Delaware, 

Dutchess, Genesee, Greene, Livingston, Niagara, Onondaga, Orange, Orleans, Oswego, Putnam, Schenectady, Schoharie, Sullivan, Tioga, Ulster, Westchester.

4–01–2004 ...... 12–31–2004 .... 2–28–2005 ...... 10–28–2005 .... S2065 .......... Excessive rain, flooding, flash flooding, high winds, hail. 22 20 

NY ................................ ........................................................ 4–01–2004 ...... 12–31–2004 .... 2–28–2005 ...... 10–28–2005 .... S2065 .......... Excessive rain, flooding, flash flooding, high winds, hail. .......... 2 NY ................................ ........................................................ 4–01–2004 ...... 12–31–2004 .... 2–28–2005 ...... 10–28–2005 .... S2065 .......... .............................................................. .......... 1 NY ................................ ........................................................ 4–01–2004 ...... 12–31–2004 .... 2–28–2005 ...... 10–28–2005 .... S2065 .......... .............................................................. .......... 2 NY ................................ ........................................................ 4–01–2004 ...... 12–31–2004 .... 2–28–2005 ...... 10–28–2005 .... S2065 .......... .............................................................. .......... 5 TN ................................ Lawrence, Wayne ........................... 10–18–2004 .... 10–19–2004 .... 2–28–2005 ...... 10–28–2005 .... S2066 .......... Storm, with heavy rains, lightning, 

winds, tornadoes, flooding.

2 6 

AL ................................ ........................................................ 10–18–2004 .... 10–19–2004 .... 2–28–2005 ...... 10–28–2005 .... S2066 .......... .............................................................. .......... 1 TX ................................ Blanco ............................................ 11–01–2004 .... 11–23–2004 .... 3–07–2005 ...... 11–07–2005 .... S2067 .......... Excessive rain, flash flooding, tornado 1 7 TX ................................ Brown ............................................. 11–15–2004 .... continuing ....... 3–07–2005 ...... 11–07–2005 .... S2068 .......... Excessive rain, flash flooding, flooding, hail, high winds, lightning. 1 7 TX ................................ Sherman ........................................ 11–30–2004 .... continuing ....... 3–07–2005 ...... 11–07–2005 .... S2069 .......... Excessive rain ..................................... 1 5 OK ................................ ........................................................ 11–30–2004 .... continuing ....... 3–07–2005 ...... 11–07–2005 .... S2069 .......... Excessive rain ..................................... .......... 2 TX ................................ Harris ............................................. 11–20–2004 .... 11–24–2004 .... 3–07–2005 ...... 11–07–2005 .... S2070 .......... Excessive rain, flash flooding, high 

winds, tornadoes.

1 7 

WY ............................... Park ............................................... 1–01–2004 ...... continuing ....... 3–07–2005 ...... 11–07–2005 .... S2071 .......... Drought ................................................ 1 2 MT ................................ ........................................................ 1–01–2004 ...... continuing ....... 3–07–2005 ...... 11–07–2005 .... S2071 .......... Drought ................................................ .......... 2 
430 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

NY ................................ Albany, Cayuga, Dutchess, Genesee, Livingston, Monroe, Oneida, Orange, Orleans, 

Rensselaer, Steuben, Sullivan, Ulster, Wayne, Yates.

5–01–2004 ...... continuing ....... 3–08–2005 ...... 11–08–2005 .... S2072 .......... Multiple disasters related to severe 

storms, including excessive rain, hail, flooding, flash flooding, high winds, lightning, low temperatures.

15 25 

CT ................................ ........................................................ 5–01–2004 ...... continuing ....... 3–08–2005 ...... 11–08–2005 .... S2072 .......... Multiple disasters related to severe 

storms, including excessive rain, hail, flooding, flash flooding, high winds, lightning, low temperatures.

.......... 2 

MA ............................... ........................................................ 5–01–2004 ...... continuing ....... 3–08–2005 ...... 11–08–2005 .... S2072 .......... Multiple disasters related to severe 

storms, including excessive rain, hail, flooding, flash flooding, high winds, lightning, low temperatures.

.......... 1 

NJ ................................. ........................................................ 5–01–2004 ...... continuing ....... 3–08–2005 ...... 11–08–2005 .... S2072 .......... Multiple disasters related to severe 

storms, including excessive rain, hail, flooding, flash flooding, high winds, lightning, low temperatures.

.......... 2 

PA ................................ ........................................................ 5–01–2004 ...... continuing ....... 3–08–2005 ...... 11–08–2005 .... S2072 .......... Multiple disasters related to severe 

storms, including excessive rain, hail, flooding, flash flooding, high winds, lightning, low temperatures.

.......... 4 

VT ................................ ........................................................ 5–01–2004 ...... continuing ....... 3–08–2005 ...... .......................... S2072 .......... Multiple disasters related to severe 

storms, including excessive rain, hail, flooding, flash flooding, high winds, lightning, low temperatures.

.......... 1 
431 

AR ................................ Arkansas, Ashley, Chicot, Cleveland, Columbia, Conway, 

Crawford, Dallas, Desha, Drew, Franklin, Garland, Grant, Hempstead, Hot Spring, Jackson, Jefferson, Johnson, Lafayette, Lee, Lincoln, Little River, Logan, Lonoke, Marion, Miller, Monroe, Montgomery, Nevada, Phillips, Pope, Prairie, Pulaski, Saline, Scott, Sebastian, Union, White, Woodruff, Yell.

10–01–2004 .... 11–30–2004 .... 3–11–05 .......... 11–14–2005 .... S2073 .......... Excessive rain, flooding ...................... 40 25 

LA ................................ ........................................................ 10–01–2004 .... 11–30–2004 .... 3–11–05 .......... 11–14–2005 .... S2073 .......... Excessive rain, flooding ...................... .......... 8 MO ............................... ........................................................ 10–01–2004 .... 11–30–2004 .... 3–11–05 .......... 11–14–2005 .... S2073 .......... Excessive rain, flooding ...................... .......... 2 MS ............................... ........................................................ 10–01–2004 .... 11–30–2004 .... 3–11–05 .......... 11–14–2005 .... S2073 .......... Excessive rain, flooding ...................... .......... 5 OK ................................ ........................................................ 10–01–2004 .... 11–30–2004 .... 3–11–05 .......... 11–14–2005 .... S2073 .......... Excessive rain, flooding ...................... .......... 4 TX ................................ ........................................................ 10–01–2004 .... 11–30–2004 .... 3–11–05 .......... 11–14–2005 .... S2073 .......... Excessive rain, flooding ...................... .......... 2 TX ................................ Schleicher ...................................... 10–01–2004 .... 11–30–2004 .... 3–11–2005 ...... 11–14–2005 .... S2074 .......... Excessive rain ..................................... 1 7 TX ................................ Hutchinson, Moore ......................... 10–01–2004 .... continuing ....... 3–15–2005 ...... 11–15–2005 .... S2075 .......... Excessive rain, excessive snow ........... 2 9 ME ............................... Aroostook, Somerset ...................... 1–01–2004 ...... 12–31–2004 .... 3–15–2005 ...... 11–15–2005 .... S2076 .......... Excessive rain, wet conditions; cold 

spring, summer.

2 6 

TN ................................ Marion, Sequatchie ........................ 12–05–2004 .... continuing ....... 3–17–2005 ...... 11–17–2005 .... S2077 .......... Storms, excessive rain, flooding ......... 2 6 AL ................................ ........................................................ 12–05–2004 .... continuing ....... 3–17–2005 ...... 11–17–2005 .... S2077 .......... Storms, excessive rain, flooding ......... .......... 1 GA ................................ ........................................................ 12–05–2004 .... continuing ....... 3–17–2005 ...... 11–17–2005 .... S2077 .......... Storms, excessive rain, flooding ......... .......... 1 TX ................................ Waller ............................................. 5–13–2004 ...... continuing ....... 3–18–2005 ...... 11–18–2005 .... S2078 .......... Excessive rain, flooding ...................... 1 6 TX ................................ Jack ................................................ 6–01–2004 ...... continuing ....... 3–18–2005 ...... 11–18–2005 .... S2079 .......... Excessive rain, hail ............................. 1 7 NV ................................ Clark, Lincoln ................................ 1–09–2005 ...... 1–15–2005 ...... 3–18–2005 ...... 11–18–2005 .... S2080 .......... Heavy rain, snow melt, resulting in 

severe flooding.

2 2 

AZ ................................ ........................................................ 1–09–2005 ...... 1–15–2005 ...... 3–18–2005 ...... 11–18–2005 .... S2080 .......... Heavy rain, snow melt, resulting in 

severe flooding.

.......... 1 

CA ................................ ........................................................ 1–09–2005 ...... 1–15–2005 ...... 3–18–2005 ...... 11–18–2005 .... S2080 .......... Heavy rain, snow melt, resulting in 

severe flooding.

.......... 2 

UT ................................ ........................................................ 1–09–2005 ...... 1–15–2005 ...... 3–18–2005 ...... 11–18–2005 .... S2080 .......... Heavy rain, snow melt, resulting in 

severe flooding.

.......... 4 

OR ................................ Klamath ......................................... 10–01–2002 .... continuing ....... 3–22–2005 ...... 11–22–2005 .... S2081 .......... Drought ................................................ 1 5 CA ................................ ........................................................ 10–01–2002 .... continuing ....... 3–22–2005 ...... 11–22–2005 .... S2081 .......... Drought ................................................ .......... 2 TX ................................ Williamson ..................................... 10–01–2004 .... continuing ....... 3–22–2005 ...... 11–22–2005 .... S2082 .......... Excessive rain, flash flooding ............. 1 6 MA ............................... Hampshire, Hampden .................... 7–15–2004 ...... 10–31–2004 .... 3–22–2005 ...... 11–22–2005 .... S2083 .......... Abnormally wet weather conditions .... 2 3 CT ................................ ........................................................ 7–15–2004 ...... 10–31–2004 .... 3–22–2005 ...... 11–22–2005 .... S2083 .......... Abnormally wet weather conditions .... .......... 3 
432 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

TX ................................ Brewster ......................................... 7–28–04 ..........

06–01–04 ........

7–29–04 ..........continuing .......

3–22–2005 ...... 11–22–2005 .... S2084 .......... Excessive rain, flash flooding ............. 1 4 

TX ................................ Randall .......................................... 9–01–2004 ...... 12–31–2004 .... 3–25–2005 ...... 11–25–2005 .... S2085 .......... Excessive rain, flash flooding ............. 1 7 TX ................................ Roberts .......................................... 11–01–2004 .... continuing ....... 3–25–2005 ...... 11–25–2005 .... S2086 .......... Excessive rain, freeze, excessive temperatures. 1 8 OH ................................ Ashland, Ashtabula, Clermont, 

Delaware, Fairfield, Geauga, Hancock, Holmes, Lake, Licking, Logan, Marion, Morgan, Morrow, Muskingum, Wyandot.

12–23–2004 .... continuing ....... 3–25–2005 ...... 11–25–2005 .... S2087 .......... Extreme weather conditions: Freezing 

rain, ice, excessive rain, excessive snow, high winds, flash flooding, flooding.

16 36 

KY ................................ ........................................................ 12–23–2004 .... continuing ....... 3–25–2005 ...... 11–25–2005 .... S2087 .......... Extreme weather conditions: Freezing 

rain, ice, excessive rain, excessive snow, high winds, flash flooding, flooding.

.......... 3 

PA ................................ ........................................................ 12–23–2004 .... continuing ....... 3–25–2005 ...... 11–25–2005 .... S2087 .......... Extreme weather conditions: Freezing 

rain, ice, excessive rain, excessive snow, high winds, flash flooding, flooding.

.......... 2 

CT ................................ Fairfield, Hartford, Litchfield, 

Tolland.

7–01–2004 ...... 10–31–2004 .... 3–25–2005 ...... 11–25–2005 .... S2088 .......... Abnormally wet weather conditions .... 4 4 

MA ............................... ........................................................ 7–01–2004 ...... 10–31–2004 .... 3–25–2005 ...... 11–25–2005 .... S2088 .......... Abnormally wet weather conditions .... .......... 3 NY ................................ ........................................................ 7–01–2004 ...... 10–31–2004 .... 3–25–2005 ...... 11–25–2005 .... S2088 .......... Abnormally wet weather conditions .... .......... 3 UT ................................ Iron, Washington ........................... 1–09–2005 ...... 1–11–2005 ...... 3–25–2005 ...... 11–25–2005 .... S2089 .......... Severe flooding .................................... 2 3 AZ ................................ ........................................................ 1–09–2005 ...... 1–11–2005 ...... 3–25–2005 ...... 11–25–2005 .... S2089 .......... Severe flooding .................................... .......... 1 NV ................................ ........................................................ 1–09–2005 ...... 1–11–2005 ...... 3–25–2005 ...... 11–25–2005 .... S2089 .......... Severe flooding .................................... .......... 1 OH ................................ Franklin, Pickaway, Pike, Ross, 

Seneca, Shelby, Tuscarawas.

12–23–2004 .... 1–23–2005 ...... 4–14–2005 ...... 12–14–2005 .... S2090 .......... Excessive rain, flash flooding, flooding. 7 12 

TX ................................ Callahan ........................................ 11–15–2004 .... continuing ....... 4–14–2005 ...... 12–14–2005 .... S2091 .......... Excessive rain ..................................... 1 6 TX ................................ Hemphill ........................................ 11–01–2004 .... continuing ....... 4–14–2005 ...... 12–14–2005 .... S2092 .......... Excessive rain, excessive temperatures, freeze. 1 4 OK ................................ ........................................................ 11–01–2004 .... continuing ....... 4–14–2005 ...... 12–14–2005 .... S2092 .......... Excessive rain, excessive temperatures, freeze. .......... 2 TX ................................ Hunt ............................................... 11–01–2004 .... continuing ....... 4–14–2005 ...... 12–14–2005 .... S2093 .......... Excessive rain ..................................... 1 8 TX ................................ Armstrong, Oldham ....................... 11–25–2004 .... continuing ....... 4–14–2005 ...... 12–14–2005 .... S2094 .......... Excessive rain ..................................... 2 10 
433 

NM ............................... ........................................................ 11–25–2004 .... continuing ....... 4–14–2005 ...... 12–14–2005 .... S2094 .......... Excessive rain ..................................... .......... 1 TX ................................ Potter ............................................. 11–25–2004 .... continuing ....... 4–14–2005 ...... 12–14–2005 .... S2095 .......... Excessive rain ..................................... 1 7 TX ................................ Haskell ........................................... 11–01–2004 .... continuing ....... 4–28–2005 ...... 12–28–2005 .... S2096 .......... Excessive rain ..................................... 1 7 TX ................................ Crosby ............................................ 5–12–2005 ...... 5–13–2005 ...... 6–21–2005 ...... 2–21–2006 ...... S2097 .......... Excessive rain, flash flooding, flooding, hail, high winds, lightning, 

tornadoes.

1 8 

CA ................................ Yuba .............................................. 3–09–2005 ...... 3–15–2005 ...... 7–18–2005 ...... 3–20–2006 ...... S2098 .......... Unseasonably high temperatures, low 

humidity.

1 6 

MN ............................... Anoka, Benton, Carver, Chisago, 

Clay, Grant, Hennepin, Isanti, Kanabec, Mille Lacs, McLeod, Morrison, Pine, Pope, Sherburne, Steele, Wabasha, Wilkin, Wright.

11–01–2004 .... 4–30–2005 ...... 7–18–2005 ...... 3–20–2006 ...... S2099 .......... Winterkill; below freezing temperatures; cool, wet weather. 19 29 

ND ................................ ........................................................ 11–01–2004 .... 4–30–2005 ...... 7–18–2005 ...... 3–20–2006 ...... S2099 .......... Winterkill; below freezing temperatures; cool, wet weather. .......... 2 WI ................................ ........................................................ 11–01–2004 .... 4–30–2005 ...... 7–18–2005 ...... 3–20–2006 ...... S2099 .......... Winterkill; below freezing temperatures; cool, wet weather. .......... 5 TX ................................ Callahan ........................................ 6–04–2005 ...... 6–04–2005 ...... 7–18–2005 ...... 3–20–2006 ...... S2100 .......... Excessive rain, flash flooding, hail, 

high winds, lightning.

1 6 

TX ................................ Knox ............................................... 5–23–2005 ...... 5–23–2005 ...... 7–18–2005 ...... 3–20–2006 ...... S2101 .......... Excessive rain, flash flooding, hail, 

high winds, lightning.

1 6 

TX ................................ Floyd .............................................. 6–09–2005 ...... 6–09–2005 ...... 7–20–2005 ...... 3–20–2006 ...... S2102 .......... Excessive rain, flooding, hail, high 

winds, lightning, tornadoes.

1 7 

CA ................................ Fresno, Kern, Madera, Merced, 

Tulare.

4–28–2005 ...... 5–09–2005 ...... 7–26–2005 ...... 3–27–2006 ...... S2103 .......... Rain, hail storms ................................ 5 14 
434 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

OK ................................ Alfalfa, Atoka, Beckham, Blaine, 

Bryan, Caddo, Canadian, Carter, Choctaw, Cleveland, Coal, Comanche, Cotton, Craig, Creek, Custer, Delaware, Dewey, Ellis, Garfield, Garvin, Grady, Grant, Haskell, Hughes, Jefferson, Johnston, Kingfisher, Latimer, Le Flore, Lincoln, Logan, Love, McClain, McCurtain, McIntosh, Major, Marshall, Mayes, Murray, Muskogee, Okfuskee, Oklahoma, Pawnee, Payne, Pittsburg, Pontotoc, Pottawatomie, Pushmataha, Roger Mills, Rogers, Seminole, Stephens, Tillman, Tulsa, Washita, Woods, Woodward.

1–01–2005 ...... continuing ....... 7–26–2005 ...... 3–27–2006 ...... S2104 .......... Drought ................................................ 58 17 

AR ................................ ........................................................ 1–01–2005 ...... continuing ....... 7–26–2005 ...... 3–27–2006 ...... S2104 .......... Drought ................................................ .......... 6 KS ................................ ........................................................ 1–01–2005 ...... continuing ....... 7–26–2005 ...... 3–27–2006 ...... S2104 .......... Drought ................................................ .......... 6 MO ............................... ........................................................ 1–01–2005 ...... continuing ....... 7–26–2005 ...... 3–27–2006 ...... S2104 .......... Drought ................................................ .......... 1 TX ................................ ........................................................ 1–01–2005 ...... continuing ....... 7–26–2005 ...... 3–27–2006 ...... S2104 .......... Drought ................................................ .......... 14 TX ................................ Crosby ............................................ 6–09–2005 ...... 6–10–2005 ...... 7–26–2005 ...... 3–27–2006 ...... S2105 .......... Excessive rain, flash flooding, flooding, hail, high winds, lightning, 

tornadoes.

1 8 
435 

IL ................................. Adams, Boone, Brown, Bureau, 

Calhoun, Carroll, Cass, Champaign, Clark, Clay, Clinton, Coles, Cook, Crawford, Cumberland, De Kalb, De Witt, Douglas, Du Page, Edgar, Edwards, Effingham, Fayette, Ford, Fulton, Gallatin, Greene, Grundy, Hamilton, Hardin, Henderson, Henry, Iroquois, Jackson, Jasper, Jefferson, Jersey, Jo Daviess, Johnson, Kane, Kankakee, Kendall, Knox, La Salle, Lake, Lawrence, Lee, Livingston, Logan, Macoupin, Madison, Marion, Marshall, Mason, Massac, McDonough, McHenry, McLean, Menard, Mercer, Monroe, Morgan, Moultrie, Ogle, Peoria, Perry, Piatt, Pike, Pope, Putnam, Randolph, Richland, Rock Island, Saline, Sangamon, Schuyler, Scott, Shelby, St. Clair, Stark, Stephenson, Tazewell, Vermilion, Wabash, Warren, Washington, Wayne, White, Whiteside, Will, Williamson, Winnebago, Woodford.

1–01–2005 ...... continuing ....... 7–27–2005 ...... 3–27–2006 ...... S2106 .......... Drought ................................................ 93 8 

IN ................................. ........................................................ 1–01–2005 ...... continuing ....... 7–27–2005 ...... 3–27–2006 ...... S2106 .......... Drought ................................................ .......... 10 IA ................................. ........................................................ 1–01–2005 ...... continuing ....... 7–27–2005 ...... 3–27–2006 ...... S2106 .......... Drought ................................................ .......... 8 KY ................................ ........................................................ 1–01–2005 ...... continuing ....... 7–27–2005 ...... 3–27–2006 ...... S2106 .......... Drought ................................................ .......... 4 MO ............................... ........................................................ 1–01–2005 ...... continuing ....... 7–27–2005 ...... 3–27–2006 ...... S2106 .......... Drought ................................................ .......... 11 WI ................................ ........................................................ 1–01–2005 ...... continuing ....... 7–27–2005 ...... 3–27–2006 ...... S2106 .......... Drought ................................................ .......... 6 TX ................................ Duval ............................................. 12–01–2004 .... continuing ....... 7–29–2005 ...... 3–29–2006 ...... S2107 .......... Drought, high winds ........................... 1 7 TX ................................ Baylor ............................................. 5–31–2005 ...... 5–31–2005 ...... 7–29–2005 ...... 3–29–2006 ...... S2108 .......... Excessive rain, flash flooding, hail, 

high winds, lightning.

1 8 

TX ................................ Jones .............................................. 5–31–2005 ...... 5–31–2005 ...... 7–29–2005 ...... 3–29–2006 ...... S2109 .......... Excessive rain, flash flooding, hail, 

high winds, lightning.

1 7 

TX ................................ Brooks, Jim Hogg ........................... 3–01–2005 ...... continuing ....... 7–29–2005 ...... 3–29–2006 ...... S2110 .......... Drought, high winds, excessive temperatures. 2 8 
436 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

CA ................................ Tehama .......................................... 3/01/05 ............

03/23/05 ..........

05/01/05 ..........3/15/05 ............03/23/05 ..........06/08/05 ..........

8–12–2005 ...... 4–12–2006 ...... S2111 .......... Hot, dry, windy weather ......................

Severe hailstorm .................................Rain, wind, unusually cool temperatures.

1 6 

TX ................................ Gillespie ......................................... 6–01–2005 ...... 6–01–2005 ...... 8–12–2005 ...... 4–12–2006 ...... S2112 .......... High winds .......................................... 1 6 

...................................... Sutter ............................................. 3–05–2005 ...... 3–15–2005 ...... 8–18–2005 ...... 4–18–2006 ...... S2113 .......... Severe high temperatures, low humidity, strong winds. 1 6 

CA ................................ Mendocino ...................................... 5–15–2005 ...... 5–19–2005 ...... 8–22–2005 ...... 4–24–2006 ...... S2114 .......... Rain, hail ............................................ 1 6 CA ................................ Stanislaus ...................................... 4–30–2005 ...... 5–01–2005 ...... 8–22–2005 ...... 4–24–2006 ...... S2115 .......... Rains ................................................... 1 7 CA ................................ Butte .............................................. 4–25–2005 ...... 5–20–2005 ...... 8–22–2005 ...... 4–24–2006 ...... S2116 .......... Hail, late rains .................................... 1 6 CA ................................ Lake ............................................... 5–18–2005 ...... 6–16–2005 ...... 8–22–2005 ...... 4–24–2006 ...... S2117 .......... Unseasonable heavy rainfall ............... 1 6 TX ................................ Burleson ......................................... 5–01–2005 ...... 6–30–2005 ...... 8–22–2005 ...... 4–24–2006 ...... S2118 .......... Drought ................................................ 1 5 
437 

MO ............................... Adair, Andrew, Audrain, Barry, 

Barton, Bates, Benton, Bollinger, Boone, Buchanan, Butler, Caldwell, Callaway, Camden, Cape Girardeau, Carroll, Carter, Cass, Cedar, Chariton, Christian, Clark, Clay, Clinton, Cole, Cooper, Crawford, Dade, Dallas, Daviess, Dekalb, Dent, Douglas, Dunklin, Franklin, Gasconade, Gentry, Greene, Grundy, Harrison, Henry, Hickory, Howard, Howell, Iron, Jackson, Jasper, Jefferson, Johnson, Knox, Laclede, Lafayette, Lawrence, Lewis, Lincoln, Linn, Livingston, Macon, Madison, Maries, Marion, McDonald, Mercer, Miller, Mississippi, Moniteau, Monroe, Montgomery, Morgan, New Madrid, Newton, Nodaway, Oregon, Osage, Ozark, Pemiscot, Perry, Pettis, Phelps, Pike, Platte, Polk, Pulaski, Putnam, Ralls, Randolph, Ray, Reynolds, Ripley, Saline, Schuyler, Scotland, Scott, Shannon, Shelby, St Charles, St Clair, St Francois, St Louis, Ste Genevieve, Stoddard, Stone, Sullivan, Taney, Texas, Vernon, Warren, Washington, Wayne, Webster, Worth, Wright.

1–01–2005 ...... continuing ....... 8–23–2005 ...... 4–24–2006 ...... S2119 .......... Drought ................................................ 112 3 

AR ................................ ........................................................ 1–01–2005 ...... continuing ....... 8–23–2005 ...... 4–24–2006 ...... S2119 .......... Drought ................................................ .......... 12 IL ................................. ........................................................ 1–01–2005 ...... continuing ....... 8–23–2005 ...... 4–24–2006 ...... S2119 .......... Drought ................................................ .......... 12 IA ................................. ........................................................ 1–01–2005 ...... continuing ....... 8–23–2005 ...... 4–24–2006 ...... S2119 .......... Drought ................................................ .......... 9 KS ................................ ........................................................ 1–01–2005 ...... continuing ....... 8–23–2005 ...... 4–24–2006 ...... S2119 .......... Drought ................................................ .......... 10 KY ................................ ........................................................ 1–01–2005 ...... continuing ....... 8–23–2005 ...... 4–24–2006 ...... S2119 .......... Drought ................................................ .......... 4 OK ................................ ........................................................ 1–01–2005 ...... continuing ....... 8–23–2005 ...... 4–24–2006 ...... S2119 .......... Drought ................................................ .......... 2 TN ................................ ........................................................ 1–01–2005 ...... continuing ....... 8–23–2005 ...... 4–24–2006 ...... S2119 .......... Drought ................................................ .......... 2 
438 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

CA ................................ Sutter ............................................. 5–08–2005 ...... 5–19–2005 ...... 8–25–2005 ...... 4–25–2006 ...... S2120 .......... Unseasonable rain .............................. 1 6 KS ................................ Butler, Ford, Gove, Grant, Meade, 

Sedgwick, Trego, Wabaunsee.

6–03–2005 ...... 6–16–2005 ...... 8–25–2005 ...... 4–25–2006 ...... S2121 .......... Hail, high winds, lightning, tornadoes, excessive rain, flash flooding, flooding. 8 37 

OK ................................ ........................................................ 6–03–2005 ...... 6–16–2005 ...... 8–25–2005 ...... 4–25–2006 ...... S2121 .......... .............................................................. .......... 1 MN ............................... Aitkin, Beltrami, Benton, Clearwater, Dakota, Grant, Itasca, 

Kittson, Koochiching, Lake of the Woods, Marshall, Mille Lacs, Pennington, Roseau, Traverse, Washington, Wilkin.

5–07–2005 ...... continuing ....... 8–25–2005 ...... 4–25–2006 ...... S2122 .......... Excessive rain, hail, high winds ......... 17 28 

ND ................................ ........................................................ 5–07–2005 ...... continuing ....... 8–25–2005 ...... 4–25–2006 ...... S2122 .......... Excessive rain, hail, high winds ......... .......... 4 SD ................................ ........................................................ 5–07–2005 ...... continuing ....... 8–25–2005 ...... 4–25–2006 ...... S2122 .......... Excessive rain, hail, high winds ......... .......... 1 WI ................................ ........................................................ 5–07–2005 ...... continuing ....... 8–25–2005 ...... 4–25–2006 ...... S2122 .......... Excessive rain, hail, high winds ......... .......... 3 OR ................................ Polk, Yamhill ................................. 3–24–2005 ...... 4–30–2005 ...... 8–31–2005 ...... 5–01–2006 ...... S2123 .......... Heavy winds, rains .............................. 2 7 TX ................................ Wilbarger ....................................... 3–01–2005 ...... 7–05–2005 ...... 8–31–2005 ...... 5–01–2006 ...... S2124 .......... Drought, high winds, excessive temperatures. 1 5 TX ................................ ........................................................ 3–01–2005 ...... 7–05–2005 ...... 8–31–2005 ...... 5–01–2006 ...... S2124 .......... Drought, high winds, excessive temperatures. .......... 2 VA ................................ Fauquier ......................................... 4–01–2005 ...... 6–30–2005 ...... 8–31–2005 ...... 5–01–2006 ...... S2125 .......... Drought, high temperatures ................ 1 7 
439 

MS ............................... Adams, Amite, Attala, Choctaw, 

Claiborne, Clarke, Copiah, Covington, Forrest, Franklin, George, Greene, Hancock, Harrison, Hinds, Jackson, Jasper, Jefferson, Jefferson Davis, Jones, Kemper, Lamar, Lauderdale, Lawrence, Leake, Lincoln, Lowndes, Madison, Marion, Neshoba, Newton, Noxubee, Oktibbeha, Pearl River, Perry, Pike, Rankin, Scott, Simpson, Smith, Stone, Walthall, Warren, Wayne, Wilkinson, Winston, Yazoo.

8–29–2005 ...... continuing ....... 9–09–2005 ...... 5–09–2006 ...... S2126 .......... Hurricane Katrina ................................ 31 4 

AL ................................ ........................................................ 8–29–2005 ...... continuing ....... 9–09–2005 ...... 5–09–2006 ...... S2126 .......... Hurricane Katrina ................................ .......... 3 AR ................................ ........................................................ 8–29–2005 ...... continuing ....... 9–09–2005 ...... 5–09–2006 ...... S2126 .......... Hurricane Katrina ................................ .......... 6 LA ................................ ........................................................ 8–29–2005 ...... continuing ....... 9–09–2005 ...... 5–09–2006 ...... S2126 .......... Hurricane Katrina ................................ .......... 2 TN ................................ ........................................................ 8–29–2005 ...... continuing ....... 9–09–2005 ...... 5–09–2006 ...... S2126 .......... Hurricane Katrina ................................ .......... 3 IA ................................. Cedar, Clinton, Davis, Des Moines, 

Henry, Iowa, Jackson, Jefferson, Johnson, Keokuk, Lee, Louisa, Muscatine, Scott, Van Buren, Washington.

1–01–2005 ...... continuing ....... 9–13–2005 ...... 5–15–2006 ...... S2127 .......... Drought ................................................ 16 10 

IL ................................. ........................................................ 1–01–2005 ...... continuing ....... 9–13–2005 ...... 5–15–2006 ...... S2127 .......... Drought ................................................ .......... 7 MO ............................... ........................................................ 1–01–2005 ...... continuing ....... 9–13–2005 ...... 5–15–2006 ...... S2127 .......... Drought ................................................ .......... 3 KS ................................ Ellsworth, Geary, Gove, Greeley, 

Jewell, Osage, Riley, Russell, Trego, Wabaunsee.

1–01–2005 ...... continuing ....... 9–13–2005 ...... 5–15–2006 ...... S2128 .......... Freeze, drought, excessive heat, high 

winds.

10 34 

CO ................................ ........................................................ 1–01–2005 ...... continuing ....... 9–13–2005 ...... 5–15–2006 ...... S2128 .......... Freeze, drought, excessive heat, high 

winds.

.......... 3 

NE ................................ ........................................................ 1–01–2005 ...... continuing ....... 9–13–2005 ...... 5–15–2006 ...... S2128 .......... Freeze, drought, excessive heat, high 

winds.

.......... 2 
440 

EMERGENCY PREPAREDNESS AND PROGRAMS BRANCH (EPPB) DISASTER DESIGNATION REQUESTS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal Year 2005—Secretarial Designations for Production Losses] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Sec- retary Termination Date Designation Number Description of disaster Primary Contig- uous 

OH ................................ Ashland, Ashtabula, Athens, 

Auglaize, Belmont, Brown, Butler, Carroll, Champaign, Clermont, Clinton, Columbiana, Coshocton, Crawford, Cuyahoga, Darke, Defiance, Erie, Fairfield, Fayette, Franklin, Fulton, Gallia, Geauga, Guernsey, Hamilton, Hancock, Hardin, Henry, Highland, Hocking, Huron, Jackson, Knox, Lake, Lawrence, Licking, Logan, Lorain, Lucas, Madison, Mahoning, Medina, Meigs, Mercer, Miami, Monroe, Montgomery, Morgan, Muskingum, Noble, Ottawa, Paulding, Perry, Pickaway, Pike, Preble, Putnam, Richland, Ross, Sandusky, Scioto, Seneca, Shelby, Trumbull, Tuscarawas, Union, Van Wert, Vinton, Warren, Washington, Wyandot.

5–25–2005 ...... continuing ....... 9–20–2005 ...... 5–22–2006 ...... S2129 .......... Extreme weather conditions ................ 72 16 

IN ................................. ........................................................ 5–25–2005 ...... continuing ....... 9–20–2005 ...... 5–22–2006 ...... S2129 .......... Extreme weather conditions ................ .......... 9 KY ................................ ........................................................ 5–25–2005 ...... continuing ....... 9–20–2005 ...... 5–22–2006 ...... S2129 .......... Extreme weather conditions ................ .......... 9 MI ................................ ........................................................ 5–25–2005 ...... continuing ....... 9–20–2005 ...... 5–22–2006 ...... S2129 .......... Extreme weather conditions ................ .......... 3 PA ................................ ........................................................ 5–25–2005 ...... continuing ....... 9–20–2005 ...... 5–22–2006 ...... S2129 .......... Extreme weather conditions ................ .......... 5 WV ............................... ........................................................ 5–25–2005 ...... continuing ....... 9–20–2005 ...... 5–22–2006 ...... S2129 .......... Extreme weather conditions ................ .......... 11 TX ................................ Bowie, Hunt, Rains ........................ 4–01–2005 ...... continuing ....... 9–19–2005 ...... 5–19–2006 ...... S2130 .......... Drought ................................................ 3 11 AR ................................ ........................................................ 4–01–2005 ...... continuing ....... 9–19–2005 ...... 5–19–2006 ...... S2130 .......... Drought ................................................ .......... 2 OK ................................ ........................................................ 4–01–2005 ...... continuing ....... 9–19–2005 ...... 5–19–2006 ...... S2130 .......... Drought ................................................ .......... 1 TX ................................ Foard .............................................. 3–01–2005 ...... continuing ....... 9–19–2005 ...... 5–19–2006 ...... S2131 .......... Drought ................................................ 1 6 TX ................................ Jim Wells ....................................... 10–01–2004 .... continuing ....... 9–19–2005 ...... 5–19–2006 ...... S2132 .......... Drought, high winds ........................... 1 6 
441 

TX ................................ Kleberg ........................................... 10–01–2004 .... continuing ....... 9–19–2005 ...... 5–19–2006 ...... S2133 .......... Drought, excessive temperatures ........ 1 4 TX ................................ Red River ....................................... 4–01–2005 ...... continuing ....... 9–19–2005 ...... 5–19–2006 ...... S2134 .......... Drought, excessive temperatures ........ 1 7 OK ................................ ........................................................ 4–01–2005 ...... continuing ....... 9–19–2005 ...... 5–19–2006 ...... S2134 .......... Drought, excessive temperatures ........ .......... 2 

TOTAL ACTIVE ........................................................ .......................... .......................... .......................... .......................... ...................... .............................................................. 1,126 2048 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

IL ......................................... Alexander, Franklin, Hancock, Pulaski, 

Union.

1–01–05 ...... continuing .... 10–04–05 .... 6–05–06 ...... S2106, 

Amendment 1.

Drought ............................................ 5 12 

IA ......................................... ................................................................... 1–01–05 ...... continuing .... 10–04–05 .... 6–05–06 ...... S2106, 

Amendment 1.

Drought ............................................ .......... 1 

KY ........................................ ................................................................... 1–01–05 ...... continuing .... 10–04–05 .... 6–05–06 ...... S2106, 

Amendment 1.

Drought ............................................ .......... 2 

MO ....................................... ................................................................... 1–01–05 ...... continuing .... 10–04–05 .... 6–05–06 ...... S2106, 

Amendment 1.

Drought ............................................ .......... 6 

MS ....................................... Alcorn, Lee, Tippah, Tishomingo ............... 8–29–05 ...... continuing .... 10–31–05 .... 7–03–06 ...... S2126, 

Amendment 1.

Hurricane Katrina ............................ 4 ..........

AL ........................................ ................................................................... 8–29–05 ...... continuing .... 10–31–05 .... 7–03–06 ...... S2126, 

Amendment 1.

Hurricane Katrina ............................ .......... 2 

TN ........................................ ................................................................... 8–29–05 ...... continuing .... 10–31–05 .... 7–03–06 ...... S2126, 

Amendment 1.

Hurricane Katrina ............................ .......... 2 

CA ........................................ Glenn ......................................................... 5–01–05 ...... 6–10–05 ...... 10–04–05 .... 6–05–06 ...... S2135 ........ Rain, wind, unusually cool temperatures. 1 5 CA ........................................ Yuba .......................................................... 5–09–05 ...... 5–19–05 ...... 10–04–05 .... 6–05–06 ...... S2136 ........ Unseasonably heavy rains .............. 1 6 MT ....................................... Fergus ....................................................... 1–01–05 ...... continuing .... 10–04–05 .... 6–05–06 ...... S2137 ........ Drought ............................................ 1 8 TX ........................................ Fannin ....................................................... 4–01–05 ...... continuing .... 10–04–05 .... 6–05–06 ...... S2138 ........ Drought ............................................ 1 5 OK ........................................ ................................................................... 4–01–05 ...... continuing .... 10–04–05 .... 6–05–06 ...... S2138 ........ Drought ............................................ .......... 1 
442 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

TX ........................................ Webb ......................................................... 3–01–05 ...... continuing .... 10–04–05 .... 6–05–06 ...... S2139 ........ Drought, high winds, excessive 

temperatures.

1 7 

SD ........................................ Bon Homme, Clay, Lincoln, Turner ........... 1–01–05 ...... continuing .... 10–07–05 .... 6–07–06 ...... S2140 ........ Drought, high winds, spring frosts, 

excessive heat, flash flooding, hail, excessive rainfall.

4 6 

IA ......................................... ................................................................... 1–01–05 ...... continuing .... 10–07–05 .... 6–07–06 ...... S2140 ........ Drought, high winds, spring frosts, 

excessive heat, flash flooding, hail, excessive rainfall.

.......... 2 

NE ........................................ ................................................................... 1–01–05 ...... continuing .... 10–07–05 .... 6–07–06 ...... S2140 ........ Drought, high winds, spring frosts, 

excessive heat, flash flooding, hail, excessive rainfall.

.......... 3 

UT ........................................ Washington ............................................... 6–26–05 ...... 8–01–05 ...... 10–07–05 .... 6–07–06 ...... S2141 ........ Fires caused by lightning ............... 1 2 AZ ........................................ ................................................................... 6–26–05 ...... 8–01–05 ...... 10–07–05 .... 6–07–06 ...... S2141 ........ Fires caused by lightning ............... .......... 1 NV ........................................ ................................................................... 6–26–05 ...... 8–01–05 ...... 10–07–05 .... 6–07–06 ...... S2141 ........ Fires caused by lightning ............... .......... 1 AR ........................................ Entire State ............................................... 5–01–05 ...... continuing .... 10–13–05 .... 6–13–06 ...... S2142 ........ Drought, extremely high temperatures. 75 ..........AR ........................................ ................................................................... 5–01–05 ...... continuing .... 10–13–05 .... 6–13–06 ...... S2142 ........ Drought, extremely high temperatures. .......... 8 AR ........................................ ................................................................... 5–01–05 ...... continuing .... 10–13–05 .... 6–13–06 ...... S2142 ........ Drought, extremely high temperatures. .......... 6 AR ........................................ ................................................................... 5–01–05 ...... continuing .... 10–13–05 .... 6–13–06 ...... S2142 ........ Drought, extremely high temperatures. .......... 11 AR ........................................ ................................................................... 5–01–05 ...... continuing .... 10–13–05 .... 6–13–06 ...... S2142 ........ Drought, extremely high temperatures. .......... 5 AR ........................................ ................................................................... 5–01–05 ...... continuing .... 10–13–05 .... 6–13–06 ...... S2142 ........ Drought, extremely high temperatures. .......... 4 AR ........................................ ................................................................... 5–01–05 ...... continuing .... 10–13–05 .... 6–13–06 ...... S2142 ........ Drought, extremely high temperatures. .......... 2 OR ....................................... Lane .......................................................... 3–01–05 ...... 5–15–05 ...... 10–18–05 .... 6–19–06 ...... S2143 ........ Excessive rains ................................ 1 6 TX ........................................ Comanche ................................................. 8–09–05 ...... 8–10–05 ...... 10–18–05 .... 6–19–06 ...... S2144 ........ Flooding ........................................... 1 5 TX ........................................ Haskell ...................................................... 8–09–05 ...... 8–15–05 ...... 10–18–05 .... 6–19–06 ...... S2145 ........ Excessive rain, flash flooding ......... 1 7 TX ........................................ Haskell ...................................................... 8–09–05 ...... continuing .... 12–21–05 .... 8–21–06 ...... S2145, 

Amendment 1.

Excessive rain, flash flooding ......... 1 7 
443 

TX ........................................ Jones, Knox ................................................ 8–14–05 ...... continuing .... 10–18–05 .... 6–19–06 ...... S2146 ........ Excessive rain, flash flooding ......... 2 11 TX ........................................ Camp, Franklin, Hopkins, Lamar, Morris, 

Titus.

4–01–05 ...... continuing .... 10–18–05 .... 6–19–06 ...... S2147 ........ Drought ............................................ 6 10 

OK ........................................ ................................................................... 4–01–05 ...... continuing .... 10–18–05 .... 6–19–06 ...... S2147 ........ Drought ............................................ .......... 2 KY ........................................ Adair, Allen, Anderson, Ballard, Barren, 

Bath, Bell, Boone, Bourbon, Boyd, Boyle, Bracken, Breckinridge, Bullitt, Butler, Caldwell, Calloway, Campbell, Carlisle, Carroll, Carter, Casey, Clark, Clinton, Crittenden, Cumberland, Daviess, Edmonson, Elliott, Estill, Fayette, Fleming, Floyd, Franklin, Gallatin, Garrard, Grant, Graves, Grayson, Green, Johnson, Kenton, Knott, Larue, Lawrence, Lee, Leslie, Letcher, Lewis, Lincoln, Livingston, Logan, Lyon, Madison, Magoffin, Marion, Marshall, Martin, Mason, McCracken, McCreary, Meade, Menifee, Mercer, Metcalfe, Monroe, Montgomery, Morgan, Muhlenberg, Nelson, Nicholas, Ohio, Oldham, Owen, Owsley, Pendleton, Perry, Pike, Powell, Pulaski, Robertson, Rockcastle, Rowan, Russell, Scott, Shelby, Simpson, Spencer, Taylor, Todd, Trimble, Union, Warren, Washington, Wayne, Webster, Whitley, Wolfe, Woodford.

2–01–05 ...... continuing .... 10–25–05 .... 6–26–06 ...... S2148 ........ Drought ............................................ 109 10 

IL ......................................... ................................................................... 2–01–05 ...... continuing .... 10–25–05 .... 6–26–06 ...... S2148 ........ Drought ............................................ .......... 6 IN ......................................... ................................................................... 2–01–05 ...... continuing .... 10–25–05 .... 6–26–06 ...... S2148 ........ Drought ............................................ .......... 12 MO ....................................... ................................................................... 2–01–05 ...... continuing .... 10–25–05 .... 6–26–06 ...... S2148 ........ Drought ............................................ .......... 1 OH ....................................... ................................................................... 2–01–05 ...... continuing .... 10–25–05 .... 6–26–06 ...... S2148 ........ Drought ............................................ .......... 6 TN ........................................ ................................................................... 2–01–05 ...... continuing .... 10–25–05 .... 6–26–06 ...... S2148 ........ Drought ............................................ .......... 2 VA ........................................ ................................................................... 2–01–05 ...... continuing .... 10–25–05 .... 6–26–06 ...... S2148 ........ Drought ............................................ .......... 4 WV ....................................... ................................................................... 2–01–05 ...... continuing .... 10–25–05 .... 6–26–06 ...... S2148 ........ Drought ............................................ .......... 2 TX ........................................ Fisher ........................................................ 8–01–05 ...... 8–16–05 ...... 10–20–05 .... 6–20–06 ...... S2149 ........ Flooding ........................................... 1 7 
444 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

LA ........................................ Acadia, Allen, Avoyelles, Beauregard, 

Bienville, Bossier, Caddo, Calcasieu, Caldwell, Cameron, Catahoula, Claiborne, Concordia, De Soto, East Carroll, Evangeline, Franklin, Grant, Jackson, Jefferson Davis, La Salle, Lafayette, Lincoln, Madison, Morehouse, Natchitoches, Ouachita, Rapides, Red River, Richland, Sabine, St. Landry, St. Martin, Tensas, Union, Vermilion, Vernon, Webster, West Carroll, Winn.

4–26–05 ...... continuing .... 10–24–05 .... 6–26–06 ...... S2150 ........ Drought, Hurricane Katrina, Hurricane Rita. 40 6 

AR ........................................ ................................................................... 4–26–05 ...... continuing .... 10–24–05 .... 6–26–06 ...... S2150 ........ Drought, other disasters ................. .......... 6 MS ....................................... ................................................................... 4–26–05 ...... continuing .... 10–24–05 .... 6–26–06 ...... S2150 ........ Drought, other disasters ................. .......... 6 TX ........................................ ................................................................... 4–26–05 ...... continuing .... 10–24–05 .... 6–26–06 ...... S2150 ........ Drought, other disasters ................. .......... 9 NE ........................................ Holt ............................................................ 5–24–05 ...... 6–10–05 ...... 10–24–05 .... 6–26–06 ...... S2151 ........ Cool, wet weather ........................... 1 8 OR ....................................... Linn ........................................................... Early spring .. 5–15–05 ...... 10–24–05 .... 6–26–06 ...... S2152 ........ Excessive ongoing rains .................. 1 6 OR ....................................... Wasco ........................................................ 3–01–05 ...... 5–31–05 ...... 10–24–05 .... 6–26–06 ...... S2153 ........ Severe frosts, rain events ............... 1 7 WA ....................................... ................................................................... 3–01–05 ...... 5–31–05 ...... 10–24–05 .... 6–26–06 ...... S2153 ........ Severe frosts, rain events ............... .......... 1 TX ........................................ Delta .......................................................... 4–01–05 ...... continuing .... 10–24–05 .... 6–26–06 ...... S2154 ........ Drought ............................................ 1 6 TX ........................................ Coryell ....................................................... 7–15–05 ...... 7–17–05 ...... 10–31–05 .... 7–03–06 ...... S2155 ........ High winds ...................................... 1 ..........ND ....................................... Adams, Benson, Bottineau, Bowman, 

Burke, Cavalier, Dickey, Divide, Emmons, Grand Forks, Grant, Griggs, Hettinger, Kidder, LaMoure, McHenry, McIntosh, McLean, Mercer, Mountrail, Nelson, Oliver, Pembina, Pierce, Ramsey, Ransom, Renville, Richland, Rolette, Sargent, Sheridan, Slope, Steele, Towner, Traill, Walsh, Ward.

1–01–05 ...... continuing .... 10–31–05 .... 7–03–06 ...... S2156 ........ Freeze, damage, late spring snow 

storms, overland flooding, torrential, rainfall, standing water, hail, high winds, tornadoes.

37 16 

MN ....................................... ................................................................... 1–01–05 ...... continuing .... 10–31–05 .... 7–03–06 ...... S2156 ........ Freeze, damage, late spring snow 

storms, overland flooding, torrential, rainfall, standing water, hail, high winds, tornadoes.

.......... ..........
445 

MT ....................................... ................................................................... 1–01–05 ...... continuing .... 10–31–05 .... 7–03–06 ...... S2156 ........ Freeze, damage, late spring snow 

storms, overland flooding, torrential, rainfall, standing water, hail, high winds, tornadoes.

.......... ..........

SD ........................................ ................................................................... 1–01–05 ...... continuing .... 10–31–05 .... 7–03–06 ...... S2156 ........ Freeze, damage, late spring snow 

storms, overland flooding, torrential, rainfall, standing water, hail, high winds, tornadoes.

.......... ..........

WI ........................................ Clark, Marinette, Milwaukee, Outagamie, 

Walworth, Waukesha, Waushara.

1–01–05 ...... 5–31–05 ...... 10–31–05 .... 7–03–06 ...... S2157 ........ Winterkill, due to unusually warm 

weather; followed by below freezing temperatures, and ice.

7 25 

IL ......................................... ................................................................... 1–01–05 ...... 5–31–05 ...... 10–31–05 .... 7–03–06 ...... S2157 ........ Winterkill, due to unusually warm 

weather; followed by below freezing temperatures, and ice.

.......... 2 

MI ........................................ ................................................................... 1–01–05 ...... 5–31–05 ...... 10–31–05 .... 7–03–06 ...... S2157 ........ Winterkill, due to unusually warm 

weather; followed by below freezing temperatures, and ice.

.......... 2 

OR ....................................... Douglas ..................................................... 1–01–05 ...... continuing .... 10–24–05 .... 6–26–06 ...... S2158 ........ Severe weather conditions .............. 1 6 NE ........................................ Chase, Cheyenne, Deuel, Dundy, Furnas, 

Garden, Hayes, Hitchcock, Morrill, Perkins, Red Willow, Scotts Bluff, Sheridan, Sioux.

1–01–05 ...... continuing .... 11–03–05 .... 7–03–06 ...... S2159 ........ Freeze incidents; hail, disease, ongoing drought. 13 13 

NE ........................................ ................................................................... 1–01–05 ...... continuing .... 11–03–05 .... 7–03–06 ...... S2159 ........ Freeze incidents; hail, disease, ongoing drought. .......... 4 NE ........................................ ................................................................... 1–01–05 ...... continuing .... 11–03–05 .... 7–03–06 ...... S2159 ........ Freeze incidents; hail, disease, ongoing drought. .......... 5 NE ........................................ ................................................................... 1–01–05 ...... continuing .... 11–03–05 .... 7–03–06 ...... S2159 ........ Freeze incidents; hail, disease, ongoing drought. .......... 1 NE ........................................ ................................................................... 1–01–05 ...... continuing .... 11–03–05 .... 7–03–06 ...... S2159 ........ Freeze incidents; hail, disease, ongoing drought. .......... 2 CO ....................................... Delta, Kit Carson ...................................... 1–01–05 ...... continuing .... 11–07–05 .... 7–07–06 ...... S2160 ........ (1) Freezing temperatures ...............

(2) Drought ......................................

2 7 

KS ........................................ ................................................................... 1–01–05 ...... continuing .... 11–07–05 .... 7–07–06 ...... S2160 ........ Drought ............................................ .......... 3 TX ........................................ Wood .......................................................... 4–01–05 ...... continuing .... 11–07–05 .... 7–07–06 ...... S2161 ........ Drought ............................................ 1 7 WI ........................................ Dane, Vernon ............................................. 8–18–05 ...... 8–18–05 ...... 11–07–05 .... 7–07–06 ...... S2162 ........ Tornadoes, severe storms ............... 2 12 IA ......................................... ................................................................... 8–18–05 ...... 8–18–05 ...... 11–07–05 .... 7–07–06 ...... S2162 ........ Tornadoes, severe storms ............... .......... 1 MN ....................................... ................................................................... 8–18–05 ...... 8–18–05 ...... 11–07–05 .... 7–07–06 ...... S2162 ........ Tornadoes, severe storms ............... .......... 1 TX ........................................ Collin ......................................................... 4–01–05 ...... continuing .... 11–02–05 .... 7–03–06 ...... S2163 ........ Drought ............................................ 1 6 
446 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

MI ........................................ Calhoun, Huron, Jackson, Kalamazoo, 

Mecosta, Sanilac, St. Joseph, Tuscola, Van Buren.

6–05–05 ...... 7–24–05 ...... 11–14–05 .... 7–14–06 ...... S2164 ........ Storms with excessive rain, localized flooding, high winds, hail. 9 22 

IN ......................................... ................................................................... 6–05–05 ...... 7–24–05 ...... 11–14–05 .... 7–14–06 ...... S2164 ........ Storms with excessive rain, localized flooding, high winds, hail. .......... 2 IA ......................................... Clay, Dubuque, Harrison, Monona ............ 1–01–05 ...... continuing .... 11–14–05 .... 7–14–06 ...... S2165 ........ Drought ............................................ 4 17 IL ......................................... ................................................................... 1–01–05 ...... continuing .... 11–14–05 .... 7–14–06 ...... S2165 ........ Drought ............................................ .......... 1 NE ........................................ ................................................................... 1–01–05 ...... continuing .... 11–14–05 .... 7–14–06 ...... S2165 ........ Drought ............................................ .......... 3 WI ........................................ ................................................................... 1–01–05 ...... continuing .... 11–14–05 .... 7–14–06 ...... S2165 ........ Drought ............................................ .......... 1 MI ........................................ Alger, Allegan, Antrim, Baraga, Berrien, 

Calhoun, Cass, Charlevoix, Cheboygan, Chippewa, Delta, Dickinson, Emmet, Gogebic, Grand Traverse, Houghton, Ionia, Iron, Kalamazoo, Kalkaska, Kent, Keweenaw, Leelanau, Luce, Mackinac, Manistee, Marquette, Mason, Mecosta, Menominee, Missaukee, Muskegon, Newaygo, Oceana, Ontonagon, Osceola, Otsego, Ottawa, Presque Isle, Schoolcraft, Van Buren.

4–01–05 ...... continuing .... 11–14–05 .... 7–14–06 ...... S2166 ........ Drought ............................................ 41 19 

IN ......................................... ................................................................... 4–01–05 ...... continuing .... 11–14–05 .... 7–14–06 ...... S2166 ........ Drought ............................................ .......... 3 WI ........................................ ................................................................... 4–01–05 ...... continuing .... 11–14–05 .... 7–14–06 ...... S2166 ........ Drought ............................................ .......... 5 TX ........................................ Cameron .................................................... 7–19–05 ...... 7–20–05 ...... 11–14–05 .... 7–14–06 ...... S2167 ........ Flooding, high winds, hurricane, 

lightning.

1 2 

CA ........................................ El Dorado .................................................. (1) 05–16–05 

(2) 04–15–05 

(1) 06–16– 

05(2) 05– 15–05.

11–14–05 .... 7–14–06 ...... S2168 ........ (1) Unseasonable rains ...................

(2) Hail, freezing conditions ...........

1 4 

NV ........................................ ................................................................... (1) 05–16–05 

(2) 04–15–05 

(1) 06–16–05 (2) 05–15–05 

11–14–05 .... 7–14–06 ...... S2168 ........ (1) Unseasonable rains ...................

(2) Hail, freezing conditions ...........

.......... 1 

TX ........................................ Hidalgo ...................................................... 1–01–05 ...... 6–30–05 ...... 11–14–05 .... 7–14–06 ...... S2169 ........ Drought, excessive temperatures .... 1 5 TX ........................................ Kenedy ....................................................... 10–01–04 .... continuing .... 11–14–05 .... 7–14–06 ...... S2170 ........ Drought, excessive temperatures .... 1 4 CA ........................................ San Joaquin .............................................. 3–01–05 ...... 5–31–05 ...... 11–14–05 .... 7–14–06 ...... S2171 ........ Spring rains .................................... 1 6 CA ........................................ Nevada ...................................................... 3–01–05 ...... 6–15–05 ...... 11–14–05 .... 7–14–06 ...... S2172 ........ Rains ............................................... 1 3 NV ........................................ ................................................................... 3–01–05 ...... 6–15–05 ...... 11–14–05 .... 7–14–06 ...... S2172 ........ Rains ............................................... .......... 1 
447 

TN ........................................ Clay, Fentress, Giles, Greene, Hancock, 

Hawkins, Jackson, Morgan, Overton, Pickett, Scott, Smith, Sumner, Unicoi, Van Buren, Washington, White, Williamson, Wilson.

5–01–05 ...... continuing .... 11–23–05 .... 7–24–06 ...... S2173 ........ Extreme drought, higher than normal temperatures. 19 28 

AL ........................................ ................................................................... 5–01–05 ...... continuing .... 11–23–05 .... 7–24–06 ...... S2173 ........ Extreme drought, higher than normal temperatures. .......... 2 KY ........................................ ................................................................... 5–01–05 ...... continuing .... 11–23–05 .... 7–24–06 ...... S2173 ........ Extreme drought, higher than normal temperatures. .......... 7 NC ....................................... ................................................................... 5–01–05 ...... continuing .... 11–23–05 .... 7–24–06 ...... S2173 ........ Extreme drought, higher than normal temperatures. .......... 3 VA ........................................ ................................................................... 5–01–05 ...... continuing .... 11–23–05 .... 7–24–06 ...... S2173 ........ Extreme drought, higher than normal temperatures. .......... 2 TX ........................................ Bailey ........................................................ 8–27–05 ...... 8–27–05 ...... 11–23–05 .... 7–24–06 ...... S2174 ........ Excessive rain, flash flooding, hail, 

high winds, lightning.

1 4 

NM ....................................... ................................................................... 8–27–05 ...... 8–27–05 ...... 11–23–05 .... 7–24–06 ...... S2174 ........ Excessive rain, flash flooding, hail, 

high winds, lightning.

.......... 2 

TX ........................................ Coryell ....................................................... 8–08–05 ...... 8–10–05 ...... 11–23–05 .... 7–24–06 ...... S2175 ........ Excessive rain, flooding, high winds 1 5 TX ........................................ Garza ......................................................... 8–27–05 ...... 8–27–05 ...... 11–23–05 .... 7–24–06 ...... S2176 ........ Excessive rain, hail, high winds ..... 1 7 TX ........................................ Lee ............................................................. 4–01–05 ...... continuing .... 11–23–05 .... 7–24–06 ...... S2177 ........ Drought ............................................ 1 6 TX ........................................ Nacogdoches ............................................. 3–01–05 ...... continuing .... 11–23–05 .... 7–24–06 ...... S2178 ........ Drought, excessive heat, high 

winds.

1 5 

TX ........................................ Willacy ....................................................... 1–01–05 ...... continuing .... 11–23–05 .... 7–24–06 ...... S2179 ........ Drought, high winds ....................... 1 3 MI ........................................ Alger, Allegan, Antrim, Berrien, Cass, 

Delta, Dickinson, Hillsdale, Ingham, Iron, Jackson, Kalamazoo, Kent, Livingston, Marquette, Mecosta, Menominee, Muskegon, Newaygo, Ottawa, St. Joseph, Schoolcraft, Shiawassee, Van Buren.

4–01–05 ...... 5–05–05 ...... 11–21–05 .... 7–21–06 ...... S2180 ........ Above average temperatures, followed by frost, freeze, excessive 

snow, hail.

24 30 

IN ......................................... ................................................................... 4–01–05 ...... 5–05–05 ...... 11–21–05 .... 7–21–06 ...... S2180 ........ Above average temperatures, followed by frost, freeze, excessive 

snow, hail.

.......... 5 

OH ....................................... ................................................................... 4–01–05 ...... 5–05–05 ...... 11–21–05 .... 7–21–06 ...... S2180 ........ Above average temperatures, followed by frost, freeze, excessive 

snow, hail.

.......... 2 

WI ........................................ ................................................................... 4–01–05 ...... 5–05–05 ...... 11–21–05 .... 7–21–06 ...... S2180 ........ Above average temperatures, followed by frost, freeze, excessive 

snow, hail.

.......... 4 

TX ........................................ Hockley ...................................................... 8–27–05 ...... 8–28–05 ...... 11–14–05 .... 7–14–06 ...... S2181 ........ Hail .................................................. 1 8 
448 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

NY ........................................ Chenango, Columbia, Dutchess, Ontario, 

Rensselaer, Ulster, Wayne, Westchester.

4/01/05 ........05/05/05 ......

4/04/05 ........05/17/05 ......

11–23–05 .... 7–24–06 ...... S2182 ........ (1) Excessive rain, flooding, flash 

flooding.

(2) Extreme and unseasonably cold 

temperatures, frost, freezes.

8 22 

CT ........................................ ................................................................... 4/01/05 ........

05/05/05 ......

4/04/05 ........05/17/05 ......

11–23–05 .... 7–24–06 ...... S2182 ........ (1) Excessive rain, flooding, flash 

flooding.

(2) Extreme and unseasonably cold 

temperatures, frost, freezes.

.......... 2 

MA ....................................... ................................................................... 4/01/05 ........

05/05/05 ......

4/04/05 ........05/17/05 ......

11–23–05 .... 7–24–06 ...... S2182 ........ (1) Excessive rain, flooding, flash 

flooding.

(2) Extreme and unseasonably cold 

temperatures, frost, freezes.

.......... 1 

NJ ........................................ ................................................................... 4/01/0505/ 

05/05.

4/04/0505/ 

17/05.

11–23–05 .... 7–24–06 ...... S2182 ........ (1) Excessive rain, flooding, flash 

flooding.

(2) Extreme and unseasonably cold 

temperatures, frost, freezes.

.......... 1 

VT ........................................ ................................................................... 4/01/05 ........

05/05/05 ......

4/04/05 ........05/17/05 ......

11–23–05 .... 7–24–06 ...... S2182 ........ (1) Excessive rain, flooding, flash 

flooding.

(2) Extreme and unseasonably cold 

temperatures, frost, freezes.

.......... 1 

CA ........................................ Sutter ........................................................ 2–14–05 ...... 2–24–05 ...... 12–13–05 .... 8–14–06 ...... S2183 ........ Cold, wet weather ........................... 1 6 OR ....................................... Benton, Yamhill ........................................ 3–01–05 ...... 6–30–05 ...... 12–13–05 .... 8–14–06 ...... S2184 ........ Excessive ongoing rains, cool temperatures. 2 8 OR ....................................... Wasco ........................................................ 1–01–05 ...... continuing .... 12–13–05 .... 8–14–06 ...... S2185 ........ Drought ............................................ 1 7 WA ....................................... ................................................................... 1–01–05 ...... continuing .... 12–13–05 .... 8–14–06 ...... S2185 ........ Drought ............................................ .......... 1 TX ........................................ Coryell ....................................................... 4–01–05 ...... 8–04–05 ...... 12–13–05 .... 8–14–06 ...... S2186 ........ Drought ............................................ 1 5 TX ........................................ Lamb ......................................................... 9–12–05 ...... 9–12–05 ...... 12–13–05 .... 8–14–06 ...... S2187 ........ Hail .................................................. 1 7 CO ....................................... Crowley, El Paso, Lincoln, Otero, Park, 

Phillips, Pueblo, Teller, Washington, Yuma.

1–01–05 ...... continuing .... 12–19–05 .... 8–21–06 ...... S2188 ........ Various disasters: Drought, wind, 

hail, heavy rains.

10 20 

KS ........................................ ................................................................... 1–01–05 ...... continuing .... 12–19–05 .... 8–21–06 ...... S2188 ........ Various disasters: Drought, wind, 

hail, heavy rains.

.......... 1 

NE ........................................ ................................................................... 1–01–05 ...... continuing .... 12–19–05 .... 8–21–06 ...... S2188 ........ Various disasters: Drought, wind, 

hail, heavy rains.

.......... 3 
449 

NY ........................................ Chemung, Dutchess, Essex, Jefferson, 

Oneida, Onondaga, Oswego, Saratoga, Schuyler, Seneca, Tioga, Ulster.

4–02–05 ...... continuing .... 12–19–05 .... 8–21–06 ...... S2189 ........ Drought & various disasters ........... 12 33 

CT ........................................ ................................................................... 4–02–05 ...... continuing .... 12–19–05 .... 8–21–06 ...... S2189 ........ Drought & various disasters ........... .......... 2 MA ....................................... ................................................................... 4–02–05 ...... continuing .... 12–19–05 .... 8–21–06 ...... S2189 ........ Drought & various disasters ........... .......... 1 PA ........................................ ................................................................... 4–02–05 ...... continuing .... 12–19–05 .... 8–21–06 ...... S2189 ........ Drought & various disasters ........... .......... 3 VT ........................................ ................................................................... 4–02–05 ...... continuing .... 12–19–05 .... 8–21–06 ...... S2189 ........ Drought & various disasters ........... .......... 2 TX ........................................ Taylor ......................................................... 8–03–05 ...... 8–29–05 ...... 12–19–05 .... 8–21–06 ...... S2190 ........ Excessive rain ................................. 1 6 TX ........................................ Bosque, Grayson, Henderson, Houston, 

Johnson, Leon, Navarro, Tarrant, Van Zandt, Waller.

4–01–05 ...... continuing .... 12–19–05 .... 8–21–06 ...... S2191 ........ Drought ............................................ 10 36 

OK ........................................ ................................................................... 4–01–05 ...... continuing .... 12–19–05 .... 8–21–06 ...... S2191 ........ Drought ............................................ .......... 3 NY ........................................ Livingston, Madison .................................. 5–12–05 ...... 6–17–05 ...... 12–27–05 .... 8–28–06 ...... S2192 ........ Various disasters : Excessive rain, 

flash flooding, frost.

2 12 

TX ........................................ Calhoun ..................................................... 4–15–05 ...... 9–30–05 ...... 12–27–05 .... 8–28–06 ...... S2193 ........ Drought ............................................ 1 5 TX ........................................ Llano, Mason ............................................. 8–25–05 ...... continuing .... 12–27–05 .... 8–28–06 ...... S2194 ........ Drought ............................................ 2 7 VA ........................................ Amelia, Bland, Brunswick, Buckingham, 

Campbell, Charlotte, Chesterfield, Cumberland, Dinwiddie, Essex, Floyd, Fluvanna, Franklin, Frederick, Giles, Greensville, Halifax, Isle ght, King d een, Lee, Louisa, Lunenburg, Mecklenburg, Montgomery, Nelson, Nottoway, Page, Patrick, Pittsylvania, Powhatan, Prince Edward, Pulaski, Scott, Shenandoah, Smyth, Southampton, Tazewell, Wythe.

6–01–05 ...... 8–31–05 ...... 12–27–05 .... 8–28–06 ...... S2195 ........ Drought, high temperatures ............ 38 51 

KY ........................................ ................................................................... 6–01–05 ...... 8–31–05 ...... 12–27–05 .... 8–28–06 ...... S2195 ........ Drought, high temperatures ............ .......... 2 NC ....................................... ................................................................... 6–01–05 ...... 8–31–05 ...... 12–27–05 .... 8–28–06 ...... S2195 ........ Drought, high temperatures ............ .......... 11 TN ........................................ ................................................................... 6–01–05 ...... 8–31–05 ...... 12–27–05 .... 8–28–06 ...... S2195 ........ Drought, high temperatures ............ .......... 4 WV ....................................... ................................................................... 6–01–05 ...... 8–31–05 ...... 12–27–05 .... 8–28–06 ...... S2195 ........ Drought, high temperatures ............ .......... 9 KS ........................................ Cheyenne, Edwards, Harper, Haskell, 

Linn, Rush, Stanton.

6–03–05 ...... 6–13–05 ...... 12–21–05 .... 8–21–06 ...... S2196 ........ Severe storms .................................. 7 29 

CO ....................................... ................................................................... 6–03–05 ...... 6–13–05 ...... 12–21–05 .... 8–21–06 ...... S2196 ........ Severe storms .................................. .......... 4 MO ....................................... ................................................................... 6–03–05 ...... 6–13–05 ...... 12–21–05 .... 8–21–06 ...... S2196 ........ Severe storms .................................. .......... 2 NE ........................................ ................................................................... 6–03–05 ...... 6–13–05 ...... 12–21–05 .... 8–21–06 ...... S2196 ........ Severe storms .................................. .......... 1 OK ........................................ ................................................................... 6–03–05 ...... 6–13–05 ...... 12–21–05 .... 8–21–06 ...... S2196 ........ Severe storms .................................. .......... 2 NY ........................................ (1) Columbia, Ontario ...............................

(2) Fulton, Hamilton, Herkimer, Madison, 

Montgomery, Ontario, Orange, Rensselaer, Suffolk, Sullivan.

(1) 06–09–05 (2) 05–01–05 

(1) 07–27–05 (2) continuing 

12–21–05 .... 8–21–06 ...... S2197 ........ (1) Excessive rain, hail, flash 

flooding.

(2) Drought, heat, high temperatures.

11 31 
450 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

CT ........................................ ................................................................... (1) 06–09–05 (1) 07–27–05 12–21–05 .... 8–21–06 ...... S2197 ........ (1) Excessive rain, hail, flash 

flooding.

.......... 1 

MA ....................................... ................................................................... (1) 06–09–05 

(2) 05–01–05 

(1) 07–27–05 (2) continuing 

12–21–05 .... 8–21–06 ...... S2197 ........ (1) Excessive rain, hail, flash 

flooding.

(2) Drought, heat, high temperatures.

.......... 1 

NJ ........................................ ................................................................... (2) 05–01–05 

(2) continuing 

12–21–05 .... 8–21–06 ...... S2197 ........... (2) Drought, 

heat, high temperatures.

.......................................................... 2 

PA ........................................ ................................................................... (2) 05–01–05 (2) continuing 12–21–05 .... 8–21–06 ...... S2197 ........ (2) Drought, heat, high temperatures. .......... 2 VT ........................................ ................................................................... (2) 05–01–05 (2) continuing 12–21–05 .... 8–21–06 ...... S2197 ........ (2) Drought, heat, high temperatures. .......... 1 SD ........................................ Aurora, Bon Homme, Butte, Charles Mix, 

Douglas, Harding, Hughes, Hutchinson, Hyde, Perkins, Potter, Stanley, Sully, Yankton.

1–01–05 ...... continuing .... 12–21–05 .... 8–21–06 ...... S2198 ........ Drought, late spring frosts, extreme 

heat, high winds, hail, prairie fires.

14 22 

MT ....................................... ................................................................... 1–01–05 ...... continuing .... 12–21–05 .... 8–21–06 ...... S2198 ........ Drought, late spring frosts, extreme 

heat, high winds, hail, prairie fires.

.......... 2 

ND ....................................... ................................................................... 1–01–05 ...... continuing .... 12–21–05 .... 8–21–06 ...... S2198 ........ Drought, late spring frosts, extreme 

heat, high winds, hail, prairie fires.

.......... 3 

NE ........................................ ................................................................... 1–01–05 ...... continuing .... 12–21–05 .... 8–21–06 ...... S2198 ........ Drought, late spring frosts, extreme 

heat, high winds, hail, prairie fires.

.......... 3 

WY ....................................... ................................................................... 1–01–05 ...... continuing .... 12–21–05 .... 8–21–06 ...... S2198 ........ Drought, late spring frosts, extreme 

heat, high winds, hail, prairie fires.

.......... 1 

TX ........................................ Cooke ......................................................... 3–01–05 ...... continuing .... 12–21–05 .... 8–21–06 ...... S2199 ........ Drought, excessive temperatures .... 1 4 OK ........................................ ................................................................... 3–01–05 ...... continuing .... 12–21–05 .... 8–21–06 ...... S2199 ........ Drought, excessive temperatures .... .......... 1 
451 

TX ........................................ Falls .......................................................... 2–01–05 ...... 10–21–05 .... 12–21–05 .... 8–21–06 ...... S2200 ........ Drought ............................................ 1 5 TX ........................................ McLennan .................................................. 3–01–05 ...... continuing .... 12–21–05 .... 8–21–06 ...... S2201 ........ Drought ............................................ 1 6 MS ....................................... All MS Counties, except Pontotoc & Union 1–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2202 ........ Hurricane Rita Drought ................... 80 2 AL ........................................ ................................................................... 1–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2202 ........ Hurricane Rita Drought ................... .......... 10 AR ........................................ ................................................................... 1–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2202 ........ Hurricane Rita Drought ................... .......... 5 LA ........................................ ................................................................... 1–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2202 ........ Hurricane Rita Drought ................... .......... 10 TN ........................................ ................................................................... 1–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2202 ........ Hurricane Rita Drought ................... .......... 5 NJ ........................................ Atlantic, Bergen, Burlington, Camden, 

Cape May, Cumberland, Essex, Gloucester, Hunterdon, Mercer, Middlesex, Monmouth, Morris, Ocean, Passaic, Salem, Somerset, Sussex, Warren.

6–01–05 ...... 10–06–05 .... 1–09–06 ...... 9–11–06 ...... S2203 ........ Drought, high humidity, excessive 

heat.

19 2 

DE ........................................ ................................................................... 6–01–05 ...... 10–06–05 .... 1–09–06 ...... 9–11–06 ...... S2203 ........ Drought, high humidity, excessive 

heat.

.......... 1 

NY ........................................ ................................................................... 6–01–05 ...... 10–06–05 .... 1–09–06 ...... 9–11–06 ...... S2203 ........ Drought, high humidity, excessive 

heat.

.......... 6 

PA ........................................ ................................................................... 6–01–05 ...... 10–06–05 .... 1–09–06 ...... 9–11–06 ...... S2203 ........ Drought, high humidity, excessive 

heat.

.......... 7 

NY ........................................ (1) Allegany, Cattaraugus, Cayuga, Orleans, Rensselaer, Steuben, Yates.

(2) Dutchess, Putnam, Rensselaer, Suffolk, Ulster, Westchester.

4–01–05 ......10–07–05 ....

continuing ....continuing ....

1–09–06 ...... 9–11–06 ...... S2204 ........ (1) Drought; drought related disasters.

(2) Excessive rain, flooding; related 

disasters.

12 26 

CT ........................................ ................................................................... 4–01–05 ......

10–07–05 ....

continuing ....continuing ....

1–09–06 ...... 9–11–06 ...... S2204 ........ (1) Drought; drought related disasters.

(2) Excessive rain, flooding; related 

disasters.

.......... 2 

MA ....................................... ................................................................... 4–01–05 ......

10–07–05 ....

continuing ....continuing ....

1–09–06 ...... 9–11–06 ...... S2204 ........ (1) Drought; drought related disasters.

(2) Excessive rain, flooding; related 

disasters.

.......... 1 

PA ........................................ ................................................................... 4–01–05 ......

10–07–05 ....

continuing ....continuing ....

1–09–06 ...... 9–11–06 ...... S2204 ........ (1) Drought; drought related disasters.

(2) Excessive rain, flooding; related 

disasters.

.......... 4 

VT ........................................ ................................................................... 4–01–05 ......

10–07–05 ....

continuing ....continuing ....

1–09–06 ...... 9–11–06 ...... S2204 ........ (1) Drought; drought related disasters.

(2) Excessive rain, flooding; related 

disasters.

.......... 1 

TX ........................................ Duval ......................................................... 10–27–05 .... 10–27–05 .... 1–09–06 ...... 9–11–06 ...... S2205 ........ Excessive rain, hail, high winds, 

lightning, tornado.

1 7 
452 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

TX ........................................ Ellis ........................................................... 2–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2206 ........ Drought ............................................ 1 7 TX ........................................ Frio ............................................................ 5–01–05 ...... 10–24–05 .... 1–09–06 ...... 9–11–06 ...... S2207 ........ Drought ............................................ 1 7 TX ........................................ Gregg, Smith, Upshur ............................... 4–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2208 ........ Drought, excessive heat .................. 3 9 TX ........................................ Hill ............................................................. 2–01–05 ...... 10–24–05 .... 1–09–06 ...... 9–11–06 ...... S2209 ........ Drought ............................................ 1 6 TX ........................................ Jim Wells ................................................... 10–27–05 .... 10–27–05 .... 1–09–06 ...... 9–11–06 ...... S2210 ........ Excessive rain, flooding, hail, high 

winds, lightning, tornado.

1 6 

TX ........................................ Kimble ....................................................... 9–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2211 ........ Drought ............................................ 1 7 TX ........................................ Lynn ........................................................... 8–28–05 ...... 9–14–05 ...... 1–09–06 ...... 9–11–06 ...... S2212 ........ Excessive rain, hail, high winds, 

lightning.

1 7 

TX ........................................ Mills, San Saba ........................................ 9–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2213 ........ Drought ............................................ 2 7 TX ........................................ Parker, Wharton ........................................ 6–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2214 ........ Drought ............................................ 2 12 WA ....................................... Benton, Clark, Columbia, Cowlitz, Douglas, Franklin, Kittitas, Klickitat, Lincoln, Skamania, Wahkiakum, Walla 

Walla, Yakima.

1–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2215 ........ Drought ............................................ 13 13 

OR ....................................... ................................................................... 1–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2215 ........ Drought ............................................ .......... 10 WA ....................................... (1) Garfield, Whitman ...............................

(2) Pacific .................................................

1–01–05 ......09–09–05 ....

continuing ....09–09–05 ....

1–09–06 ...... 9–11–06 ...... S2216 ........ (1) Drought ......................................

(2) Hailstorm ...................................

3 9 

ID ......................................... ................................................................... 1–01–05 ......

09–09–05 ....

continuing ....09–09–05 ....

1–09–06 ...... 9–11–06 ...... S2216 ........ Drought ............................................ .......... 3 

OR ....................................... ................................................................... 1–01–05 ......

09–09–05 ....

continuing ....09–09–05 ....

1–09–06 ...... 9–11–06 ...... S2216 ........ Drought ............................................ .......... 1 

CO ....................................... Logan ........................................................ 1–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2217 ........ Drought, crop diseases ................... 1 6 NE ........................................ ................................................................... 1–01–05 ...... continuing .... 1–09–06 ...... 9–11–06 ...... S2217 ........ Drought, crop diseases ................... .......... 2 TX ........................................ Wilson ........................................................ 3–20–05 ...... 11–14–05 .... 1–09–06 ...... 9–11–06 ...... S2218 ........ Drought ............................................ 1 5 TX ........................................ Denton, Kaufman, Robertson, Rockwall, 

Shelby, Wise.

3–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2219 ........ Drought ............................................ 6 24 

LA ........................................ ................................................................... 3–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2219 ........ Drought ............................................ .......... 2 TX ........................................ Gillespie .................................................... 5–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2220 ........ Drought ............................................ 1 6 
453 

IN ......................................... Bartholomew, Clark, Crawford, Dearborn, 

Elkhart, Floyd, Harrison, Jackson, Jasper, Jefferson, Kosciusko, Lake, LaPorte, Newton, Ohio, Orange, Porter, Posey, Scott, St. Joseph, Starke, Switzerland, Warrick, Washington.

6–01–05 ...... 8–31–05 ...... 1–17–06 ...... 9–18–06 ...... S2221 ........ Drought ............................................ 24 25 

IL ......................................... ................................................................... 6–01–05 ...... 8–31–05 ...... 1–17–06 ...... 9–18–06 ...... S2221 ........ Drought ............................................ .......... 6 KY ........................................ ................................................................... 6–01–05 ...... 8–31–05 ...... 1–17–06 ...... 9–18–06 ...... S2221 ........ Drought ............................................ .......... 11 MI ........................................ ................................................................... 6–01–05 ...... 8–31–05 ...... 1–17–06 ...... 9–18–06 ...... S2221 ........ Drought ............................................ .......... 3 OH ....................................... ................................................................... 6–01–05 ...... 8–31–05 ...... 1–17–06 ...... 9–18–06 ...... S2221 ........ Drought ............................................ .......... 2 SD ........................................ Lawrence ................................................... 1–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2222 ........ Drought, late spring frosts, extreme 

heat, high winds, hail, prairie fires.

1 3 

WY ....................................... ................................................................... 1–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2222 ........ Drought, late spring frosts, extreme 

heat, high winds, hail, prairie fires.

.......... 2 

TX ........................................ Bee, De Witt, Hood, Somervell .................. 6–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2223 ........ Drought ............................................ 4 14 TX ........................................ Brazos, Dimmit, Freestone, Guadalupe, La 

Salle, Madison, Stephens, Zavala.

4–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2224 ........ Drought ............................................ 8 31 

TX ........................................ Edwards, Hamilton .................................... 9–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2225 ........ Drought ............................................ 2 13 TX ........................................ Hall ............................................................ 10–10–05 .... 10–10–05 .... 1–17–06 ...... 9–18–06 ...... S2226 ........ Excessive rain, hail, high winds ..... 1 6 TX ........................................ Hardeman .................................................. 1–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2227 ........ Drought ............................................ 1 4 OK ........................................ ................................................................... 1–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2227 ........ Drought ............................................ .......... 2 TX ........................................ Medina ...................................................... 4–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2228 ........ Drought, excessive heat .................. 1 6 TX ........................................ Montague .................................................. 8–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2229 ........ Drought ............................................ 1 4 OK ........................................ ................................................................... 8–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2229 ........ Drought ............................................ .......... 2 TX ........................................ Runnels ..................................................... 5–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2230 ........ Drought, excessive temperatures .... 1 6 TX ........................................ Williamson ................................................. 4–15–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2231 ........ Drought ............................................ 1 6 TX ........................................ Zapata ....................................................... 1–01–05 ...... continuing .... 1–17–06 ...... 9–18–06 ...... S2232 ........ Drought ............................................ 1 3 MT ....................................... Hill Co. & Rocky Boy Indian Reservation 8–10–05 ......

01–01–05 ....

8–10–05 ......continuing ....

1–27–06 ...... 9–27–06 ...... S2233 ........ (1) Severe hail, windstorm .............

(2) Drought ......................................

1 3 

TX ........................................ Austin, Cass, Eastland, Palo Pinto .......... 8–01–05 ...... continuing .... 1–23–06 ...... 9–25–06 ...... S2234 ........ Drought ............................................ 4 19 AR ........................................ ................................................................... 8–01–05 ...... continuing .... 1–23–06 ...... 9–25–06 ...... S2234 ........ Drought ............................................ .......... 1 LA ........................................ ................................................................... 8–01–05 ...... continuing .... 1–23–06 ...... 9–25–06 ...... S2234 ........ Drought ............................................ .......... 1 TX ........................................ Caldwell, Comal, Hays .............................. 8–01–05 ...... continuing .... 1–23–06 ...... 9–25–06 ...... S2235 ........ Drought ............................................ 3 8 TX ........................................ Goliad, McMullen ...................................... 7–01–05 ...... continuing .... 1–23–06 ...... 9–25–06 ...... S2236 ........ Drought ............................................ 2 11 KS ........................................ Cheyenne ................................................... 1–01–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2237 ........ Drought, excessive heat, high 

winds.

1 2 

CO ....................................... ................................................................... 1–01–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2237 ........ Drought, excessive heat, high 

winds.

.......... 2 
454 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

NE ........................................ ................................................................... 1–01–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2237 ........ Drought, excessive heat, high 

winds.

.......... 1 

KS ........................................ Sherman, Wallace ..................................... 6–19–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2238 ........ Severe storms .................................. 2 6 CO ....................................... ................................................................... 6–19–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2238 ........ Severe storms .................................. .......... 2 NY ........................................ Cayuga, Ontario, Tompkins, Wayne .......... 12–20–04 .... 12–20–04 .... 2–01–06 ...... 10–02–06 .... S2239 ........ Freeze, excessive cold temperatures 4 11 TX ........................................ Anderson, Dallas ....................................... 3–01–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2240 ........ Drought ............................................ 2 12 TX ........................................ Blanco ....................................................... 5–01–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2241 ........ Drought ............................................ 1 7 TX ........................................ Gonzales .................................................... 7–01–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2242 ........ Drought ............................................ 1 8 TX ........................................ Haskell ...................................................... 9–30–05 ...... 9–30–05 ...... 2–01–06 ...... 10–02–06 .... S2243 ........ Excessive rain, hail, high winds ..... 1 7 TX ........................................ Karnes ....................................................... 7–25–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2244 ........ Drought, abnormally high temperatures. 1 7 TX ........................................ Kinney ........................................................ 3–15–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2245 ........ Drought, excessive heat .................. 1 5 TX ........................................ Limestone .................................................. 4–01–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2246 ........ Drought ............................................ 1 7 TX ........................................ Live Oak .................................................... 7–01–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2247 ........ Drought ............................................ 1 7 TX ........................................ Starr .......................................................... 1–01–05 ...... continuing .... 2–01–06 ...... 10–02–06 .... S2248 ........ Drought, excessive heat .................. 1 4 AR ........................................ Conway ...................................................... 11–27–05 .... 11–27–05 .... 2–07–06 ...... 10–09–06 .... S2249 ........ Excessive rainfall, high winds, tornadoes, lightning. 1 5 AR ........................................ Arkansas, Ashley, Chicot, Conway, 

Crittenden, Desha, Drew, Jefferson, Lee, Lincoln, Little River, Lonoke, Monroe, Phillips, Pope, Prairie, St. Francis, Woodruff.

9–24–05 ...... 9–24–05 ...... 2–07–06 ...... 10–09–06 .... S2250 ........ Excessive rainfall, high winds, tornadoes, lightning, due to Tropical Storm Rita. 18 22 

LA ........................................ ................................................................... 9–24–05 ...... 9–24–05 ...... 2–07–06 ...... 10–09–06 .... S2250 ........ Excessive rainfall, high winds, tornadoes, lightning, due to Tropical Storm Rita. .......... 4 MS ....................................... ................................................................... 9–24–05 ...... 9–24–05 ...... 2–07–06 ...... 10–09–06 .... S2250 ........ Excessive rainfall, high winds, tornadoes, lightning, due to Tropical Storm Rita. .......... 6 OK ........................................ ................................................................... 9–24–05 ...... 9–24–05 ...... 2–07–06 ...... 10–09–06 .... S2250 ........ Excessive rainfall, high winds, tornadoes, lightning, due to Tropical Storm Rita. .......... 1 TN ........................................ ................................................................... 9–24–05 ...... 9–24–05 ...... 2–07–06 ...... 10–09–06 .... S2250 ........ Excessive rainfall, high winds, tornadoes, lightning, due to Tropical Storm Rita. .......... 2 
455 

TX ........................................ ................................................................... 9–24–05 ...... 9–24–05 ...... 2–07–06 ...... 10–09–06 .... S2250 ........ Excessive rainfall, high winds, tornadoes, lightning, due to Tropical Storm Rita. .......... 1 MA ....................................... Bristol, Plymouth ....................................... 6–01–05 ...... 9–30–05 ...... 2–09–06 ...... 10–09–06 .... S2251 ........ Drought ............................................ 2 3 RI ......................................... ................................................................... 6–01–05 ...... 9–30–05 ...... 2–09–06 ...... 10–09–06 .... S2251 ........ Drought ............................................ .......... 3 OR ....................................... Hood River ................................................. 6–01–05 ...... 6–30–05 ...... 2–09–06 ...... 10–09–06 .... S2252 ........ Severe Weather events .................... 1 3 WA ....................................... ................................................................... 6–01–05 ...... 6–30–05 ...... 2–09–06 ...... 10–09–06 .... S2252 ........ Severe Weather events .................... .......... 2 TX ........................................ Bandera ..................................................... 8–01–05 ...... continuing .... 2–09–06 ...... 10–09–06 .... S2253 ........ Drought ............................................ 1 6 TX ........................................ Colorado .................................................... 6–01–05 ...... continuing .... 2–09–06 ...... 10–09–06 .... S2254 ........ Drought, excessive heat, high 

winds.

1 5 

TX ........................................ Jack, Washington ...................................... 4–01–05 ...... continuing .... 2–09–06 ...... 10–09–06 .... S2255 ........ Drought ............................................ 2 14 TX ........................................ Kendall ...................................................... 5–01–05 ...... continuing .... 2–09–06 ...... 10–09–06 .... S2256 ........ Drought ............................................ 1 6 OR ....................................... Sherman .................................................... 1–01–05 ...... continuing .... 2–09–06 ...... 10–09–06 .... S2257 ........ Drought ............................................ 1 2 WA ....................................... ................................................................... 1–01–05 ...... continuing .... 2–09–06 ...... 10–09–06 .... S2257 ........ Drought ............................................ .......... 1 TX ........................................ Wise ........................................................... 12–26–05 .... 12–27–05 .... 2–09–06 ...... 10–09–06 .... S2258 ........ Fire, high winds .............................. 1 6 TX ........................................ Callahan .................................................... 12–26–05 .... continuing .... 2–09–06 ...... 10–09–06 .... S2259 ........ Fire, high winds .............................. 1 6 CT ........................................ Entire State ............................................... 6–01–05 ...... 10–15–05 .... 2–13–06 ...... 10–13–06 .... S2260 ........ Drought ............................................ 8 ..........MA ....................................... ................................................................... 6–01–05 ...... 10–15–05 .... 2–13–06 ...... 10–13–06 .... S2260 ........ Drought ............................................ .......... 3 NY ........................................ ................................................................... 6–01–05 ...... 10–15–05 .... 2–13–06 ...... 10–13–06 .... S2260 ........ Drought ............................................ .......... 3 RI ......................................... ................................................................... 6–01–05 ...... 10–15–05 .... 2–13–06 ...... 10–13–06 .... S2260 ........ Drought ............................................ .......... 3 NY ........................................ Broome, Delaware ..................................... 5–01–05 ...... 9–30–05 ...... 2–13–06 ...... 10–13–06 .... S2261 ........ Drought, heat .................................. 2 8 PA ........................................ ................................................................... 5–01–05 ...... 9–30–05 ...... 2–13–06 ...... 10–13–06 .... S2261 ........ Drought, heat .................................. .......... 2 NY ........................................ Clinton ....................................................... 10–06–05 .... 10–06–05 .... 2–13–06 ...... 10–13–06 .... S2262 ........ High winds ...................................... 1 2 VT ........................................ ................................................................... 10–06–05 .... 10–06–05 .... 2–13–06 ...... 10–13–06 .... S2262 ........ High winds ...................................... .......... 2 NY ........................................ Clinton, Essex ........................................... 10–25–05 .... 10–25–05 .... 2–13–06 ...... 10–13–06 .... S2263 ........ Excessive rain, excessive snow ....... 2 4 VT ........................................ ................................................................... 10–25–05 .... 10–25–05 .... 2–13–06 ...... 10–13–06 .... S2263 ........ Excessive rain, excessive snow ....... .......... 3 NY ........................................ Franklin ..................................................... 10–07–05 ....

10–20–05 ....

10–24–05 ....10–22–05 ....

2–13–06 ...... 10–13–06 .... S2264 ........ Excessive rain Freeze ...................... 1 4 

NY ........................................ Monroe ....................................................... 9–01–05 ...... 10–31–05 .... 2–13–06 ...... 10–13–06 .... S2265 ........ Excessive rain ................................. 1 5 NY ........................................ Ontario ...................................................... 9–15–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2266 ........ Excessive rain ................................. 1 6 TN ........................................ Bradley, Cumberland, DeKalb, Johnson, 

Macon, Polk, Trousdale, Warren.

5–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2267 ........ Drought, high temperatures ............ 8 23 

GA ........................................ ................................................................... 5–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2267 ........ Drought, high temperatures ............ .......... 4 KY ........................................ ................................................................... 5–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2267 ........ Drought, high temperatures ............ .......... 2 NC ....................................... ................................................................... 5–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2267 ........ Drought, high temperatures ............ .......... 4 VA ........................................ ................................................................... 5–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2267 ........ Drought, high temperatures ............ .......... 2 TN ........................................ Bradley, Polk ............................................. 8–29–05 ...... 9–30–05 ...... 2–13–06 ...... 10–13–06 .... S2268 ........ Hurricane related wind and storms 2 4 GA ........................................ ................................................................... 8–29–05 ...... 9–30–05 ...... 2–13–06 ...... 10–13–06 .... S2268 ........ Hurricane related wind and storms .......... 4 NC ....................................... ................................................................... 8–29–05 ...... 9–30–05 ...... 2–13–06 ...... 10–13–06 .... S2268 ........ Hurricane related wind and storms .......... 1 TX ........................................ Cherokee .................................................... 3–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2269 ........ Drought, frost .................................. 1 7 
456 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

TX ........................................ Cooke ......................................................... 12–27–05 .... 12–27–05 .... 2–13–06 ...... 10–13–06 .... S2270 ........ Fire .................................................. 1 4 OK ........................................ ................................................................... 12–27–05 .... 12–27–05 .... 2–13–06 ...... 10–13–06 .... S2270 ........ Fire .................................................. .......... 1 TX ........................................ Fayette ....................................................... 4–15–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2271 ........ Drought ............................................ 1 8 TX ........................................ Lavaca ....................................................... 9–13–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2272 ........ Drought, excessive temperatures, 

high winds.

1 6 

TX ........................................ Palo Pinto .................................................. 1–01–06 ...... 1–01–06 ...... 2–13–06 ...... 10–13–06 .... S2273 ........ High winds, wildfire ........................ 1 7 TX ........................................ Rusk .......................................................... 3–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2274 ........ Drought ............................................ 1 7 WI ........................................ Adams, Brown, Burnett, Calumet, Dodge, 

Door, Fond du Lac, Kenosha, Kewaunee, Manitowoc, Marinette, Marquette, Oconto, Racine, Sheboygan, Walworth, Washburn, Waupaca.

3–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2275 ........ Drought ............................................ 18 28 

IL ......................................... ................................................................... 3–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2275 ........ Drought ............................................ .......... 3 MI ........................................ ................................................................... 3–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2275 ........ Drought ............................................ .......... 2 MN ....................................... ................................................................... 3–01–05 ...... continuing .... 2–13–06 ...... 10–13–06 .... S2275 ........ Drought ............................................ .......... 2 PA ........................................ Armstrong, Bedford, Bradford, Centre, 

Clearfield, Clinton, Elk, Fayette, Fulton, Greene, Jefferson, Lackawanna, Lehigh, Luzerne, McKean, Pike, Potter, Susquehanna, Sullivan, Tioga, Washington, Wayne, Wyoming.

5–01–05 ...... continuing .... 2–21–06 ...... 10–23–06 .... S2276 ........ Drought ............................................ 23 27 

MD ....................................... ................................................................... 5–01–05 ...... continuing .... 2–21–06 ...... 10–23–06 .... S2276 ........ Drought ............................................ .......... 3 NJ ........................................ ................................................................... 5–01–05 ...... continuing .... 2–21–06 ...... 10–23–06 .... S2276 ........ Drought ............................................ .......... 1 NY ........................................ ................................................................... 5–01–05 ...... continuing .... 2–21–06 ...... 10–23–06 .... S2276 ........ Drought ............................................ .......... 10 OH ....................................... ................................................................... 5–01–05 ...... continuing .... 2–21–06 ...... 10–23–06 .... S2276 ........ Drought ............................................ .......... 1 WV ....................................... ................................................................... 5–01–05 ...... continuing .... 2–21–06 ...... 10–23–06 .... S2276 ........ Drought ............................................ .......... 7 TX ........................................ Sterling ...................................................... 1–01–06 ...... 1–01–06 ...... 2–21–06 ...... 10–23–06 .... S2277 ........ Fire .................................................. 1 6 TX ........................................ Tom Green ................................................. 1–01–06 ...... continuing .... 2–23–06 ...... 10–23–06 .... S2278 ........ Grass fires ....................................... 1 8 VA ........................................ Bedford, Hanover, Russell, Wise ............... 6–01–05 ...... continuing .... 2–23–06 ...... 10–23–06 .... S2195, 

Amendment 2.

Drought, high temperatures ............ 4 24 

KY ........................................ ................................................................... 6–01–05 ...... continuing .... 2–23–06 ...... 10–23–06 .... S2195, 

Amendment 2.

Drought, high temperatures ............ .......... 3 
457 

VA ........................................ Culpeper, Goochland, Grayson, King William, Surry, Washington. 6–01–05 ...... continuing .... 2–28–06 ...... 10–30–06 .... S2195, Amendment 1. Drought, high temperatures ............ 6 30 NC ....................................... ................................................................... 6–01–05 ...... continuing .... 2–28–06 ...... 10–30–06 .... S2195, 

Amendment 1.

Drought, high temperatures ............ .......... 3 

TN ........................................ ................................................................... 6–01–05 ...... continuing .... 2–28–06 ...... 10–30–06 .... S2195, 

Amendment 1.

Drought, high temperatures ............ .......... 2 

OK ........................................ Entire State ............................................... 7–01–05 ...... continuing .... 2–28–06 ...... 10–30–06 .... S2279 ........ Drought, high temperatures, high 

winds, fire.

77 ..........

AR ........................................ ................................................................... 7–01–05 ...... continuing .... 2–28–06 ...... 10–30–06 .... S2279 ........ Drought, high temperatures, high 

winds, fire.

.......... 8 

CO ....................................... ................................................................... 7–01–05 ...... continuing .... 2–28–06 ...... 10–30–06 .... S2279 ........ Drought, high temperatures, high 

winds, fire.

.......... 1 

KS ........................................ ................................................................... 7–01–05 ...... continuing .... 2–28–06 ...... 10–30–06 .... S2279 ........ Drought, high temperatures, high 

winds, fire.

.......... 14 

MO ....................................... ................................................................... 7–01–05 ...... continuing .... 2–28–06 ...... 10–30–06 .... S2279 ........ Drought, high temperatures, high 

winds, fire.

.......... 2 

NM ....................................... ................................................................... 7–01–05 ...... continuing .... 2–28–06 ...... 10–30–06 .... S2279 ........ Drought, high temperatures, high 

winds, fire.

.......... 1 

TX ........................................ ................................................................... 7–01–05 ...... continuing .... 2–28–06 ...... 10–30–06 .... S2279 ........ Drought, high temperatures, high 

winds, fire.

.......... 20 
458 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

GA ........................................ Appling, Bacon, Banks, Barrow, Bartow, 

Ben Hill, Bibb, Bleckley, Bryan, Bulloch, Butts, Carroll, Catoosa, Chattooga, Cherokee, Clarke, Clayton, Clinch, Cobb, Columbia, Coweta, Crawford, Crisp, Dade, Dawson, Decatur, De Kalb, Dodge, Dooly, Douglas, Elbert, Emanuel, Evans, Fannin, Fayette, Floyd, Forsyth, Franklin, Fulton, Gilmer, Glascock, Gordon, Grady, Gwinnett, Habersham, Hall, Haralson, Harris, Hart, Heard, Henry, Houston, Irwin, Jackson, Jeff Davis, Jefferson, Johnson, Lamar, Lanier, Laurens, Lincoln, Long, Lumpkin, McDuffie, Macon, Madison, Marion, Meriwether, Miller, Mitchell, Monroe, Montgomery, Murray, Muscogee, Oconee, Oglethorpe, Paulding, Peach, Pickens, Pike, Polk, Pulaski, Rabun, Richmond, Rockdale, Screven, Seminole, Spalding, Stephens, Sumter, Talbot, Tattnall, Taylor, Telfair, Thomas, Towns, Treutlen, Troup, Turner, Twiggs, Union, Upson, Walker, Walton, Warren, Washington, Wayne, Wheeler, White, Whitfield, Wilkes, Wilkinson.

8–01–05 ...... continuing .... 3–07–06 ...... 11–07–06 .... S2280 ........ Drought ............................................ 112 39 

AL ........................................ ................................................................... 8–01–05 ...... continuing .... 3–07–06 ...... 11–07–06 .... S2280 ........ Drought ............................................ .......... 9 FL ........................................ ................................................................... 8–01–05 ...... continuing .... 3–07–06 ...... 11–07–06 .... S2280 ........ Drought ............................................ .......... 6 NC ....................................... ................................................................... 8–01–05 ...... continuing .... 3–07–06 ...... 11–07–06 .... S2280 ........ Drought ............................................ .......... 4 SC ........................................ ................................................................... 8–01–05 ...... continuing .... 3–07–06 ...... 11–07–06 .... S2280 ........ Drought ............................................ .......... 8 TN ........................................ ................................................................... 8–01–05 ...... continuing .... 3–07–06 ...... 11–07–06 .... S2280 ........ Drought ............................................ .......... 4 
459 

TX ........................................ Angelina, Aransas, Archer, Armstrong, 

Atascosa, Bailey, Bastrop, Baylor, Bell, Bexar, Borden, Briscoe, Brown, Burnet, Callahan, Cameron, Carson, Castro, Childress, Clay, Cochran, Coke, Coleman, Collingsworth, Comanche, Concho, Coryell, Cottle, Crockett, Crosby, Dawson, Deaf Smith, Dickens, Donley, Erath, Fisher, Floyd, Fort Bend, Gaines, Garza, Glasscock, Gray, Grimes, Hale, Hall, Hansford, Harris, Harrison, Haskell, Hemphill, Hockley, Howard, Hutchinson, Irion, Jackson, Jasper, Jones, Kent, Kerr, King, Knox, Lamb, Lampasas, Lipscomb, Lubbock, Lynn, Marion, Maverick, McCulloch, Menard, Milam, Mitchell, Montgomery, Moore, Motley, Newton, Nolan, Nueces, Ochiltree, Oldham, Panola, Parmer, Polk, Potter, Randall, Reagan, Real, Refugio, Roberts, Sabine, San Augustine, San Jacinto, San Patricio, Schleicher, Scurry, Shackelford, Sherman, Sterling, Stonewall, Sutton, Swisher, Taylor, Terry, Throckmorton, Tom Green, Travis, Trinity, Tyler, Upton, Uvalde, Val Verde, Victoria, Walker, Wheeler, Wichita, Yoakum, Young.

4–01–05 ...... continuing .... 3–07–06 ...... 11–07–06 .... S2281 ........ Drought, above normal temperatures, wildfires. 117 87 

LA ........................................ ................................................................... 4–01–05 ...... continuing .... 3–07–06 ...... 11–07–06 .... S2281 ........ Drought, above normal temperatures, wildfires. .......... 6 NM ....................................... ................................................................... 4–01–05 ...... continuing .... 3–07–06 ...... 11–07–06 .... S2281 ........ Drought, above normal temperatures, wildfires. .......... 4 OK ........................................ ................................................................... 4–01–05 ...... continuing .... 3–07–06 ...... 11–07–06 .... S2281 ........ Drought, above normal temperatures, wildfires. .......... 10 NY ........................................ Cortland, Tompkins ................................... 10–20–05 .... 11–20–05 .... 3–10–06 ...... 11–10–06 .... S2282 ........ Excessive rain ................................. 2 9 TN ........................................ Anderson, Campbell, Cannon, Carter, 

Knox, Sullivan.

5–01–05 ...... continuing .... 3–10–06 ...... 11–10–06 .... S2283 ........ Drought, higher than normal temperatures. 6 19 

KY ........................................ ................................................................... 5–01–05 ...... continuing .... 3–10–06 ...... 11–10–06 .... S2283 ........ Drought, higher than normal temperatures. .......... 2 
460 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

NC ....................................... ................................................................... 5–01–05 ...... continuing .... 3–10–06 ...... 11–10–06 .... S2283 ........ Drought, higher than normal temperatures. .......... 2 VA ........................................ ................................................................... 5–01–05 ...... continuing .... 3–10–06 ...... 11–10–06 .... S2283 ........ Drought, higher than normal temperatures. .......... 3 TX ........................................ Jack ........................................................... 1–12–06 ...... 1–12–06 ...... 3–10–06 ...... 11–10–06 .... S2284 ........ Wildfire, high winds ........................ 1 7 TX ........................................ Erath ......................................................... 1–01–06 ...... 1–01–06 ...... 3–29–06 ...... 11–29–06 .... S2285 ........ Wildfire ............................................ 1 7 WV ....................................... Barbour, Berkeley, Boone, Brooke, Cabell, 

Grant, Hampshire, Hancock, Hardy, Jefferson, Lincoln, Logan, Marion, Marshall, Mason, Mineral, Mingo, Monongalia, Morgan, Ohio, Pendleton, Preston, Putnam, Randolph, Taylor, Tucker, Tyler, Wayne, Wetzel.

3–01–05 ...... 11–30–05 .... 3–29–06 ...... 11–29–06 .... S2286 ........ Drought ............................................ 29 12 

KY ........................................ ................................................................... 3–01–05 ...... 11–30–05 .... 3–29–06 ...... 11–29–06 .... S2286 ........ Drought ............................................ .......... 4 MD ....................................... ................................................................... 3–01–05 ...... 11–30–05 .... 3–29–06 ...... 11–29–06 .... S2286 ........ Drought ............................................ .......... 3 OH ....................................... ................................................................... 3–01–05 ...... 11–30–05 .... 3–29–06 ...... 11–29–06 .... S2286 ........ Drought ............................................ .......... 8 PA ........................................ ................................................................... 3–01–05 ...... 11–30–05 .... 3–29–06 ...... 11–29–06 .... S2286 ........ Drought ............................................ .......... 4 VA ........................................ ................................................................... 3–01–05 ...... 11–30–05 .... 3–29–06 ...... 11–29–06 .... S2286 ........ Drought ............................................ .......... 8 CO ....................................... Huerfano, Kiowa, Las Animas, Sedgwick 3–01–05 ...... continuing .... 4–05–06 ...... 12–05–06 .... S2287 ........ Drought, related disasters .............. 4 14 KS ........................................ ................................................................... 3–01–05 ...... continuing .... 4–05–06 ...... 12–05–06 .... S2287 ........ Drought, related disasters .............. .......... 1 NE ........................................ ................................................................... 3–01–05 ...... continuing .... 4–05–06 ...... 12–05–06 .... S2287 ........ Drought, related disasters .............. .......... 4 NM ....................................... ................................................................... 3–01–05 ...... continuing .... 4–05–06 ...... 12–05–06 .... S2287 ........ Drought, related disasters .............. .......... 2 TX ........................................ Frio ............................................................ 1–01–06 ...... continuing .... 4–18–06 ...... 12–18–06 .... S2288 ........ Drought, high temperatures ............ 1 7 TX ........................................ Wheeler ...................................................... 3–12–06 ...... 3–15–06 ...... 4–18–06 ...... 12–18–06 .... S2289 ........ Fire, high winds .............................. 1 5 OK ........................................ ................................................................... 3–12–06 ...... 3–15–06 ...... 4–18–06 ...... 12–18–06 .... S2289 ........ Fire, high winds .............................. .......... 2 TX ........................................ Collingsworth ............................................ 3–12–06 ...... continuing .... 4–20–06 ...... 12–20–06 .... S2290 ........ Fire, high winds .............................. 1 5 OK ........................................ ................................................................... 3–12–06 ...... continuing .... 4–20–06 ...... 12–20–06 .... S2290 ........ Fire, high winds .............................. .......... 2 TX ........................................ Gray ........................................................... 3–12–06 ...... 3–12–06 ...... 4–20–06 ...... 12–20–06 .... S2291 ........ Fire, extreme wind ........................... 1 7 TX ........................................ Roberts ...................................................... 3–12–06 ...... 3–12–06 ...... 4–20–06 ...... 12–20–06 .... S2292 ........ Fire .................................................. 1 8 TX ........................................ Taylor ......................................................... 1–01–06 ...... continuing .... 4–20–06 ...... 12–20–06 .... S2293 ........ Drought ............................................ 1 6 HI ......................................... Honolulu, Kauai ......................................... 2–20–06 ...... 3–26–06 ...... 4–24–06 ...... 12–27–06 .... S2294 ........ Rain, flooding .................................. 2 ..........TX ........................................ Cottle ......................................................... 3–12–06 ...... continuing .... 5–03–06 ...... 1–03–07 ...... S2295 ........ Fire, high winds .............................. 1 7 AZ ........................................ All counties except La z .............................1–01–06 ...... continuing .... 5–09–06 ...... 1–09–07 ...... S2296 ........ Drought ............................................ 14 1 CA ........................................ ................................................................... 1–01–06 ...... continuing .... 5–09–06 ...... 1–09–07 ...... S2296 ........ Drought ............................................ .......... 2 
461 

CO ....................................... ................................................................... 1–01–06 ...... continuing .... 5–09–06 ...... 1–09–07 ...... S2296 ........ Drought ............................................ .......... 1 NM ....................................... ................................................................... 1–01–06 ...... continuing .... 5–09–06 ...... 1–09–07 ...... S2296 ........ Drought ............................................ .......... 6 NV ........................................ ................................................................... 1–01–06 ...... continuing .... 5–09–06 ...... 1–09–07 ...... S2296 ........ Drought ............................................ .......... 2 UT ........................................ ................................................................... 1–01–06 ...... continuing .... 5–09–06 ...... 1–09–07 ...... S2296 ........ Drought ............................................ .......... 3 TX ........................................ Armstrong .................................................. 1–01–06 ...... continuing .... 5–15–06 ...... 1–16–07 ...... S2297 ........ Drought, high winds ....................... 1 7 TX ........................................ Donley ........................................................ 1–01–06 ...... continuing .... 5–15–06 ...... 1–15–07 ...... S2298 ........ Fire, high temperatures .................. 1 7 TX ........................................ Hutchinson ................................................ 3–12–06 ...... 3–12–06 ...... 5–15–06 ...... 1–15–07 ...... S2299 ........ Fire .................................................. 1 7 TX ........................................ Runnels ..................................................... 1–01–06 ...... continuing .... 5–15–06 ...... 1–15–07 ...... S2300 ........ Drought ............................................ 1 6 NM ....................................... All counties except Chaves, Los Alamos .. 1–01–06 ...... continuing .... 5–18–06 ...... 1–18–07 ...... S2301 ........ Drought, high winds ....................... 31 2 AZ ........................................ ................................................................... 1–01–06 ...... continuing .... 5–18–06 ...... 1–18–07 ...... S2301 ........ Drought, high winds ....................... .......... 3 CO ....................................... ................................................................... 1–01–06 ...... continuing .... 5–18–06 ...... 1–18–07 ...... S2301 ........ Drought, high winds ....................... .......... 7 OK ........................................ ................................................................... 1–01–06 ...... continuing .... 5–18–06 ...... 1–18–07 ...... S2301 ........ Drought, high winds ....................... .......... 1 TX ........................................ ................................................................... 1–01–06 ...... continuing .... 5–18–06 ...... 1–18–07 ...... S2301 ........ Drought, high winds ....................... .......... 16 UT ........................................ ................................................................... 1–01–06 ...... continuing .... 5–18–06 ...... 1–18–07 ...... S2301 ........ Drought, high winds ....................... .......... 1 TX ........................................ Hemphill .................................................... 3–12–06 ...... 3–12–06 ...... 5–18–06 ...... 1–18–07 ...... S2302 ........ Fire .................................................. 1 4 OK ........................................ ................................................................... 3–12–06 ...... 3–12–06 ...... 5–18–06 ...... 1–18–07 ...... S2302 ........ Fire .................................................. .......... 2 TX ........................................ Coryell ....................................................... 3–24–06 ...... 3–24–06 ...... 5–22–06 ...... 1–22–07 ...... S2303 ........ Freeze .............................................. 1 5 TX ........................................ Gillespie .................................................... 1–01–06 ...... continuing .... 5–22–06 ...... 1–22–07 ...... S2304 ........ Drought ............................................ 1 6 TX ........................................ Lipscomb ................................................... 4–11–06 ...... 4–11–06 ...... 5–22–06 ...... 1–22–07 ...... S2305 ........ Wildfires .......................................... 1 3 OK ........................................ ................................................................... 4–11–06 ...... 4–11–06 ...... 5–22–06 ...... 1–22–07 ...... S2305 ........ Wildfires .......................................... .......... 2 TX ........................................ Oldham, Potter .......................................... 1–01–06 ...... continuing .... 5–30–06 ...... 1–30–07 ...... S2306 ........ Drought, high winds ....................... 2 7 NM ....................................... ................................................................... 1–01–06 ...... continuing .... 5–30–06 ...... 1–30–07 ...... S2306 ........ Drought, high winds ....................... .......... 1 TX ........................................ Armstrong .................................................. 3–05–06 ...... 3–11–06 ...... 5–31–06 ...... 1–31–07 ...... S2307 ........ Wildfires .......................................... 1 7 TX ........................................ Calhoun, Hamilton .................................... 1–01–06 ...... continuing .... 5–31–06 ...... 1–31–07 ...... S2308 ........ Drought ............................................ 2 11 TX ........................................ Cooke ......................................................... 4–28–06 ...... 4–28–06 ...... 5–31–06 ...... 1–31–07 ...... S2309 ........ Flash flooding, hail, high winds ..... 1 4 OK ........................................ ................................................................... 4–28–06 ...... 4–28–06 ...... 5–31–06 ...... 1–31–07 ...... S2309 ........ Flash flooding, hail, high winds ..... .......... 1 TX ........................................ Gillespie .................................................... 3–24–06 ...... 3–25–06 ...... 5–31–06 ...... 1–31–07 ...... S2310 ........ Freeze .............................................. 1 6 TX ........................................ Brewster .................................................... 1–01–06 ...... continuing .... 6–05–06 ...... 2–05–07 ...... S2311 ........ Drought, high winds ....................... 1 4 TX ........................................ Oldham ...................................................... 3–12–06 ...... 3–12–06 ...... 6–05–06 ...... 2–05–07 ...... S2312 ........ Wildfires .......................................... 1 5 NM ....................................... ................................................................... 3–12–06 ...... 3–12–06 ...... 6–05–06 ...... 2–05–07 ...... S2312 ........ Wildfires .......................................... .......... 1 AR ........................................ Ashley, Bradley .......................................... 4–07–06 ...... 4–07–06 ...... 6–12–06 ...... 2–12–07 ...... S2313 ........ Hail, high winds .............................. 2 5 LA ........................................ ................................................................... 4–07–06 ...... 4–07–06 ...... 6–12–06 ...... 2–12–07 ...... S2313 ........ Hail, high winds .............................. .......... 2 KS ........................................ Cherokee, Morton ...................................... 8–01–05 ...... continuing .... 6–12–06 ...... 2–12–07 ...... S2314 ........ Drought, high winds, wildfires, 

above-normal temperatures.

2 4 

CO ....................................... ................................................................... 8–01–05 ...... continuing .... 6–12–06 ...... 2–12–07 ...... S2314 ........ Drought, high winds, wildfires, 

above-normal temperatures.

.......... 2 

MO ....................................... ................................................................... 8–01–05 ...... continuing .... 6–12–06 ...... 2–12–07 ...... S2314 ........ Drought, high winds, wildfires, 

above-normal temperatures.

.......... 1 

OK ........................................ ................................................................... 8–01–05 ...... continuing .... 6–12–06 ...... 2–12–07 ...... S2314 ........ Drought, high winds, wildfires, 

above-normal temperatures.

.......... 4 
462 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

CA ........................................ Alameda, Amador, Butte, Calaveras, 

Contra Costa, El Dorado, Fresno, Glenn, Humboldt, Kings, Lake, Madera, Mendocino, Merced, Nevada, Plumas, Sacramento, San Joaquin, San Mateo, Shasta, Sierra, Solano, Sonoma, Stanislaus, Sutter, Tehama, Tulare, Yolo, Yuba.

12–17–06 .... 4–26–06 ...... 6–15–06 ...... 2–15–07 ...... S2315 ........ Storms: Excessive rainfall, hail, 

high winds, Frost, freeze, fluctuating temperatures.

29 21 

NV ........................................ ................................................................... 12–17–06 .... 4–26–06 ...... 6–15–06 ...... 2–15–07 ...... S2315 ........ Storms: Excessive rainfall, hail, 

high winds, Frost, freeze, fluctuating temperatures.

.......... 2 

TX ........................................ Bosque, Johnson, McLennan ..................... 1–01–06 ...... continuing .... 6–15–06 ...... 2–15–07 ...... S2316 ........ Drought ............................................ 3 12 TX ........................................ Terrell ........................................................ 1–01–06 ...... continuing .... 6–15–06 ...... 2–15–07 ...... S2317 ........ Drought, high winds ....................... 1 4 TX ........................................ Collin ......................................................... 5–09–06 ...... 5–09–06 ...... 6–19–06 ...... 2–19–07 ...... S2318 ........ Tornado ............................................ 1 6 TX ........................................ Kleberg ...................................................... 1–01–06 ...... continuing .... 6–19–06 ...... 2–19–07 ...... S2319 ........ Drought, excessive temperatures, 

high winds.

1 4 

TX ........................................ McLennan .................................................. 5–06–06 ...... 5–06–06 ...... 6–19–06 ...... 2–19–07 ...... S2320 ........ Excessive rain, hail, high winds, 

tornado.

1 6 

VT ........................................ Entire State ............................................... 5–01–06 ...... continuing .... 6–23–06 ...... 2–23–07 ...... S2321 ........ Severe weather; excessive rainfall .. 14 ..........MA ....................................... ................................................................... 5–01–06 ...... continuing .... 6–23–06 ...... 2–23–07 ...... S2321 ........ Severe weather; excessive rainfall .. .......... 2 NH ....................................... ................................................................... 5–01–06 ...... continuing .... 6–23–06 ...... 2–23–07 ...... S2321 ........ Severe weather; excessive rainfall .. .......... 4 NY ........................................ ................................................................... 5–01–06 ...... continuing .... 6–23–06 ...... 2–23–07 ...... S2321 ........ Severe weather; excessive rainfall .. .......... 4 CA ........................................ Placer ........................................................ 3–01–06 ...... 4–30–06 ...... 6–26–06 ...... 2–26–07 ...... S2322 ........ Excessive rainfall, hail .................... 1 5 NV ........................................ ................................................................... 3–01–06 ...... 4–30–06 ...... 6–26–06 ...... 2–26–07 ...... S2322 ........ Excessive rainfall, hail .................... .......... 3 CA ........................................ Placer ........................................................ 3–01–06 ...... 4–30–06 ...... 6–26–06 ...... 2–26–07 ...... S2322 ........ Excess rainfall [sic], hail ................ 1 ..........TX ........................................ McLennan .................................................. 3–24–06 ...... 3–25–06 ...... 6–29–06 ...... 3–01–07 ...... S2323 ........ Freeze .............................................. 1 6 TX ........................................ Mitchell ..................................................... 5–02–06 ...... 5–02–06 ...... 6–29–06 ...... 3–01–07 ...... S2324 ........ Flash flooding, hail, tornado .......... 1 7 
463 

AL ........................................ Baldwin, Coffee, Barbour, Bibb, Bullock, 

Butler, Chambers, Cherokee, Choctaw, Clarke, Clay, Etowah, Colbert, Conecuh, Coosa, Covington, Crenshaw, Cullman, Dale, Elmore, Escambia, Lee, Franklin, Geneva, Greene, Hale, Henry, Houston, Jackson, Lauderdale, Lawrence, Randolph, Macon, Madison, Marengo, Mobile, Monroe, Montgomery, Morgan, Perry, Pike, Russell, St. Clair, Sumter, Tallapoosa, Tuscaloosa, Washington, Wilcox.

1–01–06 ...... continuing .... 6–30–06 ...... 3–02–07 ...... S2325 ........ Drought, high temperatures ............ 48 18 

MS ....................................... ................................................................... 1–01–06 ...... continuing .... 6–30–06 ...... 3–02–07 ...... S2325 ........ Drought, high temperatures ............ .......... 6 TN ........................................ ................................................................... 1–01–06 ...... continuing .... 6–30–06 ...... 3–02–07 ...... S2325 ........ Drought, high temperatures ............ .......... 15 AL ........................................ ................................................................... 1–01–06 ...... continuing .... 6–30–06 ...... 3–02–07 ...... S2325 ........ Drought, high temperatures ............ .......... 10 AL ........................................ ................................................................... 1–01–06 ...... continuing .... 6–30–06 ...... 3–02–07 ...... S2325 ........ Drought, high temperatures ............ .......... 7 CA ........................................ Lassen ....................................................... 1–01–06 ...... 4–30–06 ...... 7–05–06 ...... 3–05–07 ...... S2326 ........ Excessive rainfall, flooding, cooler 

than normal temperatures.

1 4 

NV ........................................ ................................................................... 1–01–06 ...... 4–30–06 ...... 7–05–06 ...... 3–05–07 ...... S2326 ........ Excessive rainfall, flooding, cooler 

than normal temperatures.

.......... 1 

CO ....................................... Adams, Alamosa, Broomfield, Baca, 

Chaffee, Cheyenne, Conejos, Costilla, Custer, Denver, Dolores, Douglas, Elbert, Fremont, Hinsdale, Huerfano, Kit Carson, Lake, Las Animas, Mineral, Montezuma, Morgan, Prowers, Pueblo, Rio Grande, Saguache, San Miguel, Weld.

1–01–06 ...... continuing .... 7–10–06 ...... 3–12–07 ...... S2327 ........ Drought ............................................ 28 24 

AZ ........................................ ................................................................... 1–01–06 ...... continuing .... 7–10–06 ...... 3–12–07 ...... S2327 ........ Drought ............................................ .......... 1 KS ........................................ ................................................................... 1–01–06 ...... continuing .... 7–10–06 ...... 3–12–07 ...... S2327 ........ Drought ............................................ .......... 7 NE ........................................ ................................................................... 1–01–06 ...... continuing .... 7–10–06 ...... 3–12–07 ...... S2327 ........ Drought ............................................ .......... 1 NM ....................................... ................................................................... 1–01–06 ...... continuing .... 7–10–06 ...... 3–12–07 ...... S2327 ........ Drought ............................................ .......... 5 OK ........................................ ................................................................... 1–01–06 ...... continuing .... 7–10–06 ...... 3–12–07 ...... S2327 ........ Drought ............................................ .......... 1 UT ........................................ ................................................................... 1–01–06 ...... continuing .... 7–10–06 ...... 3–12–07 ...... S2327 ........ Drought ............................................ .......... 1 WY ....................................... ................................................................... 1–01–06 ...... continuing .... 7–10–06 ...... 3–12–07 ...... S2327 ........ Drought ............................................ .......... 1 NY ........................................ Cattaraugus, Chautauqua, Erie ................ 4–25–06 ...... 4–27–06 ...... 7–10–06 ...... 3–12–07 ...... S2328 ........ Frost ................................................ 3 4 PA ........................................ ................................................................... 4–25–06 ...... 4–27–06 ...... 7–10–06 ...... 3–12–07 ...... S2328 ........ Frost ................................................ .......... 3 
464 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

CO ....................................... Arapahoe, Archuleta, Bent, Boulder, 

Crowley, Delta, El Paso, Gunnison, Jefferson, Kiowa, La Plata, Montrose, Ouray, Park, Phillips, Teller, Washington.

1–01–06 ...... continuing .... 7–11–06 ...... 3–12–07 ...... S2329 ........ Drought ............................................ 17 37 

KS ........................................ ................................................................... 1–01–06 ...... continuing .... 7–11–06 ...... 3–12–07 ...... S2329 ........ Drought ............................................ .......... 11 NE ........................................ ................................................................... 1–01–06 ...... continuing .... 7–11–06 ...... 3–12–07 ...... S2329 ........ Drought ............................................ .......... 2 NM ....................................... ................................................................... 1–01–06 ...... continuing .... 7–11–06 ...... 3–12–07 ...... S2329 ........ Drought ............................................ .......... 2 UT ........................................ ................................................................... 1–01–06 ...... continuing .... 7–11–06 ...... 3–12–07 ...... S2329 ........ Drought ............................................ .......... 2 CO ....................................... Dolores, Montezuma, San Miguel ............. 5–09–06 ...... 5–30–06 ...... 7–13–06 ...... 3–13–07 ...... S2330 ........ Freeze .............................................. 3 4 AZ ........................................ ................................................................... 5–09–06 ...... 5–30–06 ...... 7–13–06 ...... 3–13–07 ...... S2330 ........ Freeze .............................................. .......... 1 NM ....................................... ................................................................... 5–09–06 ...... 5–30–06 ...... 7–13–06 ...... 3–13–07 ...... S2330 ........ Freeze .............................................. .......... 1 UT ........................................ ................................................................... 5–09–06 ...... 5–30–06 ...... 7–13–06 ...... 3–13–07 ...... S2330 ........ Freeze .............................................. .......... 1 NE ........................................ Boyd, Brown, Buffalo, Garfield, Howard, 

Kearney, Keya Paha, Loup, Rock, Sherman, Valley, Webster, Wheeler.

1–01–06 ...... continuing .... 7–13–06 ...... 3–13–07 ...... S2331 ........ High winds, excessive heat,a late 

freeze, drought.

13 18 

KS ........................................ ................................................................... 1–01–06 ...... continuing .... 7–13–06 ...... 3–13–07 ...... S2331 ........ High winds, excessive heat,a late 

freeze, drought.

.......... 2 

SD ........................................ ................................................................... 1–01–06 ...... continuing .... 7–13–06 ...... 3–13–07 ...... S2331 ........ High winds, excessive heat,a late 

freeze, drought.

.......... 4 

NE ........................................ Arthur, Banner, Blaine, Box Butte, Chase, 

Cherry, Cheyenne, Custer, Dawes, Dawson, Deuel, Dundy, Franklin, Frontier, Furnas, Garden, Gosper, Grant, Harlan, Hayes, Hitchcock, Holt, Hooker, Keith, Kimball, Lincoln, Logan, McPherson, Morrill, Perkins, Phelps, Red Willow, Scotts Bluff, Sheridan, Sioux, Thomas.

1–01–06 ...... continuing .... 7–13–06 ...... 3–13–07 ...... S2332 ........ High winds, excessive heat [high 

temperatures], drought.

36 15 

CO ....................................... ................................................................... 1–01–06 ...... continuing .... 7–13–06 ...... 3–13–07 ...... S2332 ........ High winds, excessive heat [high 

temperatures], drought.

.......... 5 

KS ........................................ ................................................................... 1–01–06 ...... continuing .... 7–13–06 ...... 3–13–07 ...... S2332 ........ High winds, excessive heat [high 

temperatures], drought.

.......... 6 
465 

SD ........................................ ................................................................... 1–01–06 ...... continuing .... 7–13–06 ...... 3–13–07 ...... S2332 ........ High winds, excessive heat [high 

temperatures], drought.

.......... 5 

WY ....................................... ................................................................... 1–01–06 ...... continuing .... 7–13–06 ...... 3–13–07 ...... S2332 ........ High winds, excessive heat [high 

temperatures], drought.

.......... 3 

OR ....................................... Malheur ..................................................... 3–29–06 ...... 5–10–06 ...... 7–13–06 ...... 3–13–07 ...... S2333 ........ Flooding, cooler temperatures, abnormally high precipitation. 1 3 ID ......................................... ................................................................... 3–29–06 ...... 5–10–06 ...... 7–13–06 ...... 3–13–07 ...... S2333 ........ Flooding, cooler temperatures, abnormally high precipitation. .......... 4 NV ........................................ ................................................................... 3–29–06 ...... 5–10–06 ...... 7–13–06 ...... 3–13–07 ...... S2333 ........ Flooding, cooler temperatures, abnormally high precipitation. .......... 1 AR ........................................ Jefferson .................................................... 5–10–06 ...... 5–10–06 ...... 7–13–06 ...... 3–13–07 ...... S2334 ........ Excessive rainfall, high winds, tornadoes, lightning. 1 6 AR ........................................ Little River ................................................ 5–04–06 ...... 5–04–06 ...... 7–13–06 ...... 3–13–07 ...... S2335 ........ Excessive thunderstorms, rainfall, 

high winds, hail, lightning.

1 4 

OK ........................................ ................................................................... 5–04–06 ...... 5–04–06 ...... 7–13–06 ...... 3–13–07 ...... S2335 ........ Excessive thunderstorms, rainfall, 

high winds, hail, lightning.

.......... 1 

TX ........................................ ................................................................... 5–04–06 ...... 5–04–06 ...... 7–13–06 ...... 3–13–07 ...... S2335 ........ Excessive thunderstorms, rainfall, 

high winds, hail, lightning.

.......... 1 

TX ........................................ Lee ............................................................. 4–20–06 ...... 4–20–06 ...... 7–13–06 ...... 3–13–07 ...... S2336 ........ High winds ...................................... 1 6 TX ........................................ Kenedy ....................................................... 1–01–06 ...... continuing .... 7–13–06 ...... 3–13–07 ...... S2337 ........ Drought, excessive temperatures, 

high winds.

1 4 

TX ........................................ Colorado, Pecos ......................................... 1–01–06 ...... continuing .... 7–20–06 ...... 3–20–07 ...... S2338 ........ Drought ............................................ 2 12 TX ........................................ Dimmit ...................................................... 1–01–06 ...... continuing .... 7–20–06 ...... 3–20–07 ...... S2339 ........ Drought ............................................ 1 5 TX ........................................ Duval ......................................................... 1–01–06 ...... continuing .... 7–20–06 ...... 3–20–07 ...... S2340 ........ Drought, high winds, high temperatures. 1 7 TX ........................................ Mason ........................................................ 1–01–06 ...... continuing .... 7–20–06 ...... 3–20–07 ...... S2341 ........ Drought, excessive heat .................. 1 6 TX ........................................ Nolan ......................................................... 1–01–06 ...... continuing .... 7–20–06 ...... 3–20–07 ...... S2342 ........ Drought, fire, high winds ................ 1 7 OK ........................................ Entire State ............................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2343 ........ Drought, extreme heat, high winds, 

stressful moisture conditions.

77 ..........

AR ........................................ ................................................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2343 ........ Drought, extreme heat, high winds, 

stressful moisture conditions.

.......... 8 

CO ....................................... ................................................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2343 ........ Drought, extreme heat, high winds, 

stressful moisture conditions.

.......... 1 

KS ........................................ ................................................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2343 ........ Drought, extreme heat, high winds, 

stressful moisture conditions.

.......... 14 

MO ....................................... ................................................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2343 ........ Drought, extreme heat, high winds, 

stressful moisture conditions.

.......... 2 

NM ....................................... ................................................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2343 ........ Drought, extreme heat, high winds, 

stressful moisture conditions.

.......... 1 
466 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

TX ........................................ ................................................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2343 ........ Drought, extreme heat, high winds, 

stressful moisture conditions.

.......... 20 

SD ........................................ Brule, Buffalo, Campbell, Corson, Custer, 

Dewey, Edmunds, Fall River, Faulk, Hughes, Hyde, Jackson, Jerauld, Jones, Lyman, Meade, Pennington, Perkins, Potter, Stanley, Sully, Walworth, Ziebach.

1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2344 ........ Spring killing frost, extreme heat, 

high winds, hail, insect damage, drought.

23 18 

ND ....................................... ................................................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2344 ........ Spring killing frost, extreme heat, 

high winds, hail, insect damage, drought.

.......... 4 

NE ........................................ ................................................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2344 ........ Spring killing frost, extreme heat, 

high winds, hail, insect damage, drought.

.......... 2 

WY ....................................... ................................................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2344 ........ Spring killing frost, extreme heat, 

high winds, hail, insect damage, drought.

.......... 2 

SD ........................................ Brule, Buffalo, Campbell, Corson, Custer, 

Dewey, Edmunds, Fall River, Faulk, Hughes, Hyde, Jackson, Jerauld, Jones, Lyman, Meade, Pennington, Perkins, Potter, Stanley, Sully, Walworth, Ziebach.

1–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2344, 

Amendment 1.

ADDS: prairie fires caused by dry 

lightning to disasters for 23 counties.

23 18 

ND ....................................... ................................................................... 1–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2344, 

Amendment 1.

ADDS: prairie fires caused by dry 

lightning to disasters for 23 counties.

.......... 4 

NE ........................................ ................................................................... 1–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2344, 

Amendment 1.

ADDS: prairie fires caused by dry 

lightning to disasters for 23 counties.

.......... 2 

WY ....................................... ................................................................... 1–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2344, 

Amendment 1.

ADDS: prairie fires caused by dry 

lightning to disasters for 23 counties.

.......... 2 

SD ........................................ Turner ........................................................ 6–16–06 ...... 6–16–06 ...... 7–27–06 ...... 3–27–07 ...... S2345 ........ High winds, heavy rain, hail .......... 1 6 
467 

TN ........................................ Rutherford ................................................. 5–11–06 ...... 5–25–06 ...... 7–27–06 ...... 3–27–07 ...... S2346 ........ Hail, excessive rain ......................... 1 7 TX ........................................ Live Oak, McMullen ................................... 1–01–06 ...... continuing .... 7–27–06 ...... 3–27–07 ...... S2347 ........ Drought ............................................ 2 9 TX ........................................ Calhoun ..................................................... 6–20–06 ...... 6–20–06 ...... 7–31–06 ...... 4–02–07 ...... S2348 ........ Excessive rain, flash flooding, 

flooding.

1 5 

TX ........................................ Hartley, La Salle, Presidio ........................ 1–01–06 ...... continuing .... 8–02–06 ...... 4–02–07 ...... S2349 ........ Drought ............................................ 3 14 NM ....................................... ................................................................... 1–01–06 ...... continuing .... 8–02–06 ...... 4–02–07 ...... S2349 ........ Drought ............................................ .......... 2 TX ........................................ Robertson .................................................. 4–18–06 ...... 4–20–06 ...... 8–07–06 ...... 4–09–07 ...... S2350 ........ Hail, high winds .............................. 1 7 CO ....................................... Eagle, Fremont, Garfield, Larimer, Logan, 

Otero, Pitkin, Rio Blanco, Yuma.

1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2351 ........ Drought, heat, high winds .............. 8 21 

KS ........................................ ................................................................... 1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2351 ........ Drought, heat, high winds .............. .......... 1 NE ........................................ ................................................................... 1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2351 ........ Drought, heat, high winds .............. .......... 4 UT ........................................ ................................................................... 1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2351 ........ Drought, heat, high winds .............. .......... 2 WY ....................................... ................................................................... 1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2351 ........ Drought, heat, high winds .............. .......... 2 CO ....................................... Fremont ..................................................... 7–05–06 ...... 7–05–06 ...... 8–08–06 ...... 4–09–07 ...... S2352 ........ Flooding ........................................... 1 7 CO ....................................... Yuma ......................................................... 4–28–06 ...... 6–10–06 ...... 8–08–06 ...... 4–09–07 ...... S2353 ........ Hail .................................................. 1 4 KS ........................................ ................................................................... 4–28–06 ...... 6–10–06 ...... 8–08–06 ...... 4–09–07 ...... S2353 ........ Hail .................................................. .......... 1 NE ........................................ ................................................................... 4–28–06 ...... 6–10–06 ...... 8–08–06 ...... 4–09–07 ...... S2353 ........ Hail .................................................. .......... 2 TX ........................................ Llano ......................................................... 1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2354 ........ Drought, excessive heat .................. 1 5 TX ........................................ Lubbock ..................................................... 1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2355 ........ Drought, high winds, extreme temperatures. 1 8 TX ........................................ Victoria ...................................................... 1–01–06 ...... 6–01–06 ...... 8–08–06 ...... 4–09–07 ...... S2356 ........ Drought ............................................ 1 6 SD ........................................ Aurora, Beadle, Bennett, Butte, Clark, 

Codington, Douglas, Haakon, Hand, Harding, Hutchinson, Mellette, McPherson, Sanborn, Shannon, Spink, Todd, Tripp.

1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2357 ........ Late spring killing frost, extreme 

heat, high winds, hail, insect damage, insufficient subsoil moisture, prairie fires caused by dry lightning, ongoing drought.

18 35 

MT ....................................... ................................................................... 1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2357 ........ Late spring killing frost, extreme 

heat, high winds, hail, insect damage, insufficient subsoil moisture, prairie fires caused by dry lightning, ongoing drought.

.......... 2 

NE ........................................ ................................................................... 1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2357 ........ Late spring killing frost, extreme 

heat, high winds, hail, insect damage, insufficient subsoil moisture, prairie fires caused by dry lightning, ongoing drought.

.......... 4 
468 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

ND ....................................... ................................................................... 1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2357 ........ Late spring killing frost, extreme 

heat, high winds, hail, insect damage, insufficient subsoil moisture, prairie fires caused by dry lightning, ongoing drought.

.......... 4 

WY ....................................... ................................................................... 1–01–06 ...... continuing .... 8–08–06 ...... 4–09–07 ...... S2357 ........ Late spring killing frost, extreme 

heat, high winds, hail, insect damage, insufficient subsoil moisture, prairie fires caused by dry lightning, ongoing drought.

.......... 1 

CT ........................................ Entire State ............................................... 4–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2358 ........ Cool spring, excessively wet weather pattern. 8 ..........MA ....................................... ................................................................... 4–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2358 ........ Cool spring, excessively wet weather pattern. .......... 3 NY ........................................ ................................................................... 4–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2358 ........ Cool spring, excessively wet weather pattern. .......... 3 RI ......................................... ................................................................... 4–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2358 ........ Cool spring, excessively wet weather pattern. .......... 3 NJ ........................................ Atlantic, Bergen, Burlington, Camden, 

Cape May, Cumberland, Gloucester, Hunterdon, Mercer, Middlesex, Monmouth, Morris, Ocean, Salem, Somerset, Sussex, Warren.

6–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2359 ........ Excessive precipitation, high winds, 

hail, high humidity.

17 4 

DE ........................................ ................................................................... 6–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2359 ........ Excessive precipitation, high winds, 

hail, high humidity.

.......... 1 

NY ........................................ ................................................................... 6–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2359 ........ Excessive precipitation, high winds, 

hail, high humidity.

.......... 3 

PA ........................................ ................................................................... 6–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2359 ........ Excessive precipitation, high winds, 

hail, high humidity.

.......... 6 

RI ......................................... Entire State ............................................... 4–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2360 ........ unusually cool spring, excessively 

wet weather pattern (excessive rainfall).

5 ..........
469 

CT ........................................ ................................................................... 4–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2360 ........ unusually cool spring, excessively 

wet weather pattern (excessive rainfall).

.......... 2 

MA ....................................... ................................................................... 4–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2360 ........ unusually cool spring, excessively 

wet weather pattern (excessive rainfall).

.......... 3 

TX ........................................ Dallam, Hardeman, Jim Wells, Kinney, 

San Patricio, Wilson, Zavala.

1–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2361 ........ Drought ............................................ 7 28 

NM ....................................... ................................................................... 1–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2361 ........ Drought ............................................ .......... 1 OK ........................................ ................................................................... 1–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2361 ........ Drought ............................................ .......... 3 TX ........................................ Foard, Stephens, Wilbarger ....................... 1–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2362 ........ Drought, high winds ....................... 3 12 OK ........................................ ................................................................... 1–01–06 ...... continuing .... 8–15–06 ...... 4–16–07 ...... S2362 ........ Drought, high winds ....................... .......... 2 CA ........................................ Tulare ........................................................ 5–01–06 ...... 5–15–06 ...... 8–21–06 ...... 4–23–07 ...... S2363 ........ Unseasonable heat spell ................. 1 4 GA ........................................ All counties except Fannin, Gilmer, 

Towns, Union.

3–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2364 ........ Drought, excessive heat .................. 155 4 

AL ........................................ ................................................................... 3–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2364 ........ Drought, excessive heat .................. .......... 11 FL ........................................ ................................................................... 3–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2364 ........ Drought, excessive heat .................. .......... 9 NC ....................................... ................................................................... 3–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2364 ........ Drought, excessive heat .................. .......... 3 SC ........................................ ................................................................... 3–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2364 ........ Drought, excessive heat .................. .......... 10 TN ........................................ ................................................................... 3–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2364 ........ Drought, excessive heat .................. .......... 4 NH ....................................... Entire State ............................................... 5–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2365 ........ Flooding, excessive rain .................. 10 ..........ME ....................................... Entire State ............................................... 5–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2365 ........ Flooding, excessive rain .................. .......... 2 MA ....................................... Entire State ............................................... 5–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2365 ........ Flooding, excessive rain .................. .......... 4 VT ........................................ Entire State ............................................... 5–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2365 ........ Flooding, excessive rain .................. .......... 5 NY ........................................ Albany, Schoharie ..................................... 5–01–06 ...... 6–30–06 ...... 8–21–06 ...... 4–23–07 ...... S2366 ........ Excessive rain, cold temperatures .. 2 8 NY ........................................ Columbia, Greene ...................................... 4–01–06 ...... 5–31–06 ...... 8–21–06 ...... 4–23–07 ...... S2367 ........ Freeze, frost, hail, excessive rain ... 2 6 CT ........................................ ................................................................... 4–01–06 ...... 5–31–06 ...... 8–21–06 ...... 4–23–07 ...... S2367 ........ Freeze, frost, hail, excessive rain ... .......... 1 MA ....................................... ................................................................... 4–01–06 ...... 5–31–06 ...... 8–21–06 ...... 4–23–07 ...... S2367 ........ Freeze, frost, hail, excessive rain ... .......... 1 NY ........................................ Cortland, Jefferson, Washington ............... 4–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2368 ........ Tree tent caterpillar infestation due 

to unusually mild winter weather.

3 14 

VT ........................................ ................................................................... 4–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2368 ........ Tree tent caterpillar infestation due 

to unusually mild winter weather.

.......... 3 

NY ........................................ Dutchess, Ulster ........................................ 6–24–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2369 ........ Excessive rain, flooding, flash 

flooding, high winds.

2 6 

CT ........................................ ................................................................... 6–24–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2369 ........ Excessive rain, flooding, flash 

flooding, high winds.

.......... 2 

MA ....................................... ................................................................... 6–24–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2369 ........ Excessive rain, flooding, flash 

flooding, high winds.

.......... 1 

NY ........................................ Wayne ........................................................ 5–11–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2370 ........ Hail, high winds, excessive rain ..... 1 4 TX ........................................ Fannin, Hopkins, Hunt, Jeff Davis, Lavaca 1–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2371 ........ Drought ............................................ 5 24 
470 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

OK ........................................ ................................................................... 1–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2371 ........ Drought ............................................ .......... 1 TX ........................................ Knox ........................................................... 7–11–06 ...... 7–11–06 ...... 8–21–06 ...... 4–23–07 ...... S2372 ........ Hail .................................................. 1 6 TX ........................................ Red River .................................................. 1–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2373 ........ Drought, excessive heat .................. 1 7 OK ........................................ Red River .................................................. 1–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2373 ........ Drought, excessive heat .................. .......... 2 TX ........................................ Willacy ....................................................... 1–01–06 ...... continuing .... 8–21–06 ...... 4–23–07 ...... S2374 ........ Drought, high temperatures, high 

winds.

1 3 

WI ........................................ Adams, Ashland, Barron, Bayfield, Burnett, Douglas, Dunn, Iron, Langlade, 

Lincoln, Marquette, Polk, Price, Rusk, St. Croix, Sawyer, Taylor, Washburn, Waushara.

4–01–06 ...... continuing .... 8–25–06 ...... 4–25–07 ...... S2375 ........ Drought ............................................ 19 20 

MI ........................................ ................................................................... 4–01–06 ...... continuing .... 8–25–06 ...... 4–25–07 ...... S2375 ........ Drought ............................................ .......... 1 MN ....................................... ................................................................... 4–01–06 ...... continuing .... 8–25–06 ...... 4–25–07 ...... S2375 ........ Drought ............................................ .......... 5 VA ........................................ Pittsylvania, Rappahannock ..................... 3–01–06 ...... continuing .... 8–28–06 ...... 4–30–07 ...... S2376 ........ Drought, high temperatures ............ 2 11 NC ....................................... ................................................................... 3–01–06 ...... continuing .... 8–28–06 ...... 4–30–07 ...... S2376 ........ Drought, high temperatures ............ .......... 2 TX ........................................ Glasscock .................................................. 1–01–06 ...... continuing .... 8–28–06 ...... 4–30–07 ...... S2377 ........ Drought, heat, high winds, low humidity. 1 6 MN ....................................... Aitkin, Anoka, Beltrami, Benton, Carlton, 

Cass, Chisago, Clearwater, Cook, Crow Wing, Hennepin, Hubbard, Isanti, Itasca, Kanabec, Kittson, Koochiching, Lake, Lake of the Woods, Mahnomen, Marshall, Mille Lacs, Morrison, Norman, Pennington, Pine, Polk, Pope, Red Lake, Roseau, St. Louis, Sherburne, Stearns, Todd, Wadena, Wright.

5–10–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2378 ........ Drought ............................................ 36 15 

ND ....................................... ................................................................... 5–10–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2378 ........ Drought ............................................ .......... 5 WI ........................................ ................................................................... 5–10–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2378 ........ Drought ............................................ .......... 3 TX ........................................ Karnes ....................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2379 ........ Drought ............................................ 1 7 
471 

WA ....................................... Adams, Benton, Chelan, Douglas, Grant, 

Lincoln, Okanogan, Spokane, Franklin, Walla Walla, Whitman, Yakima.

5–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2380 ........ Adverse weather conditions: Excessive rain, excessive heat, hail, 

high winds, severe thunderstorms, lightning, flash flooding, freezing weather.

12 15 

ID ......................................... ................................................................... 5–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2380 ........ Adverse weather conditions: Excessive rain, excessive heat, hail, 

high winds, severe thunderstorms, lightning, flash flooding, freezing weather.

.......... 5 

OR ....................................... ................................................................... 5–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2380 ........ Adverse weather conditions: Excessive rain, excessive heat, hail, 

high winds, severe thunderstorms, lightning, flash flooding, freezing weather.

.......... 2 

AL ........................................ Autauga, Blount, Calhoun, Chilton, 

Cleburne, Dallas, De Kalb, Fayette, Jefferson, Lamar, Limestone, Lowndes, Marion, Marshall, Pickens, Shelby, Talladega, Walker, Winston.

1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2381 ........ Drought, high temperatures ............ 19 24 

GA ........................................ ................................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2381 ........ Drought, high temperatures ............ .......... 6 MS ....................................... ................................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2381 ........ Drought, high temperatures ............ .......... 4 TN ........................................ ................................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2381 ........ Drought, high temperatures ............ .......... 2 CO ....................................... Jackson, Lincoln, Mesa, Moffat ................ 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2382 ........ Drought ............................................ 4 18 MS ....................................... ................................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2382 ........ Drought ............................................ .......... 4 TN ........................................ ................................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2382 ........ Drought ............................................ .......... 3 IA ......................................... Cerro Gordo, Cherokee, Clay, Crawford, 

Des Moines, Dickinson, Harrison, Humboldt, Ida, Lee, Lucas, Madison, Monona, Monroe, Montgomery, Plymouth, Sac, Sioux, Woodbury, Worth.

1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2383 ........ Drought, severe weather ................. 20 44 

IL ......................................... ................................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2383 ........ Drought, severe weather ................. .......... 3 MN ....................................... ................................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2383 ........ Drought, severe weather ................. .......... 3 MO ....................................... ................................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2383 ........ Drought, severe weather ................. .......... 1 NE ........................................ ................................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2383 ........ Drought, severe weather ................. .......... 4 SD ........................................ ................................................................... 1–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2383 ........ Drought, severe weather ................. .......... 2 MA ....................................... Barnstable, Berkshire, Bristol, Essex, 

Franklin, Hampden, Hampshire, Middlesex, Norfolk, Plymouth, Worcester.

5–01–06 ...... 6–30–06 ...... 8–31–06 ...... 5–01–07 ...... S2384 ........ Cool temperatures, excessive rain, 

floods.

11 2 
472 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

CT ........................................ ................................................................... 5–01–06 ...... 6–30–06 ...... 8–31–06 ...... 5–01–07 ...... S2384 ........ Cool temperatures, excessive rain, 

floods.

.......... 4 

NH ....................................... ................................................................... 5–01–06 ...... 6–30–06 ...... 8–31–06 ...... 5–01–07 ...... S2384 ........ Cool temperatures, excessive rain, 

floods.

.......... 3 

NY ........................................ ................................................................... 5–01–06 ...... 6–30–06 ...... 8–31–06 ...... 5–01–07 ...... S2384 ........ Cool temperatures, excessive rain, 

floods.

.......... 3 

RI ......................................... ................................................................... 5–01–06 ...... 6–30–06 ...... 8–31–06 ...... 5–01–07 ...... S2384 ........ Cool temperatures, excessive rain, 

floods.

.......... 3 

VT ........................................ ................................................................... 5–01–06 ...... 6–30–06 ...... 8–31–06 ...... 5–01–07 ...... S2384 ........ Cool temperatures, excessive rain, 

floods.

.......... 2 

TN ........................................ Fentress, Franklin, McMinn, Meigs, Morgan, Scott. 5–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2385 ........ Drought, extreme heat .................... 6 18 TN ........................................ ................................................................... 5–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2385 ........ Drought, extreme heat .................... .......... 2 TN ........................................ ................................................................... 5–01–06 ...... continuing .... 8–31–06 ...... 5–01–07 ...... S2385 ........ Drought, extreme heat .................... .......... 2 CA ........................................ Butte, Calaveras, Fresno, Glenn, Imperial, 

Kern, Kings, Madera, Merced, San Bernardino, Solano, Sonoma, Stanislaus, Sutter, Tehama, Tulare.

7–15–06 ...... 7–31–06 ...... 9–07–06 ...... 5–07–07 ...... S2386 ........ Record setting HEAT WAVE ............. 16 31 

AZ ........................................ ................................................................... # N/A ............ # N/A ............ # N/A ............ # N/A ............ S2386 ........ Record setting HEAT WAVE ............. .......... 3 NV ........................................ ................................................................... # N/A ............ # N/A ............ # N/A ............ # N/A ............ S2386 ........ # N/A ............................................... .......... 1 NY ........................................ Cayuga, Chenango, Clinton, Columbia, 

Cortland, Essex, Franklin, Fulton, Greene, Herkimer, Jefferson, Lewis, Montgomery, Orange, Otsego, Rensselaer, St. Lawrence, Saratoga, Suffolk, Sullivan, Washington.

4–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2387 ........ Excessive rain, flooding, flash 

flooding.

21 20 

CT ........................................ ................................................................... # N/A ............ # N/A ............ # N/A ............ # N/A ............ S2387 ........ # N/A ............................................... .......... 1 MA ....................................... ................................................................... # N/A ............ # N/A ............ # N/A ............ # N/A ............ S2387 ........ # N/A ............................................... .......... 1 NJ ........................................ ................................................................... # N/A ............ # N/A ............ # N/A ............ # N/A ............ S2387 ........ # N/A ............................................... .......... 2 PA ........................................ ................................................................... # N/A ............ # N/A ............ # N/A ............ # N/A ............ S2387 ........ # N/A ............................................... .......... 2 VT ........................................ ................................................................... 4–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2387 ........ Excessive rain, flooding, flash 

flooding.

.......... 5 

ND ....................................... Entire State ............................................... 1–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2388 ........ Drought, drought-related disasters 53 ..........MN ....................................... ................................................................... 1–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2388 ........ Drought, drought-related disasters .......... 7 
473 

MT ....................................... ................................................................... 1–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2388 ........ Drought, drought-related disasters .......... 5 SD ........................................ ................................................................... 1–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2388 ........ Drought, drought-related disasters .......... 8 TX ........................................ Camp, Franklin, Grayson, Morris, Rains, 

Titus, Wood.

4–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2389 ........ Drought ............................................ 7 15 

OK ........................................ ................................................................... 4–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2389 ........ Drought ............................................ .......... 3 MS ....................................... Entire State ............................................... 3–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2390 ........ Drought ............................................ 82 ..........AL ........................................ ................................................................... 3–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2390 ........ Drought ............................................ .......... 10 AR ........................................ ................................................................... 3–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2390 ........ Drought ............................................ .......... 5 LA ........................................ ................................................................... 3–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2390 ........ Drought ............................................ .......... 10 TN ........................................ ................................................................... 3–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2390 ........ Drought ............................................ .......... 5 MT ....................................... Stillwater ................................................... 1–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2391 ........ Drought ............................................ 1 5 SD ........................................ Brown, Brookings, Charles Mix, Davison, 

Grant, Gregory, Hamlin, Hanson, Kingsbury, Miner.

1–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2392 ........ Drought ............................................ 10 22 

MN ....................................... ................................................................... 1–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2392 ........ Drought ............................................ .......... 4 NE ........................................ ................................................................... 1–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2392 ........ Drought ............................................ .......... 3 ND ....................................... ................................................................... 1–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2392 ........ Drought ............................................ .......... 2 VA ........................................ Campbell ................................................... 6–01–06 ...... continuing .... 9–12–06 ...... 5–14–07 ...... S2393 ........ Drought, high temperatures ............ 1 7 TX ........................................ Collin ......................................................... 4–01–06 ...... continuing .... 9–25–06 ...... 5–25–07 ...... S2394 ........ Drought, excessive temperatures .... 1 6 NE ........................................ Adams, Antelope, Boone, Burt, Butler, 

Cedar, Clay, Colfax, Dakota, Dixon, Dodge, Fillmore, Greeley, Hall, Hamilton, Jefferson, Johnson, Knox, Lancaster, Madison, Merrick, Nemaha, Nuckolls, Pawnee, Pierce, Richardson, Saline, Saunders, Seward, Stanton, Thayer, Thurston, Wayne, York.

1–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2395 ........ Drought, high winds, extreme heat, 

hail, tornadoes.

34 20 

IA ......................................... ................................................................... 1–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2395 ........ Drought, high winds, extreme heat, 

hail, tornadoes.

.......... 3 

KS ........................................ ................................................................... 1–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2395 ........ Drought, high winds, extreme heat, 

hail, tornadoes.

.......... 7 

MO ....................................... ................................................................... 1–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2395 ........ Drought, high winds, extreme heat, 

hail, tornadoes.

.......... 2 

SD ........................................ ................................................................... 1–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2395 ........ Drought, high winds, extreme heat, 

hail, tornadoes.

.......... 5 

NE ........................................ Sheridan .................................................... 6–20–06 ...... 6–20–06 ...... 9–27–06 ...... 5–28–07 ...... S2396 ........ Storm with high winds, hail, excessive rain, lightning, tornado. 1 6 SD ........................................ ................................................................... 6–20–06 ...... 6–20–06 ...... 9–27–06 ...... 5–28–07 ...... S2396 ........ Storm with high winds, hail, excessive rain, lightning, tornado. .......... 2 
474 

DISASTER ASSISTANCE BRANCH/EMERGENCIES SECTION (DAB/ES) DISASTER DECLARATIONS: FINAL TOTALS SECRETARIAL—Continued 

[Fiscal year 2006] 

State Counties requested Beginning Date of disaster Ending Date of disaster Approved by Secretary Termination Date Designation Number Description of disaster Primary Contig- uous 

TX ........................................ Bee, Blanco, Clay, Delta, DeWitt, Hood, 

Jack, Navarro, Palo Pinto, Somervell, Tom Green.

1–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2397 ........ Drought ............................................ 11 46 

OK ........................................ ................................................................... 1–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2397 ........ Drought ............................................ .......... 2 TX ........................................ Bowie ......................................................... 4–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2398 ........ Drought ............................................ 1 3 AR ........................................ ................................................................... 4–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2398 ........ Drought ............................................ .......... 2 OK ........................................ ................................................................... 4–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2398 ........ Drought ............................................ .......... 1 TX ........................................ Brooks, Jim Hogg ...................................... 1–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2399 ........ Drought, excessive temperatures, 

high winds.

2 8 

TX ........................................ Gregg, Upshur ........................................... 4–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2400 ........ Drought, excessive heat .................. 2 7 TX ........................................ Haskell, Jones, Knox .................................. 1–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2401 ........ Drought, high winds, excessive 

heat.

3 10 

TX ........................................ Lynn ........................................................... 1–01–06 ...... continuing .... 9–27–06 ...... 5–28–07 ...... S2402 ........ Drought, high winds ....................... 1 7 

TOTAL ACTIVE ........ ................................................................... ...................... ...................... ...................... ...................... ................... .......................................................... 2,301 3,861 
475 

AGRICULTURAL CREDIT INSURANCE FUND

Question. For each of the years 2003, 2004, 2005 and 2006, please document in 

detail for the record exactly how the funds provided through the Agricultural Credit 

Insurance Fund account were actually obligated and used by the Agency. 

Answer. The information on obligation of ACIF funds by loan category for fiscal 

year 2003 through fiscal year 2006 will be provided for the record. 

[The information follows:] 

AGRICULTURAL CREDIT INSURANCE FUND OBLIGATIONS BY FISCAL YEAR 

[In thousands of dollars] 

Fiscal year 2003 Fiscal year 2004 Fiscal year 2005 Fiscal year 2006 

Direct Loans: 

Ownership ............................................................ 168,575 142,404 271,929 274,604 

Operating ............................................................. 689,849 609,565 556,008 640,742 

Emergency ............................................................ 95,698 29,789 23,570 51,525 

Indian Land Acquisition ...................................... 110 1,586 ........................ 360 

Boll Weevil ........................................................... 99,000 97,695 83,070 22,000 

Guaranteed Loans: 

Ownership ............................................................ 1,231,167 1,099,052 1,027,016 949,122 

Operating Unsubsidized ....................................... 1,012,926 951,314 884,523 937,655 

Operating Subsidized ........................................... 418,379 271,217 283,423 271,589 

Question. Also please provide a detailed accounting of any S&E funds, such as the 

IT budget or others, that were obligated and used in support of Farm Loans. In each 

year, what was the percentage of the total FSA S&E appropriation actually obligated and used to support Farm Loans in the Field, in the State Offices, at the IT 

or Finance Office level, and at the National Office level? 

Answer. As generally required by the Federal Credit Reform Act (FCRA) and by 

OMB Circular A–11, administrative expenses in support of the ACIF loan programs 

are appropriated to the ACIF program account. These funds are then transferred 

to Farm Service Agency (FSA) Salaries and Expenses (S&E) account. Per the A–11, 

‘‘administrative expenses means all costs that are directly related to credit program 

operations, including payments to contractors. The FCRA generally requires that 

administrative expenses for both pre-1992 and post-1991 direct loans and loan guarantees be included in program accounts.’’ 

Therefore, there is relative transparency in the amount of funding in the FSA 

S&E account that is used in support of ACIF, since these funds are originally budgeted in and appropriated to ACIF. The table below provides the amounts of ACIF 

administrative funds that are transferred to the FSA S&E account, and the relative 

percentage of ACIF administrative expenses to total S&E funding. 

[The information follows:] 

AGRICULTURAL CREDIT INSURANCE FUND OBLIGATIONS AS A PERCENT OF FSA S&E 

OBLIGATIONS 

Fiscal year 2003 Fiscal year 2004 Fiscal year 2005 Fiscal year 2006 

ACIF Administrative Expenses ...................................... $277,361 $281,350 $291,414 $301,545 

Total Salaries and Expenses ........................................ $1,249,900 $1,267,428 $1,318,733 $1,309,028 

ACIF Admin as percent of Total S&E ........................... 22.19 22.20 22.10 23.04 

FARM LOAN PROGRAM STAFFING

Question. FSA has a formal training and testing procedure in place for Farm Loan 

Officers and Farm Loan Officer Trainees. It is module type training—complete a 

module and take a test. This training takes about a year to complete and covers 

loan making and loan servicing. Then before an FLO is granted loan approval authority they must submit 5 loan dockets they have prepared and the loans pass a 

review. In addition to the formal training, senior management officials state that 

it requires at least another year or two of on the job training for a FLO to attain 

the experience needed to fully and independently perform the loan officer duties. 

For a FLO to attain the knowledge skills and ability to become a Farm Loan Manager, Farm Loan Specialist or advance to a Farm Loan Chief position will require 

additional years of experience. 
476 

According to a Strategic Human Capital Management study, many Farm Loan 

employees will be retiring very soon. The Farm Loan employees are in the GS–1165 

series. On average, 1,165 employees are retiring within 3 months of their retirement 

eligibility date. 50 percent of supervisory 1,165 employees are eligible to retire between now and 2008. Twenty-eight percent of all FSA 1,165 employees are eligible 

to retire between now and 2008. 

What is FSA’s plan to replace these experienced Farm Loan employees, and how 

much will Congress need to invest to make sure there is no crisis in the ability of 

FSA to deliver the Farm Loan programs? 

Answer. FSA Farm Loan Officers functions are critical to the effective delivery 

and service of Agency Farm Loan Programs (FLP). Because the GS–1165 series 

within FLP requires specialized training, it is essential that resources to support the 

Farm Loan Officer Training program be allocated prior to announced retirements. 

FSA plans to fund additional loan officer trainee positions from within existing 

resources. In fiscal year 2006, FSA funded 30 loan officer trainee positions and 

plans on an additional 15 positions available for fiscal year 2007. The fiscal year 

2008 budget assumes 45 trainee positions. Analysis of available Human Resources 

data indicates that from fiscal year 2006 through fiscal year 2009, 26 percent of currently employed loan officers will be eligible to retire. 

QUESTIONS SUBMITTED BY SENATOR SAM BROWNBACK

NATIONAL VETERINARY MEDICAL SERVICES ACT

Question. In the 2006 Agriculture Appropriations hearings, you stated that the 

implementation of the full National Veterinary Medical Service Act would take 18 

months. One year later, we are informed that you have not yet submitted for public 

comments a proposed rule and we are concerned that the National Veterinary Medical Service Act may not be implemented within the timeframe you initially provided. 

What steps do you have planned that will assure implementation of the NVMSA 

by October 2007 (18 months from the testimony in which you estimated 18 months 

would be necessary to complete the rules)? 

Answer. Although there are additional administrative steps that must be completed prior to the distribution of funds, a framework for the program has been proposed by CSREES. This proposal has recently been reviewed by the appropriate 

legal and regulatory entities. On March 12, 2007, the Final Rule was approved. The 

Final Rule was published in the Federal Register on March 19, 2007, and permits 

CSREES to implement a NVMSA program. The Department recognizes the importance of this Act to both the veterinary community as well as the supporters of the 

Act. You can be assured that we have communicated with agency personnel responsible for moving this program forward to ensure that it is implemented appropriately and as quickly as possible. 

Question. Section 2 of NVMSA, Public Law 108–161, reads ‘‘The National Agricultural Research, Extension, and Teaching Policy Act of 1977 (7 U.S.C. 3101 et seq.) 

is amended by inserting after section 1415 the following new section:’’ Given that 

3101 of the 7 U.S.C. is entitled ‘‘Purposes of agricultural research, extension, and 

education’’ and that the money appropriated for NVMSA has been allocated to 

CSREES’s Research and Education Activities, why has the USDA not formally designated CSREES as the administering agency for NVMSA? 

Answer. A Final Rule will be published in the Federal Register on March 19, 2007 

delegating NVMSA to CSREES. 

Question. A study of Food Supply Veterinary Medicine released in June 2006 

quantified existing and projected shortages of veterinary practitioners in various 

practice areas. How has this study helped the NVMSA implementation process? 

Answer. CSREES has utilized the 2006 Kansas State University study on Food 

Supply Veterinary Medicine to identify an area of critical need in veterinary medicine. Results of this study indicate that among the highest forecasted future shortages in veterinary practice between 2004 and 2016 will be the Federal-animal 

health career and Federal-food safety and security sectors. The finding of the study 

correlates with the large number of difficult-to-fill vacancies for veterinarians in 

FSIS. 

Question. I do not consider the short-term pilot FSIS program, currently being developed by CSREES, to be an acceptable substitute for progress on the intended 

NVMSA program, especially the parts of NVMSA that would address rural practice 

and emergency response shortages. Furthermore, I do not approve of CSREES’s intention to reprogram the NVMSA funds into a different loan repayment program 
477 

within FSIS. Is your work on the FSIS pilot program diverting resources that could 

otherwise be used to implement the rural and emergency response portions of 

NVMSA? 

Answer. CSREES has entered into a reimbursable agreement to implement the 

loan repayment provisions of the Act. The FSIS-oriented implementation strategy 

represents an approach that enables the initiation of the use of NVMSA funds as 

loan repayments to eligible veterinarians in the shortest possible time frame. Funding is not sufficient to implement the emergency portion of the Act. 

Question. Your colleague, former HHS Secretary Tommy Thompson, was quoted 

to have said, ‘‘I, for the life of me, cannot understand why terrorists have not attacked our food supply because it is so easy to do.’’ Given that the risks of bioterrorism are high, that the Federal Government has been criticized for its preparedness for and response to recent disasters, and that you have in the form of NVMSA 

a program within the USDA that would create a ‘‘Veterinary National Guard’’ available for immediate mobilization in the event of a zoonotic or major food animal disease outbreak and improve disease surveillance in the form of escalated geographic 

veterinary coverage, why are you not expediting the implementation of NVMSA? 

Answer. Implementation of the loan repayment sections of NVMSA are being expedited through the use of a reimbursable agreement with FSIS, which was developed in order to take advantage of current student loan regulations. Funding is not 

sufficient to implement the emergency portion of the Act. Moreover, eligibility for 

service to the Federal Government in emergency situations is dependent on first establishing eligibility for the loan repayment program. The current strategy, therefore, helps to establish a population of veterinarians eligible to serve as emergency 

responders. 

(479) 

DEPARTMENT OF HEALTH AND HUMAN SERVICES 

FOOD AND DRUG ADMINISTRATION

STATEMENT OF HON. ANDREW VON ESCHENBACH, COMMISSIONER, 

FOOD AND DRUG ADMINISTRATION 

ACCOMPANIED BY: 

JOHN DYER, DEPUTY COMMISSIONER FOR OPERATIONS, FOOD 

AND DRUG ADMINISTRATION 

RICHARD TURMAN, DEPUTY ASSISTANT SECRETARY FOR BUDGET, 

DEPARTMENT OF HEALTH AND HUMAN SERVICES 

Senator KOHL. Our next panel will include the FDA Commissioner, Dr. Andrew von Eschenbach; Mr. John Dyer, who is the 

FDA Chief Operating Officer; and also Mr. Richard Turman of the 

Department of Health and Human Services Budget Office. 

Dr. von Eschenbach, whenever you are ready, we’ll take your testimony. 

STATEMENT OF DR. ANDREW VON ESCHENBACH

Dr. von ESCHENBACH. Good morning, Mr. Chairman. I am very 

honored to present to you and the members of the subcommittee 

the President’s fiscal year 2008 budget request for the Food and 

Drug Administration. I am joined this morning by Mr. John Dyer, 

the FDA’s Deputy Commissioner for Operations, and Mr. Richard 

Turman, the Deputy Assistant Secretary for Budget at the Department of Health and Human Services. 

Mr. Chairman, at the outset may I emphasize our extraordinary 

gratitude for your support and the support of the committee that 

was provided by Congress in fiscal year 2007. Soon after the President proposed our budget on February 5, Congress enacted a revised continuing resolution for fiscal year 2007, and we are in the 

midst of developing the operating plan for fiscal year 2007 that we 

will be forwarding to you within the very near future, in the 30- 

day time commitment. 

But, taken together, the fiscal year 2007 and the fiscal year 2008 

budgets are components of an ongoing investment strategy needed 

to create a modern Food and Drug Administration capable of addressing the challenges and the opportunities of the 21st century. 

We recognize how precious these assets are to the administration 

and the Congress, and we will be good stewards of the funds you 

provide. 

For fiscal year 2008, the President’s budget represents a 5.3 percent increase above the fiscal year 2007 President’s budget, and the 

requested $2.08 billion consists of $1.64 billion in budget authority, 

$428 million in current law user fees, and $42.7 million for three 

new user fees. The additional dollars that are requested in fiscal 

year 2008 are principally directed to support the work force of the 

FDA and to enhance our programs of food safety, enhanced drug 
480 

and medical product safety, and to accelerate the approval of generic drugs. 

At its core, FDA is a scientific data analysis, information management, and decision-making organization, and as such we are 

critically dependent upon the expertise of a strong, diverse work 

force that is using modern information technologies and state-ofthe-art scientific equipment. Eighty percent of the FDA budget 

funds payroll and related personnel costs, and these costs have 

been increasing yearly. For fiscal year 2008 we request $64.7 million to cover nondiscretionary increased costs for pay raises, rent, 

utilities, and security, and our relocating to our White Oak, Maryland campus. 

Food safety is an important cornerstone of the FDA mission. 

During recent years there have been changes in our food supply 

that create new challenges to the FDA to enhance food safety. 

Consumption of fresh produce, particularly ready-to-eat products 

that include raw and fresh foods, has increased dramatically. Products are harvested from the vine, stem, and from the soil, and then 

are delivered rapidly to our tables, with an increasing proportion 

coming from outside our domestic borders. 

We propose a $10.7 million increase for a food safety initiative 

that’s focused on fresh produce. FDA is taking a multitiered risk 

management approach to the product life cycle of food that will 

build enhanced quality into the food chain from farm to fork. This 

will include development and dissemination of new and refined 

Good Agricultural Practices for prevention, the deployment of scientific tools for the detection of intentional and unintentional contamination, and accelerated processes to detect, trace, and more 

rapidly contain outbreaks. 

A few examples of how we would use FDA resources include conducting research to develop new methods to detect foodborne pathogens; conducting advanced training for our partners in State and 

local agencies that we will work with to prevent outbreaks; and 

employing new microbiological techniques to identify ways to improve the safety of produce. We will also enhance our traceback 

teams and mechanisms, and deploy IT decision systems to detect 

high risk food imports. 

In addition to food, we will focus on drug and device safety. Last 

month FDA released its commitment to drug safety which outlined 

41 initiatives that will cover the life cycle of a drug from its development to its delivery. The $11.2 million increase for modernizing 

drug safety supports FDA’s response to the report by the Institute 

of Medicine on drug safety. 

With these resources, FDA will strengthen the science and tools 

we use to ensure drug safety. We will improve communication and 

information flow among all stakeholders involved in the safe use of 

drugs. And we will restructure our operations and management 

systems to ensure optimum review, analysis, consultation, and 

communication to achieve a stronger drug safety system. 

With regard to medical devices, we will build on the programs already in place by directing an additional $7.2 million to enhance 

active surveillance of devices in the post-market area that employs 

modern information technology for data mining and analysis. 
481 

In addition to safer and more effective medical products, the public also needs more cost-effective choices, and to that end the President’s budget for fiscal year 2008 requests $5.6 million in budget 

authority and $15.7 million in user fees that are dedicated to enhancing the approval of generic drugs. We expect to be able to, 

with the $5.6 million increase in BA, to approve an additional 50 

applications during fiscal year 2008. 

The proposed user fee program ensures that FDA can measurably improve generic drug review performance over the next 4 to 

8 years, and this investment will return many billions in savings 

to consumers and government-sponsored health plans. 

PREPARED STATEMENT

We recognize that all these dollars we are requesting are in fact 

precious assets of the American taxpayer, and yet the programs 

they will make possible are essential to protecting and promoting 

the health of all Americans. There are critical challenges to be addressed, but there are enormous opportunities, such as accelerating 

the development and delivery of lifesaving interventions. Meeting 

these challenges and seizing these opportunities are only made possible by your support, for which we are very incredibly grateful. 

Thank you, Mr. Chairman. 

Senator KOHL. Thank you very much, Dr. von Eschenbach. 

[The statement follows:] 

PREPARED STATEMENT OF ANDREW C. VON ESCHENBACH, M.D. 

Introduction 

Chairman Kohl and members of the Subcommittee, this year as a confirmed Commissioner I am honored to present for your consideration and approval the President’s fiscal year 2008 budget request for FDA. I am joined by Mr. John Dyer, my 

recently appointed Deputy Commissioner and Chief Operating Officer and Mr. Richard Turman, Deputy Assistant Secretary for Budget at the Department of Health 

and Human Services. I also have members of FDA’s senior leadership with me, who 

at your discretion can respond to any specific questions you may have. 

We live in an era of rapid science, technology, and individualized medicine that 

is changing the products FDA regulates and the environment for FDA regulation. 

Congress and the Administration recognize the challenges we face and have responded with the resources in fiscal year 2007 that will allow FDA to begin addressing these challenges. 

As you consider our fiscal year 2008 request, please do so mindful of the extraordinary gratitude of the FDA for your support in fiscal year 2007. The budgets for 

these two fiscal years represent important steps in an ongoing effort to create a 

modern FDA capable of responding to the challenges and opportunities to protect 

and promote public health in the 21st century. We will be good stewards of the 

funds you provide and we will search for efficient and effective solutions to the problems we are working to solve. 

The resources requested in the President’s budget for fiscal year 2008 will allow 

FDA to respond to emerging challenges, advance the gold standard for regulating 

food and drugs, and strengthen America’s confidence in the work of our important 

agency. 

Our achievements during the past year reflect our service to the American public 

and our dedication to their health and safety. These achievements also justify the 

trust you placed in us with your support in fiscal year 2007. Using funds that you 

appropriated, FDA: 

—approved a new test to diagnose avian influenza virus in humans 

—issued guidelines to expedite seasonal and pandemic flu vaccine development 

—approved new vaccines for shingles and to prevent HPV infections 

—approved new treatments for cancer, HIV, diabetes, Parkinson’s, schizophrenia, 

and macular degeneration 

—issued more than 510 generic drug approvals or tentative approvals 

—approved the first totally implanted artificial heart 
482 

—embraced many of the Institute of Medicine findings on The Future of Drug 

Safety 

—launched a program to achieve the optimum safety system for drugs and other 

medical products 

—developed proposals to renew prescription drug and medical device user fee programs 

—conducted drug reviews and issued approvals under the President’s Emergency 

Plan for Aids Relief 

—conducted enforcement actions to protect consumers against unapproved drugs 

and devices, to safeguard the blood supply, and to protect consumers from dietary supplements containing ephedrine alkaloids 

—worked with Federal, State, and local partners to respond to Salmonella, E. coli 

O157:H7, and other foodborne threats 

—issued a final rule on health claims for barley products and issued guidance on 

whole grain content in food 

—protected consumers with food allergies by publishing guidance documents for 

industry on food allergen labeling and soy derived products 

—conducted a CARVER ∂ vulnerability assessment in eight food products to distinguish between real and perceived food vulnerabilities. 

FDA’s 2008 President’s Budget Request 

For fiscal year 2008, the President’s budget request builds on success of fiscal year 

2007 to maintain the trajectory, by proposing a 5.3 percent increase above the fiscal 

year 2007 President’s budget. This will provide FDA with $2.085 billion, which consists of $1.641 billion in discretionary budget authority and $428 million in current 

law user fees. Our budget also includes $42.7 million for three proposed user fees 

related to reviewing generic drugs, reinspecting facilities, and issuing export certificates for food and animal feed. 

Strengthening Food Safety 

FDA is committed to ensuring that America’s food supply continues to be among 

the safest in the world, but we face challenges. For example, consumption of 

produce, particularly ready-to-eat products, has increased dramatically during the 

past decade. Americans often consume these products in their raw state, harvested 

from the vine, stem, or soil without processing to reduce or eliminate pathogens that 

may be present. Consequently, the manner in which these products are grown, harvested, packed, processed, and distributed is crucial to ensuring that microbial contamination is minimized, thereby reducing the risk of illness to consumers. Even if 

a small amount of what is harvested is contaminated, it can result in severe illness. 

FDA is taking a ‘‘farm-to-fork’’ systematic risk management approach to food safety 

to reduce the risk of food illness at all points in the food chain. 

FDA’s ability to prevent and respond to outbreaks of foodborne illness needs to be strengthened. For fiscal year 2008, we propose a $10.7 million increase for a food 

safety initiative focused on fresh produce. FDA will develop methods to prevent food 

outbreaks from occurring by rapidly detecting contamination that leads to illness, 

more quickly tracking contamination to its source, and more effectively conducting 

root cause analysis of contamination. We will also provide training to our State and 

local partners and develop a geographic information mapping system for faster 

emergency response. Finally, we will develop a decision-making system to detect 

high-risk imports before they enter U.S. commerce, so they can be evaluated by 

FDA. 

Access to Safe and Effective Medical Products 

On January 30, 2007, FDA released a report, The Future of Drug Safety—Promoting and Protecting the Health of the Public, that presents our comprehensive 

commitment to the safety of drugs and other medical products throughout their 

lifecycle. The report addresses issues referred to FDA by the 2006 Institute of Medicine report. The report details initiatives FDA will take to achieve the best possible 

safety systems for medical products, and ensures that FDA processes and scientific 

methods keep pace with, and harness the benefits of, the rapid evolution of science, 

technology, and health care. 

At FDA, we use a systems approach to ensure drug quality and maintain the right balance between the benefits and risks of the drugs we approve. An $11.2 million increase for modernizing drug safety allows FDA to advance a lifecycle approach to regulating drugs and managing drug risks. Using the fiscal year 2008 increase and base resources in the drug program, FDA will revolutionize our ability 

to identify safety issues and rapidly and effectively communicate safety concerns to 

health professionals, patients, and the public. These efforts will improve drug safety 

both before FDA grants approval and after drugs reach the market. We will also 
483 

strengthen our organizational culture to further foster an environment dedicated to 

the safety of drugs and biologics. 

As the complexity and utility of medical devices increases by virtue of advances 

in electronics and engineering, FDA maintains the same commitment to the safety 

of medical devices. Our budget contains a $7.2 million increase to strengthen medical device safety and improve FDA’s ability to identify, analyze, and act on 

postmarket safety information and use this information to improve the quality of 

new devices coming to market. 

Generic drugs are an important part of our health care system. The Congressional Budget Office estimates that generic drug use results in savings of $10 billion per 

year. During the next few years, $60 to $70 billion in brand name drugs will lose 

their patent protection, and FDA must be poised to respond to the growing number 

of generic drug applications. To help ensure that consumers enjoy a wide selection 

of lower-cost generic drugs, FDA requests an additional $5.6 million in budget authority and $15.7 million in new user fees to accelerate the review and approval of 

generic drugs. With the $5.6 million budget authority increase, FDA expects to approve an additional 50 applications during fiscal year 2008. The new user fee program ensures that FDA can measurably improve generic drug review performance 

over the next 4 to 8 years. With this new program in place, by 2014 FDA expects 

to approve 90 percent of generic drug applications within 180 days. These investments will return many billions of dollars in savings to consumers and governmentsponsored health plans. 

Our budget includes long-standing user fee programs. These programs provide 

supplemental resources that not only allow FDA to provide services in response to 

manufacturers’ product applications but also ensure that Americans have access to 

safe and effective medical products. Two of these programs, the Prescription Drug 

User Fee Act (PDUFA) and the Medical Device User Fee Modernization Act 

(MDUFMA) expire on September 30, 2007. We have engaged with stakeholders to 

develop proposals to extend these programs for an additional 5 years. In the case 

of PDUFA, FDA published a draft proposal for PDUFA IV in the Federal Register 

and conducted a public meeting with stakeholders on February 16, 2007. In the case 

of MDUFMA, FDA is nearing the end of discussions on the reauthorization of 

MDUFMA. FDA will notify Congress of our results when we complete this process. 

Ensure a Strong FDA 

To successfully perform its broad mission, FDA must hire and retain a world-class 

workforce that can respond to complex and escalating public health challenges. Our 

workforce is FDA’s most important asset, and securing the resources to support our 

workforce is a top priority in our fiscal year 2008 budget. We have nearly 10,000 

employees, consisting of medical officers, consumer safety officers, food and drug 

safety experts, medical product reviewers, and other scientists and professionals 

with specialized education, training, and experience to address complex public 

health challenges. Eighty percent of the FDA budget funds payroll or costs related 

to personnel, such as rent, utilities, and security. These are operational costs, and 

the amount we pay rises each year. For fiscal year 2008, we propose a $64.7 million 

initiative to ensure that increased costs for the pay raise, infrastructure costs, and 

the cost of relocating to our new White Oak, Maryland campus do not erode core 

FDA programs. 

Closing 

FDA’s request of $2.085 billion is essential to the success of our mission—established by Congress—to protect and promote the health and safety of the American 

public. These resources are an essential step in building a 21st century FDA that 

responds to the new opportunities and new challenges of science and technology. 

Our budget allows FDA to strengthen the tools we use to ensure the safety of foods, 

evaluate new products, and better predict—earlier and more accurately—the safety 

and efficacy of drugs, biologics and medical devices. With these resources, we will 

work to ensure that Americans enjoy the benefits of personalized medicine, a safe 

and wholesome food supply, and the promise of a better, healthier future. Our goal 

is to enable all Americans to go to bed each night confident that the food they ate 

is safe, the medical devices they used are reliable, and the drugs that they gave to 

their children and grandchildren are safe and effective. 

Thank you. 

Senator KOHL. I’d like to start by asking you to comment on the 

generic situation, generic drug situation at FDA, and the recent 

funding resolution. We provided an increase of $5 million for generic drug review. The increase provided in this resolution should 
484 

allow for 10 additional approvals or tentative approvals per month, 

which would be a 25 percent increase above the current average of 

40 approvals per month. If we can do that, it would be very beneficial in bringing more generic drugs to market. 

You stated in the requested increase in fiscal year 2008 that it 

would allow FDA to approve just 50 additional applications per 

year. Now, that would average about $112,000 per application, 

which seems very high, and it doesn’t come close, the 50 doesn’t 

come close to what we estimated would be an additional 10 per 

month, which would be more than double the 50 that you are talking about. How do you explain this discrepancy? 

Dr. VON ESCHENBACH. Well, Mr. Chairman, first of all let me 

point out that in addition to hiring the additional reviewers, which 

is an important part of the allocation to then be able to increase 

capacity, we also intend to increase capacity by the efficiencies that 

we’re building into the review process. 

One particular example is to be able to do cluster analysis, where 

we can take groups of generic drugs that are of a similar nature 

and be able to deal with them in a cluster type of analysis, so that 

we can increase the number of outputs per the number of people 

and reviewers that we have. So it’s not just a matter of the 50 that 

is allocated to the increased reviewers; it’s also what we can do by 

virtue of how we increase the systems we’re using for generic drug 

review. 

Senator KOHL. So the number that we thought we heard from 

your department, 50 additional applications to be approved for this 

year with the increased budget allocation that we gave you, that 

number of 50 is really not what we should be focusing on? 

Dr. VON ESCHENBACH. Well, again I apologize for not explaining 

to you clearly. What I indicated was, we would go in an incremental way to increasing the total output. And so what we’re expecting is, as we bring reviewers on, as we train them up, there 

will be a gap and then we will pick up on the outputs as we go 

forward over time by virtue of, one, the fact that we’re bringing the 

reviewers on, training them up, getting outputs from them and, 

two, adjusting our systems. So I think what we’re indicating is 

what is initial and then there will be a ramp-up beyond that. 

Senator KOHL. Okay. I just point out that the increase in generic 

drug applications submitted to FDA has increased from 307 applications in 2002 to almost 800 in 2006, and as you know, we are 

all very intent on bringing more and more generics to market in 

an effort to reduce the cost of drugs to our population, particularly 

our senior population. Generic is key to that, as you know. My understanding is that you are most sympathetic to that attempt, want 

to do everything you can to facilitate it and to increase the number 

of approvals that we annually can give through the FDA to the generic market. Is that a fair statement? 

Dr. VON ESCHENBACH. Yes, sir, that is a fair statement and I 

think, as we have spoken before, we’re doing this not only in terms 

of increasing numbers but trying to do this strategically as well. So 

we’re looking at opportunities to make sure that we have a broad 

portfolio of options across that portfolio, and so we’re expediting, if 

you will, the process to get first generics out. 
485 

We’re educating the industry to get better applications in the 

first place. So as the application numbers increase, if they’re better 

applications, that will enhance the review process and the likelihood of success. So we’re taking a multipronged approach to being 

able to accomplish the goal that you have felt so strongly about and 

have proposed to us. 

Senator KOHL. That’s good. As you know, we’re planning a hearing in Madison, Wisconsin, on I believe it’s March 12, and I’m looking forward to that hearing on food safety. And I don’t want to get 

into too much detail about that because we’ll deal with it at that 

time, but there is a report that you may want to comment on, that 

between 2003 and 2006 FDA food safety inspections have dropped 

by 47 percent. This was reported yesterday by the Associated 

Press. 

Now, clearly with all the concern about food safety in our country, dropping the number of inspections by nearly half, according 

to that report, is I am sure something that concerns you greatly, 

to the extent that it is accurate. And what we are allocating in 

your budget for strengthening food safety is an increase of less 

than 3 percent for food safety, to include food inspections. 

Now we have all these ongoing recalls. Just this morning I was 

informed, as this hearing unfolded, there is a recall on cantaloupes. 

I don’t know any details on it, but it’s out there. Perhaps you’ve 

heard about it, maybe you haven’t heard about it, but it came over 

the press this morning. 

But people are going to be very concerned when they read in the 

paper that the number of food safety inspections has declined by 

47 percent over a 3-year period. Do you wish to say something to 

them and to us at this time? 

FOOD SAFETY INSPECTIONS

Dr. VON ESCHENBACH. Well, Mr. Chairman, let me first of all address the issue with regard to the magnitude of the decline. The 

data that I have available indicates that the number of inspections 

in 2004 was 21,876, and in 2006 it was 17,730. Now, that’s a reduction of about 23 percent. 

The issue there is the realization that we have been implementing a risk management approach to inspections, and so rather 

than a blanket inspection, we are targeting particular facilities 

that propose a particular high risk or probable high risk. That 

makes the inspection much more intense, and so the inspection 

itself is increasing in its magnitude and scale and scope. 

Now, the numbers have gone down but the intensity and the targeting of the inspections have actually increased, and we’re doing 

that because we recognize that there are differences among these 

various facilities, depending upon what they’re producing, as to 

how likely they might result in a food outbreak. For example, facilities that are producing bread have very low probabilities of problems, whereas those that are processing seafood have a much higher risk. So we want to target the inspections to those areas, rather 

than just simply look across at the numbers. 

As far as expanding our capability and our capacity to do this, 

that’s an important part of what has been an ongoing effort to look 

at our field operations and to make strategic decisions as to what 
486 

type of field investigators we need going forward and how we can 

most effectively utilize our resources. 

So as we have recognized that we have less need for laboratory 

investigators, and more need for field investigators, who have the 

tools of modern science available to them to be deployed and dispersed at the site of inspection, we’re shifting our work force over 

the next few years to that goal, and that will in itself bring another 

75 to 100 investigators into that work force to enhance our inspection capability. But it is a systems approach to the problem, rather 

than just simply a matter of counting facilities that we inspect. 

Senator KOHL. According to this same report that I’m holding, 

which I got from Senator Harkin, who could not remain but wanted 

to have these issues raised with you this morning, safety tests for 

U.S.-produced food have dropped nearly 75 percent, from 9,748 in 

2003 to 2,455 last year, according to your agency’s own stats, which 

are being used on this report that I got from Senator Harkin this 

morning. It’s from cnn.com/Associated Press. 

Now, I think those numbers, at least on their face, would be of 

great concern to you, certainly of great concern to the American 

public. Do you have any comment on that? 

Dr. VON ESCHENBACH. Well, as I indicated, what we are attempting to do is really maximize our ability to have impact with regard 

to these inspections. In some degree that is a matter of increasing 

the kind of—the number of investigators and their unique skill 

sets, and that is a process that we have engaged in and are committed to. 

In addition to that, I think the real opportunity is to realize that 

there are 60,700 food firms that are out there that we must inspect, and where we have the opportunity to really make major inroads is to place the inspection process on a sound foundation of 

risk management. And so by targeting those facilities that we 

think are at the highest risk and maximizing our efforts there, it 

really gives us an opportunity to protect the public health, I think 

in a more effective way. So it’s not just a matter of numbers, it’s 

a matter of how we are doing the inspections and how we’re deploying our work force, and I think both of those are important. 

PANDEMIC FLU

Senator KOHL. All right. I’d like to turn to Mr. Turman now and 

ask you this question. In Dr. von Eschenbach’s opening statement 

he talked about some of the FDA accomplishments over the past 

year. The first two of those had to do with pandemic flu. 

Could you talk about efforts at the department level on pandemic 

flu? We had discussed this earlier with Secretary Johanns. How 

are the various agencies at HHS, where you occupy a very high 

ranking position, working together and with the USDA in order to 

make sure that we have a streamlined and coordinated plan for 

dealing with any potential outbreaks of avian flu, Mr. Turman? 

Mr. TURMAN. Thank you, Mr. Chairman. I can affirm that indeed 

Secretary Leavitt is working very closely with his Cabinet colleagues such as Secretary Johanns, as part of the President’s plan 

which the Congress funded last year at $5.6 billion through supplemental funding for avian flu and being prepared for it. And within 

the Department of Health and Human Services, we work very 
487 

closely together with the FDA, with the CDC, with the NIH, with 

our other partners in the Office of the Secretary, we work very 

closely together to make sure that we can be protected as best we 

can for that which we see and foresee coming. 

And the areas where the funding has gone, they have been primarily to work both on purchasing those antivirals which we can 

get and stockpile, and also developing vaccines which would be of 

use against some of the strains that could be coming in terms of 

avian influenza. And in that regard FDA has a very key role and 

has been playing an important role on helping us try and speed the 

development of those vaccines. 

That is a key position that FDA has relative to their expertise, 

and their counsel and their efforts have been well integrated with 

the department’s plans, and they have been making a key contribution in that regard. And so they used the funding provided from 

the Congress in the initial supplemental, and indeed our 2008 

budget request has additional funds over current investments to 

not only help deepen those efforts but also work on engaging in 

some tools which would help detect foodborne transmission potentially of any of these virus items. 

So it’s an area where Dr. von Eschenbach may want to amplify 

in terms of FDA’s piece, but they are an integral partner of the department’s plans. 

WOMEN’S HEALTH

Senator KOHL. All right. Dr. von Eschenbach, fiscal year 2007 House and Senate bills included $4 million for the Office of Women’s Health. In fiscal year 2008 the President’s budget request includes a decrease of $350,000 for that office. According to FDA, this 

funding will be transferred to the National Center for Toxicological 

Research, for research pertaining to women’s health that is ongoing. However, this is the first time that women’s health funding 

has been decreased in the budget. I was disappointed to see the decrease in that budget of $350,000 

for women’s health, and in today’s Washington Post there was a report that FDA is intending to cut the fiscal year 2007 level down 

to $2.8 million from the $4 million requested by the President and 

provided by Congress. Now, I know that your spending plan has 

not yet been finalized, but this information must have come from 

somewhere. Can you assure us that the budget for fiscal year 2007 

is going to be $4 million and not something less? 

Dr. VON ESCHENBACH. Well, Mr. Chairman, at the outset let me 

assure you and other members of the committee that I personally, 

and the FDA is absolutely committed to enhancing the issues of 

women’s health within the agency. We are, as you pointed out, in 

the process of developing our plan for 2007, and will be bringing 

that to you within the next few weeks. 

With regard to the issue of the 2008 budget, I think it’s important to put this entire issue into context. When I say that we are 

committed to women’s health, this is a comprehensive effort. 

One of the most important aspects of it is the critically important 

research that’s going on in the National Center for Toxicologic Research, that is helping us identify genetic and molecular differences 

that are related to gender and how we can begin to really address 
488 

many of the challenges that have been presented by the Women’s 

Health Initiative. Actually, Women’s Health has been using dollars 

to fund that research in NCTR all along, and what this is essentially is a transfer of that $350,000, to get them integrated into the 

NCTR’s research base so that we can really amplify that portfolio. 

So it’s not in any stretch of the imagination a diminishing of our 

commitment to women’s health. It’s actually enhancing our ability 

to create a research base that will address critically important scientific issues in women’s health, as well as provide that foundation 

for other similar questions, including the kind of challenges we’re 

seeing in personalized medicine that not only recognize gender differences but even potentially differences that come about beyond 

gender, including racial differences. 

Senator KOHL. That toxicological research is for 2008, but in today’s paper it was reported that the FDA is intending to cut the 

fiscal year 2007 budget for Women’s Health down from $4 million 

to $2.8 million. Now, I would like you to say that that’s an inaccurate report, it’s not operable, that for fiscal year 2007, which is 

not fiscal year 2008 and targeting this $350,000, but for fiscal year 

2007 the number of $4 million remains intact and is not going to 

be reduced. 

Dr. VON ESCHENBACH. Well, Mr. Chairman, the answer to your 

question is, we haven’t made that decision yet as to what the 2007 

final plan would be. I’m looking at the entire portfolio, so that 

we’re responsive across the entire budget, and have not at this 

point made any final decision about any particular component of 

that budget. 

Senator KOHL. Are you, just let me ask the question, are you familiar with any consideration for a reduction in fiscal year 2007 of 

the Office of Women’s Health to something below the $4 million? 

Dr. VON ESCHENBACH. Well, we have been looking across the entire Office of the Commissioner, of which the Office of Women’s 

Health is a component, and we’re looking to bring that entire office 

into fiscal balance, if you will, with regard to our overall budget. 

Now, with regard to the specific details of what’s happening with 

each of those compartments within the Office of the Commissioner, 

I can’t speak to, but I’ll be happy to get back to you on that for 

the record. But the fact of the matter is, we haven’t made a final 

decision, so I can’t commit to any particular number at this point, 

until that is done. 

Senator KOHL. All right. We’ll continue to work on that number 

and get some report, as you have indicated, as soon as you can. I 

thank you. 

[The information follows:] 

WOMEN’S HEALTH

We are currently working on our fiscal year 2007 operating plan, as required 

under section 113 of Public Law 110–5, the Revised Continuing Resolution for fiscal 

year 2007. We expect to fund the Office of Woman’s Health at not less than last 

year’s level. FDA is committed to activities sounding women’s health. The concerns 

of women are a priority at FDA, and the Office of Women’s Health serves as a 

champion for women’s health issues. 

Senator KOHL. At this time I would like to turn to Senator Reed. 
489 

SUNSCREEN MONOGRAPH

Senator REED. Thank you very much, Mr. Chairman. 

Thank you, doctor. Just a point, not a question. But since 1997 

the agency has been struggling to get a UVA/UVB labeling protocol, monograph, together. I’m going to follow up with a written 

question and ask you, bottom line, when it might happen. 

TOBACCO

Turning to another topic of interest, I just left the HELP hearing 

on the regulation of tobacco, and it raises serious questions. You 

have extensive experience as a former director of the National Cancer Institute. I believe personally that authority for FDA is long 

overdue, to have some role in the regulation of tobacco, and I’m 

hopeful we can get the legislation through. What are your views 

with respect to FDA’s role in potentially the regulation of tobacco 

products? 

Dr. VON ESCHENBACH. Well, Senator, as you point out, from my 

perspective and my career at the National Cancer Institute, like 

you and everyone, I recognize the serious public health threat that 

occurs as a result of smoking and tobacco. 

From the perspective of the Food and Drug Administration, as 

Commissioner, one of the things I think is extremely important is 

to realize the complexity of this issue and the complexity of the 

kind of issues that it presents, on one hand looking at it from the 

perspective of what has emerged with regard to the science and our 

understanding of addiction as it’s related to nicotine, all the other 

way to the other end of the continuum, where we’re looking at a 

cigarette which is a complex product. It has tobacco that has additives of one type or another, wrapped in paper and set on fire, and 

someone breathes in smoke. 

And from that perspective, with all that complexity, I think it’s 

extremely important that we engage in a careful assessment of how 

we might address that complexity as a way of then beginning to 

address what role FDA should or should not have in that process. 

Senator REED. But the complexity itself is not such that you 

would be incapable as an agency of dealing with the issue. The 

question would be what you could do effectively. I think that would 

be the first question. 

Dr. VON ESCHENBACH. Well, as I look at it and the question, 

framing it within the mission of the FDA to protect and promote 

the public health, I think it’s an issue of being able to determine 

how we could regulate whether a product was in fact safe under 

any circumstances or in any possible way, and what potential benefit or value it might have to health in any possible circumstance 

or any possible way. 

So that is what I believe is at the core and the base of a regulatory decision, the complexity of a regulatory process as it relates 

to tobacco. And I think those are discussions and issues that need 

to occur and are going on. 

Senator REED. At a threshold level you certainly could identify 

the ingredients and publicize those, of a cigarette. 

Dr. VON ESCHENBACH. I think that’s one of the questions that we 

have to address. 
490 

Senator REED. That you could or could not do that? 

Dr. VON ESCHENBACH. Correct. 

Senator REED. How difficult is it to identify the ingredients of a 

cigarette? 

Dr. VON ESCHENBACH. If you’re talking about the ingredients in 

the inhaled smoke, that, which is what in fact would have the public health impact, not what’s in the product prior to it being 

smoked, that is the kind of scientific challenge and question that 

I think underscores the complexity of the problem. 

Senator REED. Do you think that the companies themselves have 

that information or do that research? 

Dr. VON ESCHENBACH. I honestly don’t know the answer to that 

question, Senator. 

USER FEES

Senator REED. Turning to another issue, and that is the issue of 

user fees, so many of your programs have user fees attached to 

them, which raises a question of what percentage of your total 

budget is covered by annual appropriations, what percentage is 

paid for through user fees. 

Dr. VON ESCHENBACH. As far as the absolute percentage, I’m 

going to turn to my right to ask Mr. Dyer to quickly calculate that 

for you. But while he’s doing that, let me state specifically that I 

view the user fees as exactly that. They are a fee for service, so 

that they do not impact upon the overarching mission of the agency, but allow us to provide a service that is of value or benefit to 

the industry in terms of their ability to move applications more efficiently and more rapidly through the system, by having the resources with which to do that. 

And so I know that issues have been raised about whether the 

fact that we have user fees is in some way creating problems with 

regard to the mission and focus of the agency, and let me assure 

you, Senator, that is not the case and will not be the case. 

Having said that, I think that they provide for us the opportunity 

to enhance resources, infrastructure, personnel to address issues 

like our ability to accelerate drug approvals, our ability to bring 

new products, whether they be devices or drugs or biologics, to patients as rapidly as possible, while we still at the same time assure 

the safety and the efficacy of those products. 

Senator REED. Mr. Dyer. 

Mr. DYER. Sir, the budget proposes $444 million in fiscal year 

2008 for user fees in total, out of a total program level of about 

$2.1 billion, which makes about 20 percent. 

Senator REED. Twenty percent? And how has that number 

changed, that percentage changed, over the last 5 years? Has it increased, decreased, remained stable? 

Mr. DYER. I don’t have the exact numbers. We’ll provide them for 

the record. But it has been increasing. 

[The information follows:] 

USER FEES

From fiscal year 2002 to fiscal year 2006, the percent of FDA user fees compared 

to the total FDA budget increased from 12 to 20 percent. During this time, FDA 

established two new user fees for Medical Devices and Animal Drugs. FDA began 

to collect fees under these two user fee programs in fiscal year 2003 and fiscal year 
491 

2004, respectively. These new user fees account for nearly one fifth of the total fee 

increase from fiscal year 2002 to fiscal year 2006. 

Senator REED. Has been increasing. And as you project forward, 

do you project an increase in the fees, this 20 percent getting bigger and bigger? 

Mr. DYER. The amount of fees will go up, but again it depends 

on what percentage of the overall budget, depending on how much 

budget authority this committee gives us. 

Senator REED. And, doctor, you have assured us that these fees 

in no way distort your approach to your duties, i.e., because you’re 

being paid but with fees you have to do certain things, where other 

appropriated functions are not tended to. That’s your statement. 

Dr. VON ESCHENBACH. What I was speaking to, Senator, was 

where the concerns that have been raised about user fees in the 

press and et cetera allow me the opportunity to assure you that as 

far as the regulatory process is concerned, the integrity of that 

process is not in any way impacted or adulterated by the fact that 

user fees make up a portion of our resource base. They are strictly, 

as I have indicated, a fee for service. 

With regard to our ability to manage our portfolio of resources, 

I think it’s an issue that we are addressing, to make certain that 

we are able to deploy resources as efficiently and as effectively 

across that entire continuum. And so I am committed to putting all 

components of the agency on that sound foundation, whether they 

have user fees or not. 

Senator REED. Are there new user fees in this budget, proposed 

budget? 

Dr. VON ESCHENBACH. Yes, sir. There are three particular user 

fees that are proposed in the fiscal year 2008 budget. One of them 

has to do with generic drugs, and the other ones are user fees that 

have previously been presented, having to do with reinspection fees 

and export certificate fees. 

Senator REED. And will we receive a formal proposal to enact 

these fees? 

Dr. VON ESCHENBACH. Yes, sir. That, as far as the proposal for 

authorization of these fees, the two that I mentioned, the reinspection fees and the export certificates, they have previously been introduced and we will reintroduce them again. The generic drug 

user fee is a new fee, and we are in the process of developing that 

proposal for authorization. 

Senator REED. It seems, the impression, at least, that because of 

constraints on your appropriated budget there is a strong tendency 

to ask for user fees. Is that what seems to be happening here? 

Dr. VON ESCHENBACH. I think they present an option with regard 

to continuing to increase our ability to provide services. And in addition to the appropriations, we have looked for a variety of ways 

to be able to do that, including our ability to collaborate and cooperate in relationships, for example, with the NIH. 

So the approach I’m taking, Senator, is to build a resource base 

and a business plan that supports our overall mission, recognizing 

that there is a critically important part of that that is the appropriation; there are user fees that can contribute to that; and then 

there may be other opportunities as well. And the point of all of 

that is to enhance our ability to serve the American people by 
492 

bringing safe and effective products and food to them as rapidly 

and as efficiently as possible, while still assuring the safety and the 

efficacy of those products. 

DEPARTMENT OF HEALTH AND HUMAN SERVICES

Senator REED. A final question, doctor. It’s my understanding 

that other agencies like the National Science Foundation don’t 

have to go through all of the hoops and the hurdles that you do 

through HHS and OMB, that they have much more direct engagement with Congress on their budget. Would a more direct engagement help you? 

Dr. VON ESCHENBACH. Well, I have found that the process that 

I have at this point, since I’ve been in this position, has really 

worked quite well, Senator. I think as we looked at the 2007 budget and the 2008 budget, the collaboration and cooperation within 

the department, within the administration, and with Congress is 

working quite well at this point. 

Senator REED. Thank you, Mr. Chairman. 

Senator KOHL. Thank you, Senator Reed. And we would like to 

thank you. Dr. von Eschenbach, as well as Mr. Dyer and Mr. 

Turman, for helping us to conduct an informative hearing, and we 

look forward to continuing to work with you. 

ADDITIONAL COMMITTEE QUESTIONS

We want to thank all of our witnesses, yourself and the Secretary of Agriculture, for being here. Members should provide us 

with questions for the record by Tuesday, March 6. And we look 

forward to continuing our dialogue and our collaboration together 

on behalf of the American people. Thank you so much. 

Dr. VON ESCHENBACH. Thank you. 

[The following questions were not asked at the hearing, but were 

submitted to the Department for response subsequent to the hearing:] 

QUESTIONS SUBMITTED BY SENATOR HERB KOHL

OVERALL FUNDING

Question. Please provide a crosswalk table, in the same format as was provided 

on page 68 of FDA’s fiscal year 2008 Budget Summary, that shows how FDA will 

allocate requested increases from the fiscal year 2007 spending plan level to the fiscal year 2008 President’s budget request. If possible, please do not include any ‘‘redeployments’’. 

Answer. FDA is in the process of finalizing the fiscal year 2007 spending plan and 

developing the bridge between the spending plan and the fiscal year 2008 President’s budget. 

Question. Please provide updated performance data based on this information. 

Answer. The performance data submitted in the President’s budget may change. 

The fiscal year 2008 President’s Budget uses the fiscal year 2007 President’s Budget 

as a baseline, which is different from the fiscal year 2007 enacted appropriation. We 

appreciate that the fiscal year 2007 enacted appropriations fully funded our pay and 

infrastructure needs, allowing FDA to keep more staff on board to maintain our current performance levels throughout the Agency. 

Question. If the Committee provided FDA with all increases requested in the President’s budget, totaling $95,439,000, would the performance data submitted by 

FDA still be accurate, even though these increases would be based on a number that 

is higher than the original level FDA budgeted from? 

Answer. The performance data submitted in the President’s budget may change. 

The fiscal year 2008 President’s Budget uses the fiscal year 2007 President’s Budget 

as a baseline, which is different from the fiscal year 2007 enacted appropriation. We 
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appreciate that the fiscal year 2007 enacted appropriations fully funded our pay and 

infrastructure needs, allowing FDA to keep more staff on board to maintain our current performance levels throughout the Agency. 

FOOD SAFETY

Question. Please provide information on how additional funding provided for food 

safety activities at FDA above the President’s request would be allocated. Please 

provide this information in $5 million increments up to $50 million. 

Answer. FDA is committed to ensuring that America’s food supply continues to 

be among the safest in the world, but we face challenges. For example, consumption 

of produce, particularly ‘‘ready-to-eat’’ products, has increased dramatically during 

the past decade. Americans usually co nsume these products in their raw state, harvested from the vine, stem, or soil without processing to reduce or eliminate pathogens that may be present. Consequently, the manner in which these products are 

grown, harvested, packed, processed, and distributed is crucial to ensuring that microbial contamination is minimized, thereby reducing the risk of illness to consumers. Even if a small percentage of what is harvested is contaminated, it can result in severe illness. FDA is taking a ‘‘farm-to-fork’’ systematic risk management 

approach to food safety to reduce the risk of food illness at all points in the food 

chain. 

For fiscal year 2008, we propose a $10.644 million increase for a food safety initiative focused on fresh produce. FDA will develop methods to prevent food outbreaks 

from occurring by rapidly detecting contamination that leads to illness, more quickly 

tracking contamination to its source, and more effectively conducting root cause 

analysis of the contamination. We will also provide training to our State and local 

partners and develop a geographic information mapping system for faster emergency response. Finally, we will develop a decision-making system to detect highrisk imports before they enter U.S. commerce, so they can be evaluated by FDA. 

Due to the increased consumption of fresh produce and the current outbreaks of 

contamination, FDA would allocate additional funding for specific areas where we 

could expand the food safety program in order to promote and improve the public 

health. FDA has identified the following five critical areas as targets for future 

growth: 

—preventing contamination and produce safety research 

—preventing outbreaks and mitigating outbreak impact 

—monitoring antibiotic usage and antibiotic resistance in bacteria from farmraised aquatic animals and their environments 

—developing efficient techniques for identifying foodborne pathogens that cause 

outbreaks 

—providing additional field support for the Foods and Animal Drugs and Feed 

Programs. 

Question. Please provide information on how the rapid response teams in the 

Strengthening Food Safety initiative would be set up and what activities they would 

undertake. Please provide an estimate of how much it will cost to create and support each rapid response team. 

Answer. The $3.5 million requested in the fiscal year 2008 Congressional Justification, Strengthening Food Safety Initiative, will support FDA costs for 12 staff 

members, and provide equipment and training for each team member. The Office 

of Regulatory Affairs, or ORA, will be able to develop teams trained in traceback 

technologies and incident command. ORA will strategically position these teams in 

areas with large produce-growing regions. In addition, ORA will provide training, 

equipment, and other assistance to States so that they can be full partners with 

FDA in responding to and preventing produce-related outbreaks. After the first 

year, ORA will have 12 fully equipped and trained FTEs with traceback equipment, 

such as handheld GPS devices that can be used with geographic information systems to facilitate investigations of outbreaks. 

These teams will be modeled on the California Food Emergency Response Team, 

or CalFERT, which investigated the recent E. coli outbreak in spinach. CalFERT is 

a joint FDA and California Department of Health Services’ Food and Drug Branch, 

or FDB, Rapid Response Team trained and ready to respond within hours of the 

verification of a food borne outbreak. That team, consisting of ORA Investigators 

and Microbiologists and State of California FDB personnel, demonstrated the importance of FDA collaboration with State regulatory partners. Team members can immediately start the outbreak investigation because they have clearly defined roles 

and responsibilities, a previously identified chain of command and a known procedure to keep other involved parties informed, such as the Incident Command Center 
494 

of FDA’s Office of Crisis Management. These teams will benefit the entire food program, not just produce safety. 

Question. Does CFSAN have an overall ‘‘produce safety’’ plan? If so, please provide 

this to the Committee, including all cost estimates to implement this plan, even if 

they were not include in the President’s budget request. 

Answer. In October 2004, FDA issued a Produce Safety Action Plan(the PSAP) designed to target microbial and other food safety hazards, such as bacteria, viruses, 

and parasites, in or on produce consumed in the United States, whether produced 

in the United States or abroad. The PSAP extends to all parts of the food chain from 

farm through retail or consumer preparation and consumption and has four general 

objectives: 1—to prevent contamination of fresh produce with pathogens; 2—to minimize the public health impact when contamination of fresh produce occurs; 3—to 

improve communication with producers, preparers, State and local government entities, and consumers about fresh produce; and 4—to facilitate and support research 

relevant to fresh produce. For each objective, the PSAP identifies steps that could 

contribute to the achievement of the objective. 

The fiscal year 2008 President’s Budget Request contributed to these objectives. 

GENERIC DRUGS

Question. As you know, in the JR, we also provided an increase of $5 million for 

generic drug review at FDA. It is my understanding that the increase provided in 

the JR will allow for ten additional approvals or tentative approvals per month, 

which is a 25 percent increase above the current average of 40 approvals per month. 

What is the current backlog of generic drugs? Do you expect it to increase this year, 

even with the additional funds provided, because of an increase in applications submitted? 

Answer. The current backlog is around 1,300 abbreviated new drug applications 

(ANDAs) as of the end of February 2007. However, not all ANDAs are available to 

be approved currently due to patent protection and exclusivities. There are currently 

about 600 abbreviated new drug applications that do not have patent or exclusivity 

protection. Because we are still not at a point where we can process (approve or tentatively approve) the number of applications that we receive, the backlog will continue to increase. The rate of increase, however, will not be as steep with the provision of additional funds. Our goal is to use the FTEs obtained with the $5 million 

to address certain review areas to increase the number of approvals and tentative 

approvals. Through additional efficiency initiatives, we will still endeavor to approach the projected percent increase in approvals. 

Question. What will the $5.5 million increase requested in the budget buy? How 

many additional approvals will you get with this money? 

Answer. It is expected that an additional $5.5 million will provide 13 FTEs. Although it is difficult to predict the number of additional approvals due to the increasing scientific and legal complexity of the applications being received, the escalating workload involved with responding to Citizen Petitions received, and the 

growing number of requests for information received by the office, the Office of Generic Drugs or OGD, will strive to increase the yearly number of approvals and tentative approvals by 50. It is important to note that each Abbreviated New Drug Application, or ANDA, represents a product intended to be marketed in this country 

and contains a full scientific data package that must be carefully evaluated. The increasing complexity of many of the applications received is increasing the review 

time needed to fully and comprehensively review these applications. 

Question. Please provide information on how many additional approvals could be 

provided with increases of up to $20 million, in $5 million increments. 

Answer. We estimate that we would be able to increase the number of approvals 

in fiscal year 2009 (from 60 to 135) more than fiscal year 2008 (from 50 to 125), 

taking into account that 10–15 percent of the increase used for IT investment and 

time to hire all the reviewers and train them to conduct reviews could affect the 

projected number of approvals: 

[The information follows:] 

NUMBER OF APPROVALS 1

Increment Fiscal year 2008 Fiscal year 2009 

$5 million ................................................................................................................................ 50 60 

$10 million .............................................................................................................................. 80 90 

$15 million .............................................................................................................................. 110 120 
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NUMBER OF APPROVALS 1—Continued 

Increment Fiscal year 2008 Fiscal year 2009 

$20 million .............................................................................................................................. 125 135 

1 Note we assume that the full $20 million is received in fiscal year 2008 and fiscal year 2009. 

Question. Please provide a breakdown of the pending generic drug applications by 

the four paragraphs of the Hatch Waxman Act. 

Answer. The current breakdown is as follows: 

Paragraph I: patent information has not been filed—418 

Paragraph II: patent has already expired;—186 

Paragraph III: date on which the patent will expire (generic drug will not seek 

final approval until that date passes);—344 

Paragraph IV: patent is challenged as invalid or not infringed.—347 

Question. How many pending applications would be ‘‘first’’ generics? Of those, how 

many could immediately be marketed if approved? 

Answer. It is difficult to determine what you intend to include in the term ‘‘first’’ 

generic. There may be a number of pending applications for the same product that 

does not currently have generic competition. They could not all be counted as the 

‘‘first’’ generic and we will not know which will be the ‘‘first’’ generic until we issue 

an approval. For this reason, applications are not classified as ‘‘first’’ generics upon 

receipt in the office, making the tracking of ‘‘first’’ generics in the list of pending 

applications difficult. 

Regarding the pending applications in OGD, 344 applications have been submitted with paragraph 3 patent certifications (will wait until a patent in force expires) and 347 applications have been submitted with paragraph 4 certifications (are 

challenging a listed patent as invalid or not infringed). Since products to which 

these applications refer still have patents in force which may have prevented previous generic approvals, many of these 691 applications have the potential to be 

‘‘first’’ generic applications. The majority, of course, will be approved subsequent to 

the first generic approval, and, until the time of approval, we will not be able to 

determine which product will be THE first generic for a particular reference listed 

drug. 

Of the remaining applications, 445 were submitted with paragraph 1 certifications 

(no listed patents) and 187 were submitted with paragraph 2 certifications (patents 

have expired). Because many of the products referenced in these applications already have generic competition, only a few of these are likely to be ‘‘first’’ generics 

when approved. To address the products in this category for which no generic has 

been previously approved, the Office of Generic Drugs, or OGD, instituted a revision 

in its first-in, first-reviewed policy last October (10/06). Instead of reviewing these 

products in the order of receipt, OGD will now expedite any application for a ‘‘first’’ 

generic product for which there are no listed patents on the reference product at 

the time of the generic application’s submission. We believe that this will allow critically needed ‘‘first’’ generics of products without patent protection to reach the market place faster. 

Question. Please provide specific productivity outputs should the proposed generic 

drug user fee program be authorized. 

Answer. Following the first full implementation year, during which time additional staff will be hired and trained, the Generic Drug User Fee will result in a 

50 percent increase in approvals/tentative approvals compared to the current average of 40 approvals/tentative approvals per month. During the next 5 years, the goal 

is to meet the statutory requirement for generic drug review by acting on 90 percent 

of original Abbreviated New Drug Application, or ANDA, and amendments to unapproved applications within 180 days. 

IMPORT INSPECTION

Question. How many import lines did FDA review from 2002–2007, by year? How 

many import lines does FDA anticipate reviewing in 2008? 

Answer. I will be happy to provide that information for the record 

[The information follows:] 
496 

IMPORT LINES FOR FISCAL YEAR 2002–2006 

Fiscal year 

2002 2003 2004 2005 2006 

TOTALS ............................................. 7,838,956 9,336,735 11,616,348 13,819,402 14,977,795 

ESTIMATED IMPORT LINES BY FISCAL YEAR 2007–2008 

Fiscal year 

Estimate 2007 Estimate 2008 

TOTALS ..................................................................................................................................... 16,323,947 17,893,795 

Question. What percentage of imports were physically inspected by FDA in 2006? 

What percentage does FDA anticipate inspecting in fiscal year 2007 and 2008? 

Answer. Approximately .89 percent of all imports were physically inspected by 

FDA in fiscal year 2006. FDA estimates it will physically inspect .73 percent in fiscal year 2007 and .66 percent in fiscal year 2008. 

It is important to note that FDA electronically screens imports through the Operational and Administrative System for Import Support, or OASIS. OASIS is an automated system for processing and making admissibility determinations for FDA regulated products that are offered for import. FDA also performs laboratory analysis 

on products offered for import into the United States; conducts foreign inspections 

to evaluate manufacturing conditions of products before they are offered for import; 

and, performs periodic filer evaluations to ensure that the import data being provided to FDA is accurate. 

The Prior Notice Center, or PNC, is another important part of FDA’s import strategy. The mission of FDA’s PNC is to identify imported food and feed products that 

may be intentionally contaminated with biological, chemical or radiological agents, 

or which may pose significant health risks to the American public, and intercept 

them before they enter the United States. FDA will continue to focus resources on 

Intensive Prior Notice Import Security Reviews of products that pose the highest potential bioterrorism risks. By using a risk based approach, the PNC can intercept 

potentially hazardous products before they enter the United States. 

The benefit of these reviews comes from the quality and targeting of review activities; not from the volume of imports inspected. Thus the quality of import screening 

is a better measure of FDA’s import strategy rather than simply focusing on the 

items physically examined. 

I will be happy to provide information on the percentage of imports physically inspected in table form for the record. 

[The information follows:] 

Import Lines Physical Exam 

Subtotal 

Percent Physically Examined 

Fiscal year 2006 ........................................................................................ 14,977,795 132,594 0.89

Fiscal year 2007 estimates ....................................................................... 16,323,947 118,400 0.73 

Fiscal year 2008 estimates ....................................................................... 17,893,795 118,370 0.66 

Question. Please provide information regarding total field staff working on import 

inspections? How has this number changed in the last 5 years? 

Answer. FDA estimates that 611 FTE will perform import investigative work in 

fiscal year 2008 and 643 FTE in fiscal year 2007. This number compares to 674 FTE 

in fiscal year 2006; 666 FTE in fiscal year 2005; 653 FTE in fiscal year 2004; and, 

807 FTE in fiscal year 2003. These resources include FTE who perform import laboratory analyses. 

I am happy to provide the information in table form for the record. 

[The information follows:] 
497 

Fiscal year 

Import Investigative FTE (includes import 

lab analyses resources) 

2008 estimate ...................................................................................................................................................... 611 

2007 actual .......................................................................................................................................................... 643 

2006 actual .......................................................................................................................................................... 674 

2005 actual .......................................................................................................................................................... 666 

2004 actual .......................................................................................................................................................... 653 

2003 actual .......................................................................................................................................................... 807 

Question. What percentage of fresh produce was physically inspected in fiscal year 

2006? What percentage does FDA anticipate inspecting in fiscal year 2007 and 

2008? 

Answer. Approximately .82 percent of fresh produce was physically inspected by 

FDA in fiscal year 2006. FDA estimates it will physically inspect .69 percent in fiscal year 2007 and .67 percent in fiscal year 2008. An FDA physical inspection of 

an import line is defined as either having had a field exam conducted or a sample 

of the import line collected and analyzed in the laboratory. A field examination is 

simply an on-the-spot examination or field test performed on a product to support 

a specific decision. A physical inspection does not include import lines that were detained at entry without a physical exam, or DWPE, based upon an Import Alert. 

I will be happy to provide that information in table form for the record. The information follows. The following tables reflect the estimated percentage of fresh 

produce imports that were physically inspected in fiscal year 2006, and the estimated percentage of fresh produce that will be physically inspected in fiscal year 

2007 and fiscal year 2008. 

[The information follows:] 

Fresh Produce 

Import Lines 

Physical Exam 

Subtotal Percent Physically Examined 

Fiscal year 2006 ........................................................................................ 1,553,401 12,668 0.82 

Fiscal year 2007 estimates ....................................................................... 1,591,345 10,980 0.69 

Fiscal year 2008 estimates ....................................................................... 1,630,216 10,922 0.67 

Question. Is the FDA’s Prior Notice Center fully staffed and operational? Please 

provide a breakdown of staff makeup, including permanent staff, temporary staff, 

detailees, etc. 

Answer. The Prior Notice Center is opened and operating on a 24/7 basis. The current composition of the permanent PNC staff includes one Director, one Deputy Director; eight Watch Commanders; and, 22 Reviewers. In addition, the PNC presently 

has one Watch Commander and three Reviewers on detail to the PNC. 

FDA is currently advertising a vacancy announcement for 2 additional reviewers. 

Ideally, the PNC would like to hire 1 additional Watch Commander, 3 additional 

reviewers, one support staff person, and 1 statistician. This would bring the total 

staff at the PNC to 1 Director, 1 Deputy Director, 9 Watch Commanders, 27 reviewers, 1 support staff person and 1 statistician. 

AERS II

Question. Please provide a copy of the November 2006 report of the Breckinridge 

Institute on AERS II. 

Answer. I would be happy to provide that for the record. Please note that although the reports has a confidential heading FDA has cleared the document for 

public disclosure 

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Question. Please provide a breakdown of all expenditures on AERS II since inception. 

Answer. Approximately $1,405,000 has been spent on the Adverse Events Reporting System II, or AERS II, project since its inception and the breakdown of expenditures is: development of high level requirements, $140,000; system requirements 

specification, $315,542; contract support, $54,558; development contract support, 

$578, 000; and program management support, $219,996; Organizational Design and 

Planning work, $10,000; and Independent Verification and Validation work, 

$97,340. 

Question. Please discuss any and all actions FDA is taking in response to this report. 

Answer. The Breckenridge report made three recommendations. The first two recommendations allude to problems with organizational culture which are being ad-
686 

dressed on a higher, more inclusive level than the cultural problems related to this 

particular report. FDA and CDER recognize the need to improve our culture, and 

we are addressing the issues raised on that topic by the Institute of Medicine, or 

IOM, Drug Safety Report. I refer you to the FDA response to the IOM Drug Safety 

report at http://www.fda.gov/oc/reports/iom013007.html for more details. 

The third recommendation suggests FDA begin the process of acquiring a replacement for Adverse Events Reporting System I, or AERS I, immediately. Despite allegations in the Breckenridge report that we differ with, AERS II development has 

continued to move ahead, and a timeline has been developed with initial operations 

projected for fiscal year 2008. Materials such as the requirements mapping associated with the Breckenridge report are being used in developing AERS II, in addition 

to other requirements documents that are already available. 

USER FEES

Question. Please provide us with a brief update on the reauthorization of both the 

Prescription Drug and Medical Device User Fee Acts. What is status of MDUFMA 

negotiations? 

Answer. On March 23, 2007, the Secretary transmitted to key House and Senate 

authorizing committees the HHS/FDA recommendations for changes to the statute 

and to the performance commitment letter for the Prescription Drug User Fee Act 

IV, or PDUFA IV. These recommendations reflected the results of FDA’s discussions 

with the pharmaceutical and biotechnology industry, which concluded in November 

2006, and further revisions to the commitment letter based on public input received 

in response to the January 16, 2007 Federal Register R notice publishing FDA’s proposed recommendations, and received at the PDUFA IV public meeting FDA held 

on February 16, 2007. FDA’s recommended changes to the statute and commitment 

letter are currently being reviewed by the Senate Health, Education, Labor and 

Pensions, or HELP, Committee staff and House Energy and Commerce Committee 

staff. 

FDA and the medical device industry have been discussing legislative recommendations for the Medical Devices User Fee and Modernization Act, or 

MDUFMA, reauthorization since the fall of 2005. Almost all issues of interest to 

FDA and to industry have been resolved. We are working to resolve the outstanding 

issues very quickly. 

Question. How will you work to ensure that any ‘‘triggers’’ included in these pieces 

of legislation are continually, and fully, funded in your budget request? 

Answer. We will work to ensure that the Agency’s annual budget enables FDA 

to meet the performance goals it has committed to under PDUFA IV and MDUFMA 

II. 

PROPOSED USER FEES

Question. The budget includes new proposed mandatory user fees for reinspection 

costs and for export certification, which if enacted, would bring in an additional $27 

million to FDA. Please explain the need for these user fees. 

Answer. FDA is re-proposing from fiscal year 2007 two user fees that would fund 

activities currently supported by budget authority dollars. The proposed user fees 

for Reinspections and Food and Animal Feed Export Certification are mandatory 

user fees. These fees will replace budget authority in FDA’s budget. In fiscal year 

2008, if Congress enacts these user fees, any fees collected for these two proposed 

user fees will result in an equal transfer of budget authority back to the U.S. treasury. In fiscal year 2009 FDA will not need any budget authority resources for these 

activities if Congress enacts the user fees. 

When a company fails an FDA inspection, we are asking Congress to impose the 

cost of conducting follow-up inspections on the company. When we find a violation, 

FDA typically conducts a follow-up inspection to ensure that the problem is corrected. Currently, if companies fail to comply with FDA standards, then FDA must 

shift resources from other public health activities to reinspect the company and confirm they have corrected the problem. What we recommend is that the company 

pays the cost of follow-up inspections when FDA finds health or safety violations. 

It is important for companies to ensure the safety of products before the products 

reach consumers and this user fee provides an additional incentive for companies 

to meet FDA safety standards. 

In the case of food export certificates, we are asking Congress to impose the cost 

of preparing export certificates, required by foreign governments, on the companies 

that export products. Currently, FDA charges exporters for certificates in all other 

FDA product areas except foods for this service. As with the reinspection user fee 
687 

proposal, we recommend that the company benefiting from this service pay for this 

service. 

Question. If these user fees were enacted, would there be a subsequent decrease 

in discretionary budget authority needs? 

Answer. Yes, there would be a subsequent decrease in discretionary budget authority needs if the user fees are enacted. However, the current proposals are structured in such a way that budget authority of $27 million is initially requested by 

FDA at the beginning of fiscal year 2008 to continue these activities in case the user 

fee proposals are not enacted in a timely fashion. If the user fee proposals are enacted and become fully operational in fiscal year 2008, the collection of these user 

fees will result in decreases of equal amounts in discretionary budget authority that 

will be returned to the Treasury. If enacted, no budget authority resources will be 

needed for these activities in fiscal year 2009, as they will be fully funded by user 

fees. 

Question. How would the additional revenue be used at FDA? Is this reflected in 

the budget? 

Answer. Revenue will not be used to fund new activities at FDA. The purpose of 

the user fee proposals is to charge industry FDA’s current costs for reinspections 

and issuance of food export certificates. In FDA’s budget request, $27 million is initially requested at the beginning of fiscal year 2008 to continue these activities in 

case the user fee proposals are not enacted in a timely fashion. If the user fee proposals are enacted and become fully operational in fiscal year 2008, the collection 

of these user fees will result in decreases of equal amounts in discretionary budget 

authority that will be returned to the Treasury. If enacted, no budget authority resources will be needed for these activities in fiscal year 2009, as they will be fully 

funded by user fees. 

PAY COSTS

Question. Will the funding requested for pay costs meet the actual need for pay 

and benefit increases at FDA in fiscal year 2008? Part of the reason there was such 

a hole that had to be filled in the Joint Resolution was because for several years, 

FDA has had to cut into program funding to fully fund their pay and rent costs. 

We would like to prevent finding ourselves in a similar situation 5 years from now. 

Answer. The funding requested for the pay costs in fiscal year 2008 cover the 

mandatory government-wide annualized pay raise of 2.8 percent. 

RENT

Question. The President’s budget includes an increase of nearly $30 million for 

Rent and Rent-related costs. It is a breathtaking amount, and it is interesting to 

note that the increase requested for rent alone is more than the requested increases 

for drug safety, food safety and medical device safety combined. Further, if the rent 

costs aren’t accurate in the budget, as has happened in the past, increased rental 

needs have to come out of FDA program activities. How does the FDA rent costs 

compare to other Federal agencies of the same size? What actions have you taken 

to try to decrease these costs? 

Answer. The President’s budget includes a substantial increase for Rent-related 

costs due to the new White Oak facility and higher costs for essential services, such 

as utilities, security and service contracts to operate and maintain FDA’s facilities. 

FDA is not privy to other Federal agencies’ rent costs. GSA sets rental rates for all 

of its Federal tenant agencies as a pass-through of the underlying GSA lease contract rent for their leased facilities, and by appraisal based on comparable properties for GSA-owned facilities. Rent is charged per square foot occupied. Aside from 

the White Oak consolidation of headquarters locations, FDA has made considerable 

efforts in the past several years to consolidate, reduce space, or close existing offices. 

For example, the Office of Criminal Investigations recently co-located its Metropolitan Washington Field Office in Laurel, MD, and its Special Prosecution Task Force 

in Beltsville, MD, saving over $50,000 in annual rent costs. Additionally, the Office 

of Regulatory Affairs (ORA) closed seven resident posts in fiscal year 2006, saving 

the Agency $150,000 annually in GSA rent. We have notified GSA that we will be 

closing five additional offices in the coming months. Finally, ORA has developed a 

comprehensive proposal to centralize laboratory management. ORA plans to consolidate staff, equipment, and other resources from ORA’s 13 laboratories into six existing laboratories located across the country. Seven lab facilities will be closed and 

returned to GSA. If approved as currently planned, these closures will save the 

Agency almost $5 million in annual GSA rent. 

Question. When can we expect to see decreases in these rent costs, as White Oak 

continues to be occupied? 
688 

Answer. Consolidation of the FDA in the field and at headquarters will result in 

operational efficiencies and improved quality of the work environment. For the 

headquarters consolidation, the total number of locations will be significantly reduced. However, the headquarters consolidation does not result in a reduction of 

space for the Agency’s current occupancy. This is partially due to staffing increases 

provided by FDA’s prior appropriations and industry funding of additional staff 

through user fees. Further, because the White Oak space is often replacing outdated 

facilities with leases that are from 15 to 20 years old, rents in the consolidated facilities exceed the rents that were paid for the outdated facilities. The White Oak 

consolidation does effect a savings when compared to replacing the FDA headquarters inventory through new leases acquired on an incremental basis as older 

building leases expire. Additionally, when consolidating to Government-owned space 

controlled by the GSA, there is typically a savings because GSA bills only the fair 

market value of space, with no administrative or overhead fees that would be added 

for a private-sector lease. 

WHITE OAK

Question. The budget includes an increase of $13.2 million for continued White 

Oak Consolidation. This will prepare the facility for 1,300 employees to move in during fiscal year 2009. Could you please speak to this increase and provide an update 

on White Oak. When do you expect everyone to be there? 

Answer. The budget increase of $13.2 million will make it possible for FDA to prepare Office Building 66 for the occupancy of approximately 1,300 staff from the Center for Devices and Radiological Health and support personnel from the Office of the 

Commissioner. The funding will enable FDA to provide furniture and furnishings 

for staff offices, support areas, and conference rooms; security system cabling and 

equipment; and IT and telecom equipment, cabling and services. There are five completed and occupied buildings at White Oak: Life Sciences I Laboratory; Office 

Buildings 21 and 22; Central Shared Use Building and the Engineering and Physics 

Laboratory which was just occupied in March 2007. Under construction are Office 

Building 51 scheduled to be complete in early 2008 and Office Building 66 scheduled 

to be complete spring 2009. Historic Building I and Office Buildings 31 and 32 are 

currently in design and construction completion is expected in November 2008 and 

November 2009, respectively. FDA plans to have everyone at White Oak in fiscal 

year 2013, depending upon funding included in the General Services Administration’s and FDA’s future appropriations. 

RESEARCH REDUCTION

Question. The budget includes a requested decrease in funding of nearly $4 million for outreach, coordination and research. Even more than that, I was surprised 

to read that part of that reduction was to come from the FDA Animal Drugs and 

Feeds program—including, and I quote from your budget, ‘‘research on prohibited 

materials in animal feed, research on microbiology of animal feed and feed commodities, and research on drug residues. In addition, the program will reduce Field activities supporting enforcement, investigations and compliance.’’ Canada very recently found a new BSE case. Please explain these proposed reductions. Have we 

really done all of the research necessary on animal feeds, and is it prudent to decrease enforcement and compliance activities? 

Answer. The Center for Veterinary Medicine, or CVM, completed development of 

a real-time Polymerase chain reaction, or PCR, based method. Once field validation 

of the real-time method is completed, the field has a necessary tool to support enforcement of the feed ban. Companies are not marketing new rapid test kits for detecting prohibited proteins in animal feeds; therefore, CVM does not have additional 

test kits to evaluate. 

The Office of Regulatory Affairs, ORA, intends to absorb the reduction of $593K 

in the Animal Drugs and Feeds Program by reducing both personnel and operating 

funds for coordination activities in either the ORA Office of Enforcement; ORA 

Headquarters; or Compliance Officers and Public Affairs Specialists located in the 

Region and District Offices. Operating fund reductions will be taken in travel, training and meetings with State or industry officials to perform outreach activities in 

support of the Field Animal Drugs and Feed Program. Management and coordination functions will continue by using electronic media/technology and realigning and 

consolidating coordination responsibilities to improve efficiencies. 

The research reduction allows CVM and ORA to fund the full cost of fiscal year 

2008 priority initiatives. 
689 

OFFICE OF WOMEN’S HEALTH

Question. Please provide a list of all research activities funded by the Office of 

Women’s Health in 2006 and 2007, including all recipients of the funds. 

Answer. I would be happy to provide that for the record. 

[The information follows:] 

Recipient Research Funding Fiscal Year 2006 Fiscal Year 2007 

IAG/NIH–ORWH ............................... Specialized Centers of Research on Sex and Gender 

Factors Affecting Women’s Health (SCOR)..

$100,000 $100,000 

CDER .............................................. Prevlence study of all drugs used in pregnancy’? ... 35,000 ........................

IAG/WHO&CFSAN ............................ Develop and evaluate an effective COMBI program 

on sanitation and personal hygiene practices.

152,000 ........................

CDER .............................................. The MATT Consortium (Molecular Assays & Targeted 

Therapies) within the OBQI (Oncology Biomarker 

Qualification Initiative) specifically for a project 

on lung cancer.

25,000 ........................

GNSI ............................................... Development of the Clinical Review Template ......... 100,065 ........................

CDER .............................................. Gender Differences & Impact of Pharmocogenomics 

in Rheumatoid Arthritis.

16,000 6,500 

CDER .............................................. Women in Clinical Trials and Gender Analysis of 

Data in New Molecular Entities (NME) approved 

2000–2002.

13,000 ........................

CDER .............................................. Impact of gender and pharmocogenomics on clinical efficacy, safety and pharmocokinetics of 

drugs used for treatement of alsheimer’s disease.

16,000 7,500 

CDRH .............................................. Evaluation of equality and availability of information on females included in mechanical circulatory support device trials.

32,900 ........................

CDER .............................................. Women in HIV Trials: A Comprehensive Review and 

Meta-Analysis.

9,500 9,000 

CFSAN ............................................ Modulating effects on estrogens on food allergens 

induced lung inflammation in a highly sensitive 

rat model for postmenopausal asthma.

33,000 ........................

NCTR .............................................. Molecular mechanisms underlying gender-associated differences in the adverse reactions to the 

anti-retroviral agent, zidovudine (AZT): role of 

mitochondria) toxicity.

93,800 87,000 

NCTR .............................................. Sex Differences in chemotherapeutic toxicity: 

profiling of transporter genes in humans.

110,100 88,000 

CDRH .............................................. Assessment of the accuracy of the Tropinin Assay 

in the Diagnosis of Myocardial Infarction by 

Gender and How Gender Influences Treatment.

30,000 ........................

NCTR .............................................. Protective effect of vaginal Lactobacillus species 

against Staphylococcus aureus-mediated toxic 

shock syndrome.

42,500 

CBER .............................................. HIV-SELECTEST: A novel assay for diagnosis of HIV 

infections in the presence of antibodies induced 

by candidate HIVE vaccines: Evaluation of gender bias in sensitivity and specificity.

135,000 38,000 

UN of Arizona ................................. University of Arizona: Dr. Marlene Freeman: PK/PD 

Sertraline in Pregnancy.

71,600 ........................

OC/OPPL ......................................... K.Morgan—Evaluation of How Best to Communicate to Heatlh Care Providers about the Risks.55,000 ........................

UN of Boston ................................. .................................................................................... ........................ 50,000 

UN of Wisconsin ............................ University of Wisconsin: Dr. Gloria Sarto—PK/PD of 

selected atibiotics during pregnancy.

32,900 ........................

CDER .............................................. Quantitative Tumor Size—Survival Relationship in 

Oncology Clinical Trials.

52,000 ........................

CDER .............................................. Statistical analyses of gender-specific data from 

New Drug Application (NDA) submissions.

11,300 ........................

CBER .............................................. Gender Dimorphism in HIV Infection in Primary 

Macrophages and T-Lymphocytes: Kinetics of.

16,200 ........................
690 

Recipient Research Funding Fiscal Year 2006 Fiscal Year 2007 

AHRQ .............................................. JAG with AHRQ: Research on the Effects of Drug 

Exposures in Pregnancy.

25,000 ........................

CDER .............................................. Cardiac safety, and specifically to build on ongoing activities re: the ECG Warehouse and the.50,000 ........................

CDER .............................................. Development of an HL 7 standard for the exchange 

of protocols, protocol summaries, and study.

50,000 ........................

UN of Wisconsin ............................ PK/PD of selected atibiotics dining pregnancy ........ 16,300 ........................

CDER/OTCOM ................................. Pregnancy Seminar: Pathways to Drug Development—A focus on Women’s Health.......................... 3,400 

Total ................................. .................................................................................... 1,384,165 339,400 

Question. Please explain the process by which OWH determines how to fund research activities. 

Answer. The FDA Office of Women’s Health, or OWH, determines research funding priorities by coordinating with other FDA and HHS activities around women’s 

health issues to leverage existing funds and target projects to meet Agency and Departmental priorities. OWH created a Women’s Health Advisory Council with numerous Agency representatives to help identify areas of highest priority with respect 

to women’s health and a better understanding of sex/gender differences. By participating with the HHS OWH, FDA OWH is able to identify cross cutting activities. 

The Office sends an announcement out to all Centers in the FDA announcing the 

availability of intramural funding for research projects aimed at protecting and improving women’s health. The announcement specifies the research focus for the fiscal year (e.g. sex related differences in safety or efficacy of FDA regulated products) 

and the application due dates. Research Proposals, called Concept Papers, are 

drawn up within individual Centers and go though an initial screening by the respective Center’s Women’s Health Coordinator to evaluate the proposal’s eligibility 

for context and institutional involvement. The Concept Papers are sent to OWH and 

to the Center Coordinators who independently rank the proposals based on the need 

and priority for women’s health issues in the respective Centers. After a thorough 

assessment of the proposals, selected investigators are asked to further expand their 

proposals and submit to OWH for evaluation and funding. OWH identifies panels 

of experts to perform an independent review of the expanded proposals rating specific criteria such as Research Question, Study Design, Feasibility, Relevance, Performance History, Investigator Qualifications, and Budget. Final decisions on funding are based on scientific reviews (Center Scientists, external experts and OWH 

Scientists) and available funds. 

Question. For fiscal year 2008, why are you proposing reducing the research funds 

of OWH? 

Answer. To be clear, research funds for women’s health activities are not reduced 

in our fiscal year 2008 budget request. Our budget proposes to transfer $350,000 

from the Office of Women’s Health, which is located within the Office of the Commissioner, to the National Center for Toxicologic Research, or NCTR. This transfer 

has been proposed to augment ongoing women’s health research within NCTR. In 

particular, NCTR research has focused on our ability to understand unique risks 

that women face when exposed to drugs, particularly on the risks to women’s cardiac health. This transfer should not, by any means, be interpreted as a reduction 

of FDA’s commitment to women’s health. This transfer represents an amplification 

of an existing research portfolio to examine pharmacological effects on women’s susceptibility to heart damage. It is not a diminishing of the Women’s Health Initiative. 

Question. The office was created in part because the Centers were not placing a 

priority on women’s health. What research will NCTR fund on women’s health? 

Answer. NCTR research will continue to focus on our ability to understand unique 

risks that women face when exposed to drugs, particularly the risk to women’s cardiac health. This transfer of research resources to NCTR will augment an alreadyrobust portfolio of toxicology research focused on examining a wide variety of healthrelated topics. 

Question. Why is it necessary to pull the funds from OWH if it is simply being 

transferred to NCTR, as opposed to letting OWH make the decision? 

Answer. As stated earlier, this transfer has been proposed because the National 

Center for Toxicological Research, or NCTR, is where we have been using those 

funds to do research in women’s health. The Office of Women’s Health, or OWH, 
691 

serves as a champion for women’s health both within and outside the agency. To 

achieve its goal, the OWH undertakes the following five activities: 

—ensures that FDA regulatory and oversight functions remain gender sensitive 

and responsive 

—works to correct any identified gender disparities in drug, device and biologics 

testing, and/or regulation policy 

—monitors progress of priority women’s health initiatives within FDA 

—promotes an integrative and interactive approach regarding women’s health 

issues across all the organizational components of the FDA 

—forms partnerships with government and non-government entities, including 

consumer groups, health advocates, professional organizations, and industry, to 

promote FDA’s women’s health objectives. 

I can assure this subcommittee that the proposed transfer of funds to NCTR, specifically for women’s health research, will not in any way diminish the ability of the 

OWH to achieve its goal. Specifically, the OWH will have full input as an equal 

partner with regards to women’s health research activities at NCTR. 

DIRECT TO CONSUMER ADVERTISING

Question. What is the current funding level of DDMAC? Please provide a breakdown of staff. 

Answer. The current funding level for the Division of Drug Marketing, Advertising, and Communications, or DDMAC, is $4,991,000. DDMAC consists of 44 FTE. 

There are nine people within the immediate office of the director, which includes 

the director, deputy director, associate director, program specialist, 3 policy and enforcement team members, one labeling specialist, and one information-technology 

specialist. In addition there are four professional review groups totaling 20 reviewers and two technical information assistants; two direct-to-consumer review groups 

with seven reviewers and two researchers, and 2 vacancies; and one training and 

support group consisting of one person on board and a vacancy. The staff breakdown 

represents all full-time and part-time onboard staff and the current vacancies. The 

funding level does not include full payroll expenditures for all positions listed above. 

Question. What percentage of DTC television advertisements are currently being 

reviewed? 

Answer. In 2006, the Division of Drug Marketing, Advertising, and Communications, or DDMAC, reviewed and provided advisory comments on 27 percent of television ads before they were publicly aired. 

Question. If the FDA’s proposed user fee for DTC advertisements is not enacted, 

what additional funding amount would be required for FDA to double the productivity of the office? What would a doubling of DDMAC allow FDA to accomplish? 

Answer. The Prescription Drug User Fee Act IV, or PDUFA IV, currently includes 

provisions for $6.25 million a year for the advisory review of DTC television ads. 

If we do not receive the $6.25 million a year as proposed in user fees, we would 

not be able to increase our productivity in the advisory review of direct-to-consumer, 

or DTC, television ads. With a doubling of the Division of Drug Marketing, Advertising, and Communications, or DDMAC, we estimate that we could cut our review 

time for these television ads nearly in half and review about two-thirds more of 

these materials than was possible in 2006. 

Question. A recent GAO report stated that DDMAC should stop using informal 

criteria when prioritizing material for review, and should develop and publish criteria for prioritization and review. Please provide a cost and time estimate for FDA 

to develop and formalize this process? 

Answer. FDA, like other regulatory agencies, exercises enforcement discretion in 

order to focus its resources on enforcement actions that would most impact public 

health. Although the Division of Drug Marketing, Advertising, and Communications, 

or DDMAC, does not document the criteria it uses to prioritize each direct-to-consumer, or DTC, piece received for review, DDMAC has identified criteria that are 

systematically applied to identify workload priorities for review of both draft and 

final DTC materials that have the greatest impact on public health. The DDMAC 

management team, and in particular the DTC group leaders, works with all the 

DTC reviewers to ensure consistent application. DDMAC exercises judgment in continually reevaluating its workload in light of these priorities, contingent on emerging scientific and regulatory events. The suggestion that each piece be reviewed 

under specified criteria, and that all reviews be documented, would require vastly 

increased staff to essentially review every piece in detail. What now happens is that 

experienced reviewers scan pieces for problems, recognizing our priorities, and 

choose the ones to pursue. We are currently evaluating this process to determine 

what, if any, changes are needed. 
692 

PROBIOTICS IN YOGURT

Question. Why does FDA require an IND when studying probiotics in food that 

is readily available on grocery shelves? Is this appropriate? 

Answer. The determining factor as to whether an investigational new drug application, or IND, is required for a probiotic product is the intended use to be studied. 

Under the Federal Food, Drug, and Cosmetic Act, or FD&C Act, if a probiotic product is intended to be used as a drug, it is regulated as a drug, and an IND would 

be required. The FD&C Act defines a drug as, among other things, an article intended for use in the diagnosis, cure, mitigation, treatment, or prevention of disease, 

as well as an article (other than food) intended to affect the structure or any function of the body. The Public Health Service Act definition of a biological product includes products containing microorganisms applicable to the prevention, treatment, 

or cure of disease or condition of human beings, and to which the FD&C Act applies. 

On the other hand, where a food, including a dietary supplement, is studied to 

determine its effect on the structure or function of the body, without reference to 

any effects on disease, an IND would not be required. 

Any clinical investigator or probiotic manufacturer interested in evaluating a 

probiotic product for the diagnosis, cure, mitigation, treatment, or prevention of a 

disease is encouraged to request a pre-IND meeting with FDA prior to submitting 

an IND. 

Question. Since this research would not require the use of a drug manufacturing 

ability, because the product is already on the shelves, how can a researcher secure 

an IND? 

Answer. The Investigational New Drug, or IND, regulations are provided in Title 

21 of the Code of Federal Regulations, Part 312. The FDA internet site provides 

many informational resources concerning how to submit an IND and how to conduct 

a clinical trial under IND. Also, the Center for Biologics Evaluation and Research’s 

Office of Communication, Training, and Manufacturer’s Assistance may be contacted 

directly at 301–827–1800 for assistance in the process. 

Question. Is there a way to allow for this research to move forward without requiring an IND that still provides the safety and assurance expected by the FDA 

from the public when conducting research? 

Answer. If a probiotic product is to be studied for use in the diagnosis, cure, mitigation, treatment, or prevention of disease, it needs to be evaluated under an Investigational New Drug, or IND. 

CARBON MONOXIDE

Question. In FDA’s March 2007 fresh fruit and vegetable guidance, FDA states 

that the use of low oxygen Modified Atmosphere Packaging (MAP) systems for perishable foods can promote the growth of spoilage organisms and pathogens that may 

be present. In light of this publication, and since MAP systems are also being used 

in fresh meat products, does FDA anticipate withdrawing its acceptance of the 

GRAS notifications that have been submitted to the agency regarding the use of carbon monoxide in fresh meat? 

Answer. FDA is currently evaluating a pending citizen petition which requests 

that the agency withdraw its response letters to the ‘‘generally recognized as safe’’ 

notifications regarding the use of carbon monoxide in fresh meat. While our review 

of that petition is ongoing, we cannot comment on whether we anticipate withdrawing the response letters. 

Question. Please provide a status on FDA’s response to a citizen petition filed on 

November 15, 2005 (Docket No. 2005P–0459) regarding carbon monoxide in fresh 

meat? Please provide a date by which this citizen petition will receive a response? 

Answer. On November 15, 2005, FDA opened a docket on a citizen’s petition submitted by Kalsec, Inc. In their petition, Kalsec requests that FDA rescind the acceptance of a number of ‘‘generally recognized as safe’’ notices related to the notifiers’ determinations that carbon monoxide (CO) is ‘‘generally recognized as safe’’ 

under specific conditions of use as a component in Modified Atmosphere Packaging 

systems (MAPs) used in fresh meat. FDA has received and continues to receive numerous submissions commenting on the Kalsec petition. We are evaluating the petition and place a high priority on preparing a timely response. However, due to other 

priorities and the ongoing review of the submissions commenting on the petition, 

FDA does not have a specific date when it will complete its review of the citizen’s 

petition submitted by Kalsec, Inc. 
693 

OFFICE OF THE COMMISSIONER

Question. Do contractors and consultants report to the Commissioner or Chief of 

Staff? If so, what are their roles? Could these functions be done by existing permanent staff? If so, why are these individuals hired as consultants rather than as Federal employees? 

Answer. There is one contractor who reports to the Commissioner. The contactor’s 

role is to provide professional services in executive leadership development for all 

of the senior FDA leadership within the Office of the Commissioner and the Centers. Specific tasks include strengthening executive leadership, enhancing crossagency integration, improving communication, mentoring and developing staff. 

These functions could not be performed by existing staff as the existing staff does 

not possess the breadth of knowledge and level of expertise as the contractor in the 

areas of executive development, coaching and organizational culture. 

There is one contractor who reports to the Chief of Staff. This contractor has an 

extensive background in media and strategic communications and a thorough understanding of how outside organizations perceive critical FDA policies and initiatives. 

This outside perspective cannot be provided by existing permanent staff. 

Question. Does the Office of the Commissioner have sufficient funds to pay for all 

of these staff with payroll dollars? Is there a ‘‘payroll deficit’’ for the Office of the 

Commissioner? 

Answer. Yes, the Office of the Commissioner, or OC, has sufficient funding for approved staffing. In fiscal year 2007, OC does not have a ‘‘payroll deficit’’. 

OFFICE OF COSMETICS AND COLORS

Question. What is the proposed fiscal year 2008 budget for the FDA Office of Cosmetics and Colors (OCAC) within the Center for Food Safety and Applied Nutrition 

(CFSAN) and the proposed number of FTE positions? How does this compare with 

fiscal year 2006 and fiscal year 2007? 

Answer. The Center for Food Safety and Applied Nutrition (CFSAN) estimates 

that its appropriated fiscal year 2008 budget for the Office of Cosmetics and Colors 

(OCAC) will support 13 full time equivalent (FTE) positions and provide $2.0 million 

for the cosmetics activities conducted by OCAC. Additionally, the non-appropriated 

Color Certification Program within OCAC will support 32 FTE positions with a 

budget of $7.568 million in fiscal year 2008. 

By comparison, in fiscal year 2006, the Agency’s Cosmetics program was staffed at 30 FTEs with a budget of $3.2 million which included staff in OCAC (not including the color certification program). In fiscal year 2007, all compliance and research 

components that were in individual program offices within CFSAN, including those 

in OCAC, were realigned to the Office of Compliance or the Office of Regulatory 

Science to concentrate these similar activities. Other FTEs within the Cosmetics 

Program left the Agency for various reasons, including retirement and buyouts. As 

a result, the estimated fiscal year 2007 budget for cosmetic activities conducted by 

OCAC is 13 FTEs/$1.825 million. 

Question. Is CFSAN planning to change the size or organizational structure of 

OCAC, and if so, what is the new organizational plan and how would OCAC be 

structured within CFSAN? 

Answer. In February 2007, as part of CFSAN’s proposed reorganization, CFSAN 

changed the size and organizational structure of OCAC. In fiscal year 2006, the entire cosmetics program was located in the Division of Cosmetics and Compliance. In 

fiscal year 2007, compliance and research components that were in individual program offices within CFSAN, including those in OCAC, were realigned to the Office 

of Compliance and to the Office of Regulatory Science to concentrate staff in offices 

with a particular focus. As a result, there was a significant reduction in personnel 

within OCAC. 

Question. The size of the personal care products industry is $60 billion, with over 

11 billion products sold annually, and with over 2,500 facilities in the United States. 

In the last 25 years there has been a vast expansion of personal care products. However, the number of FTEs in the OCAC has decreased dramatically during this same 

timeframe. Does FDA believe that there will be a sufficient number of FTEs in the 

Office of Cosmetics and Colors enough to regulate this industry and insure the safety of these consumer products? 

Answer. Thus far, FDA has been able to keep pace with developments, averting 

any serious or widespread public health problems. While it is difficult to predict, 

precisely, what the future will bring, there are several areas that loom large for cosmetic safety. Key examples include the safe use of nanotechnology in cosmetics; a 

need for more scientific information to ensure the safe use of tattoos, which has 

greatly expanded over a wider segment of the population than formerly; and the in-
694 

creasingly global nature of the industry with a corresponding need for FDA engagement in the development of international safety standards. 

PSEUDOEPHEDRINE

Question. The Senate and House Appropriations Committee Report on the fiscal 

year 2007 FDA Appropriations Bill included language regarding ‘‘Expedited Filing’’. 

In the context of this Appropriations provision, and in light of the initiatives undertaken by FDA following enactment of the Combat Meth Act, would you please outline the steps that the Agency has taken to enhance access to new prescription combinations of safe and effective marketed drugs that could provide alternative therapies to replace pseudoephedrine-containing products and thereby address the major 

public health and safety concerns arising from meth production? 

Answer. The Office of Non-Prescription Products, or ONP, is interacting with 

manufacturers to help them interpret the Combat Meth Act provisions regarding reformulation of both New Drug Applications, or NDA, and over-the-counter, or OTC, 

monograph products. Products that require NDA or a supplement to an NDA, or 

sNDA, may qualify for a priority review. We are willing to meet with applicants to 

determine if such applications qualify to be considered under priority review. We 

interact with such applicants to ensure that only essential testing is required to 

demonstrate that the reformulations will be safe and effective. For instance, clinical 

trials are not required in any instance in which a demonstration of bioequivalence 

in humans can be appropriately applied. This may help shorten the time necessary 

to provide data for the NDA or sNDA. We also respond to submissions and meeting 

requests quickly so that access is not delayed based upon the ability of a company 

to get feedback or to interact with the Agency. If applications do not qualify for priority review, they are reviewed under the specific timelines and procedures associated with the Prescription Drug User Fee Act, or PDUFA, and other pertinent regulations. 

OTC products that are marketed under the OTC Drug Review may be reformulated following the stipulations for active ingredients, manufacturing, and labeling 

that are set out in the regulations associated with the OTC monographs. These reformulations do not require approval by the FDA prior to marketing. For example, 

an immediate release tablet containing pseudoephedrine as a decongestant in combination with an antihistamine could be reformulated under the monograph to contain an alternative decongestant phenylephrine, in combination with the same antihistamine. This reformulation does not require preapproval, supporting a rapid 

transition from products containing pseudoephrine to products using other antihistamines. In addition, a new salt of phenylephrine was recently added to the monograph to allow manufacturers more flexibility in formulating products. 

COLOR CERTIFICATION FEES

Question. What is the anticipated balance that will remain in the Color Certification Fund at the end of fiscal year 2007? 

Answer. The anticipated balance that will remain in the Color Certification Fund at the end of fiscal year 2007 is $1,410,134. 

Question. What are the anticipated revenues to this fund in fiscal year 2008? Answer. The anticipated revenues to this fund in fiscal year 2008 are $7,000,000. 

Question. Please provide a list of all anticipated expenses for this program in fiscal year 2008? 

Answer. The following is a list of anticipated expenses for the Color Certification 

Program in fiscal year 2008: 

Operating Expenses:$3,309,740 (Funds the day to day operations of the Color Certification program including equipment purchases, supplies, travel, contracts and 

rent and rent related costs) 

Payroll Expenses: $4,258,384 (Funds the salaries and benefits of Color Certification employees) 

QUESTIONS SUBMITTED BY SENATOR TOM HARKIN

ADVERSE EVENT REPORTING ON DIETARY SUPPLEMENTS

Question. The Dietary Supplement and Nonprescription Drug Consumer Protection Act require manufacturers and distributors of dietary supplements and OTC 

drugs to report all serious adverse events to the FDA. The legislation requires the 

FDA to issue guidance by September 18, 2007 on the minimum data elements that 

should be included in a serious adverse event report. 

Has the FDA begun that process? 
695 

Answer. Yes, FDA has begun work on the guidance required by the new law. Before issuing final guidance, the agency intends to publish draft guidance describing 

in detail the minimum data elements that should be included in a serious adverse 

event report for both dietary supplements and OTC drugs, using the current FDA 

3500A MedWatch form for mandatory reporting. 

Question. Will the FDA be issuing a proposed guidance to solicit comment from 

stakeholders? 

Answer. Yes. In accordance with the agency’s good guidance practice regulations, 

FDA will announce the availability of the draft guidance in the Federal Register and 

invite comment on the guidance from interested parties. 

The Dietary Supplement and Nonprescription Drug Consumer Protection Act supersedes the Center for Food Safety and Nutrition’s (CFSAN’s) Adverse Event Reporting System, or ‘‘CAERS’’, which allows voluntary reporting of dietary supplement adverse events. 

Question. Since the legislation requires manufacturers and distributors to report 

serious adverse events, does FDA expect to use more resources to process Adverse 

Event Reports? 

Answer. Yes, the FDA expects to use more resources to process significant adverse 

event reports (AERs) which are submitted in response to this law. 

With respect to resources for Public Law 109–462, no funding for implementation 

was provided in the fiscal year 2007 appropriation and no funding was requested 

in the President’s fiscal year 2008 budget. 

Currently the agency has been performing tasks that will contribute to the full 

implementation of the new law. For example, FDA performed a gap analysis between the FDA3500A MedWatch form and the capabilities of the current CFSAN 

Adverse Events Reporting System (CAERS). This analysis shows that CAERS needs 

software modifications to receive fields on the 3500A MedWatch form. 

In addition, the agency is planning the additional work activities needed to fully 

implement the law. These work activities will include developing several business 

processes, making significant Information Technology (IT) improvements to CAERS, 

and modifying contracts providing records management and IT support. To accommodate the increased numbers of significant AERs expected to result from mandatory reporting, CFSAN plans to modify CAERS to accept AERs electronically via the 

MedWatch Plus initiative, which will include modifications to accommodate dietary 

supplements. 

CFSAN already has processes in place to consolidate duplicate AERs and new 

medical information on existing AERs so that all information about a given adverse 

event appears in a single report, as required by the new law. 

The Administration has proposed only $4 million above last year’s enacted level 

for CFSAN. This funding is directed to increases in food safety programs generally, 

not the CAERS system or a revised version of it. 

Question. What additional resources will FDA require for fiscal year 2008 to prepare for the full implementation of the Act? 

Answer. No funding for implementation was provided in the fiscal year 2007 appropriation and no funding was requested in the President’s fiscal year 2008 budget. 

GOOD MANUFACTURING PRACTICES OF DIETARY SUPPLEMENTS

Question. It has been over 12 years after the enactment of Dietary Supplement 

Health and Education Act and the FDA has yet to finalize the Good Manufacturing 

Practice (GMP) regulations authorized by the 1994 law. The Senate Health, Education, Labor and Pensions Committee Report that accompanied The Dietary Supplement and Nonprescription Drug Consumer Protection Act encouraged the FDA 

to act quickly to finalize a GMP regulation for supplements. The Committee also 

noted that FDA has taken action against products that arguably could not have 

been sold in the first place if strong GMPs had been promulgated. 

What date will GMP regulations be issued? 

Answer. FDA is committed to publishing this final rule. I can assure you that 

there has been significant work done on the final rule since the comment period for 

the proposed rule ended in August 2003. The Administration is currently reviewing 

the final rule. 

We have worked extremely hard to draft the final rule in such a way that would 

assure quality products for the consumer while balancing societal costs and benefits. 

I can assure you that full attention is being given to the completion of the rule as 

soon as possible. 
696 

FOOD SAFETY INSPECTIONS

Question. Between 2003 and 2006, FDA food safety inspections have dropped by 

47 percent as reported last month by the Associated Press. Will an increase of just $10 million increase the number of food safety inspections 

for products regulated by FDA? 

Answer. The number of domestic food inspections used to calculate the 47 percent 

decrease in inspections since 2003 (from 7,218 in 2003 to 3,833 in 2006) represents 

only a subset of total domestic food inspections. This subset does not include such 

high risk areas as Seafood HACCP inspections; Juice HACCP inspections; Cheese 

inspections; Low Acid Canned Foods; and, Acidified Food inspections. When ALL domestic food inspections are included, the reduction in inspections between 2003 and 

2006 is 19 percent. 

In addition, the decreases quoted are for FDA inspections only and do not recognize FDA leveraging with States to conduct contract/grant and partnership inspections. For instance, in fiscal year 2006 the States performed 8,566 food inspections 

for FDA which is an increase from 8,390 conducted by the States in fiscal year 2003. 

The $5.5 million that the Office of Regulatory, or ORA, requested as part of the 

Strengthening Food Safety Initiative in the fiscal year 2008 President’s Budget request will not result in an increased number of food safety inspections. Funding will 

be used to enhance ORA’s ability to more rapidly trace back foodborne disease outbreaks and to work proactively to encourage growers and processors to implement 

good agricultural practices and other interventions designed to prevent contamination of food. ORA will develop, train, and equip teams to work with State partners 

in large produce-growing regions. Funding will also be used to accelerate development of an import decision-making IT system capable of detecting high-risk food 

shipments before they enter U.S. commerce. While FDA already has systems that 

are used to identify and target certain high-risk import shipments the new system 

will increase current capabilities by providing for automated review and trending 

of the results of field examinations and analyses of samples, identifying candidates 

for detention without physical examination; it will score each entry line on the basis 

of risk factors and surveillance requirements, for an automated, real-time decision 

on action to be taken; and, it will incorporate exogenous data with available FDA 

operational data to create a broader picture for each shipment. 

The $4.0 million and 16 FTEs that the Center for Food Safety and Applied Nutrition, or CFSAN, requested in the fiscal year 2008 President’s Budget request will 

be used to improve its Food Safety program particularly focused on produce safety. 

CFSAN plans to utilize the fiscal year 2008 funds for resources to support four core 

critical functional areas of the FDA Food Safety Program: (1) methods development 

to detect and attribute foodborne illness outbreaks related to fresh produce, (2) expand traceback capabilities by hiring environmental epidemiologists to work with 

FDA and State and local agencies and facilitate on-farm investigations, (3) development of cost-effective regulations and/or guidance, and (4) obtain additional expertise in the production and processing of fresh produce. 

The National Center for Toxicological Research, or NCTR, will direct $165,000 to 

provide additional staff and $335,000 for supplies and services to improve methods 

for rapid screening and complete identification of foodborne pathogens. NCTR will 

also develop a genomic database to identify and assess the biological threat of 

foodborne pathogens. The total cost is $500,000. 

Also included is $644,000 for FDA’s Office of Crisis Management, or OCM, to enhance FDA’s ability to help industry mitigate the risks of foodborne outbreaks. 

Question. What will be the number of inspections as compared to fiscal year 2006 

and fiscal year 2007? 

Answer. The Office of Regulatory Affairs, or ORA, currently estimates it will perform 19,212 food inspections, including inspections performed by the States for FDA 

under State contracts and partnerships in fiscal year 2008. This represents a slight 

increase over the fiscal year 2007 estimate of 19,137 food inspections. In fiscal year 

2006, FDA and the States performed 17,730 food inspections. 

Question. Is $10 million enough money to ensure public safety? 

Answer. Ensuring the safety of the food supply is a top priority for FDA and the 

Administration and we will continue to strive to reduce the incidence of foodborne 

illness, and the associated impact of public health to the lowest level possible. 

The $5.5 million that the Office of Regulatory Affairs, or ORA, requested as part 

of the Strengthening Food Safety Initiative in the fiscal year 2008 President’s Budget request will be used to enhance ORA’s ability to more rapidly trace back 

foodborne disease outbreaks and to perform on farm investigations. Once the outbreak and food involved has been identified, the ability to deploy rapid response 

teams trained in outbreak response and traceback procedures will prevent addi-
697 

tional exposure of consumers to contaminated produce and reduce the number of illnesses by more quickly identifying implicated shipments and removing them from 

the market. In addition, the development of these teams enhances FDA’s ability to 

perform on farm and at processor investigations and thereby help prevent future 

outbreaks. Funding will also be used to accelerate development of an import decision-making IT system capable of detecting high-risk shipments before they enter 

U.S. commerce which will improve ORA’s ability to intercept contaminated products 

at the border and before they enter U.S. commerce. While FDA already has systems 

that are used to identify and target certain high-risk import shipments. the new 

system will increase current capabilities by providing for automated review and 

trending of the results of field examinations and analyses of samples, identifying 

candidates for detention without physical examination; it will score each entry line 

on the basis of risk factors and surveillance requirements, for an automated, realtime decision on action to be taken; and, it will incorporate exogenous data with 

available FDA operational data to create a broader picture for each shipment. 

The $4.0 million and 16 FTEs that the Center for Food Safety and Applied Nutrition or CFSAN, requested in the fiscal year 2008 President’s Budget request will 

be used to improve its Food Safety program particularly focused on produce safety. 

In a continued commitment to improve the safety of the U.S. food supply, FDA is 

taking action to prevent or reduce foodborne outbreaks and the number of illnesses 

and deaths due to consumption of contaminated food, bolstering public confidence 

in the safety of fresh produce, the consumption of which the U.S. Government has 

been encouraging as part of a healthful diet, and encouraging the States and industry to respond to new information on potential food contamination. 

The National Center for Toxicological Research, or NCTR, will direct $165,000 to 

provide additional staff and $335,000 for supplies and services to improve methods 

for rapid screening and complete identification of foodborne pathogens. NCTR will 

also develop a genomic database to identify and assess the biological threat of 

foodborne pathogens. The total cost is $500,000. 

Also included is $644,000 for FDA’s Office of Crisis Management, or OCM, to enhance FDA’s ability to help industry mitigate the risks of foodborne outbreaks. 

Since September of last year, there have been multiple large-scale outbreaks of 

foodborne illness in the United States. Press reports suggest the reason for the recent outbreak of foodborne illness is FDA’s lack of resources in the area of food safety. The President’s fiscal year 2008 budget calls for an increase of $10.6 million for 

food safety at FDA. 

Question. What changes will FDA make with this money to ensure future outbreaks of foodborne illness are prevented? 

Answer. The fiscal year 2008 budget requests funds for food safety improvements 

in the Center for Food Safety and Applied Nutrition, or CFSAN ($4 million), the 

Office of Regulatory Affairs, or ORA ($5.5 million), the National Center for Toxicological Research, or NCTR ($500,000) and the Office of Crisis Management, or 

OCM ($644,000). 

CFSAN expects to utilize the fiscal year 2008 increase for resources to support 

four core functional areas of the FDA Foods Program: 

—Methods Development ($1 million).—Funds will develop better methods to detect 

and attribute foodborne illness outbreaks related to produce and allow for 

quicker intervention to reduce the illnesses and deaths from contaminated food 

and quicker resumption of marketing of uncontaminated food. 

—Surveillance ($1 million).—Funds will increase sampling and traceback capabilities, including conducting produce sampling surveys of imported and domestic 

produce to examine pathogens along the distribution chain to establish a baseline. 

—Regulations and Guidance ($1 million).—Funds will help develop cost-effective 

regulations and/or guidance to prevent and reduce outbreaks, thus reducing the 

instance of illness and death. 

—Produce Experts ($1 million).—Funds will obtain additional expertise in the production and processing of fresh produce, with emphasis on microbiological safety 

issues. 

Also included is $644,000 for FDA’s Office of Crisis Management, or OCM, to enhance FDA’s ability to help industry mitigate the risks of increased foodborne outbreaks. 

The National Center for Toxicological Research, or NCTR, will direct $165,000 to 

provide additional staff and $335,000 for supplies and services to improve methods 

for rapid screening and complete identification of foodborne pathogens. NCTR will 

also develop a genomic database to identify and assess the biological threat of 

foodborne pathogens. 
698 

The Office of Regulatory Affairs, or ORA, plans to allocate $3.5 million to develop 

the capacity for more rapid traceback of produce-related outbreaks and the capacity 

to determine the root cause of an outbreak. ORA will develop teams trained in 

traceback technologies, incident command, and root cause analysis. These teams will 

be strategically positioned in areas with large produce-growing regions. In addition, 

ORA will provide training, equipment, and other assistance to States so that they 

can be full partners with FDA in responding to and preventing produce-related outbreaks. After the first year, ORA will have 12 fully equipped and trained FTEs with 

traceback equipment. 

ORA also plans to allocate $2 million towards developing an import decision-making system capable of detecting high risk shipments of FDA-regulated products before they are admitted or released into U.S. commerce. While FDA already has systems that are used to identify and target certain high-risk import shipments the 

new system will increase current capabilities by providing for automated review and 

trending of the results of field examinations and analyses of samples, identifying 

candidates for detention without physical examination; it will score each entry line 

on the basis of risk factors and surveillance requirements, for an automated, realtime decision on action to be taken; and, it will incorporate exogenous data with 

available FDA operational data to create a broader picture for each shipment. 

From what I can see, the FDA needs a far greater investment in food safety in 

order to effect real improvements in actual practice. 

Question. If given more than $10 million for food safety, which programs would 

benefit most from additional money to increase the safety of our food supply, especially in fresh produce? 

Answer. FDA is committed to ensuring that America’s food supply continues to 

be among the safest in the world, but we face challenges. For example, consumption 

of produce, particularly ‘‘ready-to-eat’’ products, has increased dramatically during 

the past decade. Americans usually consume these products in their raw state, harvested from the vine, stem, or soil without processing to reduce or eliminate pathogens that may be present. Consequently, the manner in which these products are 

grown, harvested, packed, processed, and distributed is crucial to ensuring that microbial contamination is minimized, thereby reducing the risk of illness to consumers. Even if a small percentage of what is harvested is contaminated, it can result in severe illness. FDA is taking a ‘‘farm-to-fork’’ systematic risk management 

approach to food safety to reduce the risk of food illness at all points in the food 

chain. 

For fiscal year 2008, we propose a $10.644 million increase for a food safety initiative focused on fresh produce. FDA will develop methods to prevent food outbreaks 

from occurring by rapidly detecting contamination that leads to illness, more quickly 

tracking contamination to its source, and more effectively conducting root cause 

analysis of the contamination. We will also provide training to our State and local 

partners and develop a geographic information mapping system for faster emergency response. Finally, we will develop a decision-making system to detect highrisk imports before they enter U.S. commerce, so they can be evaluated by FDA. 

Due to the increased consumption of fresh produce and the current outbreaks of 

contamination, FDA would allocate additional funding for specific areas where we 

could expand the food safety program in order to promote and improve the public 

health. FDA has identified the following five critical areas as targets for future 

growth: 

—preventing contamination and produce safety research 

—preventing outbreaks and mitigating outbreak impact 

—monitoring antibiotic usage and antibiotic resistance in bacteria from farmraised aquatic animals and their environments 

—developing efficient techniques for identifying foodborne pathogens that cause 

outbreaks 

—providing additional field support for the Foods and Animal Drugs and Feed 

Programs. 

SALT

Question. In 1979, the Federation of American Societies for Experimental Biology 

submitted a final report to FDA, Evaluation of the Health Aspects of Sodium Chloride and Potassium Chloride as Food Ingredients. This report reviewed the adverse 

biological effects of dietary sodium and concluded that these effects might be harmful to the health of a significant proportion of the public. It further concluded that 

‘‘it is the prevalent judgment of the scientific community that the consumption of 

sodium chloride in the aggregate should be lowered in the United States.’’ 
699 

1 Center for Science in the Public Interest v. Novitch, Food, Drug, and Cosm. L. Rep. (CCH)¶ 

38,275 (D.D.C. June 11, 1984) 

Since that time, additional studies have demonstrated with much greater certainty that diets high in sodium promote high blood pressure. In 2003, the National 

Heart, Lung and Blood Institute’s high blood pressure committee called for a 50- 

percent reduction in sodium in processed and restaurant foods over the next 10 

years, or 5 percentage points a year for 10 years. In a January 2004 commentary 

in the American Journal of Public Health, the director of the National Heart, Lung 

and Blood Institute (NHLBI) and two colleagues estimated that halving sodium levels in packaged and restaurant foods would save 150,000 lives a year in the United 

States. 

In the early 1980s, likely based in part on the 1979 FASEB report, FDA agreed 

that a reduction in the consumption of salt would be beneficial, and it initiated a 

modest campaign of public education and expanded labeling provisions to encourage 

consumers and food manufacturers to use less salt. Around that time, FDA also rejected calls to revisit the GRAS status of salt. However, in 1984, a Federal district 

court ordered FDA to reconsider the GRAS status of salt if voluntary measures did 

not succeed in reducing salt intake. 

Per the instructions of the Federal district court in 1984, has FDA taken steps 

to reconsider the GRAS status of salt? 

Answer. In response to a 1979 review on salt by the Select Committee on GRAS 

Substances (SCOGS) of the Federation of American Societies for Experimental Biology, and concern about the health effects of salt in the U.S. diet, FDA reviewed the 

regulatory status of salt and issued Federal Register (FR) publications discussing 

salt’s status in a 1982 notice (47 FR 26580; June 18, 1982) and a 1984 final rule 

(49 FR 15510; April 18, 1984). In these documents, FDA outlines its voluntary review of salt and the decision not to alter salt’s status as a GRAS ingredient. 

The question references the ‘‘instructions of the Federal district court in 1984.’’ 

These instructions were contained in a court ruling 1 that granted summary judgment to FDA in response to a suit filed by Center for Science in the Public Interest 

(CSPI) seeking the court’s review of FDA’s denial of the CSPI citizen petition to reclassify salt as a food additive. The cited ‘‘instructions’’ were non-binding instructions for FDA to make a decision on the GRAS status of salt after it had completed 

its review of the effectiveness of several FDA initiatives for salt. FDA had concurrently completed a voluntary review of salt and subsequently opted not to alter its 

regulatory status. The conclusions of FDA’s review that are the basis of our decision 

are documented in the 1982 and 1984 FR documents. 

Question. If so, what is the result of those deliberations? If not, why has FDA not 

done so? 

Answer. The results of those deliberations in the early 1980s regarding the GRAS 

status of salt ultimately led to a decision not to alter GRAS status (47 FR 26580, 

June 18, 1982; 49 FR 15510, April 18, 1984). FDA opted instead to pursue a consumer information-based approach where declarations of the salt (listed on the food 

label as the sodium ion) content of foods would encourage individuals to control 

their own salt intake as well as encourage food manufacturers to limit the salt content of their products. FDA explained in the 1982 FR notice its rationale for choosing this approach. FDA cited several legal and regulatory issues that confounded the 

regulation of salt as a food additive. These legal and regulatory issues include the 

complexity of determining limitations of salt in foods and the complexity of the diet 

in general (i.e., changing the salt content of a particular food or foods may not impact a person’s total intake of salt). Furthermore, ‘‘prior sanctions’’—sanctions or approvals of a use of a food ingredient that were granted by either FDA or the U.S. 

Department of Agriculture before the Food Additives Amendment to the FFDCA 

was enacted in 1958—exist for uses of salt; revocation of prior sanctions presents 

further complications. 

Question. What resources does FDA currently devote, both budget resources and 

FTSs, to sodium and sodium reduction? 

Answer. Unfortunately, the Agency’s financial system does not track programmatic resources to this level of detail. 

Question. What would the FDA do, if it had increased resources, to lower sodium 

levels in processed and restaurant foods? 

Answer. Food label education remains a key priority for FDA. In 2006, FDA released a web-based program, ‘‘Make Your Calories Count,’’ to assist consumers understand and use the food label to help manage their calorie and nutrient intake. 

Sodium is one of the nutrients featured on the program. 

Additionally, in 2005 FDA amended its regulations concerning the maximum sodium levels permitted for foods that bear the implied nutrient content claim 
700 

‘‘healthy.’’ In this rule the agency retained sodium levels of 480 mg or less for all 

food categories, including individual foods, and 600 mg or less for meals and main 

dishes. Most of the comments from industry suggested that it was difficult to make 

certain products, particularly soups, which would be both palatable and marketable 

at lower levels. Many consumer groups, including Center for Science in the Public 

Interest (CSPI), supported this decision. The agency had concluded that going to 

more restrictive sodium levels could result in the substantial elimination of meal 

and main dish products bearing the claim ‘‘healthy’’ from the marketplace and that 

the proposed sodium levels would help consumers achieve a total diet that would 

be consistent with dietary recommendations. 

Moreover, the fiscal year 2006 CFSAN Program Priorities include publishing an 

advance notice of proposed rulemaking (ANPRM) to solicit comments on updating 

daily values in nutrition labeling. All nutrients, including sodium, will be taken into 

consideration as part of the development of the ANPRM. We will be encouraging 

comments on this ANPRM from a broad range of stakeholders. 

The FDA is currently preparing for a public hearing to discuss issues related to 

FDA’s regulation of salt. As part of this hearing, FDA will invite comment on the 

effectiveness of current measures and discuss potential initiatives aimed at reducing 

salt intake in the United States. Additional resources might be used to further any 

of the FDA efforts related to reducing sodium levels identified above. 

TRANS FAT

Question. The FDA considers partially hydrogenated oil, with its trans fat, to be 

‘‘generally recognized as safe,’’ even though the agency’s own evaluations indicate 

that the ingredient is causing thousands of premature deaths and significant economic costs each year. 

Is there any reason that the FDA should not seek to eliminate trans fat, other 

than naturally occurring trans fat, from the food supply? 

Answer. FDA is currently evaluating this issue in its review of a citizen petition 

from the Center for Science in the Public Interest (CSPI), requesting that FDA revoke the ‘‘generally recognized as safe’’ status of trans fat. In response to this petition, we have received comments from industry that show that revoking the ‘‘generally recognized as safe’’ status of trans fat is a complex issue. 

We note that when FDA affirmed partially hydrogenated oils as ‘‘generally recognized as safe,’’ the data on trans fats were very limited. Since then, additional research has shown that some trans fats are unhealthful. Research in this area is ongoing to determine the identity, levels, safety and other variables of trans fats in 

food. 

We are considering all options to address concerns regarding trans fat in foods, 

including those raised in the citizen petition currently under review. For example, 

one approach we have already taken is to give consumers the information they need 

to make healthier food choices and provide industry with an incentive to produce 

healthier foods. Due in part to FDA’s trans fat labeling regulation that went into 

effect in January 2006, and FDA’s education and outreach efforts, there has been 

an increase in consumer demand for trans fat-free products. Therefore, these activities are having a positive effect on reducing trans fat intake. 

Question. What steps is the FDA taking to reduce or eliminate trans fat in the 

food supply? 

Answer. The level of trans fatty acids in the diet affects risk of coronary heart 

disease. To assist consumers in choosing foods with lower amounts of trans fat, the 

FDA issued a final rule in 2003 (68 FR 41434, July 11, 2003) that requires the 

amount of trans fat to be declared on the Nutrition Facts panel directly below the 

saturated fat line. This rule became effective January 1, 2006, for all food under the 

jurisdiction of FDA. 

Americans face a plethora of food choices in grocery stores and at restaurants. 

Our responsibility is to empower consumers to make informed decisions about their 

food selections and to encourage them to make changes in their diets for better 

health. The Nutrition Facts panel, along with other education campaigns, provides 

invaluable information to the consumer. At the same time, FDA’s public health mission is to foster the development of healthier food products for American consumers. 

The requirement to declare trans fat on product labeling is changing consumer demand and prompting reformulation, which was anticipated by FDA. FDA is monitoring industry progress in developing and using alternative ingredients and processing techniques for reducing trans fat. 

At the same time that the final rule published, FDA issued an advance notice of 

proposed rulemaking (ANPRM) (68 FR 41507; July 11, 2003) to request comment 

on establishing trans fat nutrient content claims, disqualifying/disclosure levels, and 
701 

a possible footnote about cholesterol raising lipids to help consumers make heart 

healthy food choices. 

FDA is currently reviewing a citizen petition from the Center for Science in the 

Public Interest requesting FDA to revoke the ‘‘generally recognized as safe’’ status 

of partially hydrogenated vegetable oils (see Docket No. 2004P–0236). 

Question. Does the FDA plan to reconsider the GRAS status of partially hydrogenated vegetable oil given that it contains trans fat? 

Answer. FDA is currently evaluating this issue in the review of a citizen petition 

from the Center for Science in the Public Interest, requesting that FDA revoke the 

GRAS status of trans fats. 

Question. If so, what is the result of those deliberations? If not, why has FDA not 

done so? 

Answer. There is no change in the conclusion made in the trans fat labeling regulation that trans fat represents a health concern. The trans fat information provided 

on food labels will enable consumers to make healthier food choices. As part of our 

ongoing review of the citizen petition from the Center for Science in the Public Interest, requesting that FDA revoke the GRAS status of trans fats, we are considering all available options to address concerns regarding consumption of trans fat. 

FDA plans to monitor the effect of the trans fat labeling regulation on consumer 

behavior and industry practices to help determine what, if any, additional action 

should be taken. 

QUESTIONS SUBMITTED BY SENATOR BYRON L. DORGAN

DIRECT-TO-CONSUMER ADVERTISING

Question. The United States is one of only two nations that allow DTC advertising. The other is New Zealand. The amount of money spent on DTC ads has increased by 20 percent per year since 1997. In 2005, drug companies spent $4.2 billion on DTC ads. 

I think we have to take a hard look at whether these ads have value to consumers. I have seen some ads that don’t even mention what the product does. I remember an ad for Levitra—an erectile dysfunction drug—that showed a man trying 

to throw a football through a tire swing. He had no luck until the word Levitra 

flashed on the screen. In the next scene, the man is being embraced by a woman. 

Do you believe this type of ad is beneficial to consumers? Should pharmaceutical 

companies be required to clearly state what the product is for in addition to listing 

the risks and benefits associated with the product? 

Answer. FDA believes consumer-directed advertisements can play an important 

role in advancing the public health. There are a number of serious medical conditions that are undertreated in the United States. Conditions such as diabetes, depression, hyperlipidemia, and hypertension, left untreated, can have devastating effects in patients. We believe the public health is benefited when consumer-directed 

promotion provides information that encourages patients to speak with their doctors 

and get their serious medical conditions treated. The benefit depends critically on 

the participation of the physician, who must devise a treatment plan, consider alternative treatments, and monitor the patient’s response to treatment. But we believe 

the role of DTC advertising in initiating contacts is important for these serious conditions. The advertisement you described, which is a so-called ‘‘reminder ad,’’ however, contains little useful information. 

There are 2 types of product promotion for prescription drugs. The first type is 

full product promotion, which must clearly state the indication (approved use) of the 

advertised drug and must provide balancing risk information about the drug. In addition, any claims that are presented in the advertisement must be substantiated. 

These ads can remind patients to see physicians about serious illness. The second 

type is reminder promotion. Reminder advertisements are advertisements that call 

attention to the name of the drug product but do not include indications or dosage 

recommendations for use of the product, or any other representations or suggestions 

about the product. Reminder advertisements contain the proprietary name of the 

drug and the established name of each active ingredient. They may also contain additional limited information, such as the name of the company, price, or dosage 

form. These advertisements are exempt from the FDA regulations that require that 

the indication and risks of the product be presented. However, if a supposed reminder advertisement includes more information than is allowed, it is considered to 

be a full product advertisement and must include the indication and risk information or it is in violation of FDA regulations. 
702 

Although reminder advertisements are legal, PhRMA has encouraged companies 

not to run reminder television advertisements to consumers but rather to run only 

full product ads. Principle #10 of PhRMA Guiding Principles—Direct to Consumer 

Advertisements About Prescription Medicines states ‘‘DTC television advertising 

that identifies a product by name should clearly state the health conditions for 

which the medicine is approved and the major risks associated with the medicine 

being advertised.’’ Note that these are voluntary guidelines and only apply to television advertisements. Below is the link to PhRMA Guiding Principles. http:// 

www.phrma.org/files/DTCGuidingprinciples.pdf. The Agency encourages companies 

to follow these guidelines so that consumer-directed television ads provide the public 

with both indication and risk information for advertised drugs. 

Question. In fiscal year 2006, the FDA spent slightly more than $1 million to monitor DTC ad content. A total of 8 full time staff are responsible for reviewing all 

DTC ads. Do you believe that the FDA has adequate resources to review DTC ad 

content? 

Answer. The Center for Drug Evaluation and Research devotes 13 full time 

equivalents (representing some full-time staff and portions of time spent by other 

staff). With these resources, we cannot review every one of the nearly 11,000 DTC 

promotional pieces disseminated by companies annually. We are proposing to recommend a program (separate from, but related to PDUFA IV) assessing user fees 

for advisory reviews of DTC television advertisements. These new fees would provide sufficient resources for FDA to hire additional staff to review television advisory submissions in a predictable, timely manner. FDA anticipates collecting $6.25 

million in annual fees during the first year of the program to support 27 additional 

staff. 

Question. According to a recent GAO report, from 2004 to 2005, by the time the 

FDA acted to stop misleading ad campaigns, more than half of the ad campaigns 

had already ended. Should the FDA be required to approve DTC ads before they 

are broadcast? 

Answer. FDA does not have the legal authority to require that broadcast ads be 

approved before they are publicly used. In the event that FDA was given the authority to pre-approve certain ads, as noted in Question 3 above, it would require an 

increase in staff resources to perform this review and approval in a timely manner. 

DRUG IMPORTATION

Question. Do you believe that prescription drugs sold in brick and mortar pharmacies in Canada are safe? 

Answer. Prescription drugs sold in brick and mortar pharmacies in Canada are 

regulated by Health Canada, the Canadian Federal department responsible for their 

approval. For this reason, the Administration can only comment on those products 

that fall under FDA regulatory authority. FDA can only assure the safety and efficacy of products that have been approved for marketing in the United States. 

Question. Under current law, drug companies are free to manufacture prescription 

drugs in other countries and import them for sale in the United States. About onequarter of the drugs sold in the United States today are made in other countries 

and imported to the United States for sale by pharmaceutical manufacturers. If importation can be deemed safe for manufacturers, why can’t it be made safe for consumers? 

Answer. Drug companies can manufacture prescription drugs in other countries 

and import them for sale in the United States only if they fulfill FDA’s regulatory 

requirements. Foreign drug establishments must be registered with FDA and comply with all regulations that apply to domestic drug establishments. This includes 

submission of all qualifying information with each drug product and being subject 

to inspections to insure the integrity of the product and the manufacture, process, 

handling, and storage of the product. It is only under these conditions that FDA can 

confirm the integrity of the product and allow importation of these products. 

Unapproved products pose a public safety concern since they are produced outside 

of this closed regulatory system. Unapproved products may include counterfeit drug 

products that may be making their way into the United States distribution system 

through consumers purchasing drug products from unregulated sources, such as the 

internet. Patients are at risk when they purchase these products from rogue 

websites, as it is uncertain whether the product they receive is genuine or counterfeit, contains inert or harmful ingredients, or contains sub-potent or super-potent 

amounts of the active ingredient. FDA does not have the resources to expand inspection capabilities to all possible sites from which a consumer may obtain unapproved 

drug products. 
703 

The HHS Drug Importation Task Force Report issued in December 2004 outlined 

the measures that would be needed to implement an importation program that provides adequate safeguards and resources to ensure that the imported drugs are safe 

and effective. A program that does not take these measures into consideration, regulated or not, would perpetuate the ‘‘buyer beware’’ situation that is currently occurring and consumers would continue to put themselves at risk for harm by importing 

unapproved drugs into the United States for personal use. 

The Task Force found that under such a system, importing drug products would 

yield minimal cost savings. Based on observations during a recent survey of packages intercepted at an international mail facility, FDA Office of Criminal Investigations suggests that cost savings for imported drugs is already questionable. Of over 

400 drug products assessed, approximately 50 percent were available as United 

States approved generic drug products. Further examination revealed that more 

than 40 percent of the generic drug products were available through national retail 

pharmacy chain programs that offer generic prescriptions for $4 each—which is likely less than the cost of shipping. 

Question. Wouldn’t a regulated system be safer than what is occurring today? 

Answer. The current system is regulated; the Food Drug and Cosmetic Act, or 

FD&C Act, gives the Secretary of HHS the authority to regulate drug products in 

the United States through FDA. Currently FDA does not have the resources or a 

regulatory mechanism to assess the safety and effectiveness of drug products imported into the United States outside of the existing closed distribution system. To 

effectively assess the safety and efficacy of these imported drug products, a new 

mechanism for the review and approval of these products would need to be created. 

This could entail creating a program similar to the generic drug program, which determines therapeutic equivalence of generic drug products. This is achieved by a 

thorough scientific review of chemistry, manufacturing and controls, clinical bioequivalence studies comparing the innovator product to the generic product, and labeling. Clinical, analytical, and manufacturing sites are subject to inspection by the 

agency. Creation of this program is impractical since it would require additional resources well beyond those currently available and allow for the approval of foreign 

generic products without regard to intellectual property protections of the innovator 

drug product. 

Consumers are likely to continue to purchase drug products from foreign or rogue 

websites. It is important to recognize that many who attempt to purchase medications from foreign sources are not doing so as a cost-savings measure, but are seeking to circumvent the need for a legitimate doctor’s prescription. As a public health 

agency, FDA understands the importance of protecting the public health not only 

through regulation and enforcement, but also through education and collaboration. 

FDA’s website is replete with consumer information about drug importation, buying 

drugs online, counterfeit drugs, enforcement activities, potential public health 

threats, as well as resources to report problems with FDA regulated products or 

websites that could be selling counterfeit or harmful products. 

PENDING APPROVAL OF CEFQUINOME

Question. The Washington Post recently reported that the FDA is on the verge 

of approving cefquinome for use in animals, despite a warning from the FDA’s Veterinary Medical Advisory Committee that approving cefquinome for use in animals 

may erode the effectiveness of a related drug that is used to treat human infections. 

I understand that that FDA will likely approve cefquinome because of a guidance 

document (Guidance #152) that was issued in 2003. The guidance makes it hard for 

the FDA to reject any drug unless it is clear that the use of the drug in animals 

will reduce the effectiveness of antibiotics that are used to treat food-borne illnesses 

in humans. Why is the threat assessment in Guidance #152 limited to food-borne 

illnesses? 

Answer. First, we would like to clarify that Guidance 152 is ‘‘guidance’’ and, 

therefore, provides nonbinding recommendations on an approach for evaluating antimicrobial drugs as part of the new animal drug approval process. In developing this 

guidance, FDA obtained broad stakeholder input through public meetings and 

through publication of a draft document. The guidance document was first published 

as a draft for public comment in September 2002, consistent with the Agency’s Good 

Guidance Practices Regulations. 

After considering public comment on the draft document, FDA issued a final guidance in October 2003. The guidance outlines an approach for conducting a qualitative risk assessment to evaluate the likelihood that an antimicrobial drug used 

to treat an animal may cause an antimicrobial resistance problem in humans consuming food from that animal. The guidance focuses on food-borne pathogens be-
704 

cause FDA believes that human consumption of animal-derived foods represents the 

most significant pathway for human exposure to antimicrobial resistant bacteria 

that have emerged or been selected as a consequence of antimicrobial drug use in 

animals. Nonetheless, as stated in the guidance, although FDA’s primary focus will 

be food-borne pathogens, other bacteria may be considered when deemed necessary. 

The risk assessment approach recommended in the guidance includes three key elements that are collectively considered in determining an antimicrobial drug’s potential risk to humans if used to treat food-producing animals. The first is the ‘‘release 

assessment,’’ which estimates the probability that resistant bacteria will be present 

in animals as a result of the proposed use of the new antimicrobial drug. The second 

is the ‘‘exposure assessment,’’ which gauges the likelihood that humans would ingest 

the resistant bacteria from the relevant food product. The third is the ‘‘consequence 

assessment,’’ which assesses the probability that human exposure to the resistant 

bacteria would result in adverse human health consequences. 

The input for the ‘‘consequence assessment’’ component is based on a system, developed as part of the guidance, for ranking the importance of antimicrobial drugs 

in human medicine. The ranking system, included as Appendix A of the guidance, 

results in a drug being ranked as Important, Highly Important, or Critically Important to human medicine. This ranking system was developed in collaboration with 

physicians at FDA’s Center for Drug Evaluation and Research (CDER), CDER’s 

Anti-Infective Drugs Advisory Committee, and the Centers for Disease Control and 

Prevention (CDC). The criteria for ranking human importance considers factors including whether the antimicrobial (1) is used to treat food-borne infection; (2) is a 

sole therapy or one of limited therapies to treat serious human disease, or is an essential component among many antimicrobials in the treatment of human disease; 

(3) is used to treat enteric pathogens in non-food-borne disease; and (4) is a drug 

for which cross-resistance or co-resistance to other drugs is a concern. Therefore, the 

human importance ranking process and, hence the consequence assessment component, considers a number of relevant factors in addition to whether the drug is important for treating food-borne disease. 

Based on a consideration of the release, exposure, and consequence components 

of the assessment, the guidance outlines an approach by which the animal drug in 

question is placed into one of three risk categories. The guidance outlines examples 

of risk management steps that FDA may apply to an antimicrobial drug based on 

the risk category such as the level of concern to human health. These range from 

denying the approval if the drug is not shown to be safe to approving the application 

with certain restrictions on its use. 

We reiterate that the final decision regarding the safety of an antimicrobial drug 

is not driven solely by Guidance 152. Pursuant to the Federal Food, Drug, and Cosmetic Act, FDA’s decision regarding whether to approve a new animal drug application is driven by factors that include (1) whether such application included adequate 

tests to determine whether or not the drug is safe, (2) whether the results of such 

tests show the drug is unsafe or do not show the drug to be safe, or (3) whether, 

based on information either in the application or otherwise available to FDA, there 

is sufficient information to determine that the drug is safe. 

In regard to the drug cefquinome, FDA has not made a final decision regarding 

its approval. FDA is currently reviewing the comments from its Veterinary Medical 

Advisory Committee, carefully reviewing the drug’s assessment under Guidance 152, 

and considering any and all other information relevant to the safety of the drug. 

Question. I understand that the World Health Organization recommends that animal drugs should only be approved if the use of the drug would not result in resistance to any antibiotic that is important to fighting human disease. Why is the scope 

of the FDA standard much narrower? 

Answer. FDA recognizes that food-borne human exposure to antimicrobial resistant bacteria is complex and often involves contributions from other sources of exposure, for example, direct contact between animals and humans, introduction of resistant bacteria, and resistance determinants into the environment. However, FDA 

believes that evaluating antimicrobial new animal drug safety relative to the most 

significant exposure pathway, such as the food-borne pathway, is the best way to 

qualitatively assess the risk of antimicrobial drug use in food-producing animals. 

Nonetheless, as stated in Guidance 152, non-food-borne bacteria may be considered 

when deemed necessary; for example, uncertainties regarding the contribution of 

other exposure pathways may be considered during the development of appropriate 

risk management strategies. 

In developing criteria for ranking antimicrobial drugs with regard to their importance in human medicine, FDA considered broad issues associated with the efficacy 

of drugs in human medicine and factors influencing the development of antimicrobial resistance. Specific factors include the usefulness of the drug in food-borne 
705 

infections, the types of infections treated, the availability of alternative therapies, 

the uniqueness of the mechanism of action, and the ease with which resistance develops and is transferred between organisms. 

The World Health Organization (WHO) has also developed a system for ranking 

antimicrobial drugs with regard to their importance to human medicine. However, 

the WHO approach differs somewhat than the approach adopted by FDA. WHO determines the critical nature of an antimicrobial drug based on its use as the sole 

therapy or one of few alternatives to treat serious human disease, and on its use 

to treat diseases caused by organisms that may be transmitted via non-human 

sources or diseases caused by organisms that may acquire resistance genes from 

non-human sources. WHO is looking broadly at diseases worldwide that may not be 

present in the United States. 

As mentioned previously, FDA believes that human consumption of animal-derived foods represents the most significant pathway for human exposure to antimicrobial resistant bacteria that have emerged or been selected as a consequence 

of antimicrobial drug use in animals. 

Question. Should the burden be on the drug companies to prove that using a drug 

to treat animals poses no risks to human health? 

Answer. Drug companies are required to submit as part of a new animal drug application (NADA) full reports of adequate tests by all methods reasonably applicable 

to show whether or not the new animal drug is safe and effective. For animal drugs 

intended for use in food-producing species, this requirement includes safety with regard to human health. 

FDA does not normally do the actual testing, but rather evaluates the results of 

testing that is submitted as a component of an NADA. In the case of NADAs for 

antimicrobial drugs intended for food-producing animals, FDA’s Guidance 152 provides recommendations to industry on an approach for evaluating safety concerns 

related to antimicrobial resistance. FDA considers an antimicrobial new animal 

drug to be ‘‘safe’’ with regard to human health if it concludes that there is reasonable certainty of no harm to human health from the proposed use of the drug in 

food-producing animals. 

QUESTIONS SUBMITTED BY SENATOR RICHARD J. DURBIN

DIETARY SUPPLEMENTS

Question. Late last year, Congress enacted a law that requires manufacturers of 

dietary supplements to report serious adverse events that result from the use of 

their products. The supplement ephedra caused seizures and strokes and the loss 

of over 150 lives before it was finally taken off the market. The new law will provide 

an important early warning system and is a first step in addressing safety concerns 

with supplements. Have you developed a timeline for developing regulations? What 

resources will the Food and Drug Administration (FDA) need to implement the law? 

Answer. The Dietary Supplement and Nonprescription Drug Consumer Protection 

Act requires by December 22, 2007, that the labels of dietary supplements include 

a domestic address or phone number which persons can use to submit adverse event 

reports (AERs) to the manufacturer, packer, or distributor of the product, and declares dietary supplements misbranded if they are labeled on or after this date without this information. In addition, the firm whose name and address appears on the 

supplement label must submit to FDA any serious adverse event reports associated 

with the use of the supplement within 15 business days of receiving the report. Any 

new medical information received within a year of the initial report must also be 

submitted to the Secretary within 15 days of receipt. The reporting and labeling requirements for industry are self-implementing. 

The new law directs FDA to issue guidance by September 18, 2007, on the minimum data elements that should be included in a serious adverse event report for 

a dietary supplement, and to develop systems to consolidate duplicate reports of, 

and new medical information related to, a serious adverse event into a single AER. 

Before issuing final guidance on the minimum data elements that should be included in a serious adverse event report for a dietary supplement, CFSAN intends 

to publish draft guidance and solicit comments from the public, in accordance with 

FDA’s good guidance practice regulations. CFSAN already has processes in place to 

consolidate duplicate AERs and new medical information on existing AERs so that 

all information about a given adverse event appears in a single report, as required 

by the new law. 
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With respect to resources for Public Law 109–462, no funding for implementation 

was provided in the fiscal year 2007 appropriation and no funding was requested 

in the President’s fiscal year 2008 budget. 

Currently, the agency has been performing tasks that will contribute to the full 

implementation of the new law. For example, FDA performed a gap analysis between the FDA 3500A MedWatch form and the capabilities of the current CFSAN 

Adverse Events Reporting System (CAERS). This analysis shows that CAERS needs 

software modifications to receive fields on the 3500A MedWatch form. 

In addition, the agency is planning the additional work activities needed to fully 

implement the law. These work activities will include developing several business 

processes, making significant Information Technology (IT) improvements to the existing CAERS, and modifying contracts providing records management and IT support. To accommodate the significant adverse event reports expected to result from 

mandatory reporting, CFSAN plans to modify CAERS to accept AERs electronically 

via the MedWatch Plus initiative, which will include modifications to accommodate 

dietary supplements. 

ADVISORY COMMITTEES

Question. The credibility of FDA’s decisions is seriously undermined when its advisory committee members have financial ties to the industries whose products they 

are reviewing. I think the FDA has too readily granted waivers to existing conflict 

of interest laws. In July, FDA announced a plan to strengthen the advisory committee process. And in January, as part of its response to drug safety recommendations from the Institute of Medicine, FDA said it would issue three guidances on 

advisory committees in 2007. Can you tell me what issues FDA is looking at and 

when we can expect to see those guidances? 

Answer. FDA has been engaged in a high level review of our advisory committee 

processes. We are committed to making the FDA advisory committee process even 

stronger and better understood so that the public has confidence in the integrity of 

advisory committee recommendations. Our goals are to increase the consistency, 

predictability, and transparency of the process. As part of our efforts to improve advisory committee processes, we announced that we would develop three new guidance documents in furtherance of these goals. One of these guidances has already 

gone on display at the Federal Register, and we plan to issue the other two in the 

near future. The first guidance will help ensure that briefing materials prepared for 

advisory committee members are made available to the public and will assist sponsors and others in preparing and submitting such briefing materials to FDA. The 

second draft guidance will provide guidelines for reviewing conflicts of interest and 

determining who may participate in FDA advisory committee meetings. This draft 

guidance will also simplify the process for determining who may participate in advisory committee meetings and will recommend a consistent and predictable decisionmaking process for all FDA advisory committees. FDA’s third draft guidance document on disclosure of conflicts of interest and waivers for advisory committee members will bring increased transparency to FDA’s waiver process by making additional information about waivers and members’ conflicts of interest available on 

FDA’s website. 

FOOD SAFETY

Question. The Government Accountability Office (GAO) recently designated food 

safety as one of the high risk Federal Government programs. In addition to the 

GAO’s report, the spinach and Taco Bell E. coli outbreaks last year and the recent 

outbreak of salmonella in peanut butter underscore the need for increased food inspections. 

Although FDA’s overall funding has been steadily increasing since 2001, the budget for FDA’s core functions, including the Center for Food Safety and Applied Nutrition has been slowly eroding since 2002. FDA regulates 80 percent of the food supply. According to FDA, staffing is the main barometer of FDA resources. The total 

staff is not increasing even though the workload continues to increase. What is FDA 

doing to ensure that the incidence of food-borne illnesses decreases? Does FDA have 

any plans to increase the number of food inspectors on its staff? 

Answer. FDA uses a risk-based approach to allocate available resources. When 

outbreaks occur FDA moves resources to address the immediate need to protect public health. Since 1998, FDA has increased efforts toward minimizing food safety hazards associated with fresh produce. For example, we have been and are working 

with industry as it develops commodity-specific safety guidelines for a number of 

fresh produce products, including lettuce and leafy greens, melons, and tomatoes; 

food safety guidelines for green onions and herbs are being drafted. We also recently 
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issued the draft final guidance for fresh-cut produce. We are holding public meetings 

to allow us to gather comments, data, and other useful scientific information about 

current agricultural and manufacturing practices, risk factors for contamination of 

fresh produce, and possible steps we can take to enhance the safety of fresh produce. 

In addition, FDA launched a multi-year Leafy Greens Safety Initiative with assessment, research and communication components. This Initiative is a collaboration between FDA, the California Department of Health Services and the California Department of Food and Agriculture, intended to reduce public health risks by 

proactively focusing on the product, agents, and areas of greatest concern in advance of an outbreak. We are looking at using this Initiative as a model for other 

commodities, such as tomatoes. 

For fiscal year 2008 we have requested a total of $10.6 million for additional food 

safety activities. We consider this amount as an initial deposit on the many activities that are necessary to continue our campaign for improved food safety. Funds 

will be used to begin to address the lifecycle of produce production; to develop better 

methods to detect and attribute foodborne illness outbreaks, to increase sampling 

and traceback capabilities; to develop and update guidance to prevent and reduce 

outbreaks; to obtain additional expertise in the production and processing of fresh 

produce; and to enhance our response to foodborne outbreaks. 

The $5.5 million that the Office of Regulatory (ORA) requested as part of the 

Strengthening Food Safety Initiative in the fiscal year 2008 President’s Budget request will not result in an increased number of food safety inspections. Funding will 

be used to enhance ORA’s ability to more rapidly trace back foodborne disease outbreaks and to work proactively to encourage growers and processors to implement 

good agricultural practices and other interventions designed to prevent contamination of food. ORA will develop, train, and equip teams to work with State partners 

in large produce-growing regions. Funding will also be used to accelerate development of an import decision-making IT system capable of detecting high-risk food 

shipments before they enter U.S. commerce. While FDA already has systems that 

are used to identify and target certain high-risk import shipments, the new system 

will increase current capabilities by providing for automated review and trending 

of the results of field examinations and analyses of samples, identifying candidates 

for detention without physical examination; it will score each entry line on the basis 

of risk factors and surveillance requirements, for an automated, real-time decision 

on action to be taken; and, it will incorporate exogenous data with available FDA 

operational data to create a broader picture for each shipment. 

QUESTIONS SUBMITTED BY SENATOR JACK REED

SUNSCREEN MONOGRAPHS

Question. The FDA Reform Act of 1997 directed your agency to complete a sunscreen monograph, which will guide UVA and UVB labeling information for overthe-counter (OTC) sunscreen products. The fiscal year 2006 Agriculture Appropriations conference report again included language directing the FDA to complete the 

sunscreen monograph, within 6 months of passage of the agriculture appropriations 

bill. That bill was signed into law on November 10, 2005. The FDA began drafting 

this monograph for sunscreen products in 1978 and has yet to complete it. Meanwhile, another summer season is approaching and millions of consumers will again 

use sunscreen products that provide half the protection. As you know, around 

60,000 people worldwide die each year from skin cancer caused by too much sun 

exposure. 

Why is the FDA unable to complete this monograph despite repeated requests 

from Congress, the public health community, and health care providers? 

Answer. Revisions to the stayed final sunscreen monograph that address the issue 

of measuring protection against UVA rays, including UVA and UVB labeling requirements, involve the resolution of complex scientific and legal issues, both of 

which have contributed to this lengthy process. 

Question. What is the status of the monograph and how much longer can we expect to wait before a final monograph will be available? 

Answer. On May 12, 1993, FDA published a tentative final monograph (TFM) that 

included UVB testing and labeling requirements. On May 21, 1999, FDA published 

a final monograph (FM) for OTC sunscreen drug products. The FM included UVB 

testing and labeling requirements, but deferred UVA testing and labeling requirements to a future publication. On December 31, 2001, FDA stayed the December 

31, 2002, effective date of the FM to develop a comprehensive monograph that addresses formulation, labeling and testing requirements for both UVB and UVA radi-
708 

ation protection. The proposed rule that addresses formulation, labeling and testing 

requirements for both UVB and UVA radiation protection has been written and is 

in final FDA clearance. 

Question. Once the final monograph is completed, how much longer will it take 

for skin screen manufacturers and makers of skin care products that include sunscreen to adopt necessary changes to their products? 

Answer. FDA cannot provide an exact time estimate, but the agency is aware 

there are many factors involved for manufacturers to implement necessary changes 

to their products, such as the seasonal nature of the sunscreen industry, time required for product testing and relabeling and economic impact considerations for the 

industry and consumers. All of these factors affect the speed with which changes 

can be made to products and how quickly the products reach the market. 

Question. As the former Director of the National Cancer Institute, could you talk 

about the potential health impact of excess exposure to UVA rays? 

Answer. Ultraviolet (UV) rays are a part of sunlight that is an invisible form of 

radiation. UV rays can penetrate and change the structure of skin cells. UVA is the 

most abundant source of solar radiation at the earth’s surface and penetrates beyond the top layer of human skin. Scientists believe that UVA radiation can cause 

damage to connective tissue and increase a person’s risk for developing skin cancer. 

UV exposure appears to be the most important environmental factor in the development of skin cancer. A person’s risk of skin cancer is related to lifetime exposure 

to UV radiation. Most skin cancer appears after age 50, but the sun damages the 

skin from an early age. 

Skin cancer is the most commonly occurring cancer in the United States. Basal 

cell carcinoma and squamous cell carcinoma are the most common forms of skin 

cancer, but are easier to cure than melanoma. The number of new cases of skin cancer appears to be increasing each year. 

It is important to decrease UV exposure by limiting time in the sun, wearing protective clothing, and using a sunscreen. 

QUESTIONS SUBMITTED BY SENATOR ROBERT F. BENNETT

COUNTERFEIT DRUGS

Question. Dr. von Eschenbach, earlier this month, FDA notified consumers that 

a number of Americans who had placed orders over the internet for common prescription drugs instead received a product that contained a very powerful anti-psychotic drug. As a result of taking these fake products, consumers had to seek emergency medical treatment for symptoms such as difficulty in breathing, muscle 

spasms and muscle stiffness. FDA warned consumers not to purchase prescription 

drugs off the internet unless they were certain that the internet sites were legitimate pharmacy sites. 

In your opinion, how prevalent are counterfeit drugs in the United States? 

Answer. We believe that in the United States, counterfeit drugs are quite rare. 

By all accounts, the overwhelming majority of prescription drugs sold in the United 

States are genuine, FDA-approved drug products. While we have no direct quantitative evidence about the prevalence of counterfeit drugs, we believe that counterfeit drugs represent significantly less than 1 percent of the total U.S. drug supply. 

Question. Please explain the steps FDA is taking to find and prosecute counterfeit 

drug manufacturers. 

Answer. The FDA Office of Criminal Investigations, OCI, actively elicits and receives information from many entities to identify counterfeit drug sources, including 

industry, the public and other domestic law enforcement agencies. OCI also coordinates counterfeit drug investigations with several foreign counterparts, especially 

those in China, Israel, the Netherlands, and Canada, to enhance criminal investigations. These efforts continue to produce positive outcomes for both OCI and its foreign counterparts. OCI will continue to aggressively pursue counterfeit drug investigations with law enforcement partners in foreign countries as well as with Federal, State, and local law enforcement here in the United States. 

As an example, in September 2006, an individual from China was arrested by officers of the Hong Kong Customs and Excise Department based on a Federal arrest 

warrant issued by the U.S. District Court for the District of Colorado. The defendant 

was arrested in Hong Kong after meeting with an undercover OCI agent who posed 

as a buyer of over 400,000 counterfeit Cialis® and Viagra® tablets. This investigation also involved the sale of several thousand counterfeit Tamiflu® capsules that 

were manufactured in China and shipped to the United States. Information developed by OCI and Immigration and Customs Enforcement, or ICE, was shared with 
709 

Chinese authorities had already led to the August 2006 arrests of four individuals 

in China. In addition to the arrest in Hong Kong, three other defendants in the 

United States have pled guilty to counterfeit drug charges. Furthermore, information developed during this joint OCI, ICE counterfeit drug investigation was the 

basis for another counterfeit Percocet® investigation in Philadelphia, Pennsylvania 

which resulted in a sentence of 32 months incarceration for the defendant. 

Question. Since many counterfeit products come from other countries, does FDA 

receive adequate assistance from foreign governments to find and prosecute drug 

counterfeiters? 

Answer. The adequacy of assistance the Office of Criminal Investigations, or OCI, 

receives from foreign governments depends on the respective governments involved. 

OCI has had success with foreign governments regarding counterfeit drug investigations, but increased cooperation, collaboration, and strengthening of relationships 

with foreign governments would lead to enhanced identification and prosecution of 

counterfeit drug operations. Our success is limited because OCI does not have a foreign presence in countries such as China and therefore, OCI must leverage its resources with other agencies such as the Immigration and Customs Enforcement, or 

ICE and the Drug Enforcement Administration or DEA, which do have a presence 

in other countries. 

In another example of assistance OCI receives from foreign governments, an individual from the State of Washington was indicted and arrested in September 2005 

for his involvement in the importation from China and subsequent distribution of 

counterfeit drugs, including Viagra®, Cialis® and Lipitor®. The defendant pled 

guilty to distributing counterfeit drugs and was sentenced in October 2006 to 10 

months of incarceration. In this joint OCI and ICE investigation, cooperation was 

sought and received from the Chinese government. As a result of this cooperation, 

the Chinese authorities arrested eleven individuals in China and recovered significant amounts of counterfeit drugs and counterfeit drug packaging. 

FDA PAY COSTS

Question. During user fee negotiations this year, FDA and industry agreed that 

annual inflation for pay and benefit costs is approximately 5.8 percent. This calculation was based on a moving 5-year average. However, the budget request includes 

only a 3.0 percent increase for pay costs. 

Why does the budget request not include the total amount for pay? 

Answer. In the fiscal year 2008 President’s Budget FDA requested an increase of 

$21.77 million for the 3 percent mandated cost-of-living increase for employees, 

which is in concurrence with the Administration’s policy. Funding the annual pay 

increase enables FDA to perform its public health mission. 

Question. What is the rationale for shortchanging basic inflationary costs in the 

budget? 

Answer. In the fiscal year 2008 President’s Budget FDA requested an increase of 

$21.77 million for the 3 percent mandated cost-of-living increase for employees, 

which is in concurrence with the Administration’s policy. Funding the annual pay 

increase enables FDA to perform its public health mission. 

Question. How do pay shortfalls affect the ability of FDA to utilize initiative increases, such as food safety or drug safety, to the fullest extent? 

Answer. In the fiscal year 2008 President’s Budget FDA requested an increase of 

$21.77 million for the 3 percent mandated cost-of-living increase for employees, 

which is in concurrence with the Administration’s policy. 

Funding the annual pay increase enables FDA to perform its public health mission. Without these funds, FDA must reduce the number of inspectors, medical and 

consumer safety officers, food safety technologists, medical product reviewers, 

postmarket safety experts, and other public health experts to meet higher payroll 

obligations. These workforce reductions would limit FDA’s ability to safeguard the 

American public. 

Question. How does under-budgeting for pay affect FDA staffing and future budget requests? 

Answer. In the fiscal year 2008 President’s Budget FDA requested an increase of 

$21.77 million for the 3 percent mandated cost-of-living increase for employees, 

which is in concurrence with the Administration’s policy. 

Funding the annual pay increase enables FDA to perform its public health mission. Without these funds, FDA must reduce the number of inspectors, medical and 

consumer safety officers, food safety technologists, medical product reviewers, 

postmarket safety experts, and other public health experts to meet higher payroll 

obligations. These workforce reductions would limit FDA’s ability to safeguard the 

American public. 
710 

GENERIC DRUG REVIEW FISCAL 2007 FUNDING

Question. The fiscal 2007 joint resolution provided an increase of $5 million for 

the Office of Generic Drugs. 

How does FDA plan to use this funding and how will generic drug review performance be enhanced as a result of the additional funding? Answer. The $5 million increase to the office of generic drugs in fiscal year 2007 

will allow FDA to help make up for lost performance, due to the loss of 10 FTE 

under the continuing resolution. The Center for Drug Evaluation and Research, or 

CDER, currently is recruiting to backfill these lost positions. In fiscal year 2008 this 

$5 million increase is expected to yield an additional 10 approvals a month, once 

all of the reviewers have been hired and trained to conduct reviews. FDA expects 

that it will take at least 1 year to recruit and train staff for the Office of Generic 

Drugs. 

Question. What is the current backlog for generic drug applications? 

Answer. There is currently a backlog of about 1,300 original generic applications 

as of the end of February 2007. 

FDA ALLIANCE REQUEST FOR FDA FUNDING

Question. Dr. von Eschenbach, a couple groups, the FDA Alliance and the Coalition for a Stronger FDA, have been lobbying for more money for FDA. They estimate 

that Congress needs to add $250 million in non-user fee funding this year to effectively fund FDA’s needs. This estimate is obviously well above the budget request 

for FDA. 

Are you aware of their analysis of FDA funding needs? 

Answer. We have read accounts of their analysis that has been reported in the 

press. 

Question. What do you think about their suggestion that FDA needs an increase 

of $250 million this year? 

Answer. This is an amount that greatly exceeds the President’s budget request. 

PROPOSED GENERIC DRUG USER FEE

Question. The budget request includes a proposal to implement a generic drug 

user fee in fiscal 2008. According to FDA’s calculations, the fee will generate $15.7 

million in the first year. 

Has industry been receptive to this fee proposal? 

Answer. We are currently exploring with industry the possibility of user fees for 

generic drugs. 

PROPOSED RE-INSPECTION USER FEE

Question. For the second year, FDA is proposing a re-inspection user fee, which 

will require manufacturers to pay for the full cost of follow-up inspections when 

FDA must revisit facilities because of initial bad inspection reports. FDA plans to 

collect $23.2 million in fiscal 2008 as a result of this fee. 

Please explain for what services these fees are intended to be collected. 

Answer. When FDA finds that a firm fails to comply with applicable FDA law, 

then FDA may take various regulatory actions to ensure the firm’s compliance. 

Often, the firm’s voluntary corrective action can address these compliance failures 

and thus preclude the need for FDA initiating any regulatory action. In other cases, 

agency regulatory action will mean that the firm can no longer market some or all 

of its products. For example, in some cases FDA will not grant export certificates, 

approve product applications, or award government contracts because of the firm’s 

compliance status. If a firm undertakes corrective action to achieve compliance, FDA 

will verify the appropriateness and completeness of the corrective action. For the 

firm to satisfy FDA’s concerns and, if regulatory action was taken, to resume its full 

ability to market products, FDA must reinspect the firm to confirm compliance. 

When a firm believes it has corrected its noncompliance and addressed FDA’s concerns, the timely reinspection by FDA to evaluate such compliance benefits the firm 

by allowing a quicker resolution of these compliance questions and, where applicable, allowing the firm to resume its full ability to market products. 

These user fees will permit FDA to act in a timely manner to ensure that noncompliant firms have taken appropriate corrective action and to facilitate the return 

of compliant firms to full marketing. Some of the activities that FDA performs in 

conducting reinspections include the scheduling and preparatory reinspection work 

by the FDA investigator, the reinspection itself, collecting and analyzing samples, 

preparing reports on the inspection, review and analysis by compliance officers, consulting with experts, and travel and administrative time. 
711 

Question. How does FDA determine the costs that each facility must pay for reinspection? 

Answer. The Office of Regulatory Affairs determined the costs that each facility 

must pay for re-inspections based on the number of violative inspections in fiscal 

year 2006; the average length of time performing those inspections; and, the average 

cost of each Office of Regulatory Affairs FTE. 

Question. Would FDA charge small or start-up companies differently than larger, 

more established companies? 

Answer. The Secretary of Health and Human Services will establish reinspection 

fees to be collected based on the Secretary’s estimate of the cost to conduct reinspections for a particular year. The legislation submitted to the Congress in fiscal year 

2007 for this proposal allows the Secretary to provide for waivers, reductions, or 

other adjustment of fees based on financial hardship or other circumstances as determined appropriate by the Secretary. 

Question. Has industry been receptive to this fee proposal? 

Answer. We are currently exploring with industry the possibility of user fees for 

resinspections. 

USER FEE REAUTHORIZATION

Question. FDA is currently in the process of renegotiating the user fee agreements 

for prescription drugs and medical devices. These two user fee programs are crucial 

to maintaining FDA review times and bring in almost $400 million in revenue annually. 

Please provide us with an update on the progress FDA and industry are making 

toward reauthorizing these programs. 

Answer. On March 23, 2007, the Secretary transmitted to key House and Senate 

authorizing committees the HHS/FDA recommendations for changes to the statute 

and to the performance commitment letter for the Prescription Drug User Fee Act 

IV, or PDUFA IV. These recommendations reflected the results of FDA’s discussions 

with the pharmaceutical and biotechnology industry, which concluded in November 

2006, and further revisions to the commitment letter based on public input received 

in response to the January 16, 2007 Federal Register notice publishing FDA’s proposed recommendations, and received at the PDUFA IV public meeting FDA held 

on February 16, 2007. FDA’s recommended changes to the statute and commitment 

letter are currently being reviewed by the Senate Health, Education, Labor and 

Pensions, or HELP, Committee staff and House Energy and Commerce Committee 

staff. 

FDA and the medical device industry have been discussing legislative recommendations for the Medical Devices User Fee and Modernization Act, or 

MDUFMA, reauthorization since the fall of 2005. Almost all issues of interest to 

FDA and to industry have been resolved. We are working to resolve the outstanding 

issues very quickly. 

PANDEMIC INFLUENZA

Question. In the fiscal 2006 supplemental, we provided $20 million for pandemic 

influenza preparedness. This funding was continued in the fiscal 2007 joint resolution. 

What has FDA accomplished with this funding? 

Answer. FDA reports the following 12 activities have been accomplished with the 

funding: 

—engaged in efforts to build and enhance our infrastructure to support new vaccine development and licensure for pandemic influenza, hired 75 employees 

with expertise in essential clinical, product safety, and manufacturing areas; 

initiated contracts to ensure facilities have needed surge capacity and being prepared to handle viruses at the Biosafety Level 3, which include laboratories critical for vaccine testing 

—approved another influenza vaccine under the new accelerated approval pathway, giving consumers five FDA-licensed influenza vaccines 

—approved 35 influenza vaccine BLA supplements, which contribute to capacity 

building for seasonal and pandemic influenza vaccines 

—involved in activities to determine the potency of vaccines against a pandemic 

strain, develop tests and assays to ensure safety of cell cultures used to manufacture vaccines, and explore requirements to prepare libraries of pandemic influenza viral strains, so the strains are available for manufacturing vaccines 

—published two draft guidance documents outlining approaches that influenza 

vaccine developers can follow to ensure the safety and effectiveness of new vaccines 
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—developed a Lot Release Information Technology System to support testing and 

release of vaccines to ensure safety and effectiveness 

—hosted a meeting with foreign regulatory authorities to discuss harmonizing 

regulatory pathways for pandemic influenza vaccines 

—participated in meetings on issues such as existing and ‘‘next generation’’ vaccine production technologies, current Good Manufacturing Practices and research needs, and participated in a public-private working group to develop 

guidelines to assure the public of the safety of the food supply during an outbreak in animals 

—provided technical assistance to support HHS decision making on the mix of 

antiviral medications to include in the Strategic National Stockpile 

—served as technical advisor to HHS and others on FDA regulation of masks and 

other personal protective equipment (PPE) and workplace guidance on the use 

of PPE during an influenza pandemic 

—conducted investigations and covert surveillance operations to detect counterfeit, impure, contaminated, sub-potent, or super-potent products that claim to 

prevent or treat seasonal or pandemic influenza 

—issued 41 warning letters to internet sellers of unproven bird flu cures and preventatives. 

Question. How many pandemic influenza products have been approved? 

Answer. With the funding associated with the $20 million supplemental funding 

CBER has approved one influenza vaccine biologics license application, or BLA, 

Flulaval, which was a priority review, and 35 influenza vaccine BLA supplements, 

which contribute to capacity building for seasonal and pandemic influenza vaccines. 

In this same time frame, CBER held 28 meetings with influenza vaccine manufacturers and received and reviewed 21 investigational new drug applications, or INDs, 

for influenza vaccines. 

In October 2006, CBER received the first U.S. BLA for a vaccine against H5N1 

influenza virus. FDA also designated this application as a priority review, which 

means that FDA will take an action on the application within 6 months of receiving 

it. In February 2007, CBER presented this application to the Vaccines and Related 

Biological Products Advisory Committee to obtain the Committee’s input regarding 

the safety and effectiveness of the vaccine. The action due date for this H5N1 vaccine is April 17, 2007. If approved, this will be the first vaccine approved for H5N1, 

a potential pandemic influenza strain. 

FDA has also approved other pandemic influenza products with base funding used 

in both CDER and CDRH. There are four antiviral drugs currently approved by 

CDER at FDA to treat acute, uncomplicated influenza. Two related drugs, 

amantadine (approved 1966; Trade Name Symmetrel, also available as generic 

Amantadine Hydrochloride) and rimantadine (approved 1993; Trade Name 

Flumadine, also available as generic Rimantadine Hydrochloride), are approved for 

treatment and prevention of influenza A; however, many recent influenza viruses 

are resistant to these drugs, seriously limiting their usefulness. Two newer drugs, 

zanamivir (approved 1999; Trade Name Relenza; no approved generics) and 

oseltamivir phosphate (approved 1999; Trade Name Tamiflu; no approved generics), 

are approved for treatment of acute uncomplicated illness due to influenza A and 

B. Both zanamivir and oseltamivir are approved for preventive use. 

CDRH approved a diagnostic device for the detection of novel influenza (H5N1) 

which is directly related the Pandemic Influenza. This product is called the Influenza A/H5 (Asian lineage) Virus Real-time RT–PCR Primer and Probe Set. The test 

provides preliminary results on suspected H5 influenza samples within four hours 

once a sample arrives at the lab and testing begins. Previous testing technology 

would require at least 2 to 3 days to render results. If the presence of the H5 strain 

is identified, then further testing is conducted to identify the specific H5 subtype 

(e.g., H5N1). 

There are a number of devices regulated by FDA that would be in increased demand in a pandemic. Examples include devices such as ventilators, bacterial filters 

for breathing circuits, resuscitators, infusion pumps, IV administration sets, vaccination needles, surgical masks, surgical respirators, gloves and gowns. None of 

these is specifically cleared for use in a pandemic, but carry more general labeling 

claims. CDRH assessed types, number and the increase in submissions for cleared 

products in increased demand during a pandemic. CDRH observed an increase in 

the number of clearances from an average of 0.5 respirators per year prior to October 1 2005 to an average of 5.6 respirators per year between October 1, 2005 and 

February 27, 2007—for a total of 8 respirators cleared in the latter time period. 
713 

RESEARCH REDUCTIONS TO BSE

Question. Dr. von Eschenbach, the budget request includes a proposal to reduce 

research by $3.8 million. According to the budget request, one area where FDA 

plans to reduce research is on prohibited materials in animal feed. 

Why is FDA reducing funding for this research, especially when it is so critical 

to FDA’s role in reducing the risk that cattle will contract mad cow disease? 

Answer. The Center for Veterinary Medicine, or CVM, completed development of 

a real-time Polymerase chain reaction, or PCR, based method. Once field validation 

of the real-time method is completed, the field has a necessary tool to support enforcement of the feed ban. Companies are not marketing new rapid test kits for detecting prohibited proteins in animal feeds; therefore, CVM does not have additional 

test kits to evaluate. 

The Office of Regulatory Affairs, or ORA, intends to absorb the reduction of 

$593,000 in the Animal Drugs and Feeds Program by reducing both personnel and 

operating funds for coordination activities in either the ORA Office of Enforcement; 

ORA Headquarters; or Compliance Officers and Public Affairs Specialists located in 

the Region and District Offices. Operating fund reductions will be taken in travel, 

training and meetings with State or industry officials to perform outreach activities 

in support of the Field Animal Drugs and Feed Program. Management and coordination functions will continue by using electronic media/technology and realigning 

and consolidating coordination responsibilities to improve efficiencies. 

The research reduction allows CVM and ORA to fund the full cost of fiscal year 

2008 priority initiatives. 

MEDICAL DEVICE USER FEE AND MODERNIZATION ACT (MDUFMA)

Question. I have paid close attention to the Medical Device User Fee and Modernization Act (MDUFMA) review program, and this subcommittee has provided 

substantial appropriated dollars for the review of medical devices. 

How is FDA doing in regards to meeting the performance goals associated with 

the user fee program with the user fee and appropriated funding it has received to 

date? 

Answer. FDA has made excellent progress towards meeting the Medical Device 

User Fee and Modernization Act’s, or MDUFMA, complex and demanding performance goals, and particularly so for the decision goals that both FDA and industry 

regard as the key indicators of performance. We review our performance at the end 

of each quarter, and I am providing a table for the record that summarizes total 

FDA progress on each goal through December 31, 2006. As soon as we have prepared similar information for the quarter that ends March 31, 2007, I will send you 

an updated table. 

Let me cite just three examples of our progress in meeting MDUFMA’s performance goals from fiscal year 2003 through the end of 2006. For premarket approval 

applications and panel-track PMA supplements, we made 169 ‘‘FDA decisions’’ during that period, and we made 94.7 percent of those decisions within our target of 

320 days. For 180-day PMA supplements, we made 532 ‘‘FDA decisions’’ and we 

made 95.7 percent of those decisions within 180 days. And for 510(k) premarket notifications, we made 13,670 decisions, and we made 86.1 percent of these decisions 

within 90 days. 

I believe the performance we have achieved to date clearly demonstrates FDA’s 

strong commitment to pursuing and meeting MDUFMA’s performance goals. The 

proposals FDA and industry have developed to reauthorize medical device user fees 

for fiscal years 2008 through 2012 build on the progress we have made, and include 

a refined set of performance goals that provide a clear pathway to further improvements in our review of medical devices. 

[The information follows:] 
714 

QUARTERLY REPORT ON PROGRESS TOWARDS ACHIEVING MDUFMA PERFORMANCE GOALS 

Summary Tables 

[Actions through December 31, 2006—Data for FDA] 

Activity Review Time Goal 

Performance Goals and Actual Performance to Date 

Fiscal Year 2003 Fiscal Year 2004 Fiscal Year 2005 Fiscal Year 2006 Fiscal Year 2007 Overall, Fiscal 

Year 2003 to 

Date (Actual) Goal Percent Actual Percent Goal Percent Actual Percent Goal Percent Actual Percent Goal Percent Actual Percent Goal Percent Actual Percent 

VIAs, Panel-Track: Supplements, Premarket Reports: 

FDA decision (approval, approvable, approvablepending GMP inspection, not approvable, denial) ................................................................................................... 320 days .......... 91.7 .......... 91.7 .......... 97.9 80 100 90 .......... 94.7 First action—major deficiency letter ........................................................................ 150 days .......... 84.6 .......... 82.1 75 91.9 80 92.9 90 100 87.5 First action-all other first actions (approval,approvable, approvable pending GMP 

inspection,not approvable, or denial) ................................................................... 180 days .......... 95.8 .......... 95 75 90 80 90.5 90 .......... 92.9 

Second or later action—major deficiency letter ...................................................... 120 days .......... 100 .......... 100 75 70.6 80 100 90 .......... 81.5 Action on an amendment containing a completeresponse to a major deficiency 

or not approvable letter ........................................................................................ 180 days .......... 92. .......... 88.9 75 90.2 80 90 90 .......... 90.3 

Action on an amendment containing a complete response to an approvable letter .......................................................................................................................... 30 days 90 33.3 90 .......... 90 70 90 .......... 90 .......... 44.4 

Expedited PMAs: 

FDA decision (approval, approvable, approvable pending GMP inspection, not approvable, denial) ................................................................................................... 300 days .......... 100 .......... 92.3 70 50 80 .......... 90 .......... 85 First action major deficiency letter ........................................................................... 120 days .......... 100 .......... 80 70 80 80 .......... 90 .......... 82.4 First action—all other first actions (approval, approvable, approvable pending 

GMP inspection, not approvable, or denial) ......................................................... 170 days .......... 100 .......... 25.0 70 100 80 100 90 .......... 57.1 

Second or later action—major deficiency letter ...................................................... 100 days .......... .......... .......... .......... 70 100 80 .......... 90 .......... 50 Action on an amendment containing a completeresponse to a major deficiency 

or not approvable letter ........................................................................................ 170 days .......... 100 .......... 62.5 70 100 80 .......... 90 .......... 80 

Action on an amendment containing a complete response to an approvable letter .......................................................................................................................... 30 days 90 100 90 50 90 .......... 90 .......... 90 .......... 66.7 

180-day PMA Supplements: 

FDA decision (approval, approvable, approvable pending GMP inspection, not approvable, denial) ................................................................................................... 180 days .......... 94.1 .......... 96.2 80 95 80 98.3 90 100 95.7 First action—not approvable letter .......................................................................... 120 days .......... 18.8 .......... 83.7 80 90 85 81.1 90 .......... 71.1 First action—all other first actions (approval, approvable, approvable pending 

GMP inspection, not approvable, or denial) ......................................................... 180 days .......... 95.3 .......... 96.8 80 98.4 85 98.9 90 100 96.9 

Action on an amendment containing a complete response to a not approvable 

letter ...................................................................................................................... 160 days .......... 96 .......... 97.6 80 86.1 85 92.3 90 .......... 93.1 
715 

510(k)s: 

FDA decision (SE/NSE) .............................................................................................. 90 days .......... 76.1 .......... 83.9 75 91.3 75 95.3 80 100 86.1 First action—additional information letter .............................................................. 75 days .......... 58.6 .......... 78.6 70 93.8 80 92.8 90 98.1 81.9 Second or later action ............................................................................................... 60 days .......... 50.9 .......... 81.9 70 91.5 80 96 90 100 80.7 

Biologics Licensing Applications BLAs: 

Review and act on standard original BLAs (issue complete action letter) ............. 10 months .......... .......... .......... 100 .......... 100 75 100 90 100 100 Review and act on priority original BLA submissions (issue complete action letter) ........................................................................................................................ 6 months .......... .......... .......... .......... .......... .......... 75 .......... 90 .......... ....................

BLA Supplements: 

Review and act on standard BLA efficacy supplements (issue complete-action 

letter) .................................................................................................................... 10 months .......... 100 .......... .......... .......... .......... 75 .......... 90 .......... 100 

Review and act on priority BLA efficacy supplements (issue complete action letter) ........................................................................................................................ 6 months .......... .......... .......... .......... .......... .......... 75 .......... 90 .......... ....................Review and act on BLA manufacturing supplements that require prior approval 

(issue complete action letter) .............................................................................. 4 months .......... 98.6 .......... 100 .......... 96 75 100 90 100 98.9 

BLA Resubmissions,Supplement Resubmissions: 

Review and act on a Class 1 resubmission to an original BLA or BLA efficacy 

supplement (issue complete action letter) .......................................................... 2 months .......... .......... .......... .......... 75 100 80 .......... 90 .......... 100 

Review and act on a Class 2 resubmission to an original BLA or BLA efficacy 

supplement (issue complete action letter) .......................................................... 6 months .......... 100 .......... 80 75 100 80 100 90 .......... 95 
716 

Question. Would you be willing to adopt a method to determine incremental direct 

and indirect costs associated premarket application (PMA) and 510(k) device approvals? 

Answer. FDA is committed to providing a full accounting of our use of those resources entrusted to us. To that end, we have established cost accounting systems 

that meet or exceed generally-accepted government accounting practices. As required by the Chief Financial Officers Act of 1990, as amended, our records are subject to periodic independent audits by the Office of Inspector General, or OIG. The 

OIG issued unqualified audit opinions on FDA’s financial statements for fiscal years 

1998 through 2004. This is the most favorable category of audit opinion. Auditors 

did not render an opinion on FDA’s financial statements for fiscal year 2005, primarily due to the mid-year conversion to the new HHS Unified Financial Management System. In fiscal year 2006, HHS incorporated the FDA financial audit as part 

of the HHS financial statement audit. We are pleased to report that HHS received 

an unqualified opinion on its financial statements. Our implementation of the Medical Device User Fee and Modernization Act of 2002, or MDUFMA, has been addressed by three reports by the U.S. Government Accountability Office, which made 

no adverse findings and provided no recommendations for change. We have also provided a MDUFMA financial report to Congress each year since the program was enacted. 

FDA and industry discussed whether additional information was required for adequate oversight of our MDUFMA initiatives. Our joint recommendations for reauthorization 6 months to discuss issues relating to performance and medical device 

user fees includes an agreement to meet informally every expenditures, including 

an FDA update on how funding is being used for the device review process, including investments in information technology and training. 

I believe these systems, safeguards, audits, oversight, reports, and commitments 

provide the necessary transparency concerning our costs and our use of resources. 

Question. What criteria does the agency use to determine the allocation and priority for the distribution of staff and funding increases across FDA components, including offices, divisions, or branches resulting from the medical device user fees 

and related appropriated funding? 

Answer. I would describe our general approach as combining a risk-based assessment of our needs, and a focus on accomplishing our public health missions through 

the most efficient and effective means possible. FDA allocates medical device user 

fees and other medical device appropriations to best achieve FDA’s public health objectives, performance goals and other expectations established under the Medical 

Device User Fee and Modernization Act of 2002 and its amendments. The user fees 

and additional appropriations provided to FDA under MDUFMA have been allocated to reflect the workload balance between the Center for Devices and Radiological Health, or CDRH, and the Center for Biologics Evaluation and Research, or 

CBER. Soon after Congress enacted MDUFMA, FDA estimated the percent of the 

device review workload that was performed in CDRH and the percent that was performed in CBER. FDA allocated its MDUFMA resources to CDRH and CBER using 

those percentages. 

Field resources are allocated among districts by the Office of Regulatory Affairs 

according to each district’s projected workload, such as Quality Systems Regulation 

and preapproval inspections of medical device establishments. 

Each Center and ORA is responsible for apportioning its overall resource allocation to its offices, divisions, and branches. The general approach is to prioritize additional needs and to allocate additional resources accordingly. 

Question. Are third party review and third party inspection programs useful? Is 

there anything that can be done to improve these programs? 

Answer. I believe that both the third-party inspection program and third-party reviews of 510(k) premarket notifications have the potential to be useful adjuncts to 

the corresponding FDA processes, helping us conserve and focus FDA’s resources. 

In implementing the third-party inspection program, FDA met all of the Medical 

Device User Fee and Modernization Act’s, or MDUFMA, statutory requirements and 

deadlines. We accredited 17 well-qualified organizations to conduct third-party inspections. We trained third-party inspectors so they would fully understand FDA’s 

inspectional requirements. We prepared guidance to facilitate the understanding of 

the statutory requirements and the processes FDA would use to administer the program. We wrote to device establishments to make them aware of the program. Despite these efforts, establishments have been reluctant to participate because of perceived procedural burdens. So far, only two establishments have requested and received a third-party inspection. 
717 

FDA is currently working on changes to this program as part of the MDUFMA 

reauthorization negotiations. I look forward to communicating these recommendations to you and working with you to see that these changes are made. 

Although the third party 510(k) review program has grown significantly since it 

was established, the program has not yet saved FDA the resources that we had 

hoped we could reallocate to other 510(k) reviews. This is because all third party 

submissions undergo FDA quality review and because the training and continuing 

education of third parties remains resource intensive. 

Nonetheless, more than 1,300 510(k)s have undergone third-party review since 

the inception of the program, and the number of submissions has been rising steadily. During fiscal year 2006, the third-party program was responsible for 287 submissions, compared with just 107 5 years earlier, and accounted for about 7 percent 

of all 510(k)s. For some types of devices, third-party submissions account for a much 

larger share of our overall workload. For example, during the past 3 years, over 80 

percent of radiology devices have been reviewed through the third-party program. 

We have worked hard to ensure that third-party reviews meet our expectations 

for quality and completeness. When we observed some unevenness in the quality of 

third-party submissions, we provided additional guidance to FDA staff and thirdparty reviewers. We also believe that quarterly teleconferences with third-party reviewers and continuous quality feedback from FDA review divisions will contribute 

to further quality improvement over time. We believe the program may further improve as third parties gain further review experience and proficiency that can be 

applied to subsequent reviews, and as FDA develops guidance documents for more 

devices. 

BIOLOGIC LICENSE APPLICATION APPROVALS

Question. According to a recent news article, the Center for Biologics Evaluation 

& Research’s average time to approval of biologic license applications (BLAs) was 

18.9 months in 2006, almost doubling the previous year’s average of 9.3 months. 

This is a troubling statistic. 

What has caused the increase in review times and what steps is FDA taking to 

make improvements? 

Answer. The approval number quoted in the Pink Sheet article does not reflect 

a doubling of Agency review time from 2005 to 2006. Time to approval is the time 

from initial submission to final approval, including all the time that elapses while 

a company revises its application to correct deficiencies in its initial application. In 

fiscal year 2005, the Center for Biologics Evaluation and Research, or CBER, had 

eight biologics license application, or BLA, approvals, with all eight approved during 

the first review cycle. The review cycle is the time between application receipt and 

issuance of an action letter. Sometimes an application contains deficiencies that prevent CBER from approving the license application in the first review cycle. In this 

event, CBER issues what is known as a complete response letter. A complete response letter describes the deficiencies in the application, stops the review clock, 

and gives the company an opportunity to correct the deficiencies and resubmit its 

application. Sometimes companies can correct the deficiencies quickly by explaining 

or clarifying existing data or methods; other times companies must submit more 

data or even conduct completely new clinical trials before the application can be approved. In 2005, because CBER was able to approve all BLAs in the first review 

cycle, total approval times were considerably shorter than if a complete response letter had been issued. 

In fiscal year 2006, CBER had five approvals: three during the first review cycle; 

one in the second review cycle; and one in the third review cycle. The approval that 

went through three review cycles took almost 53 months. Thirty-two of those 

months did not involve FDA review time. They were time between review cycles 

that the applicant used to address CBER’s complete response letters. With only five 

total approvals in fiscal year 2006, that one application—along with the other application that required more than one review cycle—skewed the average approval time 

significantly. The difference between the median approval time, which was 13 

months, and the average approval time, which was 19.4 months—the Pink Sheet’s 

figure differs because it includes Center for Drug Evaluation and Research-approved 

licenses, reflects the effect of the two applications that could not be approved in the 

first review cycle. 

In contrast, the CBER approvals in fiscal year 2005 were completed in extremely 

short times with no second review cycles required. The average CBER approval time 

was 9.1 months, and the median CBER approval time was 9.9 months. CBER reviewers completed those reviews expeditiously through intense review effort but also 

were aided considerably by the quality of the submissions. While CBER reviewers 
718 

made similar intense review efforts in 2006, and continue those efforts today, we 

also continue to explore ways to improve the quality of submissions and shorten review times further. 

QUESTIONS SUBMITTED BY SENATOR ARLEN SPECTER

FOLLOW-ON BIOLOGICS

Question. There is concern among biologic drug companies that the FDA does not 

have the resources to handle the regulatory procedures necessary to ensure safe and 

effective follow-on or generic biologics. In your opinion does the FDA have the regulatory ability to ensure the safety and efficacy of follow-on biologics? 

Answer. FDA has the scientific expertise to determine the safety and effectiveness 

of follow-on biologics. This is demonstrated by FDA’s approval of certain follow-on 

protein products under section 505(b)(2) of the Federal Food, Drug, and Cosmetic 

Act and the agency’s substantial expertise and experience in approving biologics license applications under section 351 of the Public Health Service Act, or PHS Act. 

FDA will address the scientific challenges related to follow-on protein products in 

a manner consistent with its approach in other scientific arenas: on a case-by-case 

basis as issues arise, in accordance with FDA’s statutory authority and its mission 

to both advance and protect the public health. If a new regulatory pathway is enacted by statute for the approval of follow-on biologics under section 351 of the PHS 

Act, it will be necessary to consider the adequacy of agency resources needed to efficiently and effectively implement such a program. 

ORA CONSOLIDATION

Question. It is my understanding that FDA plans on consolidating the FDA’s Office of Regulatory Affairs laboratories. I appreciate your response to a joint letter 

to you sent on January 29, 2007. Could you elaborate in more detail on the proposal 

to include which labs are planned on being closed and the number of employees that 

would be affected. Further, what does the agency plan on offering those employees 

that work at labs that are proposed to be closed? Finally, will the consolidation plan 

negatively impact our Nation’s safety of food, medical equipment, and cosmetics? 

Answer. FDA’s Office of Regulatory Affairs, or ORA, plans to enhance its laboratory capabilities by strengthening six of ORA’s regulatory labs, moving to these six 

labs the personnel, equipment and other resources from seven other existing labs. 

The seven labs are older facilities in need of costly renovations, cannot expand to 

accommodate merging with another lab, have expiring leases, and meet a range of 

other criteria which have led FDA to consolidation in these areas. This transformation will allow ORA scientists to work more closely together and improve collaboration and synergy. This will allow us to invest in state-of-the-art equipment 

and processes in the remaining laboratories and to increase investment in other critical areas. Because the ORA restructuring is still early in its planning phase, the 

number of employees impacted has not yet been determined. 

Strengthening these six labs will help FDA better meet its mission to protect and 

promote the public health. Currently, FDA must pay the costs associated with approximately 40 percent more laboratory space than is needed to conduct the laboratory work to support all of FDA’s field programs and activities. These six labs will 

accommodate and exceed the capacity of testing conducted in the existing 13 labs. 

Although overnight delivery services diminish the need for laboratories to be in 

close proximity to sample collection sites, the consolidated laboratories will be dispersed geographically. In addition, the six labs will continue to provide supporting 

layers of expertise with appropriate redundancies to protect against unforeseen 

operational problems, and surge capacity to deal with emergencies. 

This proposed restructuring of ORA would begin in fiscal year 2008. Costs for the 

restructuring in fiscal year 2008 are covered within the fiscal year 2008 budget 

level. All analysts from closing labs will be offered jobs in the labs to which their 

work is transferred. We realize that some employees will not relocate and in order 

to retain as many of these valued employees as possible, we will seek to place them 

in other jobs in their current location. ORA needs to invest intellectual and financial 

capital in new approaches to emerging challenges such as the increasing complexity 

of the products and processes we regulate. ORA transformation provides an opportunity to staff teams of national experts in a variety of disciplines. Towards this 

end, the transformation plan provides for Centers for Excellence in those geographic 

regions of the country where labs will be closed. 

The seven closing laboratories include Denver District Laboratory (Denver, Colorado); Detroit District Laboratory (Detroit, Michigan); Kansas City District Labora-
719 

tory (Lenexa, Kansas); Philadelphia District Laboratory (Philadelphia, Pennsylvania); San Francisco District Laboratory (San Francisco, California); San Juan District Laboratory (San Juan, Puerto Rico); and, the Winchester Engineering and Analytical Center (Winchester, Massachusetts). 

In the seven areas where there have been laboratories, FDA is planning to utilize 

the significant expertise that already exists and focus on the 21st Century challenges unique to each region. The ORA transformation provides the opportunity to 

address the specific challenges that ORA is facing in each of these regions, and to 

respond to the rapidly changing profile of the products it regulates. These regions, 

and the capability of the FDA employees who are stationed there, will continue to 

play a critical role in ensuring the safety of our Nation’s food and drugs. 

CONCLUSION OF HEARING

Senator KOHL. This hearing is recessed. 

[Whereupon, at 12:18 p.m., Tuesday, February 27, the hearing 

was concluded, and the subcommittee was recessed, to reconvene 

subject to the call of the Chair.] 

(721) 

1The ad hoc coalition is composed of the American Maritime Congress, American Maritime 

Officers, American Maritime Officers’ Service, American Soybean Association, International 

Food Additives Council, International Organization of Masters, Mates & Pilots, Liberty Maritime Corporation, Marine Engineers’ Beneficial Association, Maritime Institute for Research and 

Industrial Development, National Association of Wheat Growers, National Corn Growers Association, National Council of Farmer Cooperatives, National Oilseed Processors Association, 

North American Millers’ Association, Seafarer’s International Union, Sealift, Inc., TECO Ocean 

Shipping, Inc., Tosi Maritime Consultants, LLC, Transportation Institute, U.S. Dry Bean Council, USA Rice Federation, and U.S. Wheat Associates, Inc. 

AGRICULTURE, RURAL DEVELOPMENT, FOOD 

AND DRUG ADMINISTRATION, AND RELATED AGENCIES APPROPRIATIONS FOR 

FISCAL YEAR 2008 

U.S. SENATE, 

SUBCOMMITTEE OF THE COMMITTEE ON APPROPRIATIONS, Washington, DC. 

NONDEPARTMENTAL WITNESSES 

[The following testimonies were received by the Subcommittee on 

Agriculture, Rural Development, Food and Drug Administration, 

and Related Agencies for inclusion in the record. The submitted 

materials relate to the fiscal year 2008 budget request for programs within the subcommittee’s jurisdiction.] 

PREPARED STATEMENT OF THE AD HOC COALITION

Mr. Chairman, Members of the Subcommittee, this statement is respectfully submitted on behalf of the ad hoc coalition 1 composed of the organizations listed below. 

The coalition supports sustained funding for our Nation’s food aid programs, including Titles I and II of Public Law 480, and therefore strongly opposes the administration’s twice-rejected proposal to convert Public Law 480 food aid funding into cash 

donations for commodities purchases in overseas markets. 

GUIDING PRINCIPLES OF FOOD AID POLICY

The coalition recognizes that American food assistance policy is well-established 

and founded on certain guiding principles, including the following: 

—Meeting America’s humanitarian obligation to sustain food assistance programs, 

with U.S. participation in such programs constituting more than 50 percent of 

all food aid worldwide. 

—Employing food assistance programs as stepping stones for economic growth and 

development. 

—Employing food assistance programs to promote respect worldwide for American 

values and our economic system, thereby enhancing goodwill toward America 

among disadvantaged populations that may be breeding grounds for terrorism. 

THE SHARP DECLINE IN OVERALL FOOD AID PROGRAM LEVELS

The programs needed to implement these principles have enjoyed broad, bipartisan support for many decades. The strength of our commitment has made the 

United States the world’s leading food aid supplier. In the process, American agriculture is bolstered as food aid recipients strengthen and stabilize their economies. 
722 

In recent years, however, food aid shipments have declined sharply. The United 

States shipped 5.9 million tons of commodities in fiscal year 2002, 4.2 million tons 

in fiscal year 2005, and 3.7 million tons in fiscal year 2006. For fiscal year 2008, 

the administration’s proposal would support only 2.975 million tons of commodities. 

We respectfully request that this steady erosion of food aid be reversed, and that 

funding be restored to sustainable levels to assure the continued effectiveness and 

stability of these important and historically successful programs. 

THE ADMINISTRATION’S BUDGET FOR FISCAL YEAR 2008

The administration proposes to continue last year’s total elimination of funding 

for Title I. 

Over the last several years, as funding for Title I has disappeared, the vast majority of food aid donations have been provided through the Food for Peace Title II program, which the administration proposes to further reduce by $413 million from fiscal year 2006 levels, supporting the shipment of only 2.5 million tons of commodities 

in fiscal year 2008. Moreover, under the President’s budget, Title II food aid would 

be reduced by up to $305 million and converted to overseas purchases of food aid 

at the discretion of the Administrator for the U.S. Agency for International Development (‘‘USAID’’). 

Our coalition strongly opposes the administration’s proposal to convert essential 

American food assistance to a program under which USAID would use appropriated 

funds to procure food supplies overseas. It has provided no sound basis for doing 

so, and there are many reasons why this proposal should be rejected again, just as 

it was rejected by the Congress in 2005 and 2006. 

Under authority provided by Section 416(b) of the Agricultural Act of 1949, the 

administration states that no surplus commodities will be made available for donation in 2008. This represents another year of diminished reliance on the 416(b) program, which is funded through the Commodity Credit Corporation (‘‘CCC’’). 

In its fiscal year 2008 Budget Summary, the Department of Agriculture (‘‘USDA’’) 

estimates that CCC-funded Food for Progress (‘‘FFP’’) shipments will be 385,000 

metric tons of grain equivalent. Unfortunately, this falls short of the 400,000 ton 

level established for CCC-funded FFP shipments in the 2002 Farm Bill. 

Finally, the administration has requested $100 million for the McGovern-Dole 

International Food for Education and Child Nutrition Program (‘‘IFEP’’), representing approximately 90,000 tons of commodities. This increase of only 3 percent 

from fiscal year 2006 is far overshadowed by the decreases in other programs. 

The administration’s recommendations, taken together, would lead to further reductions in food aid. Of even more significance, the administration’s recommendation to reduce Title II funding in favor of USAID cash assistance undermines the 

foundation upon which U.S. food aid policy has been built in the post-World War 

II era. For the reasons set forth below, the coalition urges this subcommittee to sustain Title II funding, reinvigorate the Title I program, and reject, for a third time, 

the administration’s unwise and unnecessary proposal to siphon off a quarter of 

Title II appropriations into a discretionary account for USAID. 

RESTORATION OF OVERALL FOOD ASSISTANCE PROGRAM LEVELS

The coalition recommends that food aid be restored over time to sustainable levels 

in the range of 5.0 million to 6.0 million metric tons of grain equivalent in each fiscal year. In fiscal year 2008, this would require restoration of Title I funding, incremental increase in the Title II funding to $1.6 billion, and greater use of existing 

authorities of the CCC. 

USDA’s Budget Summary justifies the elimination of Title I as necessary because 

recipient countries have been more interested in direct grants than concessional 

sales. Of course, the demand for donated food will always exceed the supply and the 

coalition recognizes that recipient countries would prefer grants over concessional 

sales—even sales at extremely favorable terms. 

In order to ensure that the most desperate countries have sufficient donated food 

aid, the coalition recommends that USDA offer the Title I concessional sales program to countries that can afford the terms. Among the countries receiving Title IIfunded grants in recent years, there are surely some who reasonably could afford 

to make the transition from grant assistance to concessional sales, using the direct 

loan authority of Title I. And to the extent that the Title I funding truly cannot be 

used for concessional sales, it may be converted to donations on full grant terms 

through FFP. 
723 

ELIMINATION OF TITLE II FUNDING FOR LOCAL PURCHASE

The coalition is strongly opposed to the administration’s attempts to eliminate up 

to 25 percent ($305 million) of Public Law 480 Title II funding in favor of an experimental program whereby the USAID Administrator will be granted unchecked discretion to divert U.S. tax dollars to foreign producers. Congress has wisely rejected 

this proposal in each of the last two budget cycles, and there is no authority for this 

program. 

The administration intimated that its cash-based proposal was prompted by concerns regarding the timeliness of shipments from the United States in times of crisis. However, USAID already has adequate options for overcoming time constraints 

in appropriate circumstances, including: 

—using the existing authority in the International Disaster and Famine Assistance Program (‘‘IDFA’’); 

—borrowing commodities from a nearby available source and later replacing them 

with Title II commodities once shipped into the region; 

—transferring commodities between approved Title II programs before they are 

distributed; 

—expanding the existing prepositioning program by developing forward deployed 

food stocks closer to areas of need; and 

—diverting commodities already in transit to areas in extreme need, as was done 

when a shipload of aid was diverted to the tsunami-damaged areas of Asia in 

2005. 

Surely some combination of these solutions could be developed to address any 

timeliness concerns, obviating the justification for raiding our Nation’s longest-running and most successful food aid program. 

Little study has been conducted regarding the dangers of purchasing aid locally, 

near areas of food insecurity. USAID has admitted that local purchases threaten to 

destabilize local food markets. Additionally, discretionary expenditures of large 

sums for aid in third world countries raise the specter of corruption and abuse, including theft, kick-backs, and market manipulation by local traders. Local markets 

lack adequate seasonal storage capacity in many instances, putting relief efforts at 

the mercy of the very market fluctuations they are designed to alleviate, and cannot 

be counted upon to provide the high-quality, fortified blend products that are most 

essential to saving lives in severe food crises. 

Moreover, the administration’s proposal to eliminate up to a quarter of in-kind aid 

under Title II would undermine our position in the World Trade Organization 

(‘‘WTO’’) where the United States has spent the last several years defending our 

current food assistance programs as a necessity if the world is committed to reducing hunger. 

Lastly, the proposal to buy commodities overseas, instead of from American farmers and processors, threatens to undermine the broad-based political and support 

framework that has made Title II a success over the last half century. Indeed, Europe’s conversion to cash-based aid resulted in a dramatic drop in aid levels. 

CONCLUSIONS AND RECOMMENDATIONS

Mr. Chairman, the coalition is committed to maintaining U.S. food assistance programs at responsible levels in order to meet humanitarian needs and enhance the 

potential for economic growth in recipient countries. Our recommendation is to increase, over time, annual food assistance at combined program levels of between 4.0 

million and 6.0 million metric tons of grain equivalent. This can be accomplished, 

as in the past, with a blend of programs supported by direct appropriations and 

CCC program authorities. 

The coalition respectfully recommends the following: 

—Title I program levels should be restored, and responsibly increased again in 

succeeding years, so that the unique advantages of the program are not lost. 

—The Title II program should be restored to its fiscal year 2006 level of $1.632 

billion, and funding should not be diverted to programs relying primarily on the 

purchase of foreign commodities for food assistance. These actions will also help 

ensure that the United States fulfills its moral obligation to provide not less 

than one-half of the world’s donated food aid. 

—In committee report language, the House Appropriations Committee should reiterate its directive to the FAS in the fiscal year 2003 cycle to make greater use 

of existing CCC authorities to expand food aid to regions in critical need, and 

explicitly reject the administration’s proposal to convert American food aid to 

so-called ‘‘local purchase’’ initiatives. 
724 

The in-kind food programs of Public Law 480 have been a bulwark of American 

food aid policy since the days of the Marshall Plan, and they deserve the strong support of your subcommittee, the Congress, and the entire Nation. 

Thank you, Mr. Chairman. 

PREPARED STATEMENT OF THE ADVANCED MEDICAL TECHNOLOGY ASSOCIATION

AdvaMed is pleased to provide this testimony on behalf of our member companies 

and the patients and health care systems we serve around the world. AdvaMed is 

the largest medical technology trade association in the world, representing more 

than 1,300 medical device, diagnostic products and health information systems manufacturers of all sizes. AdvaMed’s members manufacture nearly 90 percent of the 

$86 billion of health care technology products purchased annually in the United 

States, and more than 50 percent of the $220 billion purchased annually around the 

world. AdvaMed members range from the largest to the smallest medical technology 

innovators and companies and directly employ about 350,000 workers in the United 

States. More than 75 percent of our members have $30 million or less in domestic 

sales annually. 

AdvaMed supports the President’s fiscal year 2008 budget request of $240,122,000 

for the Food and Drug Administration’s (FDA’s) Center for Devices and Radiological 

Health (CDRH). This inflationary increase amount maintains the annual inflationary increases for the agency that have helped meet the requirements of the 

Medical Device User Fee and Modernization Act (MDUFMA—Public Law 107–250) 

and the Medical Device User Fee and Stabilization Act (MDUFSA—Public Law 109– 

43) to date, and is crucial to ensure patients have timely access to lifesaving and 

life-enhancing products. 

Medical Device User Fees 

We are pleased that the President’s budget proposal includes a 5 percent increase 

in FDA funding over 2007, which will help maintain a reasonable balance between 

user fees and appropriated funds in the device center and expand other resources 

to address key public health needs. 

The increasing number and complexity of medical device submissions have overwhelmed CDRH over the last decade. When MDUFMA was crafted, review times 

for breakthrough products often exceeded over 400 days, despite a statutory ceiling 

of 180 days. To address these chronic delays, Congress passed MDUFMA in October 

of 2002 to supplement FDA’s resources and expertise and reduce review times for 

medical technologies. MDUFMA creates a predictable and adequate funding base for 

CDRH through a combination of industry-paid user fees and an increase in Congressional funding for the agency. Congress passed MDUFSA in 2002 to ensure the continuance of this critical program, and we are hopeful that MDUFMA will be reauthorized this summer to continue the program for another 5 years. 

Medical technology companies will have added over $150 million to CDRH resources during the first 5 years of the historic MDUFMA agreement. Although the 

additional appropriations did not materialize in the first 2 budget years of the 

MDUFMA agreement, Congress provided nearly $26 million in fiscal year 2005 and 

inflationary required amounts for fiscal year 2006 and fiscal year 2007. The fiscal 

year 2008 requested amount shows the strong support by the Administration to 

maintain the MUDFMA program. 

CDRH must be funded adequately to ensure the goals of MDUFMA are met, 

maintain the United States’ position in the rapidly advancing field of medical technology, and ensure patients’ timely access to needed medical breakthroughs. 

AdvaMed requests that the fiscal year 2008 Agriculture Appropriations bill fully 

fund CDRH at $240,122,000 to accomplish these important goals. 

Additional Fees and Issues 

AdvaMed notes with interest that the President’s budget calls for collecting over 

$23 million for re-inspection fees. We are interested to learn more about the nature 

of these fees and to which services currently provided by the FDA they will apply. 

As noted above, we are in the process of reauthorizing the MDUFMA program this 

year. This reauthorization will include significant increases in the current user fees 

the industry pays already for the review process. Given the significant number of 

small companies within our industry, we have strong concerns about additional fees 

being applied, especially before any substantial dialogue between the industry and 

the Agency over the level and intended use of the fees. Any additional fees must 

be additive to the baseline and must be associated with clearly identified performance goals above and beyond current levels. 
725 

Additionally, AdvaMed is concerned that, as in years past, attempts will be made 

in the fiscal year 2008 appropriations process to alter FDA policy and procedures 

related to the regulation of new and existing devices, including the advisory panel 

process. AdvaMed generally opposes such attempts to alter fundamental FDA regulatory policy for medical devices on appropriations bills. We stand ready to offer our 

expertise on such matters should the need arise in the coming months. 

Background on the Medical Device User Fee Program 

America is on the cusp of an unprecedented revolution in medical technology driven by major private and public investments in scientific research and computer 

technology. Congress has also made a multi-billion dollar commitment to double 

medical research at NIH and unravel the human genome. Medical technology companies also doubled research and development spending in the decade of the 90’s. 

The vibrant medical technology sector has driven employment gains and a strong 

balance of trade much to the benefit of the American patient and economy over the 

last several years. At the same time, the growing number and complexity of new 

medical devices throughout the last decade, coupled with a drop in the absolute 

number of reviewers at CDRH has resulted in severe budget strain and increasing 

delays in approval of new medical technologies for patients. 

Prior to passage of MDUFMA, CDRH faced increasing challenges as a result of 

dwindling resources and accelerating innovation. Staff levels had dropped by eight 

percent between 1995 and 2001. By 2001, the average total review time for premarket approval applications had risen to 411 days, more than twice the statutory 

review time. An FDA science panel warned at the time that increasingly rapid advances in technology ‘‘threaten to overwhelm’’ CDRH’s limited resources. 

On October 26, 2002, President Bush signed MDUFMA, which was unanimously 

passed by Congress, into law to give CDRH additional resources and expertise to 

help provide timely patient access to new medical technologies. It established an industry-funded user fee program to provide up to $35 million each year to help the 

agency meet rigorous new performance goals. 

Key regulatory reforms in MDUFMA are designed to: 

—Eliminate bureaucratic delays in review of combination products by establishing 

a new office to oversee these technologies 

—Authorize FDA to accredit third-party inspectors to audit medical technology 

companies with a good track record of compliance; 

—Encourage timely, thorough premarket reviews by codifying the PMA ‘‘modular 

review’’ program and extending the third-party review program for 510(k)s; 

—Permit paperless device labeling and electronic facility registration. 

—Strengthen FDA regulation of reprocessed disposable devices. 

From bioengineered organs and implantable artificial hearts to gene-based diagnostic tests and molecular imaging systems, America’s medical technology companies are developing thousands of promising new tests and treatments. AdvaMed believes full implementation of MDUFMA will help ensure these advances reach the 

millions of patients who need them. 

The user fee provisions in the law set fees for premarket approval applications, 

supplements and 510(k) submissions. Under the original law, these fees, combined 

with funds from increased appropriations, will provide FDA’s device program with 

more than $225 million in additional resources over the 5 years of the program. A 

letter agreement accompanying the bill sets review performance goals for the agency. 

To assure that these user fees would have an additive effect on the CDRH budget, 

MDUFMA required that CDRH receive a $15 million appropriations increase in 

each of the first 3 years of the program (fiscal year 2003, fiscal year 2004 and fiscal 

year 2005) for a total of $45 million by the end of fiscal year 2005, or the user-fee 

program would have terminated in fiscal year 2006. These funds were designed to 

allow CDRH to upgrade information technology and other infrastructure necessary 

to carry-out a user-fee program and to meet the performance goals. 

MDUFMA passed both houses of Congress on the last day of the regular session 

in October 2002. Owing to the extremely late timing of MDUFMA passage and a 

very tight budget climate, MDUFMA funding targets were not met in either of the 

first 2 years of the MDUFMA agreement. MDUFSA was passed last year to allow 

the program to continue despite the funding shortages in the early years of the program. MDUFSA also addressed the significant rate of increases in fees paid by industry. As Congress has struggled to provide its funding, industry paid user fees 

(per submission) that far exceed what was expected by MDUFMA. Increases of 35 

percent, 15.7 percent and a projected 20 percent for fiscal year 2006 for individual 

PMA submissions were troubling to industry, and we appreciate the steps Congress 
726 

1 AF&PA is the national trade association of the forest, paper and wood products industry. 

AF&PA represents more than 200 companies and related associations that engage in or represent the manufacture of pulp, paper, paperboard and wood products. The U.S. forest products 

industry accounts for approximately 6 percent of the total U.S. manufacturing output, employs 

more than a million people, and ranks among the top 10 manufacturing employers in 42 States 

with an estimated payroll exceeding $50 billion. 

took to limit the rates of increase until the program can be reauthorized by September 30, 2007. 

To maintain the MDUFMA program and protect investments made by the Agency, 

American consumers and a leading source of job growth in our economy, we ask 

Congress to again meet the President’s fiscal year 2008 budget request for CDRH. 

Conclusion 

AdvaMed appreciates the Subcommittee’s efforts last year and urges them to continue on this path to fully fund MDUFMA and ready FDA for the coming era of 

biomedical innovation and patients that await timely access to the coming dramatic 

breakthroughs in medicine. AdvaMed requests that the fiscal year 2007 Agriculture 

Appropriations, Rural Development, Food and Drug Administration and Related 

Agencies bill fully fund CDRH at $240,122,000 to accomplish these important goals. 

We have concerns about the inclusion of new fees for the FDA to carry out core mission activities and urge the committee to refrain from altering FDA policy and procedures related to the regulation of new and existing devices in the fiscal year 2008 

appropriations process. 

AdvaMed thanks the committee for this opportunity to present our views and we 

look forward to working with you to help prepare FDA for the coming revolution 

in medical technology. 

PREPARED STATEMENT OF THE AMERICAN FOREST & PAPER ASSOCIATION

The American Forest & Paper Association 1 (AF&PA) supports the sustainable 

management of our Nation’s forests and encourages increased funding to advance 

forestry research, combat invasive species, and enhance food packaging innovations. 

The following recommendations concern fiscal year 2008 appropriations for the U.S. 

Department of Agriculture. 

Cooperative State Research, Education, and Extension Service (CSREES) 

There is a critical need to focus resources on research and outreach that addresses 

forest productivity, wood utilization, inventory, and conversion of wood to produce 

bioenergy/bioproducts. This practical research and outreach will advance our capacity to produce and measure healthier, faster-growing forests. CSREES and its 

partnering universities play a key role on-the-ground in meeting this need. 

—McIntire-Stennis (Cooperative Forestry Research) Program.—AF&PA recommends an increase over the President’s fiscal year 2008 request of $20.5 million. This program is the foundation of forest resources research and scientist 

education efforts at universities. It supports cutting-edge research on forest productivity, wood utilization, and development of new technologies. AF&PA opposes the President’s proposal to divert 63 percent of existing funds to competitive funding, as it would undermine valuable forestry research being conducted 

by our Nation’s universities. Instead, we encourage a phased approach to building in a competitive grants component to the program. 

—National Research Initiative (NRI) Competitive Grants Program.—AF&PA supports the President’s request of $256 million, but with increased focus on forestry research. These grants are a significant source of funding for basic and 

applied research on forest resources, including their management and utilization. In recent years, however, less than 6 percent of available funding has been 

allocated for forestry-related research. Given the considerable potential of the 

program to contribute to the Nation’s sustainable forestry research needs, that 

percentage should be increased, with specific focus on grants that support Agenda 2020 research, such as the Pine Genome Initiative. 

—Renewable Resources Extension Act (RREA) Program.—AF&PA recommends an 

increase over the President’s request of $4 million. RREA provides the foundation for extension and outreach efforts delivered to private landowners through 

universities. Cutting-edge forestry research is of limited benefit unless it can be 

effectively delivered to the Nation’s forest landowners. 
727 

Animal and Plant Health Inspection Service (APHIS) 

Emerging Plant Pests Program.—AF&PA encourages increased funding to ensure 

adequate research, eradication, and control efforts targeting the Sirex woodwasp, 

emerald ash borer, Asian longhorned beetle, and sudden oak death pathogen. All 

four introduced organisms have already done significant damage and threaten further damage to trees in our forests and communities. For example, the Sirex 

woodwasp is now found across much of New York State and parts of Pennsylvania, 

and threatens valuable pine timber resources, especially those of the Southeast. 

Without sufficient funding to prevent movement of these insects and diseases 

through infested wood, nursery stock, and other materials, the economic cost could 

escalate to hundreds of billions of dollars. 

Food and Drug Administration (FDA) 

Food Contact Notification (FCN) Program.—AF&PA urges restoration of funding 

at $6 million for this program, which is proposed for elimination in the President’s 

fiscal year 2008 budget request. This highly successful program provides efficient 

review and timely approval of new food packaging materials and additives. New 

food-contact materials have enhanced the safety and security of the U.S. food supply 

while increasing the availability of environmentally friendly products. The elimination of the FCN program would be an enormous detriment to manufacturers seeking clearances for new food-contact materials to be introduced in the U.S. marketplace. The FCN program is essential for continued paper and paperboard food packaging innovation, and for ensuring the most effective protection of packaged foods 

during transportation, storage and ultimate use by the consumer. 

Conclusion 

AF&PA appreciates the opportunity to provide the Subcommittee with testimony 

regarding the fiscal year 2008 budget for the U.S. Department of Agriculture. If implemented, increased funding for the programs listed above will help promote the 

sustainable management of our Nation’s public and private lands and the products 

that are produced from these lands. 

PREPARED STATEMENT OF THE AMERICAN HONEY PRODUCERS ASSOCIATION, INC. 

Chairman Kohl and Members of the Subcommittee: My name is Mark Brady from 

Waxahachie, Texas, and I currently serve as President of the American Honey Producers Association (‘‘AHPA’’). I am pleased today to submit the following statement 

on behalf of the AHPA, a national organization of commercial beekeepers actively 

engaged in honey production throughout the country. The purpose of this statement 

is bring to your attention both new and continuing serious threats to the domestic 

bee industry and to request your continued assistance in supporting Agricultural 

Research Service (‘‘ARS’’) research to address the many challenges that face the domestic beekeeping industry. 

First, we wish to thank again the Subcommittee for the strong support you have 

provided in past fiscal years for agricultural research activities on behalf of the beekeeping industry. As you know, in the fiscal year 2003 cycle, the Subcommittee rejected a proposal that would have resulted in the elimination of three ARS laboratories that are indispensable to the survival of our industry. In the years since then, 

the Subcommittee has worked to restore proposed cuts in honey bee research. Such 

support has enabled the ARS to address the critical research needs of the industry. 

For fiscal year 2008, the Administration’s budget again proposes to eliminate certain funding for ARS that it did not request but that the Congress provided in the 

appropriations process. To continue the research that is critical to honey bees, however, the AHPA requests that Congress maintain the funding for the ARS Honey 

Bee Research Laboratories at Baton Rouge, Louisiana; Weslaco, Texas; Tucson, Arizona; Beltsville, Maryland; and the ARS Wild Bee Research Laboratory at Logan, 

Utah. We also support increased funding for honey bee genome research at the ARS 

laboratory in Baton Rouge, as proposed before by the Administration. 

In addition to the maintenance of these ongoing efforts, we strongly urge the Subcommittee to provide at least $1 million in new funding through the ARS laboratories at Beltsville and Tucson, and possibly in conjunction with researchers at the 

University of California in Davis, to address a new threat to domestic honey bees: 

Colony Collapse Disorder (CCD). CCD is currently ravaging bee colonies across the 

United States. The causes of CCD are unknown and appear to be complicated mix 

of factors, including the stresses caused by continuing infestations of mites and 

pests and by the high demands of pollination today. I provide a more detailed description of CCD in this statement. 
728 

The President’s Budget Proposal 

Our understanding is that while OMB has not yet agreed to the ARS funding levels under the fiscal year 2007 Continuing Resolution, the most likely outcome will 

be a continuation of honey bee research at the fiscal year 2006 levels. As the Subcommittee reviews the proposed fiscal year 2008 budget and the fiscal year 2007 

baseline, we urge you also to consider that in its fiscal year 2007 bill, the House 

originally provided (H. Rep. 109–463) additional fiscal year 2007 research funding 

as follows: ‘‘Bee Research, Weslaco, TX, $244,077’’ and ‘‘Honey Bee Research (Varroa 

Mites), Baton Rouge, LA, $390,101.’’ The fiscal year 2007 Senate bill (S. Rep. 109– 

266) provided continued funding for ‘‘Bee Research (Chalk Brood)), Logan, Utah,’’ 

and separately recommended an increase of $100,000 for Logan, Utah for non-Apis 

research. 

The AHPA is concerned that the President’s fiscal year 2008 budget proposal to 

eliminate ongoing spending set by Congress would reduce funding for critical research at two key ARS Honey Bee Research Laboratories at Baton Rouge and at 

Weslaco. Such cuts to these ARS Honey Bee Research Laboratories would have a 

severe effect on the honey industry as well as on all pollination-dependent agriculture and many native plants. This budget recommendation seems particularly inappropriate considering the substantial benefits that flow from these research efforts, which help assure the vitality of the American honey bee industry and is integral to many aspects of U.S. agriculture. 

The four ARS Honey Bee Research Laboratories provide the first line of defense 

against exotic parasite mites, Africanized bees, and brood diseases. Equally, the laboratories are prepared to respond to new pests, pathogens and other conditions as 

they arise, such as CCD, that pose very serious and growing threats to the viability 

and productivity of honey bees and the plants they pollinate. If continued funding 

is not provided, scientists at the Baton Rouge and Weslaco laboratories will be overburdened and forced to discontinue essential research, thereby jeopardizing the U.S. 

honey bee industry and the production of agricultural crops that require pollination 

by honey bees. 

The Importance of Honey Bees to U.S. Agriculture 

Honey bees are a critical element in the production of more than 90 food, fiber, and seed crops, valued at more than $20 billion a year in the United States, according to the Department of Agriculture. The role of pollination is even more important 

given today’s dietary importance of fruit, vegetables and nuts, most of which are dependent on pollination. Honey bees are necessary for the production of such diverse 

crops as almonds, apples, oranges, melons, broccoli, tangerines, cranberries, strawberries, vegetables, alfalfa, soybeans, sunflower, and cotton, among others. In fact, 

honey bees pollinate about one-third of the human diet. 

The importance of this pollination to contemporary agriculture cannot be understated—the value of such pollination is 143 times greater than the total value of 

honey and wax produced by honey bees. More than 140 billion honey bees representing 2 million colonies are transported by U.S. beekeepers across the country 

every year to pollinate crops. 

The importance of honey bees—and the U.S. honey industry which supplies the 

honey bees for pollination—is illustrated by the pollination of California’s almond 

crop, which is that State’s largest agricultural export. California grows 100 percent 

of the Nation’s almond crop and supplies 80 percent of the world’s almonds. Honey 

bees are transported from all over the Nation to pollinate California almonds, which 

is the largest single crop requiring honey bees for pollination. More than one million 

honey bee hives are needed to pollinate the 600,000 acres of almond groves that line 

California’s Central Valley. That means nearly half of the managed honey-producing 

colonies in the United States are involved in pollinating almonds in California during February and early March. As with other agricultural products, having enough 

bees to pollinate the almond crop can mean the difference between a good crop and 

disaster. Moreover, almond producers estimate that California may need as many 

as 2 million hives for pollination by 2012 to pollinate the expected 800,000 acres 

of almonds that will be in production then. As OnEarth magazine noted recently, 

the fate of California’s almond crop rests ‘‘on the slender back of the embattled 

honey bee.’’ 

Many other U.S. agriculture producers rely on extensive honey bee pollination. A 

Maine blueberry grower recently put it quite succinctly—‘‘without bees in May, 

there are no blueberries in August.’’ Additionally, avocados—a $363 million crop in 

California—receive more than 90 percent of their pollination from the honey bee. 

Studies on the effect of pollination of cotton by honey bees show an increase of 17 

to 19 percent in the yield of seed cotton, as compared to a cotton crop that is not 

pollinated by honey bees. The cattle and farm-raised catfish industries also benefit 
729 

from honey bee pollination, as pollination is important for growing alfalfa, which is 

fodder for cattle and farm-raised fish. 

Unfortunately, due to bee losses caused by pests and mites and other recent problems plaguing the U.S. honey industry, U.S. farmers were forced to import honey 

bees from other countries (New Zealand and Australia) last year for pollination. 

This marked the first time since 1922 that honey bees were imported into the 

United States for pollination services, underscoring the fragile State of the U.S. 

honey industry and highlighting the critical need for research. 

Yet, the health of the beekeeping industry is dependent upon the production of 

honey and beeswax. Honey bees are responsible for the production of an average of 

200 million pounds of honey annually in the United States, the sales of which help 

sustain this nation’s beekeepers. 

THREATS TO THE HONEY BEES

Since 1984, the survival of the honey bee has been threatened by continuing infestations of mites and pests for which appropriate controls must continually be developed by scientists at the four ARS laboratories. Within the past year, however, CCD 

has emerged as an additional and grave new threat with unknown causes but destructive force. 

COLONY COLLAPSE DISORDER (CCD)

As chronicled in several recent news accounts, including the attached articles 

from the New York Times, CNN, ABC News and AP, reports of the sudden death 

of bees in colonies has been reported in 22 States. Often, most of the adult bees in 

a colony mysteriously disappear, and soon the colony is completely empty. The news 

outlets quote various Federal and State researchers who have not been able to determine the cause of the collapse of the colonies. There are also increasing reports 

that otherwise healthy bee colonies are not reproducing at anywhere near historic 

levels. 

This severe and baffling destruction of domestic honey bee populations will require additional resources for the ARS laboratories as soon as possible to determine 

the causes of CCD and to develop effective treatment strategies. CCD remains a 

mystery to both beekeepers and scientists. There are a wide range of factors that— 

either alone or in combination—may be possible causes of this serious condition. 

Areas to explore include the stress from the movement of bees to different parts of 

the country for extensive commercial pollination, the additional stress of pollinating 

crops, such as almonds, that provide little honey to the bees, and the impact of certain crop pesticides and genetic plants with altered pollination characteristics. Additionally, continuing infestations of the highly destructive Varroa mite, combined 

with other pests and mites, are also thought to compromise the immune systems 

of bees and may leave them more vulnerable to CCD. At the same time, researchers 

will need to focus on the many reported instances in which otherwise healthy, pestfree, stationary bee colonies are also suffering collapse or problems with reproduction. 

In many ways, CCD is the latest is a series of threats faced by the modern U.S. 

honey bee industry as it continues to evolve to both produce honey and meet the 

ever-increasing demands of crop producers for vital pollination. Unfortunately, CCD 

will not be the last challenge faced by the industry. But at this time, it is clearly 

the most critical threat to our industry. As every week goes by, additional members 

of AHPA report that CCD is affecting their bees. The AHPA respectfully requests that additional funding of at least $1 million be 

provided in a dedicated manner to respond to CCD. Such funding could be allocated 

to the ARS laboratories at Beltsville, Maryland, and Tucson, Arizona. We would also 

recommend that funding be considered for the University of California at Davis, because it has particular expertise in honey bee research and is in close proximity to 

the almond groves of the California Central Valley. Such a joint effort could better 

analyze the relationship between CCD, pollination and other stress factors. The 

joint effort would also take advantage of the fact that, in February of each year, 

almost the entire honey bee industry has its bees in California for pollination purposes. 

ONGOING RESEARCH

The research being done at the ARS laboratories is critical in a number of areas. 

For example, the pinhead-sized Varroa mite is systematically destroying bee colonies and has been considered by many in recent years to be the most serious threat 

to honey bees. Tracheal mites are another contributing factor to the loss of honey 

bees. Tracheal mites infest the breathing tubes of adult honey bees and also feed 
730 

on the bees’ blood. The mites essentially clog the bees’ breathing tubes, blocking the 

flow of oxygen and eventually killing the infested bees. The industry is also plagued 

by a honey bee bacterial disease that has become resistant to antibiotics designed 

to control it, and a honey bee fungal disease that has no known medication to control it. These pests and diseases, especially Varroa mites and the bacterium causing 

American foulbrood, are now resistant to chemical controls in many regions of the 

country. Further, we have seen that these pests are building resistance to newlydeveloped chemicals more quickly than in the past, thereby limiting the longevity 

of chemical controls. 

Unfortunately, there is no simple solution to these problems, and the honey bee 

industry is too small to support the cost of the needed research, particularly given 

the depressed state of honey prices. Further, there are no funds, facilities, or personnel elsewhere available in the private sector for this purpose. Accordingly, the 

beekeeping industry is dependent on research from public sources for the scientific 

answers to these threats. Since the honey bee industry is completely comprised of 

small family-owned businesses, it relies heavily on the ARS for needed research and 

development. The key to the survival of the honey industry lies with the honey bee 

research programs conducted by ARS. 

The sequencing of the honey bee genome at Baylor University has opened the door 

to creating highly effective solutions to these problems via marker-assisted breeding. 

Marker-assisted breeding would permit the rapid screening of potential breeders for 

specific DNA sequences that underlie specific desirable honey bee traits. The 

sequenced honey bee genome is the necessary key that will allow scientists to discover the important DNA sequences. Because of the sequenced honey bee genome, 

it is now possible to apply molecular biological studies to the development of marker-assisted breeding of honey bees. Marker-facilitated selection offers the first real 

opportunity to transform the beekeeping industry from one that has been dependent 

upon a growing number of expensive pesticides and antibiotics into an industry that 

is free of chemical inputs and that is economically viable in today’s competitive global marketplace. 

Furthermore, research on honey bees, one of five animals chosen by the National 

Institutes of Health for genome sequencing, may provide important insight into 

other areas of science. The honey bee is the first agricultural species to be 

sequenced, and such work may provide breakthrough advances in many areas of 

science. In fact, honey bees are being studied by the U.S. Department of Defense 

as sentinel species that could detect and locate agents of harm, such as chemical 

or biological threats. According to one researcher, it appears that honey bees’ olfactory capabilities are at least on par with those of a dog, if not more sensitive. Thus, 

the scientific advances achieved by ARS will provide an array of benefits across 

many disciplines. 

The Work of the ARS Honey Bee Research Laboratories 

The ARS Honey Bee Research Laboratories work together to provide research solutions to problems facing businesses dependent on the health and vitality of honey 

bees. The findings of these laboratories are used by honey producers to protect their 

producing colonies and by farmers and agribusinesses to ensure the efficient pollination of crops. Each of the four ARS Honey Bee Research Laboratories (which are 

different in function from the ARS Wild Bee Research Laboratory at Logan, Utah) 

focuses on different problems facing the U.S. honey industry and undertakes research that is vital to sustaining honey production and assuring essential pollination services in this country. Furthermore, each of the four ARS Honey Bee Research Laboratories has unique strengths and each is situated and equipped to support independent research programs which would be difficult, and in many cases impossible, to conduct elsewhere. 

Research at the ARS Weslaco Laboratory 

Because the AHPA recommends that the appropriation for the Weslaco laboratory 

be approved at not less than current levels, we respectfully request that Congress 

again restore an additional $244,100 in funding for the ARS Honey Bee Laboratory 

at Weslaco, Texas. This funding would be eliminated under the administration’s 

budget. Retaining the current level of funding for the Weslaco laboratory will enable 

this facility to continue its work in finding a chemical solution to parasitic mites 

that are causing a crisis for the U.S. beekeeping and pollination industries. Varroa 

mites are causing the loss of hundreds of thousands of domestic honey bee colonies 

annually as well as devastating wild bee colonies. As noted in a February 2005 USA 

Today article, the Varroa mite has destroyed as much as 60 percent of the hives 

in some areas. 
731 

For example, in Florida, the number of commercial bee colonies has fallen from 

approximately 360,000 hives in 1990 to just 160,000 in 2005—in large part as a result of the Varroa mite. These tiny parasites—also known as the ‘‘vampire mite’’— 

attach themselves to the backs of adult bees and literally suck out their insides. 

When these mites were first discovered in the United States in the 1980s, beekeepers were able to fight them with strips of the chemical fluvalinate. However, 

the Varroa mites have evolved into a parasite seemingly immune to current pesticides. The ARS laboratory at Weslaco has been developing alternative chemicals 

to control the Varroa mite. Presently, there are no other chemicals available for controlling the Varroa mite, and the laboratory is working frantically to develop other 

means of control. The laboratory also is working with a potent fungus, which may 

kill the mites without impeding colony development or population size. 

Furthermore, the laboratory at Weslaco is researching methods that may control 

the small hive beetle. Since its discovery in Florida in 1998, this pest has caused 

severe bee colony losses in California, Florida, Georgia, South Carolina, North Carolina, Pennsylvania, Ohio, and Minnesota. Estimates put these losses in just one season at over 30,000 colonies. The beetles are now spreading all across the United 

States. The ARS honey bee research scientists at the Weslaco laboratory have been 

working diligently to find chemicals, techniques, pheromones, or other methods of 

controlling the beetle. Time is of the essence and a control must be found immediately, because all the bee colonies in the Western Hemisphere are at risk. 

This facility also focuses its research efforts on developing technologies to manage 

honey bees in the presence of Africanized honey bees, parasitic mites, and other 

pests. In order to ensure that further pests are not introduced into the United 

States, scientists at the Weslaco facility provide technical assistance to agriculture 

departments in foreign countries on the control of parasitic mites. The laboratory 

has worked with officials in Guatemala, Costa Rica, Mexico, and South Africa to 

protect the U.S. honey bee population from further devastation by infestation of foreign parasites, diseases, and other pests. This inter-governmental cooperation is 

necessary to ensure the continued viability of the U.S. honey bee industry. 

Research at the ARS Baton Rouge Laboratory 

We were pleased with past Administration budgets that requested increased funding in the amount of $500,000 for honey bee genome research at the Baton Rouge 

Laboratory and applaud the Subcommittee’s efforts in fiscal year 2006 to provide 

$375,000 of the $500,000 requested. In light of the importance of genome research, 

we encourage the Committee to provide additional funds to move this area of research forward. An increase in funding will allow the vital genome research to 

achieve the breakthrough successes that are closer than ever to realization. 

It is also important that Congress fully restore the $390,101 in ‘‘add-on’’ funding 

for the Baton Rouge facility that it has provided in previous years. This Baton 

Rouge facility is the only laboratory in the United States and, we believe, in the 

world, developing long-term, genetic-based solutions to the Varroa mite. Existing 

stocks of U.S. honey bees are being tested to find stocks that exhibit resistance to 

the parasitic mites. Research scientists with the laboratory have also been to the 

far corners of the world looking for mite-resistant bees. For example, in eastern Russia, they found bees that have co-existed for decades with the mites and survived. 

Using these bees, the laboratory develops stocks of honey bees resistant to the 

parasites. Before these new stocks are distributed to American beekeepers, the laboratory ensures that the resistance holds up under a wide range of environmental 

and beekeeping conditions, testing attributes such as vigor, pollination, and honey 

production. We believe recent scientific breakthroughs with this genomic research 

will allow scientists in the near future to breed honey bees that are resistant to the 

Varroa mite and other parasites. 

The Baton Rouge facility also operates the only honey bee quarantine and mating 

station approved by the Animal and Plant Inspection Service. These stations are 

necessary to ensure that new lines of bees brought into the United States for research and development are free of diseases unknown in the United States. In addition, Baton Rouge research scientists are focused on the applications of new technologies of genomics. This work has the potential to enhance the proven value of 

honey bee breeding for producing solutions to the multiple biological problems that 

diminish the profitability of beekeeping. 

Research at the ARS Tucson Laboratory 

The American Honey Producers Association appreciates past Administration support for maintaining funding at the ARS Honey Bee Research Laboratory in Tucson 

at current levels. At the same time, consideration should be given to possibly increased funding at this facility to address the emerging CCD issue, and also to sup-
732 

porting two new research positions at the laboratory. The addition of an insect 

behaviorist position and a pollination biologist position at the Tucson Honey Bee Research Laboratory will strengthen the research programs conducted at the laboratory, including research related to preventing the spread of Africanized honey bees, 

which are jeopardizing the queen breeding and packaged bee industry. 

This research center is the only ARS honey bee laboratory serving the needs of 

beekeepers and farmers in the western United States. It also serves as the primary 

facility developing methods to prevent the spread of Africanized honey bees in our 

country. The facility works to improve crop pollination and honey bee colony productivity through quantitative ecological studies of honey bee behavior, physiology, pest 

and diseases, and feral honey bee bionomics. Currently, the Tucson laboratory is 

working to finalize the development of a pheromone that kills the Varroa mite. 

Because more than one million colonies are transported from across the country 

for pollination into crops grown in the western United States (primarily California), 

the Tucson research center addresses problems that arise from transporting and introducing colonies for pollination of crops such as almonds, plums, apricots, apples, 

cherries, citrus, alfalfa, vegetable seed, melons, and berries. The importance of this 

work is illustrated by the pollination of California’s almond crop discussed earlier 

in this statement. More than one million honey bee hives are needed to pollinate 

the half a million acres of almond groves that line California’s Central Valley. That 

means nearly half of the managed colonies in the United States are involved in pollinating almonds in California during February and early March. 

The work of the ARS Tucson Honey Bee Research Laboratory is indispensable in 

ensuring the successful pollination of crops in California and other areas of the 

western United States. This research center has been instrumental in disseminating 

information on technical issues associated with the transport of bee colonies across 

State lines. Additionally, in order to ensure that transported colony populations remain stable during transport and also during periods before the crop to be pollinated comes into bloom, scientists at the laboratory have developed an artificial diet 

that stimulates brood production in colonies. A large bee population is necessary to 

ensure that efficient pollination occurs, creating superior quality crops. 

Research at the ARS Beltsville Laboratory 

AHPA strongly supports an increase in funding for the Beltsville Laboratory to 

help address CCD and other threats to our domestic beekeeping industry. This facility, the oldest of the Federal bee research centers, conducts research on the biology 

and control of honey bee parasites, diseases, and pests to ensure an adequate supply 

of bees for pollination and honey production. Using biological, molecular, chemical, 

and non-chemical approaches, scientists in Beltsville are developing new, cost-effective strategies for controlling parasitic mites, bacterial diseases, and emergent pests 

that threaten honey bees and the production of honey. 

The laboratory also develops preservation techniques for honey bee germplasm in 

order to maintain genetic diversity and superior honey bee stock. Scientists at the 

facility also provide authoritative identification of Africanized honey bees and diagnosis of bee diseases and pests for Federal and State regulatory agencies and beekeepers on a worldwide basis. In operating this bee disease diagnosis service, the 

Beltsville facility receives over 2,000 samples annually from across the United 

States. 

Conclusion 

In conclusion, we wish to thank you again for your strong support of honey bee 

research in the past and for your Subcommittee’s understanding of the critical importance of these ARS laboratories. 

By way of summary, the American Honey Producers Association strongly encourages at least $1 million in additional new funding for the ARS laboratories at Beltsville, Maryland, and Tucson, Arizona, as well as possibly for the University of California at Davis, to address the new CCD threat that is suddenly devastating bee 

colonies across the country. AHPA also appreciates your continued support by (1) 

restoring the $390,101 in funding for the ARS Honey Bee Research Laboratory in 

Baton Rouge, Louisiana, that had previously been added by the Congress but is proposed for elimination in the Administration’s budget proposal; (2) continuing the increased funding of $375,000 for genome research at the ARS Honey Bee Research 

Laboratory in Baton Rouge, as proposed by the administration and approved by the 

Congress in fiscal year 2006; (3) increasing the level of funding for the ARS Honey 

Bee Research Laboratory in Beltsville, Maryland, by at least $500,000 in new funding for CCD research; (4) restoring $244,100 for the Weslaco, Texas, facility as previously provided by the Congress but not contained in the President’s budget submission; (5) maintaining at least the current level of funding for the ARS Honey Bee 
733 

Research Laboratory in Tucson, Arizona, but also considering additional funding of 

$500,000 for CDC research; and (6) maintaining the current level of funding for the 

ARS Wild Bee Research Laboratory at Logan, Utah. 

Only through research can we have a viable U.S. beekeeping industry and continue to provide stable and affordable supplies of bee-pollinated crops, which make 

up fully one-third of the U.S. diet. 

Furthermore, we urge you to reject any effort to cut the operating budgets of these 

vitally important research laboratories by consolidating their functions. Any proposed cuts and their resulting budget and staff reductions would significantly diminish the quality of research conducted by these laboratories, harming bee keepers as 

well as farmers who harvest pollination-dependent agriculture. Congress cannot 

allow these cuts to occur and must continue to provide sufficient funding for the 

ARS Honey Bee Research Laboratories to perform their vital role. 

I would be pleased to respond to provide answers to any questions that you or 

your colleagues may have. 

PREPARED STATEMENT OF THE AMERICAN SHEEP INDUSTRY ASSOCIATION

The American Sheep Industry Association (ASI) is a federation of State member 

associations representing over 68,000 sheep producers in the United States. The 

sheep industry views numerous agencies and programs of the U.S. Department of 

Agriculture as important to lamb and wool production. Sheep industry priorities include expanding the United States sheep inventory which has grown two of the past 

3 years. We believe strengthening the infrastructure of the industry primarily 

through the programs of USDA, APHIS, Veterinary Services and Wildlife Services 

is critical. The industry and the benefits to rural communities will be strengthened 

by fully funding critical predator control activities, national animal health efforts, 

and expanding research capabilities. 

We appreciate this opportunity to comment on the USDA fiscal year 2008 budget. 

ANIMAL AND PLANT HEALTH INSPECTION SERVICE (APHIS)

Scrapie 

The American Sheep Industry Association supports the appropriations approved in fiscal year 2006 of $18.4 million and urges the Subcommittee increase funding 

to this level in fiscal year 2008. 

Through concerted effort, USDA/APHIS, along with industry and State regulatory 

efforts, is in the position to eradicate scrapie from the United States with a multiyear attack on this animal health issue. As the collective and aggressive efforts of 

Federal and State eradication efforts have expanded into slaughter-surveillance and 

other methods and systems, the costs are, as expected, escalating. 

Scrapie is one of the families of transmissible spongiform encephalopathies 

(TSEs), all of which are the subject of great importance and interest around the 

globe. USDA/APHIS, along with the support and assistance of the livestock and allied industries, began an aggressive program to eradicate scrapie in sheep and goats 

four years ago. The plan USDA/APHIS is implementing is designed to eradicate 

scrapie by 2010. Through a subsequent monitoring and surveillance program, the 

United States could be declared scrapie-free by 2017. Becoming scrapie-free will 

have significant positive economic impact to the livestock, meat and feed industries 

and, of course, rid our flocks and herds of this fatal animal disease. 

Essential to the eradication effort being accomplished in a timely manner is adequate appropriated funds. The program cannot function properly without sufficient 

emphasis on diagnostic support and surveillance activities that are dedicated to 

scrapie eradication as an animal health priority. We believe adequate funding will 

help provide for an achievable scrapie eradication program and the eventual scrapiefree status for the United States. As with the other successful animal disease eradication programs conducted by USDA/APHIS in the past, strong programs at the 

State level are key. We therefore urge the Subcommittee to send a clear message 

to USDA/APHIS to (A) make scrapie eradication a top disease eradication priority 

within USDA and the APHIS field staff with a focus on ID compliance and enforcement; and (B) increase the slaughter-surveillance numbers so that the disease can 

be found and dealt with where it resides. 

Wildlife Services 

With well over one-quarter million sheep and lambs lost to predators each year, 

the Wildlife Services (WS) program of USDA–APHIS is vital to the economic survival of the sheep industry. The value of sheep and lambs lost to predators and 

predator control expenses are second only to feed costs for sheep production. Costs 
734 

associated with depredation currently exceed our industry’s veterinary, labor and 

transportation costs. 

Wildlife Service’s cooperative nature has made it the most cost effective and efficient program within the Federal Government in the areas of wildlife management 

and public health and safety. Wildlife Services has more than 2,000 cooperative 

agreements with agriculture, forestry groups, private industry, State game and fish 

departments, departments of health, schools, county and local governments to mitigate the damage and danger that the public’s wildlife can inflict on private property 

and public health and safety. 

ASI strongly supports the fiscal year 2006 appropriations for Wildlife Services operations and methods development programs, particularly as related to livestock 

protection. We ask the Subcommittee to fund the livestock industry request for the 

western region of Wildlife Services operations of livestock protection at $19 million. 

The line item of the fiscal year 2006 appropriations for the livestock protection 

program in the western region of WS was funded at $10.7 million, an increase of 

$700,000 which is very important to our industry and the agency operations. Fuel 

costs alone for aerial operations and ground vehicles have increased dramatically 

which burdens the operations budgets. 

The additional $8.3 million increase requested will increase the effectiveness of 

the livestock protection program. Federal funding available for livestock predation 

management by the Western Region program has remained relatively constant for 

approximately 16 years. WS program cooperators have been forced to fund more and 

more of the costs of the program. WS Western Region base funding has increased 

only 5.6 percent in the past 10 years while cooperative funding has increased 110 

percent. This increase has primarily come from individual livestock producers, associations, counties, and States. 

Additionally, new Federal mandates and program investments such as narrowbanding of radios, computer record keeping and compliance with the Endangered 

Species Act are requiring a larger portion of the already stretched budget and negatively impacting the amount of livestock predation management work that WS can 

conduct. 

We encourage and support continued recognition in the appropriations process for 

fiscal year 2007 of the importance of aerial hunting as one of Wildlife Service’s most 

efficient and cost-effective core programs. It is used not only to protect livestock, 

wildlife and endangered species, but is a crucial component of the Wildlife Services 

rabies control program. 

Similar to the increasing needs in the aerial hunting program, we encourage continued emphasis in the programs to assist with management of wolf depredation in 

the States of Montana, Idaho, Wyoming, Minnesota, Wisconsin, Michigan, New Mexico and Arizona. Additionally, program expenses are expected in the States surrounding the Montana, Idaho and Wyoming wolf populations. It is strongly supported that appropriations be provided for $586,000 for additional wolf costs anticipated in Washington, Oregon, Nevada, Utah, Colorado and North Dakota. 

Economics of Predation Management 

The WS Western Region predation management program is one of the few government sponsored programs that is cost-shared, and this provides a significant benefit 

to both the producers and the government. Predation management, as conducted by 

the WS program, is cost effective and returns more money to the U.S. treasury than 

it costs. An analysis of 1998 data shows that for every dollar spent for predation 

management, $3 worth of livestock was saved. In that same year the total investment in just the predation management program was $20 million ($9 million Federal and $11 million cooperative funds); therefore, the full impact of this investment 

was a $250 million net increase in economic activity. Using today’s values for livestock, every Federal dollar spent on predation management results in $10.84 in livestock saved, conservatively, $97.5 million in livestock saved ($52.5 million in calves, 

$34 million in sheep and lambs, $11 million in goats). When cooperative funding is 

included with federal funds, the benefit cost ratio is $4.87:1. 

Type of Livestock No protected No saved from 

predators 

Total value of 

livestock saved 

Calves ........................................................................................................ 2,500,000 70,000 $52,500,000 

Adult Sheep ................................................................................................ 2,000,000 82,000 8,200,000 

Lambs ........................................................................................................ 1,850,000 214,600 25,752,000 

Goats .......................................................................................................... 292,000 110,960 11,096,000 
735 

The value of livestock saved is much greater in rural economies than any other 

type of economic development. Livestock dollars, that would have been lost without 

adequate predation management, generate an additional three fold increase in nonagricultural economic activity in rural America. The total economic activity (both agriculture and non-agricultural sectors) generated by predation management is 

$390.2 million. 

Emerging Issues 

Additional issues are emerging in the West that will challenge the Federal WS 

program. 

—Wolves.—Recently a Federal judge struck down the threatened species status 

for wolves in the Western Distinct Population area eliminating the ability of 

private land ranchers to deal with wolves, thus requiring additional government 

intervention. 

—Wildlife.—The declines in predation management that have already occurred, 

and that will continue to occur without additional Federal funding, have resulted in negative impacts on many native wildlife populations. Several western 

States currently need to fund predation management to prevent the listing of 

sage grouse as an endangered species or to recover mule deer herds. 

Without additional Federal funding to support existing western livestock protection programs, predation management expertise will be lost and livestock grazing 

in some areas will be jeopardized. Rural economies need this support and the return 

for the investment exceeds the requested assistance. 

ASI urges the Subcommittee to provide USDA, APHIS, WS, Western Region an 

additional $8.3 million of Federal funds for livestock protection. At a nominal 16 

percent tax rate on the economic activity generated by the investment would result 

in over $62 million to the Treasury. 

Total Livestock Protected ..................................................................................................................................... 6,642,000 

Total Value of Livestock Saved (Using $10.84:1 Ratio) ..................................................................................... $97,548,000 

Value incl. Multiplier ............................................................................................................................................ $390,192,000 

16 percent Nominal Tax rate ............................................................................................................................... $62,430,720 

CHART 1.—Ten Year Comparison—WR Federal Base and Cooperative Funds 

(Including Livestock Protection) 

FARM AND FOREIGN AGRICULTURAL SERVICES

Foreign Agricultural Service (FAS) 

The sheep industry participates in FAS programs such as the Market Access Program (MAP), Quality Samples Program (QSP) and the Foreign Market Development 

Program (FMD). ASI strongly supports appropriations at the full authorized level 

for these critical Foreign Agricultural Service programs. ASI is the cooperator for 

American wool and sheep pelts and has achieved solid success in increasing exports 

of domestic product. Exports of American wool have increased dramatically with approximately 60 percent of U.S. production now competing overseas. 
736 

Risk Management Agency (RMA) 

Through ASI, the U.S. sheep industry is working with RMA on the development 

of ‘‘Livestock Risk Protection’’ for lamb (LRP-Lamb), a model-based, price-risk insurance product to help sheep producers manage the primary factor in their operation’s 

financial exposure. The sheep industry is very anxious to participate in a 27 State 

pilot project with LRP-Lamb as approved in September of 2006. The goal is a market-based, user-friendly risk management tool that effectively and efficiently protects against unexpected price downswings that provides producers and their lenders with a critically needed financial management option. 

ASI urges the Subcommittee to support the agency’s research and developmental 

costs to design creative new programs for the livestock sector as well as in the ‘‘Administrative and Operating Expenses’’ category to enable RMA to deliver these products, including appropriate maintenance expenses. 

NATURAL RESOURCES CONSERVATION SERVICE (NRCS)

ASI urges increased appropriations for the range programs of the Soil Conservation Service to benefit the private range and pasture lands of the United States with 

conservation assistance. We support the budget item and recommend an increased 

level for the Grazing Lands Conservation Initiative, which ASI has worked with, 

along with other livestock and range management organizations to address this important effort for rangelands in the United States. 

RESEARCH, EDUCATION AND ECONOMICS

Our industry is striving to be profitable and sustainable as a user of and contributor to our natural resource base. Research, both basic and applied, and modern 

educational programming is essential if we are to succeed. We have been disappointed in the decline in resources USDA has been targeting toward sheep research and outreach programs. In order for the sheep industry to continue to be 

more globally competitive, we must invest in the discovery and adoption of new 

technologies for producing, processing and marketing lamb and wool. We urge the 

Subcommittee to send a strong message to USDA supporting sheep research and 

educational funding increases. 

Agricultural Research Service 

We continue to vigorously support the administration’s funding of research concerning emerging and exotic diseases. Emerging and exotic diseases continue to 

have significant impact on our industry due to animal health and trade issues. The 

animal disease portion should be substantial and is urgently needed to protect the 

U.S. livestock industry. We note the President’s request for fiscal year 2007 includes 

$9.5 million for BSE and CWD research. We agree that BSE has been an extremely 

important disease issue; however it is well established that BSE is being controlled 

globally and research has shown that since BSE is not transmitted by casual contact, actual disease concerns regarding BSE in the United States should be minimal. 

With this in mind, we respectfully remind the Subcommittee that scrapie along with 

CWD are Transmissible Spongiform Encephalopathies that are endemic in the 

United States and unlike BSE are transmitted by casual contact. We recommend 

that any additional funds for BSE and CWD research also address scrapie with emphasis toward scrapie eradication needs (detection and control methods). We also respectively remind the Subcommittee that scientists in the Animal Disease Research 

Unit (ADRU), ARS, Pullman Washington, have made significant progress in the 

early diagnosis of TSEs, in understanding genetic resistance to TSEs and in understanding mechanisms of TSE transmission, which are important in eradication of 

all TSEs. The programs of these scientists at ADRU should be enhanced and expanded to include, for instance, the development of further improvements in rapid 

and accurate TSE detection methods and to provide an understanding of the role 

of other small ruminants as environmental sources of the TSE agent in the transmission of TSEs within the United States and world and to further understand the 

basis of genetic resistance and susceptibility to these devastating diseases. 

We note and strongly support the ARS 2008 priority initiative (3.8 million) entitled ‘‘Functional Genomics to Improve Nutrient Utilization in Beef Cattle’’. Due to 

the extreme importance of this approach to enhancing the economics of sheep production and the recent progress in acquiring the sheep genome, we respectively request that this initiative be expanded to include sheep genomics. Since 2001, Congress has had the foresight to appropriate $756,553 each year to this unit for ‘‘Microbial Genomics.’’ Microbial genomics is the cornerstone project for their genomic 

research infrastructure and has resulted in very important genomics based research 

advancements for infectious diseases of livestock such as Ovine Progressive Pneu-
737 

monia virus (OPPV), caseous lymphadenitis and foot rot. OPPV, caseous lymphadenitis and foot rot cause infections and environmental contaminations that continue 

to have significant economic impact for U.S. sheep producers. Also, pneumonia of 

big horn sheep continues to be a major concern for the domestic sheep industry. 

Regulatory impact on the use of public lands by domestic sheep producers due to 

the perceived possibility of disease transmission events between big horn and domestic sheep continues to be significant. Most recently genomics based research has 

yielded advancements in the understanding of the pneumonia complex affecting big 

horn sheep. This research is consistent with the ARS 2008 priority initiative (4.9 

million) entitled ‘‘Livestock Immunology and Microbial Genomics to Improve Animal 

Health’’. Very promising on-going genomic research efforts are directed at early determination of which sheep are susceptible to disease and responsible for economic 

losses. High throughput genomics has ushered in a new era of integrated research 

regarding the ability to link control of chronic, economically important diseases such 

as OPPV and important production traits. There are a number of infectious diseases 

across domestic and wild animals that will benefit from this research focus. It is 

becoming clear that not all infected animals transmit diseases with equal efficiency; 

in fact it appears that the ‘‘super shedders’’ are a small proportion of an infected 

population. In addition to aiding in the control of chronic infectious diseases such 

as OPPV, caseous lymphadenitis and foot rot, control of Big Horn Sheep pneumonia 

and internal parasitism may well be aided by this genomics approach. Early detection of susceptibility and resistance will lead to practical intervention strategies. We 

respectively request the Subcommittee to recommend the restoration and enhancement of microbial genomics to ADRU for the fiscal year 2008 budget. With this in 

mind, we respectively request the subcommittee to recommend restoration of the 

$764,195 and enhancement of the microbial genomics budget of ADRU by $900,000 

to a total of $1,664,195 to use in collaboration with the University of Idaho, Washington State University and the U.S. Sheep Experiment Station in Dubois and other 

collaborators to expand research concerning causation and transmission of the pneumonia complex of big horn sheep and link predictive genomics based tests with the 

genetics of production. 

We also urge the Subcommittee to recommend the restoration of $484,292 for Malignant Catarrhal Fever (MCF) at the ARS/ADRU in Pullman for the fiscal year 

2007 budget. MCF is a viral disease of ruminants that is of great concern to our 

livestock industries. The exotic variant of MCF is considered a high priority select 

agent. This funding is provided for collaborative research with the U.S. Sheep Experiment Station, Dubois ID and the University of Idaho, for vaccine development 

directed at preventing transmission and economic losses caused by MCF. 

Research into Johne’s disease has received additional funding through ARS over 

the past several years with a focus on cattle. Johne’s disease is also endemic in the 

U.S. sheep population and is not well understood as a sheep disease. The same food 

safety concerns exist in both sheep and cattle; other countries are also very concerned about Johne’s in sheep. We urge the Subcommittee to send a strong message 

to ARS that Johne’s disease in sheep should receive more attention with an emphasis on diagnostics. 

We appreciate and support USDA’s strategic goals and note that strategic goal (3) 

‘‘Enhance Domestic Rural and Farm Economies States in part as follows: ‘‘Work to 

expand production and market opportunities for bioenergy and biobased products’’. 

In response to this strategic goal of the USDA we request that the Subcommittee 

recommend $350,000 as a targeted increase for ARS/ERRC research at Wyndmoor, 

PA to be directed toward research on wool at the molecular level focusing on antimicrobial properties, flame retardation and enhancement of fiber properties through 

enzyme treatments targeting high priority military needs and other niche market 

applications for consumers. 

Cooperative State Research, Education, and Extension Service (CSREES) 

The Minor Use Animal Drug Program is funded through a ‘‘Special Research 

Grant’’ that has had great benefit to the U.S. sheep industry. The research under 

this category is administered as a national program ‘‘NRSP–7’’ cooperatively with 

FDA/CVM to provide research information for the approval process on therapeutic 

drugs that are needed. Without this program, American sheep producers would not 

have effective products to keep their sheep healthy. We appreciate the fiscal year– 

2006 funding level of $582,000 for this program, and we urge the Subcommittee to 

recommend that it be funded at least at this level in fiscal year 2008 to help meet 

the needs of our rapidly changing industry and increasing costs for research necessary to meet the requirements for approving additional therapeutics for sheep. 

On-going funding for the Food Animal Residue Avoidance Databank (FARAD) program is critically important for the livestock industry in general and especially for 
738 

‘‘minor species’’ industries such as sheep where extra-label use of therapeutic products is more the norm rather than the exception. We urge the Subcommittee to recommend that it be funded at least at the fiscal year 2006 level of $806,000 in 2008 

to help meet the needs of the animal industries. FARAD provides veterinarians the 

ability to accurately prescribe products with appropriate withdrawal times protecting both animal and human health. 

On-going research to improve value quantification and marketing of wool is critically important to the sheep and wool industry. ASI urges the Subcommittee’s support to restore and continue the CSREES special grants program for wool research 

at least to the fiscal year 2006 level of $298,000 for fiscal year 2008. 

Research for the Montana Sheep Institute is important to the sheep and wool industry. Sheep grazing is being used as an important tool for natural resource management to improve the competitiveness of lamb and wool in the marketplace and 

reduce the impacts of invasive plant species. ASI encourages the Subcommittee’s 

support to continue funding at the fiscal year 2006 level of $591,000 for 2008. 

The Livestock Marketing Information Center (LMIC) is a unique and very effective cooperative effort. This is not a State specific effort; it operates as a national 

virtual ‘‘Center of Excellence’’ for Extension education, research, and public policy. 

Members of the LMIC represent 26 Land Grant Universities, 6 USDA agencies, and 

a variety of associate institutions. In conjunction with the USDA’s Economic Research Service (ERS), this cooperative effort started in the mid-1950’s. This effort 

is an integral part of U.S. livestock marketing and outlook programs for cattle, hogs, 

sheep, dairy and poultry. Demands on the LMIC staff continue to increase from 

other USDA agencies, Land Grant Universities, State governments, commodity associations and directly from producers. We strongly support funding be continued 

at least at the previously funded level of $194,000 for the Livestock Marketing Information Center (LMIC) in fiscal year 2008. The coordinating office for this national Land Grant University directed effort is located in Lakewood, Colorado. As 

in the past, line-item funding will be directed through the USDA CSREES. 

The Joe Skeen Institute for Rangeland Restoration is an on-going collaborative research program with Texas A&M University, New Mexico State University and 

Montana State University. Federal support is sought to help correct critical degradation of public lands, especially desertification of rangelands through research 

and education. 

The rangelands of the United States have been degraded for decades impacting 

water runoff and production of amenities enjoyed by the general public. Innovative 

methods for control of invasive plants though goats and sheep are providing biological solutions while improving the environment. We urge the Subcommittee to support the Institute at $2 million for fiscal year 2008. 

Grants to Train Farm Workers in Technologies and Specialized Skills Necessary for 

Higher Value Crops 

The shortage of skilled sheep shearers has increasingly become a problem for U.S. 

sheep producers and strong interest has been expressed in utilizing this grant program through USDA as authorized in section 6025 of the 2002 Farm Security and 

Rural Investment Act. Grant funds are authorized; however appropriations would 

be necessary for the program to allow the U.S. sheep industry the opportunity to 

apply for funds to train U.S. workers as sheep shearers. 

PREPARED STATEMENT OF THE AMERICAN SOCIETY FOR MICROBIOLOGY

The American Society for Microbiology (ASM) is pleased to submit the following 

testimony on the fiscal year 2008 appropriation for the U.S. Department of Agriculture (USDA) research and education programs. The ASM is the largest single life 

science organization with more than 42,000 members. The ASM mission is to enhance the science of microbiology, to gain a better understanding of life processes, 

and to promote the application of this knowledge for improved health and for economic and environmental well-being. 

The ASM is concerned with the fiscal year 2008 proposed budget of approximately 

$2 billion for agricultural research and development, a $245 million decrease from 

fiscal year 2007, and a $428 million cut from fiscal year 2006. The steady decline 

in Federal funding for agricultural research will have detrimental effects on both 

public health and the Nation’s economy. Agricultural research is critical to USDA’s 

role in oversight of domestic and imported food production to ensure a safe food supply and to the Nation’s stake in domestic and global markets. In 2006, U.S. agricultural exports reached a record $71 billion, an $8 billion increase over 2005. There 

are strong correlations between food safety, food markets, and the U.S. economy. 
739 

The estimated costs of five foodborne bacterial diseases alone total nearly $7 billion 

per year, with more than $71 million just for E. coli O157 in contaminated ground 

beef. Recent outbreaks of disease linked to spinach and peanut butter and subsequent product recalls illustrate the effects of contaminated food on private sector 

markets. 

The ASM asks Congress to increase support for the USDA Agricultural Research 

Service (ARS), the lead scientific agency that conducts intramural research, and the 

USDA National Research Initiative (NRI), the competitive, peer-reviewed grants 

program that supports extramural research. USDA research efforts in food safety, 

climate change, crop production, alternative fuels, the environment and other strategic areas are producing tangible returns on past federal investments. U.S. agricultural output has more than doubled in the last 50 years, attributed by economists 

almost entirely to increased productivity by U.S. producers who benefit from the Nation’s investment in research and technology. Genetic improvements, for example, 

have accounted for half the yield gains in major cereal crops since the 1930s. The 

net gain from crop genetics research is estimated to be about $385 million per year 

in the United States and more than $600 million globally. The world’s population 

likely will reach 9 billion by about 2050 but agricultural experts foresee shortfalls 

in cropland expansion for food production, thus the increased food supply will need 

to come from enhanced yields based on basic and applied research. 

The President’s fiscal year 2008 budget request would reduce funding for the ARS 

by 11 percent from fiscal year 2007 and fiscal year 2006. The ASM urges Congress 

to provide at least $1.15 billion for the ARS in fiscal year 2008, the same level as 

fiscal year 2007 and fiscal year 2006. The President proposes funding the NRI at 

$257 million in fiscal year 2008, an increase of $67 million over fiscal year 2007; 

however, $61 million of the increase will be allocated to the integrated programs 

transferred into the NRI and biofuel research, providing the NRI with an actual increase of only $6 million for its base programs. 

Food Safety 

Strong support for the NRI and ARS is needed to provide the fundamental research essential to creating efficient and accurate technologies for the protection of 

human health and agricultural quality. This research is critical considering there 

are approximately 76 million foodborne illness cases in the United States per year. 

The United States has recently suffered from several bacterial foodborne illness outbreaks, including a widespread E. coli outbreak in spinach last summer that 

sickened more than 200 people and killed three. Several other outbreaks of salmonella and E. coli also occurred last year. The most recent problem resulted in a 

large recall of all Peter Pan and certain Great Value peanut butter contaminated 

with salmonella. 

Recently, USDA supported scientists identified a safe and effective new sanitizer 

(acidified sodium chlorite, or SANOVA) that achieved a 5-log reduction of E. coli 

O157:H7, Listeria monocytogenes, and Salmonella on produce even in the presence 

of large organic loads. The researchers optimized sanitation treatment procedures 

to ensure good quality of shredded carrot and fresh-cut lettuce while maintaining 

the effective killing power of the sanitizer. 

Because livestock and poultry are often the original source of pathogens (even in 

the case of produce-borne outbreaks), additional research is needed to strengthen 

production safeguards that can protect animal and human health. Other ARS research groups have been developing interventions using bacteriocins (natural antimicrobial agents) and bacteriophage (bacteria-killing agents) that upon commercialization will contribute to a reduction in campylobacter on chicken, leading to 

greater food safety. 

Additionally, there is concern that some food borne bacterial pathogens may become resistant to certain antimicrobial agents. It is necessary to have continued 

support for antimicrobial resistance monitoring programs, such as the National 

Antimicrobial Resistance Monitoring System (NARMS) the Collaboration on Animal 

Health Food Safety Epidemiology (CAHFSE) program to generate data that will 

guide appropriate interventions in the food production chain to minimize and contain antimicrobial resistant bacterial pathogens in the food supply. 

Through the Food Safety and Inspection Service (FSIS) and the Animal and Plant 

Health Inspection Service (APHIS), the USDA is ensuring the Nation’s food quality, 

providing safety interventions, and contributing to pathogen reduction. The ASM 

supports the President’s fiscal year 2008 requested increases above fiscal year 2007 

of 4.8 percent and 35.4 percent for FSIS and APHIS respectively. 

In 2002, the import share of total U.S. food consumption was 13 percent and continues to grow today. As agricultural imports increase, it is important to develop 

better systems to screen produce and other food imports at the borders. Federal sup-
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port of research is needed to develop better methods for rapid detection, sampling, 

and intervention to protect the public from food borne pathogens. 

Bioeconomy Based Systems 

Agricultural research is a critical component of discovering biobased products such 

as polymers, lubricants, solvents, composites, and energy. The USDA research programs expand science-based knowledge and technologies to support the efficient, economical and environmentally friendly conversion of biomass, more specifically agricultural and municipal residuals into value-added industrial products and biofuels. 

Microbial research is essential to understanding and thus creating efficient conversion and production methods of biomass. 

As research in the area of biofuels and bioenergy expands, it also affects other 

aspects of food production such as the fact that corn prices for livestock will increase 

as more is diverted to biofuel production potentially affecting the food supply, exports, and agricultural practices overall. The ASM urges the USDA to expand further the research programs on alternative bioenergy production to explore new resources and methods that would not compete with the food system, such as cellulose-based fermentation. 

The ASM notes that more research is needed to understand the impact that removing biomass for energy and other products has on the sustainability of soils and 

water. Since soil sustainability is intrinsically linked to the microbial health of the 

soil, and the health of soil can directly affect its ability to filter and clean water, 

a greater understanding of soil microbiology is essential to ensuring sustainability. 

Greater support for the NRI and ARS is essential to address the challenges of the 

emerging biobased industry with programs that support research, development and 

demonstration. 

Climate Change 

One of the most pressing issues faced by plant and animal producers is adapting 

to the impact of global change and climate on crop or animal production. Changing 

climate may alter bacterial and fungal pathogen pressures on plant and animal production and nutrient cycling and availability. Agriculture can contribute to a reduction in greenhouse gases that are microbial driven. The agricultural community 

needs scientific information for planning and decision making, to ensure economic 

viability. Scientific information on global change and climate and its impacts on 

soils, water, air, microbial biology, as well as plant and animal biology, and the general environment will produce robust simulation models to provide guidance on the 

relative benefits associated with agronomic decisions. 

Current NRI-funded weather and climate projects focus on determining the effects 

of global change and climate on land-based systems and the global carbon cycle and 

on identifying agricultural and forestry activities that can help reduce greenhouse 

gas concentrations. Research can help identify, describe, and quantify processes involved in the cycling of organic and inorganic carbon in soil. Strong support of NRI 

is needed to develop new tools for accurately measuring greenhouse gases, methods 

for measuring and estimating carbon in ecosystems at different scales, and effective 

ways to sustain productivity in a changing environment. Information from this research can be used to achieve national goals on carbon dioxide and methane emissions reductions. 

Genomics 

The Microbial Genome Sequencing Program has been supported jointly by the 

NRI and the National Science Foundation (NSF) since fiscal year 2001. The program supports high-throughput sequencing of the genomes of a broad range of 

microorganisms and the development and implementation of strategies, tools, and 

technologies to make currently available genome sequences more valuable to the 

user community. Over 100 microbial genomes have been sequenced to date because 

of this program. The broad availability of these sequences has led to important insights into how the structure and content of microbial genomes affect the ability of 

microorganisms to function and adapt to the environments in which they live. The 

USDA/CSREES and NSF Microbial Genome Sequencing Program will lead to improved breeding strategies, increased disease resistance, and enhanced yield and nutritive value of agriculturally important plants and animals. The ASM urges Congress to provide strong support for the USDA genomics initiative. 

Soil Processes 

Microbial research is essential in protecting the Nation’s natural resources, soil 

and water, and the subsequent impact on the supply and quality of food. The NRI 

is currently supporting research that will potentially lead to an effective treatment 

to entrap, remove, or inactivate cryptosporidia oocysts, which persist in soil and 
741 

water. Cryptosporidia are a potentially fatal protozoan that infects humans, livestock, and wildlife. When an effective control mechanism is developed, it may prove 

to be effective in dealing with all pathogens, including Salmonella, enteric bacteria, 

and viruses. The ASM urges Congress to increase support for the NRI to continue 

and expand on opportunities in soil processes research that is critical for the health 

and well-being of the Nation. 

Workforce Development and Training 

Studies project that over the period 2005–2010, employment opportunities for U.S. 

college graduates with expertise in the food, agricultural, and natural resources systems are expected to average over 52,000 openings per year, with some 49,300 qualified graduates available each year for these positions; with approximately 32,300 

new graduates available from the U.S. colleges of agriculture and life sciences, forestry, and veterinary medicine and 17,000 qualified graduates from allied higher 

education programs such as biological sciences, engineering, business, health 

sciences, communication, and applied technologies will be available. It is essential 

to foster programs that assess what the future workforce demands will be in agricultural research and contribute to workforce development and training to meet these 

demands. 

The ASM urges Congress to increase support for the NRI. As grant applications 

have increased, and funding has remained flat essentially for the last 4 years, young 

scientists are discouraged by the low funding rate of just 16 percent. Increasing 

funding for the NRI will increase the funding rate, providing greater opportunity 

for young scientists. 

Conclusion 

The ASM urges Congress to increase research funding for the USDA. The 2002 

Farm Bill stated the sense of Congress to double funding for agriculture research 

over the next 5 years. The ASM is concerned that we are losing ground in the important field of agricultural research, just as the challenges the Nation faces in competitiveness, food safety, energy, and climate change, places more emphasis on the 

need for greater research to answer these demands. 

The ASM appreciates the opportunity to provide written testimony and would be 

pleased to assist the Subcommittee as it considers the fiscal year 2008 appropriation 

for the USDA. 

PREPARED STATEMENT OF THE AMERICAN SOCIETY FOR MICROBIOLOGY

The American Society for Microbiology (ASM) appreciates the opportunity to comment on the fiscal year 2008 budget submission for the Food and Drug Administration (FDA). The ASM is the largest single life science Society with over 42,000 members, who work in academic, clinical, government and industry laboratories and are 

involved in research and diagnostic testing. The Society has a special interest in the 

activities of the FDA which are critical to safeguarding the health and welfare of 

the public. The ASM supports an increase in funding for FDA activities, which are 

expanding because of scientific innovations, rapid globalization and new and reemerging diseases. The ASM urges that the FDA budget be increased and specifically recommends a significant increase for FDA Food Safety activities. An increase 

in the FDA budget will better equip the agency to address new public health issues 

and additional funding for food safety programs will help to protect the safety and 

quality of food consumed in the United States. 

The FDA has enormous responsibilities that affect the public every day. About 20 

percent of consumer spending in the United States buys FDA regulated products, 

an annual expenditure of nearly $1.5 trillion. The FDA plays a critical role in overseeing and evaluating new products with significant potential to greatly improve 

public health and reduce costs to society. Annual spending on health care in the 

United States reached nearly $2 trillion in 2005. Last year, FDA approved an array 

of new cost containing medical advances, including vaccines to fight cervical cancer, 

shingles, and gastroenteritis. FDA scientific and support staff must be prepared to 

respond to disease outbreaks, like those recently linked to contaminated salad 

greens and peanut butter. It is essential that FDA receive the federal funding which 

it needs to meet its changing and expanding regulatory responsibilities. 

The proposed fiscal year 2008 budget for FDA includes $1.64 billion in budget authority and nearly $444 million to be collected as industry user fees, an overall 6.8 

percent increase above the fiscal year 2007 request. The fiscal year 2008 budget authority includes a net increase of $95.3 million to subsidize high priority initiatives 

identified as crucial by the FDA and external reviewers. The ASM agrees that this 

is a justifiable and wise investment in these priority initiatives, which include 
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strengthening food safety, modernizing FDA drug safety programs, and assuring 

FDA expertise and infrastructure upgrades. 

Strengthening Food Safety 

Foodborne disease continues to be a problem in the United States. In 2006, FDA 

investigators helped pinpoint the sources of pathogens in familiar products sold at 

grocery stores and restaurants, by testing contaminated spinach and lettuce, oysters, and peanut butter. More than 250 foodborne illnesses are recognized by the 

FDA’s Center for Food Safety and Applied Nutrition (CFSAN). Federal officials estimate that each year about 76 million become sick, more than 300,000 are hospitalized, and 5,000 die from foodborne illnesses. The high priority initiative to enhance 

food safety includes much needed improvements like hiring experts in fresh produce 

microbiology, enhancing geographic information systems (GIS/GPS) to better map 

disease outbreaks, and expanding genomic databases used in screening imported 

foods. 

The FDA’s food program regulates $417 billion worth of U.S. produced foods, $49 billion in imported foods, and $59 billion in cosmetics, from point of entry or production to point of sale. Global marketing, the threat of bioterrorist agents added to 

foods, changing American diets, and the rapidly growing diet supplement industry 

converge to further complicate FDA efforts toward a safe food supply. CFSAN personnel oversee consumer products as diverse as tattoo inks and infant formula. In 

fiscal year 2006, they inspected lettuce farming and processing operations in California, completed construction of a high level containment laboratory to develop 

methods for identifying biothreat agents, established a repository of pathogenic 

Escherichia coli O157:H7, and augmented advanced research tools for pinpointing 

sources of contamination by specific bacterial strains. 

The fiscal year 2008 budget request includes $10.6 million to strengthen the 

FDA’s food safety activities, as part of the overall $467 million allocated to the agency’s Foods Program (a 4 percent increase over fiscal year 2007). The proposed increase in FDA’s food safety activities is not sufficient to provide the resources needed to ensure adequate protection and programs based on the best science. The FDA 

is responsible for ensuring the safety and quality of 75 percent of the food consumed 

in the United States. Despite the fact that additional funding was provided to FDA 

in the 2007 Joint Resolution, no increase was provided for food safety. The food safety program must, therefore, absorb infrastructure and payroll costs at the expense 

of funding critical program needs. When the fiscal year 2008 CFSAN food safety request is compared to funding for food safety in the 2007 Joint Resolution, the net 

increase in fiscal year 2008 is only $1 million. The proposed increase for food safety 

activities at CFSAN would be at the expense of current CFSAN programs. 

FDA food safety activities are not able to keep pace with the demands to protect 

food in this country. The two primary centers within FDA that address food safety 

are CFSAN and the Office of Regulatory Affairs (ORA). In fiscal year 2004, CFSAN 

was authorized 901 FTEs, with a major focus on addressing food safety issues. Since 

then, several additional responsibilities have been delegated to the Center for regulatory oversight, including nutritional claims, food allergens, nanotechnology, and 

food security, and major reductions in appropriated personnel positions have occurred. In fiscal year 2008, only 756 FTEs have been proposed for CFSAN. In addition, in fiscal year 2004 2,086 FTEs were appropriated for ORA, the inspection program of FDA. About 30 percent of the ORA is allotted to food inspection, which 

equates to 626 inspectors. In fiscal year 2008, 1,946 FTEs have been proposed for 

ORA, which equates to 584 for food inspectors. Currently, the United States Department of Agriculture (USDA) Food Safety and Inspection Service (FSIS) has approximately 7,600 inspectors for approximately 6,500 meat and poultry processing facilities. FDA has about 600 food inspectors for over 50,000 food processing facilities 

which the agency oversees. The FDA would need at least 58,500 inspectors to be 

on par with the USDA–FSIS meat and poultry inspection program. Both FDA’s 

CFSAN and the foods program within ORA are woefully under funded to adequately 

accomplish the tasks required to verify the safety of the U.S. food supply. Addressing gaps in inspection and compliance, enhancing scientific risk assessment, management and analysis, and science based food standards are examples of areas in 

need of new resources to provide adequate public health protection to the nation’s 

food supply. The ASM recommends the FDA Food Safety programs be appropriated 

an additional $75 million to strengthen CFSAN and ORA Food Safety activities. 

The FDA’s Center for Veterinary Medicine (CVM) regulates animal drugs and 

feeds used to care for a momentous number of animals: 9 billion chickens, 266 million turkeys, 97 million cattle, 61 million pigs, 11 million sheep and goats, 130 million dogs and cats, and 5 million horses. The current recall of 60 million containers 

of pet food by a major Canadian manufacturer, following reports of kidney failure 
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in dogs and cats, is the most recent example of CVM’s rapid response to consumer 

complaints. The FDA quickly alerted the public and the media of the potential 

threat to pet health, while CVM personnel are onsite at the company’s U.S. plants 

to search for any connection between the reported cases and product processing. The 

fiscal year 2008 budget requests $106 million to support FDA’s supervision of animal drugs and feeds, roughly a 7 percent increase. CVM programs slated to receive 

a funding increase include an interagency effort against the rising incidence of drug 

resistant microorganisms. In September 2006, the FDA released its third annual retail meat report, based on laboratory testing for resistance among meat associated 

microorganisms, part of the interagency National Antimicrobial Resistance Monitoring System. The FDA also issued an order last year that prohibits the extra label 

use in poultry of two classes of human anti influenza drugs, to avoid emergence of 

resistant strains of type A influenza that include the avian H5N1 virus. Other fiscal 

year 2008 funding targets are vigilance against Bovine Spongiform Encephalopathy 

(BSE) in cattle and evaluation of genetically modified animals as human food 

sources. Emerging infectious diseases and cutting edge science force regulators to 

adapt, to acquire new scientific methods and evaluate previously unknown food safety issues. Last December, the FDA issued three draft documents on the safety of 

animal cloning, concluding that meat and milk from clones and their offspring are 

safe as food, but asking producers to refrain from selling such products until final 

documents are released following public comment. The three documents illustrate 

the breadth and complexity of FDA oversight of specific food sources: a draft risk 

assessment, a proposed risk management plan, and a draft guidance for industry. 

Modernizing Drug Safety 

In 2006, two reports released by the Institute of Medicine (IOM) warned health 

officials about high numbers of prescription drug dispensing errors and about problems with drug safety oversight. The first report estimated that at least 1.5 million 

preventable adverse drug events (ADEs) occur each year in the United States. The 

report also concluded that preventable ADEs in hospitals alone could be costing the 

U.S. economy about $3.5 billion annually in treatment expenses, adding that the 

extra cost of drug error related illness and death in the ambulatory setting had already reached an estimated $177.4 billion by 2000. In response to these crises in 

prescription errors, the proposed fiscal year 2008 budget specifically requests nearly 

$9 million to modernize FDA’s drug safety programs. The FDA expects the fiscal 

year 2008 initiative to revolutionize the agency’s ability to identify drug safety 

issues, by collecting surveillance numbers from more databases, acquiring the latest 

scientific tools to evaluate drugs and patient reactions, hiring specialist investigators to detect and resolve problems, and improving communication on safety to all 

stakeholders. 

The proposed fiscal year 2008 budget sets aside nearly $571 million for the FDA’s 

ongoing oversight of human drugs, a 10 percent increase over fiscal year 2007. Without adequate funding, the quality of drug oversight will deteriorate at the same time 

as regulatory demands are expanding steadily. Each year, the FDA’s Center for 

Drug Evaluation and Research (CDER) evaluates growing numbers of new and onmarket drug products, routinely investigating adverse medical events and clarifying 

consumer information included in packaging. In 2006, the FDA approved several 

significant new drugs after extensive research and review, including the first inhaled insulin for self treatment by adult patients, the first drug patch for depression, the first drug treatment for a rare glycogen storage disease (Pompe disease, 

designated an FDA orphan drug), and the first drug for dementia of Parkinson’s disease. Throughout the year, the agency announced a number of drug labeling 

changes based on adverse event reports. The FDA also contributed to ongoing 

counterbioterrorism initiatives, approving a nerve agent treatment for use by civilian emergency personnel and generic versions of a drug already FDA approved for 

inhalational anthrax. 

Improving Generic Drug Review 

The budget requests $5.6 million to improve the evaluation of new generic drugs 

and $15.7 million in new generic drug user fees to be collected from drug manufacturers to underwrite the rapidly expanding generic drug industry. In 2005, prescription drug sales accounted for roughly 10 percent of the $2 trillion in total health 

care spending (about $200.7 billion), making medications the third largest spending 

category. During the past six years, generic drug applications to the FDA’s Office 

of Generic Drugs (OGD) increased by 158 percent (793 in fiscal year 2006), and the 

OGD estimates that 857 applications will be filed in fiscal year 2008. The fiscal year 

2008 request to fund the FDA’s generic drug initiative recognizes this expanding demand on FDA oversight. The agency already has implemented steps to improve pro-
744 

gram efficiency, to shorten turn around time for applications. It estimates that funding for the fiscal year 2008 initiative will permit approval of as many as 550 generic 

drugs annually, reducing U.S. prescription drug costs and making more treatments 

available to more patients. In fiscal year 2006, the FDA approved or tentatively approved a record 510 new generic drug applications. Among those approved were 13 

HIV/AIDS drugs and medications for hyperlipidemia, depression, osteoarthritis, and 

high cholesterol. 

Modernizing Biologics Safety 

The initiative to modernize drug safety, which is allocated $11.2 million in the fiscal year 2008 budget, includes more than $2.2 million to enhance safety assessments of biologics, blood and blood products, human tissue, cell and gene therapies, 

vaccines, and allergenic products. Statistics from 2006 reveal the extent of products 

regulated by the FDA’s Center for Biologics Evaluation and Research (CBER): more 

than 14 million units of blood and blood products transfused, over 235 million vaccinations administered, and more than one million human tissues transplanted. 

Funding would expand postmarket surveillance, strengthen adverse event assessment, and improve communication with the medical community and other partners. 

The overall fiscal year 2008 budget for the Biologics Program would be $216 million, 

a 10.8 percent increase over fiscal year 2007 that properly recognizes safe biologic 

products save lives and economic resources. CBER scientists must be able to evaluate cutting edge product development, including their involvement in the nearly 250 

new gene therapy studies presently overseen by the Center. CBER oversight has 

been highly effective; for example, the risk of HIV and hepatitis C transmission 

through blood transfusion has been reduced from 1 in 100 units in the 1980s to less 

than 1 in a million units today. Cost effective vaccines in particular are credited 

with saving thousands of lives and millions of dollars in health care costs. In 2006, 

CBER approved new vaccines against three pathogenic viruses that cause significant death and disability: human papillomavirus (cervical cancer, sexually transmitted disease), herpes zoster virus (shingles), and rotavirus (gastroenteritis in infants and children). 

Improving Medical Device Safety 

A high priority initiative proposed in the fiscal year 2008 budget would help the 

FDA better evaluate the safety of a wide range of medical devices marketed in the 

United States. Of the $285 million allocated to the Medical Devices Program, about 

$7.2 million will fund specific advances in safety analysis and consumer information 

provided by the Center for Devices and Radiological Health (CDRH). As elsewhere 

in the FDA, demands on CDRH staff are being intensified by global market forces, 

rapidly advancing technologies, and shifting population demographics. In fiscal year 

2006, CDRH received over 150,000 adverse event reports requiring review and in 

some cases follow up actions to protect the public health. Last year, FDA personnel 

continued collaboration with the Federal Trade Commission and eBay to make certain that unapproved medical devices were not being sold on the website. The 

CDRH also approved innovative devices with significant health enhancing potential, 

including the first easy to use portable lead poisoning test system, a device that will 

reduce brain damage in some hospitalized infants by keeping the head cool, a rapid 

diagnostic test for avian influenza viruses based on polymerase chain reaction (PCR) 

technology, and a sensor that wirelessly transmits blood glucose readings in real 

time for use by diabetics at home. The CDRH recently provided the scientific support for a large clinical trial of digital mammography, showing that the new technology was significantly more accurate than standard film mammography among 

patients with dense breasts, under age 50, or pre and perimenopausal. In fiscal year 

2008, CDRH expects to certify new mammography facilities after evaluation of their 

technological expertise, plus examine and recertify one third of the more than 8,900 

existing mammography facilities in the United States. 

ASM Supports the Proposed FDA Budget for Fiscal Year 2008 

The ASM supports an increase of $75 million in the proposed budget for food safety and asks the Congress to appropriate the funding necessary to strengthen FDA 

regulation of foods, drugs, medical devices and other products that affect the public 

health. The ASM reminds the Congress that without its highly skilled staff of scientists and professionals, the FDA will not succeed in fully protecting U.S. public 

health with activities that are based on the best science available. If the agency does 

not receive adequate funding, it will be forced to reduce the number of safety officers, onsite inspectors, product reviewers, and laboratory researchers so necessary 

to effective and efficient oversight of FDA regulated products. 
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PREPARED STATEMENT OF THE ANIMAL HEALTH INSTITUTE

Dear Mr. Chairman: I write today to request that you include funding for priorities important to the animal health industry in the fiscal year 2008 Agriculture Appropriations Bill. 

The Animal Health Institute strongly endorses the Administrations fiscal year 2008 budget request of $19.867 million for the U.S. Department of Agriculture’s 

Center for Veterinary Biologics, an increase of about $4.4 million over its fiscal year 

2007 funding level. For the past three fiscal years, CVB’s funding has not included 

cost of living increases, so no progress has been made in filling vacant positions for 

reviewers, inspectors, and laboratory personnel. The CVB Inspection and Compliance division is currently at about 65 percent of its authorized personnel level, and 

the Policy, Evaluation, and Licensing division (including the laboratory) is below 50 

percent. CVB’s leadership anticipates that another year of level funding would force 

staff cutbacks in order to absorb the new activities relating to beginning operations 

in the new laboratories and added security responsibilities. 

Every year, U.S. animal health companies produce 83 billion doses of animal vaccines. These vaccines are critical to protecting the health of America’s flocks, herds, 

and pets from domestic and foreign animal diseases. Animal health companies, for 

instance, are developing new and innovative biologic to greatly reduce the presence 

of food-borne pathogens in animals just prior to slaughter, resulting in less pressure 

on pathogen reduction programs during processing. These new products represent 

a step forward in on-farm contributions to food safety. The lack of funding at CVB 

is dire, and threatens the innovation and availability of these products. 

Additionally, Congress has authorized the Animal Drug User Fee Act, implementing a system of performance standards and user fees to improve the new animal drug review process at FDA’s Center for Veterinary Medicine. Now in the 

fourth year of ADUFA implementation, CVM continues to make steady progress toward its performance goals. Animal producers will benefit from a supply of new and 

innovative products being brought to market more efficiently. The Committee has 

generously funded the fees in the previous four appropriations cycles. The President’s budget proposal includes $13.696 million that needs to be appropriated for 

fiscal year 2008, the last year of ADUFA authorization. The fiscal year 2008 user 

fee request includes the first quarter of fees for fiscal year 2009, funds which would 

be needed to ramp down the program if it were not reauthorized. The industry and 

Administration have not yet begun to negotiate a re-authorization agreement, but 

we are confident that ADUFA will be reauthorized. We ask for the user fees to be 

included in this year’s appropriations bill. Similar to appropriations for the Prescription Drug User Fee Act, this appropriation is entirely budget neutral as the money 

will be provided by animal health companies. 

The Animal Health Institute also endorses the President’s budget request of $94.809 million for FDA’s Center for Veterinary Medicine (CVM). This amount includes the additional budget authority that is needed to make sure that user fee 

triggers are met. The additional funding will ensure that CVM is able to continue 

essential post market safety programs that would otherwise be adversely affected 

in order to meet ADUFA trigger fee requirements. 

Finally, the Animal Health Institute strongly urges the Committee to fund the Administration’s request of $1.8 million for the Collaboration for Animal Health and 

Food Safety Epidemiology (CAHFSE), a joint effort of the Animal and Plant Health 

Inspection Service, the Food Safety and Inspection Service, and the Agricultural Research Service. CAHFSE will enable USDA to identify and track emerging diseases 

and identify and implement mitigation strategies in a timely manner thereby averting economic, animal health, and public health consequences. Further, it will provide comprehensive, science based answers regarding animal health and public 

health and will serve as a model for future surveillance efforts on a national level. 

Finally, it is the only pre-harvest food safety request included in the President’s 

budget request. 

Thank you for your consideration. Please do not hesitate to contact me if you have 

any questions or need additional information. 

PREPARED STATEMENT OF THE ANIMAL WELFARE INSTITUTE

Dear Mr. Chairman: We are writing in support of an fiscal year 2008 appropriation of $1.8 million for the Animal Welfare Information Center (AWIC) at the National Agricultural Library. The AWIC was established in 1986 in response to a 

mandate in the Improved Standards for Laboratory Animals amendment to the Animal Welfare Act. The Center serves as a clearinghouse, training center, and education resource for those involved in the use of animals for research, testing and 
746 

teaching, and the need and demand for its services continue to outstrip its ability 

to respond. The AWIC’s subject areas include husbandry, handling, and care of animals; personnel training; animal behavior; alternatives; improved methodologies; environmental enrichment of non-human primates, and pain control via anesthesia 

and analgesia. Further information on the Center is on the web at: http:// 

www.nal.usda.gov/awic. 

The AWIC staff also compiles and distributes information resources from the scientific literature on zoonotic diseases such as avian influenza, transmissible 

spongiform encephalopathies, tuberculosis, etc. 

An appropriation of $1.8 million would be used as follows: 

—$1,273,000—Staff salary and benefits, including 2 critical new positions to support and enhance the use and usability of AWIC’s most essential tool, its database. A Technical Information Specialist is needed to meet growing demand for 

complex AWIC database searches; to train the research community to meet the 

AWA’s information requirements; and to produce large topical information resources. A new Information Technology Specialist would build, manage, and improve use of the AWIC database. 

—$61,400—Present exhibitions at conferences, including 3 regional AALAS conference in underserved areas of the country 

—$36,000—Present workshops in cooperation with Animal Care to assist licensees/registrants frequently cited for AWA violations 

—$28,000—Prepare and conduct informational workshops at research institutions 

across the country 

—$4,100—Prepare and conduct local workshops 

—$38,000—Acquisition of and electronic access to data 

—$29,200—Printing and reproduction (paper and electronic) 

—$26,000—Office supplies (software, hardware, etc.) 

—$20,400—Internet services 

—$13,900—NAL staff training 

—$270,000 overhead to ARS and NAL 

AWIC’s services are vitally important to the nation’s biomedical research enterprise because they facilitate compliance with specific requirements of the Federal 

animal welfare regulations and policies governing animal-related research. In addition, the AWIC provides extensive research services for us, thereby greatly benefiting our work on animal research issues. We appreciate and look forward to a continued working relationship with the Animal Welfare Information Center and hope 

you will support our modest request for appropriations. 

PREPARED STATEMENT OF THE CALIFORNIA INDUSTRY AND GOVERNMENT CENTRAL

CALIFORNIA OZONE STUDY COALITION

Mr. Chairman and Members of the Subcommittee, on behalf of the California Industry and Government Central California Ozone Study (CCOS) Coalition, we are 

pleased to submit this statement for the record in support of our fiscal year 2008 

funding request of $400,000 from the Department of Agriculture for CCOS. These 

funds are necessary for the State of California to address the very significant challenges it faces to comply with new national ambient air quality standards for ozone 

and fine particulate matter. The study design incorporates technical recommendations from the National Academy of Sciences (NAS) on how to most effectively comply with Federal Clean Air Act requirements. 

First, we want to thank you for your past assistance in obtaining Federal funding 

for the Central California Ozone Study (CCOS) and California Regional PM10/PM2.5

Air Quality Study (CRPAQS). Your support of these studies has been instrumental 

in improving the scientific understanding of the nature and cause of ozone and particulate matter air pollution in Central California and the Nation. Information 

gained from these two studies is forming the basis for the 8-hour ozone, PM2.5, and 

regional haze State Implementation Plans (SIPs) that are due in 2007 (ozone) and 

2008 (particulate matter/haze). As with California’s previous and current SIPs, all 

future SIPs will continue to be updated and refined due to the scientific complexity 

of our air pollution problem. Our request this year would fund the completion of 

CCOS to address important questions that won’t be answered with results from previously funded research projects. 

To date, our understanding of air pollution and the technical basis for SIPs has 

largely been founded on pollutant-specific studies, like CCOS. These studies are conducted over a single season or single year and have relied on modeling and analysis 

of selected days with high concentrations. SIPs are now more complex than they 

were in the past. The National Academy of Sciences (NAS) now recommends a 
747 

weight-of-evidence approach that will involve utilizing more broad-based, integrated 

methods, such as data analysis in combination with seasonal and annual photochemical modeling, to assess compliance with Federal Clean Air Act requirements. 

This will involve the analysis of a larger number of days and possibly an entire season. In addition, because ozone and particulate matter are formed from some of the 

same emissions precursors, there is a need to address both pollutants in combination, which CCOS will do. 

Consistent with the NAS recommendations, the CCOS study includes corroborative analyses with the extensive data provided by past studies, advances the stateof-science in air quality modeling, and addresses the integration of ozone and particulate pollution studies. In addition, the study will incorporate further refinements 

to emission inventories, address the development of observation-based analyses with 

sound theoretical bases, and includes the following four general components: 

—Performing SIP modeling analyses—2005–2011 

—Conducting weight-of-evidence data analyses—2006–2008 

—Making emission inventory improvements—2006–2010 

—Performing seasonal and annual modeling—2008–2011 

CCOS is directed by Policy and Technical Committees consisting of representatives from Federal, State, and local governments, as well as private industry. These 

committees, which managed the San Joaquin Valley Ozone Study and are currently 

managing the California Regional Particulate Air Quality Study, are landmark examples of collaborative environmental management. The proven methods and established teamwork provide a solid foundation for CCOS. 

For fiscal year 2008, our Coalition is seeking funding of $400,000 from the Department of Agriculture/CSREES in support of CCOS. Domestic agriculture is facing 

increasing international competition. Costs of production and processing are becoming increasingly more critical. With the recent SJV PM10 SIP and the upcoming 

ozone and PM2.5 SIPs, the agricultural industry within the study area is facing 

many new requirements to manage and reduce their air quality impacts. The identification of scientifically validated, cost-effective options for reducing the environmental impacts of on-field and livestock related air emissions will contribute significantly to the long-term health and economic stability of local agriculture. Funding 

will support livestock and crop-related research that will help maintain a vital agricultural industry within the state. Research will be focused to measure baseline 

emissions, and to study the most economical and effective approaches for reducing 

the impacts of agriculture on air quality. These studies also have nationwide benefits. 

The funding request is for: (1) Study of agricultural volatile organic compound 

(VOC) emissions from pesticide application that will help answer questions relevant 

to farmers and regulators throughout the Nation, (2) Evaluation of baseline livestock emissions (VOCs, PM10, ammonia) and effective methods to reduce these emissions, (3) Development of livestock facility emissions models as recommended by the 

National Academy of Sciences and (4) Improvement of emissions estimates for agricultural related diesel engines, both on-road and off-road. This includes emission 

factors, activity data, fleet characteristics, seasonality of emissions, and benefits of 

incentive programs to accelerate the introduction of cleaner engines. 

Thank you very much for your consideration of our request. 

PREPARED STATEMENT OF THE COALITION ON FUNDING AGRICULTURAL RESEARCH

MISSIONS

The Coalition on Funding Agricultural Research Missions (CoFARM) appreciates 

the opportunity to submit testimony on the fiscal year 2008 appropriation for the 

United States Department of Agriculture (USDA). CoFARM is a coalition of 24 professional scientific organizations with over 200,000 members dedicated to advancing 

and sustaining a balanced investment in our nation’s research portfolio. 

The USDA sponsors research and education programs which contribute to solving 

agricultural problems of high national priority and ensuring food availability, nutrition, quality and safety, as well as a competitive agricultural economy. Agriculture 

faces new challenges, including threats from emerging infectious diseases in plants 

and animals, climate change, and public concern about food safety and security. It 

is critical to increase the visibility and investment in agriculture research to respond to these challenges, and we appreciate the efforts of Congress to fund the National Research Initiative (NRI) at $190 million in fiscal year 2007. We urge the 

Subcommittee to support the Administration’s fiscal year 2008 request of $257 million for this program. 
748 

1 ‘‘Agricultural Research and Productivity: Questions and Answers,’’ USDA Economic Research 

Service, December 2005. http://www.ers.usda.gov/Briefing/AgResearch/Questions/ 

APRDQA6.HTM 

USDA National Research Initiative Competitive Grants Program 

The National Research Initiative Competitive Grants Program (NRI) was established in 1991 in response to recommendations outlined in the report, Investing in 

Research: A Proposal to Strengthen the Agricultural, Food and Environmental System, by the National Research Council’s (NRC) Board of Agriculture. This report 

called for increased funding by USDA of high priority research through a competitive peer-review process directed at: 

—Increasing the competitiveness of U.S. agriculture. 

—Improving human health and well-being through an abundant, safe, and highquality food supply. 

—Sustaining the quality and productivity of the natural resources and the environment upon which agriculture depends. 

Stakeholders of the research community continue their interest in and support of 

the NRI, which is reflected in two subsequent NRC reports, Investing in the National Research Initiative: An Update of the Competitive Grants Program of the 

U.S. Department of Agriculture, published in 1994, and National Research Initiative: A Vital Competitive Grants Program in Food, Fiber, and Natural Resources Research, published in 2000. 

Today, the NRI, housed within USDA’s Cooperative State Research, Education, 

and Extension Service (CSREES), supports research on key problems of national 

and regional importance in biological, environmental, nutritional, physical, and social sciences relevant to agriculture, food, health and the environment on a peerreviewed, competitive basis. Additionally, NRI enables USDA to develop new partnerships with other Federal agencies that advance agricultural science like its current collaborations between NRI and DOE and NSF. 

CoFARM urges Congress to support the Administration’s requested increase for 

NRI in fiscal year 2008. NRI’s proposed increase comes from the shifting of CSREES 

Integrated Activities, such as food safety, pest management, and water quality, 

making up $42 million of the proposed increase, providing a net increase of $25 million for NRI. The Administration also requests $19 million of the NRI budget be 

used for bioenergy research. CoFARM supports the Administration’s effort to increase competitively awarded funding mechanisms. 

By increasing the funding for this program, the United States is investing in our 

nation’s future. Failure to make this investment will imperil the future of agriculture in the United States by reducing competitiveness and decreasing productivity. With limited dollars our scientists already produce an annual rate of return 

of at least 40 percent.1 This high rate of return suggests that an increase in funds 

to agricultural research would be beneficial to the U.S. economy. 

Because of Federal investment, we have made since 1991, we have gained valuable new knowledge in areas such as: 

Food Safety and Nutrition 

USDA funded competitive research has supported studies to understand incentives for firms to adopt food safety controls and industry response to losses when 

products are recalled for food safety violations. 

USDA supported scientists identified a safe and effective new sanitizer (SANOVA) 

that achieved a 5-log reduction of E. coli, Listeria, and Salmonella on produce even 

in the presence of large organic loads. The researchers optimized sanitation treatment procedures to ensure good quality of shredded carrot and fresh-cut lettuce 

while maintaining the effective killing power of the sanitizer. This research is critical considering there are approximately 76 million foodborne illness cases in the 

U.S. per year and the findings from this research is especially useful to the fresh 

produce industry as they provide practical information in selecting a suitable sanitizer to maintain microbial safety and quality of fruits and vegetables. 

Iowa State University researchers have studied fatty acid composition in beef and 

dairy cattle through a NRI funded grant. They have discovered a single nucleotide 

polymorphism that is correlated to content of C14–O (myristic acid, the most 

atherogenic of saturated fatty acids) of beef. Thus, the marker in the throesterase 

domain in fatty acid synthase gene can be used to select for healthier beef. 

University of Illinois scientists are involved with the assessment of general risk 

posed from transgenic animals, which is important to their future contributions to 

society. Identification of potentially harmful properties of transgenic livestock is the 

initial step in a risk assessment. Direct and indirect impacts of potential harmful 

properties of transgenic livestock are being evaluated at three levels: (1) character-
749 

2 ‘‘Biomass as Feedstock for a Bioenergy and Bioproducts Industry: The Technical Feasibility 

of a Billion-Ton Annual Supply, April 2005’’ http://www1.eere.energy.gov/biomass/pdfs/ 

finallbilliontonlvisionlreport2.pdf 

ization of how the transgene, the transgene product, and the transgenic livestock 

behave in their immediate environment, that is, in their barn or pen, (2) determination of possible impacts of large scale release of transgenic livestock, that is, if they 

were to be integrated into the larger population of food animal livestock, and (3) determination of the more complex environmental and safety consequences of their release into the livestock population. This study will determine whether a mammary 

specific transgene, bovine a-lactalbumin (Ba-LA) is expressed in tissues other than 

the mammary gland and whether the transgene (Tg) itself, the transgenic RNA or 

the transgenic protein cross over into non-transgenic (C) animals under various 

physiological and physical conditions. 

Renewable Energy and Fuels 

In a time of volatile gasoline prices, USDA dollars have helped provide economic 

and policy analyses for specific renewable energy technologies and will estimate national impacts of certain renewable energy policy alternatives. 

An April 2005 joint study of the U.S. Departments of Energy and Agriculture 

found that with continued advances in research there will be enough renewable biomass grown in the United States. to meet more than one-third of the current demand for transportation fuels in the nation, without diverting from food crop production.2 With advances in plant and microbial research, land in every state in the 

nation could be used to grow plants that produce clean-burning cellulosic ethanol 

resulting in decreased dependence on foreign oil, reduction of the trade deficit, reduced emissions of stored greenhouse gases, revitalized rural economies and 

strengthened national security. 

Plant and Animal Health and Well-Being 

Pennsylvania researchers are developing rapid diagnostic tests to curb avian in- fluenza, a disease that could cripple the state’s $700 million poultry industry. 

Entomologists and Nematologists developed a vaccine for the protection of cattle 

from the horn fly, a major insect pest in many parts of the world costing the North 

American cattle industry alone more than $1 billion annually. 

Iowa State University researchers studied fatty liver syndrome in dairy cattle. 

They found that daily injections of glucagon can be used to prevent and treat fatty 

liver in transition dairy cows. A patent has been issued for this technology. 

Waste Remediation 

Researchers in Florida have tested a common fern’s ability to soak up arsenic, a 

cancer-causing heavy metal, from contaminated soils. The market for plant-based 

remediation of wastes is estimated to be $370 million in 2005. 

With the support of Congress, increased funding for research will continue to 

boost the American agricultural enterprise and improve our economy by increasing 

food safety, boosting production, protecting the environment, finding new uses for 

renewable resources, and enhancing food itself so that food and agricultural systems 

contribute to a stronger and more healthful society. Research programs in nutrition 

and food science help to ensure high-quality, safe, and affordable food for consumers, and contribute to the success of a food and agricultural system that creates 

jobs and income in the United States. 

CoFARM appreciates the opportunity to provide written testimony and would be 

pleased to assist the Subcommittee as the Department of Agriculture bill is considered throughout the appropriations process. 

PREPARED STATEMENT OF THE COLORADO RIVER BASIN SALINITY CONTROL FORUM

The Congress concluded that the Colorado River Basin Salinity Control Program 

(Program) should be implemented in the most cost-effective way. Realizing that agricultural on-farm strategies were some of the most cost-effective strategies, the 

Congress authorized a program for the United States Department of Agriculture 

(USDA) through amendment of the Colorado River Basin Salinity Control Act in 

1984. With the enactment of the Federal Agriculture Improvement and Reform Act 

of 1996 (FAIRA), the Congress directed that the Program should continue to be implemented as one of the components of the Environmental Quality Incentives Program (EQIP). Since the enactment of the Farm Security and Rural Investment Act 

(FSRIA) in 2002, there have been, for the first time in a number of years, opportunities to adequately fund the Program within the EQIP. 
750 

The Program, as set forth in the Colorado River Basin Salinity Control Act, is to 

benefit Lower Basin water users hundreds of miles downstream from salt sources 

in the Upper Basin as the salinity of Colorado River water increases as the water 

flows downstream. There are very significant economic damages caused by high salt 

levels in this water source. Agriculturalists in the Upper Basin where the salt must 

be controlled, however, don’t first look to downstream water quality standards but 

look for local benefits. These local benefits are in the form of enhanced beneficial 

use and improved crop yields. They submit cost-effective proposals to the State Conservationists in Utah, Wyoming and Colorado and offer to cost share in the acquisition of new irrigation equipment. The Colorado River Basin Salinity Control Act 

provides that the seven Colorado River Basin States will also cost share with the 

Federal funds for this effort. This has brought together a remarkable partnership. 

After longstanding urgings from the States and directives from the Congress, the 

USDA has concluded that this program is different than small watershed enhancement efforts common to the EQIP. In this case, the watershed to be considered 

stretches more than 1,200 miles from the river’s headwater in the Rocky Mountains 

to the river’s terminus in the Gulf of California in Mexico and receives water from 

numerous tributaries. The USDA has determined that this effort should receive a 

special funding designation and has appointed a coordinator for this multi-state effort. 

In recent fiscal years, the Natural Resources Conservation Service (NRCS) has directed that over $19 million be used for the Program. The Colorado River Basin Salinity Control Forum (Forum) appreciates the efforts of the NRCS leadership and 

the support of this subcommittee. The plan for water quality control of the Colorado 

River was prepared by the Forum, adopted by the States, and approved by the 

United States Environmental Protection Agency (EPA). The Colorado River Basin 

Salinity Control Advisory Council has taken the position that the funding for the 

salinity control program should not be below $20 million per year. Over the last 

three fiscal years, for the first time, funding almost reached the needed level. State 

and local cost-sharing is triggered by the Federal appropriation. In fiscal year 2007, 

it is anticipated that the States will cost share with about $8.3 million and local 

agriculture producers will add another $7.5 million. Hence, it is anticipated that in 

fiscal year 2007 the State and local contributions will be 45 percent of the total program cost. 

Over the past few years, the NRCS has designated that about 2.5 percent of the 

EQIP funds be allocated to the Colorado River salinity control program. The Forum 

believes this is the appropriate future level of funding as long as the total EQIP 

funding nationwide is around $1 billion. Funding above this level assists in offsetting pre-fiscal year 2003 funding below this level. The Basin States have cost sharing dollars available to participate in funding on-farm salinity control efforts. The 

agricultural producers in the Upper Basin are waiting for their applications to be 

considered so that they might improve their irrigation equipment and also cost 

share in the Program. 

Overview 

The Program was authorized by the Congress in 1974. The Title I portion of the 

Colorado River Basin Salinity Control Act responded to commitments that the 

United States made, through a Minute of the International Boundary and Water 

Commission, to Mexico specific to the quality of water being delivered to Mexico 

below Imperial Dam. Title II of the Act established a program to respond to salinity 

control needs of Colorado River water users in the United States and to comply with 

the mandates of the then newly-enacted Clean Water Act. This testimony is in support of funding for the Title II program. 

After a decade of investigative and implementation efforts, the Basin States concluded that the Salinity Control Act needed to be amended. The Congress agreed 

and revised the Act in 1984. That revision, while keeping the Department of the 

Interior as lead coordinator for Colorado River Basin salinity control efforts, also 

gave new salinity control responsibilities to the USDA. The Congress has charged 

the Administration with implementing the most cost-effective program practicable 

(measured in dollars per ton of salt controlled). It has been determined that the agricultural efforts are some of the most cost-effective opportunities. 

Since Congressional mandates of three decades ago, much has been learned about 

the impact of salts in the Colorado River system. The Bureau of Reclamation (Reclamation) has conducted studies on the economic impact of these salts. Reclamation 

recognizes that the damages to United States’ water users alone are hundreds of 

millions of dollars per year. 

The Forum is composed of gubernatorial appointees from Arizona, California, Colorado, Nevada, New Mexico, Utah and Wyoming. The Forum has become the seven- 
751 

state coordinating body for interfacing with Federal agencies and the Congress in 

support of the implementation of the Salinity Control Program. In close cooperation 

with the EPA and pursuant to requirements of the Clean Water Act, every 3 years 

the Forum prepares a formal report evaluating the salinity of the Colorado River, 

its anticipated future salinity, and the program elements necessary to keep the salinity concentrations (measured in Total Dissolved Solids—TDS) at or below the levels measured in the river system in 1972 at Imperial Dam, and below Parker and 

Hoover Dams. 

In setting water quality standards for the Colorado River system, the salinity concentrations at these three locations in 1972 have been identified as the numeric criteria. The plan necessary for controlling salinity and reducing downstream damages 

has been captioned the ‘‘Plan of Implementation.’’ The 2005 Review of water quality 

standards includes an updated Plan of Implementation. In order to eliminate the 

shortfall in salinity control resulting from inadequate Federal funding for a number 

of years from the USDA, the Forum has determined that implementation of the Program needs to be accelerated. The level of appropriation requested in this testimony 

is in keeping with the agreed upon plan. If adequate funds are not appropriated, 

significant damages from the higher salt concentrations in the water will be more 

widespread in the United States and Mexico. Concentrations of salts in the river cause $330 million in quantified damages and 

significantly more in unquantified damages in the United States and result in poorer quality water being delivered by the United States to Mexico. Damages occur 

from: 

—a reduction in the yield of salt sensitive crops and increased water use for leaching in the agricultural sector, 

—a reduction in the useful life of galvanized water pipe systems, water heaters, 

faucets, garbage disposals, clothes washers, and dishwashers, and increased use 

of bottled water and water softeners in the household sector, 

—an increase in the use of water for cooling, and the cost of water softening, and 

a decrease in equipment service life in the commercial sector, 

—an increase in the use of water and the cost of water treatment, and an increase 

in sewer fees in the industrial sector, 

—a decrease in the life of treatment facilities and pipelines in the utility sector, 

—difficulty in meeting wastewater discharge requirements to comply with National Pollutant Discharge Elimination System permit terms and conditions, 

and an increase in desalination and brine disposal costs due to accumulation 

of salts in groundwater basins, and 

—increased use of imported water for leaching and cost of desalination and brine 

disposal for recycled water. 

For every 30 mg/L increase in salinity concentrations, there is $75 million in additional damages in the United States. The Forum, therefore, believes implementation 

of the USDA program needs to be funded at 2.5 percent of the total EQIP funding. 

Although the Program thus far has been able to implement salinity control measures that comply with the approved plan, recent drought years have caused salinity 

levels to rise in the river. Predictions are that this will be the trend for the next 

several years. This places an added urgency for acceleration of the implementation 

of the Program. 

State Cost-Sharing and Technical Assistance 

The authorized cost sharing by the Basin States, as provided by FAIRA, was at 

first difficult to implement as attorneys for the USDA concluded that the Basin 

States were authorized to cost share in the effort, but the Congress had not given 

the USDA authority to receive the Basin States’ funds. After almost a year of exploring every possible solution as to how the cost sharing was to occur, the States, 

in agreement with Reclamation, State officials in Utah, Colorado and Wyoming and 

with NRCS State Conservationists in Utah, Colorado and Wyoming, agreed upon a 

program parallel to the salinity control activities provided by the EQIP wherein the 

States’ cost sharing funds are being contributed and used. We are now several years 

into that program and, at this moment in time, this solution to how cost sharing 

can be implemented appears to be satisfactory. 

With respect to the Basin States’ cost sharing funds, the Basin States felt that 

it was most essential that a portion of the Program be associated with technical assistance and education activities in the field. Without this necessary support, there 

is no advanced planning, proposals are not well prepared, assertions in the proposals cannot be verified, implementation of contracts cannot be observed, and valuable partnering and education efforts cannot occur. Recognizing these values, the 

‘‘parallel’’ State cost sharing program expends 40 percent of the funds available on 

these needed support activities made possible by contracts with the NRCS. Initially, 
752 

it was acknowledged that the Federal portion of the Program funded through EQIP 

was starved with respect to needed technical assistance and education support. The 

Forum is encouraged with a recent Administration acknowledgment that technical 

assistance must be better funded. 

PREPARED STATEMENT OF THE COLORADO RIVER BOARD OF CALIFORNIA

This testimony is in support of funding for the U.S. Department of Agriculture 

(USDA) with respect to its on-farm Colorado River Basin Salinity Control Program 

for fiscal year 2008. This program has been carried out through the Colorado River 

Basin Salinity Control Act (Public Law 93–320), since it was enacted by Congress 

in 1974. With the enactment of the Federal Agricultural Improvement and Reform 

Act (FAIRA) in 1996 (Public Law 104–127), specific funding for salinity control 

projects in the Colorado River Basin were eliminated from the federal budget and 

aggregated into the Department of Agriculture’s Environmental Quality Incentives 

Program (EQIP) as one of its program components. With that action, Congress concluded that the salinity control program could be more effectively implemented as 

one of the components of the EQIP. 

The Program, as set forth in the Act, benefits both the Upper Basin water users 

through more efficient water management and the Lower Basin water users, hundreds of miles downstream from salt sources in the Upper Basin, through reduced 

salinity concentration of Colorado River water. California’s Colorado River water 

users are presently suffering economic damages in the hundreds of million of dollars 

per year due to the River’s salinity. 

The Colorado River Board of California (Colorado River Board) is the state agency 

charged with protecting California’s interests and rights in the water and power resources of the Colorado River system. In this capacity, California along with the 

other six Colorado River Basin states through the Colorado River Basin Salinity 

Control Forum (Forum), the interstate organization responsible for coordinating the 

Basin States’ salinity control efforts, established numeric criteria in June 1975 for 

salinity concentrations in the River. These criteria were established to lessen the 

future damages in the Lower Basin states of Arizona, California, and Nevada, as 

well as assist the United States in delivering water of adequate quality to Mexico 

in accordance with Minute 242 of the International Boundary and Water Commission. 

The goal of the Colorado River Basin Salinity Control Program is to offset the effects of water resources development in the Colorado River Basin after 1972 as each 

state develops its Colorado River Compact apportionments. In close cooperation with 

the U.S. Environmental Protection Agency (EPA) and pursuant to requirements of 

the Clean Water Act (Public Law 92–500), every 3 years the Forum prepares a formal report analyzing the salinity of the Colorado River, anticipated future salinity, 

and the program elements necessary to keep the salinity concentrations (measured 

in Total Dissolved Solids—TDS) at or below the levels measured in the Colorado 

River system in 1972 at Imperial Dam, and below Parker and Hoover Dams. The 

latest report was prepared in 2005 titled: 2005 Review, Water Quality Standards 

for Salinity, Colorado River System (2005 Review). The plan necessary for controlling salinity and reducing downstream damages has been captioned the ‘‘Plan of Implementation.’’ The 2005 Review includes an updated Plan of Implementation. 

Concentrations of salts in the River annually cause about $330 million in quantified damage in the United States (there are significant unquantified damages as 

well). For example, damages occur from: 

—A reduction in the yield of salt sensitive crops and increased water use for 

leaching in the agricultural sector; 

—A reduction in the useful life of galvanized water pipe systems, water heaters, 

faucets, garbage disposals, clothes washers, and dishwashers, and increased use 

of bottled water and water softeners in the household sector; 

—An increase in the use of water for cooling, and the cost of water softening, and 

a decrease in equipment service life in the commercial sector; 

—An increase in the use of water and the cost of water treatment, and an increase in sewer fees in the industrial sector; 

—A decrease in the life of treatment facilities and pipelines in the utility sector; 

—Difficulty in meeting wastewater discharge requirements to comply with National Pollutant Discharge Elimination System permit terms and conditions, 

and an increase in desalination and brine disposal costs due to accumulation 

of salts in groundwater basins, and fewer opportunities for recycling due to 

groundwater quality deterioration; and 
753 

—Increased use of imported water for leaching and the cost of desalination and 

brine disposal for recycled water. 

For every 30 milligram per liter increase in salinity concentrations, there are $75 

million in additional damages in the United States. Although the Program, thus far, 

has been able to implement salinity control measures that comply with the approved 

plan, recent drought years have caused salinity levels to rise in the River. Predictions are that this will be the trend for the next several years. This places an 

added urgency for acceleration of the implementation of the Program. 

Enactment of the Farm Security and Rural Investment Act of 2002 provided an 

opportunity to adequately fund the Salinity Program within EQIP. The Colorado 

River Basin Salinity Control Advisory Council has taken the position that the USDA 

portion of the effort be funded at 2.5 percent of the EQIP funding but at least $20.0 

million annually. Over the past few years, the Natural Resources Conservation 

Service (NRCS) has designated 2.5 percent of EQIP funds be allocated to the Colorado River Salinity Control program. The Forum suggests that this is an appropriate level of funding as long as it does not drop below $20.0 million. Funding 

above this level assists in offsetting pre-fiscal year 2003 funding below this level. 

The Colorado River Board supports the recommendation of the Forum and urges 

this Subcommittee to support funding for the Colorado River Basin Salinity Control 

Program for 2008 at this level. 

These Federal dollars will be augmented by the State cost sharing of 30 percent 

with an additional 25 percent provided by the agricultural producers with whom 

USDA contracts for implementation of salinity control measures. Over the past 

years, the Colorado River Basin Salinity Control program has proven to be a very 

cost effective approach to help mitigate the impacts of increased salinity in the Colorado River. Continued Federal funding of this important Basin-wide program is essential. 

In addition, the Colorado River Board recognizes that the federal government has 

made significant commitments to the Republic of Mexico and to the seven Colorado 

River Basin States with regard to the delivery of quality water to Mexico. In order 

for those commitments to continue to be honored, it is essential that in fiscal year 

2008, and in future fiscal years, that Congress continues to provide funds to USDA 

to allow it to provide needed technical support to agricultural producers for addressing salinity control in the Basin. 

The Colorado River is, and will continue to be, a major and vital water resource 

to the 18 million residents of southern California as well as throughout the Colorado 

River Basin. As stated earlier, preservation and improvement of the Colorado River 

water quality through an effective salinity control program will avoid the additional 

economic damages to users of Colorado River water in California, Arizona, and Nevada. 

PREPARED STATEMENT OF FLORIDA STATE UNIVERSITY

Summary of Request 

Florida State University is requesting $4,500,000 from the U.S. Department of 

Agriculture; Cooperative State Research, Education and Extension Service/Research 

and Education Activities/Federal Admin. Account for the Risk Reduction for Agricultural Crops project for fiscal year 2008. 

Mr. Chairman, I would like to thank you and the Members of the Subcommittee 

for this opportunity to present testimony before this Committee. I would like to take 

a moment to briefly acquaint you with Florida State University. 

Located in Tallahassee, Florida’s capitol, FSU is a comprehensive Research I university with a rapidly growing research base. The University serves as a center for 

advanced graduate and professional studies, exemplary research, and top-quality 

undergraduate programs. Faculty members at FSU maintain a strong commitment 

to quality in teaching, to performance of research and creative activities, and have 

a strong commitment to public service. Among the current or former faculty are numerous recipients of national and international honors including Nobel laureates, 

Pulitzer Prize winners, and several members of the National Academy of Sciences. 

Our scientists and engineers do excellent research, have strong interdisciplinary interests, and often work closely with industrial partners in the commercialization of 

the results of their research. Florida State University had over $190 million this 

past year in research awards. 

Florida State University attracts students from every State in the nation and 

more than 100 foreign countries. The University is committed to high admission 

standards that ensure quality in its student body, which currently includes National 
754 

1See http://www.fsis.usda.gov/Help/glossary-C/index.asp. 

Merit and National Achievement Scholars, as well as students with superior creative talent. 

At Florida State University, we are very proud of our successes as well as our 

emerging reputation as one of the Nation’s top public research universities. 

Mr. Chairman, let me summarize our primary interest today. The Southeast Climate Consortium (SECC), which consists of Florida State University, the University 

of Florida, the University of Miami, the University of Georgia, Auburn University, 

and University of Alabama at Huntsville, has been at the forefront of research and 

extension for the applications of climate predictions to risk reduction for agriculture. 

With support from NOAA and USDA, the SECC has developed new methods to predict the consequences of climate variability for agricultural crops, forests, and water 

resources in the southeast United States. In recent real-life tests, these methods 

have been applied to the problems that farmers raising specialty crops face arising 

from variable rainfall, temperature, and wild fires. 

In the SECC, Florida State University will provide the climate forecasts and risk 

reduction methodology. The University of Florida and University of Georgia will 

translate this climate information into risks associated environmental impacts on 

agriculture and, with Auburn University, will work with Extension Services to provide information to the agricultural community. The University of Miami will provide economic modeling of agricultural systems. Together UM, UF, and the University of Alabama-Huntsville are developing new tools to help minimize climate risks 

to water quality and quantity, especially for agriculture. FSU, on behalf of the 

SECC, seeks $5.0 million in fiscal year 2008 for this activity. Utilization of these 

tools and their application to agricultural problems has the strong support of extension managers. 

Mr. Chairman, FSU is seeking $4,500,000 in fiscal year 2008 to continue our important work. The new tasks for fiscal year 2008 include the development flood forecasting methods to help farmers and producers plan for reducing risks of economic 

losses and environmental damage; developing partnerships and methods for incorporating climate forecasts and other climate information into agricultural and water 

policy decisions, and beginning development of a prototype decision support system 

for the application of climate forecasts to water resource management, especially for 

agricultural water use. We are also working with the committees on agriculture on 

the upcoming farm bill, seeking to secure authorization for this program. 

Mr. Chairman, we believe this research is vitally important to our country and 

would appreciate your support. 

PREPARED STATEMENT OF FOOD & WATER WATCH

My name is Wenonah Hauter. I am the Executive Director of Food & Water 

Watch, a non-profit consumer organization. We welcome this opportunity to present 

our views on the fiscal year 2008 Agriculture, Rural Development, Food and Drug 

Administration and Related Agencies Appropriations Bill. 

USDA—Food Safety and Inspection Service (FSIS) 

Risk-Based Inspection 

We have the following concerns about this proposal: 

We believe that the agency lacks the statutory authority to execute a risk-based 

inspection scheme, especially one that contemplates food processing plants receiving 

less than daily inspection. According to both the Federal Meat Inspection Act (21 

U.S.C. 603) and the Poultry Products Inspection Act (21 U.S.C. 455), the United 

States Department of Agriculture is required to provide continuous inspection in all 

establishments that produce meat and poultry products that enter the food supply. 

FSIS’ own glossary defines continuous inspection as: 

—USDA’s meat and poultry inspection system is often called ‘‘continuous’’ because 

no animal destined for human food may be slaughtered or dressed unless an 

inspector is present to examine it before slaughter (antemortem inspection), and 

its carcass and parts after slaughter (postmortem inspection). In processing 

plants, as opposed to slaughter plants, inspectors need not be present at all 

times, but they do visit at least once daily. Processing inspection is also considered continuous.1

Under Secretary for Food Safety Richard Raymond has been quoted in the press 

advocating ‘‘virtual inspections,’’ whereby food establishments would merely transmit daily production records to FSIS inspectors either via facsimile or electronically 
755 

2Morton, Joseph. ‘‘USDA Looks at ‘Virtual’ Inspections,’’ Omaha World Herald, October 23, 

2006. 3See http://www.usda.gov/oig/webdocs/24501-01-FM.pdf. 

4See http://www.usda.gov/oig/webdocs/24601-07-CH.pdf, p. i. 

5 Hearings before the House Subcommittee on Agriculture, Rural Development, Food and 

Drug Administration, and Related Agencies Appropriations for fiscal year 2007, Food Safety and 

Inspection Service, Part 1, March 8, 2006, pp. 215–216. 6 Ibid, p. 296. 

without a physical inspection visit.2 This is not what the meat and poultry inspection statutes establish, and we believe that the agency is treading on dangerous 

legal ground as it proceeds with this proposal. 

Furthermore, we believe that this new system could spark legal challenges by food 

establishments that believe they are being singled out for more intense inspections. 

Without a statutory basis for instituting changes to the inspection process, the agency might be hard-pressed to implement this new program in light of such legal challenges. 

Risk-based inspection needs a reliable database upon which to make judgments 

about which meat and poultry plants meet or exceed performance standards. At the 

present time, there are problems with the data collected by FSIS. The USDA Office 

of Inspector General (OIG), in a November 2004 audit report, said the following 

about the agency’s Performance Based Inspection System (PBIS) database: 

Due to the lack of controls noted during our audit, FSIS cannot be assured that 

PBIS data is complete, accurate, and reliable. As a result, FSIS management may 

not have the information it needs to effectively manage its inspection activities. 

Without effective controls over data integrity, the PBIS system may be an unreliable 

repository that gives FSIS management a false sense that inspection activities are 

adequately carried out and sanitation of plant operations is accurately reported.3

In September 2006, the OIG released an audit of the agency’s Pathogen Reduction 

Enforcement Program (PREP). PREP is used to collect information from the FSIS 

salmonella testing program. The OIG found the following: 

—We found a significant number of establishments that were excluded from the 

Salmonella sampling database because of ineffective controls to identify eligible 

establishments and also because district office personnel did not fully understand the process for including the establishments in the database. At the district we visited, 28 percent of the establishments that should have been subject 

to Salmonella testing were excluded from the sampling database. This problem 

was particularly apparent at establishments inspected under Federal-State Cooperative Programs (Talmadge-Aiken establishments) in the one State we visited. The State supervisors responsible for program oversight at these establishments were not provided with the eligibility reports that could have allowed 

them to identify establishments that needed to be included in the sampling 

database.4

The agency is also lacking one critical piece of information that we consider vital 

before it can move forward with any proposal to change its inspection system—attribution data that links specific foods under the agency’s jurisdiction to food borne 

illness outbreaks. Congress has repeatedly asked the agency about this issue, and 

the agency has repeatedly responded that it is working on it.5

We have long suspected that the real reason the agency is pressing to implement 

risk-based inspection is that it would serve to mask shortages in inspection staffing 

that has plagued the agency for years. We have heard of chronic shortages in the 

number of processing inspectors. For example, just last year, we heard of one inspector in the Albany District of FSIS being assigned to 19 food plants that 

stretched from New York City to Connecticut; in the Philadelphia District, one inspector was assigned 26 plants to cover. These sorts of assignments fly in the face 

of testimony provided by the agency during last year’s appropriations hearings in 

which it asserted that FSIS inspectors spend an average of 2 hours and 40 minutes 

per processing plant each day.6 Just this week, Under Secretary Raymond testified 

before the House Agriculture Appropriations subcommittee that at least 250 establishments have not been receiving daily—or even weekly—inspection for the last 30 

years. 

The Hazard Analysis Critical Control Points (HACCP) inspection system still has 

serious problems. The authority of inspectors to prevent adulterated products from 

entering the food supply has been severely hampered. Company HACCP plans do 

not require pre-approval from FSIS before they are implemented. Under HACCP, 

inspectors have been relegated to verifying whether company-written HACCP plans 

are being followed. Even when FSIS issues directives to companies to reassess their 

HACCP plans to take into account new food safety policies (e.g., the 2002 directive 
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7 See http://www.gao.gov/new.items/d0259.pdf. 8 See http://www.foodandwaterwatch.org/about/press/meat-inspection-poll. 

requiring companies to deal with E. coli 0157:H7 as an adulterant likely to occur 

in beef processing), companies often take a long time to implement the new policy. 

In its fiscal year 2008 budget submission, the agency states that it would like to 

begin implementing risk-based inspection in slaughter facilities. We assume that its 

proposal means expansion of the HACCP-Based Inspection Models Project (HIMP) 

in poultry slaughter. HIMP still has fewer than two-dozen plants participating in 

the program. The Government Accountability Office issued the last comprehensive 

analysis of this project in December 2001 and pointed out a number of serious problems.7 Inspectors assigned to these plants report that they are not able to perform 

food safety functions because they are assigned to stationary positions on the 

slaughter lines (e.g., they are not able to look inside the cavity of poultry carcasses 

where there may be contamination). Furthermore, defects that are considered to be 

‘‘other consumer protection,’’ such as blemishes, scabs, tumors, feathers, and 

bruises, and would not pass muster in poultry slaughter plants using conventional 

inspection techniques are being permitted to enter commerce under the HIMP system. In a recent national public opinion survey conducted for Food & Water Watch 

by Lake Research Partners, nearly two-thirds of American consumers favor having 

Federal government inspectors evaluate meat and poultry products for wholesomeness as well as food safety issues.8 We do not believe that they Agency is prepared 

to extend this inspection model to the entire poultry industry at this time. There 

should be a thorough examination of HIMP project before it is expanded. 

Because there has not been a full evaluation of HIMP recently, we filed a Freedom of Information Act request on December 14, 2005 requesting certain documents 

so that we could conduct our own study. FSIS initially responded that they wanted 

us to pay more than $10,000 for the information. The agency has since relented on 

the fee, but we still have not received all of the information we requested. We believe that Congress should request full disclosure of this information so that it can 

make an informed judgment on the agency’s readiness to expand this program. 

In January 2006, the USDA Inspector General released an audit report entitled, 

‘‘Food Safety and Inspection Service Assessment of the Equivalence of the Canadian 

Inspection System’’ (Report No. 24601–05–Hy). The report indicates that Canada 

was continually exporting meat and poultry products to the United States that had 

been subject to less than daily inspection—in violation of U.S. standards. While 

those responsible for enforcing our equivalency agreements at FSIS recommended 

taking disciplinary action against Canada for their repeated violations, in 2004 the 

Secretary overruled them. We find this most troubling. FSIS has repeatedly testified 

before Congress that countries that wish to export their meat and poultry products 

to the United States must maintain inspection standards that are identical to those 

for domestic producers. Yet, in this instance, USDA has chosen to look the other 

way. 

While Canada has agreed to institute daily inspection in those establishments 

that export to the United States, Canada is in the process of conducting a study 

to justify less-than-daily inspections for processed food exports to the United States 

that would serve as the basis for a request for an equivalency determination by 

FSIS. We believe that granting Canada equivalency for less-than-daily inspection 

would establish a dangerous precedent and mark a radical departure from current 

U.S. policy. 

We have also learned that Australia is in the process of considering a ‘‘trial’’ of 

its controversial Meat Safety Enhancement Program (MSEP) for a beef processor 

that would like to export its products to the United States. MSEP is a privatized 

inspection system for beef for which there is no comparable system here in the 

United States. MSEP trials were last conducted in 1999, but were stopped since the 

inspection system raised consumer concerns both here in the United States and in 

Europe. We can only surmise that someone at USDA has signaled to Australia that 

we would accept beef products produced under a privatized inspection system. 

We view both the Canadian pilot project and the Australian MSEP trial as vehicles by the current USDA policymakers to institute backdoor changes to our inspection system through our international trading partners. Last year, Congress was 

compelled to warn USDA on changing the programs authorized under the 2002 

Farm Security and Rural Development Act through the Doha round of WTO negotiations. We suspect that USDA may be attempting to do the same with food safety 

policy. 

For all of these reasons, we do not believe that the Agency is prepared to make 

radical changes to the current inspection system, no matter what terms they use 

to describe it. The concept of ‘‘continuous’’ government inspection has been the core 
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9See http://www.fas.usda.gov/gainfiles/200703/146280447.pdf, p. 6. 

10See http://www.fsis.usda.gov/OPPDE/FAR/China/China2005.pdf and http:// 

www.fsis.usda.gov/OPPDE/FAR/China/China2004.pdf 11See http://www.cidrap.umn.edu/cidrap/content/influenza/avianflu/news/feb2807avian.html 12See http://www.usda.gov and search for Release 0065.07. 

of our meat inspection system for 100 years, and the Agency should not be permitted to abandon this principle. 

Expansion of processed poultry imports from the People’s Republic of China (PRC) 

In January 2007, we learned that FSIS was in the process of developing a proposed rule that would expand the import of processed poultry products from PRC 

to include poultry that was raised in the PRC. 

We have several concerns about any imports of poultry products from the PRC: 

—The April 24, 2006 regulation that permitted the import of poultry products 

from the PRC that were processed from slaughtered poultry of United States 

or Canadian origin was approved under suspicious circumstances and Congress 

should conduct an investigation into this matter. The fact that the Office of 

Management and Budget approved this regulation in record time—within 24 

hours of its receipt of the rule from USDA—and the day before the arrival of 

PRC President Hu Jintao in Washington on April 20, 2006 clearly indicated 

that its approval was orchestrated. 

—There is no track record to show that the April 24, 2006 regulation has been 

working. In a recent Global Agriculture Information Network (GAIN) report 

issued by USDA’s Foreign Agriculture Service, the PRP has complained that the 

rule has been a non-starter because it is economically burdensome.9 We consider that to be a weak argument to justify the expansion of the current trade 

situation for several reasons. First, we have concerns about the sanitation practices in the slaughter and processing facilities in the PRC. The audit reports 

filed by FSIS inspectors describe unsanitary conditions in some of the facilities 

in the PRC that might be eligible to export product to the United States.10 Second, the PRC still has an avian flu problem.11 Third, by USDA’s own admission, 

much of the smuggled poultry that is intercepted coming to the United States 

originates from the PRC.12 Why should we reward illegal activity by expanding 

trade? 

USDA–Agricultural Marketing Service 

Large seafood companies and trade associations have complained about the costs 

of implementing country of origin labeling for fish, while fishermen, environmental 

and consumer groups contend that the costs of compliance are fair and worthwhile. 

AMS recognized that most fishermen already keep sufficient records to document 

country of origin and wild-caught versus farm-raised claims, making a $241 per 

year estimation ‘‘within reason.’’ 

All sellers, not only supermarkets, should be included in the program. Exempting 

processed seafood from the program does not accurately reflect the law, given that 

processed foods count for up to 50 percent of the finished product. The USDA should 

ensure that all seafood sold at all retailers is labeled with the proper country and 

means of origin. 

Food and Drug Administration 

We recommend increased funding for the Food and Drug Administration’s seafood 

inspection program. Eighty percent of the seafood consumed by Americans now 

originates in foreign countries, yet according to a January 30, 2004 Government Accountability Office report entitled ‘‘FDA’s Imported Seafood Safety Programs Shows 

Some Progress, but Further Improvements Are Needed,’’ only 1.2 percent of imported seafood shipments are tested at ports of entry. Recent import inspection data 

from the FDA indicates that inspection rates are woefully low to ensure that consumers are protected from unsafe drugs and chemicals used in fish farming in other 

countries, as well as decomposed and filthy seafood—the number one inspection violation since 2003. We recommend that the FDA improve testing of seafood products, 

implement new regulatory programs, tighten its standards, provide incentives for 

producers to reduce drug and chemical use, and give consumers enough information 

to make informed decisions. 

PREPARED STATEMENT OF FRIENDS OF AGRICULTURAL RESEARCH—BELTSVILLE

Mr. Chairman, and Members of the Subcommittee, thank you for this opportunity 

to present our statement regarding funding for the Department of Agriculture’s Ag-
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ricultural Research Service (ARS), and especially for the Agency’s flagship research 

facility, the Henry A. Wallace Beltsville Agricultural Research Center (BARC), in 

Maryland. Our organization—Friends of Agricultural Research—Beltsville—promotes the Center’s current and long-term agricultural research, outreach, and educational missions. 

Our testimony will emphasize two main themes: First, we begin by adding our 

strongest endorsement for high-value ‘‘new’’ research items proposed in the President’s fiscal year 2008 budget. We provide additional support for each new research 

item in Part I. 

Second, we recommend and urge continuing full support for on-going research 

that the Congress has previously mandated to be carried out at BARC. Support for 

these items is essential to sustaining irreplaceable research momentum now and 

fundamental to the success of American agriculture in the future. We will elaborate 

on the basis for our recommendations in Part II. 

PART I. NEW RESEARCH ITEMS PROPOSED IN THE FISCAL YEAR 2008 BUDGET

Obesity Prevention Research, $1,150,000.—Obesity is a growing health menace in 

the United States. Today, an estimated 64 percent of all Americans are overweight 

or obese. Obesity has been linked to heart disease, stroke and cancer, and thus to 

spiraling health problems and rapidly rising health care costs. These funds would 

provide critical support for BARC and its collaborators to pursue vital clinical and 

translational research on the efficacy of the Dietary Guidelines and to develop improved strategies for preventing unhealthy weight gain in the diverse American population. We urge support for this research. 

Food Safety, $708,000.—Maintaining consumer confidence in the safety of the 

U.S. food supply is a primary goal for producers and marketing managers. Recent 

isolated food safety incidents highlight the need for research to identify points in 

the food chain where food can become contaminated by chemical residues, pathogenic bacteria or toxins that are capable of causing severe illness, even death in 

worst case situations. These funds provide the resources to examine production systems and pre-harvest crop management practices thoroughly, especially for leafy 

vegetables and organic produce. We endorse full funding for this work. 

Research to Support the Animal and Plant Health Inspection Service, APHIS, Citrus Canker and Ralstonia, $850,000.—APHIS needs effective diagnostic tools to 

identify emerging citrus and tree fruits diseases, to confirm infections in epidemiological studies, and to carry out regulatory programs. This research also strengthens 

the National Citrus Pathogen Collection, which is essential for effective citrus disease research. Some of this research may be directed to Ralstonia, a bacterial pathogen not known to occur in the United States. Ralstonia causes wilt in potatoes, tomatoes, peppers, eggplant, and other crop plants. APHIS and ARS need to design 

survey protocols to detect and track plant disease agents and to identify crop pathogen threats. Research on diseases of citrus, tree fruits, and other crops is extremely 

under funded. We strongly urge support for strengthening plant disease research 

and for supporting the action mission of the Animal and Plant Health Inspection 

Service. 

Emerging Diseases and Animal Health, $1,165,000.—Globalization of trade and 

the growing movement of people and goods around the world steadily raise the 

threat of disease outbreaks in the United States. Diseases such as avian influenza, 

bovine diarrhea, transmissible spongiform encephalopathies, and porcine reproductive and respiratory disease are among many such disease threats. Effective control 

strategies require a more complete understanding of not only the basic biology of 

pathogens and their mode of transmission but also of the animal’s immune system 

for resisting infections. BARC has one of the country’s premiere groups of scientists 

engaged in livestock immunology research. This funding would strengthen their research effort to more fully unravel the complexity of the animal’s immune system 

and protect the health of U.S. livestock. This research is vital to advancing our understanding of livestock immunology, and for protecting and improving animal 

health. We support full funding for these studies. 

Emerging Diseases of Livestock, $195,000.—This research is vital to further understanding genetics and genomics methods to improve disease resistance in livestock. 

We recommend full funding. 

Emerging Diseases in Crops, $500,000.—We confirm and support the proposal to 

develop diagnostics for rapid, practical, and specific identification of pathogens. This 

is an under funded research area, and we recommend full support. 

Soybean and Wheat Stem Rust, $300,000.—This goal here is to identify and incorporate diverse sources of genetic resistance into new grain and soybean varieties 

and germplasm. We fully support this research. 
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Plant Introduction Stations and the National Plant Germplasm System, 

$500,000.—These funds are necessary for making germplasm and associated information more readily available to research programs and user stakeholders. These 

funds are needed to support the activities of the Germplasm Resources Information 

Network, or GRIN, which provides germplasm information about plants, animals, 

microbes and invertebrates. We recommend full funding. 

Specialty Crops Genetic Resources, $250,000.—These funds will provide floral and 

nursery plant research to support the research mission of the U.S. National Arboretum. Full funding is recommended. 

Part II. Now we turn to the urgent need to continue support for specific research 

areas that the Congress has mandated at BARC in previous fiscal years. These 

mandates address research that has enormous national impact. We list them here 

with brief descriptions and our recommendations for continued funding. 

Dairy Genetics.—For over 75 years, the Animal Improvement Programs Laboratory has created statistical genetic predictions to aid the dairy industry in identifying the best bulls for dairy breeding. Genetic improvement in dairy cattle has 

steadily increased milk yield per cow and feed efficiency (milk produced per pound 

of feed) over many years. The result is lower milk prices for consumers and less animal waste to contaminate the environment because fewer cows are needed to 

produce the Nation’s milk supply. We confirm that this mission critical research 

should continue. 

Barley Health Food Genefits.—Barley contains soluble fiber compounds, called 

beta-glucans, that are beneficial for health. Beta-glucans can lower cholesterol and 

improve control of insulin and blood sugar. These funds support human-volunteer 

studies designed to help us better understand how barley could be used in a healthful diet to reduce the incidence of chronic disease. We recommend continued support. 

Biomineral Soil Amendments for Control of Nematodes.—Plant nematodes are microscopic worms that feed on the roots of plants. Nematodes can cause substantial 

losses in crop yields. This research focuses on using such industrial byproducts as 

environmentally benign soil additives for controlling nematodes. We recommend 

funding for these promising approaches. 

Foundry Sand Byproducts Utilization.—Waste sands from the metal-casting industry currently are dumped in landfills. This project is working with industry on 

guidelines for beneficial uses of these sands. We recommend continuation. 

Poultry Disease (Avian Coccidiosis).—Coccidiosis, a parasitic poultry disease, costs 

the industry $2–3 billion per year. This research focuses on understanding the genetics of both the parasite and the host chicken to identify targets that will allow 

better disease control. We recommend this funding. 

Biomedical materials in plants: Plants can be used as factories to manufacture 

vaccines and other pharmaceuticals for both animals and humans. This research focuses on development of tobacco as a crop with this beneficial use. This research 

should continue. 

National Germplasm Resources Program.—Sources of germplasm for all agricultural crops are maintained either as seed or live plant material at several locations 

across the country. Much of this germplasm is the result of plant exploration around 

the world. This group maintains the computer database that indexes all crop 

germplasm in our repositories with critical information as to where it was obtained, 

the specific scientific identification, and information on useful traits for plant breeding. We strongly support continued funding for this mission-critical program. 

Bovine Genetics.—This research focuses on bovine functional genomics, especially 

for dairy cattle. Scientists are identifying specific genes for quality traits such as 

easier calving, higher milk production, and resistance to mastitis. We recommend 

this funding. 

Minor-use Pesticides (IR–4).—‘‘Minor-use’’ pesticides are those that are used on 

crops such as fruits and vegetables that are not one of the ‘‘big four’’ crops like corn, 

wheat, and soybeans, and cotton. Because markets are much smaller than for major 

crops, chemical manufacturers have little incentive to obtain all the safety data 

needed to obtain EPA registration for pesticides used on minor crops. Nevertheless, 

producers of minor crops find certain agrochemicals to be essential. This project produces the data needed for EPA registration of minor-use pesticides. We recommend 

continued funding. 

National Nutrition Monitoring System.—Scientists at BARC have the unique responsibility of carrying out the national surveys of food consumption by individuals. 

This is now done in collaboration with HHS’s health surveys. BARC scientists also 

maintain the National Nutrient Database, which includes information on 126 nutrients in thousands of foods. This work supports the school lunch program, WIC, Food 
760 

Stamps, senior nutrition programs, food labeling, dietetic practices, and even the 

EPA. We urge continuation of this funding. 

Coffee and Cocoa.—Producers of chocolate candy are the single largest users of 

fluid milk, sugar, peanuts, and almonds in the United States. U.S. specialty coffee 

shop chains also are one of the major markets for fluid milk. Events that limit the 

availability of cocoa or coffee can have significant impacts on major U.S. commodity 

markets. Candy producers need a stable supply of cocoa, but smallholders in developing countries produce most cocoa. Several devastating diseases and insects threaten cocoa. This research is aimed at developing environmentally friendly ways to control pests and diseases. Some insects that threaten coffee are very similar to those 

that attack cacao, thus work on the two crops benefits from being together. We recommend continuation of this funding. 

Johne’s Disease.—Johne’s disease is a contagious bacterial disease of the intestinal tract of ruminants. It occurs most often in dairy cattle, causing weight loss and 

diarrhea. Nearly one-fourth of dairy herds are infected. Producers lose $54 million 

annually from reduced milk production. The disease is spread in manure. This research focuses on disease control. We recommend continuation of this funding 

Food Safety—Listeria, E.Coli, and Salmonella.—Food-borne illness annually costs 

$3 billion in health-care costs, and annually costs the economy up to $40 billion in 

lost productivity. This research focuses on diagnostics for food-borne pathogens, and 

on ways to control pathogens in fruits and vegetables. We recommend continuation 

of this funding 

Weed Management Research.—All farmers must contend with weeds. For organic 

farmers, weeds are the single biggest challenge to crop production. This research, 

in collaboration with the Rodale Institute and Pennsylvania State University, focuses on developing systems for controlling weeds in organic production systems. 

Organic crop production was valued at $400 million per year in the 2002 Census 

of Agriculture. These research funds will improve non-chemical weed control. 

Mr. Chairman, that concludes our statement. We again thank you for the opportunity to present our testimony and for your generous support. 

PREPARED STATEMENT OF THE HARDWOOD FEDERATION, NATIONAL ASSOCIATION OF

STATE DEPARTMENTS OF AGRICULTURE, NATIONAL ASSOCIATION OF STATE FORESTERS, THE NATURE CONSERVANCY, AND SOCIETY OF AMERICAN FORESTERS

Dear Mr. Chairman and Ranking Member, the Hardwood Federation, National 

Association of State Departments of Agriculture, National Association of State Foresters, The Nature Conservancy, and Society of American Foresters urge the Subcommittee on Agriculture, Rural Development, Food and Drug Administration, and 

Related Agencies to increase funding substantially for the USDA Animal and Plant 

Health Inspection Service (APHIS) Emerging Plant Pests program. A sharp increase 

in funding is necessary in order to ensure adequate funding for eradication and control efforts targeting the emerald ash borer, Asian longhorned beetle, sudden oak 

death pathogen, and Sirex woodwasp. All four foreign and invasive species threaten 

trees in our forests and communities and related economic values worth hundreds 

of billions of dollars. 

This coalition represents a widely diverse group of stakeholders that are unified 

in support of the following program areas. This statement of common goals supplements individual letters to the Subcommittee submitted by several of these organizations. Some of these individual letters address additional issues. 

We seek an appropriation of $45 million for fiscal year 2008 to contain the emerald ash borer. The emerald ash borer threatens twelve species of ash across the continent, especially in the upper Midwest and Southeast. At risk are the $25 billion 

ash timber industry in the Northeast, street trees across the Nation valued at $20 

to $60 billion, and myriad trees found in our neighborhoods and parks. The emerald 

ash borer outbreak is large, but the core of the infestation remains in the lower peninsula of Michigan and neighboring portions of Indiana and Ohio. It is absolutely 

crucial that APHIS and its partners carry forward detection surveys and regulatory 

and educational programs aimed at preventing movement of infested firewood, nursery stock, and other materials that spread the insect. APHIS and its State partners 

need additional funding in fiscal year 2008 to enable affected States to eradicate 

limited and isolated outbreaks found in Illinois, Maryland, Ohio, Indiana, and 

Michigan’s Upper Peninsula. Education, effective quarantine, and elimination of isolated infestations are necessary to create the potential to contain the core outbreak 

in and around Michigan. 

We seek an appropriation of $30 million for fiscal year 2008 to carry forward 

eradication of the few remaining populations of the Asian longhorned beetle. The 
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Asian longhorned beetle poses an alarming threat to hardwood forests reaching from 

New England into Minnesota and in the West, and to the hardwood timber, maple 

syrup, and autumn foliage tourism industries dependent on these forests. Also at 

risk are street trees across the Nation valued at more than $600 billion. Eradication 

has been successful in Chicago, proving the efficacy of this approach. Beetle populations in New Jersey are well on track for eradication. Only the populations in New 

York persist—and that is because funding for the New York effort has been reduced 

in past years to focus the inadequate overall resources on Illinois and New Jersey. 

It is essential to provide sufficient funding now and in coming years to complete 

eradication in New Jersey and New York. The identification of another population 

on an island near Staten Island just this past week is an indication of the risk 

placed on the environment due to chronic under-funding of these programs. 

We support a request for $10 million in appropriations for fiscal year 2008 to contain a third damaging forest pest, the sudden oak death pathogen (also called the 

phytophthora leaf and stem blight pathogen). This disease is a major threat to the 

nation’s nursery industry as it readily attacks species such as rhododendron, camellias and a long list of other common ornamentals. In addition, if sudden oak death 

does escape confinement, it threatens oaks in forests in Oregon and Washington as 

well as throughout the Appalachians, Ozarks, and even into southern New England. 

Many wildlife species are dependent upon oaks for forage—the potential for devastating impacts on forests and wildlife is very real. 

The Sirex woodwasp is now found across much of New York State and two counties in Pennsylvania, as well as in Ontario, Canada. The woodwasp threatens valuable pine timber resources, especially those of the Southeast. It is essential that 

APHIS receive $3.6 million in fiscal year 2008 to implement a program including 

regulatory and educational programs aimed at preventing movement of infested 

wood, nursery stock, and other materials that spread the insect. 

In addition to the appropriations needed to support these line items in APHIS’s 

Emerging Plant Pest program, the Hardwood Federation, National Association of 

State Departments of Agriculture, National Association of State Foresters, The Nature Conservancy, and Society of American Foresters also strongly support the Congress’ numerous statements urging the Administration to release emergency funds 

from the Commodity Credit Corporation (CCC) sufficient to enable full implementation of these management plans. The combination of the appropriations and the release of CCC funds is necessary to accomplish the needed tasks. 

Action now at the funding level requested would help ensure that these forest 

pests do not reach populations so large as to threaten trees in our forests and communities, garden nursery stock, and related economic activities worth hundreds of 

billions of dollars. 

PREPARED STATEMENT OF THE HEART RHYTHM SOCIETY

Dear Mr. Chairman, The Heart Rhythm Society (HRS) thanks the Subcommittee 

for considering our comments regarding the need for increased funding of the Food 

and Drug Administration (FDA), in particular the Center for Devices and Radiological Health (CDRH). The Heart Rhythm Society recommends that the FDA receive an additional $20 million in appropriations for medical device oversight, as 

recommend by the Coalition for a Stronger FDA. These dollars would in part go to 

reform and update the current post-market surveillance system, which is currently 

ill-equipped to handle the complex challenges of responding to product safety issues 

and providing timely information to physicians, patients and the public. 

The Heart Rhythm Society, founded in 1979, is the international leader in science, 

education and advocacy for cardiac arrhythmia professionals and patients, and the 

primary information resource on heart rhythm disorders. Our mission is to improve 

the care of patients by promoting research, education and optimal health care policies and standards. We are the preeminent professional group, representing more 

than 4,400 specialists in cardiac pacing and electrophysiology. The Heart Rhythm 

Society serves as an advocate for millions of American citizens from all 50 States, 

since arrhythmias are the leading cause of heart-disease related deaths, with Sudden Cardiac Arrest (SCA) taking 325,000 lives annually. Other, less lethal forms of 

arrhythmias are even more prevalent and account for 14 percent of all hospitalizations of Medicare beneficiaries. 

Background 

Implantable Cardioverter Defibrillators (ICD’s) are 99 percent effective in stopping life-threatening arrhythmias and are the most successful therapy to treat ventricular fibrillation, the major cause of Sudden Cardiac Arrest (SCA). However, less 
762 

than 2 years ago, there was a crisis in the patient and physician community regarding the ability of the current post-market surveillance system to react to information 

on implanted cardiac devices and to communicate the essential data to physicians 

and patients in a timely manner. In 2005, recalls and advisories issued by the three 

largest pacemaker defibrillator manufacturers and the untimely death of a patient 

with a device malfunction, led the Heart Rhythm Society to focus attention on the 

post-market system and the critical need for reform. It quickly became apparent to 

the Heart Rhythm Society, that leadership was necessary to convene members of 

our community, industry and patients to discuss the inherent issues with the current post-market surveillance system and work together to make recommendations 

for improvement. In September 2005, HRS convened a policy conference, co-sponsored with the FDA, of 300 experts in industry, the law, FDA, physician community, 

risk communication and patients to explore improvements for post market surveillance of pacemakers and ICDs. As a result of that meeting, the Society assembled 

a 15-member task force of leading cardiac care providers and experts charged with 

the development of recommendations to address concerns raised at the conference. 

In September, 2006, the Heart Rhythm Society published the Device Performance 

Recommendations to improve the post-market surveillance system for implanted devices. The guidelines have been officially endorsed by the American College of Cardiology Foundation, American Heart Association and the International Coalition of 

Pacing and Electrophysiology Organizations (COPE). 

Current Limitations of Post Market Surveillance for Implanted Devices 

As described in the Recommendations, changes to the current post-market surveillance system are required to improve the timely identification of cardiac rhythm 

management devices that do not perform according to design and that may pose a 

danger to patients. The current Manufacturer and User Device Experience 

(MAUDE) system assists with adverse event reporting and information dissemination for medical devices of all types. It contains hundreds of thousands of adverse 

event reports. Selected information is publicly searchable via the internet. However, 

because submitted adverse event reports are often cryptic or incomplete, it is often 

difficult to determine if a true device malfunction or patient injury has occurred. 

Poor organization and retrieval tools within MAUDE frustrate the users’ ability to 

retrieve useful information. It is particularly difficult to distinguish multiple reports 

about the same adverse event from several sources (from the manufacturer, physician and patient) and recognize updated information. It has been noted by many 

that MAUDE has other inherent problems including the issue of under reporting, 

out of date information, and having inadequate resources to meet the current needs 

for medical device surveillance. Registries have been created by physician groups to 

begin to meet gaps in FDA efforts in medical device surveillance. The current 

MAUDE system also utilizes a one-size-fits-all form for all medical devices, making 

it difficult to collect meaningful information. 

Needed Changes 

The Heart Rhythm Society recommends that the FDA design and implement a 

more robust reporting system for observed device malfunctions that could overcome 

many of the MAUDE shortcomings and strengthen the voluntary reporting system 

by: 

—Utilizing a specialized form for cardiac rhythm management devices to permit 

better and more precise reporting of adverse events. 

—Facilitating the reporting of all unexpected device malfunctions through the 

adoption of remote monitoring technologies. 

—Tracking devices that are returned to manufacturers for analysis and updating 

publicly available adverse event reports with root cause analyses. The system 

should allow individuals to track devices through the manufacturers’ analysis 

online, analogous to tracking an overnight package. 

—Including in the database the adjudication of root cause analysis once that has 

been determined. 

—Facilitating links to data from international sources which may permit earlier 

detection of device malfunction. 

—Employing an internet based reporting system with a user friendly format to 

encourage submission of reports by health care providers. 

—Including standardized data elements and definitions for each device malfunction such as manufacturer model and serial numbers, dates of implant and failure, signs of failure and clinical consequences. 

—Including a search engine available for public use. 

Additionally, the FDA should establish standing post-market advisory committees 

that meet on a regular basis to analyze data regarding cardiac rhythm management 
763 

device performance and to advise when and what action should be taken to address 

device malfunctions that are identified. The Heart Rhythm Society supports a centralized, rather than the current regional, system for communication of device advisory notifications to promote a broader and more inclusive interpretation of the advisory issues. In addition, the unique and specialized nature of cardiac rhythm management device advisories requires a centralized, rather than regional, intake mechanism to enable accurate interpretation of data on an ongoing basis by key knowledgeable FDA staff and by the other parties such as a post-market physician advisory panel. The Heart Rhythm Society believes that a centralized system will facilitate timely FDA classifications and urges the FDA to classify all advisory notifications and include these data on the Physician Device Advisory Notification form 

within 30 days. 

Budget Justification 

To implement the above suggested changes, the FDA will need additional resources. The FDA’s resources in recent years have diminished while Congress has 

mandated increases in FDA’s oversight responsibilities. The number of regulated 

products, imports and adverse event reports has grown rapidly in the past 6 years 

and FDA is asked do more with less. Furthermore, public confidence in the agency’s 

effectiveness has taken an unfortunate hit. We urge Congress to recognize that postmarket surveillance, analysis, and reporting of ICD and pacemaker performance is 

a high priority for ensuring patient safety. Additionally, we urge you to recognize 

and address the issue that the FDA does not currently have adequate resources to 

perform this function. The enhancements to the surveillance system that HRS recommends, particularly those to the Manufacturer and User Facility Device Experience (MAUDE) database, will require additional resources. By providing such resources, Congress will enable the FDA to achieve its mission, enhance the lives of 

the rapidly growing number of Americans with these devices and their families, and 

may decrease costs associated with delayed identification of device malfunction. 

It is for this reason that we are asking for your support to increase the FDA’s 

medical device budget by $20 million for fiscal year 2008 budget. We believe that 

these additional funds will assist the FDA in addressing concerns that have been 

raised about the safety and effectiveness of pacemakers and ICDs and the post-market surveillance of these life saving devices. We believe patient and physician 

knowledge, confidence and trust can be enhanced and strengthened through greater 

transparency in post-market surveillance, analysis, reporting and communication of 

this information. Thank you very much for your consideration of our request. 

If you have any questions or need additional information, please contact Nevena 

Minor, Coordinator, Health Policy at the Heart Rhythm Society 

(nminor@hrsonline.org or 202–464–3431) or Amy Melnick, Vice President, Health 

Policy (amelnick@hrsonline.org or 202–464–3434). 

PREPARED STATEMENT OF THE IMPERIAL VALLEY CONSERVATION RESEARCH CENTER

COMMITTEE

My name is John R. Kershaw, President of the Imperial Valley Conservation Research Center Committee (IVCRCC). This is a group of Imperial Valley agricultural 

producers who volunteer to provide support to the ARS Brawley Research Station 

in Imperial County, California. These farmers provide financial assistance and provide necessary equipment to augment the station’s annual operating budget. We are 

a 501(c)(5) nonprofit organization. This is a unique industry-government partnership that has been successfully operating since 1951 when the station was founded. 

The many achievements of this research facility rank it with the more successful 

ARS/USDA stations in the United States. For example, it is one of the lowest-cost 

field stations in the entire USDA network of agriculture research sites. This is true 

even though it is situated in one of the most challenging areas for farming and 

ranching due to the intense heat and dry conditions. Producers in our area farm 

land high in salinity content that is irrigated by water containing large amounts of 

salt. 

The region where the Brawley station is situated has an incredible variety of vectors for insect and crop disease pests. The agriculture industry could not exist without strategic research programs dealing with soil, water, pest and disease problems 

that habitually confront producers. These programs, which are and have been addressed in Brawley, range from salt tolerance studies on food crops to new crop 

management studies using high salinity water, whitefly pest densities, virus transmission and ecological genetics of pest populations, biological control programs and 
764 

IPM programs using parasites and predators in conjunction with microbial pesticides. 

With the help of crucial federal funding, the Brawley station is pioneering projects 

beneficial not only to agriculture, but, perhaps more importantly, to urban interests 

as well. It is participating with the New River Congressional Task Force addressing 

the quality of the New and Alamo Rivers. The focus of the this study is to demonstrate the effectiveness of using constructed wetlands to improve water quality in 

the Imperial Valley and inflows to the Salton Sea, whose water elevation is maintained by agricultural drainage from the tributaries of the Alamo River, New River 

and Whitewater Rivers. 

Expanding its traditional research in order to assist USDA in its desire to establish greater focus on forage research in the West, the Brawley Research Station has 

been conducting tests on a low-cost, high yield forage plant with multiple potential 

uses, including phytoremediation. This forage plant’s characteristics allow it to be 

used to improve agricultural runoff and tailwater. The plant is called Elephant 

Grass, also known as Napier Grass (Pennisetum Sp) and has a trademark name of 

Promor A. It was discovered in Brazil and brought to the United States through the 

USDA Beltsville Quarantine Station in 1991. Experimental investigations in the 

San Joaquin Valley indicated that the plant, when irrigated exclusively with dairy 

lagoon water, exhibited significant phytoremediation with respect to high absorption 

of nitrates and phosphates. This unique variety is also regarded as a real candidate 

for biomass, including a specific capability for ethanol production. 

A large group of pregnant beef cattle cows and their calves grazed the leaves of 

the grass to the ground in an experiment demonstrating its palatability and lack 

of toxicity. An additional large-field phytoremediation trial for irrigation was conducted at a raisin packing facility using processed wash water with significant nitrate levels. The grass used in this experiment was harvested after 60 days. Forage 

samples and weight measurements indicated a nitrate uptake of almost 55 pounds 

per acre per day. The harvested green chop forage was fed to dairy calves with no 

ill effects. 

Additional research at the Brawley station, including a cooperative project with 

the University of California at Meloland, show the palatability and acceptability of 

this grass as use in finishing diets for feedlot cattle. Further research being conducted at the Brawley station utilizing elephant grass fed to lactating cows under 

the direction of the University of California were also very positive. 

These experiments utilizing Pennisetum SP elephant grass have drawn the interest and financial support of the California State Quality Control Board. This Board 

regards the grass as a serious candidate for a barrier crop designation to improve 

water quality. Ongoing research with the City of Fresno on its waste water support 

the finding that this grass may have major benefits for city water supplies. Urban 

use of the grass may result as additional cities work to clean up their water. 

All of the above projects fall directly under the mandate for research designated 

by the National Program 201 Water Quality administered by ARS. This research 

is part of ARS current policy and future focus. To terminate the project prematurely 

due to lack of funding would severely limit the conclusions and potential benefits. 

This research facility is continuing the ongoing research on its popular 

Rhyzomania resistant sugar beet seeds. This research is conducted under the supervision and direction of ARS scientist Dr. Llewellen from Salinas. The resultant 

sugar beet seed has doubled sugar beet production yields. This research is benefiting sugar beet producers nationwide. 

The research station additionally serves as a work site and regional office for 

APHIS/USDA and the California Department of Food & Agriculture. 

The research facilities are also utilized by several local agricultural entities including cotton committees and the California Farm Bureau. We continue as a support laboratory for the unique Salinity Assessment Vehicle and also serve as a 

weather station reporting location. 

In addition to the station’s diversified agricultural research agenda, it is strategically located to provide quick response support to biosecurity and agroterrism detection work. It is situated less than 90 miles from six Mexican border crossings; one 

of which is only 16 miles from Brawley, and is the busiest crossing anywhere. The 

constant supply of international traffic puts Imperial Valley on the front line of protection of the American food supply from the introduction of disease, insects and 

many invasive species. The station currently headquarters research facilities and 

personnel from USDA and the California Department of Food & Agriculture which 

can quickly implement control and eradication programs in coordination with local 

authorities, thereby making use of the best capabilities of local, State and Federal 

agencies. 
765 

As for its research agenda, the station performs many trials associated with the 

arid saline conditions of the region. Specific experiments may be conducted on, but 

not limited to, water management, irrigation techniques, soil salinity, crop production, plant breeding, agricultural systems, control of aquatic weeds and integrated 

pest management. 

Our salinity trials are conducted in conjunction with the U.S. Salinity Lab based 

in Riverside, California. The salinity work done at the Brawley station could not effectively be performed at Riverside because smog there negates scientific validity of 

the findings. The Brawley Research Station is geared to be a contributor, if asked, 

to the National Salt Cedar Demonstration Project. The station has been monitoring 

native species that could be used in the revegetation of Salt Cedar that will be removed or mitigated. 

There is a date palm repository at the Imperial Valley Research Center. This is 

the largest repository of date palms in the world. It contains every known variety 

of date palm. This repository is used for research. Additionally, this repository is 

used to provide varieties of date palms to various countries where the United States 

is encouraging farmers to grow dates. 

The Imperial Valley Conservation Research Center Committee specifically re- quests that $334,514 be appropriated to fund the Water Management Research Laboratory in Brawley, CA. 

The funds for this ARS/USDA research facility were deleted from the President’s proposed budget. As you know, the President’s budget deleted over $200 million for 

ARS research facilities nationwide. Loss of these research facilities would be a blow 

to U.S. agriculture nationwide. Specifically it would be a blow to California agriculture and especially to agriculture in the Imperial Valley. 

The ARS research station in Brawley is in very good condition and has been well 

managed. The research provided by this facility far exceeds the value of the funds 

requested. The farmers in the Imperial Valley continue to support this facility with 

matching funds amounting to approximately $100,000. 

We urge you, Mr. Chairman, to support the continued funding for this important 

ARS research station in the fiscal year 2008 agricultural appropriations bill. 

PREPARED STATEMENT OF THE MULTI-CROP AFLATOXIN WORKING GROUP

As members of the Multi-Crop Aflatoxin Working Group, the undersigned associations appreciate the opportunity to share with you our agricultural research priorities for fiscal year 2008. 

As you know, corn, cotton, peanuts and tree nuts are all affected by aflatoxin, a 

toxin caused by the Aspergillus flavus fungus. Aflatoxin is the costliest, most pressing mycotoxin problem affecting each of these crops. Widespread drought conditions 

in 2005 resulted in aflatoxin contamination levels in excess of earlier levels, and 

more troubling in areas of the country that are not usually prone to the problem. 

Aflatoxin also dramatically decreases U.S. global competitiveness and farm income. Most of our export customers have more stringent aflatoxin tolerances than 

the U.S., resulting in closed markets. Likewise, an aflatoxin level in excess of FDA 

guidelines significantly limits the marketability of the product. 

Despite the dire consequences aflatoxin has on agricultural marketing and human 

safety, Federal research budgets in this area have been declining for the past decade. Given recent events and the spread of the disease, the Multi-Crop Aflatoxin 

Working Group recommends $1.25 million for aflatoxin research through the PreHarvest Control of Aflatoxin research program. Specifically, this is an increase of 

$500,000 over fiscal year 2007 funding levels. These funds will be administered by 

the Agricultural Research Service (ARS) and dispersed on a competitive basis for 

aflatoxin research. These grants are awarded on both crop specific and aflatoxinwide research. Some examples of current research are conventional crop breeding, 

use of atoxigenic strains, host and fungal genomics, genetic blocks of toxin production and transgenic resistances. Although each of these projects have different approaches, they all share one common goal, the elimination of aflatoxin from the 

worlds food supply. Following this statement, we have provided the Committee with 

an example of previous work funded by ARS. 

Thank you for the support and assistance you have provided to agricultural research over the years. Please contact Lisa Kelley with the National Corn Growers 

Association at 202–628–7001 or Howard Valentine with the Peanut Foundation at 

706–579–1755 if you need any additional information. 

APPENDIX

Previous Work Funded By ARS: 
766 

1 As part of its mission, National C–FAR seeks to increase awareness about the value of food 

and agricultural research, extension and education. For example, National C–FAR is hosting an 

educational series of ‘‘Lunch∼N∼Learn’’ seminars on the hill, featuring leading-edge researchers 

on timely topics to help demonstrate the value of public investment in food and agricultural research, extension and education. More information about National C–FAR and its programs is 

available at http://www.ncfar.org. 

In Dr. Felicia Wu’s previous work funded by ARS, ‘‘Total Economic Impact of 

Aflatoxin: Models of Economic Loss and Industry Learning,’’ she developed the conceptual basis for the aflatoxin economic model shown in Figure 1 of the Research 

Approach. She implemented the following equations under ‘‘Noncompliance Adjustment Costs’’ and ‘‘Livestock Health Effects’’ for corn, by considering two classes of 

impact: market losses and animal health losses. 

High quality corn can be sold as human-food-grade corn at the highest market 

price. Corn contaminated with aflatoxin levels between the highest-permitted levels 

of food and feed can be sold for animal feed at a lower price, and corn with high 

levels of aflatoxin is either sold for non-food-non-feed uses at an even lower price 

or rejected outright. The proportions of the total crop that are rejected at each of 

these levels depend on the national or international standards for mycotoxins in 

food and feed. Thus: 

LossMarket = Mcrop*[dPfoodQfoodRfood∂dPfeedQfeedRfeed], where 

Mcrop = proportion of total corn production sold 

dPfood = price difference between food-grade and feed-grade corn 

dPfeed = price difference between feed grade and lowest-grade corn 

Qfood, Qfeed, = quantities intended for food and feed, respectively 

Rfood, Rfeed = proportions of corn found to be above aflatoxin guidelines for feed 

and feed 

Animal health as a function of aflatoxin contamination is dependent on three factors: the number of animals experiencing mortality or morbidity as a result of 

aflatoxin consumption, the cost of treatment for sick animals, and the market value 

of each animal. 

LossAnimal =7a [(Amort,a*[Vanimal,a∂ Treata] ∂ Amorb,a Treata], 

where 

Amort, Amorb = number of animals experiencing mortality or morbidity 

Vanimal = market value per animal 

Treata = medical treatment cost per animal 

The subscript a indicates the affected species of animals a = {cattle, swine, poultry} 

Data for each of these parameters were gathered from the USDA National Agricultural Statistical Service (NASS) and elevant literature on aflatoxin’s animal effects (Lubulwa and Davis 1994, Keyl 1978, Wyatt 1991). Annual aflatoxin-related 

market losses in U.S. corn were estimated to be $163 million ($73–332 million; 95 

percent CI): $31 million in food-grade rejections and $132 million in feed-grade rejections. Annual livestock losses were estimated at $4 million ($1–9 million). Sampling and testing costs vary by year, with an average $25 million cost annually to 

growers ($10–250 million; the large confidence interval reflects the high variability 

in this area). In addition, the following currently ‘‘intangible’’ costs were considered: 

losses related to ethanol production (and the resulting concentration of aflatoxin in 

the distillation byproducts), grower disposal of highly contaminated corn, sampling 

errors, and losses on a geographical basis. The total annual loss to U.S. corn of 

measurable aflatoxin-related losses was roughly $200 million ($192 million, with uncertainty bounds); however, the intangible costs could increase this loss significantly. 

Dr. Wu’s first year of work with ARS provided her an excellent opportunity to 

meet key representatives from the major commodities that are affected by aflatoxin 

contamination. She is grateful to the following commodity experts, who, among others, provided her with useful information regarding aflatoxin’s specific impacts on 

each commodity: Larry Antilla, Scott Averhoff, Peter Cotty, David Gibson, Mike 

Hurley, Merle Jacobs, Dave Kendra, Bob Klein, Marshall Lamb, Dewey Lee, Howard Valentine, and Phillip Wakelyn. The insights and data she has gained through 

these collaborations will provide a basis for her economic research in this proposal. 

PREPARED STATEMENT OF THE NATIONAL COALITION FOR FOOD AND AGRICULTURAL

RESEARCH

Dear Mr. Chairman, Ranking Member Bennett and Members of the Subcommittee: On behalf of the National Coalition for Food and Agricultural Research 1
767 

(National C–FAR), we are pleased to submit comments in strong support of enhanced public investment in food and agricultural research, extension and education 

as a critical component of Federal appropriations for fiscal year 2008 and beyond. 

National C–FAR serves as a forum and a unified voice in support of sustaining and 

increasing public investment at the national level in food and agricultural research, 

extension and education. National C–FAR is a nonprofit, nonpartisan, consensusbased and customer-led coalition established in 2001 that brings food, agriculture, 

nutrition, conservation and natural resource organizations together with the food 

and agriculture research and extension community. 

SUPPORT FOR FISCAL YEAR 2008 FUNDING FOR FOOD & AGRICULTURAL RESEARCH, 

EXTENSION & EDUCATION

CSREES.—National C–FAR urges the Subcommittee and Committee to support 

the Administration’s fiscal year 2008 request for USDA’s Cooperative State Research, Education, and Extension Service (CSREES) of $1.036 billion, augmented at 

a minimum by restoring the funding equivalent of ‘‘earmark’’ funding incorporated 

into the fiscal year 2007 CR—and other increases to the extent practicable. The Administration’s proposal represents a 10 percent decrease as compared with fiscal 

year 2007 funding levels, and National C–FAR believes a significant increase is fully 

warranted. 

The Administration’s fiscal year 2008 request does not include about $190 million 

in funding that Congress in the past has invested in so-called ‘‘earmarks’’ in the 

CSREES account. In the fiscal year 2007 CR Congress opted to eliminate the earmarks but included the funding equivalent in the CSREES account. National C– 

FAR strongly urges the Subcommittee and Committee to restore this funding to the 

fiscal year 2008 budget for CSREES, whether designated for specific projects or for 

distribution by CSREES. 

National C–FAR supports funding the National Research Initiative (NRI) at the 

authorized level of $500 million. The Administration’s $256.5 million fiscal year 

2008 request represents a significant increase over the fiscal year 2007 Congressional funding level of $190 million. However, a portion of the proposed increase 

($42 million) results from a shift of CSREES Integrated Activities, such as food safety, pest management, and water quality, providing a net increase of $25 million for 

NRI. 

The NRI supports research on key problems of national and regional importance 

in biological, environmental, physical, and social sciences relevant to agriculture, 

food, and the environment on a peer-reviewed, competitive basis. Additionally, the 

NRI enables USDA to leverage a portion of its funds for food and agricultural research, extension and education by fostering the development of new partnerships 

with other federal agencies that advance agricultural science. Examples of successful collaborations include USDA’s involvement in the Microbial Genome Sequencing 

Program, the Maize Genome Program, the Microbial Observatories program, the 

Plant Feedstock Genomics for Bioenergy program, the Metabolic Engineering program, and the Climate Change Science Plan. 

ARS.—National C–FAR urges the Subcommittee and Committee to support the 

Administration’s fiscal year 2008 request for USDA’s Agricultural Research Service 

(ARS) of $1.056 billion, augmented at a minimum by restoring the funding equivalent of ‘‘earmark’’ funding incorporated into the fiscal year 2007 CR—and other increases to the extent practicable. National C–FAR is concerned that ARS funding 

has been cut each of the past several years and urges the Subcommittee and Committee to sustain and enhance ARS funding. Research conducted by ARS helps to 

ensure high-quality, safe food, and other agricultural products, assess the nutritional needs of Americans, sustain a competitive agricultural economy and enhance 

the natural resource base and the environment. The steady erosion in ARS funding 

could jeopardize the ability of the agency to carry out its important mission. 

According to the Administration, its fiscal year 2008 request of $1.129 billion for 

ARS does not include about $280 million in so-called ‘‘earmark’’ funding [divided 

about equally between research projects and facilities] that Congress in the past has 

invested in. In the fiscal year 2007 CR Congress opted to eliminate the earmarks 

but included the funding equivalent in the ARS account. National C–FAR strongly 

urges the Subcommittee and Committee to restore this funding to the fiscal year 

2008 budget for ARS, whether designated for specific projects or for distribution by 

ARS. 

ERS.—National C–FAR urges the Subcommittee and Committee to support the 

Administration’s fiscal year 2008 request of $83 million for the USDA, Economic Research Service (ERS), which represents a modest increase over the fiscal year 2006 

and fiscal year 2007 appropriated levels and provides additional funding to 
768 

strengthen the market analysis and outlook capabilities and bioenergy economic 

analysis. Many of the research outcomes generated through ERS efforts provide 

value in both policy and business application terms far in excess of what the modest 

size of the ERS budget might suggest. 

FS.—National C–FAR urges the Committee to support the Administration’s fiscal year 2008 funding request of $263 million for forest and rangeland research. National C–FAR is concerned that this represents a decrease in funding compared with 

fiscal year 2007. While the Administration may be justified in dropping lower priority projects, stagnant and declining funding is inappropriate in light of major challenges in forest, range and ecosystem management and utilization. 

National C–FAR urges that funding for food and agricultural research, extension 

and education be augmented to the maximum extent practicable, as an important 

next step toward building the funding levels needed to meet identified food and agricultural research, extension and education needs. 

A Sense of the Congress resolution endorsed by National C–FAR to double funding in food and agricultural research, extension and education within five years was 

incorporated into the 2002 Farm Bill that was enacted into law. However, the major 

commitment to expanded research has not yet materialized. At the five-year mark, 

the larger reality is the threat of funding cuts. National C–FAR is urging the Congress to reaffirm a commitment to doubling funding in food and agricultural research, extension and education in the 2007 farm bill. 

As a coalition representing stakeholders in both the research, extension and education community and the ‘‘customers’’ who need and depend upon their outcomes, 

National C–FAR urges expanded public participation in the Administration’s research priority setting and funding decision process and stands ready to work with 

the Administration and other interested stakeholders toward that end. 

ENHANCED INVESTMENT IN RESEARCH, EXTENSION & EDUCATION ESSENTIAL TO

SUCCESS

The research, extension & education title of the Farm Bill represents the nation’s 

signature Federal investment in the future of the food and agricultural sector. Other 

Farm Bill titles depend heavily upon the Research Title for tools to help achieve 

their stated objectives. Public investment in food and agricultural research, extension and education today and in the future must simultaneously satisfy needs for 

food quality and quantity, resource preservation, producer profitability and social 

acceptability. 

Tools provided through research, extension & education are needed to help 

achieve safer, more nutritious, convenient and affordable foods delivered to sustain 

a well nourished, healthy population; more efficient and environmentally friendly 

food, fiber and forest production; improved water quality, land conservation, wildlife 

and other environmental conditions; less dependence on non-renewable sources of 

energy; expanded global markets and improved balance of trade; and more jobs and 

sustainable rural economic development. Societal demands and expectations placed 

upon the food and agricultural system are ever-changing and growing. Examples of 

current and future needs include—strengthened bio-security; food-linked health 

costs; environment and conservation; farm income and rural revitalization; biofuels 

and climate change; the world demand for food and natural fiber and improved 

diets; and biotechnology and genetic resources research and public oversight. 

DEMONSTRATED VALUE OF PUBLIC INVESTMENTS IN RESEARCH

Publicly financed research, extension and education are necessary complements to 

private sector research, focusing in areas where the private sector does not have an 

incentive to invest, when (1) the pay-off is over a long term; (2) the potential market 

is more speculative; (3) the effort is during the pre-technology stage; and (4) where 

the benefits are widely diffused. Public research, extension and education help provide oversight and measure long-term progress. Public research, extension and education also act as a means to detect and resolve problems in an early stage, thus 

saving American taxpayer dollars in remedial and corrective actions. 

Public investment in research is a wise investment. An analysis by the International Food Policy Research Institute of 292 studies of the impacts of ag research 

and extension published since 1953 (Julian M. Austin, et al, A Meta-Analysis of 

Rates of Return to Agricultural Research, 2000) showed an average 81 Percent annual rate of return on public investments in ag research & extension! 

Food and agricultural research, extension and education to date have helped provide the United States with a food and agricultural system that consistently produces high quality, affordable food, natural fiber and other products, while at the 

same time: 
769 

—Creating Jobs and Income.—The food and agricultural sector and related industries provide over 20 million jobs, about 17 percent of U.S. jobs, and account 

for nearly $1 trillion or 13 percent of GDP. 

—Helping Reduce the Trade Deficit.—Agricultural exports average more than $50 

billion annually compared to $38 billion of imports, contributing some $12 billion to reducing the $350 billion trade deficit in the nonagricultural sector. 

—Sustaining Important Strategic Resources.—This Nation’s abundant food supply 

bolsters national security and eases world tension and turmoil. Science-based 

improvements in agriculture have saved over a billion people from starvation 

and countless millions more from the ravages of disease and malnutrition. 

—Providing Many Valuable Aesthetic and Environmental Amenities to the Public.—The proximity to open space enhances the value of nearby residential property. Farmland is a natural wastewater treatment system. Unpaved land allows 

the recharge of the ground water that urban residents need. Farms are stopovers for migratory birds. Farmers are stewards for 65 percent of non-Federal 

lands and provide habitat for 75 percent of wildlife. 

FUNDING INSUFFICIENT TO ADDRESS PRIORITY NEEDS

By any measure, Federal funding for food and agricultural research, extension 

and education has failed to keep pace with identified priority needs. Public and private investments in U.S. agricultural research and practical application of results 

have paid huge dividends to the United States and the world, especially in the latter 

part of the 20th century. However, these dividends are the result of past investments in agricultural research. The unparalleled success story in the food and agricultural system is a product in large part of past investments in food and agricultural research and extension. 

However, Federal funding for food and agricultural research, extension and education has been essentially flat for over 20 years, while support for other Federal 

research has increased substantially. Public funding of agricultural research in the 

rest of the world during the same time period has outpaced investment in the 

United States. 

Stagnant public investment in food and agricultural research, extension and education may well be a result of a view that the U.S. food and agricultural system 

is doing fine and that funds can be redirected to other needs. The U.S. food and 

agricultural sector has been a world leader and has provided unprecedented value 

to U.S. citizens, and indeed the world community. However, societal demands and 

expectations placed upon the food and agricultural system are ever-changing and 

growing. 

National C–FAR believes it is imperative to lay the groundwork now to respond 

to the many challenges and promising opportunities ahead through Federal policies 

and programs needed to promote the long-term health and vitality of food and agriculture for the benefit of both consumers and producers. Stronger public investment 

in food and agricultural research, extension and education is essential in producing 

research outcomes needed to help deliver beneficial and timely solutions. Multiple 

examples, such as those highlighted below, serve to illustrate current and future 

needs that arguably merit enhanced public investment in research, extension and 

education so that the food and agricultural system can respond to these challenges 

on a sustainable basis: 

—Strengthened bio-security is a pressing national priority. There is a compelling 

need for improved bio-security and bio-safety tools and policies to protect 

against bio-terrorism and dreaded problems such as foot-and-mouth and ‘‘mad 

cow’’ diseases and other exotic plant and animal pests, and protection of range 

lands from invasive species. 

—Food-linked health costs are high. Some $100 billion of annual U.S. health costs 

are linked to poor diets, obesity, food borne pathogens and allergens. Opportunities exist to create healthier diets through fortification and enrichment. 

—Research, extension and education are key to providing to solutions to environmental and conservation challenges related to global warming, limited water resources, enhanced wildlife habitat, and competing demands for land and other 

agricultural resources. Rural water conservation and development of droughtresistant crops have evolved from a good idea to a necessity. 

—It is a highly competitive world for food and agriculture and rural America. 

There was considerable debate during the last Farm Bill reauthorization about 

how expanded food and agricultural research, extension and education could enhance farm income and rural revitalization by improving competitiveness and 

value-added opportunities. 
770 

—Energy costs are escalating, dependence on petroleum imports is growing and 

concerns about greenhouse gases are rising. Research, extension and education 

can enhance agriculture’s ability to provide renewable sources of energy and 

cleaner burning fuels, sequester carbon, and provide other environmental benefits to help address these challenges, and indeed generate value-added income 

for producers and stimulate rural economic development. 

—Population and income growth are expanding the world demand for food and 

natural fiber and improved diets. World food demand is projected to double in 

25 years. Most of this growth will occur in the developing nations where yields 

are low, land is scarce, and diets are inadequate. Without a vigorous response, 

demand will only be met at a great global ecological cost. 

—Regardless of one’s views about biotechnology and genetic resources, an effective 

publicly funded research role is needed for oversight and to ensure public benefits. 

If these challenges and opportunities are to be met, then the nation must commit 

to a stronger investment that reflects the long-term benefits of food and agricultural 

research, extension and education. 

CONCLUSION

National C–FAR respectfully submits that— 

—The food and agricultural sector merits Federal attention and support; 

—Food and agricultural research, extension and education have paid huge dividends in the past, not only to farmers, but to the entire nation and the world; 

—There is an appropriate and recognized role for Federal support of research, extension and education; 

—Recent funding levels for food and agricultural research, extension and education have been inadequate to meet pressing needs; 

—Federal investments in food and agricultural research, extension and education 

should be enhanced in fiscal year 2008 and beyond; and 

—Actions should be taken to provide for expanded public participation, including 

during review of programs being considered for possible reforms or cuts. 

National C–FAR appreciates the opportunity to share its views and stands ready 

to work with the Chair and members of this Committee in support of these important funding objectives. 

PREPARED STATEMENT OF THE NATIONAL CORN GROWERS ASSOCIATION

The National Corn Growers Association (NCGA) appreciates the opportunity to 

share with you our agriculture appropriations priorities for fiscal year 2008. NCGA 

represents more than 32,000 members in 48 States, 47 affiliated State organizations 

and more than 300,000 corn farmers who contribute to State checkoff programs for 

the purpose of creating new opportunities and markets for corn growers. 

America’s corn producers continue to make a significant and important contribution to our nation’s economy. Over the last 5 years, the Nation’s corn crop has averaged 10.3 billion bushels resulting in an annual average farm gate value of almost 

$22 billion. The relatively stable production over the past 10 years, made possible 

by innovation in production practices and technological advances, has helped to ensure ample supplies of corn for livestock, an expanding ethanol industry, new 

biobased products and a host of other uses in the corn industry. 

Aflatoxin Research 

Aflatoxin is a significant problem for corn growers. While the disease is most common in the South, northern corn growers also experience aflatoxin, especially in 

times of drought. Aflatoxin costs corn growers millions of dollars in lost sales every 

year. 

Currently, the Agriculture Research Service (ARS) receives about $7 million per 

year for its entire aflatoxin research program. Of that, ARS awards about $750,000 

in competitive grants each year for pre-harvest aflatoxin research on corn, cotton, 

peanuts and tree nuts. These figures have been relatively flat for 10 years. NCGA 

requests an additional $500,000 for ARS’s aflatoxin cooperative agreement program, 

totaling $1.25 million. We believe the funds should be used to address cross-cutting 

issues of concern to all affected crops and the development of nondestructive testing 

protocols and technologies. 

Genomic Research 

The entire corn industry, including the academic research community, grain handlers, growers, industry and seed companies strongly believe that research on plant 
771 

and plant genomes has substantial long-term benefits. NCGA supports the plant genome research conducted by ARS through its genetic resources, genome sequencing 

and genome bioinformatics programs. Specifically, this research includes plant and 

fungal genomics exploration to determine what drives aflatoxin production, what 

causes susceptibility, and helps us understand plant and fungal nutrient and environmental needs. 

NCGA also supports the Cooperative State Research, Education and Extension 

Service’s National Research Initiative. Our research policy supports competitive 

grants where appropriate. 

APHIS Biotechnology Regulatory Service 

NCGA supports the President’s budget request of $14.141 million for the Animal 

and Plant Health Inspection Service’s Biotechnology Regulatory Service as well as 

the separate funding stream requested in the budget from the Office of the Secretary for the same. These resources are necessary to ensure the agency properly 

manages its functions associated with this expanding technology to maintain consumer and customer confidence in our strong science-based regulatory structure. 

FAS SPS Issues Resolution 

NCGA supports the President’s budget request of $27.153 million that increases funding by $6,196,000 within the Foreign Agricultural Service (FAS) for Sanitary 

and Phytosanitary (SPS) resolution. Unnecessarily restrictive regulations to address 

plant health risks are major impediments to U.S. market expansion. As trade barriers have been reduced, there has been a dramatic increase in non-tariff trade barriers to trade. 

FAS Market Access 

NCGA supports the President’s budget request of $200 million for the Market Access Program (MAP) within the Foreign Agricultural Service. This program has 

been successful in maintaining and expanding U.S. agricultural exports and 

strengthening farm income. The 2002 farm bill authorizes up to $200 million in 

mandatory spending for MAP; NCGA urges that the program be funded at the fully 

authorized level. 

National Corn to Ethanol Research Center 

In 2006, fuel ethanol production from corn generated 4.8 billion gallons of ethanol, 

displacing 3 percent of petroleum imports. Economic forecasting estimates that the 

United States is capable of producing in excess of 14 billion gallons of ethanol by 

2015. Such production is critical to our national economy, energy security and the 

environment. The National Corn-to-Ethanol Research Center (NCERC) at Southern 

Illinois University—Edwardsville is in a perfect position to: continue generation of 

baseline data, serve as training center for Workforce Development and expand as 

a Lignocellulosic Center of Excellence. To fulfill these objectives, NCGA is seeking 

additional funding on behalf of NCERC. 

Updated baseline data is continuously required to be reflective of industry 

changes and their impact on product yields and efficiencies. The goal of this objective is to continue generating baseline data under typical industry operating conditions reflective of changing industry practices and changes in inputs (e.g. 

fractionization, corn hybrids, enzymes, yeast practices). The baseline data generated 

by the NCERC is of significant interest to academic, government, industry and trade 

association ethanol researchers as well as ethanol plant operators. The baseline 

data generated by NCERC is providing a critical benchmark for all industry and institutional comparison testing. We encourage the committee to provide $400,000 to 

NCERC for this purpose. 

A key component to the success of the ethanol industry over the next decade is 

to ensure the industry has a ready and available workforce. NCERC is well-positioned to train an immediately productive workforce as it plays a unique role in 

serving both the educational mission of the university as well as meeting the growing needs of the biofuels industry. NCERC provides a year-long, hands-on workforce 

training program to student interns while conducting commercial testing trials. 

Since opening in late 2003, nearly 35 interns have helped with the successful operation of the plant and labs. NCGA requests an additional $1,000,000 to expand the 

current internship program to meet the growing needs of the industry. Through this 

endeavor, NCERC will develop and implement a National Biofuels Workforce Training Center. 

For cellulose to be a viable feedstock, the process of converting cellulose to ethanol 

must be optimized. The three ‘‘process points’’ of optimization in the cellulose to ethanol process are: pre-treatment method, enzyme functionality and fermentation organisms (yeast). The NCERC is a research leader in the conversion of corn to eth-
772 

anol and its co-product. Therefore, the NCERC is able to more cost-effectively stay 

on the cutting edge of technology as we enter a new era of converting cellulose to 

ethanol. 

The NCERC is well-positioned to work directly with USDA/ARS, the Department 

of Energy, and Academic and Industry researchers who are conducting scientific discovery research on the conversion of cellulose to ethanol. This work will spur unlimited investment by private industry as they will make that crucially important decision to enter the cellulose to ethanol market. We encourage the committee to consider NCERC as Lignocellulosic Center of Excellence. 

Ethanol Coproduct Utilization 

One of the major benefits of using corn as a feedstock for ethanol production is 

the ability to retain the protein, fat, fiber, vitamins and minerals for use as an animal feed. The co-product of ethanol production, distillers dried grain with solubles 

(DDGS), results from the concentration and drying of the components remaining 

after the starch portion of corn is converted to ethanol. Strong global demand for 

DDGS will be critical in maximizing the potential and profitability of fuel ethanol 

production from corn while ensuring livestock feed needs are met. 

While nearly 12 million tons of DDGS was fed domestically or exported in 2006, 

use of this alternative feed ingredient may be limited in the future because of real 

and perceived issues relating to DDGS consistency, quality, flowability and feed efficiency. NCGA encourages the committee to dedicate the resources necessary to 

greatly expand ARS’s efforts in this area, particularly as they relate to DDGS 

flowability, contaminant mitigation, nutritional value, and nutrient and mineral 

management issues. 

Value-Added Grants 

Grants from USDA’s Value-Added Product Market Development Grant program 

have been used by corn growers to leverage significant investments in rural communities. NCGA supports this grant program as authorized by the 2002 farm bill at 

$40 million per year. Potential technologies include processing identity-preserved 

corn varieties and adding value to the non-fermentable components of the corn feedstock. 

Thank you for the support and assistance you have provided to corn growers over 

the years. Please feel free to contact Lisa Kelley at 202–628–7001 if you need any 

additional information. 

PREPARED STATEMENT OF THE NATIONAL COMMODITY SUPPLEMENTAL FOOD

PROGRAM ASSOCIATION

The Honorable Herb Kohl, Mr. Chairman and Subcommittee members, I am 

Frank Kubik, President of the National Commodity Supplemental Food Program Association (NCSFPA). Thank you for this opportunity to present information regarding the Commodity Supplemental Food Program (CSFP). 

CSFP was our Nation’s first food assistance effort with monthly food packages designed to provide protein, calcium, iron, and vitamins A and C. It began in 1969 

for low-income mothers and children, preceding the Special Supplemental Nutrition 

Program for Women, Infants, and Children known as WIC. Pilot programs in 1983 

added low-income seniors to the list of eligible participants and they now comprise 

91 percent all participants. 

CSFP is a unique Federal/State and public/private effort. The USDA purchases 

specific nutrient-rich foods at wholesale prices for distribution. State agencies such 

as the departments of health, agriculture or education provide administration and 

oversight. These agency’s contracts with community and faith based organizations 

to warehouse and distribute food, certify eligibility and educate participants. The 

local organizations build broad collaboration among non-profits, health units, and 

area agencies on aging so that seniors and others can quickly qualify to and receive 

their monthly supplemental food package along with nutrition education to improve 

their health and quality of life. This unique public/private partnership reaches even 

homebound seniors in both rural and urban settings with vital nutrition. 

The foods provided through CSFP include canned fruits and vegetables, juices, 

meats, fish, peanut butter, cereals and grain products, cheese, and other dairy products increase healthy food consumption among these low-income populations. 

The CSFP is also an important ‘‘market’’ for commodities supported under various 

farm programs, as well as an increasingly important instrument in meeting the nutritional and dietary needs of special low-income populations. 

In fiscal year 2006, the CSFP provided services through 150 non-profit community 

and faith-based organizations at over 1,800 sites located in 32 States, the District 
773 

of Columbia, and two Indian reservations (Red Lake, Minnesota and Oglala Sioux, 

South Dakota). On behalf of those organizations NCSFPA would like to express our 

concern and disappointment regarding the reduction of available CSFP resources for 

fiscal year 2008. 

—The prospect of seniors not receiving needed CSFP food in a year when USDA has forecast in excess of $35.4 million in carryover inventory at the end of the 

fiscal year 2006 is disturbing. Clearly these inventories could and should be 

used to serve the areas that were affected by the hurricanes of 2005 and who 

were given 6 month CSFP supplemental caseload that has since been exhausted. 

—At a time when many Americans must choose between food or medicine, utilities, and other basic expenses, the Federal Government should not be reducing 

benefits for our most vulnerable citizens. 

CSFP’s 38 years of service stands as testimony to the power of partnerships 

among community and faith-based organizations, farmers, private industry and government agencies. The CSFP offers a unique combination of advantages unparalleled by any other food assistance program: 

—The CSFP specifically targets our Nation’s most nutritionally vulnerable populations: young children and low-income seniors. 

—The CSFP provides a monthly selection of food packages tailored to the nutritional needs of the population served. Eligible participants are guaranteed [by 

law] a certain level of nutritional assistance every month in addition to nutrition education regarding how to prepare and incorporate these foods into their 

diets as prescribed by their health care provider. 

—The CSFP purchases foods at wholesale prices, which directly supports the farming community. The average food package for fiscal year 2007 is $15.85, 

and the retail value is approximately $50.00. 

—The CSFP involves the entire community in confronting the problem of hunger. 

There are thousands of volunteers as well as many private companies who donate money, equipment, and most importantly time and effort to deliver food 

to needy and homebound seniors. These volunteers not only bring food but companionship and other assistance to seniors who might have no other source of 

support. (See Attachment 1) 

The White House proposed budget for fiscal year 2008 would eliminate CSFP completely, and would eliminate all of this effort and support of those 38 years. This 

proposal has shocked the entire CSFP community as well as legislators, anti-hunger 

and senior service organizations and the concerned citizens as they have become 

aware of it. America’s Second Harvest, AARP, and FRAC have all voiced their opposition to the elimination of CSFP. It is unconscionable to eliminate benefits for some 

of our most vulnerable citizens and to eliminate hope of those waiting for participation in the program. It is the cruelest cut for the greatest generation. 

In a recent CSFP survey, more than half of seniors living alone reported an income of less than $750 per month. Of those respondents from two-person households, more than half reported an income of less than $1,000 per month. Fewer than 

25 percent reported being enrolled in the Food Stamp Program. Over 50 percent 

said they ran out of food during the month. Also, close to 70 percent senior respondents say they use money for medical bills not food. 

The Senate Agriculture Appropriations Subcommittee has consistently supported 

CSFP, acknowledging it as a cost-effective way of providing nutritious supplemental 

foods. Last year this subcommittee and all of Congress provided funding for CSFP 

in direct opposition to its proposed elimination. This year, your support is again 

needed to provide adequate resources for the 485,416 mothers, children and seniors 

currently receiving benefits, 20,500 low-income participants currently waiting in five 

new States and 100,827 seniors waiting in current States for this vital nutrition program. 

There is no discernible plan to address the long-term needs of those affected by 

the elimination of CSFP. The proposed transition plan provides that seniors being 

removed from CSFP will be provided a Food Stamp Program (FSP) benefit of $20 

per month for up to six months, or until the participant actually enrolls in the FSP, 

whichever comes first. Simply transferring seniors to the FSP is an inadequate solution. It is essential for seniors to have access to services which they feel are offered 

with dignity and respect. Many will outright reject the idea of applying for FSP benefits. According to the ERS Evaluation of the USDA Elderly Nutrition Demonstrations: Volume I: 

The Commodity alternative benefit demonstration in North Carolina was popular 

both among new applicants and among existing FSP participants. Clients eligible 

for low FSP benefits were more likely to get the commodity packages, which had 

a retail value substantially greater than their FSP benefits’’. ‘‘In particular, seniors 
774 

described the anxiety of using FSP benefits in stores, where they felt shoppers and 

store clerks looked down on them’’. ‘‘The demonstrations attracted a particularly 

large share of clients eligible for the $10 benefit because the retail value of the commodity packages was worth $60–$70. 

Depending on their non-cash assets, seniors may not qualify for a FSP benefit 

level equivalent to the CSFP food package. Seniors receiving the minimum benefit 

would not be eligible for the $20/month transitional benefit. The 25 percent of current CSFP participants who already enrolled in the FSP will lose the benefits of 

CSFP and those benefits will not be replaced at a time when they are struggling 

to make ends meet. CSFP and FSP are supplemental programs. They work together 

to make up the shortfall that many of our seniors are facing each month. Both programs need to continue to be available as part of the ‘‘safety net’’ for our low-income 

participants. USDA reports that the average benefit paid to senior citizens is about $67 per 

month, but in reality, many senior citizens receive only the minimum monthly benefit of $10, which has not been updated since 1975. USDA figures also report households rather than individual participants and include households with disabled family members. 

The proposed transition plan for women, infants and children enrolled in the 

CSFP is to transfer them to WIC. However, due to increasing coordination between 

WIC and CSFP at the State and community levels, the number of WIC-eligible 

mothers and children enrolled in the CSFP is steadily declining. In some States, 

this figure is less than 2 percent of all enrolled women and children, eradicating 

supplemental food and nutrition benefits for that population as well. As referenced earlier, CSFP provides a food package that costs USDA about $15 per month. It has a retail value of approximately $50. How does someone use $20 

to purchase $50 worth of nutritious foods? What happens at the end of 6 months? 

The National Commodity Supplemental Food Program Association requested the 

Senate Agriculture Appropriations Subcommittee take the appropriate actions to 

funding CSFP for fiscal year 2008 at $157.4 million as illustrated below: 

To continue serving the 485,416 needy seniors (91 percent of participants), 

women, infants and children (9 percent of participants) currently enrolled in 

CSFP—$123 million. 

To serve the 22,577 individuals who received a food package through the supple- mental caseload provided to hurricane ravaged Gulf States.—$4.3 million. To meet USDA’s commodity procurement expenses—$0.7 million. 

Appropriation required to serve the 507,993 people who have relied upon CSFP for supplemental nutrition—$128 million. 

To begin meeting the needs of 20,500 eligible seniors in the 5 States with USDA 

approved plans: Arkansas (5,000), Delaware (2,500), Oklahoma (5,000), New Jersey 

(5,000) and Utah (3,000)—$3.9 million. 

To serve an additional 100,827 individuals among of our Nation’s most vulnerable 

individuals in the 32 States with existing programs and documented additional 

needs—$25.5 million. 

Appropriation needed to maximize this program’s effectiveness in serving 629,518 

seniors and women and their infants and young children challenged by hunger— 

$157.4 million. 

With the aging of America, CSFP must be an integral part of USDA Senior Nutrition Policy as well as comprehensive plans to support the productivity, health, independence, and quality of life for America’s seniors. 

Measures to show the positive outcomes of nutrition assistance to seniors must 

be strengthened. A 1997 report by the National Policy and Resource Center on Nutrition and Aging at Florida International University, Miami—Elder Insecurities: 

Poverty, Hunger, and Malnutrition indicated that malnourished elderly patients experience 2 to 20 times more medical complications, have up to 100 percent longer 

hospital stays, and incurs hospital costs $2,000 to $10,000 higher per stay. Proper 

nutrition promotes health, treats chronic disease, decreases hospital length of stay 

and saves health care dollars. 

Rather than eliminating the program, the NCSFPA recommends the following initiatives to strengthen CSFP: 

—Develop a formal evaluation process to demonstrate individual and program 

outcomes of CSFP with Federal, State, and local CSFP managers included in 

the study design; 

—Restore financial guidelines for seniors to the original level of 185 percent of 

poverty; 

—Set ‘‘greatest need within a project area’’ as the priority for service or let each 

State set its priority for service under a plan approved by the Secretary of Agriculture; 
775 

—Support and expand the program in those States that have demonstrated an interest in the CSFP, including the 5 States that already have USDA-approved 

plans to operate CSFP (Arkansas, Delaware, New Jersey, Oklahoma and Utah) 

or that have demonstrated a willingness to continue and expand current CSFP 

services. 

This program continues with committed grassroots operators and dedicated volunteers. The mission is to provide quality nutrition assistance economically, efficiently, 

and responsibly always keeping the needs and dignity of our participants first. We 

commend the Food and Nutrition Service of the Department of Agriculture and particularly the Food Distribution Division for their continued innovations to strengthen the quality of the food package and streamline administration. We also remain 

committed to providing quality services in collaboration with the community organizations and volunteers that contribute nearly 50 percent of the resources used in 

providing these services. 
776 

ATTACHMENT 1.—NATIONAL CSFP ASSOCIATION ADMINISTRATIVE EXPENSE VALUE SURVEY FISCAL YEAR 2006 

Programs USDA Reim- bursed Cash Not Reimbursed by USDA Cash CSFP Expendi- tures Cash Goods & Services donated to agen- cy Value Volunteer Labor Hours Value Annual Total Pro- gram Value Percent Paid by USDA Extra Goods do- nated to CSFP participants 

New Hampshire ....................................................................................... $416,648 $13,227 $429,875 $6,650 $108,235 $544,760 76 $2,625 New York ................................................................................................. 1,804,443 45,000 1,849,443 1,000 296,307 2,146,750 84 12,755 Vermont FB .............................................................................................. 246,524 300,000 546,524 ........................ 90,200 636,724 39 2,000 Washington DC ........................................................................................ 439,098 1,600,000 2,039,098 800,000 172,318 3,011,416 15 ........................Pennsylvania ........................................................................................... 835,702 53,197 888,899 22,885 186,985 1,098,769 76 92,638 Kentucky .................................................................................................. 898,857 162,681 1,061,538 22,180 704,282 1,788,000 50 714,055.00 Mississippi .............................................................................................. 400,448 ........................ 400,448 160,370 561,766 1,122,584 36 ........................North Carolina ......................................................................................... 74,583 30,000 104,583 ........................ ........................ 104,583 71 5,000 South Carolina ........................................................................................ 212,744 ........................ 212,744 ........................ 58,883 271,627 78 2,500 Tennessee 1 ............................................................................................. 804,260 ........................ 804,260 ........................ ........................ 804,260 100 ........................Illinois ...................................................................................................... 885,767 3,000 888,767 ........................ 477,447 1,366,214 65 ........................Indiana .................................................................................................... 246,603 28,072 274,675 22,000 396,880 693,555 36 443 Michigan .................................................................................................. 4,490,742 601,805 5,092,547 356,773 2,161,385 7,610,705 59 769,301 Minnesota ................................................................................................ 802,557 103,225 905,782 19,000 173,068 1,097,850 73 199,000 Red Lake, MN .......................................................................................... 5,841 ........................ 5,841 ........................ ........................ 5,841 100 ........................Ohio ......................................................................................................... 709,662 94,228 803,890 65,000 368,251 1,237,141 57 302,000 Wisconsin ................................................................................................ 276,228 56,458 332,686 3,150 300,691 636,527 43 41,845 Louisiana ................................................................................................. 4,505,386 250,000 4,755,386 452,000 825,330 6,032,716 75 ........................New Mexico .............................................................................................. 1,009,150 272,139 1,281,289 97,987 350,283 1,729,559 58 446,378 Texas ....................................................................................................... 708,521 70,000 778,521 15,000 405,900 1,199,421 59 12,000 Colorado .................................................................................................. 1,193,799 204,168 1,397,967 30,474 612,151 2,040,592 59 878,389 Iowa ......................................................................................................... 222,652 520,767 743,419 ........................ 29,712 773,131 29 ........................Kansas ..................................................................................................... 333,423 45,715 379,138 46,200 209,986 635,323 52 51,400 Missouri ................................................................................................... 532,997 29,000 561,997 2,400 398,455 962,852 55 1,010,950 Montana .................................................................................................. 385,402 35,525 420,927 107,333 2,163,357 2,691,617 14 78,825 Nebraska ................................................................................................. 756,827 87,486 844,313 21,580 308,475 1,174,369 64 89,709 North Dakota ........................................................................................... 160,216 7,800 168,016 ........................ 235,729 403,745 40 ........................South Dakota ........................................................................................... 160,962 33,520 194,482 ........................ 32,842 227,324 71 ........................Ogala Sioux, SD ...................................................................................... 37,341 ........................ 37,341 ........................ ........................ 37,341 100 ........................Alaska ...................................................................................................... 130,334 48,038 178,372 10,000 45,100 233,472 56 ........................Arizona ..................................................................................................... 883,204 450,000 1,333,204 4,516 1,549,401 2,887,121 31 580,460 California ................................................................................................. 3,078,203 1,265,849 4,344,052 68,600 2,492,966 6,905,618 45 772,308 Nevada .................................................................................................... 352,044 97,629 449,673 ........................ 84,788 534,461 66 113,000 Oregon ..................................................................................................... 78,299 48,000 126,299 ........................ 75,768 202,067 39 ........................
777 

Washington .............................................................................................. 132,094 25,000 157,094 250 39,544 196,888 67 ........................

Grand Total ................................................................................ 28,211,561 6,581,529 34,793,090 2,335,348 15,916,481 53,044,919 53 6,177,579 

1 No information provided. 
778 

1The National Environmental Services Center is located at West Virginia University. This 

statement has been prepared by Richard Bajura, Executive Director, with assistance from Pamela Schade and Trina Wafle. For more information, see our Web site at http://www.nesc.wvu.edu 

FISCAL YEAR 2008 BUDGET REQUEST

On behalf of low-income seniors and women and their infants and young children 

in need of the prescribed packages of nutritious food made available through the 

Commodity Supplemental Food Program (CSFP), we request not only the rejection 

of the proposal to eliminate CSFP, but also consideration of increases in program 

resources. At a modest cost of 15.85 per monthly food package, CSFP leverages the efforts 

and energy of thousands of volunteers at churches and charities across America to 

deliver essential nutrition with a retail value in excess of 50.00 per month to vulnerable members of ‘‘The Greatest Generation’’ and to help at-risk members of the next 

generation get a healthy start. The appropriations required and the benefits anticipated are as follows: 

To continue serving the 485,416 needy seniors (91 percent of participants), 

women, infants and children (9 percent of participants) currently enrolled in 

CSFP—$123 million. 

To serve the 22,577 individuals who received a food package through the supple- mental caseload provided to hurricane ravaged Gulf States—$4.3 million. To meet USDA’s commodity procurement expenses—$.7 million. 

Appropriation required to serve the 507,993 people who have relied upon CSFP for supplemental nutrition—$128 million. 

To begin meeting the needs of 20,500 eligible seniors in the 5 States with USDA 

approved plans Arkansas (5,000), Delaware (2,500), Oklahoma (5,000), New Jersey 

(5,000) and Utah (3,000)—$3.9 million. 

To serve an additional 100,827 individuals among of our Nation’s most vulnerable 

individuals in the 32 States with existing programs and documented additional 

needs—$25.5 million. 

Appropriation needed to maximize this program’s effectiveness in serving 629,518 

seniors and women and their infants and young children challenged by hunger— 

$157.4 million. 

PREPARED STATEMENT OF THE NATIONAL ENVIRONMENTAL SERVICES CENTER (NESC) 

Chairman Kohl, Senator Bennett, and Members of the Subcommittee: Thank you 

for the opportunity to offer testimony to the Subcommittee on Agriculture, Rural Development, FDA and Related Agencies.1 We request funding to support the programs of the National Drinking Water Clearinghouse in providing information and 

technical assistance to small and rural and underserved communities under the 

Rural Utilities Service programs of the USDA. 

Need for Federal Programs 

Clean, safe drinking water and wastewater treatment are critical to public and 

environmental health. For most of us, it’s easy to take water for granted. However, 

according to U.S. Census Bureau data, half of American homes in 1940 lacked complete plumbing facilities (defined as hot and cold piped water, a bathtub or shower, 

and a flush toilet). By 2002, EPA found that the number of homes having complete 

plumbing facilities increased to 91 percent. Much of this improvement can be attributed to Federal infrastructure investment. The U.S. Department of Agriculture’s 

Rural Utilities Service (RUS) has provided more than $20 billion for water and 

wastewater projects since 1947. In spite of these improvements, however, 670,000 

households (with nearly 2 million people) lack access to water, sanitation, or both. 

Safe, affordable water infrastructure is an investment in the economic viability and 

public health of rural America. 

Water and Wastewater Challenges 

Over 50,000 water treatment systems serve the U.S. population, with 86 percent 

of these systems being classified as ‘‘small’’ systems (serving fewer than 3,300 people) and ‘‘very small’’ systems (serving fewer than 500 customers). Because smaller 

systems have lower revenues and fewer resources, they are more likely to have difficulty in meeting regulatory requirements. When the Safe Drinking Water Act was 

passed in 1974, 18 contaminants were regulated. By 2004, that number had grown 

to 86. Another eight will be added by 2008. 

While significant progress has been made, a number of challenges confront communities as they try to safeguard public health. In many communities, water dis-
779 

tribution systems and wastewater collection systems are 40 to 50 years old, with 

many dating back more than a century. According to the American Society of Civil 

Engineers (ASCE), U.S. drinking water system operators are responsible for maintaining an estimated 800,000 miles of water delivery pipelines. In the 2002 report 

titled Clean Water and Drinking Water Infrastructure Gap Analysis, EPA estimated 

that we need to invest $265 billion for drinking water systems infrastructure 

through 2022. Wastewater infrastructure will need an estimated $388 billion during 

the same time period. ASCE puts the water infrastructure funding gap at $534 billion over the same time period, saying that the EPA estimate doesn’t adequately 

address population growth and new construction. In the 2003 update to ASCE’s Report Card for America’s Infrastructure, both water and wastewater were given a 

grade of ‘‘D.’’ The report suggests that, without new investment, progress made over 

the last 30 years is threatened. 

Federal Assistance Programs 

As a partial solution to addressing these challenges, the Water and Wastewater 

Technical Assistance and Training [TAT] grants under USDA’s Rural Community 

Advancement Program make it possible for small and rural communities to maximize their investments in water infrastructure through assistance with technology 

selection, operation and maintenance, capacity development, and asset management. 

The National Drinking Water Clearinghouse has been a strong partner with USDA 

in providing services to these communities. We are requesting appropriations in fiscal year 2008 to continue our work with USDA by providing the kinds of services 

described below. 

About the National Drinking Water Clearinghouse (NDWC) 

For 17 years, the National Drinking Water Clearinghouse at West Virginia University has helped small and rural communities with their water infrastructure 

management. In 2001, the NDWC also undertook programs related to utility security issues. 

The NDWC provides a range of assistance for small communities. Telephone callers can obtain toll-free technical assistance from our staff of engineers and scientists. Our quarterly publication On Tap, a magazine about drinking water treatment, financing, and management options, helps communities and small water systems operate, manage, and maintain their facilities, while keeping them financially 

viable. A comprehensive Web site and databases with thousands of entries provide 

round-the-clock access to contemporary information on small water system. Training 

sessions customized for small and rural areas, teleconferences, Web casts, and more 

than 400 free and low-cost educational products give people the instruction and tools 

they need to address their most pressing water issues. These services are well received by small community officials and service providers. 

In addition to our knowledge base, technical assistance through telephone consultation, and publications which we provide to the public, the NDWC wishes to develop new initiatives targeted to reach underserved communities found in places 

such as rural Appalachia, the Mississippi Delta, the Colonias in the U.S.-Mexico 

border region, and Native American Tribes. 

Request 

In fiscal year 2008, we want to strengthen our core programs in providing information and technical assistance and also develop special initiatives to address problems unique to certain underserved communities as described above. We seek an appropriation of $1.7 million to support our work in these two important program 

areas. Thank you for considering our request. 

PREPARED STATEMENT OF THE NATIONAL FISH AND WILDLIFE FOUNDATION

Mr. Chairman and Members of the Subcommittee, I appreciate the opportunity 

to submit testimony regarding the fiscal year 2008 funding request for the National 

Fish and Wildlife Foundation (Foundation). Since 2000, the Foundation has received 

$3 million annually from the U.S. Department of Agriculture’s Natural Resources 

Conservation Service (NRCS). We have worked with NRCS to focus on agency wildlife priorities in the past and look forward to continuing to do so. With a Farm Bill 

pending, we have a number of outside organizations willing to match federally provided dollars to assist in agricultural wildlife conservation projects. 

—The Foundation respectfully requests that this Subcommittee fund the Foundation at $4 million through the NRCS Appropriation. 

These dollars will be focused on mutually agreed upon projects across the country. 

Furthermore, the appropriated $4 million will be turned into a minimum of $8 mil-
780 

lion, according to the Foundation’s Congressional Charter which requires a minimum of a one-to-one match. We have been operating on a three-to-one match historically, which means that the $4 million has the potential to turn into $16 million 

or more for on-the-ground conservation. One other note of special interest is that 

according to the Foundation’s Charter, all directly appropriated funds have to be obligated to grants as they are not available to the Foundation for any direct or indirect expenses. Since 2000 when the grants partnership began, the Foundation has received $21 million in NRCS Federal funds ($3 million per fiscal year), which it has dedicated 

to a matching grant program focused on private land conservation. The Foundation 

has supported over 470 projects in 49 States, the Caribbean, and the Pacific Islands, 

by leveraging the $21 million in NRCS funds into more than $85 million in on-theground conservation. These projects have led to the direct restoration of more than 

1,232,000 acres of farmland and rangeland and 1,041 miles of streams and rivers. 

In fiscal year 2006, the Foundation received $3 million in NRCS Federal funds, 

which it leveraged into more than $14 million in on-the-ground conservation. 

Working Landscapes.—Through our partnership, the Foundation works with 

NRCS to identify and fund projects that have strong support in affected agricultural 

and rural communities. We place our highest priority on projects integrating conservation practices on ongoing agricultural, ranching, and forestry operations, with 

the goal of improving the ecological health of working lands. We fund partners and 

provide expertise by engaging watershed experts, ranchers, foresters, farmers, local 

governments, and non-profits to undertake on-the-ground private land activities 

with willing landowners. Through these efforts, the Foundation has helped to reduce 

agricultural runoff, remove invasive species, and restore native ecosystems. 

Conserving Fish, Wildlife, and Plants.—With our NRCS dollars, the Foundation 

funds projects that directly benefit diverse fish and wildlife species, including salmon in the West, migratory birds in the Midwest, and grassland birds in the South. 

Habitat for native fish has been restored on private lands throughout the United 

States, by way of vegetative planting, streambank stabilization, livestock fencing, 

and nutrient reduction efforts. In addition to improving water quality, efforts have 

been undertaken by our grantees to reduce water loss caused by invasive species 

or from outdated irrigation systems. By reducing the water taken from rivers, there 

is less chance that drought will negatively impact aquatic life. —Pulling Together Initiative (PTI).—In fiscal year 2006, NRCS joined the Foundation’s Pulling Together Initiative, a grant program that supports the creation 

of local cooperative Weed Management Area partnerships. These partnerships 

bring together local landowners, citizens groups, and weed experts to develop 

and implement strategies for managing weed infestations on public lands, natural areas, and private working lands. Through this collaborative program, 

NRCS staff is able to join invasive species experts from the U.S. Fish and Wildlife Service (FWS), USDA-Forest Service (FS), Bureau of Land Management 

(BLM), Animal and Plant Health Inspection Service, and the Department of Defense to review and jointly select the most innovative weed management 

projects. 

—Due to the successful experience with the PTI program, NRCS has expressed 

an interest in participating in the Foundation’s Bring Back the Natives (BBN) 

grant program in fiscal year 2007 (depending on appropriations). The BBN program is a public-private partnership, including FS, BLM, FWS, Trout Unlimited 

and the Foundation; it is focused on restoring native populations of sensitive 

or listed aquatic species. Priority is provided to aquatic joint ventures and to 

those projects that directly implement the recommendations of the National 

Fish Habitat Action Plan. 

The National Fish and Wildlife Foundation continues to be one of, if not the most, 

cost-effective conservation program funded in part by the Federal Government. Congress established the Foundation 23 years ago, and since that time the Foundation’s 

vision for more healthy and abundant populations of fish, wildlife, and plants has 

flourished through the creation of numerous valuable partnerships. The breadth of 

our partnerships is highlighted through our active agreements with 14 Federal 

agencies, as well as various corporations, foundations and individual grantees. 

Through these unique arrangements, we are able to leverage Federal funds, bring 

agencies and industry together, as well as produce tangible, measurable results. Our 

history of collaboration has given way to programs and initiatives such as the North 

American Waterfowl Management Plan, the Neotropical Migratory Bird Conservation Program, the Chesapeake Bay Small Watershed Grants Program, and the Pulling Together Initiative. With the support of the Committee in fiscal year 2008, we 

can continue to uphold our mission of enriching fish, wildlife, and the habitat on 

which they depend. 
781 

Federal dollars appropriated by this Committee allow the Foundation to be highly 

successful in assisting the NRCS in accomplishing its mission to help people conserve, maintain, and improve our natural resources and environment. Whether it 

involves farm, range or grassland conservation, species management or conservation 

education, the Foundation strategically invests the Federal funds entrusted to us in 

sound projects. This request would allow the Foundation to expand its highly successful grant program to better assist NRCS in maximizing private land conservation. 

The Foundation’s achievements are based on a competitive grant process where 

Federal funds are matched by the grantee with non-Federal funds and in-kind services. Grantees include Resource Conservation and Development Areas, conservation 

districts, universities, and non-profit organizations who partner with farmers and 

ranchers to support conservation efforts on private land. The Foundation also works 

to further maximize Federal funds by providing private funds through the generosity of our growing number of corporate and foundation partners. These funds 

are in addition to the non-Federal funds that are provided by the Foundation’s 

grantees. In the Foundation’s partnership with NRCS, Federal funds have been supplemented with funding from Shell Oil Company, FMC Corporation, Doris Duke 

Foundation, the Kellogg Foundation, Wal-Mart, Anheuser-Busch Companies, Inc., 

Southern Company, Summer T. McKnight Foundation, Charles Stewart Mott Foundation, William Penn Foundation, and the David and Lucile Packard Foundation. 

We also measure our success in part by preventing the listing of species under 

the Endangered Species Act, as well as by stabilizing and hopefully moving others 

off the list. Some species that have received support through our NRCS grant program include salmonids, golden-cheeked warblers, black-capped vireos, Southwestern willow flycatchers, whooping cranes, sage grouse, lesser prairie chickens, 

aplomado falcons, black-tailed prairie dogs, Louisiana black bears, bog turtles, tiger 

salamanders and Karner blue butterflies. We invest in common sense and innovative cooperative approaches to endangered species, building bridges between the 

government and the private sector. 

New Strategic Plan.—During 2006, the Foundation underwent a detailed self-evaluation, which resulted in the development of a new strategic plan for the organization. The strategic planning process revealed that the Foundation maximizes conservation benefits when it targets a series of grants towards a specific geographic 

region, habitat type, or conservation challenge. To ensure that future grants achieve 

a sustainable and measurable conservation impact, the Foundation is establishing 

targeted Keystone Initiatives around the core conservation investment areas in 

which the Foundation has historically specialized. The Keystone Initiatives represent the new core portfolio of the Foundation’s grant making with clearly defined 

long-term goals, well-articulated strategies, and defined budgets to reach desired 

outcomes. 

The four initial Keystone Initiatives, launched by the Foundation in 2007, include 

Birds; Wildlife and Landscape Scale Habitats; Freshwater Fish and Habitats; and 

Marine and Coastal Life and Habitats. Additional Keystone Initiatives being developed include Wildlife and Agriculture, Wildlife and Energy Development, Invasive 

Species, and Future Conservation Leaders. Each grant approved under a Keystone 

Initiative will be designed to provide a measurable outcome that brings us one step 

closer to the final long-term conservation goal of the Initiative. Where appropriate, 

the strategies and outcomes of the Foundation’s Special Grant Programs, such as 

the Great Lakes Restoration Fund, Bring Back the Natives, and the Coral Reef Conservation Fund, will be designed to directly contribute to the long-term Keystone 

Initiative goal. Through our targeted grants, the Foundation seeks to achieve measurable success in ‘‘moving the needle’’ on these critical conservation objectives over 

the next 5 to 10 year period. 

Accountability and Grantsmanship.—During the strategic planning process, Foundation staff spent time listening to feedback from our agency partners and grantees. 

Choke points in our grant making process were identified, and the Foundation is 

in the process of revising portions of our grant review and contracting process to 

ensure we maximize efficiency while maintaining strict financial and evaluationbased requirements. The Foundation has also launched a new website that is more 

user-friendly and content rich than the previous version. This new interactive tool 

will allow the Foundation to improve communication with our stakeholders and will 

help streamline our grant making process. 

To ensure that only those grants with the greatest likelihood of obtaining conservation outcomes directly related to a Keystone Initiative are funded, the Foundation has implemented a thorough review process. Applicants are required to submit 

a pre-proposal which allows staff to proactively work with applicants to refine and 

improve their application before submitting a full proposal. All full proposals are 
782 

then submitted to a peer review process which involves five external reviews representing State agencies, Federal agencies, affected industry, environmental nonprofits, and academics. Grants are also reviewed by the Foundation’s Keystone Initiative staff, as well as evaluation staff, before being recommended to the Board of 

Directors for approval. In addition, the Foundation provides a 30-day notification to 

the Members of Congress for the congressional district and State in which a grant 

will be funded, prior to making a funding decision, according to our Congressional 

Charter. 

Basic Facts About the Foundation.—The Foundation is governed by a 25-member 

Board of Directors, appointed by the Secretary of Interior and in consultation with 

the Secretary of Commerce. At the direction of Congress, the Board operates on a 

nonpartisan basis. Directors do not receive any financial compensation for service 

on the Board; in fact, most all of our directors make financial contributions to the 

Foundation. It is a diverse Board, and includes the Director of the U.S. Fish and 

Wildlife Service, the Administrator of the National Oceanic and Atmospheric Administration, as well as corporate and philanthropic leaders with a tenacious commitment to fish and wildlife conservation. 

None of our federally appropriated funds are used for lobbying, litigation, or the 

Foundation’s administrative expenses. By implementing strategic real-world solutions with the private sector, while avoiding regulatory or advocacy activities, we 

serve as a model for developing cooperative solutions to environmental issues. We 

are confident that the money you appropriate to the Foundation is making a positive difference. 

PREPARED STATEMENT OF THE NATIONAL POTATO COUNCIL

Legislative/Government Affairs 

My name is Ed Schneider. I am a potato farmer from Pasco, Washington and current Vice President, Legislative/Government Affairs for the National Potato Council 

(NPC). On behalf of the NPC, we thank you for your attention to the needs of our 

potato growers. 

The NPC is the only trade association representing commercial growers in 50 

States. Our growers produce both seed potatoes and potatoes for consumption in a 

variety of forms. Annual production is estimated at 437,888,000 cwt. with a farm 

value of $3.2 billion. Total value is substantially increased through processing. The 

potato crop clearly has a positive impact on the U.S. economy. 

The potato is the most popular of all vegetables grown and consumed in the 

United States and one of the most popular in the world. Annual per capita consumption was 136.5 pounds in 2003, up from 104 pounds in 1962 and is increasing 

due to the advent of new products and heightened public awareness of the potato’s 

excellent nutritional value. Potatoes are considered a nutritious consumer commodity and an integral, delicious component of the American diet. 

The NPC’s fiscal year 2008 appropriations priorities are as follows: 

Potato Research 

Cooperative State Research Education and Extension Service (CSREES) 

The NPC urges the Congress not to support the President’s fiscal year 2008 budget request to eliminate the CSREES Special Grant Programs. This program supports and fine tunes important university research work that helps our growers remain competitive in today’s domestic and world marketplace. 

The NPC supports an appropriation of $1,800,000 for the Special Potato Grant 

program for fiscal year 2008. The Congress appropriated $1,482,000 in fiscal year 

2006 and recommended the same amount in fiscal year 2007. This has been a highly 

successful program and the number of funding requests from various potato-producing regions is increasing. 

—The NPC also urges that the Congress include Committee report language as 

follows: ‘‘Potato research.—The Committee expects the Department to ensure 

that funds provided to CSREES for potato research are utilized for varietal development testing. Further, these funds are to be awarded after review by the 

Potato Industry Working Group.’’ 

Agricultural Research Service (ARS) 

The NPC urges that the Congress not support the Administration’s fiscal year 

2008 budget request to rescind Congressional increases for research projects. 

The Congress provided funds for a number of important ARS projects and, due 

to previous direction by the Congress, the ARS continues to work with the NPC on 

how overall research funds can best be utilized for grower priorities. 
783 

Foreign Market Development 

Market Access Program (MAP) 

The NPC also urges that the Congress maintain the spending level for the Market Access Program (MAP) at its authorized level of $200 million for fiscal year 2008 

as requested by the Administration. 

Foreign Agriculture Service (FAS) 

The NPC supports the President’s fiscal year 2008 budget request of $268 million 

for the USDA Foreign Agriculture Service (FAS). This level is necessary for the 

agency given the multitude of trade negotiations and discussions currently underway. The Agency has had to absorb pay cost increases as well as higher operating 

costs for its overseas offices such as increased payments to the Department of State 

for services provided at overseas posts. Recent declines in the value of the dollar, 

coupled with overseas inflation and rising wage rates, have led to sharply higher 

operating costs that must be accommodated if FAS is to maintain its overseas presence. 

Food Aid Programs 

McGovern-Dole 

The NPC supports the Administration’s fiscal year 2008 budget request of $100 

million for the McGovern-Dole International Food Aid Program. PVO’s have been including potato products in their applications for this program. 

Pest and Disease Management 

Animal and Plant Health Inspection Service (APHIS) 

Golden Nematode Quarantine.—The NPC supports an appropriation of $1,266,000 

for this quarantine which is what is believed to be necessary for USDA and the 

State of New York to assure official control of this pest. Failure to do so could adversely impact potato exports. 

Given the transfer of Agriculture Quarantine Inspection (AQI) personnel at U.S. 

ports to the Department of Homeland Security, it is important that certain USDA– 

APHIS programs be adequately funded to ensure progress on export petitions and 

protection of the U.S. potato growers from invasive and harmful pests and diseases. 

Even though DHS staffing has increased, agriculture priorities have not been adequately addressed. 

Pest Detection.—The NPC supports $45 million in fiscal year 2008, which is the 

Administration’s budget request. This increase is essential for the Plant Protection 

and Quarantine Service’s (PPQ) efforts against potato pests and diseases such as 

Ralstonia and the potato cyst nematode. 

Emerging Plant Pests.—$93 million was appropriated in fiscal year 2007. The President requests $124 million in fiscal year 2008 which the NPC supports. This 

budget request includes an increase of $4.5 million for potato cyst nematode regulatory, control and survey activity. 

The NPC supports having the Congress once again include language to prohibit 

the issuance of a final rule that shifts the costs of pest and disease eradication and 

control to the States and cooperators. 

Trade Issues Resolution Management.—$12,457,000 appropriated in fiscal year 

2007and the President requests $15 million in fiscal year 2008. The NPC supports 

this increase ONLY if it is specifically earmarked for plant protection and quarantine activities. These activities are of increased importance, yet none of these 

funds are used directly for plant protection activities. As new trade agreements are 

negotiated, the agency must have the necessary staff and technology to work on 

plant related import/export issues. The NPC also relies heavily on APHIS–PPQ resources to resolve phytosanitary trade barriers in a timely manner. 

Agricultural Statistics 

National Agricultural Statistics Service (NASS) 

The NPC supports sufficient funds and guiding language to assure that the potato 

objective yield and grade and size surveys are continued, as well as for vegetable 

pesticide use surveys, which provides valuable data to the EPA for use in registration and re registration decisions for key chemical tools. 

Rural Development Grants 

Since potato growers do not receive direct payments, the 2002 Farm Bill provided 

for, among other things, grants to allow our growers to expand their business opportunities. One program that has been used by our growers is the value-added grant 

program. The NPC would urge that the Farm Bill funding level for this program 
784 

be maintained. In addition, maintaining adequate farm labor is also important to 

our growers. The NPC urges that farm labor housing grants be maintained and not 

reduced. 

PREPARED STATEMENT OF THE NATIONAL RURAL TELECOM ASSOCIATION

SUMMARY OF TESTIMONY REQUESTS

Project Involved 

Telecommunications lending programs administered by the Rural Utilities Service 

of the U.S. Department of Agriculture 

Actions Proposed 

Supporting loan levels for fiscal year 2008 in the amounts requested in the Presi- dent’s budget for 5 percent direct ($145 million) and cost-of-money ($250 million) 

and the associated subsidy, as required, to fund those programs at the requested 

levels. 

Supporting Sec. 306 guaranteed loans in the amount ($295 million) requested in 

the budget. 

Opposing the budget request that would cut direct loans for broadband facilities 

and Internet service access by 40 percent from the fiscal year 2006 enacted level 

of $500 million to $300 million. 

Supporting renewal of the pilot broadband grant program at enhanced levels and 

an allocation of a portion of the authorized levels for broadband loans at reduced 

interest rates to accelerate deployment of this technology in rural areas. 

Seeking language strengthening and improving the operation of the broadband 

loan program in the Committee Report accompanying the bill. 

Supporting continued funding, as requested in the President’s budget, in the amount of $25 million in grant authority designated for distance learning and medical link purposes. 

Mr. Chairman, Members of the Committee, my name is John F. O’Neal. I am 

General Counsel of the National Rural Telecom Association. 

NRTA is comprised of commercial telephone companies that borrow their capital 

needs from the Rural Utilities Service of the U.S. Department of Agriculture (RUS) 

to furnish and improve telephone service in rural areas. Over 700 of the Nation’s 

local, rural telephone systems borrow from RUS. About three-fourths of these are 

commercial telephone companies. RUS borrowers serve almost 6 million subscribers 

in 46 States and employ over 22,000 people. In accepting loan funds, borrowers assume an obligation under the act to serve the widest practical number of rural users 

within their service area. 

Program Background 

Rural telephone systems have an ongoing need for long-term, fixed rate capital 

at affordable interest rates. Since 1949, that capital has been provided through telecommunications lending programs administered by the Rural Utilities Service and 

its predecessor, the Rural Electrification Agency (REA). 

RUS loans are made exclusively for capital improvements and loan funds are segregated from borrower operating revenues. Loans are not made to fund operating 

revenues or profits of the borrower system. There is a proscription in the Act 

against loans duplicating existing facilities that provide adequate service and State 

authority to regulate telephone service is expressly preserved under the Rural Electrification Act. 

Rural telephone systems operate at a severe geographical handicap when compared with other telephone companies. While almost 6 million rural telephone subscribers receive telephone service from RUS borrower systems, they account for only 

4 percent of total U.S. subscribers. On the other hand, borrower service territories 

total almost 40 percent of the land area—nearly 12 million squares miles. RUS borrowers average about six subscribers per mile of telephone line and have an average 

of more than 1,000 route miles of lines in their systems. 

Because of low-density and the inherent high cost of serving these areas, Congress 

made long-term, fixed rate loans available at reasonable rates of interest to assure 

that rural telephone subscribers, the ultimate beneficiaries of these programs, have 

comparable telephone service with their urban counterparts at affordable subscriber 

rates. This principle is especially valid today as this administration endeavors to deploy broadband technology and as customers and regulators constantly demand improved and enhanced services. At the same time, the underlying statutory authority 

governing the current program has undergone significant change. In 1993, telecommunications lending was refocused toward facilities modernization. Much of the 
785 

subsidy cost has been eliminated from the program. The subsidy that remains has 

been targeted to the highest cost, lowest density systems in accordance with this 

administration’s stated objectives. 

We are proud to state once again for the record that there has never been a loan 

default by a rural telephone system. All of these loans have been repaid in accordance with their terms: almost $13 billion in principal and interest at the end of the 

last fiscal year. 

Need for RUS Telecommunications Lending Continues 

The need for rural telecommunications lending is great today, possibly even greater than in the past. Technological advances make it imperative that rural telephone 

companies upgrade their systems to keep pace with improvements and provide the 

latest available technology to their subscribers. And 5 years ago, Congress established a national policy initiative mandating access to broadband for rural areas. 

But rapid technological changes and the inherently higher costs to serve rural areas 

have not abated, and targeted support remains essential. 

Competition among telephone systems and other technological platforms have increased pressures to shift more costs onto rural ratepayers. These led to increases 

in both interstate subscriber line charges and universal service surcharges on end 

users to recover the costs of interstate providers’ assessments to fund the Federal 

mechanisms. Pressures to recover more of the higher costs of rural service from 

rural customers to compete in urban markets continue to burden rural consumers. 

There is a growing funding crisis for the statutory safeguards adopted in 1996 to 

ensure that rates, services and network development in rural America will be reasonably comparable to urban telecommunications opportunities. 

Ongoing Congressional Mandates for Rural Telecommunications 

Considerable loan demand is being generated because of the mandates for enhanced rural telecommunications standards contained in the authorizing legislation. 

We are, therefore, recommending the following loan levels for fiscal year 2008 and 

the appropriation of the associated subsidy costs, as required, to support these levels: 

5 percent Direct Loans ........................................................................................................................................ $145,000,000 

Cost-of-Money Loans ............................................................................................................................................ 250,000,000 

Guaranteed Loans ................................................................................................................................................ 295,000,000 

Broadband Loans ................................................................................................................................................. 500,000,000 

Total ........................................................................................................................................................ 1,190,000,000 

These are the same levels for 5 percent direct, cost-of-money loans and guaranteed loans, as requested in the President’s budget for fiscal year 2008 and the enacted amount for broadband loans in the fiscal year 2006 appropriations act. The 

authorized levels of loans in each of these programs were substantially obligated in 

fiscal year 2006 and current estimates are that authorized program levels will be 

met in fiscal year 2007. 

We believe that the needs of this program balanced with the minimal cost to the 

taxpayer make the case for its continuation at the stated levels. 

The Broadband Loan Program 

The broadband loan program was funded in fiscal year 2006 at $500 million. Very 

little subsidy cost is associated with this program since most of the loans are made 

at the government’s cost-of-money. Despite that, the President’s budget recommends 

reducing the loan levels for fiscal year 2008 by 40 percent to $300 million. We are 

opposed to that reduced level and recommend to the committee that the fiscal year 

2008 appropriations bill continue to fund the program at enacted levels. The demand for this program is still quite strong and if the Congress’ stated objective of 

deploying this technology to all rural areas of this country is to be met, the $500 

million funding level should be maintained. 

Renewal of Pilot Broadband Grants and Allocating Funds for Reduced Interest Rate 

Loans 

Many of these un-served areas are in high cost, sparsely populated regions of the 

country making the feasibility of loans problematic. To facilitate the deployment of 

this technology to those areas, the Committee should consider reinstating the Pilot 

Broadband Grant program initiated by Congress in previous appropriations acts. We 

believe that supplementing loan funds with grant funds would make many of the 

projects feasible where they would not be otherwise. In fact, the government’s security interest in the loan would be enhanced. If the Committee concurs in reinstating 
786 

the pilot grant program as a national priority, we believe it should be at enhanced 

levels to achieve the Committee’s goals consistent with budgetary constraints. 

We also believe that if a portion of the loan funds provided by Congress for fiscal 

year 2008 were made available at reduced interest rates many additional areas 

could be served as well. Currently, all broadband loans are made at the government’s cost-of-money. However, both the 2002 Farm bill that authorized the 

broadband loan program as well as the President’s fiscal year 2006 Budget envisioned reduced rate loans to accelerate deployment of this technology. Reduced rate 

loans could be made concurrently with cost-of-money loans producing a blended interest rate to achieve the desired loan feasibility. The agency has successfully accomplished this in the past. 

Discretion could be left with the agency to allocate loan and grant funds according 

to program needs and the feasibility of specific applications. 

Improving Program Implementation Through Committee Report Language 

Distinct improvements can be made to the broadband loan program by providing 

the Rural Utilities Service (RUS) broader access to the legal expertise of the Department’s Office of General Counsel (OGC). Over the years, due to cost and other considerations, the agency’s access to counsel has been severely curtailed. This has resulted in an uneven application of the act’s requirements in the loan approval process permitting unbridled agency discretion in administering the program. For example, in administering the broadband loan program enacted as Title VI of the Rural 

Electrification Act of 1936, as an amendment thereto, the agency has largely ignored 

the fundamental requirements and prohibitions of Title II of the act that originally 

authorized the telephone loan program as if they simply do not apply to the 

broadband loan program. First and foremost of the prohibitions is the principle contained in Title II that loans should not be made in areas that would result in a duplication of facilities. 

Another example is that the agency is amending loan contract terms and publishing written policy standards without meeting the requirements of Title II that 

prohibits RUS from denying loans or taking adverse actions against applicants or 

borrowers for any reason not based upon a rule adopted in an informal rulemaking 

proceeding. Neither can applicants be required to increase their ratio of net income 

or margins before interest to obtain a loan nor can loans be rescinded without the 

consent of the borrower. In administering the broadband program the agency has 

not established a consistent definition of ‘‘broadband’’. The agency employs one 

standard for approving a loan and another for determining whether an area is ‘‘underserved’’. There should be a consistent definition for both to avoid duplicative 

service. 

Better access to the advice and counsel of OGC could eliminate many of these 

issues and assure Congress and the public that the program is being administered 

in accordance with the act’s requirements. This could be accomplished through language in the Committee Report requiring that OGC make available additional legal 

resources to the agency. 

Grants for Medical Link and Distance Learning Purposes 

We support the continuation in fiscal year 2008 of the $25 million in grant authority provided in the President’s budget for medical link and distance learning 

purposes and the decision to not request additional loan funds for these programs. 

The purpose of these grants is to accelerate deployment of medical link and distance 

learning technologies in rural areas through the use of telecommunications, computer networks, and related advanced technologies by students, teachers, medical 

professionals, and rural residents. We agree with the conclusion in the budget that 

these projects are more feasible when provided through grants to eligible recipients 

rather than loans. 

Conclusion 

Thank you for the opportunity to present the association’s views concerning this 

vital program. The telecommunications lending programs of RUS continue to work 

effectively and accomplish the objectives established by Congress at a minimal cost 

to the taxpayer. They serve to assure that America’s rural inhabitants will never 

become second-class citizens in this modern information age of telecommunications 

technology. 

PREPARED STATEMENT OF THE NATIONAL TURFGRASS FEDERATION, INC. 

Mr. Chairman and Members of the Subcommittee, on behalf of the National 

Turfgrass Federation (NTF), I appreciate the opportunity to present to you the 
787 

turfgrass industry’s need and justification for continuation of the $490,000 appropriated in the fiscal year 2007 budget for turfgrass research within the Agricultural 

Research Service (ARS) at Beltsville, MD. Secondly, we ask that the committee support the $1,880,000 request for Drought Mitigation, either by supporting the President’s budget request (we are unsure at this time if this funding was included in 

fiscal year 2008) or via a Congressional earmark. This funding will be used by ARS 

to conduct turfgrass water conservation and salinity research at Phoenix, AZ and 

Riverside, CA. Thirdly, we ask for your support of $450,000 in separate continuing 

funding for ongoing research programs in Beaver, WV, and $450,000 for Logan, UT. 

Finally, we request water quality research scientists at ARS stations in University 

Park, PA, ($450,000) and Madison, WI ($450,000). All funding provided by the Committee is requested to go directly to USDA–ARS, not the industry per se. 

Restoration of Funding for the Existing ARS Scientist Position and Related Support 

Activities at Beltsville, MD ($490,000) 

NTF and the turfgrass industry are requesting the Subcommittee’s support for 

$490,000 to continue funding for the full-time scientist staff position within the 

USDA, ARS at Beltsville, MD, focusing on turfgrass research, that was provided by 

the Committee in the fiscal year 2007 budget, and in the five previous budget cycles. 

We consider this funding our Congressional ‘baseline’, i.e. that funding which is central to and critical for the mission of the National Turfgrass Research Initiative. We 

are very grateful for this support and hope the Committee will continue this funding. 

Turfgrass is a 50,000,000 acre, $40 billion per year industry in the United States, 

that is growing exponentially each year. Turfgrass provides multiple benefits to society including child safety on athletic fields, environmental protection of groundwater, reduction of silt and other contaminants in runoff, and green space in home 

lawns, parks and golf courses. Therefore, by cooperating with NTF, USDA has a 

unique opportunity to take positive action in support of the turfgrass industry. 

While the vast majority of the USDA’s funds have been and will continue to be directed toward traditional ‘‘food and fiber’’ segments of U.S. agriculture, it is important to note that turfgrasses (e.g., sod production) are defined as agriculture in the 

Farm Bill and by many other departments and agencies. It should also be noted 

that the turfgrass industry is the fastest growing segment of U.S. agriculture, while 

it receives essentially no federal support. There are no subsidy programs for 

turfgrass, nor are any desired. 

For the past 70 years, the USDA’s support for the turfgrass industry has been 

modest at best. The turfgrass industry’s rapid growth, importance to our urban environments, and impact on our daily lives warrant more commitment and support 

from USDA. 

A new turfgrass research scientist position within USDA/ARS was created by 

Congress in the fiscal year 2001 budget. Additional funding was added in fiscal year 

2002 with the total at $490,000. A research scientist was hired, and is now working 

at the ARS, Beltsville, MD center. A research plan was developed and approved by 

ARS. This scientist has used the funding for a full-time technician, equipment and 

supplies to initiate the research plan and for collaborative research with universities. We have an excellent scientist in place, and he is making good progress in 

establishing a solid program. At this point, losing the funding for the position would 

be devastating to the turf industry, as significant research has begun. 

Support the President’s Budget Request for Drought Mitigation/Request a Congressional Earmark ($1,880,000) 

The turfgrass industry is excited that for the first time, the President’s fiscal year 

2007 budget contained funding for turfgrass research within ARS. Because the fiscal 

year 2007 was not passed before the President submitted his fiscal year 2008 request, we are unsure if this funding in the fiscal year 2008 President’s budget. 

Therefore, if included in the fiscal year 2008 President’s budget, we request support 

of this important drought mitigation research. If not included in the President’s fiscal year 2008 budget, we request that this funding be supported and included by 

Congress as new projects. This funding will be used to hire scientists in two very 

important locations, Riverside, CA and Maricopa, AZ, focusing on water conservation, wastewater reuse and salinity research. These issues are the most critical research needs for the survival of the turf industry. Following is a brief description 

of the research that ARS will conduct with this funding: 

ARS will: 

Develop Technology and Management Systems to Use Non-Potable Water to Reduce Agriculture’s Vulnerability to Drought ($1,880,000 total). In the process, ARS 

will develop systems to safely reuse wastewater and low-quality water as a means 
788 

of irrigating agricultural, horticultural and turf-based enterprises in an environmentally and economically sustainable manner. 

As noted in USDA’s Explanatory Notes accompanying the fiscal year 2007 budget 

request, this funding will be directed to the following two critical locations: 

Maricopa, AZ, ($940,000).—The U.S. Water Conservation Lab in Maricopa will determine the on-site impacts and movement in the air, soil, plant, and ground water 

of biological and chemical substances contained in treated and untreated waste 

water used for irrigation of turfgrass. They will also develop irrigation technologies 

and management systems to mitigate the impact of elevated levels of these compounds and nutrients when wastewater is used in the production of turf and specialty crops. 

Riverside, CA, ($940,000).—This research will be conducted at the world-renowned 

U.S. Salinity Lab. The Riverside lab will focus on the development of new irrigation 

technologies and systems to either mitigate or manage the effect of saline irrigation 

on the production of turf and specialty crops. 

Request Funding of Ongoing Programs and two ARS Scientist Positions at two ARS 

Installations @ $450,000 Each (Total: $900,000) 

The turfgrass industry also requests that the Subcommittee appropriate an additional $900,000 for funding first allocated in fiscal year 2005, and continued in fiscal 

year 2006 and fiscal year 2007 bills. As a part of the National Turfgrass Research 

Initiative, the research conducted at Logan, UT and Beaver, WV is vital to the turf 

industry. We are asking for $450,000 at each location. Following is a brief description of the research that ARS will conduct with this funding: 

Beaver, WV, ($450,000).—The lab at Beaver has significant expertise in soils and 

by-products research. They have excellent staff and facilities already in place. For 

the turfgrass industry, they are working on improving soil conditions and management systems to make athletic fields softer and with improved turf cover, thereby 

increasing safety. They also are considering the use of local by-products to develop 

improved soil systems for parks, lawns, athletic fields and golf courses. Besides 

being vital to the turf industry, this research is very important to the regional economy and many industrial concerns. 

Logan, UT, ($450,000).—Logan, UT is an ideal location for research on drought 

tolerant grasses and how they function. The Logan lab is world renowned for its efforts in collecting and improving grasses and other native plants for forage and 

range purposes. With the funding that was initiated in fiscal year 2005, they have 

directed additional efforts research on breeding and genetics of turfgrass, with emphasis on identifying plant material with superior drought and salt tolerance. Reducing water use, through more drought tolerant plant material, is the number one 

priority of the turfgrass industry. This research needs to be continued and expanded 

because of the excellent ongoing research as well as the potential for the future. 

Request new Funding of new Research on Water Quality Improvement at two ARS 

Installations @ $450,000 Each (Total: $900,000) 

Finally, the turfgrass industry requests funding for water quality improvement research at University Park, PA and Madison, WI; $450,000 for each location. Water 

quality improvement is very important to the turf industry. There is much speculation that fertilizers and pesticides applied to turf areas contribute to the contamination of streams, waterways and groundwater. Very little research has been conducted to date that proves or disproves this phenomenon. Therefore, answers are 

needed to make good production, management and regulatory decisions. In addition, 

the turf industry is concerned about our natural environment and wants to protect 

it. Therefore, research data is needed to understand the scope of the problem, as 

well as to develop practical solutions. To address the areas with the most critical 

needs, we propose funding for research at the following two locations: 

University Park, PA, ($450,000).—According to the EPA, runoff and groundwater 

contamination in the Chesapeake Bay Watershed is one of the critical contributors 

to the decline of Bay water quality. Although many industries have been implicated, 

fertilizer applications to lawns and golf courses are routinely mentioned as significant factors in this decline. Research to address this issue is virtually non-existent, 

yet is critical to the success of the turf industry in the Mid-Atlantic, as well as New 

England. The ARS lab at University Park is already researching these issues relating to pasture and forage. Therefore, they are uniquely positioned and they have 

expertise and facilities in place. We request that funding be allocated to hire a scientist dedicated to turf research. 

Madison, WI, ($450,000).—The other area of the United States with significant 

water quality concerns is the Upper Midwest. Phosphorus contamination in the region is the most pressing problem, with other nutrients also of concern. Several 
789 

states, including Minnesota and Wisconsin, have either already instituted turf fertilizer regulations or are considering them. ARS has facilities at Madison and 

Marshfield, WI, which have initiated research on dairy manure contamination and 

disposal. This is an excellent location to address the turf-related water quality 

issues in that region, issues that demand solutions to ensure the survival of the turf 

industry. 

THE NATIONAL TURFGRASS RESEARCH INITIATIVE

This Initiative has been developed by USDA/ARS in partnership with the 

turfgrass industry. The USDA needs to initiate and maintain ongoing research on 

turfgrass development and improvement for the following reasons: 

—The value of the turfgrass industry in the United States is $40 billion annually. 

There are an estimated 50,000,000 acres of turfgrass in the U.S. Turfgrass is 

the number one or two agricultural crop in value and acreage in many states 

(e.g., MD, PA, FL, NJ, NC). 

—As our society becomes more urbanized, the acreage of turfgrass will increase 

significantly. In addition, state and local municipalities are requiring the reduction of water, pesticides and fertilizers on turfgrass. However, demand on recreational facilities will increase while these facilities will still be required to 

provide safe turfgrass surfaces. 

—Currently, the industry itself spends about $10 million annually on applied and 

proprietary turfgrass research. However, private and university research programs do not have the time nor the resources to conduct basic research and to 

identify completely new sources of beneficial genes for stress tolerance. ARS 

turfgrass scientists will enhance the ongoing research currently underway in 

the public and private sectors. Because of its mission to conduct the nation’s research for agricultural commodities, ARS is the proper delivery system for this 

research. 

—Water management is a key component of healthy turf and has direct impact 

on nutrient and pesticide losses into the environment. Increasing demands and 

competition for potable water make it necessary to use water more efficiently. 

Also, drought situations in many regions have limited the water available and, 

therefore, have severely impacted the turf industry as well as homeowners and 

young athletes. Therefore, new and improved technologies are needed to monitor turf stresses and to schedule irrigation to achieve the desired quality. Technologies are also needed to more efficiently and uniformly irrigate turfgrasses. 

Drought tolerant grasses need to be developed. In addition, to increase water 

available for irrigation, waste water (treated and untreated) must be utilized. 

Some of these waste waters contain contaminants such as pathogens, heavy 

metals, and organic compounds. The movement and accumulation of these contaminants in the environment must be determined. 

—USDA conducted significant turfgrass research from 1920–1988. However, since 

1988, no full-time scientist has been employed by USDA, Agricultural Research 

Service (ARS) to conduct turfgrass research specifically, until the recently appropriated funds became available. 

ARS and the turfgrass industry enjoy a special, collaborative relationship, and 

have even entered into a cooperative Memorandum of Understanding (MOU). 

The turfgrass industry has met on numerous occasions with USDA/ARS officials 

to discuss the new turfgrass scientist positions, necessary facilities, and future 

research opportunities. In January 2002, ARS held a customer workshop to gain 

valuable input from turfgrass researchers, golf course superintendents, sod producers, lawn care operators, athletic field managers and others on the research 

needs of the turfgrass industry. As a result of the workshop, ARS and the 

turfgrass industry have developed the National Turfgrass Research Initiative. 

The highlights of this strategy are as follows: 

ARS, as the lead agency at USDA for this initiative, has graciously devoted a 

significant amount of time to the effort. Like the industry, ARS is in this research endeavor for the long-term. To ARS’ credit, the agency has committed 

staff, planning and technical resources to this effort. Last year was the first 

time ARS has been able to include some funding in the President’s budget for 

the Turfgrass Research Initiative. However, there are so many issues and 

needs, that the industry is desperate for answers. Thus, to address the critical 

research needs, the industry is left with no alternative but to come directly 

to Congress for assistance through the appropriations process. 

The role and leadership of the federal government and USDA in this research 

are justifiable and grounded in solid public policy rationale. ARS is poised 
790 

and prepared to work with the turfgrass industry in this major research initiative. However, ARS needs additional resources to undertake this mission. 

The turfgrass industry is very excited about this new proposal and wholeheartedly supports the efforts of ARS. Since the customers at the workshop 

identified turfgrass genetics/germplasm and water quality/use as their top 

priority areas for ARS research, for fiscal year 2008, the turfgrass industry 

requests that the six positions above be established within USDA/ARS. 

For this research we propose an ARS-University partnership, with funding allocated to ARS for in-house research as well as in cooperation with university partners. For each of the individual scientist positions, we are requesting $300,000 for 

each ARS scientist position with an additional $150,000 attached to each position 

to be distributed to university partners, for a total of $450,000 per position. We are 

also asking that the funding be directed to ARS and then distributed by ARS to 

those university partners selected by ARS and industry representatives. 

In addition, the Committee should be receiving Senators’ requests for funding of 

each of the positions described above. We appreciate your strong consideration of 

each individual member request for the turfgrass research position in his or her respective state. 

In conclusion, on behalf of the National Turfgrass Federation and the turfgrass 

industry across America, I respectfully request that the Subcommittee continue in 

fiscal year 2008 the funding appropriated in fiscal year 2007 for Beltsville, MD, 

($490,000) within the Agricultural Research Service. I also request that the committee support the President’s budget request (or new funding) of $1,880,000 for 

Drought Mitigation. Third, I request the Subcommittee’s support of ongoing research programs at Beaver, WV and Logan, UT @ $450,000 each. Finally, I request 

that the Subcommittee appropriate an additional $900,000 for two new water quality research positions, at University Park, PA and Madison, WI, with $450,000 provided for each location. 

PREPARED STATEMENT OF THE NEW MEXICO INTERSTATE STREAM COMMISSION

SUMMARY

This Statement is submitted in support of appropriations for the U.S. Department 

of Agriculture’s Environmental Quality Incentives Program (EQIP) and the Colorado 

River Basin Salinity Control Program. Prior to the enactment of the Farm Security 

and Rural Investment Act (FSRIA) in 2002, the salinity control program had not 

been funded at the level necessary to control salinity with respect to water quality 

standards since the enactment of the Federal Agriculture Improvement and Reform 

Act (FAIRA) of 1996. Inadequate funding of the salinity control program also negatively impacts the quality of water delivered to Mexico pursuant to Minute 242 of 

the International Boundary and Water Commission. Adequate funding for EQIP, 

from which the U.S. Department of Agriculture (USDA) funds the salinity program, 

is needed to implement salinity control measures. The President’s budget for fiscal 

year 2008 requests an appropriation of $1 billion for EQIP. I urge the Subcommittee 

to support an appropriation of at least $1 billion to be appropriated for EQIP. I request that the Subcommittee designate 2.5 percent, but no less than $20 million, 

of the EQIP appropriation for the Colorado River Basin salinity control program. I 

request that adequate funds be appropriated for technical assistance and education 

activities directed to salinity control program participants. 

STATEMENT

The seven Colorado River Basin States, in response to the salinity issues addressed by Clean Water Act of 1972, formed the Colorado River Basin Salinity Control Forum (Forum). Comprised of gubernatorial appointees from the seven Basin 

States, the Forum was created to provide for interstate cooperation in response to 

the Clean Water Act, and to provide the States with information to comply with Sections 303(a) and (b) of the Act. The Forum has become the primary means for the 

seven Basin States to coordinate with federal agencies and Congress to support the 

implementation of the Salinity control program. 

Congress authorized the Colorado River Basin salinity control program in the Colorado River Basin Salinity Control Act of 1974. Congress amended the Act in 1984 

to give new responsibilities to the USDA. While retaining the Department of the Interior as the lead coordinator for the salinity control program, the amended Act recognized the importance of the USDA operating under its authorities to meet the objectives of the salinity control program. Many of the most cost-effective projects un-
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dertaken by the salinity control program to date have occurred since implementation of the USDA’s authorization for the program. 

Bureau of Reclamation studies show that quantified damages from the Colorado River to United States water users are about $330,000,000 per year. Unquantified 

damages are significantly greater. Damages are estimated at $75,000,000 per year 

for every additional increase of 30 milligrams per liter in salinity of the Colorado 

River. It is essential to the cost-effectiveness of the salinity control program that 

USDA salinity control projects be funded for timely implementation to protect the 

quality of Colorado River Basin water delivered to the Lower Basin States and Mexico. 

Congress concluded, with the enactment FAIRA in 1996, that the salinity control 

program could be most effectively implemented as a component of EQIP. However, 

until 2004, the salinity control program since the enactment of FAIRA was not funded at an adequate level to protect the Basin State-adopted and Environmental Protection Agency approved water quality standards for salinity in the Colorado River. 

Appropriations for EQIP prior to 2004 were insufficient to adequately control salinity impacts from water delivered to the downstream States, and hampered the required quality of water delivered to Mexico pursuant to Minute No. 242 of the International Boundary and Water Commission, United States and Mexico. 

EQIP subsumed the salinity control program without giving adequate recognition 

to the responsibilities of the USDA to implement salinity control measures per Section 202(c) of the Colorado River Basin Salinity Control Act. The EQIP evaluation 

and project ranking criteria target small watershed improvements which do not recognize that water users hundreds of miles downstream are significant beneficiaries 

of the salinity control program. Proposals for EQIP funding are ranked in the States 

of Utah, Wyoming and Colorado under the direction of the respective State Conservationists without consideration of those downstream, particularly out-of-State, 

benefits. 

Following recommendations of the Basin States to address the funding problem, 

the USDA’s Natural Resources Conservation Service (NRCS) designated the Colorado River Basin an ‘‘area of special interest’’ including earmarked funds for the salinity control program. The NRCS concluded that the salinity control program is different from the small watershed approach of EQIP. The watershed for the salinity 

control program stretches almost 1,200 miles from the headwaters of the river 

through the salt-laden soils of the Upper Basin to the river’s termination at the Gulf 

of California in Mexico. NRCS is to be commended for its efforts to comply with the 

USDA’s responsibilities under the Colorado River Basin Salinity Control Act, as 

amended. Irrigated agriculture in the Upper Basin realizes significant local benefits 

of improved irrigation practices, and agricultural producers have succeeded in submitting cost-effective proposals to NRCS. 

Years of inadequate Federal funding for EQIP since the 1996 enactment of FAIRA 

and prior to 2004 resulted in the Forum finding that the salinity control program 

needs acceleration to maintain the water quality criteria of the Colorado River 

Water Quality Standards for Salinity. Since the enactment of FSRIA in 2002, an 

opportunity to adequately fund the salinity control program now exists. The President’s budget request of $1 billion accomplishes the needed acceleration of the 

NRCS salinity control program if the USDA continues its practice of designating 2.5 

percent of the EQIP funds appropriated. The requested funding of 2.5 percent, but 

no less than $20 million, of the EQIP funding will continue to be needed each year 

for at least the next few fiscal years. 

State and local cost-sharing is triggered by and indexed to the federal appropriation. Federal funding for the NRCS salinity control program of about $19.5 million 

for fiscal year 2007 has generated about $15.8 million in cost-sharing from the Colorado River Basin States and agricultural producers, or about an 80 percent match 

of the federal funds appropriated for the fiscal year. 

USDA salinity control projects have proven to be a most cost-effective component 

of the salinity control program. USDA has indicated that a more adequately funded 

EQIP program would result in more funds being allocated to the salinity program. 

The Basin States have cost-sharing dollars available to participate in on-farm salinity control efforts. The agricultural producers in the Upper Basin are willing to costshare their portion and are awaiting funding for their applications to be considered. 

The Basin States expend 40 percent of the State funds allocated for the program 

for essential NRCS technical assistance and education activities. Previously, the 

Federal part of the salinity control program funded through EQIP failed to adequately fund NRCS for these activities, which has been shown to be a severe impediment to accomplishing successful implementation of the salinity control program. Recent acknowledgement by the Administration that technical assistance and 

education activities must be better funded has encouraged the Basin States and 
792 

local producers that cost-share with the EQIP funding for implementation of the essential salinity control work. I request that adequate funds be appropriated to 

NRCS technical assistance and education activities directed to the salinity control 

program participants (producers). I urge the Congress to appropriate at least $1 billion in fiscal year 2008 for EQIP. Also, I request that Congress designate 2.5 percent, but no less than $20 million, 

of the EQIP appropriation for the Colorado River Basin salinity control program. 

PREPARED STATEMENT OF THE ORGANIZATION FOR THE PROMOTION AND

ADVANCEMENT OF SMALL TELECOMMUNICATIONS COMPANIES

SUMMARY OF REQUEST

The Organization for the Promotion and Advancement of Small Telecommunications Companies (OPASTCO) seeks the Subcommittee’s support for fiscal year 

2008 loan levels for the telecommunications loans program administered by the 

Rural Utilities Service (RUS) in the following amounts: 

5 percent hardship loans .................................................................................................................................... $145 million 

Treasury rate loans .............................................................................................................................................. 250 million 

Guaranteed loans ................................................................................................................................................. 300 million 

In addition, OPASTCO requests that the distance learning, telemedicine, and 

broadband program be funded at sufficient levels. 

OPASTCO is a national trade association of approximately 550 small telecommunications carriers serving primarily rural areas of the United States. Its 

members, which include both commercial companies and cooperatives, together 

serve over 3.5 million customers in 47 States. 

Perhaps at no time since the inception of the RUS (formerly the REA) has the 

telecommunications loans program been so vital to the future of rural America. The 

telecommunications industry is at a crossroads, both in terms of technology and 

public policy. Rapid advances in telecommunications technology in recent years are 

delivering on the promise of a new ‘‘information age.’’ Both Federal and state policymakers have made ubiquitous availability of advanced communications services a 

top priority. However, without continued support of RUS’s telecommunications loans 

program, rural telecommunications companies will be hard pressed to continue deploying the infrastructure necessary to achieve policymakers’ objectives. 

Contrary to the belief of some critics, RUS’s job is not finished. Actually, in a 

sense, it has just begun. We have entered a time when advanced services and technology—such as fiber-to-the-home, high-speed packet and digital switching equipment, and digital subscriber line technology—are expected by customers in all areas 

of the country, both urban and rural. Moreover, the ability of consumers to use increasingly popular Voice over Internet Protocol (VoIP) services requires that they 

first have a broadband connection from a facilities-based carrier. Unfortunately, the 

inherently higher costs of upgrading the rural wireline network, both for voice and 

data communications, has not abated. 

Rural telecommunications continues to be more capital intensive and involves 

fewer paying customers per square mile than its urban counterpart. In the Federal 

Communication Commission’s September 2004 report on the deployment of advanced telecommunications capability, the Commission correctly noted that ‘‘[r]ural 

areas are typically characterized by sparse and disperse populations, great distances 

between the customer and the service provider, and difficult terrain. These factors 

present a unique set of difficulties for providers attempting to deploy broadband 

services.’’ More recently, the FCC’s January 2007 release of statistics on high-speed 

connections in the United States illustrated that low population density has an inverse association with reports that high-speed subscribers are present in an area. 

Thus, in order for rural telecommunications companies to continue modernizing 

their networks and providing consumers with advanced services at reasonable rates, 

they must have access to reliable low-cost financing. 

The relative isolation of rural areas increases the value of telecommunications for 

these citizens. Telecommunications enables applications such as high-speed Internet 

connectivity, distance learning, and telemedicine that can alleviate or eliminate 

some rural disadvantages. A modern telecommunications infrastructure can also 

make rural areas attractive for some businesses which results in revitalization of 

the rural economy. For example, businesses such as telemarketing and tourism can 

thrive in rural areas, and telecommuting can become a realistic employment option. 

Certainly, telecommunications plays a major role in any rural community’s economic 
793 

development strategy, with the existence of modern and advanced telecommunications infrastructure being a major enabling factor in the development of small 

business and manufacturing enterprises in rural areas. 

While it has been said many times before, it bears repeating that RUS’s telecommunications loans program is not a grant program. The funds loaned by RUS 

are used to leverage substantial private capital, creating public/private partnerships. For a very small cost, the government is encouraging tremendous amounts 

of private investment in rural telecommunications infrastructure. Most importantly, 

the program is tremendously successful. Borrowers actually build the infrastructure 

and the government is reimbursed with interest. 

In addition to RUS’s telecommunications loans program, OPASTCO supports adequate funding of the distance learning, telemedicine, and broadband program. 

Through distance learning, rural students gain access to advanced classes which 

will help them prepare for college and jobs of the future. Telemedicine provides 

rural residents with access to quality health care services without traveling great 

distances to urban hospitals. Furthermore, funding that is targeted to finance the 

installation of broadband transmission capacity will allow more rural communities 

to gain high-speed access to the Internet and receive other advanced services. In 

light of the Telecommunications Act’s purpose of encouraging deployment of advanced technologies and services to all Americans—including schools and health 

care providers—sufficient targeted funding for these purposes is essential in fiscal 

year 2008. 

CONCLUSION

The transformation of the nationwide telecommunications network into an information superhighway, as envisioned by policymakers, will help rural America survive and prosper in any market—whether local, regional, national, or global. However, without the availability of low-cost RUS funds, building the information superhighway in communities that are isolated and thinly populated will be untenable. 

By supporting the RUS telecommunications programs at the requested levels, the 

Subcommittee will be making a significant contribution to the future of rural America. 

PREPARED STATEMENT OF PICKLE PACKERS INTERNATIONAL, INC. 

The pickled vegetable industry strongly supports and encourages your committee 

in its work of maintaining and guiding the Agricultural Research Service. To accomplish the goal of improved health and quality of life for the American people, the 

health action agencies of this country continue to encourage increased consumption 

of fruits and vegetables in our diets. Accumulating evidence from the epidemiology 

and biochemistry of heart disease, cancer and diabetes supports this policy. Vitamins (particularly A, C, and folic acid) and a variety of antioxidant phytochemicals 

in plant foods are thought to be the basis for correlation’s between high fruit and 

vegetable consumption and reduced incidence of these debilitating and deadly diseases. The problem is that many Americans choose not to consume the variety and 

quantities of fruits and vegetables that are needed for better health. 

As an association representing processors that produce over 85 percent of the tonnage of pickled vegetables in North America, it is our goal to produce new products 

that increase the competitiveness of U.S. agriculture as well as meet the demands 

of an increasingly diverse U.S. population. The profit margins of growers continue 

to be narrowed by foreign competition. Likewise, the people of this country represent an ever-broadening array of expectations, tastes and preferences derived from 

many cultural backgrounds. Everyone, however, faces the common dilemma that 

food costs should remain stable and preparation time continues to be squeezed by 

the other demands of life. This industry can grow by meeting these expectations and 

demands with reasonably priced products of good texture and flavor that are high 

in nutritional value, low in negative environmental impacts, and produced with assured safety from pathogenic microorganisms and from those who would use food 

as a vehicle for terror. With strong research to back us up, we believe our industry 

can make a greater contribution toward reducing product costs and improving 

human diets and health. 

Many small to medium sized growers and processing operations are involved in 

the pickled vegetable industry. We grow and process a group of vegetable crops, including cucumbers, peppers, carrots, onions, garlic, cauliflower, cabbage (Sauerkraut) and Brussels sprouts, which are referred to as ‘minor’ crops. None of these 

crops is in any ‘‘commodity program’’ and as such, do not rely upon taxpayer subsidies. However, current farm value for just cucumbers, onions and garlic is $2.3 bil-
794 

lion with an estimated processed value of $5.8 billion. These crops represent important sources of income to farmers, and the processing operations are important employers in rural communities around the United States. Growers, processing plant 

employees and employees of suppliers to this industry reside in all 50 States. To 

realize its potential in the rapidly changing American economy, this industry will 

rely upon a growing stream of appropriately directed basic and applied research 

from four important research programs within the Agricultural Research Service. 

VEGETABLE CROPS RESEARCH LABORATORY, MADISON, WISCONSIN

The USDA/ARS Vegetable Crops Research Lab at the University of Wisconsin is 

the only USDA research unit dedicated to the genetic improvement of cucumbers, 

carrots, onions and garlic. Three scientists in this unit account for approximately 

half of the total U.S. public breeding and genetics research on these crops. Their 

past efforts have yielded cucumber, carrot and onion cultivars and breeding stocks 

that are widely used by the U.S. vegetable industry (i.e., growers, processors, and 

seed companies). These varieties account for over half of the farm yield produced 

by these crops today. All U.S. seed companies rely upon this program for developing 

new varieties, because ARS programs seek to introduce economically important 

traits (e.g., virus and nematode resistance) not available in commercial varieties 

using long-term high risk research efforts. The U.S. vegetable seed industry develops new varieties of cucumbers, carrots, onions, and garlic and over twenty other 

vegetables used by thousands of vegetable growers. The U.S. vegetable seed, grower, 

and processing industry, relies upon the USDA/ARS Vegetable Crops Research Lab 

for unique genetic stocks to improve varieties in the same way the U.S. health care 

and pharmaceutical industries depend on fundamental research from the National 

Institutes of Health. Their innovations meet long-term needs and bring innovations 

in these crops for the United States and export markets, for which the United 

States has successfully competed. Past accomplishments by this USDA group have 

been cornerstones for the U.S. vegetable industry that have resulted in increased 

profitability, and improved product nutrition and quality. 

Both consumers and the vegetable production and processing industry would like 

to see fewer pesticides applied to food and into the environment in a cost-effective 

manner. Scientists in this unit have developed a genetic resistance for many major 

vegetable diseases that are perhaps the most important threat to sustained production of a marketable crop for all vegetables. Genetic resistance assures sustainable 

crop production for growers and reduces pesticide residues in our food and environment. Value of this genetic resistance developed by the vegetable crops unit is estimated at $670 million per year in increased crop production, not to mention environmental benefits due to reduction in pesticide use. New research in Madison has 

resulted in cucumbers with improved disease resistance, pickling quality and suitability for machine harvesting. New sources of genetic resistance to viral and fungal 

diseases, environmental stress resistance like heat and cold, and higher yield have 

recently been mapped on cucumber chromosomes to provide a ready tool for our seed 

industry to significantly accelerate the development of resistant cultivars for U.S. 

growers. Nematodes in the soil deform carrot roots to reduce yield from 10 percent 

to over 70 percent in major production areas. A new genetic resistance to nematode 

attack was found to almost completely protect the carrot crop from one major nematode. This group improved both consumer quality and processing quality of vegetables with a resulting increase in production efficiency and consumer appeal. This 

product was founded on carrot germplasm developed in Madison, Wisconsin. Carrots 

provide approximately 30 percent of the U.S. dietary vitamin A. New carrots have 

been developed with tripled nutritional value, and nutrient-rich cucumbers have 

been developed with increased levels of provitamin A. Using new biotechnological 

methods, a system for rapidly and simply identifying seed production ability in onions has been developed that reduces the breeding process up to 6 years! A genetic 

map of onion flavor and nutrition will be used to develop onions that are more appealing and healthy for consumers. 

There are still serious vegetable production problems which need attention. For 

example, losses of cucumbers, onions, and carrots in the field due to attack by 

pathogens and pests remains high, nutritional quality needs to be significantly improved and U.S. production value and export markets could certainly be enhanced. 

Genetic improvement of all the attributes of these valuable crops are at hand 

through the unique USDA lines and populations (i.e., germplasm) that are available 

and the new biotechnological methodologies that are being developed by the group. 

The achievement of these goals will involve the utilization of a wide range of biological diversity available in the germplasm collections for these crops. Classical plant 

breeding methods combined with bio-technological tools such as DNA marker-as-
795 

sisted selection and genome maps of cucumber, carrot and onion will be the methods 

to implement these genetic improvements. With this, new high-value vegetable 

products based upon genetic improvements developed by our USDA laboratories can 

offer vegetable processors and growers expanded economic opportunities for United 

States and export markets. 

U.S. FOOD FERMENTATION LABORATORY, RALEIGH, NORTH CAROLINA

The USDA/ARS Food Fermentation Laboratory in Raleigh, NC is the major public 

laboratory that this industry looks to as a source for new scientific information on 

the safety of our products and development of new processing technologies related 

to fermented and acidified vegetables. Over the years this laboratory has been a 

source for innovations, which have helped this industry remain competitive in the 

current global trade environment. We expect the research done in this laboratory 

to lead to new processing and product ideas that will increase the economic value 

of this industry and provide consumers with safe, high quality, healthful vegetable 

products. 

To maintain the current level of research we request that Congress restore the funding increases provided in the fiscal year 2004 ($270,000) and fiscal year 2005 

($100,000) budgets. It is very important that Congress restore the full $370,000 in 

the fiscal year 2008 budget, since the funds were not included in the budget sent 

to the Congress. 

We seek additional funding to support two new research initiatives for this laboratory that have substantial economic potential for our industry and health benefits for the American public. These are: (1) Preservation of a variety of high nutrient/high antioxidant vegetables using fermentation or acidification techniques so as 

to maintain the natural levels of beneficial phyotochemicals in convenient to use 

value-added products; (2) development of techniques to deliver living pro-biotic 

microorganisms to consumers in fermented or acidified vegetable products. 

Certain vitamins (Vitamin C, folic acid) and beneficial phytochemicals in vegetables are stabilized by the low pH in acidified and fermented foods. In addition, low 

pH makes it possible to preserve vegetables with low heat or, ideally, no heat, which 

typically minimizes nutrient loss. While many high nutrient/high antioxidant vegetables are pickled to a very limited extent, traditional processes include steps, such 

as preserving in very high salt or acid followed by washing out the excess salt or 

acid, that result in loss many of the health-promoting components that diet authorities emphasize when they urge people to increase their consumption of fruits and 

vegetables. The objective will be develop new low acid/low salt preservation techniques for broccoli, Brussel sprouts, sweet potato, cauliflower, and peppers that will 

provide high levels of vitamin C, folic acid, carotenoids, glucosinolates, and phenolic 

compounds to maximize the health benefits of these vegetables in products that are 

convenient and attractive to consumers. 

Most of what we hear about bacteria in foods concerns the pathogens that cause 

disease. However, lactic acid bacteria are intentionally grown in fermented foods because they are needed to give foods like sauerkraut, yoghurt, cheeses, and fermented salami the characteristic flavors and textures that we desire. There is a 

growing body of research to indicate that certain living lactic acid bacteria are ‘probiotic’ and can improve human health by remaining in the intestinal tract after they 

are consumed. Fermented or acidified vegetables may be a good way to deliver such 

pro-biotic bacteria to consumers. The objective will be to identify pro-biotic lactic 

acid bacteria that can survive in high numbers in selected vegetable products and 

investigate the potential for using vegetables as healthful delivery vehicles for probiotic organisms. 

SUGAR BEET AND BEAN RESEARCH UNIT, EAST LANSING, MICHIGAN

The USDA/ARS East Lansing, Michigan location has the only federally funded research program that is devoted to developing new and/or improved engineering technologies and systems for assessing, retaining, and assuring postharvest quality, 

marketability, and wholesomeness of pickling cucumbers and other vegetable products. The vegetable postharvest engineering research is one component of the 

postharvest engineering research program within the Sugar Beet and Bean Research Unit in East Lansing, Michigan. The postharvest engineering research program currently has a full-time research agricultural engineer whose research is primarily focused on tree fruits. Over the past few years, the location has developed 

a number of innovative engineering technologies for rapid, nondestructive measurement and inspection of postharvest quality of tree fruits and vegetables. One is a 

novel laser-based multi-spectral scattering technology for assessing the texture and 

flavor of fruits. The technology may be used for inspecting a variety of vegetable 
796 

crops including cucumbers. The location did the pioneering work in applying 

hyperspectral imaging technology for quality assessment of fruits and vegetable. It 

recently developed an advanced hyperspectral imaging system for automated detection of quality/defect of pickling cucumbers. 

Currently the location’s cucumber postharvest engineering research is grossly 

under funded, and it has not been carried out at the full scope it would have been 

expected. Additional Federal funding for the location would enable the hiring of a 

full-time research agricultural engineer to focus on development of new and/or improved engineering technologies and equipment for postharvest handling of pickling 

vegetable products. Today, consumers have increasing choices of foods and they become more conscious of food quality and nutrition. An effective quality control and 

assurance system throughout the handling steps between harvest and retail is critical for providing consistent, superior products to the marketplace. Methods currently available for measuring and grading quality of cucumbers and other vegetables are either ineffective or time consuming. New and/or improved technologies are 

needed to assess, inspect and grade fresh cucumbers rapidly and accurately for various internal and external quality characteristics so that raw products can be directed to, or removed from, appropriate processing or marketing avenues. This will 

minimize postharvest losses of food that has already been produced and ensure high 

quality, consistent final product and end-user satisfaction. Research at East Lansing 

will lead to new inspection and grading technology that will help the pickling industry in delivering high-quality safe products to the marketplace. 

U.S. VEGETABLE LABORATORY, CHARLESTON, SOUTH CAROLINA

The research program at the USDA/ARS Vegetable Laboratory in Charleston, 

South Carolina, addresses national problems in vegetable crop production and protection with emphasis on the southeastern United States. This research program is 

internationally recognized for its accomplishments, which have resulted in development of over 150 new vegetable varieties and lines along with the development of 

many new and improved disease and pest management practices. This laboratory’s 

program currently addresses 14 vegetable crops including those in the cabbage, cucumber, and pepper families, which are of major importance to the pickling industry. The mission of the laboratory is to (a) develop disease and pest resistant vegetable crops and (b) develop new, reliable, environmentally sound disease and pest 

management programs that do not rely on conventional pesticides. 

Continued expansion of the Charleston program is crucial. Vegetable growers depend heavily on synthetic pesticides to control diseases and pests. Cancellation and/ 

or restrictions on the use of many effective pesticide compounds are having a considerable influence on the future of vegetable crop production. Without the use of certain pesticides, growers will experience crop failures unless other effective, non-pesticide control methods are found quickly. The research on improved, more efficient 

and environmentally compatible vegetable production practices and genetically resistant varieties at the U.S. Vegetable Laboratory continues to be absolutely essential. This gives U.S. growers the competitive edge they must have to sustain and 

keep this important industry and allow it to expand in the face of increasing foreign 

competition. Current cucumber varieties are highly susceptible to a new strain of 

the downy mildew pathogen; this new strain has caused considerable damage to 

commercial cucumber production in some South Atlantic and Midwestern states in 

2005 and 2006, and a new plant pathologist position needs to be established to address this critical situation. 

FUNDING NEEDS FOR THE FUTURE

It remains critical that funding continues the forward momentum in pickled vegetable research that the United States now enjoys and to increase funding levels as 

warranted by planned expansion of research projects to maintain U.S. competitiveness. We also understand that discretionary funds are now used to meet the rising 

fixed costs associated with each location. Additional funding is needed at the Wisconsin and South Carolina programs for genetic improvement of crops essential to 

the pickled vegetable industry, and at North Carolina and Michigan for development 

of environmentally-sensitive technologies for improved safety and value to the consumer of our products. The fermented and acidified vegetable industry is receptive 

to capital investment in order to remain competitive, but only if that investment is 

economically justified. The research needed to justify such capital investment involves both short term (6–24 months) and long term (2–10 years or longer) commitments. The diverse array of companies making up our industry assumes responsibility for short-term research, but the expense and risk are too great for individual 

companies to commit to the long-term research needed to insure future competitive-
797 

ness. The pickled vegetable industry currently supports research efforts at Wisconsin and North Carolina and anticipates funding work at South Carolina and 

Michigan as scientists are put in place. Donations of supplies and processing equipment from processors and affiliated industries have continued for many years. 

U.S. Vegetable Laboratory, Charleston, South Carolina 

The newly constructed laboratory-office building at the U.S. Vegetable Laboratory 

was occupied in April 2003. Design of the accompanying greenhouse and head house 

using the funds appropriated for this purpose in fiscal year 2003 was completed in 

July 2004. In fiscal year 2004, construction of the head house component of this 

project was funded. The head house component of the project is now under construction with an expected completion in late spring 2006. In fiscal year 2005, $2.976 

million was appropriated for construction of greenhouses. In fiscal year 2006, an additional $1.980 million was appropriated for construction of greenhouses, but $7.794 

million is still needed for the planned $12.750 million greenhouse complex. This new 

facility replaces and consolidates outmoded laboratory areas that were housed in 

1930s-era buildings and trailers. Completion of the total research complex will provide for the effective continuation and expansion of the excellent vegetable crops research program that has been conducted by the Agricultural Research Service at 

Charleston for over 70 years. It is most critical to the mission of the U.S. Vegetable 

Laboratory that the fiscal year 2002, fiscal year 2003, and fiscal year 2004 appropriated funds for expansion of the Charleston research staff is maintained in fiscal 

year 2008. In addition, new funds are needed to establish a plant pathology position 

to address cucumber diseases, especially the disease caused by a new strain of the 

downy mildew pathogen that has caused extensive damage to cucumber production 

in some South Atlantic and Midwestern states during the past 2 years. The plant 

pathologist is needed to characterize pathogen strains using molecular methodologies and to develop new management approaches and resistant cucumber lines. This 

new plant pathologist position will greatly contribute to the accomplishment of research that will provide for the effective protection of cucumbers from disease without the use of conventional pesticides. This position will require a funding level of 

$450,000 for its establishment. 

Appropriations to restore Fiscal year Gross funds im- pacted 

Minor Use Pesticides (IR–4) ................................................................................................... 2002 $5,398 

U.S. Vegetable Laboratory ....................................................................................................... 2003 489,868 

U.S. Vegetable Laboratory ....................................................................................................... 2004 266,260 

Total Funds to Restore .............................................................................................. ........................ 761,526 

New scientific staff needed Current status New funds 

needed 

Plant Pathologist (cucumber disease) ................................................................ Needed ...................................... $450,000 

New funds needed ................................................................................. ................................................... 450,000 

Food Fermentation Laboratory, Raleigh, North Carolina 

The current funding for the laboratory is $1,274,000. This includes the new funds provided in fiscal year 2004 ($270,000) and in fiscal year 2005 ($100,000) that are 

not in the fiscal year 2008 budget proposal that was sent to the Congress. We request that the additional funding provided by the Congress in fiscal year 2004 and 

fiscal year 2005 be restored in the fiscal year 2008 budget. 

To carry out the new research initiatives to maximize retention of beneficial components in high nutrient/high antioxidant vegetables and to develop systems to deliver pro-biotic lactic acid bacteria in acidified and fermented vegetable products, we 

request additional support for the Food Fermentation Laboratory of $200,000 in fiscal year 2008. This will provide support for Post-Doctoral or Pre-Doctoral research 

associates along with necessary equipment and supplies to develop these new areas 

of research. 

Scientific staff Current status Funds 

needed 

Microbiologist ....................................................................................................... Active ........................................ $318,500 

Chemist ................................................................................................................ Active ........................................ 318,500 

Food Technologist/Biochemist ............................................................................. Active ........................................ 318,500 
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Scientific staff Current status Funds 

needed 

Microbial Physiologist .......................................................................................... Active ........................................ 318,500 

Fiscal year 2008 Post-doctoral or Predoctoral Research Associates ................. Needed ...................................... 200,000 

Total funding required ........................................................................... ................................................... 1,474,000 

Presidential Budget (fiscal year 2008) ............................................................... ................................................... 912,195 

Appropriations to restore ..................................................................................... ................................................... 361,805 

New funds needed ............................................................................................... ................................................... 200,000 

Vegetable Crops Research Laboratory Unit, Madison, Wisconsin 

Current base funding for three scientists is $849,172, of which $200,000 was 

added in fiscal year 2002. An additional $50,828 is needed to fully fund the scientists and support staff, including graduate students and post-doctorates. 

Scientific staff in place Current status Funds 

needed 

Geneticist ............................................................................................................. Active ........................................ $300,000 

Horticulturist ........................................................................................................ Active ........................................ 300,000 

Geneticist ............................................................................................................. Active ........................................ 300,000 

Total funding required ........................................................................... ................................................... 900,000 

Presidential Budget (fiscal year 2008) ............................................................... ................................................... 798,222 

Appropriations to restore ..................................................................................... ................................................... 50,950 

New funds needed ............................................................................................... ................................................... 50,828 

A temporary addition of $200,000 was provided to enhance the research effort of 

this program in fiscal year 2002, and we greatly appreciate that additional support, 

but that addition is being proposed for reduction in fiscal year 2008. Thus, the restoration of the funds proposed for reduction, is urgently requested. We request a 

$101,778 permanent addition this year to sustain the long-term research of this 

group. 

Sugar Beet and Bean Research Unit, East Lansing, Michigan 

The location urgently needs to hire a full-time research engineer to develop a comprehensive research program on nondestructive inspection, sorting and grading of 

pickling cucumbers and other vegetable crops to assure the processing and keeping 

quality of pickled products. The current base funding for the cucumber engineering 

research is $200,000. An increase of $150,000 in the current base funding level 

would be needed to fund the research engineer position. 

Scientific staff in place Current status Funds 

needed 

Postdoctoral Research Associate ......................................................................... Active ........................................ $200,000 

Research Engineer ............................................................................................... Needed ...................................... 150,000 

Total funding required ........................................................................... ................................................... 350,000 

Current Funding ................................................................................................... ................................................... 200,000 

New funds needed ............................................................................................... ................................................... 150,000 

Thank you for your consideration and expression of support for the USDA/ARS. 

PREPARED STATEMENT OF THE RED RIVER VALLEY ASSOCIATION

Mr. Chairman and members of the Committee, I am Wayne Dowd, and I am 

pleased to represent the Red River Valley Association as its President. Our organization was founded in 1925 with the express purpose of uniting the citizens of Arkansas, Louisiana, Oklahoma and Texas to develop the land and water resources 

of the Red River Basin. (Enclosure 1) 
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The Resolutions contained herein were adopted by the Association during its 82nd 

Annual Meeting in Shreveport, Louisiana on February 22, 2007, and represent the 

combined concerns of the citizens of the Red River Basin Area as they pertain to 

the goals of the Association. (Enclosure 2) 

As an organization that knows the value of our precious water resources we support the most beneficial water and land conservation programs administered 

through the Natural Resources Conservation Service (NRCS). We understand that 

attention and resources must be given to our national security and the war in Iraq; 

however, we cannot sacrifice what has been accomplished on our Nation’s lands. 

NRCS programs are a model of how conservation programs should be administered 

and our testimony will address the needs of the Nation as well as our region. 

The President’s fiscal year 2008 budget for NRCS indicates a decrease of $131,740,000 (16 percent decrease) from what Congress appropriated in fiscal year 

2007, $841,340,000. In addition, the Administration eliminated two crucial watershed programs: Watershed & Flood Prevention Operations and Watershed Survey 

& Planning. Along with drastic reductions in the other programs, NRCS manpower 

for fiscal year 2008 would have to decrease by over 1,500 staff years, if the President’s budget is implemented. This is unacceptable. 

This means that NRCS assistance to landowners will not be adequately funded, 

to the detriment of the Nation and our natural resources. We would like to address 

several of the programs administered by NRCS. Failure to adequately fund these 

initiatives would reduce assistance to those who want it and the resources that need 

protection. 

Conservation Operations.—This account has been in steady decline, in real dollars, over the past several years. The President’s budget included $689 million, which is 

a decrease of $70 million from what Congress appropriated in fiscal year 2007. Mandated increases in pay and benefits, continuing increases in the cost of doing business’ and budget reductions greatly reduces the effective work that can be accomplished in this account. Allocations should be increased not decreased. We request a total of $930 million be appropriated for Conservation Operations 

for NRCS to meet the demands it faces today. 

Conservation Technical Assistance is the foundation of technical support and a 

sound, scientific delivery system for voluntary conservation to the private users and 

owners of lands in the United States. It is imperative that we provide assistance 

to all ‘‘working lands’’ not just those fortunate few who are able to enroll in a Federal program. Working lands are not just crops and pasture (commodity staples) but 

includes forests, wildlife habitat and coastal marshes. The problem is that NRCS 

personnel funded from ‘‘mandatory programs’’ can only provide technical assistance 

to those enrolled in these programs, leaving the majority of the agricultural community without technical assistance. We recommend that adequate funding be placed 

in ‘‘Conservation Technical Assistance’’, and allow NRCS to provide assistance to all 

who are in need of assistance. 

It is our understanding that the Technical Service Providers (TSP) program has 

not lived up to its expectations. Experience indicates landowners are hesitant to use 

the program. This program funds projects at a level estimated if NRCS conducted 

the work. Usually the TSP cost exceeds this estimate and the landowner is responsible for the difference, effectively making the landowner cost share. We believe that 

TSPs should be used only after NRCS staffing is brought up to levels commensurate 

with the increase in workload caused by the Farm Bill, not to replace NRCS staffing. 

Watershed and Flood Prevention Operations (Public Law 566 & 534).—We are 

greatly disappointed that the President’s Budget provided no funding for watershed 

operations in the last two fiscal years. There is no doubt that this is a Federal responsibility, in conjunction with a local sponsor. This program addresses all watershed needs to include: flood protection, water quality, water supply and the ecosystem. There is no Corps of Engineer, Bureau of Reclamation or FEMA program 

to address small watershed needs, before disaster strikes. We recommend that Congress continue to hold oversight hearings to understand the importance and hear 

how popular this program is to our communities. 

Over the past 50 years these projects have developed a $15 billion infrastructure 

that is providing $1.5 billion in annual benefits to over 47 million people. It is not 

a Federal program, but a federally assisted program. This partnership between local 

communities, State agencies and NRCS has been successful for over 50 years. It 

would take $1.6 billion to fund the existing Federal commitment to local project 

sponsors. This cost only increases every year if adequate funding is not provided. 

All ongoing contracts will be terminated, if you allow this program to end. This 

will ultimately lead to lawsuits and tort claims filed by both sponsors and contractors, due to the Federal Government not fulfilling its contractual obligation. 
800 

We are very appreciative for the funding level of $75 million enacted in fiscal year 

2006, but that was the last year funding was provided. No funding was provided 

in fiscal year 2007. For every $1 spent, the Nation realizes $2 in benefits. Congress 

must take back responsibility for this program. 

There are many new projects, which are awaiting funds for construction under this program. We strongly recommend that a funding level of $190 million be appropriated for Watershed Operations Programs, Public Law 534 ($20 million) and Public Law 566 ($170 million). 

The Red River has proven, through studies and existing irrigation, to be a great 

water source for ‘‘supplemental’’ irrigation. The two projects mentioned below, will 

use existing, natural bayous to deliver water for landowners to draw from. The majority of expense will be for the pump system to take water from the Red River to 

the bayous. These projects will provide the ability to move from ground water dependency to surface water, an effort encouraged throughout the Nation. Both will 

enhance the environmental quality and economic vitality of the small communities 

adjacent to the projects. —Walnut Bayou Irrigation Project, AR.—Plans and specifications have been completed and it is ready to proceed into the construction phase. An irrigation district has been formed and they are prepared to take on the responsibility to 

generate the income for the O&M required to support this project. We request 

that $4,000,000 be appropriated for these projects in fiscal year 2008. —Red Bayou Irrigation Project, LA.—The plans and specifications have been completed, making this project ready for construction in fiscal year 2007. An irrigation district has been formed and is prepared to collect funds to support the 

O&M for this proposed system. We request that $2,500,000 be specifically appropriated to begin construction in 

fiscal year 2008. 

Watershed Rehabilitation.—More than 10,400 individual watershed structures 

have been installed nationally, with approximately one-third in the Red River Valley. They have contributed greatly to conservation, environmental protection and enhancement, economic development and the social well being of our communities. 

More than half of these structures are over 30 years old and several hundred are 

approaching their 50-year life expectancy. Today you hear a lot about the watershed 

approach to resource management. They protect more people and communities from 

flooding now than when they were first constructed. The benefit to cost ratio for this 

program has been evaluated to be 2.2:1. What other Federal program can claim such 

success? 

In the next 5 years over 900 watershed structures will require over $570 million 

for rehabilitation. Each year this number increases as more dams reach their 50- 

year life. There is no questioning the value of this program. The cost of losing this 

infrastructure exceeds the cost to reinvest in our existing watersheds. Without repairing and upgrading the safety of existing structures, we miss the opportunity to 

keep our communities alive and prosperous. It would be irresponsible to dismantle 

a program that has demonstrated such great return and is supported by our citizens. We cannot wait for a catastrophe to occur, where life is lost, to decide to take 

on this important work. 

The President’s budget neglects the safety and well being of our community needs 

and only recommends $6 million for this program. This is drastically lower than the 

levels authorized in the 2002 Farm Bill, which authorized $600 million for rehabilitation for 2003–2007. 

We request that $75 million be appropriated to provide financial and technical assistance to those watershed projects where sponsors are prepared (35 percent cost 

share) to commence rehabilitation. 

Watershed Survey and Planning.—In fiscal year 2006, $6.1 million was appropriated to support this extremely important community program. Again, no funding 

was provided in fiscal year 2007. NRCS has become a facilitator for the different 

community interest groups, State and Federal agencies. In our States such studies 

are helping identify resource needs and solutions where populations are encroaching 

into rural areas. The Administration decided to eliminate this program. We disagree 

with this and ask Congress to fund this program at the appropriate level. 

Proper planning and cooperative efforts can prevent problems and insure that 

water resource issues are addressed. Zeroing out the planning process assumes the 

economy will not grow and there is no need for future projects. We do not believe 

anyone supports or believes this. Another serious outcome is that NRCS will lose 

its planning expertise, which is invaluable. 

We request this program be funded at a level of $35 million. 

We request that the following two studies be specifically identified and funded in 

the fiscal year 2008 appropriation bill. 
801 

—Maniece Bayou Irrigation Project, AR.—This is a project in its initial stage of 

planning. An irrigation district is being formed to be the local sponsor. This 

project transfers water from the Red River into Maniece Bayou where landowners would draw water for supplemental irrigation. We request that $200,000 

be appropriated to initiate the plans and specifications. 

—Lower Cane River Irrigation Project, LA.—The transfer of water from the Red 

River to the Lower Cane River will provide opportunities for irrigation and economic development. Funds are needed to initiate a Cooperative River Basin 

Study. We request that $250,000 be appropriated for this study. 

Resource Conservation and Development (RC&D).—This has traditionally been a 

well-received program by the Administration, not this year. Their budget proposal 

only had $14.6 million, far short of national needs. This program leverages its resources at 4 to 1, with communities, local sponsors and non-government organizations. The benefits are realized at over 14 to 1, average per project. This drastic cut 

is proposed by eliminating 325 of 375 coordinator positions. The remaining 50 positions are supposed to serve all councils in all the 50 States. 

We request that $56 million be appropriated for this program, at the same level 

as in fiscal year 2006. 

Mandatory Accounts (CCC) Technical Assistance (TA).—Request for assistance 

through the CCC programs has been overwhelming. Requests far exceed the available funds and place an additional workload on NRCS’s delivery system. Adequate 

funding for TA must be provided at the full cost for program delivery. This includes 

program administration, conservation planning and contracting with each applicant. 

Congress, in the 2002 Farm Bill, wisely increased conservation programs each year. 

This increased investment, will increase the NRCS workload. It is imperative that 

NRCS receive the TA funding levels required to administer these programs. If they 

do not receive full funding these programs will not realize their full capability. 

It has been mandated that a set percent of TA, from the CCC Program, must be 

used for TSPs, approximately $40 million. This is equivalent to losing 600 staff 

years from NRCS manpower. This is another unacceptable policy, which will reduce 

the effectiveness of NRCS. This mandate must be eliminated. 

Over 70 percent of our land is privately owned. This is important in order to understand the need for NRCS programs and technical assistance. Their presence is 

vital to ensuring sound technical standards are met in conservation. These programs not only address agricultural production, but sound natural resource management. Without these programs and NRCS properly staffed to implement them, many 

private landowners will not be served adequately to apply conservation measures 

needed to sustain our natural resources for future generations. Technical Assistance 

cannot be contracted out to private companies. 

We are all aware of the issue with TMDL levels in our waterways. If our Nation 

is to seriously address this we must look at the impacts from our farmlands. Assistance for land treatment plans and plan implementation is exactly what the NRCS 

Watershed programs are intended to address. Watershed programs should be receiving an increase in funds, not zeroed out! 

With these new clean water initiatives why do we ignore the agency that has a 

proven record for implementing watershed conservation programs? Congress must 

decide; will NRCS continue to provide the leadership within our communities to 

build upon the partnerships already established? It is up to Congress to insure 

NRCS is properly funded and staffed to provide the needed assistance to our taxpayers for conservation programs. 

These NRCS studies and watershed projects are an example of true ‘‘cooperative 

conservation’’ initiatives. There is an interface with communities and local sponsors 

at each step of the process and local sponsors do cost share at the levels expected 

of them. 

All these programs apply to the citizens in the Red River Valley and their future 

is our concern. The RRVA is dedicated to work toward the programs that will benefit our citizens and provide for high quality of life standards. We therefore request 

that you appropriate the requested funding within these individual programs, to insure our Nation’s conservation needs are met. 

I thank you for the opportunity to present this testimony on behalf of the members of the Red River Valley Association and we pledge our support to assist you 

in the appropriation process. Please direct your comments and questions to our Executive Director, Richard Brontoli, P.O. Box 709, Shreveport, LA 71162, (318) 221– 

5233, E-mail: redriverva@hotmail.com. 

Grant Disclosure.—The Red River Valley Association has not received any Federal 

grant, sub-grant or contract during the current fiscal year or either of the 2 previous 

fiscal years. 
802 

ENCLOSURE 1.—RED RIVER VALLEY ASSOCIATION

The Red River Valley Association is a voluntary group of citizens bonded together 

to advance the economic development and future well being of the citizens of the 

four State Red River Basin area in Arkansas, Louisiana, Oklahoma and Texas. 

For the past 80 years, the Association has done notable work in the support and 

advancement of programs to develop the land and water resources of the Valley to 

the beneficial use of all the people. To this end, the Red River Valley Association 

offers its full support and assistance to the various Port Authorities, Chambers of 

Commerce, Economic Development Districts, Municipalities and other local governmental entities in developing the area along the Red River. 

The Resolutions contained herein were adopted by the Association during its 82nd 

Annual Meeting in Shreveport, Louisiana on February 22, 2007, and represent the 

combined concerns of the citizens of the Red River Basin area as they pertain to 

the goals of the Association, specifically: 

—Economic and Community Development 

—Environmental Restoration 

—Flood Control 

—Irrigation 

—Bank Stabilization 

—A Clean Water Supply for Municipal, Industrial and Agricultural Uses 

—Hydroelectric Power Generation 

—Recreation 

—Navigation 

The Red River Valley Association is aware of the constraints on the Federal budget, and has kept those constraints in mind as these Resolutions were adopted. 

Therefore, and because of the far-reaching regional and national benefits addressed 

by the various projects covered in the Resolutions, we urge the members of Congress 

to review the materials contained herein and give serious consideration to funding 

the projects at the levels requested. We can be contacted at (318) 221–5233 or 

redriverva@hotmail.com. 

ENCLOSURE 2

RED RIVER VALLEY ASSOCIATION FISCAL YEAR 2008 APPROPRIATIONS—NATURAL RESOURCES 

CONSERVATION SERVICE (NRCS) 

[In thousands of dollars] 

Discretionary Accounts Fiscal year 2006 

Approp 

Fiscal year 2007 

Approp 

Pres. 2008 

Budget 

RRVA 2008 

Request 

Conservation Operations ............................................... 839,519 759,124 689,000 930,000 

Watershed & Flood Prevention Operations ................... 75,000 ........................ ........................ 190,000 

Walnut Bayou Irrigation Project, AR .................... ........................ ........................ ........................ 4,000 

Red Bayou Irrigation Project, LA ......................... ........................ ........................ ........................ 1,600 

Watershed Rehabilitation ............................................. 31,516 31,516 6,000 75,000 

Watershed Survey & Planning ...................................... 6,083 ........................ ........................ 35,000 

Maniece Bayou Irrigation Project, AR .................. ........................ ........................ ........................ 200 

North Wallace Lake Watershed, LA ..................... ........................ ........................ ........................ 250

Resource Conservation & Development(RC&D) ............ 51,300 50,700 14,600 56,000 

NOTE: The President’s fiscal year 2008 budget is 16 percent less than Congress appropriated in fiscal year 2007. 

PREPARED STATEMENT OF THE SOCIETY FOR ANIMAL PROTECTIVE LEGISLATION

$1.8 Million Line Item for the Animal Welfare Information Center at the National 

Agricultural Library 

The Animal Welfare Information Center (AWIC) was established by the Improved 

Standards for Laboratory Animals Act (the 1985 amendment to the Animal Welfare 

Act) to serve as a clearing-house, training center, and educational resource for institutions using animals in research, testing and teaching. The Center is the single 

most important resource for helping personnel at more than 1,200, U.S. research facilities meet their responsibilities under the AWA. Supported by a modest funding 

level, its services are available to all individuals at these institutions, including cage 

washers, animal technicians, research investigators, attending veterinarians, 

IACUC representatives and the Institutional Official. 

AWIC provides data on alleviating or reducing pain and distress in experimental 

animals (including anesthetic and analgesic procedures), reducing the number of 
803 

animals used for research where possible, identifying alternatives to the use of animals for specific research projects, and preventing the unintended duplication of 

animal experiments. The Center collects, updates, and disseminates material on humane housing and husbandry, the functions and responsibilities of Institutional Animal Care and Use Committees (IACUCs), animal behavior, improved methodologies, 

psychological well-being of primates, and exercise for dogs. 

There is general consensus between the biomedical research industry (including 

the National Association for Biomedical Research) and the animal welfare community about the need for increased funding. A number of individuals representing 

these disparate interests have endorsed the request for $1.8 million in funding for 

AWIC. The AWIC helps to improve the conduct of research, including the care provided to the animals who are used, thereby ensuring a reduction in variables that 

might skew the research. Better science is the end result. 

The AWIC website (http:www.nal.usda.gov/awic) is one of the most accessed sites 

at the NAL, receiving millions of hits each year. It provides valuable information 

on issues of importance not only to the science community but also to the agriculture and public health communities, including BSE and avian influenza, two of 

the top areas of inquiry for visitors to its website. In fiscal year 2006, nearly 440 

million kbytes of information were distributed via the web, and more than 77,000 

hard copies were distributed as well. AWIC staff provided over 3,000 personal reference services. Exhibitions and/or presentations have been conducted at such 

venues as the American Association for Laboratory Animal Science (AALAS) annual 

meeting, Society of Neuroscience, New Jersey Association for Biomedical Research, 

American Veterinary Medical Association, International Conference on Environmental Enrichment, American Association for the Advancement of Science and the 

5th World Congress on the Use of Animals in the Life Sciences, Scientists Center 

for Animal Welfare meetings, and the Public Responsibility in Medicine and Research annual meeting. 

We greatly appreciate Congress’ past support for AWIC to carry out its programs. 

Given its indispensability not only in assisting with compliance with the AWA but 

also in providing up-to-date information on a range of issues, from BSE to primate 

enrichment, that are critical to the scientific and agricultural communities, we recommend that AWIC be listed as a separate line item. We urge Congress to resist 

any effort by ARS to eliminate AWIC; rather, it is essential to maintain a minimum 

base of $1.15 million. Moreover, we respectfully request an additional $650,000 in 

fiscal year 2008 for desperately needed expansion to meet growing demand for 

AWIC’s expertise on two fronts. 

First, as evidenced by the findings of an Office of Inspector General (OIG) audit, 

‘‘APHIS Animal Care Program Inspection and Enforcement Activities,’’ there has 

been an increase in apparent violations of the AWA by research facilities over the 

past few years. There appears to be a significant problem with the oversight of 

IACUCs and the audit recommends training for IACUC members. In response to 

this need, we are requesting funds to allow AWIC to do the following: 

—Continue to conduct workshops at locations around the country rather than 

being limited to conducting them only from the Center’s base in Maryland. 

—Hold a symposium on AWA requirements for IACUC nonaffilated members (i.e., 

members from the community charged with representing the communities’ concerns for the animals). 

—Work with Animal Care more closely to identify and assist those licensees and 

registrants that are cited for AWA violations most frequently. 

Second, increased funding is also necessitated by the expansion of AWIC’s mandate to include the broader industry regulated under the Animal Welfare Act: animal dealers, carriers and handlers, zoos and other exhibitors. Other topics covered 

by the Center include animal diseases, animal models, animal training, and environmental enrichment for all species. Animal Care’s veterinary medical officers and 

animal care inspectors are able to utilize the full range of services provided by the 

AWIC to better fulfill their responsibilities. The AWIC also works closely with both 

Animal Care and with Emergency Veterinary Services on emerging crises such as 

the highly pathogenic Avian Influenza. The Center is focused on transmissible 

spongiform encephalopathy, exotic Avian Newcastle disease, tuberculosis, West Nile 

Virus and microbacterial diseases. 

The $1.8 million would be used as follows: Staff salary and benefits ($1,273,000), 

including the addition of two much-needed positions: a Technical Information Specialist and an Information Technology Specialist, whose jobs would be to expand the 

content of the Center’s database and make it more user-friendly and searchable; exhibitions at major scientific conferences, including underserved areas of the country 

($61,400); workshops, in conjunction with Animal Care, to assist licensees and registrants frequently cited for AWA violations ($36,000); informational workshops at 
804 

research institutions across the country ($28,000) and locally at the Center ($4,100); 

printing and reproduction of paper and electronic material ($29,200); training for 

the NAL staff ($13,900); acquisition of, including electronic access to, data ($38,000); 

internet services ($20,400); office supplies, including hardware and software 

($26,000); and the overhead that must be provided to the Agricultural Research 

Service and the National Agricultural Library (at least $270,000). 

$750,000, Plus a One-Time Infusion of $1 Million, for APHIS/Animal Care’s Enforcement of the Horse Protection Act 

More than 30 years ago Congress adopted the Horse Protection Act, yet soring of 

Tennessee Walking Horses continues to be a widespread problem. Soring is defined 

by APHIS as ‘‘the application of any chemical or mechanical agent used on any limb 

of a horse or any practice inflicted upon the horse that can be expected to cause 

it physical pain or distress when moving.’’ Horses are sored to produce an exaggerated gait. (http://www.saplonline.org/pdf/EquusSoring.pdf) 

The most effective method to reduce the showing of sored horses is to have Animal Care (AC) inspectors present at the shows. Oftentimes, as soon as an AC inspector arrives at a show, there is a rush to put horses back into trailers and haul 

them away. If the likelihood that an AC inspector will show up increases significantly, this will have a huge deterrent effect on those who routinely sore their 

horses. 

AC was able to attend only 32 events in fiscal year 2004 out of a total of approximately 865 shows. Funding of $750,000 ($500,000 plus a $250,000 add-on) is needed 

to enable AC to attend even a modest number of events. 

Unfortunately, the amount of penalties assessed for violations of the law has 

dropped to a negligible amount. In addition to increasing the presence of inspectors, 

USDA must increase the penalties that it assesses or the industry will continue to 

defy the law with impunity. Congress should direct USDA to take this step. 

Lack of financial support has made it necessary for Animal Care to rely heavily 

on the industry to assume responsibility for enforcement of the law. This is the 

same industry that has turned a blind eye to compliance with the law since 1970! 

‘‘Designated Qualified Persons’’ (DQPs) are the ‘‘inspectors’’ from industry who are 

supposed to assist AC in identifying sore horses and pursuing action against the individuals who are responsible. The history of the DQPs reveals their failure to 

achieve the level of enforcement of the unbiased, well-trained, professional inspectors who work for AC, as illustrated by radically different enforcement rates: In 

2004 and 2005, the rate of violations cited at a variety of horse shows was as much 

as 23 times higher under USDA inspections versus HIO inspections. Oftentimes, 

owners withdraw their horses completely from a show rather than risk an inspection by USDA. 

We have few current figures on enforcement; however, we recently learned from 

USDA that in 2005, of the samples taken by a gas chromatography machine (used 

to test for use of illegal substances to sore horses) at the Kentucky Celebration 

horse show, 100 percent indicated the presence of diesel fuel or another similar fuel 

plus numbing agents. Clearly the law is not being taken seriously by the industry. 

In September 2006, having ignored repeated warnings from USDA that too many 

horses were showing signs of soring, organizers canceled the Shelbyville (TN) Celebration, the prestige event in the walking horse industry, after USDA inspectors 

disqualified most of the horses because of soring. This was an unprecedented action 

on the part of the industry and is a testament to USDA’s commitment to vigorous 

enforcement of the HPA, even in the face of threats to its inspectors. 

An appropriation of at least $750,000 is essential to permit AC to maintain a 

modest level of compliance with the Horse Protection Act by trained AC professionals. USDA also needs a one-time allocation of $1 million to purchase additional 

equipment, such as digital radiography machines to take radiographs of the hoof to 

detect changes indicative of pressure-shoeing; and algometers, which apply consistent pressure during the examination process. Adding these machines to the inspectors’ tools for verifying the use of soring techniques further enhances the objectivity and consistency of the evidence obtained. 

$21.126 Million for APHIS/Animal Care’s Enforcement of the Animal Welfare Act 

The Animal Welfare Act (AWA) is the chief Federal law for the protection of animals. The USDA seeks compliance with its minimum standards for the care and 

treatment of animals during transportation and at the nearly 13,000 sites of dealers, research, testing and teaching facilities, zoos, aquariums, circuses, carriers (airlines, motor freight lines and other shipping businesses) and handlers (ground 

freight handlers). There are a mere 101 Veterinary Medical Officers (VMOs) and 
805 

Animal Care Inspectors (ACIs) conducting searches, prelicensing inspections and enforcement inspections across the country. 

In fiscal year 2005, IES resolved 169 cases involving violations of the AWA; in 

fiscal year 2006, 191 cases were resolved through stipulations or ALJ decisions. 

These enforcement actions help ensure the protection of both animals and people 

as evidenced by the OIG Audit. 

We support the President’s request for $21.126 million for enforcement of the 

AWA. We hope the additional funds will permit USDA to hire additional inspectors 

and to conduct a national meeting, with all inspectors in attendance. A national 

meeting is indispensable to providing proper training of inspectors and ensuring 

that field inspectors nationwide apply a high and equal standard of enforcement. 

The cost for a national meeting is expected to be $150,000. 

We also support the President’s budget request for funds under the emergency 

management systems line item, which will enable Animal Care to execute its new 

responsibilities for pet evacuation during disasters. However, an additional $1 million is needed (for a total of $2 million) to ensure that AC does not have to meet 

these new obligations at the expense of ongoing services. 

Strengthened Enforcement of Humane Slaughter Act by FSIS 

When President Eisenhower signed the Humane Methods of Slaughter Act 

(HMSA) into law, he noted that if he went by his mail he would think Americans 

were interested in no other issue. That concern is as strong today as it was then. 

Over the past few years, Congress has generously provided additional appropriations to the Food Safety and Inspection Service (FSIS) to improve enforcement of 

the HMSA; nonetheless, problems persist. A big part of the problem is that the vast 

majority of animals currently slaughtered at the approximately 900 federally inspected plants are already dead by the time FSIS observes them. 

In addition, FSIS inspectors are discouraged from enforcing the law. Inspectors 

are supposed to be able to stop the slaughter line if violations are seen. However, 

stopping the line will markedly reduce the plant’s profits, so there is intense pressure for the inspector not to take action. The situation at plants appears to be cozy 

for people; meanwhile, animals are suffering. For example, the Office of the Inspector General conducted an investigation of a large plant in Iowa, issuing a report on 

April 25, 2005, that concluded that—employees of AGRI had engaged in acts of inhumane slaughter. It was also determined that FSIS employees observed the acts 

of inhumane slaughter and did nothing to stop the practice. Additionally, the investigation revealed that FSIS inspectors accepted meat products from AGRI employees 

and that FSIS employees engaged in other acts of misconduct.’’ 

FSIS has attempted a variety of machinations in an effort to dupe Congress into 

believing that enforcement efforts have increased dramatically. This is mere window 

dressing, and inspectors in the plants have confirmed that little has changed—and 

abuses are rife. The situation at AGRI, described above is but one example (http:// 

awionline.org/pubs/Quarterly/05l54l1/541p7a.htm). We vehemently oppose increased resources for FSIS because the agency hasn’t demonstrated resolve to 

strongly enforce the law. 

Bill language should direct FSIS to fill the many current vacancies in its inspector 

force and to re-assign and/or hire no fewer than 50 individual inspectors (as opposed 

to FTE’s or staff years) to serve as full-time, permanent fixtures in each of the largest slaughter plants to observe the handling, stunning and slaughter of animals for 

compliance with the law. When inspectors are not present, line speeds are increased 

and the operations are conducted in a completely different (and horrific) manner. 

A full-time presence is the only way to ensure compliance. Congress’ previous effort 

to achieve this goal has resulted in the hiring of more upper-level personnel who 

are involved in many supervisory tasks and are not present on a full-time basis in 

the these slaughter plants. FSIS should report the results of this effort to the Committee and evaluate the effectiveness of having full-time (not full time equivalent) 

enforcement of the humane slaughter requirements following a year of diligence. 

All inspectors who engage in HSA enforcement must receive adequate training 

about the law and, more importantly, must receive a strict mandate from the Secretary of Agriculture to take strong, immediate action against any violators of the 

HSA. This would be a modest step toward protecting the millions of animals who 

are killed for food from unnecessary suffering. While the Humane Activities Tracking system was intended to promote accountability regarding enforcement of the 

Humane Slaughter Act, and to provide data to guide the risk-based inspection system, it has failed to meet these goals. Instead it yields skewed data that actually 

result in needed attention being diverted from problem plants. We suggest that real 

progress in ensuring compliance with the HMSA rests with redirecting HAT funds 
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towards securing the many needed inspectors and improving training in HMSA enforcement. 

Congress Needs to Provide Increased Oversight of Wildlife Services Operations and 

Research 

Wildlife Services (WS) needs to ensure that the variety of tools it uses for management of wildlife under its purview are both effective and publicly acceptable. As 

improved tools are developed through research, operations must make use of this 

data and shift methods accordingly. 

WS needs to phase out use of steel jaw leghold traps. WS’ own research demonstrates the archaic nature of certain leghold traps; these should be prohibited immediately. Leghold traps slam shut with bone-crushing force on the limbs of their 

victims, tearing ligaments and tendons, severing toes and causing excruciating pain. 

These traps, opposed by the vast majority of Americans, have been condemned as 

‘‘inhumane’’ by the American Veterinary Medical Association, American Animal 

Hospital Association, World Veterinary Association and National Animal Control 

Association. 

WS should pursue no further testing of leghold traps as this would be an extremely wasteful and cruel use of taxpayer money. Previously, funds designated for 

trap research were merely passed through to a nongovernmental organization to utilize as it saw fit, without involvement from WS. If funds are allocated for trap testing, WS should conduct the research (on the myriad devices other than steel jaw 

traps) since the agency has the appropriate technical expertise. 

Further, WS should adopt a policy of checking all restraining traps within a 24- 

hour period. WS has developed a device that can be attached to a trap, and the device emits a signal when the trap is triggered; this wonderful new technology permits trappers to focus their energies on prompt checking of those traps that have 

actually been triggered. A wealth of scientific studies documents the fact that the 

longer an animal is in a restraining trap, the greater the injury. For this reason, 

the majority of States have a daily trap check requirement. Animals should not be 

subjected to long-drawn out pain because of a failure to assume the responsibility 

of carefully checking traps every day. This policy will help reduce the trauma experienced by non-target animals, too, ensuring that more of these animals will be able 

to be released alive. 

Thank you very much for the opportunity to submit testimony. We would be 

happy to provide any additional information that might be of interest. 

PREPARED STATEMENT OF THE HUMANE SOCIETY

As the largest animal protection organization in the country, we appreciate the 

opportunity to provide testimony to the Agriculture, Rural Development, Food and 

Drug Administration, and Related Agencies Subcommittee on fiscal year 2008 funding items of great importance to The Humane Society of the United States (HSUS) 

and its nearly 10 million supporters nationwide. 

ENFORCEMENT OF ANIMAL WELFARE LAWS

We thank you for your outstanding support during recent years for improved enforcement by the U.S. Department of Agriculture (USDA) of key animal welfare 

laws and we urge you to sustain this effort in fiscal year 2008. Your leadership is 

making a great difference in helping to protect the welfare of millions of animals 

across the country. As you know, better enforcement will also benefit people by helping to prevent: (1) orchestrated dogfights and cockfights that often involve illegal 

gambling, drug trafficking, and human violence, and can contribute to the spread 

of costly illnesses such as Exotic Newcastle Disease and bird flu; (2) injuries to 

slaughterhouse workers from animals that are still conscious; (3) the sale of 

unhealthy pets by commercial breeders, commonly referred to as ‘‘puppy mills’’; (4) 

laboratory conditions that may impair the scientific integrity of animal based research; (5) risks of disease transmission from, and dangerous encounters with, wild 

animals in or during public exhibition; and (6) injuries and deaths of pets on commercial airline flights due to mishandling and exposure to adverse environmental 

conditions. In order to continue the important work made possible by the Committee’s prior support, we request the following for fiscal year 2008: 

APHIS/ANIMAL WELFARE ACT (AWA) ENFORCEMENT

We request that you support the President’s request of $21,126,000 for AWA enforcement under APHIS. We commend the Committee for responding in recent years 

to the urgent need for increased funding for the Animal Care division to improve 
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its inspections of more than 13,000 sites, including commercial breeding facilities, 

laboratories, zoos, circuses, and airlines, to ensure compliance with AWA standards. 

Animal Care now has 100 inspectors (with eight vacancies that the agency is in the 

process of filling), compared to 64 inspectors at the end of the 1990s. We are pleased 

that the President’s budget recommends an increase of $3,340,000 (plus allowance 

for pay costs) to cover hiring 21 new staff to further improve AWA enforcement in 

fiscal year 2008. This increase will enable the agency to handle additional responsibilities as the number of licensed/registered facilities has grown by 13 percent 

from fiscal year 2005 to fiscal year 2006. 

APHIS /INVESTIGATIVE AND ENFORCEMENT SERVICES

We request that you support the President’s request of $12,728,000 for APHIS Investigative and Enforcement Services. We appreciate the Committee’s consistent 

support for this division, which handles many important responsibilities including 

animal welfare. The President’s budget recommends an increase of $2,143,000 (plus 

allowance for pay costs) and 18 staff years for IES in fiscal year 2008, of which 

$291,000 and 3 staff years will be used to improve enforcement of Federal animal 

welfare laws. In fiscal year 2006, IES resolved 191 cases through either civil penalty 

stipulations or Administrative Law Judge decisions (compared to 169 cases resolved 

during fiscal year 2005). 

OFFICE OF INSPECTOR GENERAL/ANIMAL FIGHTING ENFORCEMENT

We request sustained funding of $800,000 for the Office of Inspector General to 

focus on enforcement of animal fighting laws (this amount is incorporated in the 

President’s request for OIG base funding). We appreciate the inclusion of $800,000 

in recent years for USDA’s Office of Inspector General to focus on animal fighting 

cases. Congress first prohibited most interstate and foreign commerce of animals for 

fighting in 1976 and tightened loopholes in the law in 2002. Dogfighting and cockfighting are barbaric practices in which animals are drugged to heighten their aggression and forced to keep fighting even after they’ve suffered grievous injuries. 

Animal fighting is almost always associated with illegal gambling, and also often 

involves illegal drug trafficking and violence toward people. Dogs bred and trained 

to fight endanger public safety, and some dogfighters steal pets to use as bait for 

training their dogs. Cockfighting was linked to an outbreak of Exotic Newcastle Disease in 2002–2003 that cost taxpayers more than $200 million to contain. It’s also 

been linked to the death of at least nine people in Asia reportedly exposed through 

cockfighting activity to bird flu. Given the potential for further costly disease transmission, as well as the animal cruelty involved, we believe it would be a sound investment for the Federal Government to continue its efforts to combat illegal animal 

fighting activity. We also hope language can be included directing the agency to report back to the Committee on specific Federal animal fighting enforcement efforts 

undertaken during fiscal year 2008. 

FOOD SAFETY AND INSPECTION SERVICE/HUMANE METHODS OF SLAUGHTER ACT (HMSA)

ENFORCEMENT

We request sustained funding of no less than $5,000,000 and no fewer than 63 

staff years for HMSA enforcement (this amount is incorporated in the President’s 

request for FSIS base funding) and continued funding of $3,000,000 as provided in 

fiscal year 2007 to maintain the new Humane Animal Tracking system. We are 

grateful that Congress provided $5 million in fiscal year 2007 to sustain at least 

63 full time equivalent positions dedicated solely to inspections and enforcement related to the HMSA, plus $4 million in fiscal year 2006 and $3 million in fiscal year 

2007 to incorporate a new tracking system to ensure compliance with this law. The 

HMSA is designed to ensure that livestock are treated humanely and rendered unconscious before they are killed. The effort to target funds for this purpose was undertaken following reports of lax enforcement of the HMSA and animals being 

skinned, dismembered, and scalded while still alive and conscious. 

COOPERATIVE STATE RESEARCH, EDUCATION, AND EXTENSION SERVICE/VETERINARY

STUDENT LOAN FORGIVENESS

We request $1,000,000 to begin to fully implement the National Veterinary Medical Service Act (Public Law 108–161), specifically authorized in 2003, that received 

initial funding of $500,000 in fiscal year 2006 and an additional $500,000 in fiscal 

year 2007. We appreciate that Congress has begun to address the critical shortage 

of veterinarians practicing in rural and inner-city areas, as well as in government 

positions such as at FSIS and APHIS. Having adequate veterinary care is a core 
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animal welfare concern. A study released in June 2006 demonstrated the acute and 

worsening shortage of veterinarians working in rural farm animal practice, while 

domestic pets in both rural and urban areas are often left without necessary medical 

care. Veterinarians support our Nation’s defense against bioterrorism (the Centers 

for Disease Control estimate that 80 percent of potential bioterrorism agents are 

zoonotic—transmitted from animals to human). They are also on the front lines addressing public health problems associated with pet overpopulation, parasites, rabies, chronic wasting disease, bovine spongiform encephalopathy (‘‘mad cow’’ disease), and a host of other concerns. Veterinary school graduates face a debt burden 

of over $100,000 on average, and the lowest pay of any of the medical professions, 

with an average starting salary of $43,000. For those who choose employment in underserved rural or inner-city areas or public health practice, the National Veterinary 

Medical Service Act authorizes the Secretary of Agriculture to forgive student debt. 

It also authorizes financial assistance for those who provide services during Federal 

emergency situations such as disease outbreaks or disasters. We hope you will build 

on the initial funding provided last year to expand this needed program under 

CSREES or such other account as the Committee deems appropriate. 

APHIS/EMERGENCY MANAGEMENT SYSTEMS/DISASTER PLANNING FOR ANIMALS

We request that you support the President’s request of $1 million for Animal Care 

under APHIS’ Emergency Management Systems line item. Hurricanes Katrina and 

Rita demonstrated that many people refuse to evacuate if they are forced to leave 

their pets behind. The Animal Care division has been asked to develop an infrastructure to help prepare for and respond to animal issues in a disaster and incorporate lessons learned from previous disasters. These funds will be used for staff 

time and resources to support State and local governments’ and humane organizations’ efforts to plan for protection of people with animals. The additional resources 

will enable the agency to participate, in partnership with FEMA, in the newly revised National Response Plan without jeopardizing other Animal Care programs. 

APHIS/HORSE PROTECTION ACT ENFORCEMENT

We hope you will provide $750,000 (an add-on of $254,000 above the amount re- quested by the President for fiscal year 2008) plus a one-time appropriation of $1 

million for specialized equipment, and we urge the Committee to oppose any effort 

to restrict USDA from enforcing this law to the maximum extent possible. Congress 

enacted the Horse Protection Act in 1970 to end the obvious cruelty of physically 

soring the feet and legs of show horses. In an effort to exaggerate the high-stepping 

gate of Tennessee Walking Horses, unscrupulous trainers use a variety of methods 

to inflict pain on sensitive areas of the feet and legs for the effect of the leg-jerk 

reaction that is popular among many in the show-horse industry. This cruel practice 

continues unabated by the well-intentioned but seriously understaffed APHIS inspection program. The most effective way to meet the goal of the Horse Protection 

Act—to reduce the showing of sored horses—is to have Animal Care inspectors 

present at the shows. Owners who sore their horses go to great lengths to avoid detection, including leaving a show when USDA inspectors show up. The greater the 

likelihood of a USDA inspection, the greater the deterrent effect on those who routinely sore their horses. Unfortunately, Animal Care is able to attend fewer than 

10 of the 500-plus shows held annually. Funding of $750,000 is needed to maintain 

a modest level of compliance with the Horse Protection Act by trained Animal Care 

professionals. Moreover, a one-time infusion of $1 million is needed to enable Animal Care to buy specialized equipment, such as digital radiography machines, that 

would enhance the ability of USDA inspectors to detect evidence of soring. 

DOWNED ANIMALS AND BSE

We are pleased that the Bush Administration proposed an interim final rule in 

January 2004 to ban the use of downed cattle for human food, in the wake of the 

discovery of a cow in Washington State that was infected with Bovine Spongiform 

Encephalopathy (BSE). We hope the Committee will codify this ban—and extend it 

to other livestock besides cattle. While transmission of BSE from infected cows to 

people is most well understood, there is some science indicating that pigs may also 

harbor a form of this disease and downer pigs and other downer livestock are at 

a significantly higher risk of transmitting other serious and sometimes fatal illnesses through their meat, such as E. coli and Salmonella. Moreover, these animals 

suffer just as downed cattle do when they are moved en route to slaughter. 

As the Committee is aware, some segments of industry and members of Congress 

have recommended weakening the USDA downed cattle ban. They claim that animals unable to walk because of injury pose no health risk. But injury and illness 
809 

are often interrelated—an animal may stumble and break a leg because of disease 

that causes weakness and disorientation. And USDA inspectors would have a difficult—if not impossible—task trying to sort out the reason an animal became nonambulatory. Major consumer groups including Consumers Union and Consumer 

Federation of America, support groups for victims of food-borne illness such as Safe 

Tables Our Priority (S.T.O.P.), Creutzfeldt-Jakob Disease Foundation, and CJD 

Voice, food safety organizations, companies such as McDonald’s and Wendy’s, and 

many others have all pointed out how reckless such a system would be. Of the BSE 

cases identified in Canada and the United States to date, 10 out of 11 have involved 

downers, and at least 3 of these were identified as downed due to injuries, including 

the Washington State case (‘‘calving injuries’’) and a January 2005 case in Canada 

(‘‘slipped on ice/broken leg’’). The sole BSE-positive animal not identified as a downer was a Canadian cow exhibiting ‘‘abnormal locomotion and posture’’ who was 

euthanized in January 2006. 

From an animal welfare perspective, a comprehensive ban is needed because a 

downed animal with a broken leg would suffer just as much as a sick one if it’s 

dragged through a slaughterplant—maybe even more. A ban on use of all downers 

for human food also provides an incentive for producers to treat animals humanely 

and prevent livestock from going down. Even before the administrative ban, USDA 

estimated that only 0.4 percent to 0.8 percent of all cows processed annually were 

non-ambulatory. The downer ban encourages producers and transporters to engage 

in responsible husbandry and handling practices, so that this percentage may be reduced to levels approaching zero. Temple Grandin—advisor to the American Meat 

Institute and others in the meat industry—has noted that as many as ninety percent of all downers are preventable. Cases that involve broken bones and other injuries are perhaps the most preventable with improved husbandry. 

Most Americans had no idea that animals too sick or injured to walk were being 

dragged with chains or hauled by bulldozer en route to the food supply. When that 

fact came to light in December 2003, USDA’s prompt decision to ban all downer cattle from human food calmed consumers. Unraveling the ban would undermine consumer confidence. More than 99 percent of the 22,000∂ public comments USDA received on its downer ban called on the agency to maintain and strengthen its downer ban, with most asking that other species be included. For a report on the comments received by the agency, please go to: http://files.hsus.org/web-files/PDF/ 

2004l06l16lreptlUSDAlcomments.pdf. 

USDA testimony before various congressional committees has made clear that the 

agency need not rely on slaughterplant testing of downers for BSE surveillance purposes. Surveillance of downers can and should be conducted at rendering plants and 

on farms. 

In addition to the downer issue, we urge the Committee to provide adequate funding to ensure meaningful enforcement by the Food and Drug Administration of its 

‘‘feed ban,’’ designed to prevent BSE-contaminated animal products from being fed 

to other animals. We are concerned that inspectors visit facilities infrequently and 

rely on self-reporting by those facilities and paperwork checking rather than firsthand evaluation of feed content and dedicated production lines. We are also concerned that FDA relies a great deal on State agencies to conduct this oversight, 

when most States face severe budget constraints that may compromise their ability 

to handle this job. Preventing the spread of BSE is vital to the Nation as a whole, 

for public health, the agricultural industry, and animal welfare. Vigorous enforcement of the feed ban is an essential component of this effort. We hope adequate Federal funds will be provided in fiscal year 2008 to meet this challenge. 

ANIMAL WELFARE INFORMATION CENTER (AWIC)

AWIC was established by the 1985 amendment to the Animal Welfare Act (the 

Improved Standards for Laboratory Animals Act) to serve as a clearinghouse, training center, and educational resource for institutions using animals in research, testing and teaching. This Center is the single most important resource for helping personnel at more than 1,200 U.S. research facilities meet their responsibilities under 

the AWA. Supported by a modest funding level, its services are available to all individuals at these institutions, from cage washers to Institutional Animal Care and 

Use Committee (IACUC) representatives and the Institutional Official. Given its indispensability not only in assisting with compliance with the AWA but also in providing up-to-date information on issues ranging from BSE to primate enrichment 

that are critical to the scientific and agricultural communities, we recommend that 

AWIC be listed as a separate line item. We urge Congress to resist any effort by 

ARS to eliminate AWIC; rather, it is essential to maintain a minimum base of $1.15 

million. Moreover, we respectfully request an additional $650,000 (for a total of $1.8 
810 

million) in fiscal year 2008 for critically needed expansion and other improvements 

to meet growing demand for AWIC’s expertise. 

Again, we appreciate the opportunity to share our views and priorities for the Agriculture, Rural Development, FDA, and Related Agencies Appropriation Act of Fiscal Year 2008. We appreciate the Committee’s past support, and hope you will be 

able to accommodate these modest requests to address some very pressing problems 

affecting millions of animals in the United States. Thank you for your consideration. 

PREPARED STATEMENT OF THE WILDLIFE SOCIETY

The Wildlife Society appreciates the opportunity to submit testimony concerning 

the fiscal year 2008 budgets for the Natural Resources Conservation Service 

(NRCS), Animal Plant Health Inspection Service (APHIS), and Cooperative State 

Research, Education and Extension Services (CSREES). The Wildlife Society represents over 7,500 professional wildlife biologists and managers dedicated to sound 

wildlife stewardship through science and education. The Wildlife Society is committed to strengthening all Federal programs that benefit wildlife and their habitats 

on agricultural and other private land. 

Natural Resources Conservation Service 

The Wildlife Habitat Incentives Program (WHIP) is a voluntary program that provides technical and financial support to farmers and ranchers to create high quality 

wildlife habitat. Since 1998, nearly $150 million has been dedicated to the program 

and over 2.8 million acres involving over 18,000 contracts have been enrolled. The 

Wildlife Society recommends funding WHIP at $100 million in fiscal year 2008 so 

that the program can continue to provide for fish and wildlife benefits. 

The Wetland Reserve Program (WRP) is a valuable program designed to assist 

farmers and ranchers in protecting and restoring wetland habitat. The Wildlife Society supports the President’s enrollment target of 250,000 acres in fiscal year 2008. 

Full WRP enrollment is needed if the Administration intends to achieve the President’s stated goal of no-net-loss of wetlands. 

Animal and Plant Health Inspection Service 

Wildlife Services (WS), a unit of APHIS, is responsible for controlling wildlife 

damage to agriculture, aquaculture, forest, range, and other natural resources, for 

controlling wildlife-borne diseases, and for controlling wildlife at airports. Its activities are based on the principles of wildlife management and integrated damage 

management, and are carried out cooperatively with State fish and wildlife agencies. 

The Wildlife Society is concerned by the Administration’s proposal to decrease funding in key activity areas for WS. The President’s fiscal year 2008 proposed budget 

includes increases for wildlife monitoring and surveillance ($5.016 million) and the 

oral rabies vaccination program ($2 million), but proposes an overall decrease of 

$1.684 million in the WS Operations line item, requiring a redirection of $8.7 million. While we are pleased that these activities have gained presidential support, 

the net decrease to the WS operational budget will effectively result in an overall 

reduction in key activity areas. The Wildlife Society strongly recommends that Congress restore the proposed decrease of $1.684 million. 

We understand the importance of safeguarding our Nation against highly pathogenic avian influenza and applaud the added fiscal resources to address this critical 

issue. The President’s fiscal year 2008 budget proposal redirects $3.2 million for 

avian influenza research. The Wildlife Society recommends that Congress provide 

additional money to adequately fund this and other important and associated research. Redirection of funds for this program would have serious and, in many 

cases, terminal effects on important existing projects, including the Jack Berryman 

Institute for Wildlife Damage Management at Utah and Mississippi State Universities; the Logan, Utah Predator Research Station; the newly-established Texas 

A&M University-Kingsville Research Field Station; and the Starkville, Mississippi 

Research Field Station. 

The Wildlife Society is very concerned about the proposed $1.39 million reduction 

in the Brucellosis Program budget. Because of its presence in wild elk and bison, 

brucellosis in the Greater Yellowstone Area will be especially difficult to eliminate 

and will require more, not less, fiscal resources to accomplish. We recommend Congress restore brucellosis funding to $11 million in fiscal year 2008 and that USDA– 

APHIS-Veterinary Services continue to utilize the authorities and expertise of the 

Greater Yellowstone Interagency Brucellosis Committee to address domestic livestock interactions with wild elk and bison in the region. 

The Wildlife Society commends APHIS-Veterinary Services for providing funding 

to State wildlife management agencies for Chronic Wasting Disease (CWD) surveil-
811 

lance and management in free-ranging deer and elk. Additionally, The Wildlife Society strongly supports APHIS’ efforts to eliminate CWD from captive cervids in order 

to eliminate the risk of spread of the disease from these animals to free-ranging 

deer and elk. The surveillance and monitoring efforts conducted by all 50 States 

during 2004 and 2005 would not have been possible without this cooperative funding. Additionally, knowledge of the presence and prevalence of CWD has been enhanced by this program. Without continued funding, States will be unable to maintain the level of CWD surveillance necessary to track the disease. The Wildlife Society recommends restoring the $6.3 million decrease to return funding to fiscal year 

2007 levels. 

Cooperative State Research, Education, and Extension Service 

The Renewable Resources Extension Act (RREA) provides an expanded, comprehensive extension program for forest and rangeland renewable resources. The 

RREA funds, which are apportioned to State Extension Services, effectively leverage 

cooperative partnerships at an average of four to one, with a focus on private landowners. The need for RREA educational programs is greater today than ever because of continuing fragmentation of ownership, urbanization, the diversity of landowners needing assistance and increasing societal concerns about land use and the 

impact on natural resources including soil, water, air, wildlife and other environmental factors. The Wildlife Society recommends that the Renewable Resources Extension Act be funded at $30 million, as authorized in the 2002 Farm Bill. 

The proposed budget for fiscal year 2008 reflects a slight decrease for the 

McIntire-Stennis Cooperative Forestry program. The proposal would modify the 

McIntire-Stennis formula program by creating a multi-State research program supported by about 62 percent of the total funding. All McIntire-Stennis multi-State 

funds will be distributed through competitively awarded grants in 2008. This represents a significant departure from prior years. These funds are essential to the 

future of resource management on non-industrial private forestlands, as forest products are produced while conserving natural resources, including fish and wildlife. As 

demand for forest products grow, private-land forests will increasingly be needed to 

supplement supplies, but trees suitable for harvest take decades to produce (versus 

the single year in which crops such as corn and soybeans can be harvested). In the 

absence of long-term and on-going research, such as provided through McIntireStennis, the Nation could easily become ill-suited to meet future forest-product 

needs. Replacement of McIntire-Stennis funding with competitive grants will leave 

long-term and stable forest research to chance. The Wildlife Society strongly believes that the reasons for continuing the McIntire-Stennis Cooperative Forestry 

program into the future are compelling and urges Congress to increase the fiscal 

year 2008 budget to $25 million, an amount more consistent with historic levels. 

National Research Initiative (NRI) Competitive Grants are open to academic institutions, Federal agencies, and private organizations to fund research on improving 

agricultural practices, particularly production systems that are sustainable both environmentally and economically, and to develop methods for protecting natural resources and wildlife. Innovative grant programs such as NRI help broaden approaches to land management, such as integrating timber and wildlife management 

on private lands. The Wildlife Society supports the Administration’s request of 

$256.5 million for National Research Initiative Competitive Grants. Included within 

that total, however, is approximately $36 million for programs authorized under 

Section 406 of the Research, Extension and Education Act of 1998 and previously 

funded under the ‘‘Integrated Activities’’ line in the CSREES budget. While The 

Wildlife Society does not oppose this consolidation, Congress should ensure that sufficient funding is available to support all of these efforts at no less than their fiscal 

year 2007 levels. 

Thank you for considering the views of wildlife professionals. We look forward to 

working with you and your staff to ensure adequate funding for wildlife conservation. 

PREPARED STATEMENT OF THE UNITED STATES TELECOM ASSOCIATION

SUMMARY OF REQUEST

Project Involved 

Telecommunications Loan and Grant Programs Administered by the Rural Utilities Service of the U.S. Department of Agriculture. 
812 

Actions Proposed 

Supporting RUS loan levels and the associated funding subsidy, as required, for the 5 percent direct loan program ($145 million) and cost of money program ($250 

million) in fiscal year 2008 in the amounts requested in the President’s budget. Supporting Section 306 guaranteed loans in the amount ($295 million) requested 

in the President’s budget. 

Opposing the budget request that would cut direct loans for broadband facilities 

and internet service access by 40 percent from the fiscal year 2006 enacted level 

of $500 million. 

Supporting renewal of the pilot broadband grant program and an allocation of a 

portion of the authorized levels for broadband loans at reduced interest rates to accelerate deployment of this technology in rural areas. 

Continuation of the general provision contained in previous appropriations acts 

that would prohibit RUS from drafting or implementing any regulation or rule requiring recertification of rural status for telephone borrowers. 

Supporting the continued elimination of the 7 percent cap on cost of money loans 

Supporting continued funding, as requested in the President’s budget, in the amount of $25 million for telemedicine and distance learning grants in rural areas. 

Seeking language strengthening and improving the operation of the broadband 

loan program in the Committee Report accompanying the bill. 

Supporting provision of sufficient funds for staff, including legal staff, to properly 

administer the telecommunications and broadband programs. 

I am Walter B. McCormick, Jr., President and CEO of the United States Telecom 

Association (USTelecom). I submit this testimony in the interests of the members 

of USTelecom and the customers they serve. USTelecom represents innovative companies ranging from the smallest rural telecoms in the Nation to some of the largest 

corporations in the U.S. economy. Our member companies offer a wide range of 

services across the communications landscape, including voice, video and data over 

local exchange, long distance, Internet and cable networks. 

USTelecom members firmly believe that the targeted assistance offered by a 

strong RUS telecommunications loan and grant program remains essential to a 

healthy and growing rural telecommunications industry that contributes to the provision of universal telecom service. We appreciate the strong support this Committee has provided for the RUS telecom program since its inception in 1949 and 

look forward to a vigorous program for the future. 

Rural Areas Need Access to Broadband Service 

Access to a reliable source of capital such as the RUS loan programs is key to 

the system upgrades which will enable rural areas to experience the economic 

growth and job creation that a freely competitive market with ready access to fairly 

priced capital can provide. 

It is critically important that rural areas be included in the nationwide drive for 

greater bandwidth capacity. In order to provide higher speed data services, such as 

Digital Subscriber Line (DSL) or even fiber optic connections to the Internet, outside 

plant must be modernized and switching must be migrated to new platforms. These 

investments may not be justified by market conditions in low density high cost rural 

areas, so the RUS program provides important financial incentives for additional investment which encourages rural telecommunications companies to build facilities 

which allow advanced services, including distance learning and telemedicine, to be 

provided. The externalities measured in terms of economic development and human 

development more than justify this investment in the future by the federal government. 

Greater bandwidth and packet switching capabilities are crucial infrastructure 

elements which will allow rural businesses, schools and health care facilities to take 

advantage of the other programs available to them as end users. The money spent 

on having the most modern and sophisticated equipment available at the premises 

of businesses, schools or clinics is wasted if the local telecommunications company 

cannot afford to build facilities that quickly transport and switch the large amounts 

of voice, video and data that these entities generate. RUS funding enhances the 

synergies among the FCC and RUS programs targeted at improving rural education 

and health care through telecommunications. 

RUS endures because it is a brilliantly conceived public-private partnership in 

which the borrowers are the conduits for the federal government benefits that flow 

to rural telephone customers, the true beneficiaries of the RUS program. The government’s contribution is leveraged by the equity, technical expertise and dedication 

of local telecom companies. The small amount of government capital involved is 

more than paid back through a historically perfect repayment record by telecom borrowers, as well as the additional tax revenues generated by the jobs and economic 
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development resulting from the provision and upgrading of telecommunications infrastructure. RUS is the ideal government program—it provides incentives where 

the market does not for private companies to invest in infrastructure promoting 

needed rural economic development, it allows citizens to have access to services 

which can mean the difference between life and death, and it has never lost a nickel 

of taxpayer money because of a telecom carrier default. 

Recommendations 

For fiscal year 2008, this Committee should set the loan levels and necessary associated subsidy amounts for the 5 percent direct loan program and cost of money 

loan programs consistent with the levels recommended in the President’s budget. 

The guaranteed telecommunications loan program should also be funded at the level 

requested in the budget. 

Congress and the President have recognized the tremendous potential of 

broadband technology to enhance human and economic development in rural areas 

by establishing as a priority loans for the deployment of such technology in rural 

areas. USTelecom urges the provision of funding for these loans sufficient to support 

$500,000,000, the same amount adopted in the 2006 appropriations act. The capital 

intensive nature of the telecommunications industry, particularly with respect to 

implementation of broadband, requires a stable and predictable source of funds. 

Congress should be lauded for its recognition of the importance of broadband deployment to our Nation’s economy and particularly for the recognition, through support 

of the RUS program, of the tremendous impact broadband telecommunications can 

have on economic growth and development in rural America. The pilot broadband 

grant program, initiated by Congress in previous appropriations acts, should be renewed at a higher level and increased funding should be provided so that a portion 

of the authorized levels for broadband loans can be allocated to reduced interest rate 

loans. 

Improving the Effectiveness of the RUS Broadband Program 

Redirecting Broadband Program Funding to Unserved Areas.—Since the inception 

of the broadband program, RUS has used a substantial portion of the available 

funds to make loans to areas that already have broadband service. RUS justifies 

these loans for duplicative facilities with the contention that service in these areas 

is inadequate and so the areas are ‘‘underserved’’, thereby permitting such duplication. For purposes of making broadband loans, RUS defines broadband service as 

200 kbps. Yet when determining whether an area is underserved, RUS will make 

a loan to any entity which promises a faster speed than is provided by the incumbent, even if the incumbent is providing service far in excess of the 200kbps standard RUS has set for new loans. RUS should be directed to use the same standard 

for new broadband loans as for the determination that an area is ‘‘underserved’’. 

RUS also has determined that an area is underserved if the applicant seeking to 

provide duplicative service will offer a substantial price differential relative to the 

incumbent. RUS has no objective standard for determining what constitutes a ‘‘substantial price differential’’. RUS should be directed to establish an objective standard through report language. 

The RUS broadband program should exclusively focus on extending the reach of 

broadband in rural America with a goal of ubiquitous deployment. Making loans for 

duplicative facilities and service, when other citizens in rural America reside in 

areas with no service at all, is a waste of scarce government resources. To properly 

redirect government funds to areas unserved by broadband, Congress should clarify 

that loans funds not be used for duplicative facilities, and should reaffirm that the 

non-duplication requirements of Title II of the Rural Electrification Act are equally 

applicable to the Title VI broadband program. The Undersecretary for Rural Development should be required to make a legal finding that any loan for broadband will 

not result in a duplication of facilities. To assist the Undersecretary in making this 

finding, RUS broadband applications should include the identity, list of services and 

charges as well as the service areas of the incumbent provider. Also, to the extent 

that they do not conflict, Congress should reaffirm that all the provisions of Title 

II, such as those relating to area coverage and loan feasibility, are equally applicable to the Title VI broadband program. 

Congress Should Amend the Farm Bill to Improve the Efficiency of the Broadband 

Program.—The statutory exclusion of companies with more than 2 percent of that 

Nation’s access lines from the broadband program is an unfortunate policy decision 

that limits the effectiveness of RUS in targeting funds to unserved areas. The RUS 

telephone program contains no such exclusion. Rural customers, the true beneficiaries of the RUS program, should not be denied its benefits because of the identity of the carrier from which they receive service. Similarly, the statutory require-
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ment that the term of broadband loans cannot exceed the expected useful life of the 

facilities being financed increases the size of periodic loan repayments and diminishes loan feasibility. Since RUS has a lien on all the property of the borrower, not 

just the new facilities, in most instances there is more than sufficient security for 

the loan for the broadband equipment. As long as the security of the government’s 

loan is sufficient, the term of the loan in relation to the life of the facilities financed 

is irrelevant. 

Congress Should Take Action to Improve the Feasibility of Loans in Unserved 

Areas by Renewing the Pilot Broadband Grant Program at a Higher Level and Increasing Funding to Permit Reduced Interest Rate Loans.—The RUS program is a 

public/private partnership. The government provides funds to fulfill a social goal 

and the borrowers use those funds to implement that goal in a way that makes 

sense for their business. Both goals are met when the revenues from the financed 

facilities generate sufficient revenue to repay the loan according to its terms. Providing broadband service in rural and remote areas currently unserved is a financially challenging proposition. While cost of money loans may provide a cost savings 

sufficient to make a project financially doable in some areas, other areas may need 

below cost loans or a combination of loans and grants in order to ensure feasibility. 

The pilot broadband grant program should be renewed at a higher level and increased funding should be provided so that a portion of the authorized levels for 

broadband loans can be allocated at reduced interest rates to accelerate deployment 

of broadband facilities in rural areas. 

Elimination of the Seven Percent cap on the Interest Rate for the ‘‘Cost of Money’’ 

Program 

For a number of years, through the appropriations process, Congress has eliminated the seven percent ‘‘cap’’ placed on the insured cost-of-money loan program. 

The elimination of the cap should continue. If long term Treasury interest rates exceeded the 7 percent ceiling contained in the authorizing act, the subsidy would not 

be adequate to support the program at the authorized level. This would be extremely disruptive and hinder the program from accomplishing its statutory goals. 

Accordingly, USTelecom supports continuation of the elimination of the seven percent cap on cost-of-money insured loans in fiscal year 2008. 

Recommended Loan Levels 

USTelecom recommends that the telephone program loan levels for fiscal year 

2008 be set as follows: 

Insured 5 percent Direct Loans ........................................................................................................................... $145,000,000 

Insured Cost-of-Money Loans .............................................................................................................................. 250,000,000 

Loan Guarantees .................................................................................................................................................. 295,000,000 

Broadband Telecommunications Loans ............................................................................................................... 500,000,000 

Total ........................................................................................................................................................ 1,190,000,000 

Loans and Grants for Telemedicine and Distance Learning 

USTelecom supports the continuation of $25 million in grants for distance learning and telemedicine, as provided in the President’s budget. As we move into the 

Information Age with the tremendous potential of the Internet to increase productivity, economic development, education and medicine, such funds can help continue 

the historic mission of RUS to support the extension of vital new services to rural 

America. 

Recertification of Rural Status Would Be Disruptive and Chill Rural Telecom Investment 

The Administration’s budget notes that USDA will propose rule changes to require recertification of rural status for each electric and telecommunications borrower on the first loan request received in or after 2008 and on the first loan request received after each subsequent Census. Telecom construction and investment 

is a long term continuous process, not a project by project proposition. The uncertainty created by the possibility of decertifying a borrower as rural after it has established a relationship with RUS and begun borrowing funds for expansion and upgrading according to a long term plan would be disruptive and discourage borrowers 

from participating in the RUS program, thereby denying its benefits to subscribers. 

The ‘‘once rural always rural’’ practice of RUS has been extraordinarily successful 

at providing needed long term capital, at a careful and measured pace, to telecom 

carriers intent on expanding and upgrading service to promote rural economic development. Congress should deny funding in fiscal year 2008 for such a rule change. 
815 

Conclusion 

Our members take pleasure and pride in reminding the Committee that the RUS 

telecommunications program continues its perfect record of no defaults by telecommunications carriers in over a half century of existence. RUS telecom borrowers 

take seriously their obligations to their government, their Nation and their subscribers. They will continue to invest in our rural communities, use government loan 

funds carefully and judiciously, and do their best to assure the continued affordability of telecommunications services in rural America. Our members have confidence that the Committee will continue to recognize the importance of assuring a 

strong and effective RUS Telecommunications and Broadband Program through authorization of sufficient funding and loan levels. 

PREPARED STATEMENT OF THE UNIVERSITY OF SOUTHERN MISSISSIPPI AND THE

MISSISSIPPI POLYMER INSTITUTE

Mr. Chairman, distinguished Members of the Subcommittee, I thank you for this 

opportunity to provide testimony describing ongoing research and commercializing 

efforts of The University of Southern Mississippi (USM) and the Mississippi Polymer Institute. I am very grateful to the Subcommittee for its leadership and the 

continued support of the Institute and its work. This testimony will include an update on the progress of the Institute since my testimony of approximately one year 

ago. During the past year, our efforts have focused principally on two research and 

commercialization areas. One effort involves our novel, agricultural-based inventions 

in emulsion polymerizations, and the other is to produce a commercial quality, formaldehyde-free, soybean based adhesive for composite board materials, specifically, 

particleboard. During the past year, we have advanced emulsion polymerization 

technology, and continued to refine the soy adhesive while preparing lab scale 

particleboards that now exceed all levels of commercial specifications for 

particleboard. It is my strong belief that additional research can expand the commercial use of the products and technology produced in these projects. However, 

more work must be accomplished to capitalize upon the variety of current and potential uses for these novel agricultural derived technology developments. I will discuss the progress for each of these research and development thrusts to provide 

maximum clarity. 

Seven patents, patent applications, and memorandums of invention were generated in 2006. Additionally in 2006, seven manuscripts were published, seven presentations to technical societies were given, and students who have performed laboratory research have won three awards. We remain energized, active, and successful at utilizing funding to increase the value of agricultural products and co-products, and discovering viable methods for utilizing agricultural-based products as alternatives or supplements to petroleum-derived materials. The success of our technology depends upon the use of agricultural materials as the primary building 

blocks for emulsion-derived polymers, and thus clearly offers opportunities for using 

ag-derived materials as a basic feedstock in the polymer industry. The same is true 

for the use of soybeans as an alternative to formaldehyde, a known carcinogen. 

The 2006–2007 research and development year was quite successful resulting in 

several pilot plant trials and planned commercial scale production for vegetable oilbased monomers and polymers. Vegetable oil macromonomers (VOMMs) have 

proved valuable in the synthesis of zero volatile organic content (VOC) architectural 

latexes, associative thickeners in coatings, as well as serving as the polymer infrastructure for Navy Haze Gray paint. The DOD is desirable of a replacement technology that excludes flammable organic solvents, contains zero VOCs, and matches 

or exceeds current performance requirements. We are happy to report that these requirements have been realized by use of unique agricultural-derived monomer technology invented in these laboratories. Vegetable oil-based monomers and latexes derived from this technology are being evaluated for use in adhesives, foams, wood 

composites, and several different coatings applications. Our VOMM synthesis techniques have been optimized to achieve greater than 90 percent conversion, producing only glycerol as a byproduct. The revised and now accepted synthetic procedure affords a useful, polymerizable VOMM without extraordinary methods or processes, thus reducing the cost of manufacture. During 2005 and 2006, our successful 

and novel synthetic techniques have allowed the synthesis of new emulsion polymers whose composition contains up to 70 percent VOMM by weight (based upon 

polymer solids). Moreover, this technology provides chemically and physically stable 

polymers suitable for a variety of end uses, particularly in coatings formulations. 

A significant advancement this year is attributed to our new level of control and 

understanding between monomer design and partitioning during the emulsion po-
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lymerization process. The novel derivatives provide VOMMs that are more readily 

copolymerizable with common commercial monomers. 

As an example of the potential impact of monomers and polymers derived from 

this technology, the following statistics are cited. In 2004, sales of low gloss water 

thinned paints (including tinting bases) were 181 million gallons, with a value of 

$1,551 million (www.census.gov.mcd). A 1 percent share of this market within two 

years would amount to 1.81 million gallons of low gloss paint. A typical flat latex 

paint contains 1,200 g of latex per gallon. With latexes containing 20 percent soybean oil derivatives, this market share would consume 950,000 lbs of soybean oil 

or 89,540 bushels (up to 70 percent soy oil derivatives have already been achieved 

in 2005–2006). It would not be unrealistic to expect that in five years, a market 

share of 5 percent resulting in the annual consumption of 447,700 bushels of soybeans for high value-added monomers and high performance decorative and protective coatings. The environmental impact has potential to reduce volatile organic 

emissions by 3.6 million lbs per year at only 1 percent market share (data 250 g/ 

L VOC 3.78L/gal, 1.81 million gallons and 1 percent market share). 

Vernonia oil, a naturally occurring epoxidized oil, was reacted with supercritical 

carbon dioxide to yield carbonated vernonia oil. This derivative has much lower viscosity than its synthetic analogs and can serve as a precursor for synthesizing 

isocyanate-free polyurethanes. The synthesis is an attractive option for reducing 

global levels of carbon dioxide while utilizing mainly natural products. Additionally, 

vernonia oil was modified to yield a novel polyol that resulted in lower viscosity 

than commercial, petrochemical-based polyol at the same hydroxyl value. This polyol 

was the key component in the synthesis of rigid foams that meet or exceed the mechanical performance of commercial foams based on petrochemical derivatives. 

A soybean oil-based VOMM was employed in the synthesis of associative thickeners for use with commercial latexes. The biobased thickener provided improved 

thickening efficiency when compared to commercial petrochemical-based thickeners 

at equal concentrations. The soybean oil-based VOMM was also used in the synthesis of a biobased ultraviolet absorber (UVA). The UVA displayed good gloss retention properties and its synthesis is being optimized to improve its effect on color 

retention. 

Commercial nail polishes contain very high amounts of organic solvents which 

constitute volatile organic compounds (VOCs) and negatively impact the environment. VOMM-based latexes, without the organic solvents, were formulated into environmentally-responsible, glossy nail polishes with acceptable dry times and water 

resistance properties. 

In summary, commercialization efforts have continued over the past year with waterborne architectural coatings, new technology to meet DOD needs for Navy Haze 

Gray waterborne paint, environmentally-responsible nail polish formulations, associative thickeners, and UV absorbers. Patents have been approved; new patent applications have been submitted; high performance monomers have been created and 

scaled-up for manufacture at toll production levels; new higher performing coatings 

have been designed, manufactured, formulated, and tested; and formulation efforts 

have been directed toward the generation of high performance, low odor, and low 

VOC coatings. We are optimistic that commercialization and sales of one or more 

of these ag-derived products will be realized in the year ahead. 

In yet another of our novel ag-based technologies, we have developed formaldehyde-free adhesives for use in particleboard composites. The developmental adhesive 

is composed of soy protein isolate (SPI), and lab produced particleboards made with 

this formaldehyde-free adhesive meet or exceed industry performance requirements 

as defined by ANSI standards for M1, M2, M3, and M–S grade boards. Processing 

and board production are compatible with current equipment and methodologies. 

Sustained research efforts have resulted in higher adhesive solids resulting in faster 

line speeds. Plant trials conducted with this novel soy-derived adhesive at a commercial particleboard manufacturing plant generated boards that were consistent 

with boards made in our laboratories under similar processing conditions. 

Particleboards typically employ wood chips as the discontinuous phase. Alternate 

sources of wood furnish are of interest in expanding the utility of soybean protein 

adhesive in composite applications. We have developed biobased composites using 

our soybean protein-based adhesive in conjunction with alternative materials such 

as cork, vermiculite, kenaf, and recycled paper, while polycaprolactone, defatted soy 

flour, lignin, and cellulose were evaluated as additives. 

In 1983, the Mississippi Legislature authorized the Mississippi Polymer Institute 

at USM to work closely with emerging industries and other existing polymer-related 

industries to assist with research, problem solving, commercializing efforts, and 

workforce development. The Institute has maintained that thrust during the past 

year with much success. In fact, while manufacturing jobs alone in Mississippi have 
817 

declined over the past 10 years, manufacturing jobs in the plastics sector have continued to increase (45 percent growth in 2004). The Institute provides industry and 

government with applied or focused research, development support, commercializing 

assistance, and workforce development. This effort complements existing strong ties 

with industry and government involving exchange of information and improved employment opportunities for USM graduates. Most importantly, through basic and applied research coupled with developmental and commercializing efforts of the Institute, the School of Polymers and High Performance Materials continues to address 

national needs of high priority. 

Our research remains focused on the study and development of technology platforms that facilitate further commercialization of alternative agricultural crops for 

use in the polymer industry. The polymer industry maintains its position as the single largest consumer of petroleum chemical intermediates in the world. The finite 

supply of petroleum resources has resulted in extreme price pressures as worldwide 

demand continues to increase. Unfortunately, this feedstock normally generates 

non-biodegradable raw materials that are not carbon neutral, and therefore do not 

represent a sustainable alternative for economic development in the polymer industry. The theme of our work is to develop high performance, and environmentally responsible technology utilizing agricultural intermediates. In this way, we as a Nation can improve our environment, reduce our dependence on imported petroleum, 

and keep America’s farmlands in production. As farm products meet the industrial 

needs of the American society, rural America is the benefactor. Heretofore, these 

successful efforts to utilize alternative agricultural products as an industrial feedstock continue to receive more and more attention but drastically less than these 

high tech innovations and opportunities warrant. Your decisions are crucial to the 

accomplishment of these goals as funding from this Subcommittee has enabled us 

to implement and maintain an active group of university-based polymer scientists 

whose energies are devoted to commercializing alternative crops. We are most grateful to you for this support, and ask for your continued commitment. 

Polymers, which include fibers, plastics, composites, coatings, adhesives, inks, and 

elastomers, play a key role in the materials industry. They are used in a wide range 

of industries including textiles, aerospace, automotive, packaging, construction, medical prosthesis, and health care. In the aerospace and automotive applications, reduced weight and high strength make them increasingly important as fuel savers. 

Their non-metallic character and almost unlimited design potential support their 

use for many national defense purposes. Moreover, select polymers are possible substitutes for so-called strategic materials, some of which come from potentially unreliable sources. 

As a polymer scientist, I am intrigued by the vast opportunities offered by American agriculture. As a professor, however, I continue to be disappointed that few of 

our science and business students receive training in the polymer-agricultural discipline despite its enormous potential. At USM, we are attempting to make a difference by showing others what can be accomplished if appropriate time, energy, 

and resources are devoted to the understanding of ag-based products. For more than 

40 years, I have watched the evolution of polymers where almost each new product 

offered the opportunity for many more. Although polymer science as a discipline has 

experienced expansion and a degree of public acceptance, alternative agricultural 

materials in the polymer industry continue to be an underutilized national treasure. 

Now is the ideal time for agricultural materials to make significant inroads as environmentally-responsible, biodegradable, and renewable raw materials. 

U.S. agriculture has made the transition from the farm fields to the kitchen tables, but America’s industrial community continues to be frightfully slow in adopting ag-based industrial materials. The prior sentence was included in my last four 

testimonies but continues to ring true, even as I write this report. We are making 

progress and we must persist. We must aggressively pursue this opportunity and 

in doing so: 

—Intensify United States efforts to commercialize alternative crops and dramatically reduce atmospheric VOC emissions and odor for a much cleaner and less 

noxious air for all Americans. 

—Reduce United States reliance on imported petroleum. 

—Maintain a healthy and prosperous farm economy. 

—Foster new cooperative opportunities between American farmers and American 

industry. 

—Create advanced polymer technology-based manufacturing jobs that cannot be 

easily exported to other countries. 

—Maintain our innovative and developmental competitive edge over other less environmentally-responsible countries and less competitive economies. 
818 

Mr. Chairman, your leadership and support are deeply appreciated by the entire 

University of Southern Mississippi community. While I can greatly appreciate the 

financial restraints facing your Subcommittee, I feel confident that further support 

of the Mississippi Polymer Institute will continue to pay dividends by way of increasing commercialization opportunities for agricultural materials in the American 

industry. Advances in polymer research are crucial to food, transportation, housing, 

and defense industries. Our work has clearly established the value of ag products 

as industrial raw materials, and we must move it from the laboratories to the industrial manufacturing sector. Only then can the United States enjoy the cleaner and 

safer environment that these technologies offer, as well as new jobs, and expanded 

opportunities for the U.S. farmer. We are most grateful for the support provided by 

you in the past. The funding you provided has facilitated laboratory work to be conducted, manufacturing scale-up to be accomplished, and ensured sales (although 

limited) of products based on this technology. However, additional funds are needed 

to make these technologies cost effective while maintaining the high performance 

standards to which we are accustomed. Pilot scale processes are necessary to move 

this technology into the market place, and will be the principal focus of our upcoming work. Of course, while working to achieve commercialization, we are committed 

to continue technology advancement, as will basic research on those topic areas 

where knowledge is required. 

Since our testimony last year, our research and development efforts have effectively shown that sustained research has expanded the viability of agricultural derivatives. Indeed, the technology is maturing, which must be followed by marketing 

and sales to realize full potential. Thus, we are asking for your support to advance 

these technologies to the market place, and to continue our development of other 

useful ag-derived technologies. We therefore respectfully request $1.5 million in 

Federal funding to more fully exploit the potential of commercializing the technologies described herein. We have shown that we can be successful, yet we need 

additional resources to optimize the potential of the knowledge creation described 

herein. Our efforts will be recognized as instrumental in developing a ‘‘process’’ for 

the commercialization of new ag-based products. We have proven that we are successful in developing technologies from the ‘‘idea’’ stage to scale-up for commercialization in several market areas. Thank you, Mr. Chairman and Members of the 

Subcommittee, for your support and consideration. 

PREPARED STATEMENT OF THE UPPER MISSISSIPPI RIVER BASIN ASSOCIATION

The Upper Mississippi River Basin Association (UMRBA) is the organization created in 1981 by the Governors of Illinois, Iowa, Minnesota, Missouri, and Wisconsin 

to serve as a forum for coordinating the five States’ river-related programs and policies and for collaborating with Federal agencies on regional water resource issues. 

As such, the UMRBA has an interest in the budget for the U.S. Department of Agriculture’s conservation programs and technical assistance. 

Of particular importance to the UMRBA is funding for the Conservation Reserve 

Program (CRP), Wetlands Reserve Program (WRP), Environmental Quality Incentives Program (EQIP), and Conservation Security Program (CSP). Taken together, 

these four programs provide an invaluable means for the USDA to work with landowners, local conservation districts, and the States to maintain agricultural productivity while protecting the nation’s soil and water resources. CRP, WRP, EQIP, and 

CSP are key non-regulatory elements in the States’ efforts to address agricultural 

sources of water quality impairment through the Total Maximum Daily Load program and can help address the national concern with hypoxia in the Gulf of Mexico. 

Conservation Reserve Program 

The UMRBA supports President Bush’s fiscal year 2008 budget request of $2 billion for the Conservation Reserve Program, a slight increase over fiscal year 2007. 

Through CRP, farmers and ranchers can voluntarily establish long term conservation practices, such as filter strips and riparian buffers, on highly erodible and environmentally sensitive cropland. 

In the UMRBA States (Illinois, Iowa, Minnesota, Missouri, and Wisconsin), total 

CRP enrollment is currently 7.1 million acres, or approximately 19 percent of the 

national CRP acreage. Yet the five States’ CRP enrollment represents 41 percent 

of the total number of CRP contracts, 40 percent of the total number of farms enrolled nationwide in the CRP, and 32 percent of the total annual CRP rental payments. CRP contracts expiring in 2007 cover 2 million acres in the five UMRBA 

States. Preliminary data indicate that 77 percent of those expiring acres will be reenrolled or extended. 
819 

All five UMRBA States also have active Conservation Reserve Enhancement Programs (CREP) tailored to meet their priority conservation needs. Current CREP enrollment in the five States is over 261,000 acres, or 28 percent of the national total. 

These rates of participation clearly demonstrate the importance of the CRP and 

CREP in the nation’s agricultural heartland and reflect the compatibility of these 

programs with agricultural productivity. 

Wetlands Reserve Program 

The President’s fiscal year 2008 budget proposes $455 million for the Wetlands 

Reserve Program, an increase of 72 percent over fiscal year 2007 spending estimates. UMRBA applauds this substantial increase and the Administration’s goal of 

enrolling 250,000 acres, bringing the total acres to WRP’s authorized program cap. 

WRP easements have proven to be important tools for restoring and protecting 

wetlands in agricultural areas. This is clearly evident from the overwhelming landowner response and the resulting improvements to water quality and habitat. From 

fiscal year 1992 through fiscal year 2006, NRCS has enrolled 2,680 contracts in Illinois, Iowa, Minnesota, Missouri, and Wisconsin totaling more than 352,000 acres, 

or 19 percent of the national total. In fiscal year 2006, $56.3 million of WRP funding 

was allocated to the five Upper Mississippi River States, representing a quarter of 

all WRP investment that year. Yet the future viability of WRP is in question as a 

result of the 2006 change in the way USDA appraises property for WRP easements. 

The new ‘‘Yellow Book’’ appraisal system has resulted in lower price-per-acre offers, 

making enrollment in WRP less attractive for many landowners and potentially 

leading to enrollment of less environmentally valuable lands. UMRBA is concerned 

that WRP target the most ecologically valuable wetland areas and thus urges Congress and USDA to evaluate the impacts of the new WRP appraisal system and take 

action to maintain the program’s future effectiveness. 

Environmental Quality Incentives Program 

In contrast to conservation programs that protect land and water resources by 

curtailing production on sensitive lands, the Environmental Quality Incentives Program (EQIP) supports conservation on working lands. Promoting agricultural production and environmental quality as compatible goals is particularly important in 

the Midwest agricultural heartland. The President is proposing to fund EQIP at $1.0 billion in fiscal year 2008, essentially unchanged from the fiscal year 2007 funding level. The UMRBA supports this 

investment, noting that EQIP is a tremendously popular conservation program in 

the 5 States of the Upper Mississippi River Basin. In fiscal year 2006, $75.7 million 

was paid for conservation practices completed in UMR States under 1997–2006 

EQIP contracts. In addition, 5700 new EQIP contracts were approved in fiscal year 

2006 in the UMR States, obligating $97 million in future financial assistance. Yet 

that same year, an additional 6700 applications, totaling $125 million, were left unfunded. 

Conservation Security Program 

The President’s fiscal year 2008 budget request of $316 million for the Conservation Security Program (CSP) reflects a 22 percent increase over fiscal year 2007 for 

this popular voluntary program, which provides financial and technical assistance 

to agricultural producers who implement conservation measures on working lands. 

However, the President’s proposed funding level will only be sufficient to continue 

to support CSP contracts signed in prior years. No new enrollments would be offered 

in 2008. Given the popularity and effectiveness of the CSP, the UMRBA urges Congress to consider increasing CSP funding beyond what the Administration has proposed to enable additional eligible acreages to benefit. 

In the first 3 years of CSP (2004–2006), 28 of the 280 eligible watersheds in the 

nation were in the 5 States of the Upper Mississippi River Basin. Within those 28 

watersheds, there are 6,139 approved CSP contracts, which constitute nearly onethird of all CSP contracts, and total $56 million in approved payments. 

In fiscal year 2007, there are 51 additional watersheds eligible for CSP nationwide, including one in each of the 5 UMRBA States. 

Conservation Technical Assistance 

Through the Conservation Technical Assistance (CTA) program, NRCS provides 

the technical capability that helps people plan and apply conservation on the land. 

NRCS works through and in partnership with conservation districts to assist individuals and groups in assessing conservation needs and planning, designing, and installing conservation practices. In addition, the CTA program assists in preparing 

landowners to participate in USDA conservation financial assistance and easement 

programs, provides emergency disaster technical assistance, and enables NRCS to 
820 

coordinate with other programs such as U.S. EPA’s nonpoint source management 

program and U.S. Fish and Wildlife Service’s Partners for Wildlife. Approximately 

$91 million in CTA funding was allocated to the five UMRBA States (Illinois, Iowa, 

Minnesota, Missouri, and Wisconsin) in fiscal year 2006. 

Given that CTA is the foundation for much of the nation’s private lands conservation assistance, UMRBA supports the President’s fiscal year 2008 funding request 

of $679 million for CTA, a 3 percent increase over the fiscal year 2007 estimated 

spending level. 

Watershed Programs 

The UMRBA is concerned that the President is proposing deep cuts to NRCS’s 

watershed programs, including total elimination of the Watershed and Flood Prevention Operations program, which funds Public Law 566 and Public Law 534 

projects. Funding for Watershed Operations has declined substantially over the past 

20 years, from an historical high of $199 million in fiscal year 1994 to only $74 million in fiscal year 2006. And yet this program provides significant local, regional, 

and national benefits, by addressing watershed protection, flood prevention, erosion 

and sediment control, water supply, water quality, water conservation, agricultural 

drought problems, rural development, municipal and industrial water needs, upstream flood damages, fish and wildlife habitat enhancement, and wetland creation 

and restoration. In September 2005 there were $1.85 billion of unfunded Federal 

commitments to Public Law 566 and Public Law 534 projects nationwide, with $208 

million of that in the States of Illinois, Iowa, Minnesota, and Missouri. Despite the 

fact that Public Law 566 and Public Law 534 projects in these 4 States were allocated 31 percent of the total national funding in fiscal year 2006, that amount 

($21.7 million) was far less than the $208 million backlog. In fiscal year 2006, although there was only $69 million allocated for watershed protection and flood prevention operations nationwide, there were funding requests totaling over $174 million, $44 million of which were in the five UMRBA States. Rather than eliminating 

this important program, UMRBA urges that it be funded at least equal to the fiscal 

year 2006 level. 

The rehabilitation of aging flood control dams must also be addressed. Of the 

11,000 Public Law 534 and Public Law 566 dams nationwide, more than 3,000 will 

reach the end of their design life by 2013. Recognizing this fact, Congress authorized 

the Watershed Rehabilitation Program in 2000 and authorized significant new funding for the program in the 2002 Farm Bill. However, that authorization expires at 

the end of fiscal year 2007. Nevertheless, the President has proposed $6 million for 

the Watershed Rehabilitation program in fiscal year 2008, targeting it exclusively 

on technical assistance. That amount is well below the recent funding levels of $30 

million and only a small fraction of the $150 million authorized for fiscal year 2007. 

Repair, upgrade, or removal of aging dams, which could become a threat to public 

health and safety, is extremely important and UMRBA thus urges Congress to reauthorize and increase funding for the Watershed Rehabilitation Program. 

PREPARED STATEMENT OF THE USA RICE FEDERATION

This is to convey the rice industry’s request for fiscal year 2008 funding for selected programs under the jurisdiction of your respective subcommittees. The USA 

Rice Federation appreciates your assistance in making this letter a part of the hearing record. 

The USA Rice Federation is the national advocate for all segments of the rice industry, conducting activities to influence government programs, developing and initiating programs to increase worldwide demand for U.S. rice, and providing other 

services to increase profitability for all industry segments. USA Rice members are 

active in all major rice-producing states: Arkansas, California, Florida, Louisiana, 

Mississippi, Missouri, and Texas. The USA Rice Producers’ Group, the USA Rice 

Council, the USA Rice Millers’ Association, and the USA Rice Merchants’ Association are members of the USA Rice Federation. 

USA Rice understands the budget constraints the subcommittees face when developing the fiscal year 2008 appropriations bill. We appreciate your past support for 

initiatives that are critical to the rice industry and look forward to working with 

you to meet the continued needs of research, food aid and market development in 

the future. 

A healthy U.S. rice industry is also dependent on the program benefits offered by 

the Farm Security and Rural Investment Act of 2002. Therefore, we oppose any attempts to modify the support levels provided by this vital legislation through more 

restrictive payment limitations or other means and encourage the subcommittees 
821 

and committees to resist such efforts during the appropriations process, in particular with the 2002 farm bill up for reauthorization this year. 

A list of the programs the USA Rice Federation supports for appropriations in fiscal year 2008 are as follows: 

FUNDING PRIORITIES

Research and APHIS 

The Dale Bumpers National Rice Research Center should receive continued fund- ing at the fiscal year 2007 approved level, which was approximately $3.9 million, 

and appropriate additional funding to reflect any increased administrative and operations costs. This center conducts research to help keep the U.S. rice industry competitive in the global marketplace by assuring high yields, superior grain quality, 

pest resistance, and stress tolerance. We urge you to provide full funding to the Dale 

Bumpers National Rice Research Center. 

In addition, we have attached information outlining the top priority research request from the USA Rice Federation: funding for aromatic rice variety research at 

the Dale Bumpers Center. The request is for $250,000 for fiscal year 2008 for research to develop high-yielding, high-quality domestic aromatic rice varieties for the 

U.S. rice industry. Further details and specifics of this request are attached in a 

separate document. 

For the Western Regional Research Center, in Albany, California, we support the 

Administration’s budget proposal for the Renewable Energy Resources within the 

Agricultural Research Service (ARS) account. The total budget request for the Renewable Energy Resources project is $10,954,000, of which, we understand, approximately $5,399,000 is to be directed to the Albany, CA facility for research on modification of plant cell walls in energy crops and crop residues for efficient conversion 

to biofuels. 

This research will play a key role in the ability to utilize rice straw and other 

rice crop residues for the production of biofuels. Rice straw represents a current and 

ready-made feedstock that could meet a substantial portion of the demand for 

biofuels production in the regions of the country where rice is produced, including 

the Sacramento Valley of California. We urge you to fully fund this request as our 

researchers work to develop the technologies necessary to meet the ambitious goals 

for biofuels production set before us. 

For APHIS-Wildlife Services, we encourage the subcommittees to fund the Lou- isiana blackbird control project at $150,000. This program annually saves rice farmers in Southwest Louisiana over $4,000 per farm, or $2.9 million total. 

Market Access 

Exports are critical to the U.S. rice industry. Historically, 40–50 percent of annual 

U.S. rice production has been shipped overseas. Thus, building healthy export demand for U.S. rice is a high priority. 

The Foreign Market Development Program (FMD) allows USA Rice to focus on 

importer, foodservice, and other non-retail promotion activities around the world. 

For fiscal year 2008, FMD should be fully funded at no less than $34.5 million. 

The Market Access Program (MAP) allows USA Rice to concentrate on consumer 

promotion and other activities for market expansion around the world. For fiscal 

year 2008, MAP should be funded at no less than $200 million. 

In addition, the Foreign Agricultural Service should be funded to the fullest degree possible to ensure adequate support for trade policy initiatives and oversight 

of export programs. These programs are critical for the economic health of the U.S. 

rice industry. 

Food Aid 

We urge the subcommittees to fund Public Law 480 Title I. No Title I funding 

was provided in fiscal year 2007. At a minimum, fiscal year 2008 funding should 

be the same as 2006, the last year in which the program was funded. Public Law 

480 Title I is our top food-aid priority and we support continued funding in order 

to meet international demand. Food-aid sales historically account for an important 

portion of U.S. rice exports. 

For Public Law 480 Title II, we support funding for fiscal year 2008 at $1.632 

billion, which is its fiscal year 2006 level. We encourage the subcommittees to fund 

Title II at a level to ensure consistent tonnage amounts for the rice industry. We 

oppose any shifting of funds, as all Title II funds have traditionally been contained 

within USDA’s budget. We believe all food-aid funds should continue to be used for 

food-aid purchases of rice and other commodities from only U.S. origin. 

USA Rice supports continued funding at fiscal year 2006 levels, at a minimum, 

for the Food for Progress Program’s Public Law 480 Title I-sourced funding and at 
822 

fiscal year 2007 levels, at a minimum, for the program’s Commodity Credit Corporation funding component. Funding for this program is important to improve food security for food-deficit nations. 

The McGovern-Dole International Food for Education and Child Nutrition Program is a proven success and it is important to provide steady, reliable funding for 

multi-year programming. USA Rice supports funding at the $140 million level for 

this education initiative because it efficiently delivers food to its targeted group, 

children, while also encouraging education, a primary stepping-stone for populations 

to improve economic conditions. 

Other 

Farm Service Agency.—We encourage the subcommittees to provide adequate 

funding so the agency can deliver essential programs and services. The Agency has 

been hard hit by staff reductions and our members fear a reduction in service if sufficient funds are not allocated. 

Please feel free to contact us if you would like further information about the programs we have listed. Additional background information is available for all of the 

programs we have referenced; however, we understand the volume of requests the 

subcommittees receive and have restricted our comments accordingly. 

Thank you for your consideration of our recommendations. 

PREPARED STATEMENT OF THE WESTERN COALITION OF ARID STATES (WESTCAS) 

The Western Coalition of Arid States (WESTCAS) is submitting this testimony to 

the Senate Appropriations Subcommittee on Agriculture regarding their hearing on 

the fiscal year 2008 U.S. Department of Agriculture budget, with specific reference 

to the 2007 Farm Bill proposals. My name is Charlie Nylander, and I represent the 

interests of WESTCAS and serve on the Board of Directors (representing the State 

of New Mexico) and as Treasurer. 

WESTCAS is a coalition of approximately 125 water and wastewater districts, 

municipalities, and professional organizations focused on water quality and quantity 

issues in eight western States, including: Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, and Texas. WESTCAS advocates wise use of water resources by promoting scientifically-sound laws, regulations, appropriations, and policies that protect public health and the environment in the arid West. My testimony 

today focuses on those aspects of the fiscal year 2008 USDA budget and the 2007 

Farm Bill proposals that impact water quality and quantity in the arid West. 

This WESTCAS testimony will focus on two areas of importance to our membership, i.e. the conservation programs and the rural development programs. First, the 

Administration proposes to provide approximately 547,000 rural households with 

new and improved water and wastewater disposal facilities. The proposed $1.5 billion funding level includes $1.2 billion in loans and $349 million in grants. This 

combination of funding represents a higher loan to grant ratio than exists in 2007, 

according to the budget proposal. However, USDA is proposing to reduce the interest rate on loans, and state that most rural communities would have lower repayment costs as a result of the combination of these changes. Although WESTCAS 

would like to see a significant increase in the proposed funding for this program, 

given the current national budget demands, we support the proposed funding level 

and the approach taken with respect to loans and grants. 

The water and wastewater disposal program provides financing for rural communities to establish, expand or modernize water treatment and waste disposal facilities. Eligibility if limited to communities of 10,000 or less in population which are 

unable to obtain credit elsewhere. In addition, they are available only to those communities with low median household income levels. The eight WESTCAS member 

western states contain hundreds of communities that meet these criteria. Moreover, 

due to the evolving demographics of the western United States, many of our rural 

communities are either seeing an influx of new residents who are moving to the 

area in their retirement, or are seeing a reduction in population due to a weakened 

economic picture and the lack of reasonable employment opportunities. In either 

case, the physical and financial impact on existing, aged, or needed water and 

wastewater infrastructure is demonstrable. These rural communities cannot cope 

with the maintenance or new development of adequate water and wastewater infrastructure without programs such as proposed in this fiscal year 2008 USDA budget 

request. 

I would like to provide an example in my own State of New Mexico. I currently 

facilitate the Espan ̃ ola Basin Regional Planning Issues Forum (EBRPIF). This 

forum represents a government-to-government ad hoc group of 14 members rep-
823 

resenting city, county, and tribal jurisdictions in Northern New Mexico. For the past 

three years, this forum has met monthly to candidly discuss planning issues of regional concern, with a focus on water and wastewater. The three county governments represented among the 14 members contain rural communities that have 

populations of less than 10,000 people. Many of those communities are increasingly 

financially-burdened by water and wastewater infrastructure needs that result from: 

aged, existing infrastructure; population growth that demands new utility services; 

local groundwater contamination issues resulting from the existing use of on-site individual liquid waste systems and historic use of cesspools (that are now illegal); 

inadequate operation and maintenance; declining groundwater levels in over-drafted 

aquifers; the effects of a 7∂ year drought; naturally-occurring groundwater contaminants that exceed new, and increasingly stringent drinking water standards, e.g. the 

U.S. Environmental Protection Agency’s standard for arsenic; and challenging new 

concerns for utility safeguards and security measures. All of these very typical factors exacerbate the financial, planning, maintenance, and development demands affecting these small, rural communities, who without the availability of government 

program support, like the USDA Rural Development Program, would have no place 

to turn. 

According to the Administrations proposal, these grants are limited to a maximum 

of 75 percent of project costs, but have typically averaged 35 to 45 percent of project 

costs. Program regulations stipulate that the grant amount should only be as much 

as necessary to bring the user rates down to a reasonable level for the area. Water 

and wastewater grant and loan funds are usually combined, based on the income 

levels of users and user costs. Throughout the WESTCAS western states, when it 

comes to financing water and wastewater infrastructure, all of the rural communities are increasing user rates, while still needing to augment funding through federal and state financing programs. Thus, WESTCAS strongly supports the continuation the USDA Rural Development Program. 

The second area of concern to WESTCAS, funding and technical assistance to support the Farm Bill conservation programs is vital to the management of water resources in the arid West. The Administration’s proposal includes about $4 billion for 

these programs, an increase of $242 million over the 2007 level. This includes funding for the Conservation Security Program at a level of $316 million, and increase 

of $57 million over 2007, in order to support prior year contracts. The budget also 

includes $455 million to enroll up to 250,000 acres in the Wetlands Reserve Program in 2008 to reach the program cap of 2,275,000 acres. In addition, the proposed 

budget includes $1 billion for the Environmental Quality Incentives Program 

(EQIP), enabling nearly 39,700 producers to participate in the program, covering 

nearly 21 million acres of land. The EQIP program will continue to emphasize land 

management practices. 

WESTCAS strongly supports the proposed conservation programs, however we 

have the following comments. 

—The Conservation Security Program pays farmers for improving soil and water 

quality or enhancing wildlife habitat. Some voices in Congress have recently advocated also using these funds to promote the planting of energy crops. 

WESTCAS supports this program because it has a fundamental connection to 

water quality and quantity. By wisely managing the land, this USDA program 

has a very positive affect on non-point sources of water pollution. Sediment and 

nutrients are less likely to runoff and end up in the surface waters where they 

contribute to water pollution. In addition, this program can enhance the ability 

of soils to hold moisture and reduce the demands for irrigation water from surface or groundwater sources. Enhancing wildlife habitat is also a vital benefit, 

especially in those areas of the country, like the western states, where growth 

and development are increasingly marginalizing wildlife habitat. Additionally, 

if one examines other federal agency budgets, (like the Fish and Wildlife Service’s fiscal year 2008 proposed budget where grants are being eliminated that 

help landowners restore habitat for species on their land), there are proposed 

cuts in funding for wildlife habitat. Thus, the USDA program funding is of vital 

importance. 

WESTCAS supports increased appropriations for the Conservation Security 

Program, but does not want it be closed to new subscribers, as Secretary 

Johanns has recently proposed. Across the western states, many new opportunities exist to improve soil and water quality and enhance wildlife habitat. Rather 

than cap the program to allow funding to present subscribers, WESTCAS believes that it should be expanded, and that USDA should implement a monitoring and reporting program to quantify, to the best of their ability, the benefits derived from the program’s implementation. A comprehensive monitoring 

program could be networked with other agencies such as the U.S. Geological 
824 

Survey, Bureau of Land Management, and Environmental Protection Agency, so 

as to more efficiently collect and quantify the data. Such monitoring and reporting would greatly impact the continuation and expansion of this important program, and help assess the positive benefits being derived for water quality. 

Regarding the proposal to use these funds for the planting of energy crops, 

WESTCAS offers one caution. That caution concerns the impact of extensive 

new energy crop plantings on both water quantity and quality. By promoting 

the planting of energy crops, the USDA (or Congress) may be exacerbating the 

problems associated with nutrient-caused eutrophication of water resources due 

to seepage and/or runoff of applied crop nutrients that affect water quality. But 

more importantly, promotion of such planting may negatively impact the increasing strain on scarce water resources in the arid western states through the 

promotion of irrigated agriculture to produce energy. By promoting planting of 

energy crops, there is a promotion of irrigation which may have deleterious affects on both surface and groundwater resources in the arid West. Historically, 

USDA price supports for cotton, resulted in increased planting that resulted in 

excessive water level declines in important aquifers, such as the Ogalalla aquifer. Thus, prudent caution should be given when including such proposals in the 

program due to inadvertent consequences. 

—The Wetlands Reserve Program proposal for increased funding and maximizing 

the subscription acreage is heartily supported by WESTCAS. Although the arid 

West has minimal acres of wetlands, as a water quality organization WESTCAS 

recognizes the natural benefits of increased wetlands promoting water quality 

and wildlife. Wetlands are natural systems that greatly contribute to the promotion of water quality, and aid in providing buffer zones for riparian vegetation that mitigate the affects of runoff events and flood flows. In the arid West, 

the use of artificial wetlands is utilized more and more in the treatment and 

reclamation of wastewater effluent. The natural purification processes that take 

place in a wetland environment greatly benefit water quality, and this USDA 

program is of great national import regarding the protection of water quality 

and provision of wildlife habitat. 

—WESTCAS strongly supports the Environmental Quality Incentive Program 

(EQIP). This program is very important in providing assistance to landowners 

that face serious natural resource challenges that impact soil, water, and related natural resources. As was mentioned above regarding the Conservation 

Security Program, EQIP provides resources for those stewards of the land that 

are in need so as to enhance the natural resources. The EQIP financial resources improve water quality and quantity through the subscriber application 

of sound remedial projects that improve both land and water. 

—Lastly, WESTCAS supports the premise of the Healthy Forest Initiative in reducing the risk of catastrophic wildfires. It is very important that the USDA 

continue to implement this initiative, and reduce the risk of wildfire. Through 

hazardous fuel treatment, provision of adequate fire preparedness, and providing technical assistance, the USDA is assisting the arid West in safeguarding our vulnerable forested watersheds that provide the source of water 

for our cities, towns, industries, ranches and farms. During the past 7 years of 

sustained drought conditions, the arid West has felt the impact of catastrophic 

wildfire from California, across Arizona, through New Mexico and Colorado. 

Wildfires can destroy the vital watersheds upon which our populations depend 

for their annual and long-term supply of water. WESTCAS urges your support 

for the proposed budget for this important program. 

On behalf of WESTCAS, thank you for this opportunity to provide this testimony. 

PREPARED STATEMENT OF THE SOCIETY FOR WOMEN’S HEALTH RESEARCH AND THE

WOMEN’S HEALTH RESEARCH COALITION

On the behalf of the Society for Women’s Health Research and the Women’s 

Health Research Coalition, we are pleased to submit testimony in support of increased funding for the Food and Drug Administration, and more specifically for the 

Office of Women’s Health, a critical focal point within the Agency on women’s 

health. 

The Society is the only national non-profit women’s health organization whose 

mission is to improve the health of women through research, education, and advocacy. Founded in 1990, the Society brought to national attention the need for the 

appropriate inclusion of women in major medical research studies and the need for 

more information about conditions affecting women disproportionately, predominately, or differently than men. 
825 

The Coalition was created by the Society in 1999 to give a voice to scientists and 

researchers from across the country that are concerned and committed to improving 

women’s health research. The Coalition now has more than 650 members, including 

leaders within the scientific community and medical researchers from many of the 

country’s leading universities and medical centers, directors from various Centers 

of Excellence on Women’s Health as well as leading voluntary health associations, 

and pharmaceutical and biotechnology companies. 

The Society and the Coalition are committed to advancing the health status of 

women through the discovery of new and useful scientific knowledge. We strongly 

believe that appropriate funding of the FDA by Congress is absolutely critical for 

the Agency to be able to maintain basic functions and to assure the American public 

of the safety of our food and drugs. More specifically, we recommend that Congress 

not only sustain but should increase funding for the Office of Women’s Health and 

its women’s health research programs. These programs, often conducted with the 

Agency centers, are necessary if we are to maintain any focus on women’s health 

within the Agency Furthermore, these programs are critical to improve care and increase awareness of disease specific impacts to women such as those associated with 

differences in the efficacy of drugs, devices and diagnostics, as a function of sex. 

Therefore, we strongly urge Congress to support a robust increase for fiscal year 

2008 budget for the FDA, and within that budget to provide the Office of Women’s 

Health funding of $5 million such that it may meet and exceed its program goals. 

OFFICE OF WOMEN’S HEALTH

The Office of Women’s Health (OWH) at the FDA, established in 1994, plays a 

critical role in women’s health, both within and outside the Agency, supporting sexand gender-based research, areas in which the Society has long been a proponent. 

OWH aims to provide scientific and policy expertise on sex and gender sensitive regulatory and oversight issues; to correct gender disparities in the areas for which the 

FDA is responsible—drugs, devices, and biologics; and to monitor women’s health 

priorities, providing both leadership and an integrated approach across the agency. 

Despite inadequate funding, OWH provides all women with invaluable tools for 

their health. 

With little difficulty, OWH exhausts its tiny budget each year. For the past five 

years, OWH has been provided a flat budget of $4 million, which is, in essence, a 

decrease due to required Federal cost of living adjustments, benefit cost increases 

and other related issues. Despite this squeeze, the office has managed to advance 

its mission both within the Agency and externally through it research grants, drug 

and disease pamphlets and outreach programs. OWH’s pamphlets are the most requested of any documents at the government printing facility in New Mexico. (More 

than 3.5 million pieces are distributed to women across the Nation including target 

populations such as Hispanic communities, seniors and low income citizens.) Yet despite these successes, the OWH was targeted to have its fiscal year 2007 programs 

budget raided by $1.2 million, virtually shutting down the ability of this office to 

function for the rest of the year. Thankfully, this decision was reversed at the very 

last minute. 

Despite clear funding intentions within the Administration’s proposal for fiscal 

year 2008 for OWH to receive $4million, the FDA has indicated that it will be cutting the budget of OWH by $350,000 from the OMB designated amount of $4 million. These two actions (fiscal year 2007 and fiscal year 2008) taken together cause 

us great concern and set a precedent that leads us to believe the office’s 

functionality is in serious jeopardy. 

IT IS ABSOLUTELY CRITICAL FOR CONGRESS TO TAKE ACTION NOW TO HELP PRESERVE

THE VITAL FUNCTIONS OF OWH

Since its beginning, OWH has funded high quality scientific research to serve as 

the foundation for Agency activities that improve women’s health. To date, OWH 

has funded over 100 research projects with approximately $15.2 million. Intramural 

grants support projects within the FDA that address knowledge gaps or set new directions for sex and gender research. Extramural contracts leverage a wealth of expertise and other resources outside the Agency to provide insight on regulatory 

questions pertinent to women’ health. All contracts and grants are awarded through 

a competitive process. A large number of these studies are published, many of which 

appear in peer reviewed journals. 

OWH has recently funded research to more fully understand heart disease in 

women. Despite being the number one cause of death, women with heart disease 

face misdiagnosis, delayed diagnosis, under-treatment, and mistreatment due to 

their under-representation in heart-related research studies. Extramural research 
826 

funded by OWH is looking into the use of coronary stents in women and problems 

associated with breast interference in interpretation of heart catherization studies. 

As part of its educational outreach efforts to consumers, OWH continues to work 

closely with women’s advocacy and health professional organizations to provide clarity on the results of the Women’s Health Initiative. Due to OWH efforts, an informational fact sheet about menopause and hormones and a purse-sized questionnaire 

to review with the doctor were distributed to national and local print, radio, and 

Internet advertisements. OWH’s website received over three million hits to 

download campaign materials. This website provides free, downloadable fact sheets 

on over 40 different illnesses, diseases, and health related issues. 

In addition, OWH has recently completed medication chart brochures on seven 

chronic diseases. These are unique within the Agency. These charts list, in one 

place, all the medications that are prescribed and available for each disease. Again, 

the information is available on the website and is ideal for women to use in talking 

to their doctors, pharmacists or nurses about their treatment options. 

As a result of FDA information system aging, combined with the inability to keep 

pace with information technology needs due to budget constraints, the OWH has 

been unable to conduct much needed data analysis on women’s health and sex-related differences. This effort originally started in 2001, when the Society submitted 

testimony on behalf of the OWH in support of a centralized FDA database to coordinate clinical trial oversight, monitor the inclusion of women in clinical trials, oversee the parameters of informed consent, and identify health provider training needs. 

As a result of Society efforts and this Committee’s commitment, in 2002 Congress 

provided the OWH with funds to develop an agency-wide database focused on women’s health activities to include demographic data on clinical trials. OWH did begin 

developing this database, now known as the ‘‘Demographic Information and Data 

Repository’’, to review clinical studies, enhance product labeling, identify knowledge 

gaps, and coordinate data collection. However, without the ability to match this capability to the rest of the Agency efforts developing this important Repository have 

been halted at the present time. 

While progress has been made, the database is far from up and running due to 

the aging and outdated information technology systems of the Agency. Currently, 

the FDA receives large volumes of information in applications from drug manufacturers for review and evaluation. The FDA reviewers must manually comb through 

the submitted drug trial reports and digital data in as many as twelve formats to 

evaluate a new drug’s safety and effectiveness. With no uniform system or database, 

reviewers must handpick sex, age, and ethnicity information manually from stacks 

of paper reports and craft their own data comparisons. This is time consuming, 

makes the review process less efficient, is error-prone and delays access to important information. Scientific and medical advances are occurring rapidly and the public needs and deserves access to the most recent and accurate information regarding 

their health. Therefore, in order to fully capitalize on the potential of the data warehouse and the resulting wealth of information, we urge Congress to commit $1 million to OWH for the Demographic Information and Data Repository. It is time for 

us all to recognize that the Agency must utilize up to date information technology 

and sorely needs the resources to maintain them. 

Scientists have long known of the anatomical differences between men and 

women, but only within the past decade have they begun to uncover significant biological and physiological differences. Sex differences have been found everywhere 

from the composition of bone matter and the experience of pain, to the metabolism 

of certain drugs and the rate of neurotransmitter synthesis in the brain. Sex-based 

biology, the study of biological and physiological differences between men and 

women, has revolutionized the way that the scientific community views the sexes, 

with even more information forthcoming as a result of the sequencing of the X chromosome. The evidence is overwhelming, and as researchers continue to find more 

and complex biological differences, they are gaining a greater understanding of the 

biological and physiological composition of both sexes. 

Much of what is known about sex differences is the result of observational studies, 

or is descriptive evidence from studies that were not designed to obtain a careful 

comparison between females and males. The Society has long recognized that the 

inclusion of women in study populations by itself was insufficient to address the inequities in our knowledge of human biology and medicine, and that only by the careful study of sex differences at all levels, from genes to behavior, would science 

achieve the goal of optimal health care for both men and women. Many sex differences are already present at birth, whereas others develop later in life. These differences play an important role in disease susceptibility, prevalence, time of onset 

and severity and are evident in cancer, obesity, coronary heart disease, immune dysfunction, mental health disorders, and other illnesses. Physiological and hormonal 
827 

fluctuations may also play a role in the rate of drug metabolism and effectiveness 

of response in females and males. This research must be supported and encouraged. 

Building upon sex differences research, the Society encourages the establishment 

of drug-labeling requirements that ensure labels include language about differences 

experienced by women and men. Further, we advocate for research on the comparative effectiveness of drugs with specific emphasis on data analysis by sex. When 

available, this information should be on labels. 

Our country’s drug development process has succeeded in developing new and better medications to ensure the health of both women and men. However, there is no 

requirement that the data acquired during research of a new drug’s safety and effectiveness be analyzed as a function of sex or that information about the ways drugs 

may differ in various populations (e.g., women requiring a lower dosage because of 

different rates of absorption or chemical breakdown) be included in prescription 

drug labels and other patient educational and instructional materials. 

Proper drug labeling is not always the complete solution. If the drug is not one 

newly approved or if the sex-specific information is detected only in post-marketing 

studies, the drug label will not reflect sex specific information discovered to the prescribing physician, and it may be difficult to get new information incorporated into 

physicians’ prescribing habits. 

The Society believes the opportunity is now before us to communicate sex differences data discovered from clinical trials to the medical community and to consumers through drug labeling and packaging inserts and other forms of alerts. As 

part of advancing the need to analyze and report sex differences, the Society encourages the FDA to continue adequately addressing the need for accurate drug labeling 

to identify important sex and gender differences, as well as to ensure that appropriate data analysis of post-market surveillance reporting for these differences is 

placed in the hands of physicians and ultimately the patient. 

In conclusion, Mr. Chairman, we thank you and this Committee for its strong 

record of support for women’s health and your commitment to OWH. We encourage 

you to provide it with funding of $5 million for fiscal year 2008 and to provide the 

FDA with a significant increase over the fiscal year 2007 budget to address its urgent needs and chronic shortfalls. We look forward to continuing to work with you 

to build a healthier future for all Americans. 

(i) 

LIST OF WITNESSES, COMMUNICATIONS, AND 

PREPARED STATEMENTS 

Page 

Ad Hoc Coalition, Prepared Statement of .............................................................. 721 

Advanced Medical Technology Association, Prepared Statement of ................... 724 

American: 

Forest & Paper Association, Prepared Statement of ..................................... 726 

Honey Producers Association, Inc., Prepared Statement of .......................... 727 

Sheep Industry Association, Prepared Statement of ..................................... 733 

Society for Microbiology, Prepared Statements of..................................... 738, 741 

Animal: 

Health Institute, Prepared Statement of ........................................................ 745 

Welfare Institute, Prepared Statement of ...................................................... 745 

Bennett, Senator Robert F., U.S. Senator From Utah: 

Questions Submitted by............................................................................... 136, 708 

Statement of ...................................................................................................... 2 

Bond, Senator Christopher S., U.S. Senator From Missouri, Questions Submitted by ............................................................................................................... 156 

Brownback, Senator Sam, U.S. Senator From Kansas, Questions Submitted 

by ........................................................................................................................... 476 

Byrd, Senator Robert C., U.S. Senator From West Virginia, Questions Submitted by ............................................................................................................... 153 

California Industry and Government Central California Ozone Study Coalition, Prepared Statement of ................................................................................ 746 

Christopherson, Charles R., Jr., Chief Financial Officer, Office of the Chief 

Financial Officer, Department of Agriculture, Prepared Statement of ........... 24 

Coalition on Funding Agricultural Research Missions, Prepared Statement 

of ............................................................................................................................ 747 

Cochran, Senator Thad, U.S. Senator From Mississippi, Prepared Statement 

of ............................................................................................................................ 6 

Colorado River: 

Basin Salinity Control Forum, Prepared Statement of ................................. 749 

Board of California, Prepared Statement of ................................................... 752 

Collins, Dr. Keith, Chief Economist, Office of the Secretary, Department 

of Agriculture ........................................................................................................ 1 

Prepared Statement of ..................................................................................... 31 

Combs, David M., Chief Information Officer, Department of Agriculture, Prepared Statement of ............................................................................................... 20 

Conner, Charles, Deputy Secretary, Office of the Secretary, Department of 

Agriculture ............................................................................................................ 1 

Dorgan, Senator Byron L., U.S. Senator From North Dakota: 

Questions Submitted by............................................................................... 123, 701 

Statement of ...................................................................................................... 3 

Durbin, Senator Richard J., U.S. Senator From Illinois, Questions Submitted 

by....................................................................................................................... 123, 705 

Dyer, John, Deputy Commissioner for Operations, Food and Drug Administration, Department of Health and Human Services ............................................. 479 

Feinstein, Senator Dianne, U.S. Senator From California, Statement of ........... 5 

Florida State University, Prepared Statement of ................................................. 753 

Fong, Phyllis K., Inspector General, Office of the Inspector General, Department of Agriculture, Prepared Statement of ..................................................... 45 

Food and Water Watch, Prepared Statement of ................................................... 754 
Page

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Friends of Agricultural Research—Beltsville, Prepared Statement of ................ 757 

Hardwood Federation, Prepared Statement of ...................................................... 760 

Harkin, Senator Tom, U.S. Senator From Iowa, Questions Submitted by ......... 694 

Heart Rhythm Society, Prepared Statement of ..................................................... 761 

Imperial Valley Conservation Research Center Committee, Prepared Statement of .................................................................................................................. 763 

Johanns, Hon. Mike, Secretary, Office of the Secretary, Department of Agriculture ................................................................................................................... 1 

Prepared Statement of ..................................................................................... 10 

Statement of ...................................................................................................... 7 

Kohl, Senator Herb, U.S. Senator From Wisconsin: 

Opening Statement of ...................................................................................... 1 

Questions Submitted by................................................................................. 84, 492 

McKay, Margo M., Assistant Secretary for Civil Rights, Office of the Assistant 

Secretary for Civil Rights, Department of Agriculture, Prepared Statement 

of ............................................................................................................................ 28 

Multi-Crop Aflatoxin Working Group, Prepared Statement of ............................ 765 

National: 

Association of State: 

Departments of Agriculture, Prepared Statement of ............................. 760 

Foresters, Prepared Statement of ............................................................ 760 

Coalition for Food and Agricultural Research, Prepared Statement of ....... 766 

Commodity Supplemental Food Program Association, Prepared Statement 

of ..................................................................................................................... 772 

Corn Growers Association, Prepared Statement of ....................................... 770 

Environmental Services Center (NESC), Prepared Statement of ................ 778 

Fish and Wildlife Foundation, Prepared Statement of ................................. 779 

Potato Council, Prepared Statement of .......................................................... 782 

Rural Telecom Association, Prepared Statement of ...................................... 784 

Turfgrass Federation, Inc., Prepared Statement of ....................................... 786 

Nelson, Senator Ben, U.S. Senator From Tennessee: 

Questions Submitted by ................................................................................... 126 

Statement of ...................................................................................................... 5 

New Mexico Interstate Stream Commission, Prepared Statement of ................. 790 

Organization for the Promotion and Advancement of Small Telecommunications Companies, Prepared Statement of ....................................................... 792 

Pellett, Nancy C., Chairman and Chief Executive Officer, Farm Credit Administration, Prepared Statement of ........................................................................ 59 

Pickle Packers International, Inc., Prepared Statement of .................................. 793 

Red River Valley Association, Prepared Statement of .......................................... 798 

Reed, Senator Jack, U.S. Senator From Rhode Island: 

Questions Submitted by............................................................................... 135, 707 

Statement of ...................................................................................................... 5 

Rutherford, Boyd K., Assistant Secretary for Administration, Department 

of Administration, Department of Agriculture, Prepared Statement of .......... 18 

Society: 

For: 

Animal Protective Legislation, Prepared Statement of .......................... 802 

Women’s Health Research and the Women’s Health Research Coalition, Prepared Statement of .................................................................. 824 

Of American Foresters, Prepared Statement of ............................................. 760 

Specter, Senator Arlen, U.S. Senator From Pennsylvania, Questions Submitted by .......................................................................................................... 154, 718 

Steele, W. Scott, Budget Officer, Office of the Secretary, Department of Agriculture ................................................................................................................... 1 

Teuber, Terri, Director, Office of Communications, Department of Agriculture, 

Prepared Statement of ......................................................................................... 30 

The Humane Society, Prepared Statement of ....................................................... 806 

The Nature Conservancy, Prepared Statement of ................................................ 760 
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The Wildlife Society, Prepared Statement of ........................................................ 810 

Turman, Richard, Deputy Assistant Secretary for Budget, Food and Drug 

Administration, Department of Health and Human Services .......................... 479 

United States Telecom Association, Prepared Statement of ................................ 811 

University of Southern Mississippi and the Mississippi Polymer Institute, 

Prepared Statement of ......................................................................................... 815 

Upper Mississippi River Basin Association, Prepared Statement of ................... 818 

USA Rice Federation, Prepared Statement of ....................................................... 820 

Western Coalition of Arid States (WESTCAS), Prepared Statement of .............. 822 

von Eschenbach, Hon. Andrew, Commissioner, Food and Drug Administration, Department of Health and Human Services ............................................. 479 

Prepared Statement of ..................................................................................... 481 

(v) 

SUBJECT INDEX 

DEPARTMENT OF AGRICULTURE 

Page 

Additional Committee Questions ............................................................................ 83 

Administrative: 

Costs for Earmarks .......................................................................................... 73 

Expenses for Earmarks .................................................................................... 71 

Afghanistan/Iraq Provincial Reconstruction Activities ......................................... 85 

Agricultural: 

Credit Insurance Fund ..................................................................................... 475 

Disaster Assistance .......................................................................................... 138 

Marketing Service ........................................................................................ 105, 120 

Quarantine Inspection: 

Fees ............................................................................................................ 77 

Positions Transferred to DHS .................................................................. 77 

Reconstruction Activities ................................................................................. 103 

Research ............................................................................................................ 87 

Service, Buildings and Facilities ..................................................................... 149 

Agriculture: 

Buildings and Facilities and Rental Payments .............................................. 19 

Quarantine and Inspection .............................................................................. 121 

APHIS: 

Cooperative Agreements .................................................................................. 107 

Program Cost Share ......................................................................................... 147 

Appropriate Technology Transfer for Rural Areas ............................................... 122 

ARS Research Funding ........................................................................................... 123 

Avian Flu ................................................................................................................. 63, 88

Broadband and Distance Learning and Telemedicine Funding ........................... 124 

BSE Surveillance ..................................................................................................... 126 

Capital Security Cost Sharing Program ................................................................ 102 

Center for Nutrition Policy and Promotion ........................................................... 110 

Chronic Wasting Disease/State Match ................................................................... 90 

Commodity Supplemental Food Program........................................ 79, 109, 129, 154 

Elimination ....................................................................................................... 144 

Common Computing Environment ......................................................................... 108 

And Information Technology ........................................................................... 86 

Community Facilities Grants ................................................................................. 96 

Conservation: 

Contingency Funding ....................................................................................... 82 

Operations ......................................................................................................... 104 

Program ............................................................................................................. 125 

Security Program .............................................................................................. 122 

Corporate Activities ................................................................................................. 61 

Country of Origin Labeling .................................................................................... 69, 93 

Crop: 

Insurance ........................................................................................................... 122 

Gap Coverage ............................................................................................. 82 

Cross-Cutting Trade Negotiations and Biotechnology Resources ........................ 148 

DA Direct .................................................................................................................. 19 

DHS: 

Agricultural Inspections at U.S. Borders ....................................................... 75 

AQI Inspectors .................................................................................................. 81 

Disaster: 

Aid ...................................................................................................................... 67 

Assistance .......................................................................................................... 126 
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vi 

E. Coli in Specialty Crops ....................................................................................... 78 

Electronic Government ............................................................................................ 23 

Emerald Ash Borer .................................................................................................. 64 

Emerging Pests...................................................................................................... 88, 106 

Enterprise Architecture (EA) and IT Management Programs ............................. 23 

Eradication Versus Management ........................................................................... 89 

Examination Programs for FCS Banks and Associations .................................... 60 

Farm Program Staffing ........................................................................................... 475 

Farm Service Agency (FSA) .................................................................................... 154 

Computer System ............................................................................................. 65 

Field Staff and Office Structure ...................................................................... 102 

Financial Management System.......................................................................... 102, 141 

Financing New Electric Generation Facilities ...................................................... 99 

Fiscal Year 2008: 

Budget Request ......................................................................................... 29, 31, 36 

Key Outcomes ................................................................................................... 29 

Objectives.......................................................................................................... 18, 29 

Request .............................................................................................................. 19 

Food: 

Aid ...................................................................................................................... 81 

Stamp Program Legislative Proposals ............................................................ 110 

Food Safety and Inspection Service ....................................................................... 111 

Food Inspectors ................................................................................................. 116 

Funding ............................................................................................................. 142 

Level ........................................................................................................... 62 

IT Infrastructure .............................................................................................. 155 

Research ............................................................................................................ 152 

Risk Based Inspection ...................................................................................... 113 

Fresh Fruit and Vegetable Program in Schools .................................................... 123 

Genetically Modified Materials in Commercial Crops ....................................... 93, 120 

Global Warming ....................................................................................................... 94 

Greenbook Charges .................................................................................................. 140 

Hazardous Materials Management ........................................................................ 20 

Information: 

Security ............................................................................................................. 22 

Technology (IT) Issues ..................................................................................... 101 

International Trade ................................................................................................. 66 

Invasive Species..................................................................................................... 89, 119 

Johne’s Disease ........................................................................................................ 90 

Loan Program Delinquency Rates .......................................................................... 156 

Locally Produced Food to Schools ........................................................................... 74 

Multi-Family Housing: 

Revitalization .................................................................................................... 98 

Vouchers ............................................................................................................ 98 

Mutual and Self-Help Housing ............................................................................... 97 

National: 

Animal: 

Health Laboratory Network Funding ...................................................... 123 

Identification System............................................................... 67, 91, 118 143 

Information Technology Data Center (NITC) Hosting .................................. 22 

Organic Certification Cost Share Program .................................................... 106 

Veterinarian Medical Service Act ................................................. 70, 87, 122, 476 

Natural Resources Conservation Service ............................................................... 153 

Technical Assistance Funding ......................................................................... 126 

Number of AQI Inspectors ...................................................................................... 77 

Office: 

Consolidations ................................................................................................... 96 

Of the Secretary, Provincial Reconstruction Teams ...................................... 149 

OIG’s Fiscal Year 2008 Budget Request ................................................................ 58 

Organic Farming ...................................................................................................... 80 

Progress Implementing Local Food Purchase Provision ....................................... 135 

Proposed Limit on WIC Administrative Funding ................................................. 109 

Protecting and Improving the Integrity of USDA Programs ............................... 49 

Provincial Reconstruction Teams (PRTs) ............................................................... 73 

Public Law 480 Titles I and II and Food for Progress ......................................... 103 

Regulatory Activity .................................................................................................. 61 

Renewable Energy—Commodity Prices ................................................................. 138 

Rental Assistance .................................................................................................... 136 
Page

vii 

Research, Education, and Economics Reorganization .......................................... 146 

Resource Conservation and Development .............................................................. 105 

Risk: 

Based Inspection ............................................................................................... 142 

Management Agency...................................................................................... 94, 118 

Crop Insurance User Fee .......................................................................... 137 

Rural: 

Business Development Grants ........................................................................ 99 

Development ..................................................................................................... 154 

Direct Loans ............................................................................................... 137 

Guaranteed Lending ................................................................................. 128 

Housing Programs ..................................................................................... 125 

Rental Housing ................................................................................................. 97 

Safety, Security, and Public Health ....................................................................... 45 

Service Center Modernization Initiative—(SCMI) ................................................ 21 

Single Family Housing Loan Programs ................................................................. 95 

Small Farm/Organics/AMS Seed Mislabeling ....................................................... 91 

Telecommunications ................................................................................................ 22 

The Management of USDA’s Public Resources ..................................................... 55 

2008 Budget Request for Public Law 480 Title II Donations .............................. 82 

U.S.: 

Agricultural Trade ............................................................................................ 130 

Foreign Food Assistance .................................................................................. 121 

USDA: 

Fiscal Year 2008 Information Technology Investment Summary ................ 20 

Loan Guarantee Authority ............................................................................... 69 

Overseas Activities ........................................................................................... 150 

Renewable Energy and Biofuels Investment .................................................. 127 

User Fee Proposals .................................................................................................. 140 

Value-Added Grants.............................................................................................. 95, 120 

Veal ........................................................................................................................... 84 

Water and Waste Program ..................................................................................... 100 

WIC: 

Food Package .................................................................................................... 146 

Legislative Proposals ........................................................................................ 144 

Management Information System Funding ................................................... 145 

$200 Million Contingency Fund ...................................................................... 145 

DEPARTMENT OF HEALTH AND HUMAN SERVICES 

FOOD AND DRUG ADMINISTRATION

Additional Committee Questions ............................................................................ 492 

Adverse Event Reporting on Dietary Supplements .............................................. 694 

Advisory Committees ............................................................................................... 706 

AERS II .................................................................................................................... 497

Biologic License Application Approvals ................................................................. 717 

Carbon Monoxide ..................................................................................................... 692 

Color Certification Fees ........................................................................................... 694 

Counterfeit Drugs .................................................................................................... 708 

Department of Health and Human Services ......................................................... 492 

Dietary Supplements ............................................................................................... 705 

Direct to Consumer Advertising......................................................................... 691, 701 

Drug Importation ..................................................................................................... 702 

FDA: 

Alliance Request for FDA Funding ................................................................. 710 

Pay Costs ........................................................................................................... 709 

Follow-on Biologics .................................................................................................. 718 

Food Safety .......................................................................................................... 493, 706 

Inspections.................................................................................................... 485, 696 

Generic Drugs .......................................................................................................... 494 

Review Fiscal 2007 Funding ............................................................................ 710 

Good Manufacturing Practices of Dietary Supplements ...................................... 695 

Import Inspection .................................................................................................... 495 

Medical Device User Fee and Modernization Act (MDUFMA) ............................ 713 

Office of: 

Cosmetics and Colors ....................................................................................... 693 

The Commissioner ............................................................................................ 693 
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viii 

Office of—Continued 

Women’s Health ................................................................................................ 689 

ORA Consolidation .................................................................................................. 718 

Overall Funding ....................................................................................................... 492 

Pandemic Flu....................................................................................................... 486, 711 

Pay Costs .................................................................................................................. 687

Pending Approval of Cefquinome ........................................................................... 703 

Probiotics in Yogurt ................................................................................................. 692 

Proposed: 

Generic Drug User Fee .................................................................................... 710 

Re-Inspection User Fee .................................................................................... 710 

User Fees .......................................................................................................... 686 

Pseudoephedrine ...................................................................................................... 694 

Rent ........................................................................................................................... 687 

Research Reduction............................................................................................. 688, 713 

Salt ............................................................................................................................ 698 

Sunscreen Monographs....................................................................................... 489, 707 

Tobacco ..................................................................................................................... 489 

Trans Fat .................................................................................................................. 700

User Fees .................................................................................................................. 490

Reauthorization ................................................................................................ 711 

White Oak ................................................................................................................ 688 

Women’s Health................................................................................................... 487, 488 

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