HAZUS®

-MH 

Estimated Annualized 

Earthquake Losses for the 

United States 

FEMA 366 / April 2008

FEMA
FEMA HAZUS-MH PROGRAM

The work that provided the basis for this publication was supported by funding from the Federal 

Emergency Management Agency (FEMA) under a contract with the National Institute of Building 

Sciences (NIBS). The substance and findings of that work are dedicated to the public. NIBS is 

responsible for managerial support and the services of the Earthquake Committee for reviewing 

drafts, and PBS&J for conducting the HAZUS-MH analyses. Individual copies or bulk rate orders 

of this report are available through the FEMA Distribution Center at 1-800-480-2520. 

For information contact: 

Eric Berman

HAZUS Program Manager

FEMA 

500 C Street, SW 

Washington, DC 20472

Fax: 202-646-2787 

E-mail: eric.berman@dhs.gov

Website: http://www.fema.gov/plan/prevent/hazus

About the Cover

On October 17, 1989, at 5:04:15 p.m. (PDT), a magnitude 6.9 earthquake severely shook 

the San Francisco and Monterey Bay regions. The epicenter was located near Loma Prieta 

peak in the Santa Cruz Mountains, approximately 14 km (9 mi) northeast of Santa Cruz 

and 96 km (60 mi) south-southeast of San Francisco. Approximately 16,000 housing units 

were uninhabitable after the earthquake including 13,000 in the San Francisco Bay region. 

Another 30,000-35,000 units were moderately damaged in the earthquake.
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES i

ACKNOWLEDGMENTS

Acknowledgments

The Federal Emergency Management Agency acknowledges and appreciates the 

contributions of the following individuals and organizations to the development of this report: 

n Federal Emergency Management Agency — Washington, DC 

Frederick Sharrocks, Eric Berman, Edward Laatsch, and Doug Bausch

■ National Institute of Building Sciences — Washington, DC 

Philip Schneider and Barbara Schauer

■ PBS&J — Atlanta, Georgia 

Pushpendra Johari, Jawhar Bouabid, Sandeep Mehndiratta, R. Scott Lawson, 

Mourad Bonhafs, and Michelle Palmer 

■ Reviewers —

Dr. Robert V. Whitman, Professor Emeritus, Massachusetts Institute of Technology, 

Chairman Emeritus and member of the HAZUS Earthquake Committee 

Dr. Stuart Nishenko, Consultant, San Mateo, CA 

ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES iii

TABLE OF CONTENTS

Table of Contents

Acknowledgments..........................................................................................................................i

Executive Summary ......................................................................................................................v

1 Introduction.......................................................................................................................1

Background......................................................................................................................1

Study Objectives and Scope............................................................................................2

Casualties, Debris and Shelter ........................................................................................3

2 Analyzing Earthquake Risk.................................................................................................5

Introduction ......................................................................................................................5

Step Two: Compute Building Damage and Loss..............................................................8

Step Three: Compute the Average Annualized Earthquake Losses (AEL)......................10

Step Four: Compute the Average Annualized Earthquake Loss Ratios (AELR)............10

Step Five: Compute the Annualized Casualty, Debris, and Shelter Requirements ........10

Study Limitations ...........................................................................................................11

3 Results of the Study.........................................................................................................13

Nation ...........................................................................................................................13

States and Counties.......................................................................................................13

Region ...........................................................................................................................17

Metropolitan Areas.........................................................................................................17

Socio-Economics...........................................................................................................20

Annualized Estimates of Casualties, Debris, and Shelter Requirements ......................21
iv FEMA HAZUS-MH PROGRAM

TABLE OF CONTENTS 

4 Comparison to Previous Study..........................................................................................31

Study Parameters ..........................................................................................................31

Comparison of AEL and AELR .....................................................................................32

Effect of a Change in Hazard.........................................................................................32

Effect of Change in Building Inventory .........................................................................36

5 Interpretation and Application ..........................................................................................37

Study Findings ..............................................................................................................37

Applications ..................................................................................................................38

Appendices

A Glossary..........................................................................................................................41

B Overview of HAZUS..........................................................................................................45

Module 1: Potential Earth Science Hazard (PESH).......................................................46

Module 2: Inventory and Exposure Data .......................................................................46

Module 3: Direct Damage .............................................................................................47

Module 4: Induced Damage ..........................................................................................47

Module 5: Direct Losses ...............................................................................................47

Module 6: Indirect Losses .............................................................................................48

C Probabilistic Hazard Data Preparation and AEL Computation ...................................... 49

Step 1: Compute the PGA, SA@0.3 and SA@1.0 at each grid point for 

the eight return periods. ....................................................................................49

Step 2: Compute the PGA, SA@0.3 and SA@1.0 at each census tract 

centroid for the eight return periods. .................................................................50

Step 3: Modify the PGA, SA@0.3 and SA@1.0 at each census tract 

centroid to represent site-soil conditions for a NEHRP soil class 

type D. ...............................................................................................................51

Average Annualized Earthquake Loss Computation .....................................................51
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES v

EXECUTIVE SUMMARY 

Executive Summary 

Recent earthquakes around the world show a pattern of steadily increasing damages and 

losses that are due primarily to two factors: (1) significant growth in earthquake-prone 

urban areas and (2) vulnerability of the older building stock, including buildings constructed 

within the past 20 years. In the United States, earthquake risk has grown substantially with 

development while the earthquake hazard has remained relatively constant. Understanding 

the hazard requires studying earthquake characteristics and locales in which they occur 

while understanding the risk requires an assessment of the potential damage to the built 

environment and to the welfare of people — especially in high risk areas. 

Estimating the varying degree of earthquake risk throughout the United States is useful for 

informed decision-making on mitigation policies, priorities, strategies, and funding levels in 

the public and private sectors. For example, potential losses to new buildings may be reduced 

by applying seismic design codes and using specialized construction techniques. However, 

decisions to spend money on either of those solutions require evidence of risk. In the absence 

of a nationally accepted criterion and methodology for comparing seismic risk across regions, 

a consensus on optimal mitigation approaches has been difficult to reach.

While there is a good understanding of high risk areas such as Los Angeles, there is 

also growing recognition that other regions such as New York City and Boston have a low 

earthquake hazard but are still at high risk of significant damage and loss. This high risk level 

reflects the dense concentrations of buildings and infrastructure in these areas constructed 

without the benefit of modern seismic design provisions. In addition, mitigation policies 

and practices may not have been adopted because the earthquake risk was not clearly 

demonstrated and the value of using mitigation measures in reducing that risk may not have 

been understood.

This study highlights the impacts of both high risk and high exposure on losses caused by 

earthquakes. It is based on loss estimates generated by HAZUS®-MH, a geographic information 

system (GIS)-based earthquake loss estimation tool developed by the Federal Emergency 

Management Agency (FEMA) in cooperation with the National Institute of Building Sciences 

(NIBS). The HAZUS tool provides a method for quantifying future earthquake losses. It is national 

in scope, uniform in application, and comprehensive in its coverage of the built environment.
vi FEMA HAZUS-MH PROGRAM

EXECUTIVE SUMMARY 

This study estimates seismic risk in all regions of the United States by using two interrelated 

risk indicators:

n The Annualized Earthquake Loss (AEL), which is the estimated long-term value 

of earthquake losses to the general building stock in any single year in a specified 

geographic area (e.g., state, county, metropolitan area); and

n The Annualized Earthquake Loss Ratio (AELR), which expresses estimated 

annualized loss as a fraction of the building inventory replacement value.

While building-related losses are a reasonable indicator of relative regional earthquake risk, it 

is important to recognize that these estimates are not absolute determinants of the total risk 

from earthquakes. This study also presents the earthquake risk in terms of amount of debris 

generated and social losses including casualty estimates, displaced households, and shelter 

requirements. Seismic risk also depends on other parameters not included herein such as 

damages to lifelines and other critical facilities and indirect economic loss.

The HAZUS-MH analysis indicates that the Annualized Earthquake Loss (AEL) to the national 

building stock is $5.3 billion per year. The majority (77 percent) of average annual loss is 

located on the West Coast (California, Oregon, Washington) with 66 percent ($3.5 billion per 

year) concentrated in the state of California. The high concentration of loss in California is 

consistent with the state’s high seismic hazard and large structural exposure. The remaining 

23 percent (1.1 billion per year) of annual loss is distributed throughout the rest of the United 

States (including Alaska and Hawaii) as reflected in Figure 1. 

While the majority of economic loss is concentrated along the West Coast, the distribution 

of relative earthquake risk, as measured by the Annualized Earthquake Loss Ratio (AELR), 

is much broader and reinforces the fact that earthquakes are a national problem. There are 

relatively high earthquake loss ratios throughout the western and central United States (states 

within the New Madrid Seismic Zone) and in the Charleston, South Carolina area.

Forty-three metropolitan areas, led by the Los Angeles and San Francisco Bay areas, account 

for 82 percent of the total Annualized Earthquake Loss (AEL). Los Angeles County alone has 

about 25 percent of the total AEL, and the Los Angeles and San Francisco Bay areas together 

account for nearly 40% of the total AEL. This observation supports the need for strategies 

to reduce the current seismic risk by focusing on rehabilitation or replacement of the existing 

building stock in our most at-risk communities. Strategies to reduce future losses throughout 

the nation need to be closely integrated with policies and programs that guide urban planning 

and development.
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES vii

EXECUTIVE SUMMARY 

When casualties, debris, and shelter data are aggregated by state, California accounts for 

nearly 50% of estimated debris generated, 60% of displaced households, and 55% of shortterm shelter needs. 

Loss estimates are based on the best science and engineering that was available when the 

study was conducted; thus, future estimates based on new technology will be different from 

those presented herein. To demonstrate how risk has changed with time, comparisons are 

drawn with FEMA 366, HAZUS®99 Estimated Annualized Earthquake Loss for the United 

States, prepared in 2001.

0.57 $B

0.25 $B

3.50 $B

0.05 $B

0.04 $B

0.38 $B

0.06 $B

0.16 $B

0.25 $B

Figure E-1. Comparison of U.S. Regional Seismic Risk by Annualized Earthquake Losses (AEL).
viii FEMA HAZUS-MH PROGRAM

EXECUTIVE SUMMARY 

This loss study is an important milestone in a long-term, FEMA-led effort to analyze and 

compares the seismic risk across regions in the United States and contributes to the mission 

of the National Earthquake Loss Reduction Program (NEHRP) – to develop and promote 

knowledge and mitigation practices and policies that reduce fatalities, injuries, and economic 

and other expected losses from earthquakes. The results of this study are useful in at least 

five ways:

n Improving our understanding of the seismic risk in the nation,

n Providing a baseline for earthquake policy development and the comparison of 

mitigation alternatives,

n Supporting the adoption and enforcement of seismic provisions of building codes,

n Comparing the seismic risk with that of other natural hazards, and

n Supporting pre-disaster planning for earthquake response and recovery.
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 1

introduction 1

1 Introduction

Background

Much of the current perception of earthquakes in the United States has been shaped by 

knowledge of the earthquake hazard, which focuses on the location and type of faulting and 

ground failure, and the distribution of strong ground motion, or shaking. Earthquake hazard 

databases and maps – produced by the U.S. Geological Survey (USGS), state geological 

surveys and other research institutions – provide consistent and useful data.

While hazard maps contribute to understanding earthquakes, there is increasing recognition 

among policy makers, researchers and practitioners of the need to analyze and map the 

earthquake risk in the United States. As urban development continues in earthquake prone 

regions there is growing concern about the exposure of buildings, lifelines (e.g. utilities and 

transportation systems), and people to the potential effects of destructive earthquakes.

Earthquake risk analysis begins with hazard identification, but goes beyond that to investigate 

the potential consequences to people and property, including buildings, lifelines, and the 

environment. Risk analysis is useful for communities, regions, and the nation in making better 

decisions and setting priorities.

The ability to compare risk across states and regions is critical to the management of the 

National Earthquake Hazards Reduction Program (NEHRP). At the state and community 

level, an understanding of seismic risk is important for planning, evaluating costs and 

benefits associated with building codes, and other prevention measures. An understanding 

of earthquake risk is important to risk management for businesses and industries, as well. 

And, understanding the consequences of earthquakes is critical to developing emergency 

operations plans for catastrophes. 

This study uses Hazards U.S. Multi-hazard (HAZUS-MH) Version MR2, a PC-based standardized 

tool that uses a uniform engineering-based approach to measure damages, casualties and 

economic losses from earthquakes nationwide. HAZUS®-MH MR2 was released by FEMA in 

2006 and incorporates updates to the building valuation data and enhanced loss estimation 

functions. Appendix B contains a detailed discussion of HAZUS-MH MR2. 
2 FEMA HAZUS-MH PROGRAM

1 introduction 

Study Objectives and Scope

The objective of this study is to assess levels of seismic risk in the United States using 

HAZUS-MH and nationwide data. The study updates HAZUS®99 Estimated Annualized 

Earthquake Losses for the United States (FEMA 366/February 2001) and incorporates 

the 2002 updates to the USGS National Seismic Map and Census 2000 data to estimate 

annualized economic losses, and debris, shelter and casualty estimates for all fifty states. 

The analysis computes two inter-related metrics to characterize earthquake risk: Annualized 

Earthquake Loss (AEL) and the Annualized Earthquake Loss Ratio (AELR).

The AEL addresses two key components of seismic risk: the probability of ground motion 

occurring in a given study area and the consequences of the ground motion in terms of 

physical damage and economic loss. It takes into account the regional variations in risk. 

For example, the level of earthquake risk in the New Madrid Seismic Zone is measurably 

different from the risk in the Los Angeles Basin with respect to: a) the probability of 

damaging ground motions, and b) the consequences of the ground motions, which are 

largely a function of building construction type and quality, as well as ground shaking 

and failure during earthquakes. Consequences vary regionally, as well. For example, the 

earthquake hazard is higher in Los Angeles than in Memphis, but the general building stock 

in Los Angeles is more resistant to the effects of earthquakes. 

The AEL annualizes expected losses by averaging them per year, which factors in historic 

patterns of frequent smaller earthquakes with infrequent but larger events to provide a 

balanced presentation of earthquake risk. This enables the comparison of risk between two 

geographic areas, such as Los Angeles and Memphis, or California and South Carolina. The 

AEL values are also presented on a per capita basis, to allow comparison of relative risk 

across regions based on population.

The AELR is the AEL as a fraction of the replacement value of the building inventory and 

us useful for comparing the relative risk of events. For example, $10 million in earthquake 

damages in Evansville, Indiana represents a greater loss than a comparable dollar loss 

in San Francisco, a much larger city. The annualized loss ratio allows gauging of the 

relationship between AEL and building replacement value. This ratio can be used as a 

measure of relative risk between regions and, since it is normalized by replacement value, it 

can be directly compared across metropolitan areas, counties, or states.
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 3

introduction 1

Casualties, Debris and Shelter

This study addresses three additional dimensions of earthquake risk: casualties, debris 

and shelter. With FEMA’s emphasis on planning for catastrophic earthquakes, estimates of 

casualties, debris and shelter are useful metrics. 

Casualties estimates are central to medical response planning and for identifying potential 

lifesaving measures. For example, HAZUS-MH enables measuring reduced casualties that 

would result from various combinations of retrofit schemes for the general building stock. 

Estimates of debris on a return period basis are useful for preparing removal and disposal 

plans, particularly in urban areas, and for scaling mission requirements for urban search 

and rescue operations. The ability to compare debris estimates on a regional, state and 

local scale – including estimates by category such as brick, wood, reinforced concrete and 

steel – is valuable for planning and preparing risk reduction strategies. 

Estimating shelter requirements for households and individuals are useful for measuring the 

effects of building codes and other mitigation measures designed to strengthen structures to 

reduce damage to buildings and lessen the need for post-disaster shelter. Recent disasters 

continue to reinforce the critical nature of shelter planning. The ability to compare shelter 

needs for 250-year, 500-year and 1,000-year return periods help in estimating shelter 

capacity and in decision-making for investment in shelter retrofits. 

This report is organized into five chapters. Chapter 2 summarizes the identification of risk 

parameters and describes the procedures used to develop the economic loss estimates. 

The actual loss estimates are presented at the state, regional, county, and metropolitan 

level in Chapter 3 in a series of maps and tables. Chapter 4 discusses how changes in the 

1996 and 2002 versions of the USGS Seismic Hazard Maps, the Census data and building 

inventory affect loss estimates. The report concludes with Chapter 5 and a summary of the 

major findings and recommendations for using results of this work. The Appendices contain 

a glossary of terms as well as more detailed technical information on the methodology and 

data.

ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 5

ANALYZING EARTHQUAKE RISK 2

2 Analyzing Earthquake Risk

INTRODUCTION

Earthquake risk analysis requires measuring the likely damage, casualties, and costs of 

earthquakes within a specified geographic area over certain periods of time. A comprehensive 

risk analysis assesses various levels of the hazard, as well as the consequences to structures 

and populations, should an event occur. Appendix A defines terminology related to risk 

analysis.

There are two types of risk analyses - probabilistic and scenario. This study uses a 

probabilistic, or statistical, hazard analysis to measure the potential effects of earthquakes of 

various locations, magnitudes, and frequencies. In contrast to a single, or scenario, earthquake 

of a specific size and location, probabilistic analyses allow for uncertainties and randomness in 

the occurrences of earthquakes.

To estimate average annualized loss, a number of hazard and building structural 

characteristics were input to the HAZUS-MH earthquake model, as described in Table 2-1.

Computing annualized earthquake loss, annualized earthquake loss ratios, and annualized 

casualty, debris and shelter needs was a five step process. In the first step, the USGS 

earthquake hazard data were processed into a format compatible with HAZUS-MH. In the 

second step, the building inventory in HAZUS-MH was used to estimate losses at the census 

tract level for specific return periods. Third, HAZUS-MH computed the AEL. Fourth, the 

annualized loss values were divided by building replacement values to determine the AELRs, 

and in the final step, annualized casualty, debris and shelter estimates were computed. Each 

of the five steps is described in this section, with greater detail supplied in Appendix C.
6 FEMA HAZUS-MH PROGRAM

2 ANALYZING EARTHQUAKE RISK 

Table 2-1. Hazard and Building Parameters Used in the Study 

Parameters Used in the Study

Geotechnical 

Parameters

NEHRP soil type 'D' (thick alluvium). 

2002 USGS National Seismic Hazard Map ground motion parameters for 

eight return periods between 100 and 2,500 years (100, 250, 500, 750, 1,000, 

1,500, 2,000, and 2,500 years). 

Ground motion parameters located at the census tract centroid. 

Ground-failure effects (liquefaction, landslide) were not included in the 

analyses due to the lack of a nationally applicable database

Building Inventory 

Parameters

Basis for general building inventory exposure: 2000 U.S. Census for residential 

buildings, 2002 Dun & Bradstreet for nonresidential' buildings, and 2005 R.S. 

Means for all building replacement costs. 

Building-related direct economic losses (structural and non-structural 

replacement costs, contents damage, business inventory losses, business 

interruption, and rental income losses), debris, shelter and casualties due to 

ground shaking were computed. All other economic losses were ignored due 

to the lack of a nationally applicable database.

Step One: 

Prepare Probabilistic Hazard Data

The primary source of earthquake hazard data used in this study are probabilistic hazard 

curves developed by the USGS. These were processed for compatibility with HAZUS. 

The curves specify ground motion, such as peak ground acceleration (PGA) and spectral 

acceleration (SA), as a function of the average annual frequency that a level of motion will be 

exceeded in an earthquake. Examples of the USGS probabilistic hazard curves are illustrated 

in Figure 2-1 that show conversely average annual frequency of exceedance as a function of 

PGA for single points in seven major U.S. cities.

The USGS has developed this data for the entire U.S. (see http://earthquake.usgs.gov) as part 

of the National Earthquake Hazards Reduction Program (NEHRP). The curves were developed 

for individual points in a uniform grid that covers all 50 states and Washington, DC. 

A USGS map illustrating PGA for an average return period of 1,000 years is shown in Figure 2-2. 

The USGS hazard curves were converted to a HAZUS-compatible database of probabilistic 

ground shaking values. Probabilistic hazard data for the PGA, spectral acceleration at 0.3 

seconds (SA@0.3), and spectral acceleration at 1.0 second (SA@1.0) were processed for each 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 7

ANALYZING EARTHQUAKE RISK 2

census tract for each of the eight different return periods. Figure 2-3 compares a HAZUS-MH 

seismic hazard (PGA) map for the 1,000-year return period for California to the USGS map for 

the same return period to illustrate that the re-mapping process does not significantly affect 

the estimated losses where there is little exposure at risk. The analysis uses the 2002 USGS 

National Seismic Maps. 

The USGS-computed ground motions apply to rock (B/C soil) and have been used to modify 

the motions so they are applicable to a soil condition that, on average, is typical for populated 

metropolitan areas (D soil).

Figure 2-1.

Average Annual 

Frequency of Peak 

Ground Acceleration 

for Seven Major Cities 

Figure 2-2.

USGS 2002 Seismic 

Hazard Map for the 

1,000-year Return 

Period 
8 FEMA HAZUS-MH PROGRAM

2 ANALYZING EARTHQUAKE RISK 

Step Two: 

Compute Building Damage and Loss

In the second step, HAZUS-MH was used to generate damage and loss estimates for the 

probabilistic ground motions associated with each of eight return periods. The building damage 

estimates were then used as the basis for computing direct economic losses. These include 

building repair costs, contents and business inventories losses, costs of relocation, capitalrelated, wage and rental losses. The analyses were completed for the entire HAZUS-MH 

building inventory for each of the approximately 66,000 census tracts in the U.S. These 

building-related losses serve as a reasonable indicator of relative regional risk, as described in 

greater detail in Appendix B.

Damage and economic losses to critical facilities, transportation and utility lifelines were not 

considered in this study. While it is understood that these losses are a component of risk, 

they are not included because the inventory currently available at a national scale are not 

comprehensive enough to yield meaningful estimates.

For the loss estimates, the replacement value of the building inventory was estimated. A map 

illustrating replacement value of buildings (by county) is shown in Figure 2-4. For this study, the 

replacement value is based only on the value of the building components and omits the land 

value and building contents. Building components include piping, mechanical and electrical 

systems, contents, fixtures, furnishings, and equipment.

Figure 2-3 

Comparison of 

HAZUS-MH Seismic 

Hazard Map for PGA 

in % g (left) and a 

USGS 2002 Hazard 

Map (right) for 1,000-

year Return Period 

Ground Motion for a 

Type B/C Soil 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 9

ANALYZING EARTHQUAKE RISK 2

The building data was combined at various levels to compare replacement value between 

different regions. For example, Figure 2-5 compares the replacement value by state as a 

percentage of total replacement value for the United States. The building exposure data help to 

identify concentrations of replacement value and potential areas of increased risk. 

Figure 2-4 

Replacement Value 

of HAZUS-MH MR2 

Building Inventory by 

County 

Figure 2-5 

Distribution of 

Building Replacement 

Value by State 
10 FEMA HAZUS-MH PROGRAM

2 ANALYZING EARTHQUAKE RISK 

Step Three: 

Compute the Average Annualized Earthquake Losses (AEL)

In this step, the AEL was computed by multiplying losses from eight potential ground motions 

by their respective annual frequencies of occurrence, and then summing the values. Several 

assumptions were made for this computation. First, the losses associated with ground motion 

with return periods greater than 2,500 years were assumed to be no worse than the losses 

for a 2,500-year event. Second, the losses for ground motion with less than a 100-year return 

period were assumed to be generally small enough to be negligible, except in California, where 

losses from ground motion with less than a 100-year return period can account for up to an 

additional 15 percent of the overall statewide AEL estimate.

Step Four: 

Compute the Average Annualized Earthquake Loss Ratios (AELR)

The AEL is an objective measure of risk, however, since risk is a function of the hazard, building 

stock, and vulnerability, variation in any of these three parameters affects the overall risk at any 

one site. Understanding how the parameters influence risk is key to developing effective risk 

management strategies. To facilitate that understanding for regional comparisons, the AEL was 

normalized by the building inventory exposure to create a loss-to-value ratio, termed the AELR, 

and expressed in terms of dollars per million dollars of building inventory exposure.

Between two regions with similar AEL, the region with the smaller building inventory typically 

has a higher relative risk, or AELR, than the region with a larger inventory, since annualized 

loss is expressed as a fraction of the building replacement value. For example, while 

Charleston, South Carolina and Memphis, Tennessee have similar AELs (see Table 3.2), the 

former has a higher earthquake loss ratio, since Charleston has less building inventory and 

building replacement value. In other words, while the seismic risk in Charleston and Memphis 

is roughly the same, a comparably sized earthquake would affect a significantly larger 

percentage of the building inventory in Charleston.

Step Five: 

Compute the Annualized Casualty, Debris, and Shelter

Requirements

The HAZUS-MH software provides the capability to directly compute annualized casualty 

estimates. However, this automated capability does not exist for annualized debris and 

shelter estimates. To generate these estimates, HAZUS-MH was run to produce debris and 

shelter estimates for all eight return periods. These results then were used as inputs in a 

separate database utility external to HAZUS-MH to compute the annualized debris and shelter 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 11

ANALYZING EARTHQUAKE RISK 2

estimates. The utility used the same algorithm used by HAZUS-MH to compute the annualized 

economic loss and casualty estimates (described in Appendix C).

Casualties are estimated as a function of direct structural or non-structural building damage 

with the non-structural-related casualties derived from structural damage output. The HAZUS 

methodology is based on the correlation between building damage (both structural and 

nonstructural) and the number and severity of casualties. This method does not include 

casualties that might occur during or after earthquakes that are not directly related to 

damaged buildings such as heart attacks, car accidents, mechanical failure from power 

outages, incidents during post-earthquake search and rescue, post-earthquake clean-up and 

construction, electrocution, tsunami, landslides, liquefaction, fault rupture, dam failures, fires or 

hazardous materials releases. Psychological effects of earthquakes are also not modeled.

Debris is estimated using an empirical approach for two types of debris. The first is large 

debris, such as steel members or reinforced concrete elements of buildings, that requires 

special handling to break them into smaller pieces before removal. The second type of debris 

is smaller and more easily moved directly with bulldozers and other machinery and tools, and 

includes bricks, wood, glass, building contents and other materials.

Two types of shelter needs are estimated: the number of displaced households and the 

number of individuals requiring short-term shelter. Both are a function of the loss of habitability 

of residential structures directly from damage or from a loss of water and power. The 

methodology for calculating short-term shelter requirements recognizes that only a portion 

of displaced people will seek public shelter while others will seek shelter even though their 

residence may have no damage or insignificant damage because of reluctance to remain in a 

stricken area.

Study Limitations

The estimates provided by this study are not determinations of total risk since not all aspects 

of earthquakes are addressed. For example, the study only addresses direct economic losses 

to buildings. A comprehensive risk study would include damage to lifelines and other critical 

facilities, and indirect economic losses sustained by communities and regions.

There are also inherent uncertainties in computing losses using estimated building values, 

averaged building characteristics, spatial averaging of ground conditions, soil response 

and ground motion that are located at the centroids of census tracts, variables such as the 

magnitude and frequency of future events, and variations in the attenuation of strong ground 

motion. These variables must be considered when comparing the results of other loss studies 

based on HAZUS or other methodologies.

ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 13

RESULTS OF THE STUDY 3

3 Results of the Study

In this chapter, the Annualized Earthquake Loss and the Annualized Earthquake Loss 

Ratios are presented at five levels of geographic resolution: nation, state, county, region, 

and metropolitan area.

Nation

The analysis yielded an estimate of the national AEL of $5.3 billion per year. As previously 

stated, this does not include losses to lifeline infrastructure or indirect (long-term) economic 

losses, and is therefore, a minimum estimate of the potential losses. Moreover, the estimate 

represents a long-term average and actual losses in any single year may be much larger or 

smaller. 

States and Counties

While the AEL measures the annualized earthquake losses in any single year, the AELR 

addresses seismic risk in relation to the value of the buildings in the study area. By relating 

annualized loss to the replacement value in a given study area, the AELR provides a 

comparison of seismic risk between regions.

Figures 3-1 and 3-2 show the AEL and the AELR at the state level, and Figures 3-3 and 3-4 

show the results at the county level. Relatively high earthquake loss ratios exist throughout 

the western U.S. (including Alaska and Hawaii), the central U.S. states within the New 

Madrid Seismic Zone, the Charleston, South Carolina area, and parts of New England, as 

reflected in Figures 3-2 and 3-4. 

Nationwide and statewide losses are the result of averaging, over time, the losses caused 

by earthquakes occurring in different parts of the nation in different years. The majority 

(77 percent) of the annualized losses occur in California, Oregon and Washington, with 66 

percent ($3.5 billion) concentrated in the state of California alone and is consistent with the 

State's significant building inventory and earthquake hazard (see Figures 2-2 and 2-4).
14 FEMA HAZUS-MH PROGRAM

3 RESULTS OF THE STUDY 

AEL and AELR values for the 50 states and Washington, D.C. are shown in Table 3-1. While 

California accounts for the majority of losses, the regional distribution of annualized loss and 

loss ratios demonstrates that seismic risk is a national concern. The juxtaposition of New York 

and Nevada in the AEL column of Table 3-1 illustrates the trade-offs between the value of the 

building inventory and the level of seismic hazard when estimating seismic risk. States with 

low hazard and high value building inventories (e.g., New York) can have annualized losses 

comparable to states with greater hazards but smaller building inventories (e.g., Nevada).

Comparing the rankings of individual states in the AEL and AELR columns of Table 3-1 shows 

that while California and the Pacific Northwest region retain a high relative standing, New York 

Figure 3-1 

Annualized 

Earthquake Losses 

by State 

Figure 3-2

Annualized 

Earthquake Loss 

Ratios by State 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 15

RESULTS OF THE STUDY 3

and New Jersey, states with relatively low hazard and high inventory values, drop from 4th to 

26th and 141h to 27th place, respectively. States such as Montana and New Mexico - with 

higher hazard and lower building inventory values - rise in the ranking from 25th to 9th and 

23rd to 131h, respectively. 

In other words, while the actual dollar amounts of estimated losses are lower, a significantly 

larger percentage of the building inventory is affected. States with the highest AELRs are 

located in the western United States, while other significant concentrations occur in the 

Southeast (South Carolina), Northeast (Vermont, New Hampshire), and the Central United 

States (Illinois, Kentucky, Tennessee, Arkansas, Missouri).

Figure 3-3

Annualized 

Earthquake Losses 

by County

Figure 3-4

Annualized 

Earthquake Losses 

by County
16 FEMA HAZUS-MH PROGRAM

3 RESULTS OF THE STUDY 

Table 3-1. Ranking of States by Annualized Earthquake Loss (AEL) and Annualized Earthquake Loss 

Ratios (AELR)

Rank State AEL

($ x 1,000) Rank State AELR($/Million $)

1 California 3,503,816 1 California 1,452

2 Washington 366,431 2 Alaska 951

3 Oregon 207,686 3 Washington 884

4 New York 95,185 4 Oregon 850

5 Tennessee 94,728 5 Utah 817

6 Utah 89,554 6 Nevada 617

7 Nevada 77,841 7 Hawaii 488

8 South Carolina 77,547 8 South Carolina 363

9 Missouri 73,082 9 Montana 304

10 Hawaii 64,961 10 Tennessee 287

11 Illinois 59,146 11 Arkansas 273

12 Alaska 52,628 12 Missouri 218

13 Arkansas 42,957 13 New Mexico 205

14 New Jersey 39,724 14 Wyoming 187

15 Kentucky 39,163 15 Kentucky 151

16 Georgia 36,733 16 Mississippi 117

17 Pennsylvania 29,585 17 Idaho 106

18 Indiana 27,999 18 Vermont 103

19 North Carolina 26,027 19 Alabama 93

20 Massachusetts 25,294 20 New Hampshire 92

21 Alabama 25,144 21 Arizona 79

22 Arizona 23,354 22 Georgia 77

23 New Mexico 20,621 23 Maine 74

24 Ohio 19,932 24 Indiana 73

25 Montana 16,725 25 Illinois 71

26 Mississippi 15,368 26 New York 67

27 Texas 14,355 27 New Jersey 63

28 Virginia 13,204 28 North Carolina 62

29 Oklahoma 11,797 29 Oklahoma 56

30 Connecticut 11,622 30 Massachusetts 51

31 Colorado 11,234 31 Connecticut 45

32 Idaho 8,042 32 Colorado 40

33 Maryland 7,218 33 Pennsylvania 37

34 New Hampshire 7,199 34 Rhode Island 36

35 Maine 5,917 35 Delaware 36

36 Florida 5,460 36 West Virginia 34

37 Wyoming 4,993 37 Virginia 32

38 Michigan 4,214 38 District of Columbia 28

39 West Virginia 4,122 39 Ohio 26

40 Vermont 3,804 40 Maryland 21

41 Louisiana 3,069 41 Kansas 14

42 Rhode Island 2,720 42 Louisiana 12

43 Kansas 2,107 43 Texas 12

44 Delaware 1,995 44 South Dakota 12

45 Wisconsin 1,613 45 Nebraska 11

46 District of Columbia 1,313 46 Michigan 6

47 Iowa 1,068 47 Iowa 6

48 Nebraska 1,021 48 Florida 6

49 Minnesota 473 49 Wisconsin 4

50 South Dakota 436 50 North Dakota 2

51 North Dakota 69 51 Minnesota 1
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 17

RESULTS OF THE STUDY 3

0.57 $B

0.25 $B

3.50 $B

0.05 $B

0.04 $B

0.38 $B

0.06 $B

0.16 $B

0.25 $B

Region

Figure 3-5 shows the distribution of AEL by region. Oregon, Washington, and California account 

for $4.0 billion in estimated annualized earthquake losses, or 77 percent of the United States 

total. The remaining 23 percent of estimated annualized losses are distributed across the Central 

United States ($0.38 billion), the Northeastern states ($0.25 billion), the Rocky Mountain/

Great Basin and Range region ($0.25 billion), the Great Plains ($0.04 billion per year), and the 

Southeast ($0.16 billion per year). Hawaii and Alaska have a combined AEL of $0.11 billion.

Figure 3.5 Distribution of Average Annualized Earthquake Loss by Seismic Region 

Metropolitan Areas

County level data in Figure 3-3 can be combined to create loss estimates for metropolitan 

areas, defined by the Census as the primary Metropolitan Statistical Areas (U.S. Census, 2000). 

Metropolitan areas with annualized losses greater than $10 million are listed in Table 3-2. 
18 FEMA HAZUS-MH PROGRAM

3 RESULTS OF THE STUDY 

These 43 metropolitan areas, led by the Los Angeles and San Francisco Bay areas, account 

for 82 percent of the total annualized losses in the United States. Los Angeles alone 

accounts for 25 percent of the national figure. Annualized earthquake loss values for selected 

metropolitan areas are shown in Figures 3-6 and 3-7.

When losses for the 43 metropolitan areas are expressed as a fraction of total building 

value in the AELR column of Table 3-2, several cities rise in the rankings, notably Napa, CA, 

Anchorage, AK, and Reno, NV. Again, this is a reflection of high seismic hazard and lower 

relative value of building inventory.

Figure 3-6. 

Metropolitan Areas 

with Annualized 

Earthquake Losses 

Greater than $10 

Million

Figure 3-7. 

 Annualized 

Earthquake 

Loss Ratios for 

Metropolitan Areas 

with Annual Loss 

Greater than $10 

Million 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 19

RESULTS OF THE STUDY 3

Table 3-2. Annualized Earthquake Loss (AEL) and Annualized Earthquake Loss Ratios (AELR) for 43 

Metropolitan Areas with AEL Greater Than $10 Million 

Rank State AEL

($ Million) Rank State AELR($/Million $)

1 Los Angeles-Long Beach-Santa Ana, CA 1,312.3 1 San Francisco-Oakland-Fremont, CA 2,049.44

2 San Francisco-Oakland-Fremont, CA 781.0 2 Riverside-San Bernardino-Ontario, CA 2,021.57

3 Riverside-San Bernardino-Ontario, CA 396.5 3 El Centro, CA 1,973.77

4 San Jose-Sunnyvale-Santa Clara, CA 276.7 4 Oxnard-Thousand Oaks-Ventura, CA 1,963.00

5 Seattle-Tacoma-Bellevue, WA 243.9 5 San Jose-Sunnyvale-Santa Clara, CA 1,837.58

6 San Diego-Carlsbad-San Marcos, CA 155.2 6 Santa Rosa-Petaluma, CA 1,662.57

7 Portland-Vancouver-Beaverton, OR-WA 137.1 7 Santa Cruz-Watsonville, CA 1,580.97

8 Oxnard-Thousand Oaks-Ventura, CA 111.0 8 Los Angeles-Long Beach-Santa Ana, CA 1,574.85

9 Santa Rosa-Petaluma, CA 68.6 9 Napa, CA 1,398.18

10 St. Louis, MO-IL 58.5 10 Vallejo-Fairfield, CA 1,375.94

11 Salt Lake City, UT 52.3 11 Anchorage, AK 1,238.56

12 Sacramento-Arden-Arcade--Roseville, CA 52.0 12 Santa Barbara-Santa Maria-Goleta, CA 1,207.93

13 Vallejo-Fairfield, CA 39.8 13 Reno-Sparks, NV 1,150.40

14 Memphis, TN-MS-AR 38.2 14 Bremerton-Silverdale, WA 1,110.13

15 Santa Cruz-Watsonville, CA 36.2 15 Salinas, CA 1,075.54

16 Anchorage, AK 34.8 16 Seattle-Tacoma-Bellevue, WA 1,052.43

17 Santa Barbara-Santa Maria-Goleta, CA 34.4 17 Salt Lake City, UT 984.61

18 Las Vegas-Paradise, NV 33.1 18 Olympia, WA 969.50

19 Honolulu, HI 32.0 19 Portland-Vancouver-Beaverton, OR-WA 942.62

20 Bakersfield, CA 30.3 20 Bakersfield, CA 870.43

21 New York-Northern New Jersey-Long 

Island, NY-NJ-PA 29.9 21 San Luis Obispo-Paso Robles, CA 848.65

22 Salinas, CA 29.2 22 Ogden-Clearfield, UT 826.52

23 Reno-Sparks, NV 29.0 23 Salem, OR 797.50

24 Charleston-North Charleston, SC 22.3 24 San Diego-Carlsbad-San Marcos, CA 770.20

25 Columbia, SC 21.6 25 Charleston-North Charleston, SC 766.01

26 Stockton, CA 20.9 26 Eugene-Springfield, OR 701.95

27 Atlanta-Sandy Springs-Marietta, GA 19.1 27 Provo-Orem, UT 683.30

28 Bremerton-Silverdale, WA 17.7 28 Stockton, CA 597.79

29 Ogden-Clearfield, UT 17.5 29 Memphis, TN-MS-AR 509.13

30 Salem, OR 17.4 30 Evansville, IN-KY 485.60

31 Eugene-Springfield, OR 16.5 31 Columbia, SC 478.05

32 Napa, CA 15.9 32 Modesto, CA 473.60

33 San Luis Obispo-Paso Robles, CA 15.7 33 Las Vegas-Paradise, NV 390.28

34 Nashville-Davidson--Murfreesboro, TN 15.4 34 Sacramento--Arden-Arcade--Roseville, CA 374.73

35 Albuquerque, NM 14.7 35 St. Louis, MO-IL 337.23

36 Olympia, WA 13.7 36 Albuquerque, NM 322.20

37 Modesto, CA 13.0 37 Honolulu, HI 311.12

38 Fresno, CA 12.6 38 Fresno, CA 283.13

39 Evansville, IN-KY 11.7 39 Little Rock-North Little Rock, AR 248.74

40 Birmingham-Hoover, AL 11.3 40 Nashville-Davidson-Murfreesboro, TN 167.26

41 El Centro, CA 10.7 41 Birmingham-Hoover, AL 115.54

42 Little Rock-North Little Rock, AR 10.5 42 Atlanta-Sandy Springs-Marietta, GA 65.39

43 Provo-Orem, UT 10.4 43 New York-Northern New Jersey-Long 

Island, NY-NJ-PA 20.90
20 FEMA HAZUS-MH PROGRAM

3 RESULTS OF THE STUDY 

Socio-Economics

The ability to correlate population density and annualized loss is useful for developing policies, 

programs and strategies to minimize socio-economic loss from earthquakes. The ability to 

examine annualized loss in terms of other demographic parameters such as ethnicity, age, and 

income is also important. Figures 3-8 and 3-9 present the AEL values on a per capita basis by 

county and state to show where effects on people are most pronounced.

The AELR expresses annualized loss as a fraction of building replacement value, and Figures 

3-8 and 3-9 show annualized loss in relation to 2000 population distribution and reveal two 

important facts: 

1. The high rankings include areas with high seismic hazard and high building 

exposure (e.g., Los Angeles and San Francisco Bay areas), but also areas with high 

seismic hazard and low building exposure (e.g., Hawaii and Alaska); and 

2. California, Oregon, Washington, Alaska and Hawaii have the highest seismic risk 

when measured on a per capita basis at the state level. 

Figure 3-8. 

AEL Per Capita at the 

County Level 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 21

RESULTS OF THE STUDY 3

Annualized Estimates of Casualties, Debris, and Shelter Requirements

Estimates were made of casualties, debris, and shelter requirements for all eight return periods 

using HAZUS-MH, which were then exported and used to compute annualized losses outside 

of HAZUS. This section highlights the findings of the analysis. 

Tables 3-3 and 3-4 show the annualized estimates of debris generated and displaced 

households. California, Washington and Oregon together account for nearly 65 percent of 

estimated debris and 75 percent of displaced households. California alone accounts for 

Figure 3-9. 

AEL Per Capita at the 

State Level 

Figure 3-10. 

AEL Per Capita 

for Selected 

Metropolitan Areas 
22 FEMA HAZUS-MH PROGRAM

3 RESULTS OF THE STUDY 

nearly 50 percent of debris and 60 percent of displaced households. New York is at the top 

of the Eastern states contributing about 3 percent to displaced households. Tennessee ranks 

relatively high in debris (4th) and displaced households (5th), which can be attributed in large 

part to the vulnerability of the Memphis region to earthquakes in the New Madrid Seismic 

Zone, and the concentrations of un-reinforced masonry structures in urban areas.

Table 3-3 and Figure 3-11 and 3-12 depict the estimates of debris for 250-year and 1,000-year 

return periods, respectively. (Table 3-3 includes the 500-year return period). A cursory examination 

of the two maps shows larger increases in debris estimates for the 1,000-year return period event, 

notably the states in the New Madrid Seismic Zone (Tennessee, Arkansas, Missouri, Illinois, 

Alabama, Ohio), as well as New York, South Carolina, North Carolina and Oregon. 

Figure 3-11 

Estimates of Debris 

Generated for 250 

Year Return Period 

Figure 3-12 

Estimates of Debris 

Generated for 1000 

Year Return Period 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 23

RESULTS OF THE STUDY 3

Rank State Annualized 

Estimate

250

Year Event

500 

Year Event

1000

Year Event

1 California 985 66071 136187 188556

2 Washington 130 8117 18714 26629

3 Oregon 80 3184 11436 19937

4 Tennessee 51 1169 4620 12370

5 Utah 48 2184 6982 12070

6 Missouri 43 1099 3945 10208

7 South Carolina 41 563 2726 9933

8 New York 41 966 3036 8193

9 Illinois 35 131 3458 8468

10 Nevada 31 1539 3983 6636

11 Arkansas 26 409 2233 6727

12 Kentucky 23 600 2081 5195

13 Georgia 20 95 1427 3680

14 Arizona 20 675 1649 3557

15 Hawaii 20 1198 2656 4143

16 Pennsylvania 19 605 1699 4345

17 Indiana 18 558 1638 4012

18 New Jersey 16 354 1170 3240

19 Alabama 15 260 852 2695

20 Alaska 15 1044 2348 3091

21 New Mexico 15 386 1358 3452

22 North Carolina 14 262 944 2779

23 Ohio 13 497 1317 3012

24 Texas 11 190 939 2561

25 Massachusetts 10 277 800 2116

26 Virginia 10 299 902 2204

27 Mississippi 10 150 673 2194

28 Oklahoma 9 247 765 1914

29 Montana 8 436 894 1623

30 Colorado 7 181 516 1352

31 Florida 6 1 494 1943

32 Maryland 5 176 526 1290

33 Connecticut 5 117 348 960

34 New Hampshire 3 79 220 603

35 West Virginia 3 5 289 659

36 Maine 3 71 196 526

37 Michigan 3 19 329 821

38 Wyoming 3 109 308 590

39 Louisiana 2 27 207 557

40 Idaho 2 85 229 465

41 Vermont 2 56 147 380

42 Kansas 1 41 131 317

43 Delaware 1 32 98 262

44 Rhode Island 1 31 85 233

45 District of Columbia 1 39 112 266

46 Wisconsin 1 1 101 322

47 Iowa 1 7 84 217

48 Nebraska 1 9 66 175

49 Minnesota 0 0 3 97

50 South Dakota 0 5 28 75

51 North Dakota 0 0 1 14

Table 3-3. Estimates of Debris (x 1000 tons) 
24 FEMA HAZUS-MH PROGRAM

3 RESULTS OF THE STUDY 

Rank State Annualized 

Estimate

250

Year Event

500 

Year Event

1000

Year Event

1 California 5130 269782 634520 1040471

2 Washington 521 29778 71224 106662

3 Oregon 313 10205 41158 76754

4 New York 204 2500 10867 35811

5 Tennessee 141 1679 9651 33253

6 Utah 166 4521 20213 40532

7 Missouri 136 1646 8809 31603

8 South Carolina 116 715 5283 27324

9 Nevada 118 4609 13586 25466

10 Illinois 98 0 7312 23738

11 Arkansas 72 434 4235 17530

12 New Jersey 65 723 3292 11067

13 Alaska 64 3886 9585 13666

14 Kentucky 49 732 3743 11932

15 Georgia 43 108 2448 7345

16 Massachusetts 46 783 2834 8568

17 Hawaii 62 3081 7934 13369

18 Pennsylvania 35 526 2024 6946

19 New Mexico 30 321 1494 5153

20 Arizona 29 576 1868 4742

21 Indiana 30 571 2087 6585

22 North Carolina 24 219 1028 3903

23 Alabama 17 216 773 2963

24 Ohio 17 122 1634 4503

25 Montana 17 696 1661 3487

26 Mississippi 15 135 733 3170

27 Virginia 16 252 1000 3080

28 Connecticut 17 19308 1009 3188

29 Texas 13 157 889 2793

30 Oklahoma 12 150 670 2142

31 Colorado 11 126 476 1663

32 New Hampshire 11 179 573 1741

33 Maine 8 148 456 1327

34 Maryland 8 147 586 1841

35 Florida 6 0 302 1547

36 Vermont 6 120 351 1010

37 Rhode Island 5 89 302 955

38 Wyoming 5 124 453 1039

39 West Virginia 4 2 250 715

40 Michigan 4 17 347 1056

41 Idaho 4 76 261 694

42 Louisiana 2 21 203 682

43 District of Columbia 2 42 163 493

44 Wisconsin 2 1 159 586

45 Delaware 2 25 98 353

46 Kansas 2 39 145 439

47 Iowa 1 8 85 264

48 Nebraska 1 8 69 238

49 South Dakota 0 5 34 113

50 Minnesota 0 0 2 115

51 North Dakota 0 0 1 18

Table 3-4. Estimates of Displaced Households
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 25

RESULTS OF THE STUDY 3

Tables 3-5 and 3-6 show the annualized estimates of the number of people looking for shelter 

(shelter requirement) and the annualized estimates of number of people looking for shelter per 

million of population for all the states. The estimates of shelter requirements follow the trend of 

displaced households with California, Washington and Oregon together accounting for nearly 

75 percent, and California accounting for nearly 60 percent of the total. New York remains the 

top contributor from the Eastern states with about 3 percent of total number of people looking 

for shelter.

A comparison of the standings of individual states in the Shelter and Shelter Ratio columns 

of Tables 3-5 and 3-6 show that while California, Oregon and Washington rank in the top tier, 

New York and New Jersey – states with relatively low hazard and high population – drop from 

4th to 15th and 121h to 20th place, respectively. Alaska and Hawaii - with higher hazard and 

lower population – rise in the ordering from 13th to 3rd and 17th to 71h, respectively.

Table 3-5 and Figures 3-13 and 3-14 depict the estimates of shelter requirements generated 

for a 250-year and 1,000-year return period, respectively, aggregated at state level. (Table 3-5 

includes the 500-year return period). 
26 FEMA HAZUS-MH PROGRAM

3 RESULTS OF THE STUDY 

Rank State Annualized 

Estimate

250

Year Event

500 

Year Event

1000

Year Event

1 California 1313 70093 163635 265335

2 Washington 123 7036 16870 25276

3 Oregon 77 2532 10263 19110

4 New York 58 703 3070 10118

5 Tennessee 40 479 2788 9556

6 Utah 39 1096 4850 9596

7 Missouri 36 445 2413 8587

8 South Carolina 32 201 1478 7604

9 Nevada 30 1201 3539 6620

10 Illinois 25 0 1954 6273

11 Arkansas 21 124 1224 5033

12 New Jersey 17 187 853 2861

13 Alaska 14 842 2066 2939

14 Kentucky 14 205 1039 3272

15 Georgia 12 29 670 2024

16 Massachusetts 12 197 713 2151

17 Hawaii 11 551 1431 2436

18 Pennsylvania 9 137 526 1800

19 New Mexico 8 91 424 1445

20 Arizona 8 162 526 1318

21 Indiana 8 148 536 1679

22 North Carolina 6 59 276 1051

23 Alabama 5 64 229 873

24 Ohio 5 0 431 1184

25 Montana 4 185 441 924

26 Mississippi 4 41 215 920

27 Connecticut 4 4991 262 827

28 Virginia 4 65 260 798

29 Texas 4 51 263 814

30 Oklahoma 3 40 178 565

31 Colorado 3 31 118 410

32 New Hampshire 2 42 135 409

33 Maine 2 39 120 350

34 Maryland 2 38 149 465

35 Florida 2 0 80 405

36 Vermont 1 30 87 249

37 Rhode Island 1 24 82 260

38 Wyoming 1 27 100 231

39 West Virginia 1 1 72 206

40 Michigan 1 4 91 275

41 Idaho 1 19 65 172

42 Louisiana 1 7 62 209

43 District of Columbia 1 12 48 146

44 Wisconsin 0 0 40 149

45 Delaware 0 6 24 87

46 Kansas 0 10 37 111

47 Iowa 0 2 22 66

48 Nebraska 0 2 17 60

49 South Dakota 0 1 9 28

50 Minnesota 0 0 0 28

51 North Dakota 0 0 0 5

Table 3-5. Estimates of Short –Term Shelter Requirements (# of People) 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 27

RESULTS OF THE STUDY 3

Rank State Shelter Ratio (# of People/Million)

1 California 39

2 Oregon 23

3 Alaska 22

4 Washington 21

5 Utah 18

6 Nevada 15

7 Hawaii 9

8 South Carolina 8

9 Arkansas 8

10 Tennessee 7

11 Missouri 6

12 Montana 5

13 New Mexico 5

14 Kentucky 3

15 New York 3

16 Vermont 2

17 Wyoming 2

18 Illinois 2

19 New Hampshire 2

20 New Jersey 2

21 Massachusetts 2

22 Maine 2

23 Arizona 2

24 Mississippi 2

25 Georgia 1

26 Rhode Island 1

27 Connecticut 1

28 Indiana 1

29 Alabama 1

30 District of Columbia 1

31 Oklahoma 1

32 North Carolina 1

33 Pennsylvania 1

34 Idaho 1

35 Colorado 1

36 Virginia 1

37 Delaware 1

38 West Virginia 1

39 Ohio 0

40 Maryland 0

41 Texas 0

42 Louisiana 0

43 Kansas 0

44 South Dakota 0

45 Nebraska 0

46 Florida 0

47 Michigan 0

48 Wisconsin 0

49 Iowa 0

50 North Dakota 0

51 Minnesota 0

Table 3-6. Annualized Shelter Requirement Ratios 
28 FEMA HAZUS-MH PROGRAM

3 RESULTS OF THE STUDY 

Figure 3-11 

Estimates of Debris 

Generated for 250 

Year Return Period 

Figure 3-12 

Estimates of Debris 

Generated for 1000 

Year Return Period 

Table 3.7 divides annualized casualty estimates into three categories of injury: 1) Minor (non 

life-threatening); 2) Major (defined as injuries that pose an immediate life-threatening condition 

if not treated adequately; and 3) Fatal. Casualty rates are a direct function of the time-of-day 

or night that an earthquake occurs, as reflected in Table 3.7. A majority of injuries are in the 

minor category. 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 29

RESULTS OF THE STUDY 3

Table 3-7. Annualized Estimates of Casualties by State 

Rank State

Day Time Night Time

Minor Life 

Threatening Fatal Minor Life Threatening Fatal

1 California 1891 63 122 1276 19 36

2 Washington 260 9 17 127 2 4

3 Oregon 188 7 13 85 2 3

4 Utah 86 3 6 59 2 3

5 Tennessee 89 3 5 62 1 3

6 South Carolina 64 2 4 51 1 2

7 Missouri 67 2 4 62 2 3

8 Nevada 59 2 4 33 1 1

9 Illinois 45 1 2 48 1 2

10 Arkansas 38 1 2 33 1 2

11 Alaska 28 1 2 17 0 1

12 New York 45 1 2 45 1 2

13 Kentucky 31 1 2 25 1 1

14 Georgia 32 1 1 17 0 1

15 Hawaii 21 1 1 17 0 1

16 New Mexico 15 0 1 13 0 1

17 Indiana 19 0 1 17 0 1

18 Mississippi 16 0 1 11 0 0

19 New Jersey 20 0 1 16 0 1

20 Montana 12 0 1 7 0 0

21 Alabama 14 0 1 9 0 0

22 Arizona 14 0 1 15 0 0

23 North Carolina 15 0 1 11 0 0

24 Massachusetts 13 0 0 9 0 0

25 Pennsylvania 14 0 0 18 0 1

26 Texas 10 0 0 7 0 0

27 Ohio 12 0 0 10 0 0

28 Virginia 9 0 0 9 0 0

29 Oklahoma 7 0 0 8 0 0

30 Wyoming 4 0 0 2 0 0

31 New Hampshire 5 0 0 3 0 0

32 Connecticut 6 0 0 4 0 0

33 Colorado 6 0 0 4 0 0

34 Maine 4 0 0 2 0 0

35 Idaho 3 0 0 2 0 0

36 Vermont 3 0 0 2 0 0

37 Maryland 4 0 0 4 0 0

38 West Virginia 3 0 0 3 0 0

39 Florida 3 0 0 5 0 0

40 Louisiana 2 0 0 2 0 0

41 Michigan 2 0 0 2 0 0

42 Rhode Island 1 0 0 1 0 0

43 Delaware 1 0 0 1 0 0

44 Kansas 1 0 0 1 0 0

45 District of Columbia 1 0 0 1 0 0

46 Wisconsin 1 0 0 1 0 0

47 Iowa 1 0 0 0 0 0

48 Nebraska 1 0 0 0 0 0

49 South Dakota 0 0 0 0 0 0

50 Minnesota 0 0 0 0 0 0

51 North Dakota 0 0 0 0 0 0

ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 31

COMPARISON TO PREVIOUS STUDY 4

4 Comparison to Previous 

Study

This chapter compares the results of this study with the original earthquake loss study (FEMA 366, 

2001) and analyzes how changes in the earthquake hazard and building inventory have affected 

potential earthquake losses. The previous study was based on methods and data in HAZUS99 

which included the 1996 USGS National Seismic Hazard Maps and Census 1990 data. The 

current study utilizes HAZUS-MH MR2 methods and data and includes the 2002 USGS seismic 

maps and Census 2000 data. Two different analyses were performed, as described below.

For the Nation:

HAZUS-MH MR2 methods and data/2002 USGS National Seismic Maps. This analysis provided 

a snapshot of the current earthquake risk using the most up-to-date version of HAZUS and 

recent building, population, and hazard maps.

HAZUS-MH MR2 methods and data/1996 USGS National Seismic Hazard Maps. This analysis 

used the most up-to-date version of HAZUS and recent building and population data with the 

1996 seismic maps used for FEMA 366 and enabled comparison of the change in earthquake 

risk in the past decade.

For California only:

HAZUS-MH MR2 with HAZUS99. This analysis was conducted to test the effect of the change in 

exposure between HAZUS-MH MR2 and HAZUS99.

Study Parameters

In 1996, the USGS prepared a series of seismic hazard maps for earthquakes that were used 

in HAZUS99 for hazard characterization. The original earthquake loss study (FEMA 366, 2001) 

used the HAZUS99 methodology, the 1994 building data, and population data from the 1990 

census. With the release of HAZUS-MH several parameters changed, as reflected in Table 4-1. 

Since HAZUS-MH was used as the basis for the current study, these changes are reflected in 

the results.
32 FEMA HAZUS-MH PROGRAM

4 COMPARISON TO PREVIOUS STUDY

HAZUS 99 HAZUS-MH

1996 National Seismic Hazard Maps 2002 USGS National Seismic Hazard Maps

Loss estimates based on 1990 Census Data Loss estimates based on 2000 Census Data

1994 Building Inventory and Occupancy to 

Building Type Distributions

2002 Building Inventory (Dun and Bradstreet) and 

updated Occupancy to Building Type Distributions

Building and Content Exposure based on 

square footage from pre-defined regions

Building and Content Exposure based on General 

Building Stock datasets in the study region.

Table 4-1. Summary of Key Changes Incorporated into HAZUS-MH

1 This adjustment factor is based on the average of the ENR adjustment factor (Engineering News-Record, Construction Cost History 

— http://www.enr.com/) and the CPI adjustment factor (Bureau of Labor Statistics, Consumer Price Index - All Urban Consumers— 

http://usda.mannlib.cornell.edu/reports/nassr/price/zap-bb/) as calculated with the Engineering News Record Damage Inflation 

Calculator: Version 2.1, July 20, 2007.

Comparison of AEL and AELR 

The current study estimates a national AEL of $5.3 billion (2005 dollars), which is a 21% 

increase over the FEMA 366 estimate of $4.4 billion (1994 dollars). However, if we adjust the 

FEMA 366 study results to reflect current values (2005 dollars1), the FEMA 366 loss estimate 

would increase to $5.6 billion, which represents a small decrease in the overall earthquake 

loss potential. During the period the national building inventory increased by almost 50%, the 

estimated earthquake loss increased by only 20%.

In the following sections, the reasons why the loss did not increase at the same proportional 

rate as the building inventory will be discussed.

Effect of a Change in Hazard

To improve our understanding of how a change in a hazard (while keeping the other analysis 

parameters constant) affects losses, HAZUS-MH was run using the 1996 USGS Probabilistic 

Hazard Data and compared to results using the 2002 USGS Probabilistic Maps (which are 

incorporated in HAZUS-MH). 

Figure 4-1 depicts the differences in hazard where the negative values represent a decrease 

since 1996 and the positive values represent an increase since 1996. The following patterns 

are noted:

n A slight decrease in the hazard in Western United States, except for some parts of 

Washington and Utah.

n A slight increase in the hazard in the Great Plains.
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 33

COMPARISON TO PREVIOUS STUDY 4

n Little change in hazard in the Southeast, except for modest changes in some areas 

of Virginia, North Carolina and South Carolina and a significant increase in the 

Charleston area.

n Significant increase in hazard in the Central region, which includes the New Madrid 

Seismic Zone.

n Little change in hazard in the Northeast, except for some areas of New York, Maine 

where the hazard has gone down.

Figure 4-1 

Difference in the 

1,000-year return 

period USGS Seismic 

Hazard Map 2002 

and USGS Seismic 

Hazard Map 1996 

(differences show 

PGA 2002 values vs. 

PGA 1996 values)

Table 4-2 shows the Annualized Loss obtained from HAZUS-MH MR2 using both 2002 and 

1996 USGS National Seismic Hazard Maps for all the states, including the percentage change. 

The values in parentheses represent a decrease in losses. Analysis of the results reveals a 

general decrease in AEL, with some exceptions. Washington and Utah show a sight increase 

in losses. California shows a decrease from 74 percent of U.S. total in FEMA 366 to 66 percent 

of the U.S. total in this study. States in the New Madrid Seismic Zone in the Central U.S. 

experience an increase in AEL when using the 2002 hazard maps. 

Table 4-3 lists the Annualized Loss Ratio from both the hazards for all the states. The loss 

ratios follow the trend of the change in loss. 

For Tables 4-2 and 4-3 building inventory loss estimates were calculated by census tract and 

reported in 2005 dollars. 
34 FEMA HAZUS-MH PROGRAM

4 COMPARISON TO PREVIOUS STUDY

Rank State AEL 2002 Hazard

(x 1000)

AEL 1996 Hazard

(x 1000) Percent Change

1 California 3,503,816 3,813,745 (8)

2 Washington 366,431 336,102 9

3 Oregon 207,686 228,251 (9)

4 New York 95,185 146,906 (35)

5 Tennessee 94,728 88,374 7

6 Utah 89,554 87,948 2

7 Nevada 77,841 79,061 (2)

8 South Carolina 77,547 88,965 (13)

9 Missouri 73,082 63,669 15

10 Hawaii 64,961 70,655 (8)

11 Illinois 59,146 56,384 5

12 Alaska 52,628 55,637 (5)

13 Arkansas 42,957 33,172 29

14 New Jersey 39,724 61,218 (35)

15 Kentucky 39,163 36,417 8

16 Georgia 36,733 48,295 (24)

17 Pennsylvania 29,585 43,160 (31)

18 Indiana 27,999 26,833 4

19 North Carolina 26,027 33,767 (23)

20 Massachusetts 25,294 37,217 (32)

21 Alabama 25,144 27,531 (9)

22 Arizona 23,354 31,776 (27)

23 New Mexico 20,621 24,674 (16)

24 Ohio 19,932 22,308 (11)

25 Montana 16,725 18,847 (11)

26 Mississippi 15,368 12,852 20

27 Texas 14,355 15,072 (5)

28 Virginia 13,204 19,421 (32)

29 Oklahoma 11,797 11,115 6

30 Connecticut 11,622 18,153 (36)

31 Colorado 11,234 11,234 0

32 Idaho 8,042 8,830 (9)

33 Maryland 7,218 10,170 (29)

34 New Hampshire 7,199 10,042 (28)

35 Maine 5,917 8,046 (26)

36 Florida 5,460 6,280 (13)

37 Wyoming 4,993 5,710 (13)

38 Michigan 4,214 3,883 9

39 West Virginia 4,122 5,427 (24)

40 Vermont 3,804 5,468 (30)

41 Louisiana 3,069 3,431 (11)

42 Rhode Island 2,720 3,967 (31)

43 Kansas 2,107 1,656 27

44 Delaware 1,995 3,105 (36)

45 Wisconsin 1,613 1,628 (1)

46 District of Columbia 1,313 1,824 (28)

47 Iowa 1,068 771 39

48 Nebraska 1,021 870 17

49 Minnesota 473 362 31

50 South Dakota 436 372 17

51 North Dakota 69 57 21

TOTAL 5,280,295 5,730,658 (9)

Table 4-2. National Comparison of the AEL Values in $ by State for 2002 and 1996 USGS Hazard Maps 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 35

COMPARISON TO PREVIOUS STUDY 4

Rank State AELR 2002 Hazard

($ / Million)

AELR 1996 Hazard

($ / Million)

1 California 1,452 1,580

2 Alaska 951 1,005

3 Washington 884 811

4 Oregon 850 935

5 Utah 817 802

6 Nevada 617 626

7 Hawaii 488 531

8 South Carolina 363 417

9 Montana 304 332

10 Tennessee 287 268

11 Arkansas 273 210

12 Missouri 218 190

13 New Mexico 205 245

14 Wyoming 187 214

15 Kentucky 151 140

16 Mississippi 117 98

17 Idaho 106 116

18 Vermont 103 149

19 Alabama 93 102

20 New Hampshire 92 128

21 Arizona 79 108

22 Georgia 77 102

23 Maine 74 101

24 Indiana 73 70

25 Illinois 71 67

26 New York 67 104

27 New Jersey 63 97

28 North Carolina 62 80

29 Oklahoma 56 53

30 Massachusetts 51 76

31 Connecticut 45 71

32 Colorado 40 40

33 Pennsylvania 37 53

34 Rhode Island 36 53

35 Delaware 36 56

36 West Virginia 34 45

37 Virginia 32 47

38 District of Columbia 28 38

39 Ohio 26 30

40 Maryland 21 30

41 Kansas 14 11

42 Louisiana 12 14

43 Texas 12 12

44 South Dakota 12 10

45 Nebraska 11 9

46 Michigan 6 6

47 Iowa 6 4

48 Florida 6 6

49 Wisconsin 4 4

50 North Dakota 2 2

51 Minnesota 1 1

Table 4-3. National Comparison of the AELR Values by State for 2002 and 1996 USGS Hazard Maps 
36 FEMA HAZUS-MH PROGRAM

4 COMPARISON TO PREVIOUS STUDY

Effect of Change in Building Inventory 

In HAZUS-MH, the building distribution for the inventory of California was changed significantly. 

The primary change in the building distribution (See Table 4-4) was a proportional in-crease 

in wood frame buildings (+17%) and a reduction in the amount of masonry, steel, concrete 

buildings. This substantial revision in the building distribution was limited to California with the 

distribution in other states remaining basically the same. 

Generally, wood frame construction is less vulnerable to earthquake damage than other 

building types, so this change in inventory composition was expected to cause a reduction in 

the AELR for California. Consequently, since California accounted for over 2/3rds of the total 

AEL for the US, this change was expected to have a substantial impact on the overall study. 

This reduction in normalized loss was driven primarily by the change in the building distribution 

but was also affected by a reduction in the USGS probabilistic seismic hazard. Additional 

analysis showed that 78% of the loss reduction could be attributed to the change in building 

distribution while 22% was due to a reduction in the probabilistic seismic hazard for California.

Table 4-4. Change in Building Distribution by General Structural Types in California 

Wood Steel Concrete Masonry Manufactured 

Homes

HAZUS 99 63 10 11 13 3

HAZUS-MH MR2 80 4.2 8 7 0.8

Percent Change 17.00 (5.80) (3.00) (6.00) (2.20)
interpretation and applications 5

ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 37

5 Interpretation and 

Applications

While there is a well-established body of information on how the earthquake hazard varies 

among regions, there is less understanding of how earthquake risk differs from one region 

to another, and how the risk may be affected by changes in the hazard itself and building 

inventory. From a public policy and emergency management standpoint, understanding and 

documenting how these changes affect regional, state and local earthquake exposure and 

risk are fundamental to garnering and sustaining support for risk reduction strategies, seismic 

policy and program development. 

Study Findings 

n Although greatest on the West Coast, seismic risk exists in other areas of the U.S.

The annualized loss from earthquakes nationwide is estimated to be $5.3 billion 

per year with California, Oregon and Washington accounting for $4.1 billion, or 

77 percent. The remaining 23 percent of losses are distributed among the Central 

states ($0.38 billion per year), the Northeast ($0.25 billion per year), and the 

Southeast ($0.16 billion per year). Hawaii and Alaska have a combined $110 million 

in average annualized losses. 

n An increase in building inventory will not always translate to a proportional increase 

in seismic risk. 

In HAZUS-MH, the occupancy-to-building type profile for California was modified to 

include a higher proportion of wood frame construction (See Table 4-4). Wood frame 

construction is less vulnerable to earthquake damage than other types of building 

construction types, such as masonry construction. This modification to the building 

type profile was the primary reason for the reduction in the AELR for California 

[1,452 (HAZUS-MH) vs. 2,048 (HAZUS-99)] and is a good example of the potential 

loss reduction that can occur by replacing aging construction with more earthquake 

resistant construction. 
5 interpretation and applications 

38 FEMA HAZUS-MH PROGRAM

n Earthquake risk continues to be highest in urban areas, most notably California and 

on the West Coast.

In a number of states - New York, South Carolina, Utah, Alaska, Hawaii, California, 

Oregon, and Washington - estimated losses in metropolitan areas account for up 

to 80 percent of total state losses, which has important implications for a national 

strategy to reduce seismic risk. More than 60 percent of the annualized losses 

in California are expected in the three metropolitan areas of San Francisco, Los 

Angeles and San Diego. These three metropolitan regions have a combined 

population of 15 million (2004) and account for over 43 percent of the total estimated 

annualized earthquake loss in the United States. 

n An increase in the USGS probabilistic seismic maps will translate to increases in 

risk.

In HAZUS-MH, the probabilistic seismic hazard increased for many states in the 

Central US. This increase was due to changes in the USGS seismic hazard models 

(USGS, 2002) for the Central US and resulted in an increase in the AELR for many 

states. In some states, such as Arkansas, the increase in AELR was as much as 30 

% (See Table 4-3). 

Applications 

The findings in this study can be used to support analysis, decision making and risk reduction, 

including: 

1. To improve understanding of the seismic risk in the U.S. 

This study builds on the knowledge gained from the original study (FEMA 366, 2001) 

to incorporate new data that directly influences earthquake loss and mitigation: 1) 

the seismic hazard (2002 hazard data); 2) inventory (2002 Dun and Bradstreet); 3) 

population at risk (2000 Census Data); and 4) estimated social losses. By modifying 

these important parameters, the study provides a clearer picture of their role in 

shaping seismic risk in the U.S. In a broader sense, the information in this study 

is an integral component of a “national seismic risk baseline” – aggregated at the 

metropolitan, county, state and regional level. Key parameters that can be updated 

include: 1) Seismic hazard; 2) Inventory (general building stock, lifelines, essential 

facilities); 3) Demographic data; and 4) Loss estimation and other analyses. 
interpretation and applications 5

ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 39

2. To support the adoption and enforcement of seismic building code provisions. 

One of the objectives of the National Earthquake Hazards Reduction Program 

(NEHRP) is to promote the adoption and enforcement2 of seismic building codes 

in regions of the U.S. that experience infrequent but damaging earthquakes. The 

uneven distribution of seismic risk across the U.S. militates against uniform adoption 

and enforcement. Typically, localities with infrequent earthquakes place a low priority 

on seismic code enforcement. However, this study demonstrates the actual regional 

risk in terms of potential damage and economic loss. 

The HAZUS-MH data can be applied to evaluate the effectiveness of different 

mitigation strategies by measuring risk and their uncertainties before and after they 

are implemented. For example, a FEMA study3 concludes that if the Los Angeles 

area had been built to high seismic design standards (UBC zone 4 or NEHRP zone 

7) prior to the 1994 Northridge earthquake, the losses would have been reduced by 

$11.3 billion (including buildings, contents, and income). 

This is equivalent to avoiding about 40 percent of losses (when adjusting for 

additional costs to design and construct to higher seismic standards). This 

information type of analysis is valuable when determining policy and program 

options in for long-term risk management measures, including those that address 

building codes, land use planning, and resource allocation. 

3. To compare the seismic risk with other natural hazard risks. 

The AEL figures, which include estimated losses in regions with infrequent 

earthquakes, can be compared with more frequent flood and wind-related losses. 

The ability to measure earthquake risk relative to other natural hazards helps in 

a balanced, multi-hazard approach to risk management. For example, elevating 

structures in response to flood hazard may compromise them in terms of earthquake 

risk and would suggest a different approach to risk reduction in that case. 

2 Burby, Raymond and Peter May. Making Building Codes an Effective Tool for Earthquake Hazard Mitigation, Environmental Hazards, 

1, 1999, p. 27-37.

3 Federal Emergency Management Agency, Report on the Costs and Benefits of Natural Hazard Mitigation, FEMA 294, 1997, 

Washington, D.C. U.S. Government Printing Office.
5 interpretation and applications 

40 FEMA HAZUS-MH PROGRAM

4. To support disaster response and recovery planning. 

For planning for catastrophic earthquakes, the ability to compare annualized 

estimates of debris, casualties and shelter requirements on a regional, state and 

municipal scale enables planners to anticipate potential resource requirements 

under the National Response Plan. These estimates, along with the 250, 500 

and 1000 year estimates, are useful in planning tools, as well as identifying and 

prioritizing mitigation measures that address life safety and functionality of essential 

facilities. 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 41

GLOSSARY A

A Glossary

Annualized Earthquake Loss (AEL) – The estimated long-term value of 

earthquake losses in any given single year in a specified geographic 

area.

Annualized Earthquake Loss Ratio (AELR) – The ratio of the average 

annualized earthquake loss to the replacement value of the building 

inventory. This ratio is used as a measure of relative risk, since it 

considers replacement value, and can be directly compared across 

different geopolitical units including census tracts, counties, and states.

Average Annual Frequency – The long-term average number of events 

per year.

Basic Building Inventory – The national level building inventory incorporated 

into HAZUS-MH. The basic database classifies buildings by occupancy 

(residential, commercial, etc.) and by model building type (wall 

construction, roof construction, height, etc.). The basic mapping schemes 

are state-specific for single-family occupancy type and region-specific 

for all other occupancy types; they are building-age and height specific. 

The four inventory groups are: general building stock, essential and high 

potential loss facilities, transportation systems, and utilities.

Hazard – A source of potential danger or an adverse condition. For 

example, a hurricane occurrence is the source of high winds, rain, and 

coastal flooding, all of which can cause fatalities, injuries, property 

damage, infrastructure damage, interruption of business, or other types 

of harm or loss.

Hazard Identification – Hazard identification involves determining the 

physical characteristics of a particular hazard - magnitude, duration, 

frequency, probability, and extent – for a site or a community.
42 FEMA HAZUS-MH PROGRAM

A GLOSSARY

Hazards U.S. – Multi-Hazard (HAZUS-MH) – A standardized GIS-based 

loss estimation tool, developed by the Federal Emergency Management 

Agency (FEMA) in cooperation with the National Institute of Building 

Sciences (NIBS). See www.fema.gov/plan/prevent/hazus for more 

information.

Peak Ground Acceleration (PGA) – The maximum level of vertical or 

horizontal ground acceleration caused by an earthquake. PGA is 

commonly used as a reference for designing buildings to resist the 

earthquake movements expected in a particular location and is typically 

expressed as a percentage of the acceleration due to gravity (g). 

Probabilistic Seismic Hazard Data – An earthquake ground motion 

estimate that includes information on seismicity, rates of fault motion, 

and the frequency of various magnitudes. Earthquake hazards are 

expressed as the probability of exceeding a level of ground motion in a 

specified period of time (e.g., 10% probability of exceeding 20% g in 50 

years). 

See http://earthquake.usgs.gov/ for more information.

Return Period – The average time between hurricanes of comparable 

size in a given location. Equal to the reciprocal of the frequency.

Risk – The likelihood of sustaining a loss from a hazard event defined 

in terms of expected probability and frequency, exposure, and 

consequences, such as, death and injury, financial costs of repair and 

rebuilding, and loss of use.

Risk Analysis – The process of measuring or quantifying risk. Risk 

analysis combines hazard identification and vulnerability assessment 

and answers three basic questions: 

n what hazard events can occur in the community? 

n what is the likelihood of these hazard events occurring? 

n what are the consequences if the hazard event occurs? The 

overall significance of these consequences in the community 

or region is called the risk assessment.
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 43

GLOSSARY A

Risk Management – The reduction of risk to an acceptable level. Risk 

management addresses three issues: 

n what steps should be taken to reduce risks to an acceptable 

level (mitigation), 

n the relative trade-offs among multiple opportunities (benefit/

cost analyses, capital allocation), and 

n the impacts of current decisions on future opportunities.

Spectral Acceleration (SA) – The acceleration response of a single 

degree- of-freedom mass-spring dashpot system with a given natural 

period (e.g., 0.3 of 1 second) to a given earthquake ground motion. SA 

is most closely related to structural response and, therefore, indicates an 

earthquake's damage potential.

Vulnerability Assessment – The process of assessing the vulnerability 

of people and the built environment to a given level of hazard. The 

quantification of impacts (i.e., loss estimation) for a hazard event is part 

of the vulnerability assessment. 

ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 45

 OVERVIEW OF HAZUS B

4 Federal Emergency Management Agency, HAZUS-MH MR2 Earthquake Model Technical Manual, Prepared by the National Institute 

of Building Sciences for FEMA, 2006.

B Overview of HAZUS

Acknowledging the need to develop a standardized approach to estimating losses from 

earthquakes and other hazards, FEMA has embarked on a multiyear program to develop 

a GIS-based regional loss estimation tool. FEMA released the first version of the HAZUS 

earthquake model in 1997 followed by an updated version in 1999. In 1998, FEMA began the 

development of a multi-hazard methodology to encompass wind and flood hazards. 

FEMA developed HAZUS and HAZUS-MH under agreements with the National Institute of 

Building Sciences. HAZUS-MH is a tool that local, state, and federal government officials and 

others can use for mitigation, emergency preparedness, response and recovery planning, 

and disaster response operations. The methodology in HAZUS-MH is comprehensive. It 

incorporates state-of-the-art approaches for characterizing hazards; estimating damage and 

losses to buildings and lifelines; estimating casualties, displaced households, and shelter 

requirements; and estimating direct and indirect economic losses. 

Since HAZUS-MH is a uniform national methodology, it serves as an excellent vehicle for 

assessing and comparing seismic risk across the United States. The HAZUS technology 

is built upon an integrated geographic information system (GIS) platform that produces 

regional profiles and estimates of earthquake losses. The methodology addresses the built 

environment, and categories of losses, in a comprehensive manner. 

HAZUS-MH is composed of six major modules, which are interdependent. This modular 

approach allows different levels of analysis to be performed, ranging from estimates based 

on simplified models and default inventory data to more refined studies based on detailed 

engineering and geotechnical data for a specific study region. 

A brief description of each of the six modules is presented below. Detailed technical 

descriptions of the modules can be found in the HAZUS technical manuals.4
46 FEMA HAZUS-MH PROGRAM

B OVERVIEW OF HAZUS

Module 1: Potential Earth Science Hazard (PESH)

The Potential Earth Science Hazard module estimates ground motion and ground failure 

(landslides, liquefaction, and surface fault rupture). Ground motion demands in terms of 

spectral acceleration (SA) and peak ground acceleration (PGA) are typically estimated based 

on the location, size and type of earthquake, and the local geology.

For ground failure, permanent ground deformation (PGD) and probability of occurrence are 

determined. GIS-based maps for other earth science hazards, such as tsunami and seiche 

inundation, can also be incorporated. In the current study, hazard data from the US Geological 

Survey is used. 

Module 2: Inventory and Exposure Data

Built into HAZUS is a national-level basic exposure database that allows a user to conduct a 

preliminary analysis without having to collect any additional local data. The general stock of 

buildings is classified by occupancy (residential, commercial, etc.) and by model building type 

(structural system, material and height). The default mapping schemes are state-specific for 

the single-family occupancy type and region-specific for all other occupancy types. They are 

age- and building-height specific. 

The four inventory groups are: general building stock, essential and high potential loss 

facilities, transportation systems, and utilities. The infrastructure within the study region 

must be inventoried in accordance with the standardized classification tables used by 

the methodology. These groups are defined to address distinct inventory and modeling 

characteristics. A description of the model building types can be further examined in Chapter 3 

of the HAZUS technical manual. 

Population data is based on the 2000 United States Census5 and estimates for building 

exposure are based on default values for building replacement costs (dollars per square 

foot) for each model building type and occupancy class, in addition to certain regional cost 

modifiers. Data also were drawn from Dun and Bradstreet and RS Means. 

5 U.S. Bureau of the Census, “Standard Tape File 3,” STF-3, 2002
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 47

 OVERVIEW OF HAZUS B

6 Kircher, C.A., et al., “Estimation of Earthquake Losses to Buildings,” Earthquake Spectra, Vol. 13, No. 4, 1997, pp. 703-720.

Module 3: Direct Damage

This module provides damage estimates for each of the four inventory groups based on the 

level of exposure and the vulnerability of structures (potential for damage at different ground 

shaking levels). 

A technique using building fragility curves based on the inelastic building capacity and sitespecific response spectra is used to describe the damage incurred in building components6. 

Since damage to nonstructural and structural components occurs differently, the methodology 

estimates both damage types separately. Nonstructural building components are grouped into 

drift-sensitive and acceleration-sensitive components.

For both essential facilities and general building stock, damage state probabilities are 

determined for each facility or structural class. Damage is expressed in terms of probabilities of 

occurrence of specific damage states, given a level of ground motion and ground failure. Five 

damage states are identified - none, slight, moderate, extensive and complete. 

Module 4: Induced Damage

Induced damage is defined as the secondary consequence of an event. This fourth module 

assesses dams and levees for inundation potential, and hazardous materials sites for release 

potential. Fire following an earthquake and accumulation of debris are also assessed. 

Module 5: Direct Losses

Unlike many previous loss estimation methods, HAZUS-MH provides estimates for both 

economic and social losses. Economic losses include structural and non-structural building 

losses, costs of relocation, losses to business inventory, capital-related losses, income losses, 

and rental losses. Social losses are quantified in terms of casualties, displaced households, 

and short-term shelter needs. The output of the casualty module includes estimates for four 

levels of casualty severity at three daily time periods and for six occupancies and commuters. 

Casualties, caused by secondary effects such as heart attacks or injuries while rescuing 

trapped victims, are not included. 

Shelter needs are estimated based on the number of structures that are uninhabitable, which 

in turn is evaluated by combining damage to the residential building stock with utility service 

outage relationships. 
48 FEMA HAZUS-MH PROGRAM

B OVERVIEW OF HAZUS

Module 6: Indirect Losses

This module evaluates the long-term effects on the regional economy from earthquake losses. 

The outputs in this module include income and employment changes by industrial sector7.

7 Brookshire, D.S., et al., Direct and Indirect Economic Losses from Earthquake Damage, Earthquake Spectra, Vol. 13, No. 4, 1997, 

pp. 683-702.
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 49

PROBABILISTIC HAZARD DATA PREPARATION AND AEL COMPUTATION C

C Probabilistic Hazard Data 

Preparation and AEL 

Computation

The U.S. Geological Survey (USGS) provided the probabilistic seismic hazard data for the 

entire United States. A three-step process was used to convert the data into a HAZUScompatible format. 

Step 1: Compute the PGA, SA@0.3 and SA@1.0 at each grid point for

the eight return periods. 

The USGS provided the hazard data as a set of 18 (or 20) intensity probability pairs for each 

of the approximately 150,000 grid points used to cover the United States. For each grid point, a 

linear interpolation of the data was used to calculate the ground motion values corresponding 

to each of the eight return periods used in this study (100, 250, 500, 750, 1000, 1500, 2000, 

and 2500 years). 

Table C-1 provides an example of the USGS hazard data for an individual grid point. In 

the table, for each of the 18 intensity-probability pairs, the intensity of the ground motion 

parameters (PGA, SA @ 0.3 sec. and SA @ 1.0 sec.) is shown along with the corresponding 

Annual Frequency of Exceedence (AFE). Step 2: Compute the PGA, SA@0.3 and SA@1.0 at 

each census tract centroid for the eight return periods. 

For estimating losses to the building inventory, HAZUS uses the ground shaking values 

calculated at the centroid of the census tract. To incorporate the USGS data into HAZUS, the 

ground shaking values at the centroid were calculated from the grid-based data developed in 

Step 1. 
50 FEMA HAZUS-MH PROGRAM

C PROBABILISTIC HAZARD DATA PREPARATION AND AEL COMPUTATION

#

Ground Motion Data 

PGA AFE

SA

(0.3 sec) AFE

SA

(1.0 sec) AFE

1 5.00E-03 2.49E-02 5.00E-03 3.28E-02 2.50E-03 2.85E-02

2 7.00E-03 2.07E-02 7.50E-03 2.89E-02 3.75E-03 2.37E-02

3 9.80E-03 1.65E-02 1.13E-02 2.40E-02 5.63E-03 1.84E-02

4 1.37E-02 1.25E-02 1.69E-02 1.85E-02 8.44E-03 1.34E-02

5 1.92E-02 8.76E-03 2.53E-02 1.30E-02 1.27E-02 9.24E-03

6 2.69E-02 5.86E-03 3.80E-02 8.45E-03 1.90E-02 6.25E-03

7 3.76E-02 3.87E-03 5.70E-02 5.29E-03 2.85E-02 4.23E-03

8 5.27E-02 2.64E-03 8.54E-02 3.36E-03 4.27E-02 2.95E-03

9 7.38E-02 1.90E-03 1.28E-01 2.27E-03 6.41E-02 2.14E-03

10 1.03E-01 1.43E-03 1.92E-01 1.63E-03 9.61E-02 1.60E-03

11 1.45E-01 1.08E-03 2.88E-01 1.19E-03 1.44E-01 1.18E-03

12 2.03E-01 7.73E-04 4.32E-01 8.28E-04 2.16E-01 8.08E-04

13 2.84E-01 5.06E-04 6.49E-01 5.03E-04 3.24E-01 4.83E-04

14 3.97E-01 2.88E-04 1.30E+00 1.30E-04 4.87E-01 2.36E-04

15 5.56E-01 1.35E-04 1.95E+00 3.84E-05 7.30E-01 9.04E-05

16 7.78E-01 4.88E-05 2.92E+00 7.62E-06 1.09E+00 2.60E-05

17 1.09E+00 1.32E-05 4.38E+00 9.76E-07 1.64E+00 5.08E-06

18 1.52E+00 2.80E-06 6.57E+00 8.61E-08 2.46E+00 6.62E-07

Table C-1. Example of the USGS Hazard Data

Step 2: Compute the PGA, SA@0.3 and SA@1.0 at each census tract

centroid for the eight return periods. 

For estimating losses to the building inventory, HAZUS uses the ground shaking values 

calculated at the centroid of the census tract. To incorporate the USGS data into HAZUS, the 

ground shaking values at the centroid were calculated from the grid-based data developed in 

Step 1. 

Two rules were used to calculate the census-tract-based ground shaking values: 

1. For census tracts that contain one or more grid points, the average values of the 

points are assigned to the census tract. 
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 51

PROBABILISTIC HAZARD DATA PREPARATION AND AEL COMPUTATION C

2. For census tracts that do not contain any grid points, the average value of the four 

nearest grid points is assigned to the census tract. Using this method, census-tractbased ground motion maps are generated for all eight return periods. 

Step 3: Modify the PGA, SA@0.3 and SA@1.0 at each census tract

centroid to represent site-soil conditions for a NEHRP soil class

type D. 

The USGS data were based on a National Earthquake Hazard Reduction Program (NEHRP) 

soil class type B/C (medium rock/very dense soil). For this study, NEHRP soil class type D 

(stiff soil) was assumed for all analyses. To account for the difference in soil class types, the 

data developed in Step 2 were modified. The procedure described in Chapter 4 of the HAZUS 

technical manual was used for the modification of the ground shaking values. 

Average Annualized Earthquake Loss Computation

After the hazard data was processed, an internal analysis module in HAZUS transformed the 

losses from all eight scenarios into an Annualized Earthquake Loss (AEL). 

The calculation of AEL is illustrated in Table C-2A. HAZUS computes Annual Losses for eight 

probabilistic return periods as shown in the Return Period column. The Annual Probability of 

the occurrence of the event is 1/RP. The Differential Probabilities is obtained by subtracting the 

Annual Occurrence Probabilities. Next the Average Loss is computed by averaging the Annual 

Losses associated to various return periods as shown in the column Average Losses. Once 

average loss is computed, the Average Annualized Loss is the summation of the product of the 

Average Loss and Differential Probability of experiencing this loss. Table C-2B shows a sample 

computation for Average Annualized Loss.

Figure C-1 illustrates schematically a HAZUS example of eight loss-numbers plotted against 

the exceedence probabilities for the ground motions used to calculate these losses. 

HAZUS computes the AEL by estimating the area under the loss probability curve as 

represented in Figure C-1. This area represents an approximation to the AEL and is equivalent 

to taking the summation of the differential probabilities multiplied by the average loss for the 

corresponding increment of probability. In effect, one is approximating the area under the curve 

by summing the area of horizontal rectangular slices. 

The choice for the number of return periods was important for evaluating average annual 

losses, so that a representative curve could be connected through the points and the area 
52 FEMA HAZUS-MH PROGRAM

C PROBABILISTIC HAZARD DATA PREPARATION AND AEL COMPUTATION

under the probabilistic loss curve be a good approximation. The constraint on the upper bound 

of the number was computational efficiency vs. improved marginal accuracy. To determine the 

appropriate number of return periods, a sensitivity study was completed that compared the 

stability of the AEL results to the number of return periods for 10 metropolitan regions using 

5, 8, 12, 15 and 20 return periods. The difference in the AEL results using eight, 12, 15 and 20 

return periods was negligible.

Table C-2A and B Average Annualized Earthquake Loss Computation

# Return 

Period

Annual 

Probabilities

Differential Probabilities Annual 

Losses Average Losses Annualized Loss

Formula Values

1 2500 0.00040 P2500 0.00040 L2500 L2500 P2500 x L2500

2 2000 0.00050 P2000 - P2500 0.00010 L2000 (L2500+L2000)/2 (P2000 - P2500) x (L2500+L2000)/2

3 1500 0.00067 P1500 - P2000 0.00017 L1500 (L2000+L1500)/2 (P1500 - P2000) x (L2000+L1500)/2

4 1000 0.00100 P1000 - P1500 0.00033 L1000 (L1500+L1000)/2 (P1000 - P1500) x (L1500+L1000)/2

5 750 0.00133 P750 - P1000 0.00033 L750 (L750+L1000)/2 (P750 - P1000) x (L750+L1000)/2

6 500 0.00200 P500 - P750 0.00067 L500 (L750+L500)/2 (P500 - P550) x (L750+L500)/2

7 250 0.00400 P250 - P500 0.00200 L250 (L250+L500)/2 (P250 - P500) x (L250+L500)/2

8 100 0.01000 P100 - P250 0.00600 L100 (L100+L250)/2 (P100 - P250) x (L100+L250)/2

∑ ( )

# Return 

Period

Annual 

Probabilities

Differential 

Probabilities

Annual 

Losses

Average Losses 

(Billions of $)

Annualized Loss

(Billions of $)

1 2500 0.00040 0.00040 5.700 5.700 0.00228

2 2000 0.00050 0.00010 5.290 5.495 0.00055

3 1500 0.00067 0.00017 4.660 4.975 0.00083

4 1000 0.00100 0.00033 3.020 3.840 0.00128

5 750 0.00133 0.00033 2.600 2.810 0.00094

6 500 0.00200 0.00067 1.900 2.250 0.00150

7 250 0.00400 0.00200 1.020 1.460 0.00292

8 100 0.01000 0.00600 0.425 0.723 0.00434

0.01463
ESTIMATED ANNUALIZED EARTHQUAKE LOSSES FOR THE UNITED STATES 53

PROBABILISTIC HAZARD DATA PREPARATION AND AEL COMPUTATION C

Figure C-1.

Probabilistic Loss 

Curve