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and Quality (AHRQ) is the lead agency

charged with supporting research

designed to improve the quality of

health care, reduce its cost, address

patient safety and medical errors, and

broaden access to essential services.

AHRQ sponsors and conducts research

that provides evidence-based

information on health care outcomes;

quality; and cost, use, and access. 

The information helps health care

decisionmakers—patients and 

clinicians, health system leaders, and

policymakers—make more informed

decisions and improve the quality of

health care services.

Bioterrorism

and Health System Preparedness

Issue Brief

Mass Prophylaxis: Building Blocks

for Community Preparedness

No. 10

In the event of a bioterrorist attack or the

outbreak of a naturally occurring disease,

communities may be faced with the need

to administer mass prophylaxis to their

citizens. The goal will be twofold: to

administer the appropriate antibiotic or

vaccine to everyone who needs it in time

to protect them from becoming infected,

and to limit hospital admissions to those

who are symptomatic and in need of

treatment. Developing the capability for

such a response is a major challenge for

local health systems and for the

communities they serve. 

Background

Over the past 5 years, the Agency for

Healthcare Research and Quality (AHRQ)

has funded five projects conducted by the

Weill Medical College of Cornell

University to provide tools that local

planners can use to prepare their

communities for mass prophylaxis. The

first project was the development under

an AHRQ contract of a computer

simulation model for planning a city-wide

response to a bioterrorist attack. Four

additional products have grown or are

growing out of that original model:

▲ Community-Based Mass Prophylaxis:

A Planning Guide for Public Health

Preparedness

▲ Bioterrorism and Epidemic Outbreak

Response Model (BERM)

▲ Regional Hospital Caseload

Calculator (RHCC) Model

▲ Modeling the U.S. Health System’s

Epidemic Response Capacity

The Planning Guide explains the

components that a community must have

in place to prepare for mass prophylaxis.

BERM, a companion piece to the

Planning Guide, is an interactive database

for planners to calculate the number of

facilities and staff they will need in their

communities to administer mass

prophylaxis. The Regional Hospital

Caseload Calculator starts with a given

community’s capability to administer

mass prophylaxis and computes, on a

daily basis, the number of people who can

be reached with prophylaxis and the

number of people who will become ill

Advancing Excellence in Health Care • www.ahrq.gov

Agency for Healthcare Research and Quality
and require hospitalization. The project

that is currently underway, Modeling

the U.S. Health System’s Epidemic

Response Capacity, will start with the

capability to administer mass

prophylaxis, add local hospital bed

capacity, and calculate pre-hospital

response, hospital-based response, and

the need for assistance from outside

the region. Taken together, these four

tools constitute the building blocks for

community preparedness for mass

prophylaxis.

Community-Based

Mass Prophylaxis: A

Planning Guide for

Public Health

Preparedness

The cornerstone of the Weill/Cornell

research on building community

preparedness for mass prophylaxis is

Community-Based Mass Prophylaxis:

A Planning Guide for Public Health

Preparedness. Local officials—

including policymakers, public health

and emergency management planners,

and non-public health emergency

response professionals—can use the

Planning Guide to determine how

mass prophylaxis fits into emergency

planning and what resources are

needed to make mass prophylaxis

work. The Guide is also of interest to

State and Federal government officials

and members of industry, academia,

the media, and non-governmental

organizations, all of whom play roles

in supporting the response to public

health emergencies. 

The Planning Guide has four sections,

each for a different audience. “Section

One: Overview of Mass Prophylaxis”

is directed to a general audience,

including policymakers. It explains the

“who, what, where, when, and how” of

planning for mass prophylaxis. Actual

administration of prophylaxis will be

conducted in Dispensing/Vaccination

Centers or Clinics (DVCs). “Section

Two: Fundamentals of DVC Design”

and “Section Three: Examples of

Antibiotic Dispensing and Vaccination

Clinic Plans” are directed to public

health and emergency management

planners who will be responsible for

establishing and operating DVCs.

“Section Four: Clinic

Management/Command Structure” is

directed to non-public health

emergency response professionals who

will be involved in coordinating

response following the guidelines of

the National Incident Management

System (NIMS).

Section One: Overview of

Mass Prophylaxis

Effective public health response to a

bioterrorist attack or a natural disease

outbreak depends on four factors: 

▲ Recognition of the outbreak. 

▲ Rapid mobilization of resources to

the affected area.

▲ Dispensing of antibiotics or

vaccines to the affected population.

▲ Follow-up with patients to confirm

that the intervention has been

appropriate and effective.

In the past 5 years the Federal

government has taken steps to increase

capacity for response to disease

outbreak. The Centers for Disease

Control and Prevention (CDC)

operates a number of mechanisms to

facilitate recognition. CDC also

manages the Strategic National

Stockpile, which contains medical

supplies that can be deployed rapidly

to treat thousands of patients who

might be affected. The Federal

Emergency Management Agency

(FEMA) in the Department of

Homeland Security manages the

National Disaster Medical System,

which was established to provide rapid

response capability. All of these

Federal assets, however, are intended to

supplement, not supplant,

comprehensive local planning and

operations for mass prophylaxis. 

The Planning Guide explains how the

local community can prepare for mass

prophylaxis. Figure 1 displays the “who,

what, where, when and how” that

comprise the elements—including

DVCs—of a local mass prophylaxis plan. 

The “who” includes, of course, health

care professionals and officials from

public health and local health care

systems. But planning must start with

an understanding of the community’s

population, taking into consideration

such factors as population density and

whether translation services will be

needed. Law enforcement officers will

be needed to maintain public order at

DVC sites, guard the medical

stockpile, and conduct a criminal

investigation if the disease outbreak is

the result of an attack. Emergency

management officials will be needed

to coordinate response, including

liaison with the local media to ensure

that the information disseminated is

accurate and consistent.

The “what” includes generic office and

medical supplies and easily overlooked

items such as coolers for the

medication and tables and chairs for

staff. Transportation must be

considered, both to deliver supplies to

the DVCs and to transport those who

need medical attention to health care

facilities.

The “where” includes location of the

DVCs in relation to population density

2
and access to transportation. In

addition, DVCs will require physical

facilities with a certain amount of

space, storage capability, and water and

electrical supplies. 

The “when” may be a local decision, or

the activation may come from regional,

State, or Federal authorities. Even if

activation is triggered at higher levels of

government, however, DVC deployment

and operation will remain under local

control. 

The “how” is centered on incident

command and management. 

Section Two: Fundamentals of

DVC Design

This section is directed to public health

and emergency management planners,

who will be responsible for determining

how many DVCs will be necessary for

their community and how any

personnel will be needed to staff those

Centers. The section explains the

concept of DVC operations, discusses

patient flow through the DVC, and

presents an overview of a method for

estimating clinic and staff numbers.

DVC Operations. DVCs are intended

to dispense large volumes of

medications or vaccines to protect

people before they become infected and

to identify those who are symptomatic

and in need of hospitalization. The

concept of DVC operations is explained

in terms of core functions and support

functions. Core functions (called

“operations” in incident management

terminology), with a few exceptions,

directly facilitate the dispensing of

drugs and vaccines. Core functions

include: 

▲ Greeting

▲ Form distribution

▲ Triage

▲ Medical evaluation

▲ Transportation assistance

▲ Mental health evaluation

▲ Briefing

▲ Drug triage (pharmacotherapeutic

evaluation)

▲ Dispensing or vaccination

▲ Form collection and exit

The number of functions that are

actually performed depends upon

patient flow requirements.

Support functions (called “logistics” in

incident management terminology)

include: 

▲ Drug/vaccine inventory,

preparation, and/or resupply

3

Elements of a Local Mass Prophylaxis Plan

1. Population

1. Location

2. Size

4. Access

6. Support 

Services

3. Security

1. Planning

3. Public

Information

5. Storage

7. Communication

2. Public Health

4. Health Care Professionals

6. Community Relations

8. Media

3. Emergency 

Management

5. Law 

Enforcementment

9. Liaison 

(Interagency/

Interregional) E. How

C. Where

A. Who

B. What

D. When

Mass

Prophylaxis

Plan

Figure 1

7. Health Care System

3. Emergency 

Management

2. Regional/

Federal

Activation

2. Incident

Command/

Management

6. Transportation

4. Floor/Flow Plan

2. Staff

5. Support

Services

3. Protocols

1. Supplies and 

Stockpiles
▲ Patient traffic directors

▲ Data entry

▲ Translation services

▲ Communications/information

technology support

▲ Food service

▲ Facilities maintenance

▲ Security

▲ Managers

Again, the number of functions that

are actually performed will depend on

the situation. 

DVC Design. The Guide recommends

that planners develop a single generic

DVC design, including floor plan and

patient flow plan, for use throughout

their communities. The design will

depend on local needs, including

population size, staff resources, and

response time. Six patient flow plans

are discussed, from basic to complex.

Figure 2 shows the basic high-flow

model with entry screening. This floor

plan was used in Operation TriPOD, a

high-flow antibiotic dispensing exercise

in New York City in May 2002, and

attained patient flow rates of more

than 1,000 per hour. The Guide also

discusses potential bottlenecks in patient

flow and provides recommendations on

both how to prevent them and how to

respond to them. 

Number of DVCs and Staff. Planners

can determine the number of DVCs

they will use for a mass prophylaxis

campaign in one of three ways:

▲ Based on the total number of sites

available in the community.

▲ Deciding on the number of staff

needed to operate a center.

▲ Estimating the maximum patient

flow rate at a standard DVC.

Each has advantages and

disadvantages. The Guide provides

formulas and explains calculations for

estimates of patient flow rates per

DVC and community-wide. 

To determine the number of personnel

needed to staff a DVC, planners are

referred to the Bioterrorism and

Epidemic Outbreak Response Model

(BERM), the automated spreadsheet

that is the companion piece to the

Planning Guide. (See p. 5)

Section Three: From

Principles to Practice:

Examples of Antibiotic

Dispensing and Vaccination

Clinic Plans

Section three explains the procedures

to be followed for antibiotic

dispensing and vaccination.

Procedures are explained in the

context of what needs to be

accomplished (the objectives of mass

prophylaxis) and are accompanied by

model flow charts.

Mass antibiotic prophylaxis would be

needed for outbreaks of disease caused

by any of the three bacterial pathogens

on the CDC list of Category A agents:

anthrax, plague, or tularemia. The

most important goal in antibiotic

dispensing is to get the correct

antibiotic to the correct patient in the

shortest amount of time. 

The procedures to be followed for

vaccination are more complex than for

antibiotic dispensing, so more stations

and staff are required in each DVC.

The Planning Guide explains those

complexities and provides detailed

guidance on the procedures for

smallpox vaccination. 

Section Four: Clinic

Management/Command

Structure

A bioterrorism event or infectious

disease outbreak could result in mass

casualties that would require the use of

local, State, and Federal medical

stockpiles; coordination of multiple

local, State, and Federal agencies,

including law enforcement and public

health; and outreach to the local

community for prophylaxis and

treatment. Thus, the response to such

4

High-Flow with Entry Screening

Figure 2

Greeting/Entry

Screening

Medical

Evaluation

Drug

Dispensing

Triage

Healthcare

Center

Home
an event epitomizes the type of

complex, multi-jurisdictional operation

for which NIMS has been designed. As

the primary point of contact for

prophylaxis and treatment, DVCs are a

critical part of the larger response.

DVC operations must, therefore, have a

clearly defined command structure that

integrates seamlessly into the broader

command structure. The Planning

Guide shows non-public health

emergency response professionals how

that can be done.

For public health planners, the

Planning Guide explains how the DVC,

command structure should be organized

using the titles and terminology of

incident command. The Guide

describes the responsibilities of all

command staff positions (which are

separate from the core and support

functions described in Section Two) and

lays out the requirements for a DVC

operational guide, or “site action plan.” 

The Importance of

Modeling

The Planning Guide describes the

component parts of a community mass

prophylaxis plan and how those parts

fit together and function. The

subsequent three Weill/Cornell projects

are computer models that generate

concrete numbers to use in planning.

The value of modeling is to help

planners question their common

assumptions about what it would take

to respond to a large mass casualty

incident. Modeling permits analysis of

the variables involved (time, numbers

of patients, resources available, etc.) in

quantitative terms so that planners can

work with concrete numbers as they

develop and modify their strategies. 

The Bioterrorism and

Epidemic Outbreak

Response Model

(BERM)

BERM is an interactive computer

model that allows users to develop

realistic plans for their local

jurisdictions in response to a

bioterrorism event or epidemic

outbreak. Users enter their working

assumptions on such variables as the

size of the population to be treated, the

duration of the campaign, and how

quickly they can process patients. The

model then generates data on how

many dispensing stations will be

needed and how many core staff and

support staff will be needed in each

station. 

Section One: Inputs

Section one, allows the user to enter

data based on specific local needs and

resources. Basic data fields include the

size of the population to be treated and

the number of days the prophylaxis

campaign will last, plus the number of

hours per day the clinics will be open

and how many shifts will be needed.

More complicated data fields are as

follows:

▲ Patient flow—The single most

important number for the model is

the patient flow rate. If the user

knows the anticipated per-clinic

flow rate, that number can be

entered. Alternatively, the model

can calculate the flow rate based on

the number, size, and duration of

mandatory briefings for all patients

passing through the clinic. This

calculation is based on the fact that

the flow rate through the entire

clinic cannot exceed the rate at

which patients are briefed. 

▲ Clinic layout—The model

performs calculations for response

to a communicable or noncommunicable agent. If planning is

for a communicable disease such as

smallpox, the user can choose

whether to include two possible

optional stations: crisis/isolation

counseling (which would require

adding mental health staff) and

testing (which would require

additional staff to test for

pregnancy, HIV, etc.) 

▲ Process times—The user can select

one of three predetermined sets of

process time estimates: “Baseline”

(representing averages based partly

on data from live, large-scale

dispensing exercises in the United

States over the last two years),

“slow” (slower than “baseline”), or

“fast” (best-case scenarios). For

example, the “baseline” time

estimate for vaccination is 2

minutes, for “slow” it is 3 minutes,

and for “fast,” 1 minute. 

▲ Event characteristics—After

selecting for a communicable or

noncommunicable agent, the user

can select from one of three

possible event scenarios: 

– Pre-event, in which the

prophylaxis campaign would

operate prior to the occurrence of

any illness from the target

biological agent; 

– Small-scale event, in which the

campaign would operate in

response to a small-scale

bioterrorist event or outbreak

(defined as 5-10 percent of the

population who present to clinics

having been exposed); 

- Large-scale event, in which the

campaign would operate in

response to a large-scale

5
6

bioterrorist event or outbreak

(defined as 10-20 percent of the

population who present to clinics

having been exposed). 

For example, the percentage of patients

requesting crisis counseling at a

vaccination clinic is estimated at 5

percent in a pre-event scenario, 10

percent in a small-scale event, and 15

percent in a large-scale event. These

percentages have obvious staffing

implications. 

The final part of section one, “User

Inputs,” provides a summary of the

values the user has entered. The user

then returns to the “Table of Contents”

page and proceeds section by section to

see the results calculated by the model,

enter additional information for more

detailed calculations, and get a

complete picture of requirements for

the local prophylaxis response plan. 

Section Two: Overall Model

Outputs

Basic outputs include the number of

clinics required, the number of core

staff for each clinic, and the total

number of core staff for all clinics.

Section Three: StationSpecific Staffing

Presents station-by-station estimates of

the optimal number of core staff

needed to operate each clinic. If there is

a local limit on the total core staff size

per clinic, the user can enter the

maximum number of core staff that can

be expected. BERM will then recalculate the number of staff per

station. 

Section Four: Support Staff

Calculations

The first part of this section lists

critical support staff functions and the

recommended number of staff for each

function. Recommended numbers are

presented as a range, based on a ratio

of either core staff to support staff or

patient flow to support staff. After the

user selects the ratio appropriate for the

local site, BERM calculates the number

of support staff needed per site per

shift, plus the total number of support

staff per clinic per shift and for the

entire campaign. 

Section Five: Summary of

Model Results

The model calculates a summary of

estimated core and support staffing

requirements per clinic and for the

entire campaign. 

Section Six: Campaign

Modifications Due to Limited

Staff

All calculations generated by the model

produce optimum numbers. Section six

allows the user to see how much of the

optimum can be accomplished with the

actual number of available staff. A

limited number of core staff may force

a decrease in the number of people

who can be processed or an increase in

the time required to process an entire

population. 

At any point in this process, the user

can change values. The model will

recalculate accordingly.

A final option for BERM users is to

calculate estimates of recommended

per-clinic and campaign-wide core staff

and support staff based on user inputs.

However, instead of using the pre-set

process times (baseline, slow, or fast)

and the event scenarios (pre-event,

small-scale, or large-scale) from

Section One, the user can enter each

process time and population proportion

individually. BERM will perform these

calculations based on the customized

data that have been entered by the user.

Thus, the “customizable staffing

model” offers more flexibility but

requires more inputs. 

The Regional Hospital

Caseload Calculator

(RHCC) Model

While BERM calculates staff resources

that will be needed for a mass

prophylaxis campaign, the Regional

Hospital Caseload Calculator (RHCC)

model calculates the proportion of the

population that can be reached by that

campaign and, consequently, the

proportion that will need to be treated in

the hospital system. 

The basic concept of the RHCC model

is presented in Figure 3. This

illustration of pre-hospital capacity was

developed by Dr. Nathaniel Hupert, the

principal investigator for development

of the Weill/Cornell models, and his

colleagues. The figure shows that

degree of protection is a function of

how long it takes the community to

respond to the attack or outbreak (delay

in reaction) and the time required to

administer medication to the affected

population (time needed to protect

community). 

Dr. Hupert and his colleagues have

translated this concept into the RHCC

model. The formulas in the model start

with consensus estimates about the

biological agent and incorporate a set

of assumptions about detection,

effectiveness of treatment, and patient

compliance with medication. The type

of agent, the speed with which a

prophylaxis response is initiated once

an outbreak has been identified, and the

maximum population that the

campaign can protect when operating

at full capacity all have an impact on

the number of people who become
symptomatic and require hospital care.

The model allows for daily changing

probabilities of becoming symptomatic

or receiving prophylaxis and calculates

the changing proportion of the

population that is symptomatic and

requires hospital resources as each day

of the epidemic passes. Thus, the model

illustrates the importance of prehospital treatment in reducing hospital

surge. Applied differently, the model

also predicts when surge is most likely

to occur.

The RHCC model is currently

configured to calculate outcomes for

anthrax, bubonic plague, tularemia, or

pandemic flu. It requires only six

inputs, which may be actual or

hypothetical:

▲ Total population/community size.

▲ Number of people exposed to the

pathogen. 

▲ Percentage of exposed people who

will develop symptoms if not

treated.

▲ Number of days following the

attack the prophylaxis campaign

can begin (0-10).

▲ Number of days from start of

campaign to reach maximum

prophylaxis capacity.

▲ Maximum number of people to

whom prophylactic antibiotics could

be delivered per day.

The last three inputs are critical

components of each jurisdiction’s

response strategy. Based on the six

inputs, the RHCC calculates four

results. 

The first result is the proportion of

exposed individuals in the target

population who would be protected by

post-exposure prophylaxis campaigns

that differ by two functions: how

quickly after exposure prophylaxis

begins, and how long it takes to

complete the prophylaxis campaign.

The shorter the delay and the shorter

the time to complete, the higher the

proportion of people protected. 

The second result is the number of

casualties (people sick with the BT

illness), by day. Results are displayed in

three formats:

▲ Total number of people who

become sick.

▲ Number of people who become sick

on each succeeding day (0-30).

▲ Graph depicting number of exposed

people developing sickness, by day. 

The graph is especially valuable for

illustrating the magnitude of the surge

in demand on hospital treatment.

The third result is the number (rather

than proportion) of people protected, by

day. Results are displayed in the same

format as the number of casualties.

▲ The total number of people

protected by prophylaxis.

▲ The number protected from

sickness on each succeeding day

(0-30).

▲ Graph depicting number of people

protected, by day.

The fourth result offers information on

how outcomes would be different if the

campaign strategy were modified.

These include the additional number of

people who would be protected if the

prophylaxis campaign began one day

earlier or were completed one day

earlier. In the event the campaign could

not be initiated immediately, the model

would also calculate the additional

number of people who would be

protected if the campaign reached full

capacity without any ramp-up. 

Using the model, planners can take one

exposure scenario, play it out in a

number of different ways, and wind up

with very different daily and total

casualty loads depending on how the

community has been organized and

how successful the community is in

responding to that event. The RHCC

model demonstrates how critical it is

for communities to develop the

capability to respond immediately and

to have the personnel resources and

materiel available to complete

prophylaxis as quickly as possible. 

7

Modeling Pre-Hospital Capacity

Long (Days)

None (Hours)

More

Less

Shorter (1-2 Days) Longer (4+ Days)

DELAY 

IN

REACTION

SAFE

PROTECTION

Time needed to protect community

Figure 3
Modeling the U. S.

Health System’s

Epidemic Response

Capacity 

The Weill/Cornell team currently is

building upon and expanding the

RHCC model. The RHCC can calculate

outcomes for anthrax, bubonic plague,

tularemia, or pandemic flu. The new

project is developing models for all six

Category A bioterrorist agents and

SARS. The RHCC calculates the

number of people who can be protected

by prophylaxis and the number who will

need hospitalization. The models being

developed under the new project will

project capacity for pre-hospital and

hospital-based response and the need for

assistance from outside the region.

With funding by AHRQ, Dr. Hupert

and his colleagues have analyzed three

determinants of surge capacity. The

first is surge arrivals at the hospital, a

function of (1) the number of people

who have been exposed or involved in

an event and (2) the possible treatment

of patients outside the hospital, or “prehospital management.” As the RHCC

model shows, the number of surge

arrivals will depend on how many

patients can be accommodated by prehospital management. Once patients

arrive at the hospital or network of

health care facilities (eg, clinics,

rehabilitation facilities, and long-term

care facilities) the second determinant

of surge capacity is the availability of

hospital resources. The number of

patients who can be treated during a

surge event depends on factors such as

number of staff, quantities of medical

supplies, and circulation of beds. The

circulation of beds, in turn, depends to

some extent on the third determinant,

which is surge discharge. The concept of

surge discharge is that some patients

who were already in the hospital at the

time of the event may be transferred to

other facilities, thus making space

available for surge arrivals.

The Modeling U.S. Health System’s

Epidemic Response Capacity project

has two components. The first, which

has been completed, involved the

evaluation of patterns of emergency

health service utilization during an

actual public health emergency. It was

based on patient surges at eight New

York City emergency departments

during the 2001 anthrax attacks. Using

administrative data from the New York

Presbyterian Healthcare System, the

study assessed neighborhood-byneighborhood variability in patient

arrivals. The response of the public to

such an emergency has important

implications for mass prophylaxis

planning. 

The second component will assess

health system capacity by developing

discrete event simulation models of

hospital treatment for the six Category

A bioterrorist agents and SARS.

Models will balance hospital bed

capacity in each of the 313 United

States Hospital Referral Regions against

simulated epidemic curves that reflect

both disease and public health response

variables. Given one of the scenarios and

based on local capacity, the model will

project pre-hospital response, hospitalbased response, and need for assistance

from outside the region.

For More Information

Community-Based Mass Prophylaxis: A

Planning Guide for Public Health

Preparedness and BERM are available

on the AHRQ Web site

(www.ahrq.gov/browse/bioterbr.htm).

Dr. Hupert and his colleagues are

developing a Web-based version of the

Regional Hospital Caseload Calculator,

which will be available soon on the

AHRQ Web site. Tools developed under

the Modeling U.S. Health System’s

Epidemic Response Capacity project

will be posted on the AHRQ Web site as

they become available.

AHRQ’s Bioterrorism

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This issue brief was prepared for

AHRQ by the National Academy for

State Health Policy (NASHP) under

contract number 290-98-0009.

8

The RHCC model 

demonstrates how critical

it is for communities to

develop the capability to

respond immediately and

to have the personnel

resources and materiel

available to complete 

prophylaxis as quickly as

possible.

AHRQ Pub. No. 06-0050

June 2006