Risk Assessment of the 

Public Health Impact of 

Escherichia coli O157:H7 

in Ground Beef 

7 

 Prepared for the Food Safety and Inspection Service 

 by the Escherichia coli O157:H7 Risk Assessment Team 

List of Contributors to the 

Escherichia coli O157:H7 Risk Assessment 

This U.S. Department of Agriculture, Food Safety and Inspection Service risk assessment was 

developed with contributions from the following organizations: 

• U.S. Department of Agriculture, Food Safety and Inspection Service 

• U.S. Department of Agriculture, Economic Research Service 

• U.S. Department of Health and Human Services, Food and Drug Administration 

• U.S. Department of Health and Human Services, Centers for Disease Control and 

Prevention 

• National Advisory Committee on Microbiological Criteria for Foods 

• Interagency Food Risk Assessment Group 

• North Carolina State University 

• University of Delaware 

• University of Maryland 

• David Vose Risk Services 

• University of Tasmania 

The E. coli O157:H7 risk assessment has been reviewed by individuals chosen from these 

organizations for their diverse perspectives and technical expertise. The purpose of this review 

was to provide candid and critical comments that will assist the Food Safety and Inspection 

Service in developing a scientifically sound risk assessment. The review comments and draft 

manuscripts remain confidential to protect the integrity of the deliberative process. 

The organizations listed above have provided many constructive comments and suggestions. It 

must be emphasized, however, that responsibility for the final content of this report rests entirely 

with the U.S. Department of Agriculture, Food Safety and Inspection Service. 

September 7, 2001 iii 

Contents 

EXECUTIVE SUMMARY 1 

1 INTRODUCTION 7 

Purpose of the E. coli O157:H7 Risk Assessment 8 

Structure of the E. coli O157:H7 Risk Assessment 9 

Scope of the E. coli O157:H7 Risk Assessment 10 

Results of the E. coli O157:H7 Risk Assessment 11 

History of the E. coli O157:H7 Risk Assessment Project 13 

Organization of the Remainder of this Report 14 

References 14 

2 HAZARD IDENTIFICATION 17 

Escherichia coli 17 

Sources of E. coli O157:H7 19 

Epidemiology of Disease due to Infection with E. coli O157:H7 19 

Transmission of E. coli O157:H7 21 

Adverse Health Outcomes Associated with E. coli O157:H7 22 

Pathogenesis 24 

Factors Affecting Survival and Growth of E. coli O157:H7 in Food 25 

References 26 

3 EXPOSURE ASSESSMENT 31 

Production Module 31 

Slaughter Module 58 

Preparation Module 74 

References 98 

4 HAZARD CHARACTERIZATION 105 

Definition of Key Terms 106 

Estimating the Response 107 

Deriving the Dose-Response Function for E. coli O157:H7 113 

Estimating Severe Clinical Outcomes due to E. coli O157:H7 Infection 121 

Sensitive Subpopulations 123 

Validation of the E. coli O157:H7 Dose-Response Function Using Outbreak Data 123 

References 125 

September 7, 2001 v 
5 RISK CHARACTERIZATION 129 

Definition of Key Terms 129 

Risk of Illness from E. coli O157:H7 131 

Population Risk by Season, Age, and Location 137 

Sensitivity Analysis 141 

Conclusions 151 

Limitations 153 

Research Needs 154 

References 155 

APPENDIX A ANCHORING OF MODEL PARAMETERS 157 

APPENDIX B SUMMARY OF HUMAN CLINICAL TRIALS OF FOODBORNE PATHOGENS 163 

September 7, 2001 vi 
Executive Summary 

The Office of Public Health and Science (OPHS) in the U.S. Department of Agriculture’s Food 

Safety and Inspection Service (USDA/FSIS) conducted a farm-to-table risk assessment to 

evaluate the public health impact from Escherichia coli O157:H7 in ground beef. This risk 

assessment was initiated in response to the identification of E. coli O157:H7 in cattle, on 

carcasses, and in ground beef, as well as heightened public awareness of the association of E. 

coli O157:H7 with foodborne outbreaks that have resulted in severe illness and death. The 

purpose of this risk assessment is to systematically evaluate and integrate available scientific 

data and information to 

• provide a comprehensive evaluation of the risk of illness from E. coli O157:H7 in ground 

beef based on currently available data, 

• estimate the likelihood of human morbidity and mortality associated with specific 

numbers of E. coli O157:H7 in ground beef servings, 

• estimate the occurrence and extent of E. coli O157:H7 contamination at points along the 

farm-to-table continuum, 

• provide a tool for analyzing how to most effectively mitigate the risk of illness from E. 

coli O157:H7 in ground beef (one that is useful for Pathogen Reduction and Hazard 

Analysis and Critical Control Point applications), 

• identify future food safety research needs, and 

• assist FSIS in the review and refinement of its integrated risk reduction strategy for E. 

coli O157:H7 in ground beef. 

BACKGROUND 

E. coli O157:H7 was first recognized as a foodborne pathogen with major public health 

consequences in 1982, when it was associated with two outbreaks of bloody diarrhea in Oregon 

and Michigan. An estimated 62,000 cases of symptomatic E. coli O157:H7 infections occur 

annually in the United States due to foodborne exposures, resulting in approximately 1,800 

hospitalizations and 52 deaths. As many as 3,000 cases may develop hemolytic uremic syndrome 

annually. Surveillance data indicate that the highest incidence of illness from E. coli O157:H7 

occurs in children under 5 years of age. 

September 7, 2001 1 
Executive Summary 

Epidemiological evidence indicates that ground beef is a primary source of human exposure 

to E. coli O157:H7. Between 1982 and 1993, ground beef was identified as the transmission 

source in 54% of E. coli O157:H7 outbreaks. Of the E. coli O157:H7 outbreaks reported between 

1993 and 1998, most (72%) were foodborne. Of the foods implicated in these outbreaks, ground 

beef was the most common (45%) source. Studies of sporadic cases of E. coli O157:H7 illness 

also identified ground beef as the primary source of human exposure. 

As the public health regulatory agency responsible for ensuring that meat and poultry 

products are properly labeled, wholesome, and safe, FSIS took additional steps to prevent the 

occurrence of E. coli O157:H7 in ground beef sold to the U.S. public, including improving its 

sampling and detection methods for E. coli O157:H7 in ground beef, strengthening consumer 

education initiatives that are focused on proper cooking and handling of ground beef, and setting 

policy declaring E. coli O157:H7 in raw ground beef an adulterant. On August 18, 1998, FSIS 

announced plans to develop the farm-to-table risk assessment documented in this report. 

STRUCTURE AND SCOPE OF THE E. COLI O157:H7 RISK ASSESSMENT 

The E. coli O157:H7 risk assessment is a baseline risk assessment in that it reflects, to the extent 

practicable, a full range of current practices, behaviors, and conditions in the farm-to-table 

continuum (production, slaughter, processing, transportation, storage, preparation, and 

consumption) (Figure ES-1). Scientific data and information available through July 2001 were 

integrated into the generally accepted framework for microbiological risk assessments: hazard 

identification (Chapter 2), exposure assessment (Chapter 3), hazard characterization (Chapter 4), 

and risk characterization (Chapter 5). Each component of the assessment has a distinct role. 

Exposure Assessment

Production

On-Farm

Transport

Marketing of live

animals

Slaughter

Dehiding

Evisceration

Splitting

Chilling

Cutting

Preparation

Grinding

Transportation

Storage

Distribution

Cooking

Consumption

Hazard

Characterization

Dose-response

relationship

Risk

Characterization

Risk estimates

Morbidity and

mortality

Hazard

Identification

Ecology

Pathogenesis

Epidemiology

Predictive

microbiology

FIGURE ES-1 Farm-to-table risk assessment model for E. coli O157:H7 in ground beef. 

Hazard identification characterizes E. coli O157:H7 using data from ecology, pathology, 

epidemiology, and microbiology. 

September 7, 2001 2 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Exposure assessment comprises three modules—production, slaughter, and preparation—and 

uses probabilistic techniques to model the prevalence and concentration of E. coli O157:H7 in 

live cattle, carcasses, beef trim, and, ultimately, a single serving of cooked ground beef. Data for 

the exposure assessment include herd and within-herd prevalence of E. coli O157:H7, slaughter 

processing conditions including decontamination steps, consumer and retail storage and cooking 

behaviors contributing to the growth or decline in the number of E. coli O157:H7 organisms in 

ground beef servings, and consumer demographics (e.g., age of the consumer and location of the 

meal) and consumption patterns. Seasonal differences in herd prevalence of E. coli O157:H7 

infection were also included. 

Hazard characterization quantifies the nature and severity of the adverse health effects (i.e., 

illness or death) (response) associated with exposure to a given number of E. coli O157:H7 

organisms in a ground beef serving (dose). For E. coli O157:H7, the precise relationship between 

the number of organisms consumed and the resulting adverse human health event is not known. 

The E. coli O157:H7 dose-response function was derived using information from three sources: 

(1) the estimated annual number of symptomatic E. coli O157:H7 infections due to ground beef 

exposure, (2) the estimated number of contaminated ground beef servings from the exposure 

assessment, and (3) the lower and upper bound dose-response curves derived using surrogate 

pathogens. The upper and lower bound dose-response curves describe the uncertainty about the 

probability of symptomatic illness at an ingested dose (the median E. coli O157:H7 doseresponse function). Seasonal variability in reported E. coli O157:H7 cases was also included. 

Risk characterization integrates the results of the exposure assessment and hazard 

characterization to estimate the risk of illness from E. coli O157:H7 in ground beef. Risk 

estimates are provided for individuals, a community in a simulated outbreak scenario, and the 

U.S. population. The variability of risk among the U.S. population is considered according to 

differences in seasonal exposure and host susceptibility (based on the age of the consumer). Also 

included in the risk characterization is a sensitivity analysis to identify factors that most 

influence the occurrence and number of E. coli O157:H7 organisms in ground beef and the 

subsequent risk of illness. Factors that most influence the risk of illness, but for which there were 

limited data and information, are identified as important food safety research areas. 

As announced in the Federal Register (Volume 63, page 44232), this risk assessment is 

confined to E. coli O157:H7 exposure from the consumption of ground beef servings (e.g., 

hamburgers, meat balls, and meat loaf) in the United States. Only E. coli O157:H7 generated 

from infected cattle and subsequent contaminated beef trim and ground beef were considered. 

Exposures from cross-contamination or other sources of E. coli O157:H7 (e.g., nonground beef 

foods, water, and fomites) were outside the scope of this assessment. This risk assessment also 

does not explicitly model imported beef as distinct from domestic beef. However, seasonal 

variation in the incidence of E. coli O157:H7 infection in U.S. cattle and human population is 

included. 

RESULTS OF THE E. COLI O157:H7 RISK ASSESSMENT

The risk assessment yields intermediate and final outputs in the form of distributions that 

characterize the variability and uncertainty in estimates of a variety of risk assessment endpoints 

or human illnesses. The exposure assessment indicates that feedlot cattle (steers and heifers) 

have a higher prevalence of E. coli O157:H7 infection than culled breeding cattle (cows and 

bulls) and that prevalence is higher during June to September than October to May. Although 

only a fraction of infected live cattle result in contaminated carcasses, thousands of pounds of 

meat trim from these carcasses are combined in the grinding process. Consequently, although the 

September 7, 2001 3 
Executive Summary 

number of E. coli O157:H7 organisms in these grinder loads may be quite low, the proportion of 

grinder loads that contain at least 1 E. coli O157:H7 organism is expected to be high. Most 

ground beef servings are cooked in the United States. Less than 0.007% to 0.018% (depending 

on seasonal exposure) of cooked ground beef servings contain E. coli O157:H7 organisms. 

However, considerable uncertainty exists regarding the frequency of cooked ground beef 

servings that have 1 or more E. coli O157:H7 present. 

The median probability of illness for the general U.S. population due to E. coli O157:H7 

from a serving of ground beef is estimated to be 9.6 × 10-07 or about 1 illness in every 1 million 

servings. Based on a U.S. population risk of illness from E. coli O157:H7-contaminated ground 

beef, the per serving probability of being hospitalized but recovering is 2.0 × 10-8, of developing 

HUS is 4.2 × 10-9, and of death is 5.9 × 10-10. When variation in seasonal exposure is considered, 

the risk of illness from E. coli O157:H7 is about 1 in every 600,000 ground beef servings 

consumed during June through September and about 1 in every 1.6 million ground beef servings 

consumed during October through May. In general, children aged 0 to 5 have an almost 2.5 times 

higher risk of illness (2.4 × 10-6) from E. coli O157:H7 in ground beef than does the general U.S. 

population. 

Factors that most influence the occurrence and extent of E. coli O157:H7 contamination in 

ground beef and subsequent risk of illness were identified using sensitivity analyses. The 

occurrence and extent of E. coli O157:H7 contamination in beef trim and subsequent grinder 

loads was most influenced by feedlot and within-feedlot prevalence, occurrence and extent of 

carcass contamination, effectiveness of decontamination procedures, and the effect of carcass 

chilling. The occurrence and extent of E. coli O157:H7 contamination in cooked ground beef 

servings was most influenced by the proportion of ground beef that was frozen, the maximum E. 

coli O157:H7 population density in ground beef servings, and storage and cooking conditions. 

The importance of these factors varied by season (June to September or October to May). 

Although some factors influenced the occurrence of E. coli O157:H7 in combo bins, grinder 

loads, or ground beef servings, others were more important in influencing the extent of E. coli

O157:H7 contamination in these units. Because the overall U.S. population risk of illness from 

E. coli O157:H7 in ground beef is influenced more by the number of contaminated ground beef 

servings than by the amount of E. coli O157:H7 in a contaminated ground beef serving, these 

differences among identified influential factors may be important. 

RESEARCH NEEDS 

The E. coli O157:H7 risk assessment is structured to allow incorporation of additional data as 

they become available. The determination of which data would be most beneficial is based on 

areas identified as important and for which there is limited information. Several areas of food 

safety research would strengthen the certainty of estimates from this risk assessment, including 

• additional information on E. coli O157:H7 contamination of carcasses following 

dehiding; 

• data on the effect of carcass chilling on increases or decreases in E. coli O157:H7 

organisms; 

• predictive microbiological data on the increase and decrease in the number of E. coli

O157:H7 organisms in ground beef under various storage and preparation conditions 

along with estimates of the frequencies of occurrence of these storage and preparation 

conditions; 

September 7, 2001 4 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

• information on the maximum density of E. coli O157:H7 organisms in ground beef 

servings as a result of matrix effects, competitive microflora in ground beef, and 

environmental conditions (e.g., pH, water activity); and 

• Data on retail (hotels, restaurants, and institutions [HRI]) and consumer storage, cooking, 

and consumption (frequency and serving size) patterns by type of ground beef meal (e.g., 

grilled hamburger or baked meat loaf) and season. 

NEXT STEPS 

Some cautions on the appropriate use of this risk assessment should be noted. First, the 

conclusions are based on current data and scientific assumptions. Additional data will be 

incorporated into the model as they become available. Second, the results provide only part of 

the information needed by decision makers and regulators. This risk assessment does not address 

such issues as cost, feasibility, or effectiveness of possible interventions. These analyses are 

necessary before deciding which of many possible policies should be implemented regarding E. 

coli O157:H7 in ground beef. 

Future plans for this risk assessment include evaluating the effect that various mitigation 

strategies may have in decreasing the occurrence of E. coli O157:H7 in ground beef and 

associated human illnesses. FSIS also plans to expand the risk assessment to include other beef 

products (i.e., nonintact beef). 

FSIS is releasing this report documenting the baseline risk assessment on E. coli O157:H7 in 

ground beef for public comment and scientific peer review by the National Academy of 

Sciences. Thus, the risk assessment is a “work in progress.” FSIS invites public input to further 

strengthen this farm-to-table baseline risk assessment for E. coli O157:H7 in ground beef. 

September 7, 2001 5 

1 

Introduction 

Escherichia coli O157:H7 was first recognized as a foodborne pathogen with major public health 

consequences in 1982, when it was associated with two outbreaks of bloody diarrhea in Oregon 

and Michigan (Riley et al. 1983). Between 1982 and 1998, over 4,400 cases of human illness 

resulted from 203 outbreaks that involved exposure to E. coli O157:H7 (CDC unpublished data). 

Of these cases, 968 (22%) were hospitalized, 228 (5%) progressed to hemolytic uremic 

syndrome (HUS) or thrombotic thrombocytopenic purpura (TTP), and 28 (0.6%) died. 

Surveillance data indicate that the highest incidence of illness from E. coli O157:H7 occurs in 

children under 5 years of age (CDC 1999a). 

Epidemiological evidence indicates that ground beef is the primary source of human 

exposure to E. coli O157:H7. Between 1982 and 1993, ground beef was identified as the 

transmission source in 54% of E. coli O157:H7 outbreaks (Griffin 1995). Of the E. coli O157:H7 

outbreaks reported between 1993 and 1998, most (72%) were foodborne. Of the foods implicated 

in these outbreaks, beef was the most common (45%) source. When specified, 90% of the time 

the beef product was ground (CDC 1999b; CDC 2000; CDC 2001). Studies of sporadic cases of 

E. coli O157:H7 illness also identified ground beef as the primary source of human exposure 

(MacDonald et al. 1988; Le Saux et al. 1993; Mead et al. 1997; Slutsker et al. 1998; Kassenborg 

et al. 2001). 

As the public health regulatory agency responsible for ensuring that meat and poultry 

products are properly labeled, wholesome, and safe, the Food Safety and Inspection Service 

(FSIS) took the following additional steps to prevent the occurrence of E. coli O157:H7 in 

ground beef sold to the U.S. public: 

September 7, 2001 7 
1. Introduction 

• In August 1994, FSIS declared that ground beef containing E. coli O157:H7 is 

adulterated under the Federal Meat Inspection Act unless further processed in a manner 

that destroys this pathogen.1 

• On October 17, 1994, FSIS initiated a microbiological testing program for E. coli 

O157:H7 in raw ground beef in meat plants and retail stores.2 The initial testing program 

was established and designed to test approximately 5,000 raw ground beef samples per 

year, 50% from federally inspected plants and 50% from retail stores. 

• In 1998, because of the low concentrations of E. coli O157:H7 recovered from samples 

of frozen ground beef patties identified in 1993 and 1997 E. coli O157:H7 outbreaks in 

Colorado3,4, FSIS increased the microbiological testing sample size from 25 grams to 

325 grams. The increased sample sizes were necessary to improve detection of E. coli 

O157:H7 in raw ground beef sold to consumers. 

• In August 1998, FSIS initiated a consumer education campaign encouraging use of food 

thermometers to ensure that ground beef is cooked to an internal temperature of at least 

160°F (FSIS 1998). 

• In September 1999, FSIS introduced a more sensitive laboratory test for E. coli O157:H7 

that used an additional selective capture step based on immunomagnetic separation 

(FSIS 1999).5 

• In February 1999, FSIS proposed to permit the use of ionizing radiation for treating 

refrigerated or frozen uncooked meat food products to reduce the concentration of 

foodborne pathogens, including E. coli O157:H7 (Federal Register, Volume 64, pages 

9089-9105).6

PURPOSE OF THE E. COLI O157:H7 RISK ASSESSMENT 

In addition to setting new standards and improving microbiological testing for E. coli O157:H7 

in ground beef, on August 18, 1998, FSIS announced plans to conduct a farm-to-table risk 

assessment (Federal Register, Volume 63, page 44232). The result was the risk assessment 

documented in this report. The overall goals of this risk assessment are to 

• provide a comprehensive evaluation of the risk of illness from E. coli O157:H7 in 

ground beef based on currently available scientific data, 

• estimate the likelihood of human morbidity and mortality associated with specific 

numbers of E. coli O157:H7 in ground beef servings, 

 

1If a ground beef sample is confirmed positive, FSIS inspectors will condemn the sampled lot unless it is fully 

cooked (in accordance with 9 CFR 318.23) or processed in a way that would eliminate the pathogen (FSIS 

Directive 10,010.1). FSIS Directive 8080.1 Rev. 2 (11-3-92) outlines the basic procedures for recall of an 

inspected meat or poultry product. 

2In December 1994, the agency won a court challenge of the policy and the testing program. The testing program 

operated under FSIS Notice 50-94, issued on December 23, 1994, until the agency issued FSIS Directive 

10,010.1 on February 1, 1998. 

3The most probable number (MPN) of E. coli O157:H7 recovered from six samples from the 1993 outbreak ranged 

from 30 to 1,500 organisms per 100 grams (Johnson et al. 1995; Marks et al. 1998). 

4Tuttle et al. (1999) reported an MPN of 67 E. coli O157:H7 organisms per uncooked patty. 

5Consequently, recent increases in the reported frequency of E. coli O157:H7 detection reflect, at least in part, 

increased sample sizes and the use of a more sensitive test for detection of E. coli O157:H7. 

6The Final Rule for the Irradiation of Meat Food Products was published on December 23, 1999 (Federal Register, 

Volume 64, pages 72149-72166). 

September 7, 2001 8 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

• estimate the occurrence and extent of E. coli O157:H7 contamination at points along the 

farm-to-table continuum, 

• provide a tool for analyzing how to most effectively mitigate the risk of illness from E. 

coli O157:H7 in ground beef (one that is useful for Pathogen Reduction and Hazard 

Analysis and Critical Control Point applications), 

• identify future food safety research needs, and 

• assist FSIS in the review and refinement of its integrated risk reduction strategy for E. 

coli O157:H7 in ground beef. 

STRUCTURE OF THE E. COLI O157:H7 RISK ASSESSMENT 

The E. coli O157:H7 risk assessment follows the generally accepted structure for 

microbiological risk assessments: hazard identification, exposure assessment, hazard 

characterization, and risk characterization. Hazard identification serves to identify biological 

agents that may be present in a particular food or groups of food and are capable of causing 

adverse health effects. Exposure assessment is the quantitative evaluation of the likely intake of 

biological agents via food, as well as exposures from other sources, if relevant. Hazard 

characterization is the quantitative evaluation of the adverse health effects associated with the 

hazard. This step includes a dose-response assessment that determines the relationship between 

the magnitude of exposure dose to a biological agent and the frequency of associated adverse 

health effects (response). Finally, risk characterization is the process of determining the 

quantitative estimation, including attendant uncertainties, of the frequency of occurrence and 

severity of adverse health effects in a given population based on the hazard identification, 

exposure assessment, and hazard characterization. 

The E. coli O157:H7 risk assessment provides numerical expressions of risk and an 

indication of the attendant uncertainties. Scientific data are the foundation of this risk 

assessment. This risk assessment includes data available through July 2001. By integrating 

scientific data through a structured process, the E. coli O157:H7 risk assessment provides 

information that links policy and science. A structured process is essential to risk assessment 

because describing risk rarely involves the certainty of direct, measurable observations relevant 

to human health; instead, it involves statistical estimation and prediction, as well as transparent 

expression of uncertainty. 

The E. coli O157:H7 risk assessment is a baseline risk assessment in that it reflects, to the 

extent practicable, a full range of current practices, behaviors, and conditions in the farm-to-table 

continuum (production, slaughter, processing, transportation, storage, preparation, and 

consumption) (Figure 1-1). This risk assessment is intended to assist FSIS risk managers in 

identifying potential areas along the farm-to-table continuum to control E. coli O157:H7. Using 

this baseline risk assessment, risk managers will identify a set of feasible control options to 

analyze. Use of the risk assessment to evaluate different control strategies is known as 

conducting a scenario analysis. Subsequent scenario analyses using the E. coli O157:H7 risk 

assessment will provide FSIS decision makers with information concerning the efficacy of 

alternative mitigation strategies and a tool to evaluate these strategies to decrease the number of 

human illnesses resulting from E. coli O157:H7 in ground beef. A sensitivity analysis is included 

with this baseline risk assessment to provide FSIS risk managers with information on (1) the 

potential areas to consider in reviewing and refining mitigation strategies and (2) the most 

important data gaps and key uncertainties for future data collection and research. 

September 7, 2001 9 
1. Introduction 

Production

On-Farm

Transport

Marketing of live

animals

Slaughter

Dehiding

Evisceration

Splitting

Chilling

Cutting

Preparation

Grinding

Transportation

Storage

Distribution

Cooking

Consumption

Hazard

Characterization

Dose-response

Number ill

Severity of illness

Mortality

Risk

Characterization

Risk es

Important

Researc

timates

 variables

h needs

FIGURE 1-1 Risk assessment structure for E. coli O157:H7 in ground beef. 

SCOPE OF THE E. COLI O157:H7 RISK ASSESSMENT 

As announced in the Federal Register (Volume 63, page 44232), the scope of this risk 

assessment is confined to ground beef products, based on an analysis of available epidemiologic 

data (Mead et al. 1999).7 At the broadest level of aggregation, the scope of the assessment 

includes two classes of product: (1) products consisting of 100% ground beef and (2) other 

products containing ground beef. Due to the lack of available data, the scope of the assessment 

does not distinguish ground beef products (i.e., hamburger or meat patties [as defined in 9 CFR 

319.15] that also contain comminuted beef processed by means other than grinding [e.g., 

mechanical separation and partial defatting]). 

A number of factors were considered in assessing the risk of illness from E. coli O157:H7 in 

ground beef, including (1) the number of illnesses and severity of these illnesses caused by E. 

coli O157:H in ground beef; (2) the likelihood of E. coli O157:H7 (hazard) being present in a 

ground beef serving (exposure); (3) the likelihood that exposure to a given number of E. coli

O157:H7 in a ground beef serving will cause illness (dose-response); (4) the probability of 

illness from E. coli O157:H7 in ground beef servings (risk); (5) consideration of the risk of 

illness from several perspectives (individual, community, and population); (6) the variation in 

population exposure (e.g., seasonal exposure) and response (e.g., by age category, children under 

5 years of age) (variability); (7) identification of production, slaughter, and preparation practices 

and conditions that influence the likelihood of exposure to E. coli O157:H7 in ground beef or the 

subsequent risk of illness (sensitivity analysis); and (8) limitations in the current state of 

knowledge (uncertainty). 

Beyond the scope of the present risk assessment are nonintact cuts of beef in which E. coli 

O157:H7 may be introduced below the surface of the whole cut. This may occur by means of 

injection, mechanical tenderizing, or reconstruction (e.g., beef that has been scored to 

incorporate a marinade or that has been cubed and mechanically tenderized, and restructured 

beef products such as gyros). Contamination may also occur in a comminution process such as 

chopping, flaking, or mincing (e.g., fresh veal sausage and fabricated beefsteak) the whole cut. 

If, however, such a comminuted beef product is combined with ground beef in the formulation of 

 

7On January 19, 1999, FSIS announced that, in addition to ground beef, beef trimmings defined as intact are 

considered adulterated if they contain E. coli O157:H7. FSIS said resulting processed products from the 

contaminated trimmings are considered adulterated and must not be distributed until they have been processed 

into a ready-to-eat product (i.e., a food product that may be consumed safely without any further cooking or 

other preparation) (Federal Register, Volume 64, pages 2803-2805). For a discussion of more recent 

developments regarding FSIS policy for beef products contaminated with E. coli O157:H7, see the Federal 

Register, Volume 65, pages 6881-6886. 

September 7, 2001 10 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

a food product, it is included in the scope of this risk assessment. FSIS plans to incorporate 

nonintact beef products that are beyond the scope of the present assessment in future iterations of 

this risk assessment model. 

This risk assessment also does not explicitly model imported beef as distinct from domestic 

beef. Approximately 15% of the fresh, chilled, and frozen beef and veal consumed in the United 

States originates from outside the country, and 90% of such imports are from Australia, New 

Zealand, and Canada (APHIS:VS:CEAH 1994). Specific data regarding the prevalence of E. coli

O157:H7 in beef imported from various countries are lacking, and published surveillance data 

from the three major exporters to the U.S. are variable. However, evidence does indicate that E. 

coli O157:H7 occurs in Australian, New Zealand, and Canadian cattle and humans (Robins–

Browne et al. 1998; New Zealand Public Health Report 2000; Spika et al. 1998). In general, this 

evidence does not suggest that the prevalence of E. coli O157:H7 is dramatically greater in those 

countries than in the United States. Therefore, the assumption of equivalence in contamination of 

imported and domestic product is likely conservative in the model. 

As announced in the Federal Register (Volume 63, page 44232), the scope of the analysis 

does not extend beyond beef as a vehicle of infection. A common concern expressed in public 

comments submitted to the docket and during the October 28, 1998, public meeting was that the 

proposed scope of the analysis was limited to foods containing ground beef and thereby omitted 

other important sources of E. coli O157:H7 infection, such as vegetables, produce, juice, water, 

and person-to-person transmission. However, FSIS determined that to make the analysis 

tractable, and in light of resource and time constraints, the scope of the assessment would 

necessarily have to be fixed or defined. Furthermore, the Centers for Disease Control and 

Prevention (CDC) recently estimated the total disease burden of E. coli O157:H7 from all 

products based on epidemiologic surveillance data (Mead et al. 1999). Consequently, there has 

been no attempt to quantitatively model cross-contamination or other sources of E. coli O157:H7 

(e.g., nonbeef food products, water, and fomites). Similarly, there are currently no plans to 

quantitatively model secondary infections resulting from person-to-person contact. The delimited 

scope of the analysis has been taken into account in comparing the results predicted by the 

baseline risk assessment model with estimates of illnesses derived from observed epidemiologic 

data (Mead et al. 1999). 

An increased seasonal incidence of E. coli O157:H7 infections in U.S. cattle and human 

populations has been previously demonstrated in the warm months (i.e., June to September) 

(Hancock et al. 1997a, 1997b; Griffin 1998). Seasonal patterns are also demonstrated for Canada 

(Van Donkersgoed et al. 1997) and likely occur in other countries. Seasonal effects were 

modeled in this risk assessment using data on the prevalence of E. coli O157:H7 within infected 

cattle herds. To improve the certainty of modeling seasonal variability for the risk of illness from 

E. coli O157:H7, additional data are needed on changes in the occurrence of E. coli O157:H7 in 

raw ground beef across seasons; changes in slaughter and processing practices by season; and 

changes in storage, handling, preparation, and consumption practices by season. 

RESULTS OF THE E. COLI O157:H7 RISK ASSESSMENT 

The risk assessment model yields intermediate and final outputs in the form of distributions that 

characterize the variability and uncertainty in estimates of a variety of risk assessment endpoints 

or human illnesses (Table 1-1). For hazard identification, outputs include information on the 

September 7, 2001 11 
1. Introduction 

TABLE 1-1 Outputs of the E. coli O157:H7 Risk Assessment 

Component Module Outputs 

Epidemiological information on human morbidity and mortality 

due to E. coli O157:H7 

Microbiological information on the pathogenesis of E. coli

O157:H7 compared with other E. coli strains 

Information on the source and transmission of E. coli O157:H7 

Hazard Identification 

Information on the environmental conditions that influence 

survival and growth (predictive microbiology) of E. coli

O157:H7 

Production Herd and within-herd prevalence rates for infected live cattle 

prior to slaughter for ground beef 

Prevalence of contaminated carcasses 

Number of E. coli O157:H7 organisms on contaminated 

carcasses 

Prevalence of contaminated combo bins of trim Slaughter 

Number of E. coli O157:H7 organisms in combo bins of 

contaminated trim 

Prevalence of contaminated grinder loads of ground product 

Number of E. coli O157:H7 organisms in contaminated grinder 

loads of ground product 

Prevalence of contaminated cooked ground beef servings 

Exposure Assessment 

Preparation 

Number of E. coli O157:H7 organisms in contaminated cooked 

ground beef servings 

Annual number of E. coli O157:H7 illnesses associated with 

cooked ground beef consumption 

Annual number of hospitalizations due to E. coli O157:H7 in 

cooked ground beef 

Annual number of cases of HUS/TTP due to E. coli O157:H7 in 

cooked ground beef 

Hazard 

Characterization 

Annual number of deaths due to E. coli O157:H7 in cooked 

ground beef 

Annual risk of illness from E. coli O157:H7 in cooked ground 

beef 

Annual risk of illness from E. coli O157:H7 in cooked ground 

beef by seasonal exposure and age of the consumer 

Identification of important variables that influence the risk of 

illness from E. coli O157:H7 in ground beef 

Risk Characterization 

Identification of important food safety research areas 

September 7, 2001 12 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

epidemiology, transmission, ecology, and pathogenesis of E. coli O157:H7. Exposure assessment 

outputs include the prevalence of E. coli O157:H7-infected cattle and the occurrence and number 

of E. coli O157:H7 in combo bins of beef trim, grinder loads of ground beef, and cooked ground 

beef servings. Primary outputs of the hazard characterization are the number and severity of 

human illnesses associated with a specific number of E. coli O157:H7 organisms per serving 

(dose) and a derived dose-response function. Final outputs of the risk assessment are provided in 

the risk characterization and include (1) estimates of the risk of illness from E. coli O157:H7-

contaminated ground beef for individuals, communities, and the U.S. population; (2) estimates of 

the U.S. population risk by season (June to September and May to October) and age (i.e., 

children under 5 years of age); (3) estimates of variables that are most responsible for 

influencing the likelihood of exposure to E. coli O157:H7 in ground beef servings and 

subsequent risk of illness; and (4) identification of important food safety research needs. 

HISTORY OF THE E. COLI O157:H7 RISK ASSESSMENT PROJECT 

Work on the E. coli O157:H7 baseline risk assessment in ground beef was initiated in March 

1998 when the Interagency Food Risk Assessment Group, convened by the Office of Risk 

Assessment and Cost Benefit Analysis, formed an informal resource group. This interagency 

group identified resources and available data to initiate this risk assessment and organized a 

public meeting to solicit comment and input at an early stage of this project about the 

• scope of the risk assessment, 

• analytical framework to be used in conducting the risk assessment, 

• scientific evidence acquired by the risk assessment team to date, and 

• existing data gaps identified by the risk assessment team. 

The public meeting was held on October 28, 1998, in Arlington, Virginia, and was attended 

by more than 60 individuals. At this meeting, FSIS released the “Preliminary Pathways and Data 

for a Risk Assessment of E. coli O157:H7 in Beef.” That document summarized the currently 

available data and potential foodborne exposure pathways under consideration for this risk 

assessment. 

Comments and additional data identified during the public meeting or submitted to the 

docket in response to the August 18, 1998, Federal Register Notice were evaluated for inclusion 

in the development of the baseline risk assessment. A complete transcript of the public meeting 

and all public submissions regarding the risk assessment are on file in the FSIS docket (Docket 

Number 98-037N, U.S. Department of Agriculture, Food Safety and Inspection Service, Room 

102, 300 12th Street, SW, Washington, DC 20250-3700). 

An interim draft of the E. coli O157:H7 baseline risk assessment was presented for public 

and scientific input at several meetings, including the 1998 Annual Meeting of the Society for 

Risk Analysis (SRA); the 1999 Annual Meeting of the International Association of Milk, Food 

and Environmental Sanitarians; a week-long interagency workshop on microbial risk held in 

April 1999; the 1999 Annual Meeting of the SRA; and the National Advisory Committee on 

Microbiological Criteria for Foods (NACMCF). A revised interim draft E. coli O157:H7 baseline 

risk assessment report incorporating public and scientific input from these meetings was 

developed. This interim draft report was presented to the public on February 29, 2000, to discuss 

FSIS policy regarding E. coli O157:H7. The presentation is available at 

http://www.fsis.usda.gov/OPHS/ecolrisk. 

Based on input from these meetings, this risk assessment has been substantially revised and 

strengthened. FSIS is releasing this report documenting the baseline risk assessment on E. coli

September 7, 2001 13 
1. Introduction 

O157:H7 in ground beef for public comment and scientific peer review by the National Academy 

of Sciences. This risk assessment is a “work in progress.” In finalizing the baseline E. coli

O157:H7 risk assessment, the agency will consider the comments of the National Academy of 

Sciences and public comments submitted to the FSIS docket within 60 days of the release date of 

this report. 

ORGANIZATION OF THE REMAINDER OF THIS REPORT 

This risk assessment report is divided into five chapters. Chapter 2 (hazard identification) 

provides information on the epidemiology, pathogenesis, transmission, and ecology of E. coli

O157:H7. Chapter 3 (exposure assessment) describes the occurrence and number of E. coli

O157:H7 organisms from farm to table. Chapter 4 (hazard characterization) discusses the 

derivation of a dose-response function for E. coli O157:H7. Chapter 5 (risk characterization) 

integrates the results of the previous chapters to provide estimates of the risk of illness from E. 

coli O157:H7 in ground beef. Risk characterization also includes a sensitivity analysis, 

identifying variables along the farm-to-table continuum that greatly influence the risk of illness 

from E. coli O157:H7. Variables that are identified as important but for which there is limited 

information are listed as areas for further research in Chapter 5. 

REFERENCES 

Animal and Plant Health Inspection Service (APHIS:VS:CEAH). 1994, March. Escherichia coli

O157:H7 Issues and Ramifications. Ft. Collins, CO. 

Centers for Disease Control and Prevention (CDC). 1999a. Summary of notifiable diseases, 

United States, 1998. MMWR 47(53):1-94. 

Centers for Disease Control and Prevention (CDC). 1999b. Surveillance for Outbreaks of 

Escherichia coli O157:H7 Infection. Summary of 1998 Data. Report from the National 

Center for Infectious Diseases, Division of Bacterial and Mycotic Diseases to CSTE. March 

8, 1999. 

Centers for Disease Control and Prevention (CDC). 2000. Escherichia coli O111:H8 outbreak 

among teenage campers—Texas, 1999. MMWR 49(15):321-324. 

Centers for Disease Control and Prevention (CDC). 2001. Surveillance for Outbreaks of 

Escherichia coli O157:H7 Infection. Summary of 1999 Data. Report from the National 

Center for Infectious Diseases, Division of Bacterial and Mycotic Diseases to CSTE. June 

15, 2000. 

Food Safety and Inspection Service (FSIS). August 18, 1998. Risk Assessment for E. coli

O157:H7 in Beef and Ground Beef. Notice; Request for Comments and Public Meeting 

Notice. Federal Register 63(159):44232. 

Food Safety and Inspection Service (FSIS). January 19, 1999. Beef Products Contaminated with 

Escherichia coli O157:H7. Federal Register 64(11):2803-2805. 

Food Safety and Inspection Service (FSIS). February 24, 1999. Irradiation of Refrigerated or 

Frozen Uncooked Meat, Meat Byproducts, etc. Proposed Rule. Federal Register 64(36):9089-

9105. 

Food Safety and Inspection Service (FSIS). December 23, 1999. Irradiation of Meat Food 

Products. Final Rule. Federal Register 64(246):72149-72166. 

September 7, 2001 14 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Food Safety and Inspection Service (FSIS). February 11, 2000. Recent Developments Regarding 

Beef Products Contaminated with Escherichia coli O157:H7; Public Meeting. Notice of 

Public Meeting. Federal Register 65(29):6881-6886. 

Food Safety and Inspection Service (FSIS). 1998. Revision 1 (9/3/1999) to Chapter 5, 

Microbiology Laboratory Guidebook, 3rd edition. (Available at: 

http://www.fsis.usda.gov/OPHS/microlab/mlgchpt5.htm). 

Food Safety and Inspection Service (FSIS). 1999. USDA Urges Consumers to use Food 

Thermometer when Cooking Ground Beef Patties. (Available at: 

http://www.fsis.usda.gov/OA/topics/gb.htm). 

Griffin, P.M. 1995. Escherichia coli O157:H7 and other enterohemorrhagic Escherichia coli. Pp. 

739-761 in Infections of the Gastrointestinal Tract, M.J. Blaser, P.D. Smith, J.I. Ravdin, H.B. 

Greenberg, and R.L. Guerrant, eds. New York: Raven Press, Ltd. 

Griffin, P.M. 1998. Epidemiology of Shiga toxin-producing Escherichia coli infections in 

humans in the United States. In Escherichia coli O157:H7 and Other Shiga Toxin-Producing 

E. coli Strains, J.B. Kaper and A.D. O’Brien, eds. Washington, DC: ASM Press. 

Hancock, D.D., T.E. Besser, D.H. Rice, D.E. Herriott, and P.I. Tarr. 1997a. A longitudinal study 

of Escherichia coli O157 in fourteen cattle herds. Epidemiol Infect 118:193-195. 

Hancock, D.D., D.H. Rice, D.E. Herriot, T.E. Besser, E.D. Ebel, and L.V. Carpenter. 1997b. 

Effects of farm manure handling practices on Escherichia coli O157 prevalence in cattle. J 

Food Prot 60:363-366. 

Johnson, J.L., B.E. Rose, A.K. Sharar, G.M. Ransom, C.P. Lattuada, and A.M. McNamara. 

1995. Methods used for detection and recovery of Escherichia coli O157:H7 associated with 

a food-borne disease outbreak. J Food Prot 58(6):597-603. 

Kassenborg, H., C. Hedberg, M. Hoekstra, M.C. Evans, A.E. Chin, R. Marcus, D. Vugia, K. 

Smith, S. Desai, L. Slutsker, P. Griffin, and the FoodNet Working Group. 2001. Farm visits 

and undercooked hamburgers as major risk factors for sporadic Escherichia coli O157:H7 

infections—data from a case-control study in five FoodNet sites. Manuscript in preparation. 

Le Saux, N., J.S. Spika, B. Friesen, I. Johnson, D. Melnychuck, C. Anderon, R. Dion, M. 

Rahman, and W. Tostowaryk. 1993. Ground beef consumption in noncommercial settings is 

a risk factor for sporadic Escherichia coli O157:H7 infection in Canada [letter]. J Infect Dis 

167:500-502. 

MacDonald, K.W., M.J. O’Leary, M.L. Cohen, P. Norris, J.G. Wells, E. Noll, J.M. Kobayashi, 

and P.A. Blake. 1988. Escherichia coli O157:H7, an emerging gastrointestinal pathogen: 

Results of a one-year, prospective, population-based study. JAMA 259(24):3567-3570. 

Marks, H.M., M.E. Coleman, C.T.J. Lin, and T. Roberts. 1998. Topics in risk assessment: 

Dynamic flow tree process. Risk Anal 18:309-328. 

Mead, P.S., L. Finelli, M.A. Lambert-Fair, D. Champ, J. Townes, L. Hutwagner, T. Barrett, K. 

Spitalny, and E. Mintz. 1997. Risk factors for sporadic infection with Escherichia coli

O157:H7. Arch Intern Med 157:204-208. 

Mead, P.S., L. Slutsker, V. Dietz, L.F. McCaig, J.S. Bresee, C. Shapiro, P.M. Griffin, and R.B. 

Tauxe. 1999. Food-related illness and death in the United States. Emerg Infect Dis 5(5):607-

625. 

New Zealand Public Health Report. 2000, July/August. Shiga-Toxin Producing Escherichia coli

(STEC) Cases Increase Again in 1999. ISSN 1173-0250. Vol. 8, No. 7/8. 

Riley, L.W., R.S. Remis, S.D. Helgerson, H.B. McGee, J.G. Wells, B.R. Davis, R.J. Hebert, E.S. 

Olcott, L.M. Johnson, N.T. Hargrett, P.A. Blake, and M.L. Cohen. 1983. Hemorrhagic colitis 

associated with a rare Escherichia coli serotype. New Engl J Med 308:681-685. 

September 7, 2001 15 
1. Introduction 

Robins-Browne, R.M., E. Elliot, and P. Desmarchelier. 1998. Shiga toxin-producing Escherichia 

coli in Australia. In Escherichia coli O157:H7 and Other Shiga Toxin-Producing E. coli

Strains, J.B. Kaper and A.D. O’Brien, eds. Washington, DC: ASM Press. 

Slutsker, L., A.A. Ries, K. Maloney, J.G. Wells, K.D. Greene, P.M. Griffin, and the Escherichia 

coli O157:H7 Study Group. 1998. A nationwide case-control study of Escherichia coli

O157:H7 infection in the United States. J Infect Dis 177:962-966. 

Spika, J.S., R. Khakhria, P. Michel, D. Milley, J. Wilson, and J. Waters. 1998. Shiga toxinproducing Escherichia coli infections in Canada. In Escherichia coli O157:H7 and Other 

Shiga Toxin-Producing E. coli Strains, J.B. Kaper and A.D. O’Brien, eds. Washington, DC: 

ASM Press. 

Tuttle, J., T. Gomez, M.P. Doyle, J.G. Wells, T. Zhao, R.V. Tauxe, and P.M. Griffin. 1999. 

Lessons from a large outbreak of Escherichia coli O157:H7 infections: Insights into the 

infectious dose and method of widespread contamination of hamburger patties. Epidemiol 

Infect 122:183-192. 

Van Donkersgoed, J., K.W.F. Jericho, and H. Grogan. 1997. Preslaughter hide status of cattle 

and the microbiology of carcasses. J Food Prot 60(12):1502-1508. 

September 7, 2001 16 
2 

Hazard Identification 

Escherichia coli O157:H7, a Shiga toxin-producing E. coli, was first recognized as a human 

pathogen in 1982, when it was associated with two outbreaks of hemorrhagic colitis (bloody 

diarrhea). The outbreaks occurred in Oregon and Michigan and involved the consumption of 

hamburgers from a fast-food chain (Riley et al. 1983). The spectrum of infection with E. coli

O157:H7 includes asymptomatic fecal shedding of the organism; nonbloody or bloody diarrhea 

accompanied by abdominal cramps, vomiting, and occasionally fever; postdiarrheal hemolytic 

uremic syndrome (HUS); and thrombotic thrombocytopenic purpura (TTP). The continued 

occurrence of widespread outbreaks and an increase in the incidence of reported cases have led 

to the designation of E. coli O157:H7 as an emerging pathogen. Since 1982, epidemiologic 

studies have shown that E. coli O157:H7 can be transmitted through water (by drinking or 

swimming in contaminated water), food, or person-to-person contact, especially in a daycare 

setting. Ground beef continues to be a significant source of E. coli O157:H7 infection in humans. 

This chapter on hazard identification begins with a discussion of the importance of E. coli 

O157:H7 in the context of other Shiga toxin-producing E. coli. The chapter then discusses the 

sources of E. coli O157:H7; its epidemiology, including the types of food and risk factors 

associated with infection; adverse health outcomes; and the organism’s pathogenesis. The factors 

that contribute to the growth and persistence of E. coli O157:H7 in the environment are then 

discussed. 

ESCHERICHIA COLI 

Multiple genetic subtypes of E. coli exist; many are part of the normal mammalian intestinal 

flora and do not cause disease in humans. E. coli strains that cause diarrheal illness are 

categorized into specific groups on the basis of virulence properties, mechanisms of 

pathogenicity, and clinical syndromes. These categories include enteropathogenic E. coli 

(EPEC), enterotoxigenic E. coli (ETEC), enteroinvasive E. coli (EIEC), diffuse-adhering E. coli

(DAEC), enteroaggregative E. coli (EaggEC), and Shiga toxin-producing E. coli (STEC). E. coli

September 7, 2001 17 
2. Hazard Identification 

O157:H7 is in the STEC group and can produce Shiga toxin 1, Shiga toxin 2, or both. Shiga 

toxin production alone may not be enough to cause illness. In addition to Shiga toxin, some 

strains of STEC contain genes that code for the ability to attach and damage intestinal tract cells, 

causing what is commonly referred to as attaching and effacing lesions. When a STEC has the 

full complement of these virulence genes and has been associated with an illness such as bloody 

diarrhea, it is often referred to as enterohemorrhagic E. coli (EHEC). 

E. coli O157:H7 are easily differentiated biochemically from other enteric E. coli because 

they ferment sorbitol slowly, whereas other E. coli usually readily ferment sorbitol. Since the 

organism’s first recognition as a human pathogen in 1982, diagnostic screening assays that 

capitalize on this difference have become widely used in clinical laboratories (Wells et al. 1983). 

This practice has resulted in the generation of much more information on E. coli O157:H7 than 

that available on non-O157 STEC. 

The ability to detect E. coli O157:H7 in laboratory samples has recently been improved by 

the development of a separation technique that uses immunomagnetic beads. In this method, 

microscopic, iron cored beads are coated with antibody specific to E. coli O157:H7 (Okrend 

et al. 1992). The antibody coated beads capture E. coli O157:H7 organisms, and in turn, the 

bead-cell complexes are captured using a magnetic concentrator. These complexes can then be 

removed from the sample and plated onto MacConkey sorbitol agar for culture and isolation of 

E. coli O157:H7. This method has been especially useful for samples that have potentially large 

numbers of background organisms, such as meat products and feces, in which the growth of 

other bacterial species can obscure E. coli O157:H7 colonies during culture. 

In the United States, several outbreaks have occurred from exposure to non-O157 STEC. In 

Montana, 18 persons developed bloody diarrhea in 1994 after exposure to contaminated milk; E. 

coli O104:H21 was cultured from the stools of three of these patients (CDC 1995). E. coli

O111:H8 was responsible for an outbreak of gastrointestinal illness, including bloody diarrhea, 

in 56 persons who attended a camp in Texas in 2000 (CDC 2000a). Non-O157 serotypes of E. 

coli, including O26:H11, O111:H8, O103:H2, O113:H21, and O104:H21, have been responsible 

for a few outbreaks throughout the world. In a cluster of three cases of HUS caused by 

O113:H21 in Australia, this organism was found not to have genes coding for attaching and 

effacing (Paton et al. 1999). 

A recent Nebraska study of stool samples from persons with a differential diagnosis of 

bacterial gastroenteritis found 6 (1.8%) of 335 samples positive for E. coli O157:H7, whereas 

8 samples were positive for non-O157 STEC (Fey et al. 2000). In Washington state, a 1-year 

prospective study tested 445 stool samples from children who had diarrhea and isolated a nonO157 STEC from 13 (1.1%) patients and E. coli O157:H7 from 5 (2.9%) patients (Bokete et al. 

1993). A national study of postdiarrheal HUS estimated that less than 20% of HUS cases were 

due to non-O157 STEC; however, the authors qualified that estimate, commenting that it was 

difficult to determine the proportion of STEC-associated HUS that resulted from non-O157 

STEC (Banatvala et al. 2001). 

Most clinical laboratories in the United States do not routinely screen for non-O157 STEC 

because of the lack of a biochemical marker (Mead and Griffin 1998). In addition, surveillance 

for cases of non-O157 STEC infection is not routinely conducted. Mead et al. (1999) estimated 

that the incidence of non-O157 STEC is 20% to 50% that of E. coli O157:H7 infection. 

Therefore, because E. coli O157:H7 is the most important STEC serotype in the United States in 

terms of public health and because of the current paucity of epidemiologic data for non-O157 

STEC, this risk assessment is limited to E. coli O157:H7. 

September 7, 2001 18 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

SOURCES OF E. COLI O157:H7 

E. coli O157:H7 has been isolated from the feces or gastrointestinal tract of cattle, sheep, horses, 

pigs, turkeys, dogs, and a variety of wild animal species (Kudva et al. 1996; Rice and Hancock 

1995; Hancock et al. 1998b; Heuvelink et al. 1999); however, epidemiologic studies have found 

that cattle manure is the source of most human E. coli O157:H7 infections. E. coli O157:H7 has 

also been isolated from bodies of water (e.g., ponds, streams), wells, and water troughs and has 

been found to survive for months in manure and water trough sediments (Wang and Doyle 1998; 

Hancock et al. 1998a; Kudva et al. 1998; Sargeant et al. 2000). 

Colonization of the gastrointestinal tract for longer than 2 or 3 months has not been reported 

in any species, although only cattle, sheep, and humans have been sampled with sufficient 

intensity to assess duration of carriage (Hancock et al. 1998a). Despite this finding, E. coli

O157:H7 has been described as “ubiquitous” in dairy and beef cattle and is present at least 

occasionally on most farms or feedlots (Hancock et al. 1998a; Hancock et al. 2001). This 

widespread prevalence in cattle has been attributed to the organism’s ability to survive for at 

least 4 months in water trough sediments, providing an ongoing source of exposure to cattle 

(Hancock et al. 1998a). E. coli O157:H7 is also present in purchased animal feeds; therefore, 

such feeds may be an important route by which E. coli O157:H7 is disseminated to farms 

(Hancock et al. 2001). From the farms, E. coli O157:H7 contamination of meat occurs when beef 

carcasses come into contact with hides and feces during the slaughter process (Elder et al. 2000). 

EPIDEMIOLOGY OF DISEASE DUE TO INFECTION WITH E. COLI O157:H7 

E. coli O157:H7 was designated by the Council of State and Territorial Epidemiologists as a 

nationally notifiable disease in 1994. From 1994 to 2000, the number of reported cases of E. coli

O157:H7 in the United States increased by 211%, from 1,420 (0.8 per 100,000 population) in 

1994 to 4,410 (approximately 1.6 per 100,000 population) in 2000 (CDC 1999a; CDC 2001b) 

(Figure 2-1). Cases are reported by passive surveillance through the National Notifiable Diseases 

Surveillance System (NNDSS). Health care providers use this system to report notifiable disease 

cases to local or state health departments. The increase in reported cases over time is probably 

due to a combination of factors including (1) improvement in the effectiveness of the 

surveillance system; (2) greater awareness of E. coli O157:H7 infection among health care 

providers and the public, which has led to improved detection and reporting; (3) enhanced ability 

to detect disease through better diagnostic tests; and (4) a true increase in the incidence of 

disease. 

In 1996, the Emerging Infections Program, Foodborne Diseases Active Surveillance Network 

(FoodNet) began a program of active surveillance of clinical laboratories for specific foodborne 

diseases, including E. coli O157:H7. Five states participated initially (Minnesota, Oregon, and 

selected counties of California, Connecticut, and Georgia); as of 2000, eight states were under 

active surveillance, representing 29.5 million persons (10.8% of the 1999 U.S. population) (CDC 

2001a). The number of cases of E. coli O157:H7 infection reported annually to FoodNet ranged 

from 388 in 1996 to 631 in 2000 (Bender et al. 2000; CDC 2000c; CDC 2001a). Because the 

population under surveillance has increased, it is more appropriate to compare the number of 

reported cases per 100,000 population. For 1996 to 2000, there were 2.7, 2.3, 2.8, 2.1, and 2.9 

reported cases per 100,000 population, respectively, for the five original states (CDC 2001a). 

Data on the prevalence of symptomatic E. coli O157:H7 infection prior to the inception of 

FoodNet are scarce. Ostroff et al. (1989) reported an incidence of 2 cases per 100,000 

September 7, 2001 19 
2. Hazard Identification Number of Cases

1994 1995 1996 1997 1998 1999* 2000*

Year

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

FIGURE 2-1 Number of reported cases of E. coli O157:H7 infection, United States, 1994–2000. 

*Provisional. Sources: CDC, NNDSS. 

population during the first year of statewide surveillance in Washington in 1987. A prospective, 

population-based study, also conducted in Washington, estimated the incidence of cultureconfirmed E. coli O157:H7 infection to be 8 per 100,000 enrollees in a Seattle-based health 

maintenance organization during 1985 to 1986 and 10 per 100,000 enrollees in 1987 

(MacDonald et al. 1988; Ostroff et al. 1989). The results of this latter study may provide a more 

accurate estimate of the incidence of E. coli O157:H7 infection and suggest that substantial 

underreporting occurred in the statewide passive surveillance program. 

The incidence of E. coli O157:H7 infection varies by age group, with the highest incidence 

of reported cases occurring in children. In 1998, the incidence in children younger than 1 year of 

age was 2.01 per 100,000 population. The highest incidence was found in 1- to 4-year-olds at 

4.57 reported cases per 100,000 population, whereas 5- to 14-year-olds had an incidence of 1.83 

reported cases per 100,000 population (CDC 1999a). The lowest incidence occurred in persons 

aged 15 or older and ranged from 1.15 to 0.61 reported cases per 100,000 population. At 

FoodNet sites in 1999, 35.3% of reported cases occurred in 1- to 10-year-olds, 17.6% of cases 

occurred in 10- to 20-year-olds, and 14.1% of cases occurred in persons older than 60 (CDC 

2000b). Other studies have also found a high incidence in children (Ostroff et al. 1989; Proctor 

and Davis 2000). 

Diagnosis of E. coli O157:H7 is more common in the summer months (Mead and Griffin 

1998). Of cases reported by FoodNet sites, 70% occurred during June through September for the 

years 1996 to 1998 (Bender et al. 2000). In 1998, 1,710 (54.1%) of 3,161 cases of E. coli

O157:H7 reported through NNDSS to CDC occurred during those months (CDC 1999a). 

Outbreaks also occur more frequently in the summer, with 50 (58.8%) of 85 foodborne outbreaks 

occurring during June through September for the period 1993 to 1997 (CDC 1999a). During 

1998 to 1999, 21 (50.0%) of 42 foodborne outbreaks occurred during June through September 

(CDC 2000c; CDC 2001c). 

Most postdiarrheal HUS cases are thought to be due to E. coli O157:H7 infection. In a study 

of 83 patients infected with HUS between 1987 and 1991, STEC was implicated as the cause of 

illness in 72% of the patients; more than 80% of these cases were caused by E. coli O157:H7 

infection (Banatvala et al. 2001). Siegler et al. (1994) found that 140 (89.2%) of 157 HUS cases 

that occurred in Utah between 1971 and 1990 were postdiarrheal. E. coli O157:H7 testing was 

only available for the last 4 years of this study, but the authors concluded that E. coli O157:H7 

September 7, 2001 20 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

may have been the leading cause of HUS in that region of the United States for the duration of 

the study period (Siegler et al. 1994). 

HUS has been a nationally notifiable disease since 1996, and cases are reported by passive 

surveillance through NNDSS. Active surveillance for HUS in children at FoodNet sites began in 

1997. In 1998, the most recent year for which data are available, 90 cases of HUS were reported 

through NNDSS (CDC 1999a). In 1999, 60 cases were reported and 8 (13.3%) deaths occurred at 

FoodNet sites (CDC 2000b). HUS occurs more commonly in children than adults. During 1997 

to 1999 at FoodNet sites, the overall incidence of HUS among children younger than 15 years of 

age was 0.7 per 100,000 population; for children younger than 5, the incidence was 1.4 per 

100,000 (CDC 2000b). In a nationwide study of 83 patients with HUS, 46 (55.4%) were younger 

than 5 years old and an additional 27 (32.5%) were 5 to 17 years old (Banatvala et al. 2001). 

Similar to the seasonal distribution in reported cases of E. coli O157:H7 infection, HUS cases 

occur more frequently in summer months. In 1998 and 1999, respectively, 31 (59.6%) of 52 

reported HUS cases and 41 (68.3%) of 60 cases in the United States occurred during June 

through September (CDC 1999a; CDC 2000b). Additional details about HUS can be found in the 

section below on adverse health outcomes associated with E. coli O157:H7 infection. 

The number of reported E. coli O157:H7 cases derived from surveillance is known to be an 

underestimate of the true disease burden. Underestimation of the actual incidence of infection 

occurs for a variety of reasons: 

• Some infected persons do not seek medical care. 

• Physicians do not perform diagnostic testing on all patients who have symptoms of 

infection. 

• Some persons who obtain medical care do not provide a stool specimen. 

• Laboratories do not culture all stool samples for E. coli O157:H7. 

• Some proportion of laboratory results are false negatives. 

• Not all culture-confirmed infections are reported to public health authorities by health 

care providers and laboratories. 

For example, in a 1994 national survey, 70 (54.3%) of 129 randomly selected clinical 

laboratories reported that they did not routinely test all stools or all bloody stools for E. coli

O157:H7 (Boyce et al. 1995b). However, routine culturing of bloody diarrhea for E. coli

O157:H7 is increasingly common, particularly in FoodNet sentinel site areas. Using surveillance 

data and accounting for the factors that contribute to underreporting, Mead et al. (1999) 

estimated that 73,480 cases of E. coli O157:H7 infection occur annually in the United States and 

that 85% (62,456 cases) are a result of foodborne exposure. 

TRANSMISSION OF E. COLI O157:H7 

To choose the most appropriate product to model in this risk assessment, we assessed how 

frequently various products were implicated in E. coli O157:H7 infection by evaluating studies 

of sporadic cases of E. coli O157:H7 infection and outbreak investigation reports. Sporadic cases 

account for the majority of reported cases in a given year and therefore may be more 

representative of persons with E. coli O157:H7 infection. For example, 75% of reported cases in 

Oregon during 1991 to 1997 and 83% of reported cases in Wisconsin during 1992 to 1999 were 

sporadic (OCD 1998; Proctor and Davis 2000). 

In the first nationwide case-control study of sporadic E. coli O157:H7 infection, conducted in 

1990 to 1992, consumption of undercooked ground beef (described as “pink in the middle”) was 

the only dietary factor independently associated with diarrhea in multivariate analysis. The 

September 7, 2001 21 
2. Hazard Identification 

population-attributable risk for this behavior was 34% (Slutsker et al. 1998). A study of sporadic 

cases of E. coli O157:H7 infection in New Jersey found that these individuals were more likely 

than healthy controls to have eaten a hamburger in the week preceding illness (Mead et al. 1997). 

In addition, patients were slightly more likely than controls to report having eaten a hamburger 

that was pink in the middle (45% vs. 33%) (Mead et al. 1997). Kassenborg et al. (2001) also 

found that consumption of pink hamburgers or pink ground beef was a statistically significant 

risk factor, although merely consuming ground beef was not. Other significant risk factors by 

multivariate analysis were exposure to farms or to cattle, eating at a table service restaurant, 

using immune suppressive medication (for adults only), and obtaining beef through a private 

slaughter arrangement. This study estimated the population-attributable risk from consuming 

pink hamburger was 8% for meals consumed at home and 7% for meals consumed away from 

home and was 18% for farm exposures (visiting or living on a farm) (Kassenborg et al. 2001). 

A prospective study in Washington state identified that rare ground beef was consumed more 

often by cases than controls (MacDonald et al. 1988). A Canadian study of sporadic cases 

conducted in 1990 identified consumption of undercooked ground beef as a risk factor for E. coli

O157:H7 infection; the attributable risk was 17% (Le Saux et al. 1993). In a case-control study 

of sporadic cases conducted in Oregon during 1996 to 1997, visiting or living on a farm where 

cattle were present was a risk factor associated with E. coli O157:H7 infection (OCD 1998). 

Outbreak investigations have contributed significantly to our understanding of how E. coli

O157:H7 is transmitted. Since the first recognized ground beef-associated outbreak in 1982 

(Riley et al. 1983), outbreaks have been attributed to foodborne, waterborne, and person-toperson means of transmission. In 13 outbreaks that occurred between 1982 and 1993 in the 

United States, the transmission source was identified as hamburger or ground beef in 7 (53.9%) 

(Griffin 1995). 

A total of 128 foodborne outbreaks due to E. coli O157:H7 infection were reported in the 

United States between 1993 and 1999; of these, the food vehicle was identified in 92 (71.9%) 

(CDC 1999b; CDC 2000c; CDC 2001c). These 92 outbreaks involved 4,421 cases, with a range 

of 324 to 1,340 cases per year attributable to outbreaks. Beef was the food item most frequently 

associated with outbreaks. Of the 92 outbreaks with an identified food vehicle, 42 (45.7%) were 

attributed to exposure to beef. The specific beef product was not identified for 1993 to 1997 

outbreaks, but for the 21 beef-associated outbreaks that occurred during 1998 to 1999, ground 

beef or hamburger was identified as the vehicle in 19. Two outbreaks in 1999 were attributed to 

roast beef, and one of these was a result of environmental contamination from manure in a 

pasture where a picnic was held. A list of food vehicles implicated during 1998 to 1999 

outbreaks is shown in Table 2-1. Of the 19 ground beef/hamburger-associated outbreaks, 5 

(26.3%) occurred in multiple states. 

In summary, individuals can be exposed to E. coli O157:H7 in many ways. Current data 

based both on outbreaks and on sporadic infections indicate that consumption of ground beef is 

the primary source of E. coli O157:H7 exposure. For these reasons, ground beef is the focus of 

this E. coli O157:H7 risk assessment. 

ADVERSE HEALTH OUTCOMES ASSOCIATED WITH E. COLI O157:H7 

Ingestion of E. coli O157:H7 results in a wide range of possible outcomes, from asymptomatic 

infection to death. To cause disease, the E. coli O157:H7 must survive acidic conditions within 

the stomach before moving to distal portions of the gastrointestinal tract. Disease due to E. coli 

September 7, 2001 22 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

TABLE 2-1 Food Vehicles Implicated in Outbreaks of E. coli O157:H7, United States, 1998–

1999 

Vehicle 1998 1999 Total 

Ground beef/hamburger 10 9 19 

Roast beef 0 2 2 

Lettuce 1 3 4 

Coleslaw 2 1 3 

Salad 1 1 2 

Milk 2 0 2 

Tacos 0 1 1 

Apple cider 0 1 1 

Game meat 0 1 1 

Cake 1 0 1 

Cheese curd 1 0 1 

Fruit salad 1 0 1 

Macaroni salad 1 0 1 

Multiple 1 0 1 

Unknown 0 2 2 

Total 21 21 42 

Sources: CDC 1999b; CDC 2001c. 

O157:H7 occurs primarily in the colon. The incubation period from the time of ingestion to the 

first symptoms ranges from 1 to 8 days. Asymptomatic shedding of E. coli O157:H7 has been 

documented (Swerdlow and Griffin 1997); however, the proportion of exposed individuals who 

shed E. coli O157:H7 but do not develop symptoms is unknown. Typically the illness begins 

with abdominal cramps and nonbloody diarrhea, which can, but does not necessarily, progress to 

bloody diarrhea within 2 to 3 days (Griffin 1995; Mead and Griffin 1998). More severe 

manifestations of E. coli O157:H7 infection include hemorrhagic colitis (grossly bloody 

diarrhea), HUS (a combination of renal failure, low platelet counts, and hemolytic anemia), and 

occasionally TTP. Approximately 30% to 45% of patients are hospitalized (Ostroff et al. 1989; 

Le Saux et al. 1993; Bell et al. 1994; Slutsker et al. 1998). Of the 631 cases reported to FoodNet 

sites in 1999, 39% were hospitalized (CDC 2000c). Treatment for the more serious 

manifestations of E. coli O157:H7 infection is supportive, and the use of antimicrobial agents has 

been debated (Mead and Griffin 1998). 

Of symptomatic patients, 70% or more usually develop bloody diarrhea (Mead and Griffin 

1998). A total of 451 (90.0%) of 501 cases, most of whom were stool culture positive for E. coli

O157:H7, developed bloody diarrhea during a large outbreak in four western states in 1993 (Bell 

et al. 1994). In a study of sporadic cases in Washington state, 84 (95.5%) of 88 cases developed 

bloody diarrhea (Ostroff et al. 1989). However, patients with bloody diarrhea are more likely to 

seek medical attention, so these estimates may be subject to ascertainment bias. Symptoms of 

hemorrhagic colitis include severe abdominal cramps followed by grossly bloody diarrhea and 

edema (swelling), erosion, or hemorrhage of the mucosal lining of the colon (Su and Brandt 

1995). Hemorrhagic colitis may be the only manifestation of E. coli O157:H7 infection, or it may 

precede development of HUS. Complications from hemorrhagic colitis associated with E. coli

O157:H7 include upper-gastrointestinal bleeding and stroke (Su and Brandt 1995). Roberts et al. 

(1998, citing Boyce et al. 1995a; Ryan et al. 1986) estimate the mortality rate of those suffering 

hemorrhagic colitis without progression to HUS to be 1%, although Griffin (personal 

communication) believes that this rate is too high. 

September 7, 2001 23 
2. Hazard Identification 

The proportion of all patients who develop HUS following E. coli O157:H7 infection varies 

among sporadic cases and outbreak-associated cases. Between 3% and 7% of sporadic cases and 

20% or more of outbreak-associated cases of E. coli O157:H7 infection will progress to HUS 

(Mead and Griffin 1998). The proportion of patients who develop HUS following E. coli

O157:H7 infection is influenced by a variety of factors, including age, bloody diarrhea, fever, 

elevated leukocyte count, and toxin type (Griffin 1995). Wong et al. (2000) found that 10 

(14.1%) of 71 children with E. coli O157:H7 infection developed HUS. 

HUS is the most common cause of acute renal failure in young children, yet it also has longterm complications. Siegler et al. (1994) found that HUS causes chronic renal sequelae, usually 

mild, in 51% of survivors (48% of all cases). Neurologic complications occur in about 25% of 

HUS patients (Mead and Griffin 1998). Neurologic symptoms are generally mild, but serious 

complications, such as seizure, stroke, and coma, can occur (Su and Brandt 1995). Similar to 

treatment for E. coli O157:H7 infection, only symptomatic treatment is available for neurologic 

complications, making this manifestation of HUS especially dangerous and an important cause 

of death in HUS patients. Other complications of HUS include pancreatitis, diabetes mellitus, 

and pleural and pericardial effusions (Mead and Griffin 1998). In a nationwide study of HUS 

patients, 46 (55%) of 83 patients required either peritoneal dialysis or hemodialysis during the 

acute phase of their illness (Banatvala et al. 2001). Siegler et al. (1994) found that severe kidney 

or neurological impairments (end stage renal disease or stroke) occurred in 9 (5.7%) of 157 HUS 

cases over a 20-year period in Utah. Using 1990 Medicare data on survival rates after kidney 

transplantation and survival rates on dialysis for pediatric patients, Buzby et al. (1996) estimated 

that approximately 60% of pediatric HUS patients who develop chronic kidney failure die 

prematurely. 

On the basis of long-term studies in Minnesota (Martin et al. 1990) and King County, 

Washington (Tarr and Hickman 1987), and a 2-year, nationwide study in Canada, Rowe et al. 

(1991) and Mahon et al. (1997) estimated the acute mortality rate for HUS at 3% to 5%. In the 

study by Banatvala et al. (2001), 4 (6.5%) of 62 children with HUS died, and neither of 2 adults 

with HUS died. A long-term study in Utah reported 5% mortality (Siegler et al. 1994). 

Occasionally, patients with E. coli O157:H7 are diagnosed as having TTP, a condition 

similar to HUS but more likely to occur in adults and with more prominent neurological findings 

and less renal involvement. Of 73 children and 10 adults who met the case definition for HUS in 

the study by Banatvala et al. (2001), 8 (11.0%) children and 8 (80.0%) adults also met the case 

definition for TTP. None of the children died, but 2 (25.0%) of the adults did. There are many 

causes of TTP other than the association with E. coli O157:H7, and prior to the 1980s, 

gastrointestinal infections had not been strongly implicated in the pathogenesis of TTP (CDC 

1986). When associated with E. coli O157:H7 infection, TTP is probably the same disorder as 

HUS (Mead and Griffin 1998). 

PATHOGENESIS 

It is not our goal to provide a detailed review of Shiga toxin-producing E. coli pathogenesis, and 

interested readers are referred to recent publications (Paton and Paton 1998; Nataro and Kaper 

1998). By definition, all STEC produce Shiga toxins; although it appears that the production of 

Shiga toxins is a critical factor in the pathogenesis of E. coli O157:H7-related disease, other 

important virulence factors exist as well (see below). There are two main types of Shiga toxin: 

Shiga toxin 1 and Shiga toxin 2. STEC strains may produce either Shiga toxin 1 or Shiga toxin 2 

or both, and the genes for the toxins are encoded on lysogenic bacteriophages within the STEC 

chromosome. Shiga toxin 1 is almost identical to the Shiga toxin produced by Shigella 

September 7, 2001 24 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

dysenteriae type 1, and Shiga toxin 2 is approximately 55% homologous. A second important set 

of virulence factors in many STEC strains is a series of genes in a 35-kilobase pathogenicity 

island known as the Locus for Enterocyte Effacement (LEE) (Nataro and Kaper 1998; Paton and 

Paton 1998). A similar pathogenicity island was first described in enteropathogenic E. coli 

(EPEC). Many of the genes within the LEE are involved in the interaction of the bacteria with 

the human intestinal epithelial cell barrier. For example, the eae gene encoded on LEE encodes a 

protein expressed on the bacterial surface that is critical for the close attachment of the bacteria 

to the host cell. Other LEE genes are involved in this bacterial docking process and in changes 

that occur in the host cell following bacterial interaction. Virtually all E. coli O157:H7 strains 

possess the LEE. However, some STEC strains known to be associated with HUS, such as an 

O113:H21 strain described in Australia (Paton et al. 1999), lack the LEE but are clearly still 

pathogenic. Most E. coli O157:H7 strains also have a 60 mega dalton plasmid that encodes 

enterohemolysin (hlyA), among other things. The role of the plasmid in virulence is unknown. 

FACTORS AFFECTING SURVIVAL AND GROWTH OF E. COLI O157:H7 IN FOOD 

A number of factors have a significant influence on the survival and growth of E. coli O157:H7 

in food, including temperature, pH, salt, and water activity (Meng and Doyle 1998). Studies on 

the thermal sensitivity of E. coli O157:H7 in ground beef have revealed that the pathogen has no 

unusual resistance to heat and that heating ground beef sufficiently to kill typical strains of 

Salmonella will also kill E. coli O157:H7. Thermal pasteurization of milk has also been 

determined to be an effective treatment (Doyle et al. 1997). The optimal temperature for growth 

of E. coli O157:H7 is approximately 37o

C (98.6oF), and the organism will not grow at 

temperatures below 8°C to 10°C (46oF to 50oF) or above 44oC to 45oC (Doyle and Schoeni 1984; 

Buchanan and Doyle 1997). E. coli O157:H7 survives freezing, with some decline in the 

concentration of E. coli O157:H7 (Ansay et al. 1999). 

E. coli O157:H7 has been reported to be more acid resistant than other E. coli. Acid 

resistance enhances the survival of E. coli O157:H7 in mildly acidic foods and may explain its 

ability to survive passage through the stomach and cause infection at low doses. The ability to be 

acid resistant varies among strains and is influenced by growth phase and other environmental 

factors. Once induced, acid resistance is maintained for long periods of time during cold storage 

(Meng and Doyle 1998). Stationary-phase E. coli O157:H7 are more resistant than growing cells 

to acid (Meng and Doyle 1998). The presence of other environmental stresses, such as 

temperature or water activity stress, will raise the minimum pH for growth (Buchanan and Doyle 

1997). E. coli O157:H7 survives in such foods as dry salami, apple cider, and mayonnaise, which 

were previously considered too acidic to support the survival of foodborne pathogens. Published 

literature contains conflicting reports about the efficacy of acid spray washing of beef carcasses. 

A study by Brachett et al. (1994) found that warm and hot acid sprays did not significantly 

reduce the concentration of E. coli O157:H7 on beef carcasses. Two recent studies have found 

organic acids to be effective in reducing the presence of E. coli O157:H7 on beef carcasses 

(Berry and Cutter 2000; Castillo et al. 2001). These apparently contradictory results may reflect 

differences in acid resistance among strains of E. coli O157:H7 (Berry and Cutter 2000). 

E. coli O157:H7 can survive for extended periods under conditions of reduced water activity 

while refrigerated; however, the organism does not tolerate high salt conditions (Buchanan and 

Doyle 1997). 

September 7, 2001 25 
2. Hazard Identification 

REFERENCES 

Ansay, S.E., K.A. Darling, and C.W. Kaspar. 1999. Survival of Escherichia coli O157:H7 in 

ground-beef patties during storage at 2, –2, 15 and then –2 degrees C, and –20 degrees C. 

J Food Prot 62(11):1243-1247. 

Banatvala, N., P.M. Griffin, K.D. Greene, T.J. Barrett, W.F. Bibb, J.H. Green, J.G. Wells, and 

the Hemolytic Uremic Syndrome Study Collaborators. 2001. The United States national 

prospective hemolytic uremic syndrome study: microbiologic, serologic, clinical, and 

epidemiologic findings. J Infect Dis 183:1063-1070. 

Bell, B.P., M. Goldoft, P.M. Griffin, M.A. Davis, D.C. Gordon, P.I. Tarr, C.A. Bartleson, J.H. 

Lewis, T.J. Barrett, J.G. Wells, R. Baron, and J. Kobayashi. 1994. A multistate outbreak of 

Escherichia coli O157:H7-associated bloody diarrhea and hemolytic uremic syndrome from 

hamburgers: The Washington experience. JAMA 272(17):1349-1353. 

Bender, J., K. Smith, A. McNees, T. Fiorentino, S. Segler, M. Carter, N. Spina, W. Keene, T. 

Van Gilder, and the EIP FoodNet Working Group. 2000. Surveillance for E. coli O157:H7 

infections in FoodNet sites, 1996-1998: No decline in incidence and marked regional 

variation. 2nd International Conference on Emerging Infectious Diseases, Atlanta, Georgia, 

July. 

Berry, E.D., and C.N. Cutter. 2000. Effects of acid adaptation of Escherichia coli O157:H7 on 

efficacy of acetic acid spray washes to decontaminate beef carcass tissue. Appl Environ 

Microbiol 66(4):1493-1498. 

Bokete, T.M., C.M. O’Callahan, C.R. Clausen, N.M. Tang, N. Tran, S.L. Moseley, T.R. Fritsche, 

and P.I. Tarr. 1993. Shiga-like toxin producing Escherichia coli in Seattle children: A 

prospective study. Gastroenterology 105:1724-1731. 

Boyce, T.G., D.L. Swerdlow, and P.M. Griffin. 1995a. Escherichia coli O157:H7 and the 

hemolytic-uremic syndrome. N Engl J Med 333:364-368. 

Boyce, T.G., A.G. Pemberton, J.G. Wells, and P.M. Griffin. 1995b. Screening for Escherichia 

coli O157:H7—a nationwide survey of clinical laboratories. J Clin Microbiol 33:3275-3277. 

Brachett, R.E., Y.Y. Hao, and M.P. Doyle. 1994. Ineffectiveness of hot acid sprays to 

decontaminate Escherichia coli O157:H7 on beef. J Food Prot 57(3):198-203. 

Buchanan, R.L., and M.P. Doyle. 1997. Foodborne disease significance of Escherichia coli

O157:H7 and other enterohemorrhagic E. coli. Food Technology 51(10):69-76. 

Buzby, J.C., T. Roberts, C.T.J. Lin, and J.M. MacDonald. 1996. Bacterial Foodborne Disease: 

Medical Costs and Productivity Losses. U.S. Department of Agriculture Economic Research 

Service. Agricultural Economic Report No. 741. 

Castillo, A., M. Lucia, D.B. Roberson, T.H. Stevenson, I. Mercado, and G.R. Acuff. 2001. Lactic 

acid sprays reduce bacterial pathogens on cold beef carcass surfaces and in subsequently 

produced ground beef. J Food Prot 64(1):58-62. 

Centers for Disease Control and Prevention (CDC). 1986. Thrombotic thrombocytopenic purpura 

associated with Escherichia coli O157: H7—Washington. MMWR 35(34):549-551. 

Centers for Disease Control and Prevention (CDC). 1995. Outbreak of acute gastroenteritis 

attributable to Escherichia coli serotype O104:H21—Helena, Montana, 1994. MMWR 

44(27):501-503. 

Centers for Disease Control and Prevention (CDC). 1999a. Summary of notifiable diseases, 

United States, 1998. MMWR 47(53):1-94. 

September 7, 2001 26 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Centers for Disease Control and Prevention (CDC). 1999b. Surveillance for Outbreaks of 

Escherichia coli O157:H7 Infection. Summary of 1998 Data. Report from the National 

Center for Infectious Diseases, Division of Bacterial and Mycotic Diseases to CSTE. March 

8, 1999. 

Centers for Disease Control and Prevention (CDC). 2000a. Escherichia coli O111:H8 outbreak 

among teenage campers—Texas, 1999. MMWR 49(15):321-324. 

Centers for Disease Control and Prevention (CDC). 2000b. FoodNet Surveillance Report for 

1999. Final Report. November. 

Centers for Disease Control and Prevention (CDC). 2000c. Surveillance for foodborne-disease 

outbreaks—United States, 1993-1997. MMWR 49(SS-1):1-62. 

Centers for Disease Control and Prevention (CDC). 2001a. Preliminary FoodNet data on the 

incidence of foodborne illnesses—selected sites, United States, 2000. MMWR 50(13):241-

246. 

Centers for Disease Control and Prevention (CDC). 2001b. Provisional cases of selected 

notifiable diseases, United States, weeks ending December 30, 2000 and January 1, 2000. 

MMWR 49(51 and 52):1168. 

Centers for Disease Control and Prevention (CDC). 2001c. Surveillance for Outbreaks of 

Escherichia coli O157:H7 Infection. Summary of 1999 Data. Report from the National 

Center for Infectious Diseases, Division of Bacterial and Mycotic Diseases to CSTE. June 

15, 2000. 

Doyle, M.P., and J.L. Schoeni. 1984. Survival and growth characteristics of Escherichia coli

associated with hemorrhagic colitis. Appl Environ Microbiol 48(4):855-856. 

Doyle, M.P., T. Zhao, J. Meng, et al. 1997. Escherichia coli O157:H7. Pp. 171-191 in Food 

Microbiology: Fundamentals and Frontiers, M.P. Doyle, L.R. Beauchat, and T.J. Montville, 

eds. Washington, DC: ASM Press. 

Elder, R.O., J.E. Keen, G.R. Siragusa, G.A. Barkocy-Gallagher, M. Koohmaraie, and W.W. 

Laegreid. 2000. Correlation of enterohemorrhagic Escherichia coli O157:H7 prevalence in 

feces, hides, and carcasses of beef cattle during processing. Proc Natl Acad Sci 97(7):2999-

3003. 

Fey, P.D., R.S. Wickert M.E. Rupp, T.J. Safranek, and S.H. Hinrichs. 2000. Prevalence of nonO157:H7 Shiga toxin-producing Escherichia coli O157:H7 in diarrheal stool samples from 

Nebraska. Emerg Infect Dis 6(5):530-533. 

Griffin, P.M. 1995. Escherichia coli O157:H7 and other enterohemorrhagic Escherichia coli. Pp. 

739-761 in Infections of the Gastrointestinal Tract, M.J. Blaser, P.D. Smith, J.I. Ravdin, H.B. 

Greenberg, and R.L. Guerrant, eds. New York: Raven Press, Ltd. 

Hancock, D.D., T.E. Besser, and D.H. Rice. 1998a. Ecology of Escherichia coli O157:H7 in 

cattle and impact of management practices. Pp. 85-91 in E. coli O157:H7 and Other Shiga 

Toxin-Producing E. coli Strains, J.B. Kaper and A.D. O'Brien, eds. Washington, DC: ASM 

Press. 

Hancock, D.D., T.E. Besser, D.G. Rice, E.D. Ebel, D.E. Herriott, and L.V. Carpenter. 1998b. 

Multiple sources of Escherichia coli O157 in feedlots and dairy farms in the Northwestern 

USA. Prev Vet Med 35:11-19. 

Hancock, D., T. Besser, J. Lejeune, M. Davis, and D. Rice. 2001. The control of VTEC in the 

animal reservoir. Int J Food Microbiol 66:71-78. 

Heuvelink, A.E., J.T. Zwartkruis-Nahuis, F.L. van den Biggelaar, W.J. van Leeuwen, and E. de 

Boer. 1999. Isolation and characterization of verocytotoxin-producing Escherichia coli O157 

from slaughter pigs and poultry. Int J Food Microbiol 52(1-2):67-75. 

September 7, 2001 27 
2. Hazard Identification 

Kassenborg, H., C. Hedberg, M. Hoekstra, M.C. Evans, A.E. Chin, R. Marcus, D. Vugia, K. 

Smith, S. Desai, L. Slutsker, P. Griffin, and the FoodNet Working Group. 2001. Farm visits 

and undercooked hamburgers as major risk factors for sporadic Escherichia coli O157:H7 

infections—data from a case-control study in five FoodNet sites. Manuscript in preparation. 

Kudva, I.T., K. Blanch, and C.J. Hovde. 1998. Analysis of Escherichia coli O157:H7 survival in 

ovine or bovine manure and manure slurry. Appl Environ Microbiol 64(9):3166-3174. 

Kudva, I.T., P.G. Hatfield, and C.J. Hovde. 1996. Escherichia coli O157:H7 in microbial flora of 

sheep. J Clin Microbiol 34: 431-433. 

Le Saux, N., J.S. Spika, B. Friesen, I. Johnson, D. Melnychuck, C. Anderon, R. Dion, M. 

Rahman, and W. Tostowaryk. 1993. Ground beef consumption in noncommercial settings is 

a risk factor for sporadic Escherichia coli O157:H7 infection in Canada. J Infect Dis 

167:500-2 (letter). 

MacDonald, K.W., M.J. O’Leary, M.L. Cohen, P. Norris, J.G. Wells, E. Noll, J.M. Kobayashi, 

and P.A. Blake. 1988. Escherichia coli O157:H7, an emerging gastrointestinal pathogen: 

Results of a one-year, prospective, population-based study. JAMA 259(24):3567-3570. 

Mahon, B.E., P.M. Griffin, P.S. Mead, and R.V. Tauxe. 1997. Hemolytic uremic syndrome 

surveillance to monitor trends in infection with Escherichia coli O157:H7 and other shiga 

toxin-producing E. coli. Emerg Infect Dis (letter) 3(3):409-411. 

Martin, D., K. MacDonald, K. White, J.T. Soler, and M.T. Osterholm. 1990. The epidemiology 

and clinical aspects of the hemolytic uremic syndrome in Minnesota. New Engl J Med 

323:1161-1167. 

Mead, P., and P. Griffin. 1998. Escherichia coli O157:H7. Lancet 352:1207-1212. 

Mead, P.S., L. Finelli, M.A. Lambert-Fair, D. Champ, J. Townes, L. Hutwagner, T. Barrett, K. 

Spitalny, and E. Mintz. 1997. Risk factors for sporadic infection with Escherichia coli

O157:H7. Arch Intern Med 157:204-208. 

Mead, P.S., L. Slutsker, V. Dietz, L.F. McCaig, J.S. Bresee, C. Shapiro, P.M. Griffin, and R.B. 

Tauxe. 1999. Food-related illness and death in the United States. Emerg Infect Dis 5(5):607-

625. 

Meng, J., and M.P. Doyle. 1998. Microbiology of shiga toxin-producing Escherichia coli in 

foods. Pp. 92-108 in Escherichia coli O157:H7 and Other Shiga Toxin-Producing E. coli

Strains, J.B. Kaper and A.D. O’Brien, eds. Washington, DC: ASM Press. 

Nataro, J.P., and J.B. Kaper. 1998. Diarrheagenic Escherichia coli. Clin Microbiol Rev 11:142-

201. 

OCD (Oregon Health Division, Center for Disease Prevention & Epidemiology). 1998. Sporadic 

cases of hemorrhagic escherichiosis. CD Summary 47(6) (March 17, 1998). 

Okrend, A.J.G., B.E. Rose, and C.P. Lattuada. 1992. Isolation of Escherichia coli O157:H7 

using O157 specific antibody coated magnetic beads. J Food Prot 55:214-217. 

Ostroff, S.M., J.M. Kobayashi, and J.H. Lewis. 1989. Infections with Escherichia coli O157:H7 

in Washington State: The first year of statewide disease surveillance. JAMA 262(3):355-359. 

Paton, A.W., M.C. Woodrow, R.M. Doyle, J.A. Lanser, and J.C. Paton. 1999. Molecular 

characterization of a shiga toxigenic Escherichia coli O113:H21 strain lacking eae 

responsible for a cluster of cases of hemolytic-uremic syndrome. J Clin Microbiol 

37(10):3357-3361. 

Paton, J.C., and A.W. Paton. 1998. Pathogenesis and diagnosis of shiga toxin-producing 

Escherichia coli infection. Clin Microbiol Rev 11:450-479. 

Proctor, M.E., and J.P. Davis. 2000. Escherichia coli O157:H7 infections in Wisconsin, 1992-

1999. Wis Med J 99(5):32-37. 

September 7, 2001 28 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Rice, D.H., and D.D. Hancock. 1995. Non-bovine sources of Escherichia coli

O157:H7/Epidemiology. Conference of Research Workers in Animal Diseases: November 

13-14, 1995. Chicago, IL. Abstract #66. 

Riley, L.W., R.S. Remis, S.D. Helgerson, H.B. McGee, J.G. Wells, B.R. Davis, R. J. Hebert, 

E.S. Olcott, L.M. Johnson, N.T. Hargrett, P.A. Blake, and M.L. Cohen. 1983. Hemorrhagic 

colitis associated with a rare Escherichia coli serotype. New Engl J Med 308:681-685. 

Roberts, T., J. Buzby, J. Lin, et al. 1998. Economic aspects of E. coli O157:H7: Disease outcome 

trees, risk, uncertainty, and the social cost of disease estimates. Pp. 155-172 in New and 

Resurgent Infections: Prediction, Detection and Management of Tomorrow’s Epidemics, B. 

Greenwood and K. DeCock, eds. London School of Hygiene & Tropical Medicine. Seventh 

Annual Public Health Forum. West Sussex, England: John Wiley & Sons, Ltd. 

Rowe, P.C., E. Orrbine, G.A. Well, P.N. McLaine, and members of the Canadian Pediatric 

Kidney Disease Reference Center. 1991. Epidemiology of hemolytic-uremic syndrome in 

Canadian children from 1986 to 1988. J Pediatr 119(2):218-224. 

Ryan, C.A., R.V. Tauxe, G.W. Hosek, J.G. Wells, P.A. Stoesz, H.W. McFadden Jr., P.W. Smith, 

G.F. Wright, and P.A. Blake. 1986. Escherichia coli O157:H7 diarrhea in a nursing home: 

clinical epidemiologic and pathological findings. J Infect Dis 154:631-638. 

Sargeant, J.M., J.R. Gillespie, R.D. Oberst, R.K. Phebus, D.R. Hyatt, L.K. Bohra, and J.C. 

Galland. 2000. Results of a longitudinal study of the prevalence of Escherichia coli O157:H7 

on cow-calf farms. J Am Vet Med Assoc 61(11):1375-1379. 

Siegler, R.L., A.T. Pavia, R.D. Christofferson, and M.K. Milligan. 1994. A 20-year populationbased study of postdiarrheal hemolytic uremic syndrome in Utah. Pediatrics 94:35-40. 

Slutsker, L., A.A. Ries, K. Maloney, J.G. Wells, K.D. Greene, P.M. Griffin, and the Escherichia 

coli O157:H7 Study Group. 1998. A nationwide case-control study of Escherichia coli

O157:H7 infection in the United States. J Infect Dis 177:962-966. 

Su, C., and L.J. Brandt. 1995. Escherichia coli O157:H7 infection in humans. Ann Intern Med 

123:698-714. 

Swerdlow, D.L., and P.M. Griffin. 1997. Duration of faecal shedding of Escherichia coli

O157:H7 among children in day-care centres [letter in commentary]. Lancet 347:745-746. 

Tarr, P.I., and R.O. Hickman. 1987. Hemolytic uremic syndrome epidemiology: A populationbased study in King County, Washington, 1971 to 1980. Pediatrics 80:41-45. 

Wang, G., and M.P. Doyle. 1998. Survival of enterohemorrhagic Escherichia coli O157:H7 in 

water. J Food Prot 61(6):662-667. 

Wells, J.G., B.R. Davis, I.K. Wachsmuth, L.W. Riley, R.S. Remis, R. Sokolow, and G.K. 

Morris. 1983. Laboratory investigation of hemorrhagic colitis outbreaks associated with a 

rare Escherichia coli serotype. J Clin Microbiol 18(3):512-520. 

Wong, C.S., S. Jelacic, R.L. Habeeb, S.L. Watkins, and P.I. Tarr. 2000. The risk of the 

hemolytic-uremic syndrome after antibiotic treatment of E. coli O157:H7 infections. N Engl 

J Med 342(26):1930-1936. 

September 7, 2001 29 

3 

Exposure Assessment 

This chapter describes the model used to estimate the occurrence of Escherichia coli O157:H7 in 

single servings of ground beef. This exposure model is divided into three modules: production, 

slaughter, and preparation. The production module estimates the occurrence of E. coli O157:H7 

infection in two populations of live cattle: culled breeding cattle (cows and bulls) and cattle fed 

specifically for slaughter (steers and heifers). The slaughter module estimates the occurrence and 

extent of E. coli O157:H7 on carcasses and in beef trim combined in 2,000-pound combo bins or 

60-pound boxes. The preparation module estimates the occurrence of E. coli O157:H7 in single 

servings of cooked ground beef. When appropriate, the effects of storage (e.g., chilling) and 

cooking are included throughout the model to account for organism growth or decline with 

resultant increased or decreased numbers of E. coli O157:H7. Exposure to E. coli O157:H7-

contaminated ground beef servings was analyzed by age of the consumer and location where the 

meal was consumed (i.e., home or away from home). Each module of the exposure assessment 

model—production, slaughter, and preparation—yields one or more output distributions that 

serve either as inputs to the next module or as summary outputs. 

PRODUCTION MODULE 

The production module estimates the prevalence of E. coli O157:H7-infected cattle entering U.S. 

slaughter plants. It models culled breeding cattle (cows and bulls) and feedlot cattle (steers and 

heifers) at their points of origin through transit to the slaughter plant. 

We know that E. coli O157:H7-infected cattle entering the slaughter process may influence 

the contamination of ground beef. A determination of the quantitative association between the 

incoming status of cattle and the outgoing status of harvested meat is critical in this exposure 

assessment. This quantitative correlation between pre-harvest and post-harvest contamination is 

best predicted using fecal E. coli O157:H7 prevalence data (Elder et al. 2000). 

September 7, 2001 31 
3. Exposure Assessment 

Explanation of Scope 

The E. coli O157:H7 exposure assessment starts where beef production begins—at the farm. 

Most evidence on the occurrence and distribution of this organism in U.S. livestock was 

collected during surveys of farms and feedlots. Therefore, estimating the proportion of E. coli

O157:H7-infected cattle at slaughter begins with estimating the proportion of infected cattle on 

the farm. 

Imported beef is assumed to originate from countries whose E. coli O157:H7 epidemiology is 

similar to the United States. Approximately 15% of the fresh, chilled, and frozen beef and veal 

consumed in the United States is imported, and 90% of imports originate in Australia, New 

Zealand, and Canada (APHIS:VS:CEAH 1994). Specific data regarding the prevalence of E. coli

O157:H7 in beef imported from various countries are lacking, and published surveillance data 

from the three major exporters to the U.S. are variable. However, evidence indicates that E. coli

O157:H7 occurs in Australian, New Zealand, and Canadian cattle and humans (Robins–Browne 

et al. 1998; New Zealand Public Health Report 2000; Spika et al. 1998). In general, this evidence 

does not suggest that the prevalence of E. coli O157:H7 is dramatically greater in those countries 

than in the United States. Because this analysis intends to model all ground beef consumed in the 

United States, we assume that the share of imported ground beef that is contaminated is similar 

to the share of domestic ground beef that is contaminated. 

The prevalence of infected cattle entering slaughter plants may be reduced through actions on 

the farm or feedlot. Many risk factors thought to influence E. coli O157:H7 status in cattle apply 

to whole herds rather than to individual cattle. For example, certain feed or feeding practices are 

hypothesized to elevate the probability of cattle becoming colonized with E. coli O157:H7 

(Dargatz et al. 1997; Hancock et al. 1997b, 1998a; Herriot et al. 1998; Cray et al. 1998; Diez–

Gonzales et al. 1998). Therefore, mitigation strategies typically target herd-level risk factors for 

E. coli O157:H7 control. For example, vaccination for E. coli O157:H7 would likely be applied 

at the herd level (Jordan et al. 1999; Gyles 1998). 

Culled breeding cattle and feedlot cattle are separately modeled in this risk assessment. The 

slaughter, processing, and distribution of meat from these types of cattle are different. 

Furthermore, sampling evidence suggests that there may be differences in E. coli O157:H7 

prevalence between these two types of cattle. 

Breeding cattle comprise animals from dairy and beef cow-calf herds. In both types of 

breeding herds, mature cattle are bred to produce milk and calves. About 20% of all cattle 

slaughtered in the United States are breeding cattle (FSIS 1998). Feedlot cattle are steers and 

heifers sent to slaughter from feedlots. About 80% of all cattle slaughtered in the United States 

are feedlot cattle (FSIS 1998). 

Definition of Key Terms 

The following key terms are used throughout this module: 

• Prevalence is the proportion of infected herds or individual cattle in a population. 

• Herd prevalence is the proportion of herds with one or more E. coli O157:H7-infected 

cattle when the reference population is all herds of one type—for example, breeding 

herds. 

• Apparent herd prevalence is the proportion of herds with one or more test-positive cattle 

detected among all herds sampled. Positive cattle are those animals that were diagnosed 

as infected or contaminated, based on testing. It is assumed that when microbiologic 

culture is used, all test-positive cattle are truly infected. “Infected” refers to cattle whose 

September 7, 2001 32 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

intestinal tracts are colonized with the E. coli O157:H7 organism. “Contaminated” refers 

to cattle whose hides, hair, or hooves have some E. coli O157:H7 organisms residing on 

them. At present, no studies have specifically addressed the occurrence of contaminated 

cattle in herds, so the prevalence of infected herds is estimated based exclusively on 

infected cattle evidence. Given the limited understanding of the ecology of E. coli

O157:H7 in cattle herds, it is assumed that contaminated cattle can only reside within 

herds that have one or more infected cattle. 

• True herd prevalence is estimated by adjusting apparent herd prevalence observed in 

surveys with herd sensitivity. 

• Herd sensitivity is the proportion of infected herds that, when tested, are detected as E. 

coli O157:H7-positive. Herd sensitivity is dependent on the number of samples collected 

within herds and the detectable prevalence of infected animals in the infected herds. 

• Within-herd prevalence is the proportion of infected cattle when the reference population 

is the cattle within a specific infected herd. By convention, within-herd prevalence 

estimates only apply to infected herds. By definition, noninfected herds have a withinherd prevalence of 0%. 

• Apparent within-herd prevalence is the proportion of E. coli O157:H7-positive cattle 

detected in a sample of cattle from an infected herd. 

• True within-herd prevalence is estimated by adjusting the apparent within-herd 

prevalence observed in surveys by test sensitivity. 

• Test sensitivity is the proportion of infected cattle that, when tested, are detected as E. 

coli O157:H7-positive using a particular diagnostic test. Test sensitivity is a complex 

parameter that incorporates variability in sample collection and handling and in the 

biological properties of the sample. 

Production Module Segments 

The production module comprises three segments: on-farm, transportation, and slaughter plant 

intake. As noted previously, culled breeding cattle (“breeding herds”) are considered separately 

(Figure 3-1A) from feedlot cattle (“feedlots”) (Figure 3-1B). The on-farm segment estimates the 

prevalence of E. coli O157:H7-infected herds (herd prevalence) and of E. coli O157:H7-infected 

cattle in infected herds (within-herd prevalence). Variability of within-herd prevalence among all 

infected herds—and by season of the year—is also estimated. The transportation segment 

considers the effect of transit time and commingling on the transmission and amplification of E. 

coli O157:H7 infections. The slaughter plant intake segment considers the effect of clustering 

cattle as they enter the slaughter plant. The following sections describe data and analysis for each 

of these segments. 

On-Farm Segment 

Breeding Herd Prevalence

Herd prevalence is the proportion of all breeding herds that contain one or more infected cattle. It 

is assumed that herd prevalence remains constant over time at a national level. 

Hypothetically, herd prevalence might change across seasons or years. Seasonal changes in 

herd prevalence have been suggested (Garber et al. 1999), but these changes are most reasonably 

explained as the result of seasonal changes in the within-herd prevalence for infected herds. 

Seasonal variation in within-herd prevalence has been previously reported (Hancock et al. 1994, 

September 7, 2001 33 
3. Exposure Assessment 

BREEDING

HERDS

Figure 3-14

Table 3-1 Table 3-2

Figure 3-2

Figures 3-3 to 3-6

Table 3-5

Figures 3-7, 3-8

Tables 3-3, 3-4

Apparent herd

prevalence

Apparent

within-herd

prevalence

Frequency of

infected truckloads

Test sensitivity

Herd sensitivity

Equation 3.3

True herd

prevalence

Equations 3.1, 3.2,

3.4

Population

variability

Seasonal

variability

True within-herd

prevalence

Equation 3.5

TRANSPORT

SLAUGHTER

PLANT

Equation 3.6

FIGURE 3-1A Production module flowchart for estimation of key variables for breeding herds 

(cows and bulls). 

September 7, 2001 34 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Figure 3-15

Table 3-6 Table 3-7

Figure 3-9

Figures 3-10, 3-11

Table 3-8

Figures 3-12, 3-13

Tables 3-3, 3-4

Apparent feedlot

prevalence

Apparent

within-feedlot

prevalence

Frequency of

infected truckloads

Test sensitivity

Herd sensitivity

Equation 3.3

True feedlot

prevalence

Equations 3.1, 3.2,

3.4

Population

variability

Seasonal

variability

FEEDLOTS

True within-feedlot

prevalence

Equation 3.5

TRANSPORT

SLAUGHTER

PLANT

Equation 3.7

FIGURE 3-1B Production module flowchart for estimation of key variables for feedlot herds 

(steers and heifers). 

September 7, 2001 35 
3. Exposure Assessment 

1997b; Heuvelink et al. 1998). If within-herd prevalence varies by season, then the apparent herd 

prevalence detected in surveys will also vary in a similar pattern (assuming sample size within 

herds is constant). While herd prevalence might change across years, there is no empirical 

evidence supporting such a change in the past 5 years. 

Herd prevalence is estimated using evidence that may have been generated from sampling 

herd subpopulations other than mature cattle. Yet evidence about the existence of E. coli 

O157:H7 within any age of cattle in a herd indicates that cows or bulls culled from that herd 

might be infected. 

Apparent Breeding Herd Prevalence 

Seven studies provide evidence regarding the apparent prevalence of infected breeding herds 

(Table 3-1). Nearly all studies sampled herds from multiple states in the United States. 

TABLE 3-1 Evidence Used to Estimate Breeding Herd Prevalence 

Study 

Herds 

Tested 

Positive 

Herds 

Apparent 

Herd 

Prevalence 

Average 

Samples Per 

Herd 

Apparent 

Within-Herd 

Prevalence 

Lab 

Methods 

Months 

Sampled 

Hancock et al. 

1997a 

13 9 69% 791 1.3% 0.1 g, 

SMACct 

June–May 

Hancock et al. 

1997b 

36 27 75% 360 1.8% 0.1 g, 

SMACct 

July–

December 

Hancock et al. 

1998a 

6 6 100% 183 2.3% 0.1 g, 

SMACct 

July–

November 

Garber et al. 1999 91 22 24% 58 4.0% 1 g, 

SMACct, 

TSB 

February–

July 

Lagreid et al. 

1999 

15 13 87% 60 8.0% 10 g, IMS October–

November 

Sargeant et al. 

2000 

10 10 100% 235 1.2% 10 g, IMS January–

December 

Hancock 2001 20 18 90% 317 0.7% 0.1 g, 

SMACct 

December–

March, June–

September 

Note: g = grams of feces analyzed, 

SMACct = sorbitol MacConkey media with cefixime and tellurite, 

TSB = trypticase soy broth, and 

IMS = immunomagnetic separation. 

National studies have not shown any geographic clustering of E. coli O157:H7 among 

breeding herds (Garber et al. 1995, 1999). Therefore, U.S. herd prevalence data are pooled 

without regard for the region where the data were collected. 

Hancock et al. (1997a) sampled 13 dairy herds in three northwestern states monthly for 1 

year (1993 to 1994); 9 (69%) herds tested positive. Approximately 60 samples were collected on 

each visit from a combination of weaned heifers and adult cows. Apparent within-herd 

prevalence in the nine positive herds was 1%. 

Hancock et al. (1997b) sampled 36 dairy herds in three northwestern states from July to 

December 1994; 27 (75%) of the 36 tested herds were positive. In each herd, 60 fecal samples 

September 7, 2001 36 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

from post-weaned heifers were collected once a month, and about 2% of cattle within infected 

herds were positive. 

Hancock et al. (1998a) also sampled six dairy herds in three northwestern states from July to 

November 1996. In each herd, 60 fecal samples from post-weaned heifers were collected once a 

month for 3 months. All herds tested positive. Apparent within-herd prevalence was 2.3%. 

Garber et al. (1999) report on a national survey of the U.S. dairy industry conducted by the 

U.S. Department of Agriculture (USDA) from February to July 1996. Fecal samples were 

collected from 91 dairy herds across the United States, and 22 herds were found to have one or 

more test-positive cattle. Within each herd, the average number of samples collected was 58, and 

about 4% of sampled cattle in the positive herds were found to be E. coli O157:H7-positive. 

 Lagreid et al. (1999) sampled 15 cow-calf herds across five midwestern states in October 

and November 1997; 13 (87%) herds tested positive. In each herd, 60 fecal samples from weaned 

calves were collected. This study used more sensitive lab methods than many studies that 

preceded it. Therefore, the apparent within-herd prevalence (8%) found in this study reflects the 

improved capacity of that test to detect positive cattle. 

Sargeant et al. (2000) sampled 10 Kansas cow-calf herds once a month for 1 year (1996 to 

1997), and all 10 herds tested positive. On each visit, about 10% of the cow and bull herd was 

sampled (~20 head per month). This study also used very sensitive test methods but found an 

apparent within-herd prevalence (~1%) more consistent with studies using less sensitive 

methods. 

Hancock (2001) is completing a study of 30 dairy herds in two northwestern states. Twenty 

of these herds have been sampled during the winter (December through March) and summer 

(June through September). Eighteen of these herds were found to contain at least one positive 

cattle. Apparent within-herd prevalence for adult cattle is 0.7% using moderately sensitive test 

methods. 

True Breeding Herd Prevalence 

True herd prevalence is estimated from apparent herd prevalence using Bayes Theorem: 

∫ ΦΦΦ

ΦΦ =Φ 1

0

)()|(

)()|( )|(

dfyf

fyf yf (3.1) 

Equation 3.1 predicts the distribution for true herd prevalence (Φ), given apparent prevalence 

evidence (y). The function, f(y | Φ), is the likelihood of observing a particular sampling result 

(e.g., 27 positive herds in 36 sampled herds from Hancock et al. 1997b), given true herd 

prevalence Φ. This likelihood function depends on the herd sensitivity (HSens), the number of 

herds sampled in a study (N), and the number found positive (S): 

( )( (3.2) S SN

S

N

yf − Φ×−Φ× ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ ( )| =Φ HSens HSens1 )

The herd sensitivity (HSens) of a particular survey was defined as 

( ) dppfp ,)(11HSens i

n

∫ −−= i (3.3) 

where pi is the apparent within-herd prevalence in herd i, f(pi) is the frequency of pi, and n is the 

number of samples collected in each herd. 

September 7, 2001 37 
3. Exposure Assessment 

Using Monte Carlo methods, HSens was estimated to be 0.75 for Garber et al. (1999), 0.86 

for Lagreid et al. (1999) and Sargeant et al. (2000), 0.89 for Hancock et al. (1998a) and Hancock 

(2001), 0.96 for Hancock et al. (1997b), and 0.99 for Hancock et al. (1997a). Apparent withinherd prevalence was assumed to be an exponential distribution (as discussed in the “WithinBreeding Herd Prevalence” section). Average within-herd prevalence was modeled using a 

beta(s+1,n–s+1) distribution, where s was the number of test-positive cattle in detected herds and 

n was the total cattle tested in detected herds (Vose 1996). 

True breeding herd prevalence (Figure 3-2) was estimated by combining the results from 

Equation 3.2 across all seven studies using Equation 3.4: 

θθθ

θθ θ

dfxf

fxf xf

i i

i i

i

)()|(

)()|( )|(

1

1

0

1

−

−

∫

= (3.4) 

where xi reflects the evidence provided by study i, and f(θi–1) is the prior distribution for breeding 

herd prevalence based on evidence provided by study i–1. 

Figure 3-2 suggests that breeding herd prevalence is most likely 65%, but it could be as low 

as 50% or as high as 80% based on the available evidence. Therefore, the majority of breeding 

herds in the United States are predicted to contain one or more E. coli O157:H7-infected cattle. 

0.00

0.02

0.04

0.06

0.08

0.10

0% 20% 40% 60% 80% 100%

Breeding Herd Prevalence

Probability

FIGURE 3-2 Resultant uncertainty distribution for true breeding herd prevalence after analysis of 

data in Table 3-1. 

As defined in this risk assessment, breeding herds comprise dairy and cow-calf herds. 

Although most evidence on breeding herds was collected in dairy herds, two studies exclusively 

sampled cattle in cow-calf herds (Lagreid et al. 1999; Sargeant et al. 2000). Dairy cows are 

usually managed intensively. They are gathered at least twice daily and often confined to lots or 

pastures where contact between individuals is likely to occur. Commercial dairies are also very 

busy operations: milk trucks, feed delivery vehicles, and other visitors are common. Cows in 

cow-calf herds are less intensively managed. These cows usually live on large pastures 

throughout the year. Hypothetically, the potential for fecal-oral spread of E. coli O157:H7 is 

greater for dairy herds than for beef herds based on these management differences. Furthermore, 

the potential for introduction of E. coli O157:H7 into a dairy would seemingly be greater given 

the increased traffic and congestion in such operations. Yet the studies show that cow-calf herds 

September 7, 2001 38 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

are no less likely to be infected than dairy herds (i.e., Lagreid et al. [1999] found 87%—and 

Sargeant et al. [2000] found 100%—of cow-calf herds they studied positive). Although the 

evidence is limited, it suggests that dairy and cow-calf herds are similar with respect to E. coli

O157:H7. 

Within-Breeding Herd Prevalence

Within-herd prevalence is the proportion of infected cattle that an infected herd might send to 

slaughter. Culled breeding cattle sent to slaughter are a subset of these herds. Within-herd 

prevalence in this model applies to just these cattle. 

Apparent Within-Breeding Herd Prevalence 

Within-herd prevalence varies among the population of all infected herds. If all the infected 

herds could be examined at a given point in time, differences in within-herd prevalence among 

these herds could be observed. Within-herd prevalence also varies systematically among infected 

herds by season (Hancock et al. 2001). Therefore, within-herd prevalence is modeled as a 

frequency distribution to reflect population variability, but the frequency distribution is adjusted 

to reflect seasonal patterns. 

Population variability. Two studies provide evidence about the population variability of 

within-herd prevalence among known-infected herds (Hancock et al. 1997b; Garber et al. 1999). 

Both studies included sufficient herds (i.e., 27 and 22 herds) and samples to estimate a 

distribution. 

Figure 3-3 is a histogram of within-herd prevalence from a study that sampled dairy heifers 

in three northwestern states between July and December 1994 (Hancock et al. 1997b). This 

histogram suggests a declining frequency of herds as within-herd prevalence increases. Its mean 

and standard deviation are 1.9% and 1.3%, respectively. Hypothetically, such a histogram might 

be generated from an exponential distribution. 

0

1

2

3

4

5

6

7

0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 3.5% 4.0% 4.5% 5.0% 5.5%

Apparent Within-Herd Prevalence

Herds Observed

FIGURE 3-3 Evidence on the distribution of within-herd prevalence of E. coli O157:H7 among 27 

infected herds (adapted from Hancock et al. 1997b). 

The exponential distribution has one parameter, β, that is both its mean and standard 

deviation. A comparison of the Hancock et al. (1997b) data to predictions from an exponential 

distribution with β = 1.9% shows general agreement (Figure 3-4). Using a Chi-square statistic, 

the hypothesis that the observed and expected results were equivalent was not rejected (χ2

 = 

0.92, p>0.05). Degrees of freedom for this test were determined using Scott’s normal 

approximation (Vose 1996). 

September 7, 2001 39 
3. Exposure Assessment 

0.00

0.20

0.40

0.60

0.80

1.00

0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 3.5% 4.0% 4.5% 5.0% 5.5%

Apparent Within-Herd Prevalence

Cumulative Probability

Hancock et al. 1997b Exponential

FIGURE 3-4 Comparison of observed and expected cumulative probabilities for within-herd 

prevalence of E. coli O157:H7. 

Figure 3-5 is a histogram of within-herd prevalence from a national USDA survey of dairy 

cows (Garber et al. 1999). These data also reasonably fit an exponential distribution (χ2 = 9.2, 

p>0.05) (Figure 3-6). 

0

1

2

3

4

5

6

2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14%

Apparent Within-Herd Prevalence

Number of Herds

FIGURE 3-5 Evidence on the distribution of within-herd prevalence of E. coli O157:H7 among 22 

infected herds (adapted from Garber et al. 1999). 

September 7, 2001 40 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

0.00

0.20

0.40

0.60

0.80

1.00

0% 2% 4% 6% 8% 10% 12% 14%

Apparent Within-Herd Prevalence

Cumulative Probability

Garber et al. 1999 Exponential

FIGURE 3-6 Comparison of observed and expected cumulative probabilities for within-herd 

prevalence of E. coli O157:H7. 

Other prevalence studies either sampled very few infected herds (e.g., Besser et al. 1997; 

Hancock et al. 1994; Sargeant et al. 2000) or did not collect many samples within each infected 

herd (Rice et al. 1997). A histogram of within-herd prevalence generated from these studies 

would not adequately depict its variability. Yet by assuming that within-herd prevalence of E. 

coli O157:H7 fits an exponential distribution, the results from these studies can be used to 

estimate the average within-herd prevalence. The exponential distribution then describes the 

variability of within-herd prevalence based on this average. 

Seasonal variability. Evidence of a summer peak in cattle E. coli O157:H7 prevalence 

(Hancock et al. 1994; Garber et al. 1999; Hancock et al. 1997a; Heuvelink et al. 1998; Van 

Donkersgoed et al. 1999) suggests that the greatest E. coli O157:H7 prevalence occurs between 

June and September. It is thought that a summer rise in prevalence results from on-farm 

environmental conditions that provoke increased transmission of E. coli O157:H7 among cattle 

(Hancock 2001). For example, if feed and water are important in the transmission of E. coli

O157:H7 to cattle within a herd, then summer ambient temperatures might induce substantial 

growth of E. coli O157:H7 in the feed and water that cattle ingest and result in more infected 

cattle. 

One study of cattle in Canada found at least a fourfold difference in E. coli O157:H7 fecal 

prevalence between samples collected in the winter and summer (Van Donkersgoed et al. 1999). 

The greatest fecal prevalence was observed between June and August. In a national study of U.S. 

dairies, herds sampled between May and July were nearly eight times more likely to be fecal 

positive than those sampled between February and April (Garber et al. 1999). Longitudinal 

studies that followed the same infected herds for a full year have found a three- to sixfold 

difference in prevalence between winter and summer (Hancock et al. 1997a; Heuvelink et al. 

1998). Nevertheless, a yearlong study of 10 cow-calf herds did not demonstrate any seasonal 

difference in prevalence (Sargeant et al. 2000). 

To model the effect of season, within-herd prevalence is estimated for two periods: June to 

September, which constitutes the high prevalence season, and the other months of the year, 

which constitute the low prevalence season. Each season’s average within-herd prevalence is 

September 7, 2001 41 
3. Exposure Assessment 

estimated. During each season, population variability of within-herd prevalence is modeled via 

the exponential distribution. 

Evidence of Apparent Within-Breeding Herd Prevalence 

Six studies provide evidence on apparent within-herd prevalence of infected adult cattle in U.S. 

breeding herds (Table 3-2). Although all of these studies sampled adult cows and bulls, the study 

design, sampling scheme, and culturing methods often differed. 

TABLE 3-2 Evidence Used to Estimate Within-Herd Prevalence of E. coli O157:H7 in Breeding 

Herds 

Study 

Number Tested 

in Positive 

Herds 

Positive in 

Positive 

Herds 

Apparent 

Within-Herd 

Prevalence Lab Methods Months Sampled

Hancock et al. 

1994 

458 20 4.4% 0.1 g, SMAC June–July, 

September 

Besser et al. 

1997 

2074 53 2.6% 0.1 g, SMACct January–

December 

Rice et al. 1997 75 7 9.3% 0.1 g, SMACct July–December

Garber et al. 

1999 

1268 51 4.1% 1 g, SMACct, 

TSB 

February–July 

Sargeant et al. 

2000 

2348 29 1.2% 10 g, IMS January–

December 

Hancock et al. 

2001 

5709 38 0.7% 0.1 g, SMACct December–

March, June–

September 

Note: g = grams of feces analyzed, 

SMAC = sorbitol MacConkey media, 

SMACct = sorbitol MacConkey media with cefixime and tellurite, 

TSB = trypticase soy broth, and 

IMS = immunomagnetic separation. 

Hancock et al. (1994) surveyed 25 cow-calf herds in Washington, and 4 (16%) were positive. 

Within those positive herds, about 4% of cows were fecal positive for E. coli O157:H7. 

Sampling was conducted in June, July, and September 1992. 

Besser et al. (1997) conducted a yearlong study of 10 dairy herds in Washington, and 4 

(40%) were positive. Within those positive herds, the prevalence of positive cattle was about 3%. 

Sampling was completed during 1993 and 1994. 

Rice et al. (1997) sampled cows culled from 13 positive dairy herds in Idaho, Oregon, and 

Washington. This study found 9% of cattle from positive herds to be fecal positive. Sampling 

was conducted between July and December 1994. 

In Garber et al. (1999), 22 infected dairy herds were detected as part of a national USDA 

survey. Four percent of the cows sampled in the positive herds were E. coli O157:H7-positive. 

Sampling was conducted between February and July 1996. 

Sargeant et al. (2000) detected 10 positive Kansas cow-calf herds in a yearlong study. About 

1% of the cows were fecal positive. The study was conducted between December 1996 and 

December 1997. 

September 7, 2001 42 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Hancock et al. (2001) are completing a study in which 18 positive herds have been detected. 

Almost 1% of cattle sampled in positive herds are positive. These results reflect sampling 

conducted during 2000 and 2001. 

True within-herd prevalence can be estimated from apparent within-herd prevalence (Martin 

et al. 1987): 

True Prevalence = Apparent Prevalence

Test Sensitivity (3.5) 

Apparent prevalence is estimated as a beta(s+1,n–s+1), where s is the number of test positive 

cattle in a study and n is the total cattle tested in positive herds (Vose 1996). Test sensitivity is 

estimated from research evidence. 

Test Sensitivity 

The probability of observing a positive biological test result depends on test sensitivity. Both the 

culture methods used and the quantity of sample collected affect test sensitivity. The absolute 

sensitivity of microbiological tests applied to naturally-infected cattle has not been established 

because there is no suitable “gold” standard for determining the true infection status of cattle. 

Nevertheless, Sanderson et al. (1995) have evaluated the sensitivity of culturing methods using 

24 naturally-infected dairy cattle (Table 3-3). These relative sensitivity measures included the 

effects of different culture methods and sample quantities. The least sensitive method had a 

relative sensitivity of 0.33—in other words, only 33% of the infected cattle were found positive 

using this method. The most sensitive method had a relative sensitivity of 0.79. 

TABLE 3-3 Relative Test Sensitivity of Lab Methods. Twenty-four test-positive cattle were 

detected using different sample quantities (0.1 gram and 10 grams) and plating media. 

Lab Methods Number Positive Relative Sensitivity 

0.1 gram, TSBcv, SMACc 8 0.33 

0.1 gram, TSBcv, SMACct 14 0.58 

10 gram, TSBcv, SMACct 19 0.79 

Total positives 24 

Note: TSBcv = trypticase soy broth with cefixime and vancomycin, 

SMACc = sorbitol MacConkey media with cefixime, and 

SMACct = sorbitol MacConkey media with cefixime and tellurite. 

Source: Adapted from Sanderson et al. 1995. 

The quantity of feces sampled from cattle influences test sensitivity because infected cattle 

shed E. coli O157:H7 in varying concentrations. Variability in E. coli O157:H7 fecal 

concentration from naturally-infected cattle has been reported (Zhao et al. 1995; Cassin et al. 

1998). The range of feasible concentrations should extend to 107

 to account for shedding levels 

infrequently observed in experimentally-infected adult cattle (Cray and Moon 1995). A 

minimum shedding concentration of 10–1 colony-forming units (CFU) per gram of feces can be 

assumed, based on a 10-gram sample. Plausible frequencies for this range of fecal concentrations 

are listed in Table 3-4. 

September 7, 2001 43 
3. Exposure Assessment 

TABLE 3-4 Calculation of the Probability of Detecting One or More Organisms Given the 

Sample Quantity, Concentration of Organisms per Gram of Feces, and Frequency (f[x]). Lambda 

(λ) equals the CFU per gram multiplied by the sample size. The sum of each column is the 

expected frequency of samples containing no E. coli O157:H7 organisms from a cross-section of 

infected cattle. 

P(x=0|λ)*f(x) 

CFU per Gram of Feces f(x) 0.1 Gram Sample 1 Gram Sample 10 Gram Sample 

0.1 0.12 0.117 0.107 0.043 

1 0.12 0.107 0.043 0.000 

10 0.12 0.043 0.000 0.000 

100 0.12 0.000 0.000 0.000 

1,000 0.06 0.000 0.000 0.000 

10,000 0.35 0.000 0.000 0.000 

100,000 0.09 0.000 0.000 0.000 

1,000,000 0.02 0.000 0.000 0.000 

10,000,000 0.01 0.000 0.000 0.000 

Sum 1 0.267 0.150 0.043 

1–Sum 0.733 0.850 0.957 

Fecal prevalence studies have included 0.1-gram, 1-gram, and 10-gram sample quantities. 

The probability that a given sample quantity will not contain any organisms is predicted by the 

Poisson distribution, e–xz, where x is concentration per gram of feces and z is the sample quantity 

in grams. If x is a distribution, then this probability is the expected value across all 

concentrations (i.e., Σf(x) × e–xz), where f(x) is the frequency of concentration x. 

The probability of a sample containing one or more organisms is equal to one minus the 

probability it contains no organisms. The probability that a sample size of 0.1, 1.0, and 10 grams 

will contain at least one organism is 0.73, 0.85, and 0.96, respectively (Table 3-4). Therefore, 

increasing the sample quantity from 0.1 grams to 10 grams results in 23% (= 96% – 73%) more 

samples with 1 or more E. coli O157:H7 organisms from infected cattle. Interestingly, when 0.1- 

and 10-gram samples were evaluated using the same enrichment and plating system (i.e., TSBcv, 

SMACct), the 10-gram sample detected 79% of infected cattle while the 0.1-gram sample 

detected 58% of these cattle, a difference of 21% (Table 3-3). Therefore, the observed difference 

in sensitivity between these methods approximates the effect of different sample quantities. 

The test sensitivity applicable to the Besser et al. (1997), Rice et al. (1997), and Hancock et 

al. (2001) studies is shown in Table 3-3 (i.e., 0.58). The other within-herd prevalence studies 

used alternative methods for which test sensitivity is not directly reported. 

The Garber et al. (1999) study used 1.0-gram samples and TSB-SMACct. Neither the TSB 

enrichment nor the 1.0-gram sample size is available from the results in Table 3-3. The TSBcvSMACct culturing protocol detected 80% of samples experimentally spiked with E. coli

O157:H7 (Sanderson et al. 1995). Yet a 1.0-gram sample from infected cattle is only 85% likely 

to contain E. coli O157:H7. Therefore, a 1.0-gram, TSBcv-SMACct protocol is predicted to 

detect 68% (85% × 80%) of infected cattle. In another experiment, the difference between the 

September 7, 2001 44 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

TSB enrichment system and the TSBcv system equaled –10% (Sanderson et al. 1995). Therefore, 

the sensitivity for the 1.0-gram TSB-SMACct sampling protocol is estimated as 58%. 

Hancock et al. (1994) used 0.1-gram samples and TSBv-SMAC. The SMAC plating system 

only detected 3% of samples experimentally spiked with E. coli O157:H7 (Sanderson et al. 

1995). A 0.1-gram sample from infected cattle is only 73% likely to contain E. coli O157:H7. 

Therefore, the sensitivity of the 0.1 gram-TSBv-SMAC sampling protocol was estimated as 2% 

(73% × 3%). 

Sargeant et al. (2000) used 10-gram samples and immunomagnetic separation (IMS) with 

microbiologic culture to improve the detection of E. coli O157:H7 in fecal samples. The IMS 

process was found to have a sensitivity that was 20% greater than a single dilution microbiologic 

culture system (Sanderson et al. 1995). Therefore, sensitivity of the 10-gram IMS sampling 

protocol was estimated as 100%. 

Test sensitivities in Table 3-3 and those generated above were used in Equation 3.5 to 

estimate true prevalence. Uncertainty regarding test sensitivity was modeled using beta 

distributions (Vose 1996). 

True Within-Breeding Herd Prevalence 

Seasonal variability. Examining the monthly prevalence evidence, there appears to be a high 

prevalence season (June to September) and a low prevalence season (October to May). 

Three studies (Garber et al. 1999; Hancock et al. 1994, 2001) provide different sampling 

evidence for different months of the study. For example, Garber et al. (1999) sampled cattle from 

February through July. These data show that 7 of 193 cattle sampled in infected herds were fecal 

positive during the period from February to May. In contrast, 44 of 1,075 cattle sampled in 

infected herds during June and July were fecal positive. 

Data collected for each month of the year were pooled. Prior to pooling, true within-herd 

prevalence for each study was estimated. Average within-herd prevalence was calculated for 

each month across all the applicable studies by weighting each study by the average cattle 

sampled per month in the study. Within-herd prevalence estimated for June to September was 

averaged to calculate within-herd prevalence during the high prevalence season. Similarly, 

within-herd prevalence during the low prevalence season was the average across October to 

May. 

Table 3-5 illustrates this method of estimating seasonal averages using point estimates. 

Recall that true prevalence is a random variable estimated from two beta-distributed variables 

(apparent prevalence and test sensitivity). These point estimates illustrate one scenario when the 

averages of apparent prevalence and test sensitivity are used. To calculate true averages, Monte 

Carlo methods were used to simulate the underlying distributions (Haas et al. 1999). 

Figure 3-7 overlays a centered 3-month moving average curve upon nine illustrative 

iterations of the Monte Carlo model. The moving average curve is calculated from 1,000 

iterations of the model and demonstrates a seasonal pattern of within-herd prevalence. 

Nevertheless, the limited data and estimation method also result in considerable uncertainty 

about the true monthly within-herd prevalence. A given month’s estimate may be substantially 

influenced by the amount of available data (e.g., August) as well as the uncertainty in apparent 

prevalence and test sensitivity. Nevertheless, the volatility implied by the single iteration curves 

is dampened because the model only considers estimates of the high and low prevalence seasons. 

Figure 3-8 shows the uncertainty about the seasonal averages. Despite the apparent overlap 

of the two seasonal distributions, there were 913 of 1,000 iterations of the Monte Carlo model in 

which the prevalence for June to September (high prevalence season) was greater than that for 

September 7, 2001 45 
3. Exposure Assessment 

TABLE 3-5 Point Estimates for Monthly True Within-Herd Prevalence for Each of Six Studies 

(Table 3-2). A weighted average for each month was calculated (based on average numbers of 

samples collected per month per study), and a seasonal average was calculated for the high and 

low prevalence seasons. 

Weighted Average 

Month 

Hancock 

et al. 1994 

Besser et 

al. 1997 

Rice et al. 

1997 

Garber et 

al. 1999 

Sargeant 

et al. 2000 

Hancock et 

al. 2001 Average

January 4.5% 1.3% 1.0% 1.6% 

February 4.5% 7.1% 1.3% 1.0% 2.6% 

March 4.5% 7.1% 1.3% 1.0% 2.6% 

April 4.5% 7.1% 1.3% 4.6% 

May 4.5% 7.2% 1.3% 4.6% 

June 45.3% 4.5% 7.2% 1.3% 1.4% 4.2% 

July 66.8% 4.5% 18.0% 7.2% 1.3% 1.4% 5.0% 

August 4.5% 18.0% 1.3% 1.4% 2.1% 

September 75.6% 4.5% 18.0% 1.3% 1.4% 4.8% 

October 4.5% 18.0% 1.3% 3.3% 

November 4.5% 18.0% 1.3% 3.3% 

December 4.5% 18.0% 1.3% 1.0% 1.7% 

Weights 46 173 13 254 196 794 

October–May average (low prevalence season) 3.0% 

June–September average (high prevalence season) 4.0% 

January–December average 3.4% 

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Average Within-Herd Prevalence

Centered 3-month

moving average

FIGURE 3-7 Estimated average monthly within-herd prevalence. This illustrated seasonal trend is 

based on 1,000 iterations of the model. 

September 7, 2001 46 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

Average Within-Herd Prevalence

Probability

Low prevalence season

(October–May)

High prevalence season

(June–September)

FIGURE 3-8 Uncertainty about low and high prevalence seasons’ estimated average within-herd 

prevalence. These distributions were estimated using 1,000 Monte Carlo iterations of the model. 

the rest of the year (low prevalence season). The averages of the low and high prevalence season 

distributions were 3.1% and 4.2%, respectively. Therefore, this analysis suggests that withinherd prevalence is increased 33% during June to September relative to the rest of the year. For 

comparison, the Sargeant et al. (2000) study found no evidence of change by season, and the 

Hancock et al. (2001) study found a 66% increase during June to September. These studies 

sampled adult cows during both the low and high prevalence seasons. 

These results imply that prevalence within infected breeding herds during June to September 

varies around a greater average than during other months of the year. Consequently, cattle 

shipped to slaughter from infected herds during June to September are more likely to be infected 

than at other times. If cattle slaughtered during June to September are more likely to be infected, 

then the risk associated with ground beef produced from these cattle may also be elevated 

relative to other times of the year. 

Feedlot Prevalence

As with breeding herds, the prevalence of infected feedlots is also assumed to be constant across 

time. The occurrence of E. coli O157:H7 in feedlots does not show any geographic clustering 

(Hancock et al. 1998b, 2001). Therefore, U.S. feedlot prevalence data are also pooled without 

regard for the region where the data were collected. 

Apparent Feedlot Prevalence 

Four studies provide evidence regarding the apparent prevalence of infected feedlots (Table 3-6). 

Feedlots sampled in each study came from multiple states. 

Dargatz et al. (1997) report on a national survey conducted by USDA in 1994 (Hancock et al. 

1997c). In this study, 100 feedlots were randomly selected throughout the United States; 63 

feedlots were found to contain one or more positive cattle. Thirty fecal samples per pen were 

collected from four pens in each feedlot. About 3% of cattle sampled in positive feedlots were 

fecal positive. 

September 7, 2001 47 
3. Exposure Assessment 

TABLE 3-6 Evidence Used to Estimate Feedlot Prevalence 

Study 

Feedlots 

Tested 

Positive 

Feedlots 

Apparent 

Feedlot 

Prevalence

Average 

Samples per 

Feedlot 

Apparent 

WithinFeedlot 

Prevalence

Lab 

Methods 

Months 

Sampled 

Dargatz et 

al. 1997 

100 63 63% 120 3% 0.1 g, 

SMACct 

October–

December

Hancock et 

al. 1998b 

6 6 100% 174 4% 0.1 g, 

SMACct 

July–

November

Smith 1999 5 5 100% 611 23% 10 g, IMS June–

September

Elder et al. 

2000 

29 21 72% 12 36% 10 g, IMS July–

August 

Note: g = grams of feces analyzed, 

SMACct = sorbitol MacConkey media with cefixime and tellurite, and 

IMS = immunomagnetic separation. 

Hancock et al. (1998b) completed a survey of six feedlots in Idaho, Oregon, and Washington 

during 1996. At least one positive cattle was detected in each feedlot. An average of 174 samples 

were collected per feedlot, and about 4% of cattle in positive feedlots were positive. 

Smith (1999) sampled five midwestern feedlots, and all were found to contain positive cattle. 

Four to five pens were intensively sampled in each feedlot during a 3-month period during 

summer 1999. An average of 611 samples were collected per feedlot, and 23% of cattle in these 

feedlots were positive. This study used much more sensitive test methods than the previous 

studies. 

Elder et al. (2000) also used very sensitive test methods to sample cattle at four midwestern 

slaughter plants in 1999. It was assumed that each lot of cattle sampled in this study represented 

a pen of cattle originating from a randomly selected feedlot. Of the 29 lots sampled, 21 were 

detected to contain one or more positive cattle. While an average of only 12 samples were 

collected per lot, 36% of the cattle were E. coli O157:H7-positive in positive lots. 

True Feedlot Prevalence 

To estimate true feedlot prevalence, the same methods were used as described for breeding herd 

prevalence (Equations 3.1 to 3.4). Herd sensitivity (HSens) was estimated to be 0.77, 0.86, 0.99, 

and 0.81 based on analysis of the Dargatz et al. (1997), Hancock et al. (1998b), Smith (1999), 

and Elder et al. (2000) studies, respectively. 

Figure 3-9 shows the estimated distribution for true feedlot prevalence. This distribution 

suggests that feedlot prevalence is most likely 90%, but it may be as low as 70% or as high as 

100%. 

These results imply that most, if not all, U.S. feedlots contain one or more E. coli O157:H7-

infected cattle. Such a result is not surprising given the management—and high turnover rate—of 

cattle in feedlots. Cattle entering feedlots are typically confined in pens, fed from common feed 

bunks, and usually shipped to slaughter 3 to 6 months after arrival. Also, feedlot cattle usually 

originate from multiple locations. Therefore, feedlots hypothetically provide ample opportunity 

for exposure and transmission of E. coli O157:H7 to cattle. The elevated feedlot prevalence 

estimate from this risk assessment supports such a hypothesis. 

September 7, 2001 48 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

0.00

0.02

0.04

0.06

0.08

0% 20% 40% 60% 80% 100%

Feedlot Prevalence

Probability

FIGURE 3-9 Resultant uncertainty distribution for true feedlot prevalence after analysis of data in 

Table 3-6. 

Within-Feedlot Prevalence

Within-feedlot prevalence is estimated using the same methods employed for breeding herds. 

Apparent Within-Feedlot Prevalence 

Population variability. Like within-breeding herd prevalence, within-feedlot prevalence also 

varies. Figure 3-10 shows the apparent within-feedlot prevalence distribution for 63 infected 

feedlots (Dargatz et al. 1997). This study included the greatest number of infected feedlots of any 

published report on U.S. feedlots. 

0

5

10

15

20

25

30

1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0% 9.0% 10.0%

Apparent Within-Feedlot Prevalence

Feedlots Observed

FIGURE 3-10 Evidence on the distribution of within-feedlot prevalence of E. coli O157:H7 in 

infected feedlots (adapted from Dargatz et al. 1997). 

September 7, 2001 49 
3. Exposure Assessment 

As discussed previously, this asymmetric distribution plausibly fits an exponential 

distribution. The mean and standard deviation of this distribution are 2.7% and 2.2%, 

respectively. A comparison of this distribution to predictions from an exponential distribution 

with β = 2.7% also shows some agreement (Figure 3-11). Nevertheless, the hypothesis that the 

observed and expected results are equivalent is rejected (χ2 = 18.9, p<0.05). 

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0% 9.0% 10.0%

Apparent Within-Feedlot Prevalence

Cumulative Probability

Dargatz et al. 1997 Exponential

FIGURE 3-11 Comparison of observed and expected cumulative probabilities for within-feedlot 

prevalence of E. coli O157:H7. 

Despite the lack of statistical support to conclude that these data fit an exponential 

distribution, it is assumed that within-feedlot prevalence can be adequately represented with such 

a distribution. As with breeding cattle studies, most available feedlot data only allow estimation 

of average within-feedlot prevalence. Therefore, fitting these other data to more complex 

parametric distributions (e.g., lognormal) is not feasible. 

When available data are limited to averages, the principle of Maximum Entropy supports the 

use of an exponential distribution (Vose 1996). This distribution choice is likely conservative 

because disagreement between the observed and theoretic distributions tends to occur at lower 

prevalence levels. Nevertheless, because within-herd prevalence was shown to fit an exponential 

distribution, such a distribution seems biologically plausible. 

Seasonal variability. Most studies of feedlot cattle were completed over limited times of the 

year. Therefore, evidence of a summer season peak in prevalence is limited for this class of 

cattle. One Canadian study, which included fed steers and heifers, showed peak prevalence in the 

summer (Van Donkersgoed et al. 1999). Most U.S. studies completed between June and 

September report higher E. coli O157:H7 prevalence levels than studies completed at other times 

of the year. 

Seasonal variability in within-feedlot prevalence is modeled using the same methods as 

applied to within-breeding herd prevalence. Although the epidemiology of E. coli O157:H7 in 

cattle is not completely characterized, it seems unlikely that factors (e.g., feed or water 

September 7, 2001 50 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

contamination) associated with increased transmission in the warm summer months in breeding 

cattle are different for feedlot cattle. 

Evidence of Apparent Within-Feedlot Prevalence 

Five studies provide evidence on apparent within-feedlot (Table 3-7). Dargatz et al. (1997) 

detected 63 positive feedlots in a national USDA survey. The prevalence of E. coli O157:H7-

positive cattle in positive feedlots was about 3%. Sampling was conducted between October and 

December 1994. 

TABLE 3-7 Evidence Used to Estimate Within-Feedlot Prevalence 

Study 

Number Tested 

in Positive 

Feedlots 

Positive in 

Positive 

Feedlots 

Apparent 

Within-Feedlot 

Prevalence Lab Methods Months Sampled 

Dargatz et al. 

1997 

7,560 210 2.8% 0.1 g, SMACct October–December 

Hancock et al. 

1998b 

1,046 38 3.6% 0.1 g, SMACct July–November 

Hancock et al. 

1999 

240 14 5.8% 0.1 g, SMACct November–January, 

May–June 

Smith 1999 3,054 707 23.1% 10 g, IMS June–September 

Elder et al. 2000 254 91 35.8% 10 g, IMS July–August 

Note: g = grams of feces analyzed, 

SMACct = sorbitol MacConkey media with cefixime and tellurite, and 

IMS = immunomagnetic separation. 

Hancock et al. (1998b) found six positive feedlots in three northwestern states. The apparent 

within-feedlot prevalence was 4%. This study was completed between July and November 1996. 

Hancock et al. (1999) studied the prevalence of E. coli O157:H7 in the feces of steers and 

heifers from eight lots at four slaughter plants. When sampling was done just after the cattle were 

stunned in the slaughter plant, 5.8% of 240 cattle were reported positive. Sampling was 

conducted in November 1995 to January 1996, and May to June 1996. 

Smith (1999) found five positive midwestern feedlots that contained large numbers of 

positive cattle. The reported apparent within-feedlot prevalence was 23%. The study was 

conducted from June to September 1999. 

Elder et al. (2000) sampled cattle at four midwestern slaughter plants and found 21 positive 

lots. Within those lots, the prevalence of test-positive cattle was about 36%. This study was 

conducted in July and August 1999. 

Three of these studies used the same sampling and lab methods (Dargatz et al. 1997; 

Hancock et al. 1998b, 1999). These methods are reportedly 58% sensitive (Sanderson et al. 

1995). In contrast, the other studies collected 10-gram samples and used an IMS process 

followed by microbiologic culture to improve the detection of E. coli O157:H7 in fecal samples. 

As explained previously, this protocol is assumed to be 100% sensitive. 

True Within-Feedlot Prevalence 

True within-feedlot prevalence data were organized by study months (Table 3-8). No empirical 

evidence was available between February and April. Therefore, prevalence for these months was 

calculated using moving averages from the 3 preceding months. 

September 7, 2001 51 
3. Exposure Assessment 

TABLE 3-8 Point Estimates for Monthly True Within-Feedlot Prevalence for Each of Five 

Studies (Table 3-6). A weighted average for each month was calculated (based on average 

numbers of samples collected per month per study), and a seasonal average was calculated for 

the high and low prevalence seasons. 

Weighted Average 

Month 

Dargatz et 

al. 1997 

Hancock et 

al. 1998b 

Hancock et 

al. 1999 

Smith 

1999 

Elder et 

al. 2000 Average 

January 18% 18% 

February 10% 

March 11% 

April 13% 

May 4% 4% 

June 4% 24% 23% 

July 6% 24% 37% 22% 

August 6% 24% 37% 22% 

September 6% 24% 20% 

October 5% 6% 5% 

November 5% 6% 18% 5% 

December 5% 18% 5% 

Weights 2,520 209 48 764 127 

October–May average (low prevalence season) 9% 

June–September average (high prevalence season) 22% 

January–December average 13% 

Figure 3-12 illustrates nine random iterations of a Monte Carlo model estimating monthly 

within-feedlot prevalence. A strong seasonal peak is evident from this graph and is consistent 

from iteration to iteration. 

0%

5%

10%

15%

20%

25%

30%

Average Within-Feedlot Prevalence

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Centered 3-month

moving average

FIGURE 3-12 Estimated average monthly within-feedlot prevalence. This illustrated seasonal 

trend is based on 1,000 iterations of the model. 

September 7, 2001 52 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Figure 3-13 shows the uncertainty about the low and high prevalence seasonal averages. The 

mean within-feedlot prevalence is 9% and 22% for the low and high prevalence seasons, 

respectively. In contrast to the breeding herd analysis (Figure 3-8), the two seasonal distributions 

are distinctly different, and there is more than a twofold difference between the low and high 

prevalence seasons for feedlots. 

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0%2%4%6%8%

10%12%14%16%18%20%22%24%26%28%30%

Average Within-Feedlot Prevalence

Probability

Low prevalence season

(October–May)

High prevalence season

(June–September)

FIGURE 3-13 Uncertainty about low and high prevalence seasons’ estimated average withinfeedlot prevalence. These distributions were estimated using 1,000 Monte Carlo iterations of the 

model. 

These results imply that within-feedlot prevalence is greater than within-breeding herd 

prevalence. This difference may be related to cattle age. Feedlot cattle age is typically less than 1 

year, while breeding cattle age is over 2 years. A higher prevalence of infection in younger cattle 

has been previously demonstrated (Hancock et al. 1994; Dargatz et al. 1997; Mechie et al. 1997; 

Heuvelink et al. 1998; Van Donkersgoed et al. 1999). Acquired or natural immunity may 

increase with cattle age and result in increased resistance to infection by older cattle. Regardless 

of cause, the differences in within-feedlot and within-breeding herd prevalence seem consistent 

with the available evidence. 

These results also show that within-feedlot prevalence increases substantially during June to 

September. At all times of the year, feedlot cattle sent to slaughter are more likely than breeding 

cattle to be infected. Yet this discrepancy is greatest during the high prevalence season. While 

there are differences in management between feedlots and breeding herds, the available data do 

not explain why the seasonal peak is much greater for feedlots than for breeding herds. 

Transportation Segment 

Transmission of E. coli O157:H7 from infected to susceptible cattle may occur when cattle are 

transported to slaughter. Alternatively, some infected cattle may rid themselves of infection 

during the period they are being shipped to slaughter. This segment addresses the effect of 

transportation on prevalence of E. coli O157:H7 in feces and hides. 

September 7, 2001 53 
3. Exposure Assessment 

Transportation Effects on Fecal Prevalence

Empirical evidence suggests that there is no dramatic difference in fecal prevalence between the 

farm and slaughter plant. Rice et al. (1997) collected fecal samples of culled dairy cattle both at 

the farm and at slaughter. Of 205 samples collected at the farm, 3.4% were E. coli O157:H7-

positive. Of 103 samples collected at slaughter, 3.9% were E. coli O157:H7-positive. Of 89 

paired samples (farm and slaughter), 2.2% were positive at both the farm and slaughter, 3.3% 

were positive at the farm only, and 2.2% were positive at slaughter only. 

In a study of New York cull cows (Cornell 1998), 1.3% of 3,323 cull dairy cows were fecal 

positive for E. coli O157:H7 at a slaughter plant. No difference in the average transit time was 

found between E. coli O157:H7-positive cattle and E. coli O157:H7-negative cattle (32.6 and 

31.7 hours, respectively). Therefore, duration of transportation was not associated with being 

fecal positive. 

In a national study of dairy cattle, 2.8% of approximately 600 cows to be culled within the 

subsequent 7 days were fecal positive for E. coli O157:H7 (APHIS-VS-NAHMS 1998). This 

study also collected fecal samples from over 2,200 dairy cows at livestock markets across the 

country and found 1.8% of these animals E. coli O157:H7-positive. 

The data do not suggest that E. coli O157:H7 prevalence increases during transport to 

slaughter. Therefore, no effect from transport is included in the model. 

Feedlot cattle are typically shipped directly to slaughter and processed the same day. 

Therefore, it is reasonable that prevalence is unaffected by transport of this class of cattle. On the 

other hand, culled breeding cattle are more likely to be shipped to slaughter via livestock 

markets. This marketing route seemingly increases the elapsed time for shipment. If E. coli

O157:H7 is transmitted to susceptible cattle during this transport time, the evidence suggests that 

infected cattle are ridding themselves of infection at a rate equivalent to the transmission rate. In 

this case, prevalence after shipping remains the same as prevalence before shipping. 

Transportation Effects on Hide Contamination

Transit between the farm and slaughter plant may be important in causing changes in hide 

prevalence. Studies of hide contamination with Salmonella suggest an increase in prevalence of 

hide-contaminated cattle between the farm and slaughter (Puyalto et al. 1997; Cornell 1998). 

Data are limited on E. coli O157:H7 hide-contaminated cattle. In one study, 1.7% of 240 

feedlot cattle at four slaughter plants had hair samples that were E. coli O157:H7-positive 

(Hancock et al. 1999). Paired fecal samples were collected from the animals in this study, and no 

correspondence between fecal and hide status was found. Elder et al. (2000) collected nonpaired 

fecal and hide samples from cattle at four slaughter plants. Average fecal prevalence was 28%, 

yet average hide prevalence was only 11%. Generally, hide-positive lots also contained fecalpositive cattle, but fewer lots were detected from hide sampling. Another study conducted by the 

American Meat Institute (Bacon et al. 2000) found that 3.6% of 2,245 cattle were hide-positive 

from samples collected at 12 slaughter plants. 

Some researchers hypothesized that the degree of visible soiling of cattle surfaces (e.g., 

hides, hair) with mud, manure, and/or bedding is correlated with microbial contamination of 

carcasses (Van Donkersgoed et al. 1997; Jordan 1998). Yet no clear correlation was found. The 

concentration of E. coli Biotype I organisms on carcasses changed very little whether the lot was 

composed of cattle that had substantial hide soiling or were relatively clean. The implication of 

this research is that the role of E. coli O157:H7 hide contamination in carcass contamination may 

not be correlated with grossly visible soiling. 

Because there are no data on E. coli O157:H7 hide-contaminated cattle at the farm and only 

limited data on hide prevalence at the slaughter plant, the effect of transit time on hide 

September 7, 2001 54 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

contamination cannot be examined at this time. The available evidence suggests that fecal 

prevalence may be a better predictor of carcass contamination than hide prevalence (Elder et al. 

2000). If this is the case, then incorporating the effect of hide contamination may be 

inconsequential. Nevertheless, better hide sampling methods are needed to fully assess the 

importance of hide prevalence. 

Slaughter Plant Intake Segment 

Breeding Cattle

Culled dairy and beef cattle arrive at the slaughter plant from their farms of origin after transit on 

trucks. The majority of these cows and bulls arrive after first being shipped to one or more 

livestock markets where they are auctioned to the highest bidder and then shipped to slaughter 

(APHIS:VS:CEAH 1994). 

The combined average herd size for dairy and beef herds is approximately 300 cows (NASS 

1998). Approximately 25% of cows in dairy herds, and 11% of cows in beef herds, are culled 

each year (APHIS-VS-NAHMS 1996, 1997). These culling percentages imply that the average 

herd would ship from 1 to 1.5 cattle per week. 

Given the low culling rate per herd, it is reasonable to assume random mixing of breeding 

cattle at slaughter plants. Such an assumption implies that the prevalence of E. coli O157:H7-

infected breeding cattle at slaughter is the product of herd prevalence and within-herd 

prevalence. It also implies that the probability of one cow on the slaughter line being infected is 

independent of the probability of another cow on the slaughter line being infected. A violation of 

this assumption would be a group of cows (i.e., 40 cows) from the same farm all sent to slaughter 

together and then slaughtered one after the other. In this case, the prevalence of infected cows in 

this group is expected to equal the within-herd prevalence of their herd of origin. Violation of a 

random mixing assumption is expected to occur rarely. 

The number of infected cows and bulls in a group of 40 such animals presented for slaughter 

was simulated using Monte Carlo techniques. Forty head was a convenient count as it is the 

capacity of most trucks used to haul cattle to slaughter. Each cow and bull was simulated as an 

individual. The probability of infection is equal to the product of herd prevalence (H) and 

average within-herd prevalence (w). The number of infected culled breeding cattle per truckload 

(B) is simulated as follows: 

B [ ,1Binomial H lExponentia ( ) w (3.6) 

40

1

= ∑ × ]

Within-herd prevalence varies in the population and by season. Average within-herd 

prevalence (w) is therefore greater for cattle shipped to slaughter during June through September 

than for cattle shipped during the rest of the year (see Figure 3-8). To model population 

variability, an exponential distribution—whose only parameter is the mean within-herd 

prevalence (w)—is used. Monte Carlo simulations then estimate the number of infected 

cows/bulls in truckloads for the low and high prevalence seasons. 

Feedlot Cattle

Steers and heifers arrive at slaughter plants after being transported from their feedlot of origin in 

a tractor-trailer truck with a capacity of about 40 head. Most steers and heifers (over 90%) are 

shipped directly from the feedlot to slaughter without going through a livestock market 

(APHIS:VS:CEAH 1994). Furthermore, these cattle are typically slaughtered together in a group, 

September 7, 2001 55 
3. Exposure Assessment 

although they may be mixed during slaughter with one or more truckloads of cattle from other 

feedlots. 

The manner by which feedlot cattle are marketed does not support the assumption of random 

mixing used for culled breeding cattle. Instead, feedlot cattle are much more likely to be 

processed at the slaughter plant in a clustered pattern. Cattle within the same truckload will all 

have the same probability of infection because they originated from the same pen in a feedlot. 

The number of infected feedlot cattle per truckload (F) is simulated as follows: 

F = ( ,1Binomial H ) × [40Binomial ,Exponential (w)] (3.7) 

Each truckload is independently determined to be from an infected or noninfected feedlot 

based on feedlot prevalence (H). If the truck is from an infected feedlot, then the number infected 

in the truckload is determined based on the appropriate seasonal within-feedlot prevalence (w). 

Within-feedlot prevalence varies according to the exponential distribution. 

Production Module Results 

The four critical inputs to the production module are herd prevalence, within-herd prevalence, 

feedlot prevalence, and within-feedlot prevalence of E. coli O157:H7. Herd prevalence is the 

proportion of all breeding herds that contain one or more infected cattle. Feedlot prevalence is 

similar, but the reference population is U.S. feedlots. Within-herd (or within-feedlot) prevalence 

is the proportion of infected cattle within a herd (or feedlot), given that the herd contains one or 

more infected cattle. Within-herd (or within-feedlot) prevalence is a random variable that 

modulates by season. Given the available data, these inputs are quantitatively determined. 

Analysis of available evidence provides average, 5th, and 95th percentile estimates for these 

inputs (Table 3-9). Generally, these results demonstrate that E. coli O157:H7 prevalence is 

significantly greater for feedlot cattle than for breeding cattle (e.g., the 95th percentile for herd 

prevalence is less than the 5th percentile for feedlot prevalence). Similar findings apply to 

comparisons between within-herd and within-feedlot prevalence, regardless of season. 

TABLE 3-9 Statistics for Uncertain Parameters in the Production Module 

Model Input 5th Percentile Mean 95th Percentile

Breeding herd prevalence 55% 63% 72% 

Feedlot prevalence 78% 88% 97% 

Low prevalence season (October to May) 

Average within-herd prevalence 2% 3% 4% 

Average within-feedlot prevalence 6% 9% 14% 

High prevalence season (June to September) 

Average within-herd prevalence 3% 4% 5% 

Average within-feedlot prevalence 21% 22% 24% 

E. coli O157:H7 prevalence was lower for adult cattle than for feedlot cattle in a yearlong 

Canadian slaughter survey (Van Donkersgoed et al. 1999). In that survey, 2% of breeding cattle 

and 12% of feedlot cattle were fecal positive. 

September 7, 2001 56 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

The model’s annual predictions are the same as this Canadian survey. Average breeding 

cattle prevalence at slaughter is 3% for the June to September period and 2% for the rest of the 

year (63% × 4% and 63% × 3%, respectively). Feedlot cattle prevalence at slaughter is 19% for 

the June to September period and 8% for the rest of the year (88% × 22% and 88% × 9%, 

respectively). Therefore, on an annual basis, the model predicts that 2% of breeding cattle—and 

12% of feedlot cattle—are E. coli O157:H7-infected just prior to slaughter. Because Van 

Donkersgoed et al. (1999) used very sensitive test methods, the concordance of this model’s 

results with that survey is especially noteworthy. 

The production module simulates cattle entering the slaughter process via truckloads. 

Therefore, prevalence of infection within truckloads is this model’s output and the first input to 

the slaughter module. The prevalence of infected cattle within truckloads influences the level of 

E. coli O157:H7 contamination that occurs during slaughter. Generally, when the prevalence in a 

truckload is elevated, contamination during slaughter is also elevated. 

For breeding cattle, about 45% of truckloads are predicted to have no infected cattle (i.e., 0% 

prevalence) during the low prevalence season (Figure 3-14). Because of model input uncertainty, 

confidence limits for 0% prevalence are between 40% and 52% of truckloads. During the high 

prevalence season, 35% ( 7.5%) of these truckloads are predicted to have no infected cattle. 

Therefore, truckloads containing infected cattle arrive more frequently at slaughter plants 

between June and September than at other times of the year. 

±

FIGURE 3-14 Comparison of seasonal distributions for prevalence of infected cattle within 

truckloads of breeding cattle sent to slaughter. Error bars show the 5th 

an

Low Prevalence Season

(October–May)

Breeding Cattle

0%

10%

20%

30%

40%

50%

60%

0% 3% 5% 8% 10% 13% 15%

Prevalence of Infected Live Cattle Pre-Slaughter

Frequency of Trucks

High Prevalence Season

(June–September)

Breeding Cattle

0%

10%

20%

30%

40%

50%

60%

0% 3% 5% 8% 10% 13% 15%

Prevalence of Infected Live Cattle Pre-Slaughter

Frequency of Trucks

d 

95th percentiles of uncertainty about frequency of trucks at each prevalence level. 

For feedlot cattle, the frequency of truckloads with no infected cattle is about 32% in the low 

prevalence season and 20% in the high prevalence season (Figure 3-15). Furthermore, there are 

essentially no trucks with prevalence greater than 30% during the low prevalence season. During 

the high prevalence season, however, there is a nonnegligible frequency of trucks with greater 

than 50% prevalence. In fact, there is a 0.1% frequency of trucks with 100% prevalence in the 

high prevalence season (not shown). 

The production model outputs are distributions for cattle prevalence just prior to slaughter. 

These outputs become the inputs for the slaughter model to follow. The model results predict that 

feedlot cattle are more likely than breeding cattle to be infected. Furthermore, regardless of cattle 

type, higher frequencies of infected cattle enter slaughter plants during the June to September 

period than during the rest of the calendar year. These differences are based on survey data 

collected in the United States and have been independently verified by data collected in Canada. 

September 7, 2001 57 
3. Exposure Assessment 

Low Prevalence Season

(October–May)

Feedlot Cattle

0%

10%

20%

30%

40%

50%

0%5%

10%15%20%25%30%35%40%45%50%

Prevalence of Infected Live Cattle Pre-Slaughter

Frequency of Trucks

High Prevalence Season

(June–September)

Feedlot Cattle

0%

10%

20%

30%

40%

50%

0%5%

10%15%20%25%30%35%40%45%50%

Prevalence of Infected Live Cattle Pre-Slaughter

Frequency of Trucks

FIGURE 3-15 Comparison of seasonal distributions for prevalence of infected cattle within 

truckloads of feedlot cattle sent to slaughter. Error bars show the 5th and 95th percentiles of 

uncertainty about frequency of trucks at each prevalence level. 

SLAUGHTER MODULE 

The slaughter module estimates the occurrence and extent of E. coli O157:H7 contamination as 

live cattle transition to carcasses, then to meat trim, and finally to aggregates of meat trim in 60-

pound trim boxes or 2,000-pound combo bins destined for commercial ground beef production. 

This module links the production of live cattle to the preparation of ground beef meals by 

consumers. 

Explanation of Scope 

Two types of slaughter plants are modeled: those that handle culled breeding cattle and those that 

handle feedlot cattle. Nevertheless, the same physical plant might slaughter both classes of cattle. 

Table 3-10 shows annual slaughter numbers by plant capacity. Forty percent of culled 

breeding (cow/bull) cattle are slaughtered in large facilities that handle more than 1,000 head per 

day, while greater than 90% of feedlot (steer/heifer) cattle are slaughtered in such facilities. 

TABLE 3-10 Number of Cattle Slaughtered by Type and Plant Capacity, United States, 1997 

Annual Number Slaughtered 

Plant Capacity Breeding Cattle (Cow/Bull) Feedlot Cattle (Steer/Heifer) 

<1,000 head per day 4.4 million 2.4 million 

>1,000 head per day 3 million 26 million 

Source: FSIS 1998. 

The model only considers the commercial slaughter and processing of cattle. Although 

custom slaughter is not explicitly considered in this model, it is assumed to represent a small 

fraction of ground beef consumed in the United States. 

Prevalence distributions of E. coli O157:H7 in breeding and feedlot cattle, developed in the 

production module, serve as inputs to the slaughter module. These distributions provide the 

number of infected cattle entering a slaughter plant. 

Slaughter module outputs are distributions of E. coli O157:H7 contamination in combo bins 

and trim boxes. Breeder and feedlot cattle slaughtering operations are modeled separately, as are 

September 7, 2001 58 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

high (June to September) and low (October to May) prevalence seasons. These distributions are 

inputs to the preparation module, where grinding operations begin the process of converting meat 

trim in combo bins or boxes into ground beef. 

Definition of Key Terms 

The following key terms are used throughout this module: 

• Carcass refers to an animal that has been killed and had its hide removed. 

• Contamination is the presence of E. coli O157:H7 on carcass surfaces. 

• Trim is a by-product of processing carcasses to create cuts of meat (e.g., steaks, roasts) 

when the carcasses originate from feedlot cattle. Trim is a primary product that results 

from deboning carcasses that originate from breeding cattle. Trim consists of both muscle 

and fat. 

• Combo bins are containers that hold 2,000 pounds of meat trim (Gill and Badoni 1997; 

Biela 1998). The containers are usually cardboard boxes lined with plastic. Many cattle 

may contribute meat trim to a single combo bin. 

• Boxes of meat trim are similar to combo bins but only contain 60 pounds of product. 

• Lot is defined as the total number of cattle necessary to fill one combo bin. A single lot 

may comprise one or more truckloads of cattle. 

Slaughter Module Segments 

The slaughter module includes seven steps: (1) arrival of live cattle at slaughter plant, 

(2) dehiding, (3) decontamination following dehiding, (4) evisceration, (5) final washing, 

(6) chilling, and (7) carcass fabrication (i.e., creation of trim) (Figure 3-16). Although there are 

other steps that are normally part of the slaughter process (e.g., stunning, carcass splitting), these 

are not explicitly modeled. Generally, these other steps are incorporated into the seven steps of 

the model. 

Slaughterhouse operating procedures can either facilitate or mitigate the probability of E. coli

O157:H7 contamination on beef carcasses or trim (Galland 1997). Decontamination steps can 

significantly reduce the numbers of E. coli O157:H7 and other pathogens on the carcass (Bacon 

et al. 1999). The model assumes that either contamination or decontamination can occur at each 

step of the process, with the prevalence and extent of contamination increasing if further 

contamination occurs and decreasing if decontamination occurs. It is possible that a 

decontamination process is completely effective in eliminating E. coli O157:H7 from a carcass, 

thereby reducing the prevalence of contaminated carcasses. The probability and extent of E. coli

O157:H7 contamination or decontamination during slaughter are modeled as dependent on status 

of the incoming animal, type of processing plant, type of equipment and procedures used, 

efficacy of decontamination procedures, and sanitation processes. 

Cattle arrive at slaughter plants (Step 1) via truckloads with variable prevalence of infected 

cattle. Because slaughter lots may consist of multiple truckloads, each truck’s prevalence is 

estimated in this step, and the total number of infected cattle in the lot is estimated based on the 

total number of infected cattle on trucks contributing to a combo bin. 

Dehiding (Step 2) is the transition from live cattle to carcasses. The process of removing the 

hide creates the first opportunity for surface contamination of the carcass with E. coli O157:H7 

and other pathogenic and nonpathogenic microbes. The number of E. coli O157:H7 organisms 

that initially contaminate a carcass depends on the level of infected cattle, the average 

September 7, 2001 59 
3. Exposure Assessment 

Step 2

Step 3

Step 4

Carcass splitting

Step 5

Step 6

Step 7

Placement of trim in

combo bins and boxes

Ovals denote steps that may either

increase or decrease contamination.

Rectangles denote steps with little

or no increase in contamination.

Step 1 Input from

Production Module

Live Animal

Chiller

Evisceration

Knock box and stunning

Dehiding

First decontamination

(trim/vacuum/wash)

Second decontamination

(final wash)

Carcass fabrication

Trim

Primals sent off-site

as boxed beef

FIGURE 3-16 Steps modeled in the slaughter module. 

concentration of E. coli O157:H7 per contaminated area, and the total area of a carcass that is 

contaminated (Galland 1997). Contamination introduced during dehiding can be reduced during 

decontamination (Step 3). During decontamination, trimming, vacuuming, or washing of the 

carcass surface can reduce the number of organisms on contaminated carcass surfaces (Prasai et 

al. 1995). 

Evisceration (Step 4) is another opportunity for contamination to be introduced. If any part of 

the gastrointestinal tract is perforated during the evisceration procedure, E. coli O157:H7 

contamination of muscle tissue can occur. Carcass splitting and final washing (Step 5) follow 

evisceration. During final washing, carcasses are washed or steam pasteurized. Washing is the 

September 7, 2001 60 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

forceful application of hot or cold water to the surface of the carcass, and pasteurization is the 

application of steam to the surface of the carcass. 

Following final washing, the carcasses move to the chiller (Step 6), where E. coli 

contamination may again increase or decrease. After chilling, the carcasses are fabricated (Step 

7). Fabrication involves separating the carcass further into smaller units, trimming these units of 

excess fat, and—in the case of carcasses from breeding cattle—manually and/or mechanically 

separating muscle from bone. Feedlot carcasses are typically separated into primal (e.g., 

quarters) and subprimal units that are used to produce whole-muscle cuts of beef. A by-product 

of fabricating carcasses from feedlot cattle is meat trim, a product that is mixed and ground to 

produce ground beef. Because carcasses from breeding cattle produce less valuable whole 

muscle cuts, greater proportions of these deboned carcasses than carcasses from feedlot cattle 

contribute to ground beef. The boneless meat trim from one animal is distributed based on fat 

content into multiple combo bins or boxes, where it is mixed with trim from other cattle. 

Fabrication can also result in new or additional contamination through cross-contamination of 

work surfaces. 

The following sections describe data and analysis of each slaughter step. 

Modeling the Slaughter Process 

Arrival of Live Animals (Step 1) 

Live cattle are shipped to slaughter via trucks, where they are placed in holding pens prior to 

entering the knock box. The production module predicts the prevalence of infected cattle per 

truckload. As mentioned previously, prevalence varies by class of cattle and season. It is 

assumed that animals arriving at the plant together are processed together. 

Number of Trucks Per Lot

The number of trucks that contribute to a slaughter lot depends on the class of cattle, the weight 

of trim generated per carcass, and the number of combo bins to which carcasses can contribute. 

In 1998, 16.2 million steers, 10.6 million heifers, 5.9 million cows, and 0.6 million bulls 

were commercially slaughtered. Average carcass weights (ACW) for steers, heifers, cows, and 

bulls were assumed to be 764, 703, 539, and 851 pounds, respectively (NASS 1998). The 

proportion of carcass weight that amounts to trim ( ρ ) is 18% for steer/heifer carcasses, 53% for 

cow carcasses, and 90% for bull carcasses (Duewer 1998; AMIF 1996). These values represent 

midpoints of uncertainty distributions. Generally, these distributions can range ± 20%. 

Trim from one steer/heifer may go into a variable number of combo bins. The actual number 

of bins is a function of the number of trim lines operating simultaneously in a particular plant. In 

steer/heifer slaughter plants, it was assumed that the number of combo bins to which an 

individual carcass contributes (n) ranged from 2 to 6. In cow/bull plants, this range was 2 to 4. 

Uncertainty about the most likely number of combo bins per carcass was modeled as a 

uniform(2,5) and uniform(2,3) for steer/heifer and cow/bull plants, respectively. The ranges and 

most likely values were modeled using triangular(min, most likely, max) distributions. 

The weight of trim a carcass contributes to a single combo bin (ζ) is calculated as follows: 

n

ρ × =ζ ACW (3.8) 

The number of carcasses per combo bin equals 2,000 pounds ÷ζ. It is assumed that there are 

40 cattle per truckload. Therefore, this number of carcasses determines the number of truckloads 

September 7, 2001 61 
3. Exposure Assessment 

of live cattle that contribute to a combo bin (TLD). Consequently, the number of truckloads per 

lot is as follows: 

40

2000 TLD

× =ζ (3.9) 

Number of Infected Cattle Per Truck and Lot

Number of infected cattle per truckload originating from breeding herds or feedlots has been 

previously calculated (Equations 3.6 and 3.7). Trucks in a lot are assumed independent. The total 

infected cattle in a lot (κ) is the sum of infected cattle from each truck in the lot. 

Knock Box and Stunning (Not Modeled) 

When it is time for slaughter, the animal is directed out of the holding pen or taken off the truck 

via a chute to the “knock box,” where it is stunned. As the stunned animal falls, it is shackled on 

one hind leg, raised, and attached by a chain to an overhead rail. A knife is used to slit the throat, 

and the animal is bled out prior to entering the main floor of the slaughter plant. 

Cross-contamination of hides is possible as cattle fall to the floor or come into contact with 

sides of the chute after previously E. coli O157:H7-contaminated cattle have passed through. 

Additional contamination can occur if cattle emit feces or rumen contents at the knock box 

(Delazari et al. 1998a, 1998b) or if dirty knives are used (Labadie et al. 1977). 

The production module notes the limited data regarding prevalence of E. coli O157:H7 on 

hides and the incomplete analysis of hide sampling method sensitivity. Furthermore, the 

strongest correlate with carcass contamination is believed to be the fecal status of incoming cattle 

(Elder et al. 2000). Therefore, the stunning step is not explicitly included in the model. 

Nevertheless, the contribution of hide contamination to carcass contamination is implicit in the 

conversion of live cattle prevalence to carcass prevalence within lots. 

Dehiding (Step 2) 

At this step, cattle enter the main floor of the slaughter plant. Horns and hocks are removed using 

hydraulic cutters. The udder is removed, the head is skinned, and the hide is cut down the 

midline, legs, and front shanks. 

Contamination Occurrence during Dehiding

The dehiding operation is where a carcass is created. It is at this point that normally sterile 

muscle and fat tissues on the carcass surface are exposed to microbial contaminants. An 

individual carcass may be self- or cross-contaminated. If the carcass originates from an animal 

that is not infected, contamination may occur via aerosol diffusion or contact with contaminated 

equipment or a contaminated carcass. If the carcass originates from an infected animal, it may be 

self-contaminated via fecal or hide sources or cross-contaminated by the pathways described for 

noninfected animals. 

The exterior surface of the hide and the environment in the dehiding area are recognized 

sources of pathogens (Grau 1987). If any cattle are contaminated with E. coli O157:H7, crosscontamination can occur via workers’ gloves, knives, clothing, or during the changing of the 

hide-puller from one carcass to the next (Gill 1999). It has been suggested that gross microbial 

contamination of the carcass is the result of contamination with feces from the hide, hair, hooves 

and ruptured gut (Siragusa et al. 1998). This contamination can occur as the hide is removed 

September 7, 2001 62 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

from the carcass at several steps. For instance, the tail can flip around and create aerosols (Getz 

1999) or flip back on the carcass during hide removal. Aerosol contamination can also occur 

when the hide separates from the carcass (Galland 1997). Hide-removing machinery called uppullers are possibly more likely to cause aerosol contamination because the hide is being rolled 

up over the carcass rather than below it. 

A transformation ratio (TR) relates the frequency of contaminated carcasses to the frequency 

of infected cattle in a lot. To estimate the fraction of carcasses contaminated during dehiding, 

evidence from a study in four slaughter plants is used (Elder et al. 2000). In this study, cattle 

fecal prevalence and carcass prevalence were measured during July and August 1999. In lots 

showing evidence of E. coli O157:H7 in cattle or on carcasses, 91 of 307 cattle (30%) and 148 of 

312 carcasses at dehiding (47%) were E. coli O157:H7-positive. Therefore, a higher frequency of 

contaminated carcasses than infected cattle was detected in this study. Very sensitive testing 

methods were used in this study, and the results are assumed indicative of the relationship 

between live cattle and carcass prevalence. However, this study was completed during the 

summer months, and inferences drawn from it are most applicable to the high prevalence season 

(June to September). 

It is possible that proportionally fewer carcasses are contaminated during the low prevalence 

season (October to May). Incoming prevalence of infected cattle is generally lower in this 

season. Consequently, the probability of a carcass becoming contaminated may be reduced 

because less contamination enters the slaughter plant environment. In a study of 12 slaughter 

plants conducted in September and October 1999, the prevalence of E. coli O157:H7 hidecontaminated cattle was 3.56%, while the E. coli O157:H7 prevalence of contaminated carcasses 

was 0.44% (Bacon et al. 2000). These results suggest a lower frequency of contaminated 

carcasses than contaminated cattle entering slaughter plants. 

During the high prevalence season, TR is estimated from the Elder et al. (2000) data. 

Uncertainty about TR is modeled by incorporating these data into beta distributions (i.e., TR = 

beta (148 + 1,312 – 148 + 1)

beta (91 + 1,307 – 91 + 1) ). Using the average TR for the high prevalence season, the 

frequency of contaminated carcasses is estimated to be 160% of the prevalence of incoming 

infected cattle. 

During the low prevalence season, TR is modeled as a mixture of the beta distributions based 

on the Elder et al. (2000) data and a uniform distribution with a minimum approaching 0 and a 

maximum of the summer TR. Therefore, more uncertainty is modeled about TR during this 

season. Using the average TR for the low prevalence season, the frequency of contaminated 

carcasses is estimated to be 120% of the prevalence of incoming infected cattle. 

The number of contaminated carcasses per lot (Cd) depends on the number of infected cattle 

per lot (κ ) and TR: 

Cd = κ × TR (3.10) 

It is assumed that Cd is a random Poisson variable (i.e., Cd ~ Poisson [κ × T]). 

Level of Contamination Per Carcass

The number of E. coli O157:H7 organisms on a contaminated carcass at dehiding is calculated 

from the estimated density per cm2

 and the total contaminated surface area. 

No studies have reported the density of E. coli O157:H7 contamination at the dehiding step. 

Bell (1997) measured densities of generic E. coli on carcasses and found 2 logs CFU/cm2

contamination if the carcass came into contact with feces or a contaminated hide, and 1 log 

September 7, 2001 63 
3. Exposure Assessment 

CFU/cm2 contamination due to cross-contamination (e.g., aerosols, hands, equipment, or contact 

with a contaminated carcass). 

More relevant data regarding E. coli O157:H7 density on carcasses are available from the 

FSIS (1994) national baseline survey of slaughter plants. In this survey, a 60-cm2 surface area 

was sampled from each of 2,081 chilled carcasses originating from feedlots. Four (0.2%) 

carcasses were E. coli O157:H7-positive, and enumerated densities were reported (Table 3-11). 

TABLE 3-11 Enumeration of E. coli O157:H7 Densities on Positive Carcasses Detected by FSISUSDA (1994) 

CFU/cm2 Number of Samples Percent of Total 

<0.030 2 50 

0.030 to 0.300 0 0 

0.301 to 3.000 2 50 

Total 4 100 

Elder et al. (2000) found 6 (2%) of 330 chilled carcasses positive for E. coli O157:H7 using 

very sensitive test methods. This prevalence is substantially greater than that found in the FSIS 

survey (0.2%) and suggests that some contaminated carcasses were not detected in the latter 

survey. A ratio of these results (i.e., 0.2% ÷ 2%) suggests that about 10% of contaminated 

carcasses were detected in the FSIS survey and that about 90% of contaminated carcasses were 

below the limit of detection for that survey. This ratio (S) is modeled as follows: 

)16330,16(beta

)142081,14(beta +−+

+ − + S = (3.11) 

Additionally, of the four carcasses reported E. coli O157:H7-positive in the FSIS (1994) 

survey, two (50%) of the positive samples had densities below the measurable limit of 0.03 

CFU/cm2

. Consequently, an average of about 5% of all contaminated carcasses would be 

expected to have values above 0.03 CFU/cm2. 

The proportion of carcasses contaminated below the measurable limit (L) is modeled as L = S

+ (1 – S) × [2 ÷ (4 + 1)]. In other words, the proportion of carcasses below the measurable limit 

includes those carcasses not detected and those detected carcasses with unmeasurable densities. 

A value of one is added to the total enumerated carcasses to adjust for bias (Vose 1996). 

The initial number of E. coli O157:H7 organisms on contaminated carcasses introduced 

during dehiding (I) is modeled as a cumulative frequency distribution (Table 3-12). The 

minimum number of E. coli O157:H7 organisms predicted from this distribution is 1 organism 

on the total contaminated surface area. The maximum number of E. coli O157:H7 organisms is 

assumed to be 3 E. coli O157:H7 per cm2. Although the amount of contamination is variable, 

there is also uncertainty about S and the number of E. coli O157:H7 organisms observed in the 

FSIS survey (1994). 

September 7, 2001 64 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

TABLE 3-12 Inputs Used to Model the Number of E. coli O157:H7 Organisms per Contaminated 

Carcass 

O157 Organisms per cm2 Cumulative Frequency (%) 

0.03 L = S + (1 – S) × [2 ÷ (4 + 1)] 

Uniform(0.3,3.0) L + (1 – S) × [2 ÷ (4 + 1)] 

There is no evidence regarding the total contaminated surface area (A) on carcasses. The 

total outside surface area (TSA) of steer/heifer, cow, and bull carcasses is about 32,000, 23,000, 

and 37,000 cm2

, respectively (McAloon 1999). Arbitrarily, the minimum area that contamination 

might be spread across is assumed to be 30 cm2

 (based on the measurable detection threshold). 

Hypothetically, the maximum area that contamination might be spread across for each carcass 

type is the total outside surface area. Nevertheless, initial model runs showed that contaminated 

surface areas greater than 3,000 cm2

 produced results that were infeasible in comparison with 

FSIS ground beef sampling data (see Appendix A). Therefore, uncertainty about the total 

contaminated surface area is modeled as A = 10triangular[log10(30),log(300),log(3000)]. 

The total number of organisms on a contaminated carcass at dehiding (OCCd) is calculated as 

follows: 

 OCCd = I × A (3.12) 

Therefore, the maximum number of organisms on a contaminated carcass predicted by this 

model is 3 organisms/cm2 × 3,000 cm2, or 9,000 E. coli O157:H7 organisms, and the minimum is 

1 E. coli O157:H7 organism per contaminated carcass. 

First Decontamination (Step 3) 

Following removal of the hide, one or more decontamination steps may be applied depending on 

the amount of visible foreign matter on the carcass. Knife trimming is used to remove visible 

spots of fecal contamination greater than 1 inch in diameter. Spot steam vacuuming is used to 

remove visible spots of fecal contamination that are less than 1 inch in diameter (FSIS 1996). 

Increasingly, plants are rinsing carcasses with hot water and a variety of organic acids prior to 

evisceration. 

Any one of the three decontamination steps can reduce existing E. coli O157:H7 on the 

carcass (Bacon et al. 1999; Galland 1997). The effectiveness of knife trimming is highly variable 

(Prasai et al. 1995), and cross-contamination through the knife cuts can occur if inadequate knife 

sterilization methods are used. Sheridan et al. (1992) and Smeltzer et al. (1998) have identified 

equipment such as knives, gloves, and aprons as reservoirs of bacteria in the slaughterhouse. 

Two experimental studies have measured the reduction of E. coli on inoculated beef resulting 

from rinsing ingesta and manure from the carcass. Gill (1999) reported that carcass rinses 

reduced generic E. coli counts by 0.32 log CFU/cm2. Dorsa et al. (1997) reported a 0.7 log 

CFU/cm2 reduction with a water rinse. 

For decontamination to be effective, the procedure needs to be applied to the affected area. 

While visible signs of foreign matter can be readily identified and removed, bacterial colonies 

themselves are not directly observable. Thus, there is variability associated with the 

decontamination step actually encountering bacterial colonies as well as variability in any 

reductions in contamination. To capture this variation, the reduction from decontamination (D1) 

was modeled using a triangular distribution with a minimum value of 0 logs, an uncertain most 

September 7, 2001 65 
3. Exposure Assessment 

likely value ranging from 0.3 to 0.7 logs, and an uncertain maximum value ranging from 0.8 logs 

to 1.2 logs. 

Evisceration (Step 4) 

During evisceration, the ventral midline of the carcass is split and the gastrointestinal tract is 

removed. The remaining organs (bladder, lungs, heart, etc.) are also removed from the carcass in 

this stage. 

Studies indicate that evisceration is usually carried out with minimal contamination (Bell 

1997; Gill et al. 1996a; Gill et al. 1996b). Nevertheless, it was assumed that E. coli O157:H7 

contamination of muscle tissue could occur if any part of the gastrointestinal tract was perforated 

during the sawing of the brisket (i.e., chest) and other procedures. In addition, the gastrointestinal 

tract of some animals may be weaker and easily tear during evisceration (Galland 1997). 

Brewer (1999) suggests that perforation along the gastrointestinal tract potentially occurs in 

1 out of every 100 carcasses. The probability of this event (ε) is independent of the E. coli

O157:H7 status of the animal from which the carcass originates. Uncertainty about this 

probability uniformly ranges from 0% to 2%. 

If the intestine of a non-E. coli O157:H7-infected animal ruptures during evisceration, then 

self-contamination of that carcass is assumed not to occur. The number of carcasses that are 

contaminated at evisceration (Ce) is calculated as follows: 

Ce = κ × ε (3.13) 

It is assumed that Ce is a binomial distribution (i.e., Ce ~ binomial(κ, ε). If a rupture occurs in 

a carcass from an infected animal, then the number of E. coli O157:H7 that contaminate this 

carcass is predicted as described for dehiding (OCCe = I × A). 

Carcass Splitting (Not Modeled) 

At this step, the carcass is sawed in half, the tail is removed, and excess fat is trimmed away 

from each side. Hypothetically, the carcass might become contaminated with E. coli O157:H7 if 

a clean carcass comes into contact with contaminated machinery, hands, or other contaminated 

carcasses during splitting. No data are available on this type of contamination. 

Second Decontamination (Step 5) 

The second decontamination step occurs after carcass splitting. Different procedures for this 

decontamination step are used depending on the size of the plant. 

Knife trimming of visibly contaminated meat occurs in both large and small plants after the 

carcass is split. Spot steam vacuuming may also be used in some plants. Many plants have 

implemented at least two decontamination interventions, such as steam pasteurization and 

carcass rinses, that are effective in reducing pathogens on carcasses (Federal Register 1998). 

Decontamination of carcasses can occur as visible fecal or ingesta spots are removed from the 

carcass via knife and/or steam vacuuming. During the carcass rinse step, E. coli O157:H7 can be 

reduced or redistributed over the entire carcass (Bell 1997). Steam pasteurization of carcasses 

can significantly reduce contamination, if properly done (Gill 1998). 

It was assumed that large plants typically use a steam pasteurization process with four steps: 

(1) four sides of beef are enclosed in a stainless steel pressure chamber, (2) vertical blowers 

remove excess surface water, (3) steam is applied for 5 to 15 seconds, and (4) a cold water rinse 

September 7, 2001 66 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

is applied. The effectiveness of this equipment depends on the temperature of the steam and the 

duration it is applied. 

It was assumed that small plants typically use a hot water rinse, sometimes supplemented 

with organic acids. The effectiveness of hot water rinsing is assumed equivalent to that described 

for decontamination Step 1 (D1). 

Efficacy of steam pasteurization has been assessed. Phebus et al. (1997) found a 3.53 ± 0.49 

log CFU/cm2 reduction in E. coli O157:H7 on inoculated carcasses. Gill (1998) reported up to a 

2 log CFU/cm2 reduction for generic E. coli from pasteurizing at 105.0°C (221.0°F) for 6.5 

seconds. Nevertheless, if the carcass was not clean and dry before steam pasteurization, there 

was little effect from steam pasteurization. Other studies have shown reductions in prevalence of 

E. coli O157:H7-contaminated carcasses from steam pasteurization (Nutsch et al. 1997, 1998). 

Kastner (1998) reported that steam pasteurization was effective in reducing E. coli O157:H7 

only if the temperature was 93.3oC (200.0oF) for 6 seconds or more. Phebus (personal 

communication 1999) suggested that the standard industry practice uses 87.8oC (190.0oF) steam 

for 6 to 8 seconds. 

Given standard industry behavior and available evidence, variability in steam pasteurization 

efficacy (i.e., D2 for large plants) was modeled using a triangular distribution with a minimum 

value of 0 logs, an uncertain most likely value of 0.5 to 1.5 logs, and an uncertain maximum 

value of 1.51 to 2.5 logs. 

Chiller (Step 6) 

After the sides of beef are decontaminated for the second time, they go into a blast air chiller for 

24 to 48 hours. FSIS regulations require chilling deep muscle (6 inches) to 10.0o

C (50.0oF) 

within 24 hours and to 7.2o

C (45.0oF) within 36 hours (NACMCF 1993). Sides of beef are 

automatically or manually spaced on overhead rails within the chiller and are periodically 

sprayed with water. Occasionally distilled water, chlorine, or a lactic acid solution may also be 

used. After chilling, the sides are unloaded, graded, and sorted. 

Growth or decline of E. coli O157:H7 on the surface of carcasses is largely a function of time 

and temperature. Fluctuations in chiller temperature, or the outright failure to adequately chill 

carcasses, may enable growth. Gill and Bryant (1997) reported that generic E. coli counts 

increased by 0.25 logs in one slaughterhouse and decreased by 1.34 log CFU/cm2

 in another 

slaughterhouse. Dorsa (1997) found a 1.2 log CFU/cm2

 increase in E. coli O157:H7 on carcasses 

stored for 2 days in the chiller at 5.0°C (41.0oF). Although deep tissue mass cools slowly, it is 

generally sterile and thus not necessarily a problem (Bailey and Cox 1976; Gill 1979). 

Growth or decline is assumed only to occur on carcasses where E. coli O157:H7 is already 

present before entering the chiller. Changes to E. coli O157:H7 populations on carcasses during 

chilling (CH) are modeled using a normal distribution with an uncertain mean ranging from –0.5 

to 0.5 logs and a standard deviation of 1 log. Therefore, the most likely effect from chilling is 

that there is no change in the E. coli O157:H7 count on carcasses, yet substantial changes can 

occur with nonnegligible frequency (e.g., 2 or more logs of growth can occur in 2.5% of lots). 

Carcass Fabrication (Step 7) 

Carcasses move from the chiller to the fabrication floor, which is usually maintained at 10oC 

(50oF). The fabrication step is complicated and typically involves many plant personnel 

operating on different lines to process different parts of the carcass. 

In feedlot cattle plants, sides of beef enter the fabrication step on overhead rails where they 

are cut into primals (major cuts of beef) and subprimals (minor cuts of beef). Most primal cuts 

September 7, 2001 67 
3. Exposure Assessment 

are taken from the rail using a hook and knife. Leftover trim moves on conveyers to either the 

combo bins or to a vacuum packaging area. The trim is either put into combo bins to which dry 

ice is added prior to shipment, or it is vacuum packaged and put into boxes maintained at a 

temperature between 0°C and 2oC (32.0°F to 35.6oF). 

The fabrication area in slaughter plants is cleaned at the end of each day with a hot water 

power washer that may contain sanitizers. Larger pieces of meat and trim are periodically picked 

off equipment and carted away. Knives, chain-mail aprons, and gloves are washed with hot 

water. 

During the cutting and deboning operations, contamination is possible from environmental 

sources and contaminated sides of beef. The major source of contamination is likely to be the 

surface of incoming carcasses. Freshly cut surfaces of meat may be further contaminated when in 

contact with processing surfaces, equipment, conveyer belts, cutting surfaces, knives, gloves, and 

aprons during slaughter (Charlebois et al. 1991). Gill et al. (1999) found that despite a stringent 

sanitation regimen, and inspection by the national regulatory authority and internal plant quality 

assurance staff, E. coli O157:H7 persisted and proliferated on conveyer equipment in obscure 

areas that continued to contaminate the meat-contacting surface.1

Cross-contamination can occur via workers’ hands and the commingling of trim (Newton et 

al. 1978). Fabrication rooms are typically kept at 10oC (50oF), but lapses may occur and the 

higher temperatures that result enable microbial growth. Gill (1996) has demonstrated that the 

practice of cooling meat trim with dry ice in combo bins is generally effective in preventing E. 

coli O157:H7 growth. Scanga et al. (2000) found no difference in the concentration of E. coli

O157:H7 across fat content. Prasai et al. (1995) found no difference in concentrations of E. coli

O157:H7 between hot deboning and cold deboning. 

Minimal data are available on frequency and amounts of E. coli O157:H7 contamination 

during the fabrication process. Three studies report increases in general bacterial growth during 

this process. Hardin et al. (1995) report increased bacterial contamination on beef surfaces 

during the trimming process even with the use of sterile utensils under experimental conditions. 

Charlebois et al. (1991) sampled four locations within fabrication and concluded that the 

deboning operations resulted in the highest final count of fecal coliforms on boneless beef. 

Specifically, it was found that of 378 samples, the percent of samples that had more than 500 

fecal coliform/cm2 increased from 0.8% to 6.6%. A study in four plants found increases in 

generic E. coli contamination during fabrication ranging from 0 to 2 logs CFU/cm2

 (Gill 1999). 

The data suggest that the fabrication step might result in increased E. coli O157:H7 

populations on meat trim. The quantitative evidence is limited. Therefore, the fabrication effect 

is indirectly estimated. 

This indirect estimate results from the output of the grinder segment in the preparation 

module. FSIS ground beef sampling data for 2000 were used to set upper and lower limits for 

ground beef contamination (see Appendix A). Simulations of the slaughter segment that resulted 

in expected contamination greater than the upper limits were discarded as implausible. 

Simulations of the slaughter segment that resulted in expected contamination below the lower 

limits had additional contamination added. This additional contamination represents the effect of 

fabrication (F). 

During the low prevalence season, the model estimates the average effect from fabrication to 

be 0.33 logs. This effect can range from 0 logs to 1.5 logs because of uncertainty in the model 

 

1The cleaning regimen involved “the cleaning of the carcass breaking equipment, the removal of gross detritus by 

brushing and sweeping, washing with high pressure sprays of cold water, coating with a foaming detergent, 

washing with high pressure sprays of hot water, and treatment of the cleaned equipment with a chlorine 

sanitizer” (Gill et al. 1999). 

September 7, 2001 68 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

inputs and methods. A 0.33 log increase implies that contamination levels entering combo bins 

are more than doubled (i.e., 100.33 = 2.1) as a result of fabrication. During the high prevalence 

season, the increase from fabrication is 0.22 logs, with a similar range of uncertainty. Therefore, 

the average effect of fabrication is estimated to be substantial from this model. This conclusion 

supports the suggestion of some researchers that fabrication is a critical step for E. coli O157:H7 

transfer and amplification within the slaughter process. 

Contamination in Combo Bins and Boxes 

Contamination from a Single Carcass

For each carcass contaminated during the dehiding step (but not during evisceration), the number 

of E. coli O157:H7 organisms (Ed) after fabrication is calculated as follows: 

Ed = (OCCd × 10–DC1 × 10–DC2 × 10CH × 10F) (3.14) 

In other words, the number of organisms initially on the carcass (OCCd) is proportionally 

reduced by the log reductions predicted by DC1 and DC2, proportionally increased or decreased 

during the chilling step (CH), and proportionally increased during fabrication (F) (Table 3-13). 

TABLE 3-13 Illustrative Example for Calculating the Number of Organisms Remaining on a 

Single Carcass Following Fabrication. In this scenario, contamination only occurs at dehiding. 

Therefore, the evisceration step is omitted in this example. 

Steps Symbol Example Value Comments 

Dehiding (2) OCCd 100 organisms 

First decontamination (3) DC1 0.5 logs 10–0.5 = 0.32, Step 3 results in a 

68% reduction in organisms. 

Second decontamination (5) DC2 1 log 10–1 = 0.1, Step 5 results in a 90% 

reduction in organisms. 

Chilling (6) CH 0 logs 100

 = 1, Step 6 results in no change 

in organisms. 

Fabrication (7) F 1 logs 101

 = 10, Step 7 results in a tenfold 

increase in organisms. 

Organisms remaining 

(Equation 3.4 through 3.13) E 32 organisms 

For a carcass contaminated only at evisceration, the number of E. coli O157:H7 organisms 

(Ee) remaining after fabrication is calculated similarly: 

Ee = (OCCe × 10–DC2 × 10CH × 10F) (3.15) 

Because evisceration contamination occurs after the first decontamination step in the process, the 

first decontamination step does not influence the final number of organisms remaining on this 

carcass. 

For a carcass contaminated at both the dehiding and evisceration steps, the number of E. coli

O157:H7 organisms (Ef) remaining on the carcass after fabrication is calculated as follows: 

[ ] DC DC CH F E f 10OCC)10(OCC 1010 1 2

d e ×××+×= − − (3.16) 

September 7, 2001 69 
3. Exposure Assessment 

Given any E and the surface area contaminated (A), the amount of E. coli O157:H7 

contamination (η ) on a carcass is calculated as follows: 

A

E

η = (3.17) 

The amount of E. coli O157:H7 is signified as ηd ,ηe ,ηb to indicate the type of carcass 

contamination. 

All of the E. coli O157:H7 contamination is assumed to be on the surface of the carcass. 

Seventy-five percent of a steer/heifer carcass surface area is estimated to end up in ground beef 

(McAloon 1999). For cow/bull carcasses, approximately 90% of the surface area goes into trim. 

The number of cm2

 per pound of trim (φ) depends on the total surface area, the percent of 

surface area that becomes trim, and the total weight of trim. It is calculated as 

ρ

φ

× = ACW

TSA a , (3.18) 

where TSAa is the total surface area adjusted for the percent trim. 

For each carcass, the pounds of trim a single carcass contributes to a combo bin are 

previously calculated as ζ (Equation 3.8). Therefore, the total cm2

 placed into a combo bin per 

carcass is the product of ζ and φ. 

Some fraction of the total surface area placed into a combo bin from a carcass is 

contaminated with E. coli O157:H7. This fraction depends on the total cm2 placed in the combo 

bin (ζ × φ) and the probability of a contaminated cm2

 (A ÷TSA). The number of contaminated 

cm

2

 a carcass contributes to a combo bin (CC) is distributed as follows: 

) TSA

A Binomial( ~ CC ×φζ , (3.19) 

The total number of E. coli O157:H7 organisms a carcass contributes to a combo bin (CBO) 

depends on the number of E. coli O157:H7 organisms on the carcass per contaminated cm2 and 

the total contaminated cm2 entering the combo bin. It is distributed as follows: 

Poisson( ~ CBO η ×CC) (3.20) 

Contamination from Entire Lot

A combo bin consists of the contributions from many carcasses. E. coli O157:H7 contamination 

contributed to a combo bin can come from cattle that are contaminated at dehiding, or 

evisceration, or at both steps. The probability that a carcass is contaminated at evisceration 

depends on it being from an infected animal. In contrast, carcasses contaminated at dehiding may 

either originate from infected or noninfected cattle. The probability that a dehiding-contaminated 

carcass is also from an infected animal is unknown but is assumed uniform(0,1). If a lot consists 

of carcasses that are contaminated at dehiding and at evisceration (as predicted by Cd and Ce), 

then the number of carcasses contaminated at both sites (Cb) is predicted as binomial 

[minimum(Cd,Ce),uniform(0,1)]. Therefore, the number of carcasses contaminated only at 

dehiding is Cd – Cb, and the number of carcasses contaminated only at evisceration is Ce – Cb. 

The amount of E. coli O157:H7 contamination in a combo bin depends on the number of 

contaminated carcasses and the amount of contamination each carcass contributes. The total 

September 7, 2001 70 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

amount of E. coli O157:H7 contributed by dehiding-contaminated carcasses (TCBOd) is 

calculated as follows: 

∑ (3.21) 

−

= ×

CC bd

0

d d i TCBO Poisson( )CC i η

Similarly, the total amount of E. coli O157:H7 contributed by eviscerator-contaminated 

carcasses (TCBOe) and those carcasses contaminated at both steps (TCBOb) are calculated as 

follows: 

∑ and (3.22) 

−

= ×

CC be

0

e ie TCBO Poisson( )CC i η

= ∑ × (3.23) 

Cb

0

b b i TCBO Poisson( )CC i η

The total E. coli O157:H7 in a combo bin (TCBO), therefore, is calculated as follows: 

TCBO = TCBOd + TCBOe + TCBOb (3.24) 

Boxes 

Boxes are 60-pound versions of combo bins. Therefore, the number of E. coli O157:H7 in a box 

(TBXO) is calculated as follows: 

TBXO = Poisson ⎝

⎜

⎛

⎠

⎟

⎞ TCBO × 60 pounds

2000 pounds (3.25) 

Slaughter Module Results 

Outputs from the slaughter module are distributions describing the frequency of E. coli O157:H7 

in combo bins (and boxes) generated during high and low prevalence seasons for cow/bull and 

steer/heifer slaughter plants. These outputs become inputs to the preparation module, in which 

the contents of combo bins (i.e., trim) are processed to produce ground beef. 

Combo Bins 

Figure 3-17 shows distributions of E. coli O157:H7 contamination in combo bins generated from 

the slaughter of cows and bulls. These results were estimated from 100 simulations of the model. 

During the low prevalence season, the mean frequency of combo bins containing no E. coli

O157:H7 is 94%, but this frequency might range between 88% and 97% because of uncertainty 

in model inputs. During the high prevalence season, an average of 92% (ranging from 85% to 

97%) of combo bins contain no E. coli O157:H7. Therefore, an average of 6% and 8% of combo 

bins generated from breeding cattle are contaminated with 1 or more E. coli O157:H7 organisms 

during the low and high prevalence seasons, respectively. Furthermore, the average combo bin 

contains 2 and 3 E. coli O157:H7 organisms in the low (October to May) and high (June to 

September) prevalence seasons, respectively. 

September 7, 2001 71 
3. Exposure Assessment 

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

Number of E. coli O157:H7 in

316,228

Combo Bins Made from Cow/Bull

Carcasses in Low Prevalence Season

Frequency

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

Number of E. coli O157:H7 in

316,228

Combo Bins Made from Cow/Bull

Carcasses in High Prevalence Season

Frequency

FIGURE 3-17 Comparison of seasonal distributions for number of E. coli O157:H7 in combo bins 

constructed from the slaughter of breeding (cow/bull) cattle. Dark lines are the mean 

distributions for each season. 

Figure 3-18 shows distributions of E. coli O157:H7 contamination in combo bins generated 

from the slaughter of steers and heifers. These results were also estimated from 100 simulations 

of the model. During the low prevalence season, an average of 77% (ranging from 55% to 97%) 

of combo bins generated from steer/heifer carcasses contained no E. coli O157:H7. During the 

high prevalence season, 57% (ranging from 42% to 83%) of these combo bins contained no E. 

coli O157:H7. Therefore, an average of 23% and 43% of combo bins contain 1 or more E. coli

O157:H7 organisms during the low and high prevalence seasons, respectively. Furthermore, the 

average combo bin contains 13 and 41 E. coli O157:H7 organisms in the low and high 

prevalence seasons, respectively. 

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

316,228

Number of E. coli O157:H7 in

Combo Bins Made from Steer/Heifer

Carcasses in Low Prevalence Season

Frequency

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

316,228

Frequency

Number of E. coli O157:H7 in

Combo Bins Made from Steer/Heifer

Carcasses in High Prevalence Season

FIGURE 3-18 Comparison of seasonal distributions for number of E. coli O157:H7 in combo bins 

constructed from the slaughter of feedlot (steer/heifer) cattle. Dark lines are the mean 

distributions for each season. 

These results show that prevalence and contamination levels in combo bins increase during 

the high prevalence season. These seasonal differences in combo bin contamination reflect the 

trends in prevalence of infected cattle entering slaughter. As noted previously, the influence of 

season is much greater for feedlot cattle than for breeding cattle. For combo bins generated from 

feedlot cattle, prevalence of contaminated combo bins increases nearly twofold, and average 

contamination levels increase over threefold, during the high prevalence season. Therefore, 

ground beef generated from steer/heifer combo bins is likely to be substantially more 

contaminated during the June to September period than ground beef produced during the other 

months of the year. 

These results also show that combo bins generated from steer/heifer carcasses are more likely 

to be contaminated than those generated from cow/bull carcasses. On average, there is about a 

fourfold greater prevalence of contaminated combo bins generated from steer/heifer carcasses 

September 7, 2001 72 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

compared with those generated from cow/bull carcasses during the low prevalence season. This 

difference is over fivefold during the high prevalence season. These differences reflect the 

differences noted for incoming live cattle prevalence between these two classes of cattle. 

Boxes 

Figure 3-19 shows distributions of E. coli O157:H7 contamination in meat trim boxes generated 

from the slaughter of cows and bulls. These results were estimated from 100 simulations of the 

model. During the low prevalence season, an average of 99% of boxes (ranging from 97% to 

100%) contain no E. coli O157:H7. During the high prevalence season, an average of 98% of 

boxes contain no E. coli O157:H7. Therefore, about 1% and 2% of boxes generated from 

breeding cattle are contaminated with 1 or more E. coli O157:H7 organisms during the low and 

high prevalence seasons, respectively. Regardless of season, the average box concentration is 

much less than 1 E. coli O157:H7 organism in the low and high prevalence seasons. 

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

Number of E. coli O157:H7 in 

316,228

boxes made from cow/bull 

carcasses in low prevalence season

Frequency

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

Number of E. coli O157:H7 in 

316,228

boxes made from cow/bull 

carcasses in high prevalence season

Frequency

Number of E. coli O157:H7 in

Boxes Made from Cow/Bull

Carcasses in Low Prevalence Season

Number of E. coli O157:H7 in

Boxes Made from Cow/Bull

Carcasses in High Prevalence Season

FIGURE 3-19 Comparison of seasonal distributions for number of E. coli O157:H7 in 60-pound 

boxes constructed from the slaughter of breeding (cow/bull) cattle. Dark lines are the mean 

distributions for each season. 

Figure 3-20 shows distributions of E. coli O157:H7 contamination in meat trim boxes 

generated from the slaughter of steers and heifers. These results were also estimated from 100 

simulations of the model. During the low prevalence season, an average of 94% (ranging from 

87% to 99%) of boxes generated from steer/heifer carcasses contained no E. coli O157:H7. 

During the high prevalence season, 87% (ranging from 79% to 97%) of these boxes contained no 

E. coli O157:H7. Therefore, about 6% and 13% of boxes contain 1 or more E. coli O157:H7 

during the low and high prevalence seasons, respectively. The average box contains almost 0.5 

and 1 E. coli O157:H7 organisms in the low and high prevalence seasons, respectively. 

By definition, boxes consist of less meat trim than combo bins. Consequently, prevalence and 

levels of E. coli O157:H7 in these aggregates of meat trim are less than observed for combo bins. 

However, the number of ground beef servings generated from boxes is correspondingly reduced. 

Therefore, the risk to consumers from ground beef generated from boxes is not likely to be much 

different from the risk from ground beef generated from combo bins. Seasonal trends and cattle 

class differences noted for combo bins are also noted for boxes. 

September 7, 2001 73 
3. Exposure Assessment 

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

Number of E. coli O157:H7 in 

316,228

boxes made from steer/heifer 

carcasses in low prevalence season

Frequency

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

Number of E. coli O157:H7 in 

316,228

box e s m a de from ste e r/he ife r 

ca rca sse s in high pre va le nce se a son

Frequenc y

Number of E. coli O157:H7 in

Boxes Made from Steer/Heifer

Carcasses in Low Prevalence Season

Number of E. coli O157:H7 in

Boxes Made from Steer/Heifer

Carcasses in High Prevalence Season

FIGURE 3-20 Comparison of seasonal distributions for number of E. coli O157:H7 in 60-pound 

boxes constructed from the slaughter of feedlot (steer/heifer) cattle. Dark lines are the mean 

distributions for each season. 

PREPARATION MODULE 

The preparation module estimates the occurrence and extent of E. coli O157:H7 contamination in 

consumed ground beef servings. This module also characterizes the consumption of ground beef 

servings by age of consumer and location of meal. 

Explanation of Scope 

The preparation module simulates the annual consumption of approximately 18 billion ground 

beef servings. It considers the effects of handling and cooking on the amount of E. coli O157:H7 

in contaminated servings. Ground beef is consumed in many forms. Typical forms are 

hamburger patties, ground beef as a formed major ingredient (e.g., meatballs and meat loaf), and 

ground beef as a granulated ingredient (e.g., ground beef in spaghetti sauce). The model focuses 

on the first two forms. Because granulated ground beef has a relatively large surface area 

compared with volume, the effect of cooking on this product is considered to be similar to intact 

beef products. Intact beef products are considered to be safe after cooking (NACMCF 1997). 

Furthermore, products incorporating granulated ground beef are often subjected to further 

cooking. Consequently, these types of products are assumed to have no viable E. coli O157:H7 

organisms and are not modeled. 

Although cross-contamination could be a potential contributor for contamination of ground 

beef product, cross-contamination of ground beef products is not modeled. An analysis of 

potential pathways in which ground beef could be contaminated by food service workers or other 

foods—or alternatively, pathways in which ground beef could contaminate other products—is 

beyond the scope of this risk assessment. Currently, quantitative modeling of crosscontamination in foods is hampered by a dearth of evidence. Furthermore, cross-contamination 

pathways are potentially complex, and each pathway may require as much data regarding growth 

dynamics and cooking effect as the primary product of interest. The model, however, can serve 

as a starting point for analyzing the effects of cross-contamination on human exposure to E. coli

O157:H7. 

Definition of Key Terms 

The following key terms are used throughout this module: 

September 7, 2001 74 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

• Servings are defined as an “eating occasion” within the 1994–1996, 1998 Continuing 

Food Survey of Individual Intakes (CSFII) database. The amount of ground beef 

consumed per eating occasion varies by age of the consumer and location where the meal 

was consumed (i.e., at home versus away from home). 

• Exposure refers to the amount of contamination that is consumed in a serving. 

• Home is used when servings are prepared and served in a home environment. 

• Away from home is used when servings are prepared and served in an institutional 

environment. This is often referred to as “HRI” (hotels, restaurants, and institutions). 

• Transportation refers to nonrefrigerated transport of product from a retail or wholesale 

establishment to its place of preparation and consumption. 

• Retail refers to establishments, such as grocery stores or butcher shops, that sell ground 

beef for home consumption. 

• Wholesale refers to establishments that serve as distributors for HRI for away from home 

consumption. 

• High prevalence season refers to June through September. 

• Low prevalence season refers to October through May. 

Preparation Module Segments 

The preparation module consists of six primary steps (Figure 3-21). Five of these steps explicitly 

model growth, decline, or dispersion of E. coli O157:H7 contamination: (1) grinding, (2) storage 

during processing by the retailer or distributor, (3) transportation home or to HRI, (4) storage at 

home and “away from home” (i.e., HRI), and (5) cooking. Step 6 models the amount of ground 

beef consumed, which varies depending on the age of the consumer and the location where the 

meal was consumed. 

Inputs to this module consist of the frequency and extent of E. coli O157:H7 contamination 

in combo bins and boxes estimated in the slaughter module. The preparation module output 

consists of a single exposure distribution depicting the frequency and extent of E. coli O157:H7 

contamination consumed in a year. 

Grinding (Step 1) transforms combo bins and boxes into ground beef. Combo bins are 

processed in large commercial facilities, and boxes are typically processed in smaller settings 

such as grocery stores. 

In Step 1, multiple combo bins or boxes are combined, mixed, and extruded to produce 

finished ground beef with a specific fat content. For example, a combo bin consisting of 90% 

lean trim can be mixed with another combo bin of 50% lean trim to make a grinder load of 70% 

lean ground beef. Although the extent of E. coli O157:H7 contamination does not increase 

during the grinding process because of temperature controls, contamination from a single combo 

bin or box can be dispersed during grinding to contaminate many individual ground beef 

servings. Consequently, assuming a constant frequency of contaminated combo bins, the number 

of combo bins that contribute to a grinder load determines whether the grinder load is 

contaminated. Once ground beef is produced, it can be shaped into patties or packaged in bulk 

containers and shipped for eventual consumption. Some beef is also ground at retail or 

institutional sites. This beef consists of 60-pound boxes, in addition to trim generated in the 

facility and beef that has already been ground at a grinding facility. 

Storage conditions at retail or wholesale (Step 2) provide an opportunity for E. coli O157:H7 

levels to (a) increase as a result of time and temperature abuse or (b) decrease as a result of the 

effects of freezing ground beef (Ansay et al. 1999; Sage and Ingham 1998). Ground beef is 

September 7, 2001 75 
3. Exposure Assessment 

Step modeled (1)

Step modeled (2)

Step modeled (3)

Step modeled (4)

Step modeled (5)

Step modeled (6)

Ovals denote steps that may either

increase or decrease contamination.

Rectangles denote steps with little or

no increase in contamination.

Input from

Production Module

Trim in Combo Bins or

Boxes

Cooking

Grinding

Storage

(Retail/Distributor)

Storage

(Home/HRI)

Transportation

(Home/HRI)

Human Illness? Consumption

(by age/location)

FIGURE 3-21 Steps modeled in the preparation module. 

subject to a variety of temperatures during storage and handling conditions, depending on its site 

of production and ultimate use. These conditions at home and in HRI can significantly increase 

the numbers of E. coli O157:H7 in ground beef (Marks et al. 1998; Buchanan and Bagi 1994; 

Walls and Scott 1996). 

Step 3 models the effects of time and temperature during transportation on the level of E. coli

O157:H7 after the ground beef is purchased. 

Step 4 models the storage of ground beef in the freezer or refrigerator prior to its preparation 

and consumption and provides another opportunity for increases or decreases in E. coli O157:H7 

contamination in ground beef servings. 

Ground beef is usually cooked prior to consumption (Step 5). Cooking can significantly 

reduce E. coli O157:H7 in ground beef servings (D’Sa et al. 2000; Juneja et al. 1997; Jackson et 

al. 1996). The model uses final internal product temperature data from a commercial food 

temperature database (Audits International 1999) to determine the level of reduction in E. coli

O157:H7 contamination in ground beef servings. 

Step 6 models consumption of E. coli O157:H7-contaminated ground beef servings, taking 

into consideration the age group of the consumer (i.e., 0 to 5, 6 to 24, 25 to 65, and 65+ years of 

age) and where the meals were consumed (i.e., at home or away from home). 

The following sections describe data and analysis for each preparation step. 

September 7, 2001 76 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Modeling the Preparation Process 

Input from the Slaughter Module 

The slaughter module provides distributions for E. coli O157:H7 contamination in combo bins 

and boxes by season for breeding (cow/bull) and feedlot (steer/heifer) cattle slaughter plants. 

Combo bins can be mixed across slaughter plant type (i.e., combo bins originating from cow/bull 

plants can be mixed with combo bins originating from steer/heifer plants). Combo bins are 

characterized by the “leanness” of the ground beef. Requirements for specific fat content in 

ground beef dictate which combo bins are mixed. 

Grinding Beef Trim (Step 1) 

Ground beef produced in the United States is sold to the general public through retail 

establishments (41%) or to HRI through wholesale distributors (59%) (APHIS:VS:CEAH 1994). 

Retail establishments may use coarse ground beef and mix it with trimmings produced in-house. 

They may also buy “case ready chubs” (plastic tubes filled with 5 to 10 pounds of ground beef). 

About 22% of retail ground beef contains at least some retail trimmings (APHIS:VS:CEAH 

1994). Of the ground beef used in HRI, 98% percent comes directly from grinder establishments. 

E. coli O157:H7 contamination in beef trim generated in the slaughter module is used as an 

input to the grinding step in the preparation module. As noted in the slaughter module, beef trim 

is generated either from cows and bulls or from steers and heifers. Although individual cows and 

bulls generate more trim than individual steers and heifers, the slaughtering of greater numbers 

of steers and heifers results in about 60% of domestic beef trim coming from this source 

(Table 3-14). As noted previously, about 15% of beef is imported and either used by itself or 

mixed with domestic product. It is assumed that this product is similar to domestically produced 

product. Figure 3-22 depicts the three types of beef used to make ground beef (i.e., beef trim 

from cows/bulls or steers/heifers, imported beef trim, or ground beef). 

TABLE 3-14 Percent of Meat Trim by Types of Cattle (Cows, Bulls, Steers, and Heifers) 

Carcass 

Type 

Average Carcass 

Weight (lbs.) 

Percent 

Trim 

Annual Slaughter 

(Million Head) 

Total Meat Trim 

(Million lbs.) 

Percent of Trim by 

Class 

Cow 539 53% 6.9 1,970 

Bull 851 90% 0.7 540 

40% Cow/Bull 

Steer 764 18% 17.4 2,390 

Heifer 703 18% 11.2 1,420 60% Steer/Heifer 

The model combines combo bins of three types of beef trim (Figure 3-22) to simulate a 

grinder load of beef. It includes beef that may be blended with other ground beef after initial 

grinding. For example, beef from two separate grinder loads of 10,000 pounds representing five 

combo bins each could be further mixed together to create a grinder load of 20,000 pounds. The 

number of combo bins (NCB) that are mixed together to create a grinder load ranges uniformly 

from 2 to 15 (Smith 1998, personal communication). 

September 7, 2001 77 
3. Exposure Assessment 

Grinding

Ground Beef Servings

Imported beef trim

or ground beef

Beef trim from

steers and heifers

Beef trim from

cows and bulls

FIGURE 3-22 Inputs to grinding (Step 1). 

Retail ground beef is modeled as coming from one to seven 60-pound boxes of beef trim. 

Equation 3.26 represents the process as modeled for combo bins: 

∑ ( ) (3.26) ⎥

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ =

NCB

Pi

icol E. coli E.

2 i

, bincomboin

H7:O157 

Discrete

loadgrinderin 

H7:O157 

The discrete distribution in Equation 3.26 consists of two arrays. The first array represents 

various contamination levels that may occur in a combo bin, and the second array represents the 

corresponding probability of the occurrence of each E. coli O157:H7 contamination level. 

After E. coli O157:H7-contaminated beef trimmings have been ground, the next load may be 

contaminated unless the grinder has been thoroughly cleaned and sanitized. Farrell et al. (1998) 

reported that ground beef inoculated with 6 logs of E. coli O157:H7 per gram resulted in 

contamination of a grinder with approximately 3 logs per cm2

. Washing the grinder lowered the 

contamination to about 1 log per cm2

. Sanitizing the grinder further lowered the contamination to 

less than 1 log per cm2. Initial contamination of ground beef in a grinder with 2 logs of E. coli

O157:H7 per gram followed by cleaning and sanitizing with chlorine resulted in no detection of 

E. coli O157:H7 organisms. This “carryover” E. coli O157:H7 contamination between grinder 

loads was not modeled because (1) Farrell et al. (1998) show that even without cleaning and 

sanitizing between grinder loads, there was still a 3 log reduction in the number of E. coli

O157:H7 organisms; (2) the number of E. coli O157:H7 organisms present in grinder loads is 

very low and is therefore assumed not to contribute significantly to contamination of the next 

grinder load; and (3) such carryover contamination could potentially increase the number of 

contaminated grinder loads but would result in a corresponding decrease in the number of E. coli

O157:H7 in the previous grinder load. 

Storage and Transportation (Steps 2 through 4) 

From the time that ground beef is produced until it is prepared and consumed, it is stored under 

varying conditions. Ground beef product may be produced at the slaughter establishment, 

shipped immediately to retail, purchased shortly thereafter, and prepared. Product could also be 

produced from beef trim that was sent to a grinding establishment where it was held before it 

was shipped to a wholesaler and stored for additional time. It could then be purchased in bulk by 

an HRI establishment and stored in a freezer before refrigeration, thawing, and final preparation. 

September 7, 2001 78 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

In addition to variations in storage time, variations in fat content of the ground beef, strain of E. 

coli O157:H7, and packaging can also contribute to growth or decline in the number of E. coli

O157:H7 organisms in ground beef. 

Modeling Growth

Increase or decrease in the number of E. coli O157:H7 organisms in ground beef is based on the 

time in which ground beef is stored at certain temperatures. This risk assessment models growth 

of E. coli O157:H7 in ground beef based on three assumptions: 

1. All areas of a product are at the same temperature. In reality, the outside of the product 

would reach a stable temperature first, with the inside of the product reaching a stable 

temperature last. To construct corresponding cooling curves, however, would require data 

and assumptions about the frequency of product thickness, its correlation to storage 

temperature, and the corresponding times of storage. The result would be a much more 

complicated model that would not be more useful because the underlying assumptions 

would not be well supported. 

2. All E. coli O157:H7 strains exhibit the same growth characteristics in any ground beef 

product. This risk assessment model further assumes that temperature during storage and 

handling is the only significant variable to predict growth. Although factors other than 

temperature are known to influence the growth of E. coli O157:H7 (Buchanan and Bagi 

1994), this simplifying assumption is necessary to permit modeling. Nevertheless, 

variability in growth is modeled based on the available evidence. 

3. Lag period duration in any one stage is affected by temperatures in previous stages. The 

lag period (the time prior to cell division) duration is modeled as a cumulative percentage 

that begins at 100% and decreases as product is subjected to varying temperatures at 

different stages along the farm-to-table continuum. Although it is reasonable to assume 

that E. coli O157:H7 organisms exposed to significantly different storage conditions 

would need additional time to adjust to those conditions before entering into a rapid 

growth phase, this assumption avoids the complications of making additional 

assumptions about when to restart calculations for lag period duration. As a result, this 

assumption in the risk assessment may result in an overestimation of the increase in the 

number of E. coli O157:H7 organisms in ground beef during storage and handling. 

Estimation of the effect of storage temperatures on the growth and decline of E. coli

O157:H7 is based on two types of data: 

• consumer and retail time and temperature data from commercial food temperature 

databases (Audits International 1999), and 

• predictive microbial growth data for E. coli O157:H7 in ground beef from published 

scientific literature (Ansay et al. 1999; Marks et al. 1998; Sage and Ingham 1998; 

Jackson et al. 1996; Walls and Scott 1996; Buchanan and Bagi 1994). 

Several studies show the effect of temperature on E. coli O157:H7 levels in ground beef. 

Palumbo (1997) reported that E. coli O157:H7 grows at 8oC (46.4oF) but not at 5oC (41oF). Gill 

and Bryant (1997) reported a decline of generic E. coli as a result of freezing. Ansay et al. (1999) 

tested the effects of refrigeration over time. In this study, storage of ground beef patties at 2oC 

for 4 weeks resulted in a 1.9 log reduction of E. coli O157:H7, and storage at –2o

C for 4 weeks 

resulted in a 1.5 log reduction. Freezing (–20o

C) for 1 year resulted in a 1 to 2 log reduction 

while tempering (at 15o

C for 4 hours) increased the log reduction brought about by storage at 

–2o

C. Sage and Ingham (1998) tested the effects of freezing (–20oC, 24 hours) and thawing on E. 

coli O157:H7 in ground beef and found a wide range in freeze-thaw sensitivity, with a decrease 

in E. coli O157:H7 levels from 0.62 to 2.52 logs per gram. 

September 7, 2001 79 
3. Exposure Assessment 

Predictive microbiological models have been developed for E. coli O157:H7 in ground beef 

under various storage conditions. These microbiological models predict the growth and decline 

of E. coli O157:H7 given environmental parameters including time, temperature, pH, and 

salinity. One set of equations was developed by Buchanan and Bagi (1994) and was later 

incorporated into the Pathogen Modeling Program (PMP) available from the Agricultural 

Research Service. Another set of equations has been developed by Marks et al. (1998). 

Walls and Scott (1996) compared predictions from the PMP with observations of E. coli

O157:H7 growth in ground beef and concluded that the PMP “offers reasonably good predictions 

of growth in raw ground beef” (p. 1,335). Table 3-15 compares the predictions from the Marks et 

al. (1998) equations with the predictions from the PMP (Buchanan and Bagi 1994) and the Walls 

and Scott (1996) observations. Both sets of predictions gave similar results, although the Marks 

et al. (1998) equations gave closer predictions to lag time and generation time. 

TABLE 3-15 Comparison of Pathogen Modeling Program (PMP) with Marks et al. (1998) 

Equations Using Walls and Scott (1996) Observations 

Growth 

Conditions Generation Time (hours) 

Lag Period Duration 

(hours) 

T1000 (hours)—Time for 3 

Log Increase in E. coli 

O157:H7 Organisms 

Temp pH 

Walls 

and 

Scott 

(1996) PMP 

Marks et 

al. 

(1998) 

Walls 

and 

Scott 

(1996) PMP 

Marks et 

al. 

(1998) 

Walls 

and 

Scott 

(1996) PMP 

Marks et 

al. 

(1998) 

12oC 5.7 6.00 3.80 3.62 16.20 30.50 26.99 76.70 68.50 63.19 

12oC 6.3 3.90 3.20 3.62 2.78 27.20 26.99 38.60 59.50 63.19 

20oC 5.7 1.50 1.00 1.11 2.08 8.34 6.83 17.60 18.30 17.96 

20oC 6.3 1.30 1.00 1.11 1.25 7.54 6.83 14.40 17.30 17.96 

35oC 5.7 0.40 0.30 0.38 1.23 1.53 1.52 5.00 4.80 5.29 

35oC 6.3 0.40 0.30 0.38 1.05 1.40 1.52 5.10 4.60 5.29 

The Marks et al. (1998) equations used temperature as the only parameter. Since a single 

parameter model requires less information, and since these equations also included adjustments 

for the variability inherent in the system, these are the ones used in the model. Given a 

temperature (τ) in oC, the following sets of equations are used to predict growth of E. coli

O157:H7 in ground beef: 

Lag period duration (LPD) is calculated as follows: 

ln(LPD) = 9.98 + [–2.69 × ln(τ)] (3.27) 

ln(LPD) has a standard deviation of 0.27. Consequently, the distribution is modeled as 

ln(LPD) ~ normal {9.98 + [–2.69 × ln(τ), 0.27]}. 

Generation time (GT) is calculated as follows: 

ln(GT) = 7.03 + {–6.31 × ln[ln(τ)]} (3.28) 

ln(GT) has a standard deviation of 0.16. Consequently, the distribution is modeled as 

ln(GT) ~ normal (7.03 + {–6.31 × ln[ln(τ)]}, 0.16). 

September 7, 2001 80 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

The maximum population density (MPD) (e.g., the maximum number of E. coli O157:H7 

organisms) is calculated as follows: 

MPD = TMD + (–0.014 × τ) (3.29) 

The theoretic maximum density (TMD) at refrigeration temperatures was estimated by Marks 

et al. (1998) to be about 10 logs. Walls and Scott (1996) also demonstrated growth in ground 

beef up to 10 logs. However, the maximum growth of E. coli O157:H7 achievable in ground beef 

is also thought to be a function of the total microbial population density in the food. Such a 

phenomenon has been demonstrated for Salmonella where the suppression of growth of all 

microorganisms in the food occurred when the total microbial population achieved the MPD 

characteristic of the food (Jameson 1962). This effect has also been reported for S. aureus, 

L. monocytogenes, and Carnobacterium spp. (Buchanan and Bagi 1997; Duffes et al. 1999; 

Nilsson et al. 1999; Ross and McMeekin 1991; Grau and Vanderlinde 1992). 

Because maximum growth of E. coli O157:H7 possible in a food depends on the population 

of all microbes, and the population of other microbes in ground beef varies, it is assumed that the 

TMD varies. A triangular distribution is used to model this variability, where the minimum TMD 

is assumed to be 5 logs, the maximum TMD is assumed to be 10 logs, and the most likely TMD 

is uncertain but can range uniformly from 5 to 10 logs. 

From Marks et al. (1998), the MPD has a standard deviation of 0.15 and is thus modeled as 

follows: 

MPD = normal{triangular[5, uniform(5,10), 10] + (–0.014 × τ), 0.15} (3.30) 

Output from a Monte Carlo simulation of these equations overlaps most of the observations 

from Walls and Scott (1996) with three exceptions: the prediction of the lag period duration (1) 

for a temperature of 12oC (54oF) at a pH of 6.3, (2) for a temperature of 20oC (68oF) with a pH of 

5.7, and (3) for a temperature of 20o

C (68oF) with a pH of 6.3. In each case, the equations 

overestimate the lag period duration. Nevertheless, the T1000 times, which incorporate both the 

LPD and GT, overlap the Walls and Scott (1996) observations for all conditions. 

Continued research of the effect of various storage condition combinations (e.g., pH, 

moisture, packaging, freezing, refrigeration, thawing) on E. coli O157:H7 levels in ground beef 

products would allow construction of better predictive microbial models. Incorporation of such 

models into risk assessment is further dependent on studies to develop frequency distributions 

for various storage conditions. 

Modeling Storage Temperature

As noted in Figure 3-22, this model includes the effects of storage temperature on the increase or 

decrease of E. coli O157:H7 in ground beef at three steps: (1) retail or wholesale storage, (2) 

transportation to the location of preparation (i.e., home or HRI), and (3) storage before cooking. 

Temperatures for all three steps are based on internal product temperatures of ground beef taken 

on nearly 1,000 samples (Audits International 1999). Table 3-16 shows numbers of occurrences 

of storage temperatures above 45o

F. 

The model assumes that E. coli O157:H7 levels do not increase at refrigeration temperatures 

below 45o

F based on Palumbo (1997) and input from the National Advisory Committee on 

Microbiological Criteria for Food (NACMCF 1999). 

Temperature at each step (τS2, τS3, τS4) is modeled as a cumulative distribution in the 

following form: 

September 7, 2001 81 
3. Exposure Assessment 

TABLE 3-16 Storage Temperatures above 45oF 

Step 2 

Retail/Wholesale 

Storage 

Step 3 

Transport 

Step 4 

Home/HRI Storage 

Total samples 975 971 939 

Temperature (oF) Number of Samples above 45oF 

46 49 175 47 

49 49 223 28 

52 8 68 4 

55 4 49 5 

58 2 19 4 

61 0 19 1 

64 0 3 0 

67 0 2 1 

70 0 1 1 

Source: Audits International 1999. 

τSX = cumulative [(temperature), (p)] (3.31) 

The cumulative distribution in Equation 3.31 consists of two arrays: the first array represents 

various temperatures shown in Table 3-16, and the second array represents the corresponding 

cumulative probability of each of the temperatures. In addition to modeling the variability in 

storage temperature as a cumulative distribution, uncertainty regarding the actual frequency of 

each temperature is modeled using a beta distribution after a method reported by Vose (1999). 

Modeling Storage Time

The amount of time at each step (T2, T3, T4) that ground beef is stored at a given temperature 

determines how much growth of E. coli O157:H7 takes place. Although there are 

recommendations for how long ground beef may be stored at temperatures above 45o

F (FDA 

1997), there are no data documenting this length of time. FSIS recommends that ground beef be 

stored in the refrigerator for no more than 2 days (FSIS 2000). For Steps 2 and 4, time of storage 

is modeled as an exponential distribution with a mean of 1. An exponential distribution was 

chosen because it has a single parameter and its probability density function is monotonically 

decreasing. In other words, using this function assumes that on average, ground beef is more 

likely to be stored for shorter times than for longer times. An exponential distribution with a 

mean of 1 predicts that 99% of ground beef will be stored less than 4.6 days. Additionally, 

uncertainty about the mean of the exponential distribution is modeled using a uniform 

distribution from 0.5 days to 1.5 days. An exponential distribution with a mean of 0.5 predicts 

that 99% of ground beef will be stored less than 2.3 days, while an exponential distribution with 

a mean of 1.5 predicts that 99% of ground beef will be stored less than 6.9 days. Equation 3.32 

shows how time is modeled across the various uncertainties for Steps 2 and 4. 

 TX = exponential [uniform(0.5, 1.5)] (3.32) 

September 7, 2001 82 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

For Step 3, the time of storage for transportation is based on data from Audits International 

(1999) (Table 3-17). 

TABLE 3-17 Time of Transport from Retail to Home 

Time of Transport Number of Observations 

0.00 36 

0.25 5 

0.50 46 

0.75 168 

1.00 240 

1.25 210 

1.50 156 

1.75 67 

2.00 28 

2.25 10 

2.50 8 

2.75 3 

3.00 1 

6.50 1 

Source: Audits International 1999. 

In Step 3, time (T3) is modeled as a cumulative distribution in the following form: 

 T3 = cumulative[(time), (p)] (3.33) 

As with Equation 3.31, the cumulative distribution in Equation 3.33 consists of two arrays. 

The first array represents the times shown in Table 3-17, and the second array represents the 

corresponding cumulative probability of each of the times. Again, uncertainty regarding the 

actual frequency of each time is modeled using a beta distribution after a method reported by 

Vose (1999). 

Modeling the Effect of Freezing 

Some ground beef may be frozen during storage and transportation. A decline in E. coli

O157:H7 levels between 0 and 3 logs per gram of frozen ground beef is modeled based on 

laboratory studies of the effects of freezing on E. coli O157:H7 levels in ground beef (Ansay et 

al. 1999; Sage and Ingham 1998). Table 3-18 shows the frequency distribution used to model the 

log reduction of E. coli O157:H7 due to freezing. Uncertainty regarding the proportion of ground 

beef that is frozen is modeled uniformly from 20% to 80%. 

Modeling Growth for a Single Step

Step 2 provides the first opportunity for E. coli O157:H7 growth. First, ln(LPD) is calculated 

given τS2 using Equation 3.27. The lag period for Step 2 (LPD2) is compared with the amount of 

time in Step 2 (T2). If LPD2 < T2, then no growth occurs and the cumulative lag used in Step 2 

(CLU2) is as follows: 

September 7, 2001 83 
3. Exposure Assessment 

TABLE 3-18 Frequency Distribution for Log Reduction in E. coli O157:H7 due to Freezing 

Log Reduction Frequency 

0.0 0.000 

0.5 0.000 

1.0 0.190 

1.5 0.580 

2.0 0.170 

2.5 0.028 

3.0 0.028 

2

2

2 T

LPD CLU = (3.34) 

If LPD2 > T2, then the amount of time available for growth equals LPD2 – T2. Equation 3.28 

calculates ln(GT2) given τS2. The log of growth for Step 2 (G2) is then calculated as follows: 

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎝

⎛

=

−

2

22

GT

TLPD

102 2logG (3.35) 

CLU2 or G2 are only calculated if τS2 is greater than 45oF. Otherwise both CLU2 and G2 are 

set at 0. 

Since the CLU is modeled as a percentage that can increase across each step, the amount of 

E. coli O157:H7 growth in Steps 3 and 4 is also dependent on the CLU. If CLU2 is greater than 

0, then the LPD in Step 3 must be adjusted to account for the CLU. The adjusted LPD3 (LPD3a) 

is calculated by LPD3 × (1 – CLU2). Equations 3.34 and 3.35 can then be used to calculate G3 by 

substituting LPD3a where LPD3 would occur. The amount of E. coli O157:H7 growth in Step 4 

would be calculated in the same manner. 

Modeling Growth across Steps 2 to 4

Since CLU and G are only modeled when storage temperature exceeds 45o

F, there is a set of 

eight potential growth combinations that can occur in Steps 2 through 4 for a single ground beef 

serving. If the temperature of the ground beef serving is below 45o

F, then growth is not modeled. 

If the serving is exposed to temperatures above 45o

F in one of the three steps, then CLU and/or 

G is calculated for that step. If the temperature of the serving is above 45o

F in two of the steps, 

then CLU and/or G is calculated for that step and an adjusted LPD is calculated if CLU is less 

than 1. The same principle applies if the temperature of the uncooked ground beef serving is 

above 45o

F in all three steps. Thus, the total number of combinations of steps above or below 

45o

F is 23 or 8. The probability that a serving will be exposed to a particular combination of steps 

above 45o

F is dependent on the probability of each step being above 45oF. These probabilities 

are considered fixed but uncertain. 

The probability that a serving in a particular step will be above 45o

F is modeled using a 

beta(s+1,n–s+1) distribution incorporating the data in Table 3-16, where s equals the total 

samples above 45o

F and n equals the total samples. Consequently, a single simulation of the 

model will generate eight different growth distributions for each of the eight different 

combinations of steps above 45o

F. The eight growth distributions generated from these eight 

September 7, 2001 84 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

combinations are integrated across the probabilities of their occurrence to create an overall 

growth distribution for E. coli O157:H7 in stored ground beef. This distribution is then integrated 

with the distribution for freezing of ground beef to give a final distribution (Gpop) representing 

the change of E. coli O157:H7 due to storage in Steps 2 to 4 for all servings. 

Figure 3-23 shows the results of 20 Monte Carlo simulations where Gpop is estimated. Each 

line represents the frequency distribution returned by a single simulation. 

0.000001

0.000010

0.000100

0.001000

0.010000

0.100000

1.000000

-3-2-1

None

123456789

Log change

Frequency

Log Change

Frequency

FIGURE 3-23 Frequency of log increase or log decrease due to storage for 20 simulations. 

Cooking (Step 5) 

Step 5 simulates the effect of cooking on ground beef in homes and HRI. Nearly all ground beef 

is cooked. The effect of cooking is dependent on the cooking temperature, the storage 

temperature prior to cooking, and the thermodynamics of the product. The effects of cooking 

temperature and precooking storage are modeled. Cooking is modeled by relating log reduction 

to internal product temperatures. 

Temperatures of Cooked Ground Beef

The temperature to which a ground beef serving is cooked is based on a survey of final internal 

product temperatures of cooked hamburger patties prior to consumption (Audits International 

1999). Table 3-19 shows the internal hamburger temperatures reported. Because visual cues are 

unreliable indicators of cooking of ground beef (Liu and Berry 1996; Van Laack et al. 1996), 

quantitative time-temperature cooking data were used (Audits International 1999) rather than 

consumer behavior survey data (Brent 1999). 

September 7, 2001 85 
3. Exposure Assessment 

TABLE 3-19 Internal Temperatures of Cooked Hamburger Patties 

Internal Temperature 

(

o

C) 

Observations 

(n) 

Internal Temperature 

(

o

C) 

Observations 

(n) 

39 2 69 22 

41 5 71 18 

43 3 73 55 

45 9 75 45 

47 5 77 59 

49 14 79 19 

51 8 81 18 

53 13 83 74 

55 23 85 11 

57 12 87 5 

59 20 89 9 

61 31 91 1 

63 41 93 3 

65 25 95 3 

67 41 Total 594 

Source: Audits International 1999. 

Effect of Cooking

Juneja et al. (1997) determined the effect of cooking on hamburgers experimentally inoculated 

with an initial load of 6.6 logs of E. coli O157:H7. Final internal temperatures of the hamburgers 

ranged from 56°C to 74oC (133°F to 166oF). The log of the surviving E. coli O157:H7 was then 

measured. Given a temperature in Fahrenheit (τf), the following linear regression equation gives 

the corresponding (r2 = 0.94) log reduction: 

LR = 6.6 – (20.53 – 0.12 × τf) (3.36) 

Juneja et al. (1997) noted that 73% lean ground beef patties (100 grams) cooked to an 

internal temperature of 68.3oC (155oF) would have a 4 log reduction of a five strain cocktail of 

E. coli O157:H7. This is consistent with a report by Jackson et al. (1996) that 78% lean ground 

beef patties (114 grams) inoculated with about 6 logs of bacteria and cooked to an internal 

temperature of 68.3o

C (155oF) would have a 4.1 log reduction with a standard deviation of 0.5 

logs. In both studies, inoculated hamburgers were stored under refrigeration. 

Semanchek and Golden (1998) reported variability in heat resistance among three strains of 

E. coli O157:H7 and concluded that “exposure to different environments may select for 

resistance to suboptimum conditions or subsequent stress” (p. 399). Jackson et al. (1996) 

reported that the response of E. coli O157:H7 to cooking appeared to be related to original 

storage temperatures. E. coli O157:H7 in frozen ground beef was more heat resistant than E. coli

O157:H7 in ground beef refrigerated or stored at higher temperatures. Jackson et al. reported 

September 7, 2001 86 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

results from 27 different combinations of storage conditions and cooking temperatures (listed in 

Table 3-20). 

TABLE 3-20 Mean Log Reductions (± Sample Standard Deviation [std. dev.]) of E. coli O157:H7 

in Grilled Ground Beef Patties 

Internal Cooking Temperature 

54.4oC 62.8oC 68.3oC Pretreatment Storage 

Conditions Mean LR Std. Dev. Mean LR Std. Dev Mean LR Std. Dev

–18oC, 8 days 0.3 0.1 1.2 0.6 3.0 1.8 

–18oC, 8 days followed by 

21oC, 4 hours 

0.7 0.1 3.9 0.9 4.8 0.3 

–18oC, 8 days followed by 

30o

C, 4 hours 

1.6 0.7 5.5 0.3 5.2 0.7 

3oC, 9 hours 0.5 0.3 2.6 0.5 4.1 0.5 

3oC, 9 hours followed by 

21oC, 4 hours 

1.3 0.4 5.3 0.2 5.2 0.3 

3oC, 9 hours followed by 

30o

C, 4 hours 

1.9 0.3 6.0 0.2 5.8 0.4 

15oC, 9 hours 1.0 0.1 4.3 0.7 5.1 0.1 

15oC, 9 hours followed by 

21o

C, 4 hours 

1.6 0.8 5.4 0.5 5.6 0.4 

15oC, 9 hours followed by 

30oC, 4 hours 

2.4 0.1 5.3 1.7 6.4 0.2 

Source: Jackson et al. 1996. 

Modeling Cooking

The effect of cooking is calculated in the model by applying log reductions for the range of 

cooking temperatures shown in Table 3-19. Although Jackson et al. do not report on the effect of 

cooking at temperatures greater than 68.3oC (155oF), this effect was extrapolated in accordance 

with the linear relationship demonstrated by Juneja et al. (1997). 

Figure 3-24 depicts the variability expected for log reductions across the nine different 

pretreatments shown in Table 3-20. Individual lines are not labeled, as the purpose of the chart is 

to show the wide range of variability in log reduction based solely on precooking storage. 

The information in Table 3-20 is used to calculate a linear regression equation for each of the 

nine pretreatments with estimated y intercept (α), slope (β), and the standard error of y (stey) 

terms. For each regression equation, the probability of a particular log reduction for each of the 

30 temperatures (τ ) in Table 3-19 is calculated using the Excel Normdist function: 

LR τ )|p( = NORMDIST(LR,α + β × τ,stey, )1 (3.37) 

Integrating the probabilities of all of the temperatures and the probability of a given log 

reduction across all τ results in a log reduction curve for a given pretreatment: 

September 7, 2001 87 
3. Exposure Assessment 

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

129.9 145.0 154.9

Temperature in Fahrenheit (°)

Log Reduction

FIGURE 3-24 Variability in log reduction of E. coli O157:H7 for nine different pretreatments 

based on Jackson et al. (1996). 

= ττ×τ (3.38) ∫ f p )()|LR(()LR( dp

67

39

The probability of a particular pretreatment occurring for a ground beef serving is fixed but 

uncertain. These probabilities are dependent on probabilities used in Steps 2 to 4. For instance, 

the probability of the serving having undergone freezing before cooking is dependent on, and 

correlated with, the probability that the serving was frozen during Steps 2 to 4. 

The log reduction curves for each of the nine pretreatments are integrated to create a single 

log reduction curve. This log reduction curve (LRpop) describes the frequency of log reductions 

from cooking for the entire population of servings and is estimated using Monte Carlo methods. 

Figure 3-25 shows 20 different LRpop curves calculated from Monte Carlo simulations. 

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0123456789

10111213141516

Log Reduction due to Cooking

Frequency

FIGURE 3-25 Frequency of log reduction due to cooking for 20 simulations. 

September 7, 2001 88 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Note that considerable uncertainty exists regarding the log reduction due to cooking. Note 

also that this particular set of simulations suggests that between 4% and 8% of servings have no 

log reduction applied.2

Food items with ground beef as a major ingredient were assumed to have cooking practices 

that parallel cooking practices for hamburgers. As noted in the scope, cooking of ground beef as 

an ingredient in products such as chili, spaghetti, and soup is assumed to destroy all E. coli

O157:H7 in the product. Such ground beef is usually precooked in a granular form and then 

subjected to further cooking. 

Although D’Sa et al. (2000) have reported a difference in log reductions between singlesided and double-sided cooking, this distinction was not modeled. Results from Juneja et al. 

(1997), Jackson et al. (1996), and D’Sa et al. (2000) were based on cooking similar sized 

hamburger patties of relatively uniform thickness. Consequently, this model did not explicitly 

account for differences in patty thickness. Nevertheless, the variability of internal cooking 

temperatures included in this model should account for the thermodynamics in ground beef 

servings with varying thickness. 

Consumption (Step 6) 

Types of Ground Beef Products Modeled

Ground beef is consumed in the United States as the main course of a meal or as an ingredient in 

a recipe both at home and away from home in HRI. Data from the 1994–1996, 1998 CSFII were 

used to model ground beef consumption patterns by age of the consumer and location where the 

meal was consumed. The CSFII is a national survey of U.S. food intakes that consists of the 

following: 

• a nationally representative sample of 21,154 respondents; 

• two 24-hour recalls of foods eaten during two nonconsecutive days (with the interview 

for the second day conducted on a different day of the week, 3 to 10 days after the 

interview for the first day); 

• demographic information on consumers; 

• location where the meal was consumed (i.e., home versus away from home); and 

• annual and 4-year survey weights to reflect the consumption patterns of the 

noninstitutional U.S. population. 

Three categories of ground beef meals were considered in this step: (1) raw ground beef, (2) 

hamburger patties and sandwiches, and (3) formed ground beef products in which the ground 

beef is a major ingredient to the product (e.g., meatballs and meat loaf). Food items for each 

category were selected from over 7,200 food items within the 1994–1996 and 1998 CSFII 

(Kause 2001). Tables 3-21, 3-22, and 3-23 provide detailed information on the food items that 

comprise each ground beef category. Only food items with at least one eating occasion between 

1994 and 1996 or in 1998 were included. 

 

2The 1994–1996, 1998 CSFII included four individuals (three between 25 and 64 years of age and one less than 5 

years of age) who were reported to have consumed “raw” ground beef. These reported ground beef servings 

comprised less than 0.07% of the estimated annual number of ground beef servings consumed in the United 

States (Tables 3-24, 3-25, and 3-26). For modeling purposes, these servings are considered to be a subset of 

those servings that have no log reduction in E. coli O157:H7 during cooking (e.g., grossly undercooked 

servings). 

September 7, 2001 89 
3. Exposure Assessment 

TABLE 3-21 1994–96, 1998 CSFII Food Codes for Raw Ground Beef Meals 

Food Code Food Item 

21500000 Raw ground beef 

27116400 Steak tartare (raw ground beef and egg) 

Amounts of Ground Beef Products Consumed

The amount of ground beef in each food item was calculated using the CSFII recipe files (Tables 

3-24, 3-25, and 3-26). This provides information on the amount of ground beef consumed during 

a meal (e.g., meatball and spaghetti dinner). 

Consumption data for each ground beef category were stratified by general location of where 

the meal was eaten (i.e., either at home or away from home). This resulted in six combinations 

for ground beef consumption by location: (1) raw ground beef consumed within the home, (2) 

raw ground beef consumed away from the home in HRI, (3) ground beef consumed as 

hamburgers within the home, (4) ground beef consumed as hamburgers away from the home in 

HRI, (5) ground beef used as a primary ingredient in a recipe (e.g., meatballs or meat loaf) 

within homes, and (6) ground beef used as an ingredient in a recipe (e.g., meatballs or meat loaf) 

away from the home. 

Ground beef consumption was further stratified into four age categories (0 to 5, 6 to 24, 25 to 

64, and 65+ years of age)3 to provide more detail on exposure of susceptible age groups (0 to 5 

and 65+ years of age). The age-specific annual number of ground beef meals consumed and the 

corresponding serving size (in grams) was calculated using SAS (version 8.0) and WesVar 

(version 2.0) software (Kause 2001). The following information was derived: 

• weighted descriptive statistics (e.g., mean amount eaten in grams, number of eating 

occasions, and mean number of eating occasions) that characterize all age/location/food 

category-specific eating occasions consumed in two nonconsecutive days of eating; 

• distributions of the amount of food (in grams) that is eaten at all eating occasions, 

expressed as weighted percentiles after adjustment for the stratified sample design using a 

jackknife procedure in the WesVarPC software package with replicate weights that 

accompany the 1994–96, 1998 CSFII data; 

• weighted descriptive statistics to describe the amount of food (in grams) that is eaten per 

person per day and the number of consumers; and 

• per capita estimates of food eaten. 

The resulting number of servings and mean serving size of ground beef by age and location 

for each ground beef category are shown in Tables 3-24, 3-25, and 3-26. These ground beef 

meals account for over 18 billion ground beef servings consumed annually in the United States. 

 

3Age categories were used instead of age-specific data because of the limited number of observations for each age 

(e.g., 1-year-olds, 2-year-olds, etc.) to derive the statistics. 

September 7, 2001 90 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

TABLE 3-22 1994–96, 1998 CSFII Food Codes for Hamburger Patty and Sandwich Meals 

Food 

Code Food Item 

Food 

Code Food Item 

21500100 Ground beef or patty 27510390 Double bacon cheeseburger, on bun 

21500200 Ground beef or patty, breaded, cooked 27510400 Bacon cheeseburger, 1⁄4 lb meat, with tomato, 

on bun 

21501000 Ground beef, regular, cooked 27510420 Taco burger, on bun (include chiliburger 

with cheese) 

21501200 Ground beef, lean, cooked 27510430 Double bacon cheeseburger, with mayo, 

tomato, on bun 

21501300 Ground beef, extra lean, cooked 27510440 Bacon cheeseburger, 1⁄4 lb, with mayo and 

tomato, on bun 

25220140 Beef sausage, fresh, bulk, patty or link, 

cooked 

27510480 Cheeseburger, with onions, on rye bun 

27510210 Cheeseburger, plain, on bun 27510500 Hamburger, plain, on bun 

27510220 Cheeseburger, with mayo, on bun 27510510 Hamburger, with tomato and or catsup, on 

bun 

27510230 Cheeseburger, with mayo and tomato, 

on bun 

27510520 Hamburger, with mayo and tomato, on bun 

27510240 Cheeseburger, 1⁄4 lb meat, plain, on bun 27510530 Hamburger, 1⁄4 lb meat, plain, on bun 

27510250 Cheeseburger, 1⁄4 lb meat, with mayo, 

on bun 

27510540 Double hamburger with tomato and or 

catsup, on bun 

27510260 Cheeseburger, 1⁄4 lb meat, with 

mushroom sauce, on bun 

27510550 Double hamburger with mayo and tomato, 

double-decker bun 

27510270 Double cheeseburger, plain, on bun 27510560 Hamburger, 1⁄4 lb meat with mayo and 

tomato, on bun 

27510280 Double cheeseburger, with mayo, on 

bun 

27510590 Hamburger, with mayo, on bun 

27510300 Double cheeseburger, with mayo, on 

double-decker bun 

27510600 Hamburger, 1 oz meat, plain, on miniature 

bun 

27510310 Cheeseburger, with tomato and or 

catsup, on bun 

27510610 Hamburger, 1 oz meat, tomato, on miniature 

bun 

27510311 Cheeseburger, 1 oz meat, plain, on mini 

bun 

27510620 Hamburger, 1⁄4 lb meat, with tomato and or 

catsup, bun 

27510320 Cheeseburger, 1⁄4 lb meat, with 

tomato/catsup, bun 

27510630 Hamburger, 1⁄4 lb meat, with mayo, on bun 

27510330 Double cheeseburger, with tomato and 

or catsup, on bun 

27510640 Hamburger, 1⁄4 lb meat (modified fat) with 

tomato, on bun 

27510340 Double cheeseburger, with mayo and 

tomato on bun 

27510670 Double hamburger, with mayo and tomato, 

on bun 

27510350 Cheeseburger, 1⁄4 lb meat, with mayo 

and tomato on bun 

27510680 Double hamburger (1/2 lb meat), with 

tomato/catsup, bun 

27510360 Cheeseburger, with mayo, tomato and 

bacon on bun 

27510690 Double hamburger, 1/2 lb meat, with mayo 

and tomato/catsup, bun 

27510370 Double cheeseburger with mayonnaise, 

on bun 

27510700 Meatball and spaghetti sauce submarine 

sandwich 

27510380 Triple cheeseburger with mayo, tomato, 

on bun 

September 7, 2001 91 
3. Exposure Assessment 

TABLE 3-23 1994–96, 1998 CSFII Food Codes for Other Ground Beef-Based Meals 

Food Codes Food Item 

21500110 Ground beef, meatballs, meat only, not specified as to regular/lean 

21540100 Ground beef with textured vegetable protein, cooked 

23220010 Veal, ground or patty, cooked 

27116350 Stewed, seasoned ground beef, Mexican style 

27118110 Meatballs, p.r. (albondigas) 

27118120 Stewed, seasoned ground beef, Puerto Rican style 

27160100 Meatballs, not specified as to type of meat, with sauce 

27161010 Meat loaf, p.r. (albondigon) 

27214100 Meat loaf made with beef 

27214110 Meat loaf with beef, with tomato sauce 

27260010 Meat loaf, not specified as to type of meat 

27260050 Meatballs, with breading, with gravy 

27260080 Meat loaf made with beef and pork 

27260090 Meat loaf with beef, veal and pork 

27260100 Meat loaf with beef and pork, with tomato sauce 

27113300 Swedish meatballs with cream or white sauce (mixture) 

TABLE 3-24 Annual Number of Servings of Raw Ground Beef Consumed at Home and Away 

from Home by Age Category in the 1994–1996, 1998 CSFII 

Age in Years Number of Servings Mean Serving Size (grams) 

Home 

0–5 — — 

6–24 — — 

25–64 8,861,470 113.40 

65+ — — 

Total 8,861,470 

Away from Home 

0–5 522,315 56.70 

6–24 — — 

25–64 3,883,053 12.60 

65+ — — 

Total 4,405,368 

September 7, 2001 92 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

TABLE 3-25 Annual Number of Servings of Hamburger Patties and Sandwiches Consumed at 

Home and Away from Home by Age Category in the 1994–1996, 1998 CSFII 

Age in Years Number of Servings Mean Serving Size (grams) 

Home 

0–5 395,592,840 51.86 

6–24 1,478,341,250 95.17 

25–64 2,517,532,750 102.02 

65+ 577,825,295 86.52 

Total 4,969,292,135 

Away from Home 

0–5 717,308,950 36.88 

6–24 4,215,244,840 78.73 

25–64 5,628,291,058 87.64 

65+ 523,589,763 67.53 

Total 11,084,434,611 

TABLE 3-26 Annual Number of Servings of Ground Beef-Based Meals (Such as Meat loaf and 

Meatballs) Consumed at Home and Away from Home by Age Category in the 1994–1996, 1998 

CSFII 

Age in Years Number of Servings Mean Serving Size (grams) 

Home 

0–5 109,001,410 62.36 

6–24 362,621,113 123.02 

25–64 686,647,125 123.95 

65+ 272,269,925 100.09 

Total 1,430,539,573 

Away from Home 

0–5 27,548,375 64.01 

6–24 169,672,623 75.64 

25–64 398,076,300 101.57 

65+ 135,376,128 67.30 

Total 730,673,425 

September 7, 2001 93 
3. Exposure Assessment 

Determining Exposures to E. coli O157:H7 

The amount of E. coli O157:H7 to which a consumer is exposed in a single serving of ground 

beef is a function of the original number of E. coli O157:H7 organisms and the subsequent 

effects of storage, handling, and cooking on the growth or decline in the number of E. coli

O157:H7 organisms in ground beef. The effect of storage on the growth or decline of organisms 

has been determined in Steps 2 to 4, and the effect of cooking has been determined in Step 5. 

The original number of organisms in a product is determined by the original concentration after 

grinding (Step 1) and the amount of product consumed (Step 6). 

Equation 3.39 calculates the number of E. coli O157:H7 in a grinder load. The concentration 

in the grinder load (GLC) is calculated by dividing the total number of E. coli O157:H7 

organisms (ECO) by the weight of the grinder load in grams as shown in the following equation 

where NCB is the number of combo bins in the grinder load, 2,000 is the weight of a combo bin 

in pounds, and 454 is the number of grams in a pound: 

454000,2NCB

ECO GLC

×× = (3.39) 

For a given GLC and a given serving size (WTG) the probability of having a particular 

number of organisms (BACT) in a serving is predicted by assuming a Poisson distribution 

WTGGLC

BACT

BACT!

(GLC WTG) (BACT)

× ×− p = e (3.40) 

Integrating the probabilities of all GLCs and the probability of all BACTs across all WTGs 

results in an initial serving distribution: 

)BACT( ]WTGGLC)WTG()GLC()WTG,GLC|BACT([

7 10

7 10GLC

124

12WTG

f = p ×× d d pp ∫ ∫ − = =

 (3.41) 

This initial serving distribution describes the frequency of E. coli O157:H7 levels in all 

ground beef servings before storage and cooking (BACTpop). This distribution is estimated for 

both the low prevalence and high prevalence seasons. Figure 3-26 shows the results of 20 Monte 

Carlo simulations where BACTpop is estimated for the low prevalence season and the high 

prevalence season. 

1.E-18

1.E-16

1.E-14

1.E-12

1.E-10

1.E-08

1.E-06

1.E-04

1.E-02

1.E+00

None 0 0.5 1 1.5

Logs of E. coli O157:H7 initially in serving in low prev. season

Frequency

1.E-18

1.E-16

1.E-14

1.E-12

1.E-10

1.E-08

1.E-06

1.E-04

1.E-02

1.E+00

None 0 0.5 1 1.5

Logs of E. coli O157:H7 initially in serving in high prev. season

Frequency

 Logs of E. coli O157:H7 Initially in Serving in

Low Prevalence Season

 Logs of E. coli O157:H7 Initially in Serving in

High Prevalence Season

FrequencyFrequency

FIGURE 3-26 Frequency of logs of E. coli O157:H7 initially present in servings for low 

prevalence and high prevalence seasons. 

September 7, 2001 94 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

The final dose distribution to which the population is exposed (DOSEpop) can be expressed as 

the initial serving distribution plus the growth distribution minus the distribution describing the 

effect of cooking: 

 DOSEpop = BACTpop + Gpop – LRpop (3.42) 

Recognize that DOSEpop is a distribution that represents the summation of three uncertain 

distributions. Although Monte Carlo methods could be used to combine these distributions, the 

model instead uses combinatorial mathematics to accomplish this. 

Preparation Module Results 

Grinder Loads 

Grinder Loads Made from 2,000-Pound Combo Bins

An intermediate output of the preparation module is the distribution of E. coli O157:H7 densities 

in grinder loads of ground beef made from 2,000-pound combo bins. Figure 3-27 shows the 

results of 100 simulations for grinders in the low and high prevalence seasons. (See Appendix A 

for a discussion of how intermediate model outputs are anchored to observed ground beef 

sampling results.) 

0.00

0.05

0.10

0.15

0.20

0.25

0.30

1.0E-07 1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 1.0E-01

Frequency

0.00

0.05

0.10

0.15

0.20

0.25

0.30

1.0E-07 1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 1.0E-01

Frequency

E. coli O157:H7 per Gram in Grinder Loads

Made from Combo Bins in Low Prevalence Season

E. coli O157:H7 per Gram in Grinder Loads

Made from Combo Bins in High Prevalence Season

FIGURE 3-27 Frequency of ground beef contamination in contaminated grinder loads made from 

2,000-pound combo bins in low and high prevalence seasons. Grinder loads that are not 

contaminated are not shown in this chart. The mean grinder load distribution is represented by 

the dark line. 

Table 3-27 summarizes the prevalence of contaminated grinder loads for the 100 simulations 

depicted in Figure 3-27. The mean results imply that 32% of the grinder loads in the low 

prevalence season and 14% of the grinder loads in the high prevalence season are not 

contaminated. 

In the low prevalence season, between 40% (5th percentile) and 88% (95th percentile) of 

these grinder loads contained one or more E. coli O157:H7. In the high prevalence season, 

between 61% (5th percentile) and 94% (95th percentile) of grinder loads contained one or more 

E. coli O157:H7. 

September 7, 2001 95 
3. Exposure Assessment 

TABLE 3-27 Results of 100 Simulations for Grinder Loads Constructed from 2,000-Pound 

Combo Bins in the Low and High Prevalence Seasons 

Percent Contaminated Grinder Loads 

Low Prevalence Season High Prevalence Season 

Mean 68% 86% 

Minimum 28% 61% 

5th percentile 40% 76% 

50th percentile 71% 88% 

95th percentile 84% 93% 

Maximum 88% 94% 

Grinder Loads Made from 60-Pound Trim Boxes

Another intermediate output of the preparation module is the distribution of E. coli O157:H7 

densities in grinder loads of ground beef made from 60-pound trim boxes. Figure 3-28 shows the 

results of 100 simulations for grinder loads constructed from these 60-pound boxes in the low 

and high prevalence seasons. 

0.00

0.02

0.04

0.06

0.08

0.10

0.12

1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 1.0E-01

0.00

0.02

0.04

0.06

0.08

0.10

0.12

1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 1.0E-01

FrequencyFrequency

E. coli O157:H7 per Gram in Grinder Loads

Made from Boxes in Low Prevalence Season

E. coli O157:H7 per Gram in Grinder Loads

Made from Boxes in High Prevalence Season

FIGURE 3-28 Frequency of ground beef contamination in contaminated grinder loads made from 

60-pound trim boxes in low and high prevalence seasons. Grinder loads that are not 

contaminated are not shown in this chart. The mean grinder load distribution is represented by 

the dark line. 

Table 3-28 summarizes the prevalence of contaminated grinder loads constructed from trim 

boxes for the 100 simulations depicted in Figure 3-29. The mean results imply that 84% of the 

grinder loads in the low prevalence season and 73% of the grinder loads in the high prevalence 

season are not contaminated. 

In the low prevalence season, between 2% (5th percentile) and 13% (95th percentile) of 

grinder loads constructed from trim boxes contained one or more E. coli O157:H7. In the high 

prevalence season, between 7% (5th percentile) and 22% (95th percentile) of these grinder loads 

contained one or more E. coli O157:H7. 

September 7, 2001 96 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

TABLE 3-28 Results of 100 Simulations for Grinder Loads Constructed from 60-Pound Trim 

Boxes in the Low and High Prevalence Seasons 

Percent Contaminated Grinder Loads 

Low Prevalence Season High Prevalence Season 

Mean 7% 15% 

Minimum 1% 4% 

5th percentile 2% 7% 

50th percentile 7% 16% 

95th percentile 13% 22% 

Maximum 16% 27% 

0.000000001

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

316,228

10,000,000

316,227,766

10,000,000,000

Number of E. coli O157:H7 in 

post cooked ground beef 

servings in low prevalence season

Frequency

0.000000001

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

316,228

10,000,000

316,227,766

10,000,000,000

Number of E. coli O157:H7 in 

post cooked ground beef 

servings in high prevalence season

Frequency

Number of E. coli O157:H7 in

Post-Cooked Ground Beef Servings in

Low Prevalence Season

Number of E. coli O157:H7 in

Post-Cooked Ground Beef Servings in

High Prevalence Season

FIGURE 3-29 Frequency of exposure to various levels of E. coli O157:H7 during the low 

prevalence and high prevalence seasons. The mean exposure distribution for each is designated 

by the dark line. 

Human Exposure to E. coli O157:H7 

The primary outputs from the preparation module are distributions describing the prevalence of 

E. coli O157:H7 in ground beef servings generated during low and high prevalence seasons. 

These outputs become the inputs to risk characterization in which these exposure distributions 

are integrated with the output of hazard characterization to estimate risk of human illness from E. 

coli O157:H7 in ground beef. Figure 3-29 shows the results of 100 simulations for exposure 

distributions for the low and high prevalence seasons. 

As shown in Figure 3-29, very few cooked ground beef servings are expected to have 

surviving E. coli O157:H7 organisms present. Table 3-29 summarizes the simulations shown in 

Figure 3-29. The mean results imply that 99.993% of cooked ground beef servings in the low 

prevalence season and 99.982% of cooked ground beef servings in the high prevalence season 

have no E. coli O157:H7 present. Furthermore, of the contaminated servings shown in Figure 

3-29, about 95% have 10 or fewer E. coli O157:H7 organisms. 

September 7, 2001 97 
3. Exposure Assessment 

TABLE 3-29 Results of 100 Simulations Showing Percent of Post-Cooked Servings that Are 

Predicted to Have One or More Surviving E. coli O157:H7 in the Low and High Prevalence 

Seasons 

Percent Contaminated Servings 

Low Prevalence Season High Prevalence Season 

Mean 0.007% 0.018% 

Minimum 0.002% 0.004% 

5th percentile 0.003% 0.007% 

50th percentile 0.006% 0.019% 

95th percentile 0.013% 0.030% 

Maximum 0.014% 0.042% 

Nevertheless, considerable uncertainty exists regarding the frequency of cooked ground beef 

servings that have 1 or more E. coli O157:H7 present. Table 3-29 implies that there is 90% 

confidence that the true frequency of contaminated servings lies somewhere between 1 in 36,000 

and 1 in 7,600 in the low prevalence season and between 1 in 15,000 and 1 in 3,300 in the high 

prevalence season. In other words, there is a two- to threefold increase in the probability of 

consuming a contaminated serving in the high prevalence season compared with the low 

prevalence season. Such a difference mirrors the difference noted in FSIS ground beef sampling 

data between the high and low prevalence seasons (see Appendix A). 

REFERENCES 

American Meat Institute Foundation (AMIF). 1996, December. Relative Ground Beef 

Contribution to the United States Beef Supply. Final Report. Washington, DC: American 

Meat Institute Foundation. 

Ansay, S.E., K.A. Darling, and C.W. Kaspar. 1999. Survival of Escherichia coli O157:H7 in 

ground-beef patties during storage at 2, –2, 15 and then –2 degrees C, and –20 degrees C. 

J Food Prot 62(11):1243-1247. 

Animal and Plant Health Inspection Service (APHIS:VS:CEAH). 1994, March. Escherichia coli

O157:H7 Issues and Ramifications. Fort Collins, CO. 

Animal and Plant Health Inspection Service/National Animal Health Monitoring System 

(APHIS-VS-NAHMS). 1996, May. Part 1: Reference of 1996 Dairy Management Practices. 

Animal and Plant Health Inspection Service/National Animal Health Monitoring System 

(APHIS-VS-NAHMS). 1997, June. Part 1: Reference of 1997 Beef Cow-Calf Management 

Practices. 

Animal and Plant Health Inspection Service/National Animal Health Monitoring System 

(APHIS-VS-NAHMS). 1998, May. E. coli O157:H7 and Salmonella-Status on U.S. Dairy 

Operations. 

Audits International. 1999. U.S. Cold Temperature Evaluation. Unpublished data. 

Bacon, R.T., J.N. Sofos, K.E. Belk, et al. 1999. Evaluation of Multiple-Hurdle Microbiological 

Interventions—To Include Pre-Evisceration Spray-Washing and Other Technologies—For 

Beef Carcass Decontamination. Final Report. Submitted to National Cattlemen’s Beef 

Association, March 3, 1999. 

September 7, 2001 98 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Bacon, R.T., K.E. Belk, J.N. Sofos, et al. 2000. Incidence of Escherichia coli O157:H7 on Hide, 

Carcass and Beef Trimmings Samples Collected from United States Packing Plants. 

Presented at FSIS Public Meeting on E. coli O157:H7, February 29, 2000, Arlington, VA. 

Bailey, C., and R. Cox. 1976. The chilling of beef carcasses. Institutional Refrigeration Transport 

72:76-90. 

Bell, R.G. 1997. Distribution and sources of microbial contamination on beef carcasses. J Appl 

Microbiol 82:292-300. 

Besser, T.E., D.D. Hancock, L.C. Pritchett, E.M. McRae, D.H. Rice, and P.I. Tarr. 1997. 

Duration of detection of fecal excretion of Escherichia coli O157:H7 in cattle. J Infect Dis 

175:726-729. 

Biela, T., Texas American Food Service. 1998. Personal communication. 

Brent, C.P. 1999. Analysis of the Menu Census Survey Supplement—Hamburger and Egg 

Preparation Diary and Hamburger Consumption Quiz—for Consumer Storage and Handling 

Behaviors associated with Ground Beef. Informational memorandum to Margaret Coleman 

through Betsey Kuhn, Director, Food and Rural Economics Division, Economic Research 

Service, Washington, DC. 

Brewer, B., Food Safety and Inspection Service (Washington, DC). February 1999. Personal 

communication. 

Buchanan, R., and L. Bagi. 1994. Expansion of response surface models for the growth of E. coli

O157:H7 to include sodium nitrite as a variable. Int J Food Microbiol 23:317-332. 

Buchanan, R., and L. Bagi. 1997. Microbial competition: Effect of culture conditions on the 

suppression of Listeria monocytogenes Scott A by Carnobacterium piscicola. J Food Prot 

60:254-261. 

Cassin, M.H., A.M. Lammerding, E.C. Todd, W. Ross, and R.S. McColl. 1998. Quantitative risk 

assessment of Escherichia coli O157:H7 in ground beef hamburgers. Int J Food Microbiol 

41:21-44. 

Charlebois, R., R. Trudel, and S. Messier. 1991. Surface contamination of beef carcasses by fecal 

coliforms. J Food Prot 54:950-956. 

Cornell Collaborative Project. April 1998. Prevalence of E. coli O157:H7 Pre-Slaughter/E. coli

O157:H7 Associated Risk Factors. New York State Cull Cow Sub-Project. Final Report. 

Cray, W.C., and H.W. Moon. 1995. Experimental infection of calves and adult cattle with E. coli

O157:H7. Appl Environ Microbiol 61:1586-1590. 

Cray, W.C., T.A. Casey, B.T. Bosworth, and M.A. Rasmussen. 1998. Effect of dietary stress on 

fecal shedding of E. coli O157:H7 in calves. Appl Environ Microbiol 64:1975-1979. 

D'Sa, E.M., M.A. Harrison, S.E. Williams, and M.H. Broccoli. 2000. Effectiveness of two 

cooking systems in destroying Escherichia coli O157:H7 and Listeria monocytogenes in 

ground beef patties. J Food Prot 63(7):894-899. 

Dargatz, D.A., S.J. Wells, L.A. Thomas, D. Hancock, and L.P. Garber. 1997. Factors associated 

with the presence of Escherichia coli O157 in feces in feedlot cattle. J Food Prot 60:466-470. 

Delazari, I., S.T. Iaria, H. Riemann, D.O. Cliver, and N. Jothikumar. 1998a. Removal of 

Escherichia coli O157:H7 from surface tissues of beef carcasses inoculated with wet and dry 

manure. J Food Prot 61(10):1265-1268. 

Delazari, I., S.T. Iaria, H.P. Riemann, D.O. Cliver, and T. Mori. 1998b. Decontaminating beef 

for Escherichia coli O157:H7. J Food Prot 61:547-550. 

Diez–Gonzalez, F., T.R. Callway, and M.G. Kizoulis. 1998. Grain feeding and the dissemination 

of acid resistant E. coli from cattle. Science 281:1666-1668. 

Dorsa, W. 1997. Review: New and established carcass decontamination procedures commonly 

used in the beef-processing industry. J Food Prot 60:1146-1151. 

September 7, 2001 99 
3. Exposure Assessment 

Dorsa, W., C. Cutter, and G. Siragusa. 1997. Effects of acetic acid, lactic acid and trisodium 

phosphate on the microflora of refrigerated beef carcass surface tissue inoculated with 

Escherichia coli O157:H7, Listeria Innocua, and Clostridium Sporogenes. J Food Prot 

60:619-624. 

Duewer, L. 1998. Updated beef carcass-to-retail consumption conversion factor increases to 0.7. 

Livestock, Dairy and Poultry Situation and Outlook. LDP-M-51, ERS. Pages 11-12. 

Duffes, F., F. Leroi, P. Boyaval, and X. Dousset. 1999. Inhibition of Listeria monocytogenes by 

Carnobacterium spp. strains in a simulated cold smoked fish system stored at 4°C. Int J Food 

Microbiol 47:33-42. 

Elder, R.O., J.E. Keen, G.R. Siragusa, G.A. Barkocy-Gallagher, M. Koomaraie, and W.W. 

Laegreid. 2000. Correlation of enterohemorrhagic E. coli O157 prevalence in feces, hides, 

and carcasses of beef cattle during processing. Proc Natl Acad Sci 97(7):2999-3003. 

Farrell, B.L., A.B. Ronner, and A.C. Wong. 1998. Attachment of Escherichia coli O157:H7 in 

ground beef to meat grinders and survival after sanitation with chlorine and peroxyacetic 

acid. J Food Prot 119:817-822. 

Federal Register. July 7, 1998. Technologies for the detection and reduction of pathogens to 

improve food safety. 63(129):36654-36655. 

Food and Drug Administration (FDA). 1997. Food Code, 1997—Recommendations of the 

United States Public Health Service. National Technical Information Service PB97-133656. 

Food Safety and Inspection Service (FSIS). 1994. Nationwide Beef Microbiological Baseline 

Data Collection Program: Steers and Heifers—October 1992–September 1993. 

Food Safety and Inspection Service (FSIS). 1996. Directive #6350.1. Washington, DC. 

Food Safety and Inspection Service (FSIS). 1998. Animal Disposition Reporting System. 

(Available at: www.fsis.usda.gov/ophs/adrsdata/). 

Food Safety and Inspection Service (FSIS). 2000. Focus On Ground Beef. Consumer Education 

and Information. (Available at: http://www.fsis.usda.gov/OA/pubs/focusgb.htm.) 

Galland, J.C. 1997. Risks and prevention of contamination of beef carcasses during the slaughter 

process in the United States of America. Contamination of animal products: Prevention and 

risks for public health. Reveu Scientifique et Technique, Office International Des Epizooties. 

Garber, L.P., S.J. Wells, D.D. Hancock, M.P. Doyle, J. Tuttle, J.A. Shere, and T. Zhao. 1995. 

Risk factors for fecal shedding of Escherichia coli O157:H7 in dairy calves. J Am Vet Med 

Assoc 207:46-49. 

Garber, L., S. Wells, L. Schroeder–Tucker, and K. Ferris. 1999. Factors associated with the 

shedding of verotoxin-producing Escherichia coli O157 on dairy farms. J Food Prot 

62(4):307-312. 

Getz, D., LeFiell Company (Omaha, NE). January 1999. Personal communication. 

Gill, C.O. 1979. Intrinsic bacteria in meat. J Appl Bacteriol 47:367-378. 

Gill, C.O. 1996. Cold storage temperature fluctuations and predicting microbial growth. J Food 

Prot 43-47. 

Gill, C.O. 1998. Apparatus for Pasteurizing Red Meat Carcasses. Agriculture and Agri-Food 

Canada, Research Branch Technical Bulletin 1998-5E. 

Gill, C.O. 1999. HACCP by guesswork or by the numbers? Food Quality Jan/Feb:28-32. 

Gill, C.O., and M. Badoni. 1997. The hygienic and organoleptic qualities of ground beef 

prepared from manufacturing beef pasteurized by immersion in hot water. Meat Sci 46:67-

75. 

Gill, C.O., and J. Bryant. 1997. Assessment of the hygienic performances of two beef carcass 

cooling processes from product temperature history data or enumeration of bacteria on 

carcass surfaces. Food Microbiol 14:593-602. 

September 7, 2001 100 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Gill, C.O., M. Badoni, and T. Jones. 1996a. Hygienic effects of trimming and washing 

operations in a beef-carcass-dressing process. J Food Prot 59:666-669. 

Gill, C.O., J. McGinniss, and M. Badoni. 1996b. Assessment of the hygienic characteristics of a 

beef carcass dressing process. J Food Prot 59:136-140. 

Gill, C.O., M. Badoni, and J. McGinnis. 1999. Assessment of the adequacy of cleaning of 

equipment used for breaking beef carcasses. Int J Food Microbiol 46:1-8. 

Grau, F.H. 1987. Prevention of microbial contamination in the export beef abattoir. Pp. 221-233 

in Elimination of Pathogenic Organisms from Meat and Poultry, F.J.M. Smulders, ed. 

Amsterdam: Elsevier Press. 

Grau, F.H., and P.B. Vanderlinde. 1992. Occurrence, numbers, and growth of Listeria 

monocytogenes on some vacuum-packaged processed meats. J Food Prot 55:4-7. 

Gyles, C. 1998. Vaccines and shiga-toxin-producing Escherichia coli in animals. Pp. 434-444 in 

Escherichia coli O157:H7 and Other Shiga Toxin-Producing E. coli Strains, J.B. Kaper and 

A.D. O’Brien, eds. Washington, DC: ASM Press. 

Haas, C., J. Rose, and J. Gerba. 1999. Quantitative Microbial Risk Assessment. New York: John 

Wiley & Sons. 

Hancock, D. 2001. Personal communication. Ongoing research project in collaboration with 

FDA-CVM.

Hancock, D.D., T.E. Besser, M.L. Kinsel, P.I. Tarr, D.H. Rice, and M.G. Paros. 1994. The 

prevalence of Escherichia coli O157 in dairy and beef cattle in Washington State. Epidemiol 

Infect 113:199-207. 

Hancock, D.D., T.E. Besser, D.H. Rice, D.E. Herriott, and P.I. Tarr. 1997a. A longitudinal study 

of Escherichia coli O157 in fourteen cattle herds. Epidemiol Infect 118:193-195. 

Hancock, D.D., D.H. Rice, D.E. Herriot, T.E. Besser, E.D. Ebel, and L.V. Carpenter. 1997b. 

Effects of farm manure handling practices on Escherichia coli O157 prevalence in cattle. J 

Food Prot 60:363-366. 

Hancock, D.D., D.H. Rice, L.A. Thomas, D.A. Dargatz, and T.E. Besser. 1997c. Epidemiology 

of Escherichia coli O157 in feedlot cattle. J Food Prot 60:462-465. 

Hancock, D., T. Besser, and D. Rice. 1998a. Ecology of Escherichia coli O157:H7 in cattle and 

import of management practices. Pp. 85-91 in Escherichia coli O157:H7 and Other Shiga 

Toxin-Producing E. coli Strains, J.B. Kaper and A.D. O’Brien, eds. Washington, DC: ASM 

Press. 

Hancock, D.D., T.E. Besser, D.H. Rice, E.D. Ebel, D.E. Herriott, and L.V. Carpenter. 1998b. 

Multiple sources of Escherichia coli O157 in feedlots and dairy farms in the northwestern 

United States. Prev Vet Med 35:11-19. 

Hancock, D.D., D.H. Rice, and T.E. Besser. 1999. Prevalence of E. coli O157:H7 in feedlot 

cattle at slaughter plants. Study funded by National Cattlemen’s Association. Washington 

State University. 

Hancock, D., T. Besser, J. Lejeune, M. Davis, and D. Rice. 2001. The control of VTEC in the 

animal reservoir. Int J Food Microbiol 66:71-78. 

Hardin, M.G., L. Acuff, L.J. Oman, et al. 1995. Comparison of methods for contamination 

removal for beef carcass surfaces. J Food Prot 58:368-374. 

Herriot, D.E., D.D. Hancock, E.D. Ebel, L.V. Carpenter, D.H. Rice, and T.E. Besser. 1998. 

Association of herd management factors with colonization of dairy cattle by shiga toxinpositive E. coli O157. J Food Prot 61:802-807. 

September 7, 2001 101 
3. Exposure Assessment 

Heuvelink, A.E., F.L. Van den Biggelaar, J. Zwartkruis–Nahuis, R.G. Herbes, R. Huyben, N. 

Nagelkerke, W.J. Melchers, L.A. Monnens, and E. de Boer. 1998. Occurrence of 

verocytotoxin-producing Escherichia coli O157 on Dutch dairy farms. J Clin Microbiol 

Dec:3480-3487. 

Jackson, T.C., M.D. Hardin, and G.R. Acuff. 1996. Heat resistance of Escherichia coli O157:H7 

in a nutrient medium and in ground beef patties as influenced by storage and holding 

temperatures. J Food Prot 59:230-237. 

Jameson, J.F. 1962. A discussion of the dynamics of Salmonella enrichment. J Hygiene 

Cambridge, 60:193-207. 

Jordan, D. 1998. Pre-slaughter control of beef carcass contamination with Escherichia coli

O157:H7: A risk assessment approach. Ph.D. dissertation, University of Guelph. 

Jordan, D., S. McEwen, A. Lammerding, W. McNab, and J. Wilson. 1999. Pre-slaughter control 

of Escherichia coli O157 in beef cattle: A simulation study. Prev Vet Med 41:55-74. 

Juneja, V.K., O.P. Snyder Jr., A.C. Williams, and B.S. Marmer. 1997. Thermal destruction of 

Escherichia coli O157:H7 in hamburger. J Food Prot 60:1163-1166. 

Kastner, C. 1998. Research Highlights. Kansas State University Food Safety Consortium Annual 

Report. 

Kause, J. 2001. SAS Analysis of the 1994–1996, 1998 CSFII for Consumption of Ground Beef 

by Age and Location for the E. coli O157:H7 Risk Assessment. Informational memorandum 

to Wayne Schlosser through Carol Maczka, Director, Risk Assessment Branch, Office of 

Public Health and Science, Food Safety and Inspection Service, USDA, Washington, DC. 

Labadie, J., P. Gouet, and J. Fourand. 1977. Blood poisonings at slaughter and their 

consequences. Zentralbl Bakteriol Parasitenkd Infectionskr Hyg Abt 1 Orig Reihe B 

164:390-396. 

Lagreid, W.W., R.O. Elder, and J.E. Keen. 1999. Prevalence of E. coli O157:H7 in range calves 

at weaning. Epidemiol Infect 123(2):291-298. 

Liu, M.N., and B.W. Berry. 1996. Variability in color, cooking times, and internal temperature of 

beef patties under controlled cooking conditions. J Food Prot 59:969-975. 

Marks, H.M., M.E. Coleman, C.T.J. Lin, and T. Roberts. 1998. Topics in risk assessment: 

Dynamic flow tree process. Risk Anal 18:309-328. 

Martin, S.W., A.H. Meek, and P. Wilberg. 1987. Veterinary Epidemiology. Ames, Iowa: Iowa 

State University Press. 

McAloon, T., Cargill. March 1999. Personal communication. 

Mechie, S.C., P.A. Chapman, and C.A. Siddons. 1997. A fifteen month study of E. coli O157:H7 

in a dairy herd. Epidemiol Infect 118(1):17-25. 

National Advisory Committee on Microbiological Criteria for Foods (NACMCF). 1993. Report 

on generic HACCP for raw beef. Food Microbiol 10:449-488. 

National Advisory Committee on Microbiological Criteria in Foods (NACMCF). 1997. Minutes 

from November 20, 1997, meeting. 

National Advisory Committee on Microbiological Criteria in Foods (NACMCF). 1999. Minutes 

from December 10, 1999, meeting. 

National Agricultural Statistics Service (NASS). 1998. Livestock Slaughter: 1997 Summary. 

MtAn1-2-1(98):5,15. 

New Zealand Public Health Report. 2000, July/August. Shiga-Toxin Producing Escherichia coli

(STEC) Cases Increase Again in 1999. ISSN 1173-0250. Vol. 8, No. 7/8. 

Newton, K.G., J.C. Harrison, and A. Wauters. 1978. Sources of psychotropic bacteria on meat at 

the abattoir. J Appl Bacteriol 45(1):75-82. 

September 7, 2001 102 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Nilsson, L., L. Gram, and H.H. Huss. 1999. Growth control of Listeria monocytogenes on coldsmoked salmon using a competitive lactic acid bacteria flora. J Food Prot 62:336-342. 

Nutsch, A.L., R.K. Phebus, M.J. Riemann, J.S. Kotrola, D.E. Schaefer, J.E. Boyer, Jr., R.C. 

Wilson, J.D. Leising, and C.L. Castner. 1997. Evaluation of a steam pasteurization process in 

a commercial beef processing facility. J Food Prot 60:485-492. 

Nutsch, A.L., R.K. Phebus, M.J. Riemann, J.S. Kotrola, R.C. Wilson, J.E. Boyer, Jr., and T.L. 

Brown. 1998. Steam pasteurization of commercially slaughtered beef carcasses: Evaluation 

of bacterial populations at five anatomical locations. J Food Prot 61:571-577. 

Phebus, R., Kansas State University (Manhattan, KS). 1999. Personal communication. 

Phebus, R.K., A.L. Nutsch, D.E. Schafer, R.C. Wilson, M.J. Riemann, J.D. Leising, C.L. 

Kastner, J.R. Wolf, and R.K. Prasai. 1997. Comparison of steam pasteurization and other 

methods for reduction of pathogens on surfaces of freshly slaughtered beef. J Food Prot 

60:476-484. 

Prasai, R., R.K. Phebus, C.M. Garcia Zepeda, C.C. Kastner, A.E. Boyle, and D.Y.C. Fung. 1995. 

Effectiveness of trimming and/or washing on microbiological quality of beef carcass. J Food 

Prot 58:1114-1177. 

Puyalto, C., C. Colmin, and A. Laval. 1997. Salmonella typhimurium contamination from farm 

to meat in adult cattle. Descriptive study. Vet Res 28:449-460. 

Rice, D.H., E.D. Ebel, D.D. Hancock, D.E. Herriott, and L.V. Carpenter. 1997. Escherichia coli

O157 in cull dairy cows on farm, and at slaughter. J Food Prot 60:1-2. 

Robins-Browne, R.M., E. Elliot, and P. Desmarchelier. 1998. Shiga toxin-producing Escherichia 

coli in Australia. In Escherichia coli O157:H7 and Other Shiga Toxin-Producing E. coli

Strains, J.B. Kaper and A.D. O’Brien, eds. Washington, DC: ASM Press. 

Ross, T. and T.A. McMeekin. 1991. Predictive microbiology: Applications of a square root 

model. Food Australia 43:202-207. 

Sage, J.R., and S.C. Ingham. 1998. Survival of Escherichia coli O157:H7 after freezing and 

thawing in ground beef patties. J Food Prot 61(9):1181-1183. 

Sanderson, M.W., J.M. Gay, D.D. Hancock, C.C. Gray, L.K. Fox, and T.E. Besser. 1995. 

Sensitivity of bacteriologic culture for detection of Escherichia coli O157:H7 in bovine 

feces. J Clin Microbiol 33(10):2616-2629. 

Sargeant, J.M., J.R. Gillespie, R.D. Oberst, R.K. Phebus, D.R. Hyatt, L.K. Bohra, and J.C. 

Galland. 2000. Results of a longitudinal study of the prevalence of E. coli O157:H7 on cowcalf farms. Am J Vet Res 61(11):1375-1379. 

Scanga, J.A., A.D. Grona, K.E. Belk, J.N. Sofos, and G.R. Smith. 2000. Microbiological 

contamination of raw beef trimmings and ground beef. Meat Sci 56:145-152. 

Semanchek, J.J., and D.A. Golden. 1998. Influence of growth temperature on inactivation and 

injury of Escherichia coli O157:H7 by heat, acid, and freezing. J Food Prot 61:395-401. 

Sheridan, J., B. Lynch, and D. Harrington. 1992. The effect of boning plant cleaning on the 

contamination of beef cuts in commercial boning hall. Meat Sci 32:155-164. 

Siragusa, G.R., W.J. Dorsa, C.N. Cutter, G.L. Bennett, J.E. Keen, and M. Koohmaraie. 1998. 

The incidence of Escherichia coli on beef carcasses and its association with aerobic 

mesophilic plate count categories during the slaughter process. J Food Prot 61:1269-1274. 

Smeltzer, T., B. Peel, and G. Collins. 1998. The role of equipment that has direct contact with 

the carcass in the spread of Salmonella in beef abattoir. Aust Vet J 55:275-277. 

Smith, D.R. 1999. Designing Strategies for Food Safety Pathogen Containment in Cattle 

Feedyards. Presented at Annual Meeting of U.S. Animal Health Association, San Diego, CA. 

Smith, G., Colorado State University—Meat Sciences Department. 1998. Personal 

communication. 

September 7, 2001 103 
3. Exposure Assessment 

Spika, J.S., R. Khakhria, P. Michel, D. Milley, J. Wilson, and J. Waters. 1998. Shiga toxinproducing Escherichia coli infections in Canada. In Escherichia coli O157:H7 and Other 

Shiga Toxin-Producing E. coli Strains, J.B. Kaper and A.D. O’Brien, eds. Washington, DC: 

ASM Press. 

Van Donkersgoed, J., K.W.F. Jericho, and H. Grogan. 1997. Preslaughter hide status of cattle 

and the microbiology of carcasses. J Food Prot 60(12):1502-1508. 

Van Donkersgoed, J., T. Graham, and V. Gannon. 1999. The prevalence of vertoxins, E. coli

O157:H7, and Salmonella in the feces and rumen of cattle at processing. Can Vet J 40:332-

338. 

Van Laack, R.L.J.M., W.B. Berry, and M.B. Solomon. 1996. Effect of precooking conditions on 

color of cooked beef patties. J Food Prot 59:976-983. 

Vose, D.J. 1996. Quantitative Risk Analysis: A Guide to Monte Carlo Simulation Modeling. 

West Sussex, England: John Wiley and Sons, Ltd. 

Vose, D.J. 1999. Fitting second order nonparametric distributions to data using Bayes’ theorem, 

Unpublished manuscript. 

Walls, I., and V.N. Scott. 1996. Validation of predictive mathematical models describing the 

growth of Escherichia coli O157:H7 in raw ground beef. J Food Prot 59:1331-1335. 

Zhao, T., M.P. Doyle, J. Shere, and L. Garber. 1995. Prevalence of enterohemorrhagic 

Escherichia coli O157:H7 in a survey of dairy herds. Appl Environ Microbiol 61:1290-1293. 

September 7, 2001 104 
4 

Hazard Characterization 

This chapter describes the process used to characterize the number of symptomatic infections 

resulting from the consumption of cooked ground beef servings contaminated with Escherichia 

coli O157:H7. This process is commonly referred to as a dose-response assessment. Unlike many 

chemical hazards and some pathogens, the dose-response relationship for E. coli O157:H7 is 

unknown. Limited dose-response information is available from an animal study conducted by Pai 

et al. (1986), in which infant rabbits were exposed to E. coli O157:H7. Because there is no 

effective treatment for E. coli O157:H7 infection and the outcome of infection can include severe 

illness and death, experimental studies exposing humans to E. coli O157:H7 have not been, and 

probably never will be, performed. In contrast, a substantial amount of surveillance data exist on 

the annual number of illnesses due to infection with E. coli O157:H7. Thus, this risk assessment 

uses a multistep process to derive a dose-response function for E. coli O157:H7 (Figure 4-1). 

This process is divided into four primary steps: (1) estimation of the number of E. coli O157:H7-

related illnesses attributable to the consumption of contaminated ground beef (response); (2) 

estimation of the likelihood and level of E. coli O157:H7 in cooked ground beef servings (dose, 

derived in Chapter 3); (3) derivation of upper and lower bounds for the E. coli O157:H7 doseresponse function based on clinical studies of surrogate pathogens; and (4) derivation of the 

“most likely” (50th percentile) dose-response function for E. coli O157:H7 (Powell et al. 2000). 

This chapter begins by estimating a baseline annual number of illnesses of E. coli O157:H7 

infection from all exposures using data from the Emerging Infections Program, Foodborne 

Disease Active Surveillance Network (FoodNet). This baseline annual number of cases is 

adjusted upward to account for underdiagnosis and underreporting, providing an estimated total 

annual number of cases of symptomatic E. coli O157:H7 infection for the United States. Then, 

using data from studies of sporadic cases of E. coli O157:H7 infection and outbreaks of E. coli

O157:H7, the proportion of total cases due to ground beef exposure is derived. Next, lower and 

upper bound dose-response functions are constructed using foodborne pathogens other than 

E coli O157:H7. These lower and upper bound dose response functions are used in combination 

with the estimated number of cases due to ground beef and the estimated number of ground beef 

September 7, 2001 105 
4. Hazard Characterization 

Estimated baseline number of cases of E. coli O157:H7

illness due to all exposures, United States

Table 4-1

Total annual number of cases of E. coli O157:H7 illness

adjusted for underdiagnosis and underreporting

Tables 4-2, 4-3, 4-4

E. coli O157:H7 dose-response function

Figures 4-4, 4-5, 4-6, 4-7

Illnesses with severe

clinical outcomes

Table 4-7

Proportion of E. coli O157:H7 illnesses due to ground

beef (response)

Table 4-4, Figure 4-2

Number of E. coli O157:H7 in

ground beef servings (dose)

Chapter 3

E. coli O157:H7 dose-response

boundaries based on surrogate

pathogens

Tables 4-5, 4-6, 4-7, Figure 4-3

Validation of E. coli O157:H7 dose-response function

using data from a 1993 outbreak of E. coli O157:H7

associated with the consumption of contaminated ground

beef (Bell et al. 1994)

FIGURE 4-1 Flowchart for the derivation of the dose-response function for E. coli O157:H7 in 

ground beef. 

servings contaminated with E. coli O157:H7 to generate a dose-response function for E. coli

O157:H7. Finally, dose and response information from an outbreak of E. coli O157:H7 due to 

contaminated ground beef is compared with the E. coli O157:H7 dose-response function. 

DEFINITION OF KEY TERMS 

The following key terms are used throughout this chapter: 

• Dose is the number of E. coli O157:H7 organisms in a serving of ground beef. 

• Response refers to the number and severity of illnesses resulting from consumption of 

ground beef servings contaminated with E. coli O157:H7. 

September 7, 2001 106 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

• Dose-response function refers to the mathematical relationship between the consumption 

of a ground beef serving containing a specific number (dose) of organisms and the 

resulting number of illnesses (response). 

• Surrogate pathogens refers to pathogens that are either closely related genetically or have 

a similar mechanism of pathogenicity to the pathogen of interest. 

• Lower bound refers to the dose-response curve derived from pathogenesis studies of 

enteropathogenic E. coli (EPEC). 

• Upper bound refers to the dose-response curve derived from pathogenesis studies of 

Shigella dysenteriae. 

ESTIMATING THE RESPONSE 

Estimating the number of symptomatic E. coli O157:H7 infections due to contaminated ground 

beef first requires an estimation of the total number of cases that occur annually in the United 

States from all causes. 

Baseline Annual Number of E. coli O157:H7 Infections Due to All Causes 

FoodNet surveillance data for 1996 to 1999 were used to estimate the annual baseline number of 

symptomatic E. coli O157:H7 infections (1999 is the most recent year for which a final report is 

available). For information about FoodNet, please see Chapter 2. For each year and FoodNet site, 

the number of cases per 100,000 population was calculated. This rate per 100,000 population 

was multiplied by that state's population and then divided by the total population of all sites, for 

that year, providing a weighted rate for each state. Weighted rates for each state were then 

summed, resulting in an annual incidence estimate for 1996 to 1999 of 1.53, 1.25, 1.95, and 2.09, 

respectively (Table 4-1). 

TABLE 4-1 Population-Weighted Rate of Illness Caused by E. coli O157:H7 

Year 

1999 1998 1997 1996 

FoodNet State: California 

Cases reported to FoodNeta 23 35 19 22

FoodNet catchment populationa 2,162,359 2,063,454 2,063,454 2,063,454

Unadjusted rate (per 100,000 personyears) 

1.06 1.70 0.92 1.07

State populationb 33,145,121 32,666,550 32,182,118 31,762,190

Weighted rate 0.47 1.07 0.58 0.67

State: Connecticut 

Cases 94 58 34 38

Catchment population 3,282,031 2,460,127 2,460,127 1,626,366

Unadjusted rate 2.86 2.36 1.38 2.34

State population 3,282,031 3,274,069 3,267,240 3,263,910

Weighted rate 0.12 0.15 0.09 0.15

(continued) 

September 7, 2001 107 
4. Hazard Characterization 

TABLE 4-1 (continued) 

Year 

1999 1998 1997 1996 

State: Georgia 

Cases 44 51 8 15

Catchment population 7,788,240 3,541,230 3,541,230 2,729,783

Unadjusted rate 0.56 1.44 0.23 0.55

State population 7,788,240 7,642,207 7,489,982 7,334,183

Weighted rate 0.06 0.21 0.03 0.08

State: Marylandc

Cases 16 24

Catchment population 2,450,566 2,444,280

Unadjusted rate 0.65 0.98

State population 5,171,634 5,130,072

Weighted rate 0.04 0.07

State: Minnesota 

Cases 175 209 199 239

Catchment population 4,775,508 4,725,419 4,687,408 4,657,758

Unadjusted rate 0.65 4.42 4.25 5.13

State population 5,171,634 4,725,419 4,687,408 4,648,081

Weighted rate 0.04 0.41 0.39 0.47

State: New Yorkc

Cases 94 22

Catchment population 20,844,453 1,106,085

Unadjusted rate 4.51 1.99

State population 18,196,601 18,159,175

Weighted rate 1.08 0.48

FoodNet State: Oregon 

Cases 64 101 80 73

Catchment population 3,316,154 3,281,974 3,243,272 3,203,735

Unadjusted rate 1.93 3.08 2.47 2.28

State population 3,316,154 3,281,974 3,243,272 3,195,409

Weighted rate 0.08 0.20 0.16 0.14

TOTAL 

Cases 510 500 340 387

Catchment population 25,859,311 19,622,569 15,995,491 14,281,096

Unadjusted rate 1.97 2.55 2.13 2.71

States’ population 75,675,289 74,879,466 50,870,020 50,203,773

Weighted rate 2.09 1.95 1.25 1.53 a

Data obtained from FoodNet final reports for each calendar year from www.cdc.gov. 

b

State population estimates for July 1 of each calendar year from www.census.gov. c

Maryland and New York began surveillance in 1998. 

September 7, 2001 108 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

To represent variability in the annual number of reported cases, these four weighted rates 

were placed into a discrete uniform probability distribution (DUniform [1.53, 1.25, 1.95, 2.09]). 

During Monte Carlo simulation, one of these four rates is selected at random with equal 

probability. The output of this simulation is a list of possible rates and the frequency at which 

each possible rate occurred during multiple iterations of the model. The median rate from this 

output was multiplied by the estimated 1999 U.S. population of 272.7 million (Table 4-3) to 

obtain an estimated baseline annual number of cases of symptomatic E. coli O157:H7 infection. 

The median baseline number of cases estimated by the model was 4,200 (3,500 and 5,700—2.5th 

and 97.5th percentiles, respectively). This estimated number of cases has been rounded to two 

significant digits. 

Adjusting the Baseline for Underdiagnosis and Underreporting 

The baseline annual number of E. coli O157:H7 cases was adjusted upward to account for 

recognized sources of underdiagnosis and underreporting. These sources include ill persons who 

do not seek medical care, physicians who do not obtain stool specimens from patients with E. 

coli O157:H7 infection, laboratories that do not culture all stool samples for E. coli O157:H7, 

and the ability to detect antigen in E. coli O157:H7-contaminated stool samples (test sensitivity). 

However, before making this upward adjustment, the baseline annual number of cases was 

divided into two groups—cases with bloody diarrhea and cases with nonbloody diarrhea—by 

multiplying the baseline number of cases by the proportion expected to have bloody diarrhea 

(Table 4-2). Cases were divided into these two groups because the likelihood of seeking medical 

care, obtaining a stool specimen, and testing a stool specimen for E. coli O157:H7 is greater for 

patients with bloody diarrhea than for those with nonbloody diarrhea. 

A negative binomial distribution was then applied to each of the sources of underdiagnosis 

and underreporting described above, providing an estimation of the number of missed cases. This 

procedure was completed separately for each of the two pathways: patients with bloody diarrhea 

and patients with nonbloody diarrhea. The negative binomial probability distribution outputs the 

number of failures (i.e., unreported cases), given inputs of the number of successes (reported 

cases) and the probability of success (estimates derived from the literature, described below). 

The probability of success used in the negative binomial probability distribution was estimated 

using a beta probability distribution. The output of the beta probability distribution is the 

prevalence (proportion) of an event, given inputs of the number of successes, s, and the number 

of trials, n. 

The median (most likely) number of cases generated by the negative binomial distribution 

was used as the number of "missed cases" for each source of underdiagnosis/underreporting. 

Beginning with the baseline annual number of cases (described above), the missed cases for each 

source are summed for each group (those with bloody diarrhea and those with nonbloody 

diarrhea), and then the two group totals are summed to give an estimate of the total annual 

number of cases of symptomatic E. coli O157:H7 infection in the United States. 

The data used as inputs into the negative binomial distribution are described above and 

summarized in Table 4-2. The distributions are listed in Table 4-3. The Monte Carlo simulation 

methods used here produce a distribution of possible values for each of the outcomes. Table 4-4 

and Figure 4-2 show the results of this process, including estimates of the annual number of 

cases with bloody and nonbloody diarrhea and the total annual number of cases for the United 

States. The 2.5th and 97.5th percentiles represent the uncertainty about the number of cases at 

each step. The number of cases shown has been rounded to two significant digits to avoid 

September 7, 2001 109 
4. Hazard Characterization 

TABLE 4-2 Sources of Data Used to Estimate the Number of Undetected Cases of E. coli

O157:H7 Infection 

Event Data Reference(s) 

Cases with bloody diarrhea 

are reported 

640 of 757 (84.5%) patients with E. coli

O157:H7 had bloody diarrhea 

Ostroff et al. 1989 

Hedberg et al. 1997 

Slutsker et al. 1997 

Kassenborg et al. 2001 

Ill persons seek medical 

care 

88 of 1,100 (8.0%) survey respondents 

reported seeking medical care for diarrhea 

37 of 76 (48.7%) E. coli O157:H7 cases with 

bloody diarrhea sought medical care 

CDC 1998 

Cieslak et al. 1997 

Hedberg et al. 1997 

Physicians obtain culture 

from patients 

699 of 1,943 (36.0%) physicians surveyed 

obtain cultures from patients presenting with 

nonbloody diarrhea; 1,515 of 1,943 (78.0%) 

physicians obtain cultures from patients 

presenting with bloody diarrhea 

Hedberg et al. 1997 

Laboratories culture stool 

samples for E. coli

O157:H7 

108 of 230 (47.0%) labs surveyed test 

nonbloody stool for E. coli O157:H7 

182 of 230 (79.1%) labs test bloody stool for 

E. coli O157:H7 

CDC 1997 

Sorbitol MacConkey agar 

(SMAC) test sensitivity 

0.75 = probability a sample test is positive 

given it is infected 

Hedberg et al. 1997 

overstating the precision of the model. Outputs for intermediate steps in the pathway (e.g., 

probability of seeking care, probability of having a stool sample taken) are not shown. 

Data Used to Adjust for Underdiagnosis and Underreporting 

The proportion of patients who had bloody diarrhea was derived from the literature. A total of 

640 (84.5%) of 757 reported cases of E. coli O157:H7 infection presented with bloody diarrhea 

(Ostroff et al. 1989; Hedberg et al. 1997; Slutsker et al. 1997; Kassenborg et al. 2001). These 

data were used in a beta distribution with inputs of the number of successes, s=640 (i.e., persons 

with bloody diarrhea), and the total sample size, n=757 (number of cases of symptomatic E. coli

O157:H7 infection) (see Tables 4-2 and 4-3). 

Information on the proportion of ill persons seeking medical care, physicians who obtain 

stool samples from symptomatic patients, and laboratory testing practices was obtained from 

FoodNet surveys and is summarized in Table 4-2. A high percentage of persons with bloody 

diarrhea seek medical care. Cieslak et al. (1997) found that 32 (55.2%) of 58 cases with bloody 

diarrhea in an E. coli O157:H7 outbreak in Las Vegas reported seeking medical care. Data from 

this and another study (Hedberg et al. 1997) were input into a beta distribution with inputs of 

s=37 and n=76 to determine the most likely number of missed cases at this step and the 

associated uncertainty. In the Hedberg et al. (1997) study, 88 (8.0%) of 1,100 respondents who 

had nonbloody diarrhea reported seeking medical attention. These values were used in a beta 

distribution with s=88 and n=1,100 (Tables 4-2 and 4-3). 

September 7, 2001 110 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

TABLE 4-3 Input Values and Distributions Used to Estimate the Annual Number of Cases of E. 

coli O157:H7 Infection with Bloody and Nonbloody Diarrhea and the Total Number of Cases in 

the United States

Epidemiologic Parameter Distribution 

Population-weighted, reported 

rate of E. coli O157:H7 per 

100,000 person-years, all 

FoodNet sites, 1996–99 

Discrete Uniform (1.53, 1.25, 1.95, 2.09)a

U.S. population (1999) 272.7 million 

P(Case with bloody diarrhea is 

reported)b

Beta (640 + 1, 757 – 640 + 1)c

P(Case with nonbloody diarrhea 

is reported) 

1 – Beta (640 + 1, 757 – 640 + 1) 

Bloody Nonbloody 

P(Laboratory cultures stool 

sample for E. coli O157:H7 ) 

Beta (182 + 1, 230 – 182 + 1) Beta (108 + 1, 230 – 108 + 1) 

P(Physician obtains culture from 

patient) 

Beta (1,515 + 1, 1,943 – 

1,515 + 1) 

Beta (699 + 1, 1,943 – 699 + 

1) 

P(Ill person seeks medical care) Beta (37 + 1, 76 – 37 + 1) Beta (88 + 1, 1,100 – 88 + 1) a

In a discrete uniform distribution, each of the four values listed in parentheses is equally likely to be sampled during 

simulations. 

b

P=probability of the event described. c

The input format for a beta distribution is (s+1,n–s+1), where s=the number of events of interest and n=total 

number of events measured (e.g., the number of cases with bloody diarrhea [s] and the number of all cases of 

symptomatic E. coli O157:H7 infection [n]). 

0.00

0.05

0.10

0.15

0.20

0.25

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

50,000

55,000

60,000

65,000

70,000

Number of Cases

Probability

FIGURE 4-2 Estimated annual number of human cases of E. coli O157:H7 due to ground beef 

exposure. 

September 7, 2001 111 
4. Hazard Characterization 

TABLE 4-4 Number of Cases of Symptomatic E. coli O157:H7 Infection Due to All Exposures 

and Due to Exposure to Ground Beef Only (6,000 Iterations) 

Number of Reported Cases Median 2.5th and 97.5th Percentiles 

All exposures 

Cases with bloody diarrhea 19,000 12,000 and 28,000 

Cases with nonbloody diarrhea 74,000 45,000 and 116,000 

Total annual cases 94,000 59,000 and 138,000 

Ground beef exposures 

Cases with bloody diarrhea 3,800 1,000 and 9,000 

Cases with nonbloody diarrhea 15,000 4,100 and 37,000 

Total annual cases 19,000 5,300 and 45,000 

Note: Number of cases has been rounded to two significant digits. 

In a survey conducted in the FoodNet catchment area, 1,515 (78.0%) of 1,943 physicians 

reported that they obtained stool specimens from patients presenting with bloody diarrhea, and 

699 (36.0%) of 1,943 physicians reported obtaining specimens from patients with nonbloody 

diarrhea (Hedberg et al. 1997). These data were fit to beta distributions (Tables 4-2 and 4-3). 

In a national survey of clinical laboratories, 182 (79.1%) of 230 laboratories reported testing 

bloody stool for E. coli O157:H7 (CDC 1998), providing inputs for the beta distribution with 

s=182 and n=230 (Table 4-2). Only 108 (47.0%) of 230 laboratories reported testing all stool 

samples for E. coli O157:H7 (Hedberg et al. 1997), providing an s=108 and n=230 for input into 

a beta distribution (Tables 4-2 and 4-3). Hedberg et al. (1997) also reported that the sensitivity of 

the sorbitol MacConkey agar (SMAC) test used by the laboratories to identify E. coli O157:H7 

in stool samples is 71% (Tables 4-2 and 4-3). 

The model estimates that a median of 94,000 cases of symptomatic E. coli O157:H7 infection 

occur annually in the United States, accounting for underdiagnosis and underreporting (Table 

4-4). Of these, an estimated 19,000 (20.2%) cases were characterized by bloody diarrhea. Mead 

et al. (1999) estimated that 73,480 cases of E. coli O157:H7 due to all exposures occur annually 

in the United States, approximately 20,000 fewer cases than the estimate derived by this risk 

assessment. This difference may be explained by differences in the methods used to derive the 

annual estimated number of cases. In the Mead et al. study, a weighted rate of 1.34 cases per 

100,000 population was used to calculate a baseline number of cases. This rate is smaller than 

three of the four weighted rates used in this risk assessment (Table 4-1). In addition, Mead used a 

multiplier of 20 unreported cases for each reported case. In this risk assessment, unreported cases 

were estimated by several steps for two pathways: illnesses due to E. coli O157:H7 infection 

with bloody diarrhea and those with nonbloody diarrhea. This process resulted in 22 unreported 

cases for each reported case (94,000/4,200). 

Estimating the Number of E. coli O157:H7 Illnesses Due to Contaminated Ground Beef 

(Etiologic Fraction) 

To estimate the number of cases attributable to ground beef, the estimated total annual number of 

symptomatic E. coli O157:H7 infections for a given iteration was multiplied by an estimate of 

the proportion of cases due to exposure to ground beef (etiologic fraction). This calculation was 

done using Monte Carlo simulation and the inputs described below. 

September 7, 2001 112 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

To estimate the etiologic fraction, data from studies of sporadic cases and outbreaks of E. 

coli O157:H7 were incorporated. Data from all outbreaks in which the route of transmission was 

identified were used, including those with waterborne and person-to-person transmission (CDC 

unpublished data). Two estimates were derived from outbreaks: the proportion of illnesses and 

the proportion of outbreaks due to ground beef exposure. During 1996 to 1999 (1999 is the most 

recent year for which data are available), ground beef was the most likely vehicle in 44 (30.1%) 

of 146 reported outbreaks of E. coli O157:H7 with an identified vehicle. This information was 

input into a beta distribution with s=44 and n=146. For the 146 outbreaks, 418 (11.1%) of 3,773 

cases were attributed to ground beef; this information was input into a beta distribution with 

s=418 and n=3,773. Information from 48 outbreaks during 1996 to 1999 was excluded from this 

analysis. 

Additional estimates of the etiologic fraction of illness due to ground beef contaminated with 

E. coli O157:H7 were obtained from four different case-control studies of mostly sporadic cases 

(MacDonald et al. 1988; Mead et al. 1997; Slutsker et al. 1998; Kassenborg et al. 2001). The 

etiologic fraction estimates for these studies were 17% (MacDonald et al. 1988), 26% (Mead et 

al. 1997), and 37% (Slutsker et al. 1998), and 7% and 8% for ground beef eaten away from home 

and at home, respectively (Kassenborg et al. 2001). The etiologic fractions of ground beef eaten 

at home or away from home were averaged to provide a single estimate. 

These six estimates of the etiologic fraction, two from outbreak data and four from casecontrol studies, were input to a discrete distribution. Each of the six values were equally likely to 

be chosen during model simulation. During a given iteration, one of these six values was drawn 

at random. The etiologic fraction value drawn for a given iteration was multiplied by the 

estimated total number of cases for that iteration to arrive at the number of cases attributable to 

ground beef exposure. This process was repeated for the specified number of iterations during 

Monte Carlo simulation, producing a distribution of possible values for the annual number of 

cases attributable to ground beef. 

Using the inputs described above, Monte Carlo modeling resulted in a median of 19,000 

cases of symptomatic E. coli O157:H7 infection due to contaminated ground beef exposure 

(Table 4-4). However, uncertainty about the total number of cases implies that there may be 

fewer than 5,300 cases (2.5th percentile) or more than 45,000 cases (97.5th percentile) per year 

(Figure 4-2). This uncertainty distribution is used to develop the E. coli O157:H7 dose-response 

function. The median number of cases due to ground beef is 20.2% of the estimated median 

number of cases (94,000) due to all exposures. 

DERIVING THE DOSE-RESPONSE FUNCTION FOR E. COLI O157:H7 

The E. coli O157:H7 dose-response function was derived using information from three sources: 

(1) the estimated annual number of symptomatic E. coli O157:H7 infections due to ground beef 

exposure, (2) the estimated number of contaminated ground beef servings from the exposure 

assessment, and (3) the lower and upper bound dose-response curves derived using surrogate 

pathogens. 

This section begins with a description of the beta-Poisson function used to fit dose-response 

data, followed by a description of how the lower and upper bound dose-response curves were 

developed from foodborne pathogens other than E. coli O157:H7 (surrogates). Then, the process 

for developing the dose-response function for E. coli O157:H7 in ground beef is described. The 

chapter ends with a discussion of the uncertainty about the estimated number of E. coli O157:H7 

infections and contaminated servings. 

September 7, 2001 113 
4. Hazard Characterization 

Beta-Poisson Function 

A beta-Poisson function was chosen to perform the dose-response analysis (Powell et al. 2000). 

This functional form assumes that a single organism is capable of infecting and inciting illness in 

an individual and that organisms operate independently within the host. Such assumptions are 

considered biologically plausible and defensible and can be used to derive a family of doseresponse functions that include the beta-Poisson (WHO/FAO 2000; Buchanan et al. 2000; Haas 

et al. 1999). 

Equation 4.1 is the beta-Poisson model, which predicts the probability of illness given a dose 

pi = 1 – (1 + d/β)

-α

 (4.1) 

where 

pi = probability of illness, 

α = alpha parameter, 

d = dose of pathogen, 

β = beta parameter = N50/(2^[1/α] – 1), and 

N50 = dose necessary to cause illness in 50% of those exposed. 

The alpha and beta parameters needed in the beta-Poisson model are estimated by 

Equation 4.2, which is the maximum likelihood estimation routine developed by Regli et al. 

(1991). These estimates were obtained using the add-on program Solver, within Excel®. To 

briefly describe this process, Equation 4.2 is developed using an Excel spreadsheet, and the alpha 

and beta parameters are varied until Y is minimized. This process is performed separately for 

EPEC and S. dysenteriae data (described below): 

 Y (minimized) = 2Σ{Pi * ln(pi/poi) + (Ti – Pi) * ln[(1 – pi)/(1 – poi)]} (4.2) 

Pi is the observed number of positive responses at the ith dose, poi is the observed proportion 

of response at the ith dose, Ti is the total number of subjects in the ith dose group, and pi is the 

response estimated by the beta-Poisson function at the ith dose. 

The output of these beta-Poisson models is the estimated proportion of persons expected to 

experience illness given a dose. The proportion of persons expected to fall ill at a given dose 

multiplied by the number of servings containing that dose, as estimated by the exposure 

assessment portion of the model, results in an estimate of the number of persons expected to 

become ill during a year. 

Developing Upper and Lower Boundaries to the E. coli O157:H7 Dose-Response Function 

No human clinical trial data are available for E. coli O157:H7, but they are available for a 

number of pathogens that can be used as surrogates (see Appendix B). These surrogates are used 

to form upper and lower boundaries between which the E. coli O157:H7 dose-response function 

is assumed to fit. This method is termed the envelope method because these upper and lower 

boundaries envelop the E. coli O157:H7 dose-response function (Vose 1996, p. 202). Therefore, 

the upper and lower boundaries describe the extent of uncertainty about the true E. coli O157:H7 

dose-response. 

September 7, 2001 114 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Several Shigella and other E. coli species were considered as possible surrogates. In 

considering a species to use as a surrogate, a number of factors were evaluated, including 

availability of data, genetic relatedness, and similarities in transmission, infectivity, and 

pathogenicity. Other risk assessments of E. coli O157:H7 have used Shigella as a surrogate 

pathogen (Cassin et al. 1998; Marks et al. 1998). 

E. coli O157:H7 may be most similar to Shigella spp. with regard to transmission and 

infectivity; however, Shigella spp. are invasive pathogens that multiply within host epithelial 

cells, whereas E. coli O157:H7 does not. Both are transmitted by food, although humans are the 

reservoir of Shigella spp. contamination of food and water. The probability of infection with low 

doses of Shigella spp. is thought to be high. There are four species of Shigella spp.: S. sonnei, S. 

flexneri, S. boydii, and S. dysenteriae. A clinical experiment in human volunteers has been 

conducted using S. sonnei; however, this trial used only one dose of pathogen. Without multiple 

data points in the form of administered dose levels, a curve cannot be fitted to generate 

parameters for the dose-response function; therefore, S. sonnei was not used as a surrogate. A 

substantial amount of human experimental data are available for one strain of S. flexneri; 

however, this organism does not produce Shiga toxins and thus was not chosen as a surrogate. 

S. dysenteriae was selected as an upper bound to the E. coli O157:H7 dose-response function 

based on the assumption that E. coli O157:H7 is unlikely to be more pathogenic than this 

invasive Shigella species. Both S. dysenteriae type 1 and E. coli O157:H7 strains produce Shiga 

toxins, a virulence factor that appears to increase the severity but not necessarily the probability 

or frequency of illness. Similar to E. coli O157:H7, S. dysenteriae has a high probability of 

illness associated with low doses; both organisms cause hemolytic uremic syndrome (HUS). 

The data for S. dysenteriae (Table 4-5) include dose groups of 4, 6, or 10 volunteers 

administered four-dose levels from 10 to 10,000 pathogen cells (Levine et al. 1973). These trials 

found a generally increasing proportion of symptomatic infection as the dose was increased, with 

10% of persons exposed at the lowest doses and 83% of those exposed at the highest doses 

developing clinical symptoms. 

Another surrogate, enteropathogenic E. coli (EPEC), was chosen to represent the lower 

bound of an E. coli O157:H7 dose-response function, based on the assumption that E. coli

O157:H7 is unlikely to be less pathogenic than the EPEC. EPEC and E. coli O157:H7 have 

similar mechanisms of transmission, that is, by food, water, and person-to-person contact; 

however, unlike E. coli O157:H7, EPEC is principally a disease of children younger than 1 year 

of age and generally requires large doses (e.g., 100 million organisms) before a substantial 

probability of illness is observed. A substantial amount of data were available from human 

clinical trials for EPEC (Levine et al. 1978; Bieber et al. 1998). Therefore, three virulent EPEC 

strains were selected as surrogates. The data for EPECs (Table 4-6) include dose groups of two, 

four, five, or six volunteers administered six-dose levels from 106

 to 1010 pathogen cells. In some 

trials, no one developed symptomatic infection at lower doses; all persons developed 

symptomatic infection at higher doses. 

The dose and response information found in Tables 4-5 and 4-6 was used in Equations 4.1 

and 4.2. Dose-response calculations were performed separately for each of the two surrogate 

organisms. 

The estimated lower bound dose-response generated using EPEC clinical trial data and the 

estimated upper bound dose-response generated using Shigella dysenteriae data are illustrated in 

Figure 4-3. The estimated alpha and beta parameters are shown in Table 4-7. 

September 7, 2001 115 
4. Hazard Characterization 

TABLE 4-5 Data from Human Volunteers Administered Two Strains of Shigella dysenteriae 

Shigella 

Dysenteriae 

Strain 

Dose of 

Pathogen 

Number of Persons 

Developing 

Symptoms 

Total Persons 

Exposed 

Proportion of 

Persons Developing 

Symptoms 

M 131 10 1 10 0.10 

A-1 200 1 4 0.25 

M 131 200 2 4 0.50 

M 131 2,000 7 10 0.70 

A-1 10,000 2 6 0.33 

M 131 10,000 5 6 0.83 

Source: Levine et al. 1973. 

TABLE 4-6 Data from Human Volunteers Administered Four Strains of Enteropathogenic 

Escherichia coli (EPEC) 

EPEC Strain Dose of Pathogen 

Number of Persons 

Developing 

Symptoms 

Total 

Persons 

Exposed 

Proportion of Persons 

Developing 

Symptoms 

O128 1,000,000 0 5 0.00 

O127 1,000,000 0 4 0.00 

O142 1,000,000 1 5 0.20 

O128 100,000,000 0 5 0.00 

O142 100,000,000 1 5 0.20 

B-171-8 500,000,000 3 5 0.6 

B-171-8 2,500,000,000 6 6 1 

O128 10,000,000,000 0 5 0.00 

O127 10,000,000,000 3 5 0.60 

O142 10,000,000,000 5 5 1.00 

B-171-8 20,000,000,000 2 2 1 

Sources: Bieber et al. 1998; Levine et al. 1978. 

September 7, 2001 116 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

1

10

100

1,000

10,000

100,000

1,000,000

10,000,000

100,000,000

1,000,000,000

10,000,000...

Dose per Serving

Probability of Illness

Shigella dysenteriae EPEC

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

FIGURE 4-3 Dose-response curves for Shigella dysenteriae (Shig dys cumulative distribution 

function [cdf]) and enteropathogenic E. coli (EPEC cdf). The Shigella dysenteriae curve serves 

as the upper bound and EPEC as the lower bound to a dose-response curve for E. coli O157:H7. 

TABLE 4-7 Alpha and Beta Parameters for the Upper and Lower Bound Beta-Poisson Models, 

Shigella dysenteriae and Enteropathogenic Escherichia coli (EPEC) 

Surrogate Organism Alpha Beta 

S. dysenteriae 0.157 9.17 

EPEC 0.221 3,110,000 

For the EPEC dose-response curve, the implied dose at which 50% of persons exposed will 

become ill (N50) is 68 million organisms. E. coli O157:H7 is highly unlikely to have an N50 that 

is this high. For the Shigella dysenteriae dose-response curve, the N50 is 740 organisms. By using 

this pathogen to represent an upper bound, it is assumed that E. coli O157:H7 is unlikely to have 

an N50 lower than 740 organisms. 

Process for Developing the E. coli O157:H7 Dose-Response Function 

A beta-Poisson dose-response function for E. coli O157:H7 is derived from the distribution of E. 

coli O157:H7 illnesses attributable to ground beef (response) and the distribution of the number 

of E. coli O157:H7 organisms in consumed ground beef servings (dose) (Powell et al. 2000). The 

derived E. coli O157:H7 dose-response function is constrained to lie between beta-Poisson 

functions fit to Shigella dysenteriae and EPEC data. The derivation can be simply represented as 

× = TCDREx (4.3) 

September 7, 2001 117 
4. Hazard Characterization 

where Ex represents the exposure distribution, DR is the dose-response function, and TC is the 

total cases per year. If dose-response data for E. coli O157:H7 were available, a dose-response 

function could be fit to these data and Equation 4.3 could be directly solved for total cases. In the 

absence of dose and response data, available estimates for the total number of cases can be used 

with the model’s estimates for the exposure distribution to determine the dose-response using 

Equation 4.3. 

Uncertainty in Cases and Exposure Distribution 

Uncertainty about the exposure distribution predicted by this model was illustrated as an output 

from Chapter 3. Uncertainty about the number of E. coli O157:H7 cases associated with ground 

beef was discussed above. These uncertainties are integrated in deriving the dose-response 

function for E. coli O157:H7 (Figure 4-4). 

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Dose

P ro bab ility o f illn ess 0 .0 0000 000 1

0.00000001

0.0000001

0.000001

0.0000 1

0.0001

0.001

0 .0 1

0.1

1

0

10

316

10,000

316,228

10,000 ,000

316,227,766

10,00 0,000,0 00

Num ber of E. c oli O 1 5 7 :H 7 in 

p ost cooked grou nd be e f 

s e r vin gs in low pr e va le n ce s e a s o n

F r eq u en c y

0.000000001

0.00000001

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0

10

316

10,000

316,228

10 ,0 00,00 0

316,227,766

10,00 0,000 ,0 00

Num ber of E. c o li O 1 5 7 :H 7 in 

p ost c ook e d grou nd bee f 

s e r vings in high pr e va le nc e s e a s on

F req uen c y

0.00

0.05

0.10

0.15

0.20

0.25

0

5,000

10,00015 ,0 0 020,00025,00030,0003 5 ,0 0040,00045,00050 ,00 055,00060,00065,00070 ,00 0

H uman cases of E. coli O 157:H 7

Probability

Exposure

distribution

Annual cases

Derived dose-response

Probability of Illness

Dose

FIGURE 4-4 Illustration of process by which an E. coli O157:H7 dose-response function is 

derived from uncertain exposure distributions and uncertain total human cases. 

Because the exposure assessment estimates exposure distributions for high and low 

prevalence seasons but the estimated total cases distribution reflects an annual number, the two 

seasonal exposure distributions must be combined to represent exposures in servings of ground 

beef across a full year. This annual exposure distribution is estimated by weighting each seasonal 

distribution by its number of months. Therefore, the high prevalence season is given a weight of 

4 ÷ 12 (for June through September) and the low prevalence season is given a weight of 8 ÷ 12.

For a given draw from the uncertain exposure distributions and the total cases distribution, a 

best-fitting beta-Poisson function is determined by varying the alpha and beta parameters of that 

function. These parameters are constrained, however, by the lower and upper bound parameters 

estimated for Shigella dysenteriae and EPEC. The set of parameter values that result in 

predicting the specified total cases of E. coli O157:H7 illness given the exposure distribution is 

September 7, 2001 118 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

saved, and the algorithm is repeated for another draw from the exposure and total cases 

distributions. With this method, the uncertainty regarding exposures and total cases per year is 

fully integrated into the estimate of a dose-response function. 

Figure 4-5 shows the resulting uncertainty about the derived E. coli O157:H7 dose-response 

function. Each curve shows progressively higher percentiles of the derived dose-response 

function extending from the 5th to the 95th percentiles. The median dose-response function in 

this range is assumed to be the best estimate. 

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 1 2 3 4 5 6 7 8 9 10 11

Log Dose

Probability of Illness

FIGURE 4-5 Derived dose-response curves from combining output of hazard characterization and 

exposure assessment. Curves represent percentiles of uncertainty distribution (ranging from 5th 

to 95th percentile) about the E. coli O157:H7 dose-response function. The thick line is the 

median dose-response curve. The dashed lines are boundary dose-response functions fit to

Shigella dysenteriae and enteropathogenic E. coli (EPEC). The rectangle in the lower left 

represents the combined range of uncertainty of the dose and response derived from the 1994 

outbreak in the northwestern United States. Source: Bell et al. 1994. 

Uncertainty about the E. coli O157:H7 dose-response function extends almost across the full 

range enveloped by the lower and upper bound curves. Nevertheless, this uncertainty suggests 

more confidence in dose-response functions that lie closer to the Shigella dysenteriae boundary 

than in those that lie closer to the EPEC boundary. Therefore, the results of this derivation 

suggest that the dose-response function for E. coli O157:H7 more closely approximates that 

estimated for Shigella dysenteriae than for EPEC. 

The derived dose-response function for E. coli O157:H7 also shows consistency with 

information obtained from a ground beef-associated outbreak in the northwestern United States. 

Uncertainty about the average exposure dose and attack rate in this outbreak is shown in 

Figure 4-5. The majority of the percentiles for the derived dose-response function fit within the 

outbreak’s uncertainty range. However, even the boundary formed by the Shigella dysenteriae

dose-response function fails to explain all of the outbreak’s uncertainty. 

September 7, 2001 119 
4. Hazard Characterization 

Effect of Uncertainty in Exposures and Cases 

Although the derivation of the E. coli O157:H7 dose-response function includes the uncertainty 

from the exposure assessment and the total number of cases occurring per year, it does not 

suggest the relative contribution of each source of uncertainty to the overall uncertainty in the 

dose-response function. To examine this relative effect, the exposure distribution and the total 

cases were considered fixed, in turn, and the uncertainty about the other was used to derive the 

dose-response function. 

Figure 4-6 shows dose-response functions estimated by setting the exposure distribution at its 

median but using the 5th and 95th percentiles from the total cases per year distribution. The N50

for the dose-response curve fit to the 5th percentile of cases is about 3.5 logs. In other words, the 

dose-response function predicts that 50% of those exposed to an average dose of 3.5 logs of E. 

coli O157:H7 will become ill. The N50 for the dose-response curve fit to the 95th percentile of 

cases is about 6.5 logs. This range in uncertainty is slightly less than the range shown in 

Figure 4-5. It is also reasonably symmetrical about the median curve shown in Figure 4-5. 

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 1 2 3 4 5 6 7 8 9 10 11

Log Dose

Probability of Illness

FIGURE 4-6 Dose-response curves that result from setting exposure distribution at the median 

and using 5th and 95th percentiles (grey lines) of cases predicted from hazard characterization. 

The solid dark line is the median dose-response function including uncertainty about exposures 

and cases (Figure 4-5). The dashed lines are boundary dose-response functions fit to Shigella 

dysenteriae and enteropathogenic E. coli (EPEC). 

Figure 4-7 shows dose-response functions estimated by setting the total number of cases at 

the median but using the 5th and 95th percentiles from the exposure distribution. This figure is 

generally similar to Figure 4-6. In Figure 4-7, the N50 for the dose-response curve fit to the 5th 

percentile of the exposure distribution is about 3 logs. The N50 for the dose-response curve fit to 

the 95th percentile of the exposure distribution is about 6 logs. This range is shifted to the left 

relative to the range shown for Figure 4-6. This shift implies that fixing the number of cases at its 

median value would move estimated dose-response functions closer to the Shigella dysenteriae

curve than fixing the exposure distribution at its median (as done in Figure 4-6). 

September 7, 2001 120 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 1 2 3 4 5 6 7 8 9 10 11

Log Dose

Probability of Illness

FIGURE 4-7 Dose-response curves that result from setting total E. coli O157:H7 cases per year at 

the median and using 5th and 95th percentiles (grey lines) of the exposure distribution predicted 

from the exposure assessment. The solid dark line is the median dose-response function 

including uncertainty about exposures and cases (Figure 4-5). The dashed lines are boundary 

dose-response functions fit to Shigella dysenteriae and enteropathogenic E. coli (EPEC). 

The implication of this analysis is that neither uncertainty about the exposure distribution nor 

uncertainty about the total number of cases dominates the uncertainty about the E. coli O157:H7 

dose-response function. Instead, both sources of uncertainty contribute equally to the overall 

uncertainty. 

ESTIMATING SEVERE CLINICAL OUTCOMES DUE TO 

E. COLI O157:H7 INFECTION 

The estimates generated by this portion of the model are not used in developing a dose-response 

curve for E. coli O157:H7. Instead, they describe the consequences of symptomatic infection. 

Given the lack of dose-response data, the probability of various clinical outcomes is assumed to 

be independent of the dose of E. coli O157:H7 consumed. Estimating the clinical outcomes of 

symptomatic infection is essential for future cost-benefit analyses of intervention options. 

Estimates are provided for severe illnesses due to ground beef exposure and due to all exposures. 

The number of persons who experienced hospitalization, HUS, thrombotic thrombocytopenic 

purpura (TTP), or death was estimated using data from 203 outbreaks that occurred between 

1982 and 1998 (CDC unpublished data). A total of 4,478 cases occurred during the 203 

outbreaks; of these, 968 (21.6%) cases resulted in hospitalization, 228 (5.1%) cases progressed to 

HUS or TTP, and 28 (0.6%) cases resulted in death (Table 4-5). Only summary data were 

available for these outbreaks, preventing calculation of conditional probabilities. Therefore, for 

the purposes of modeling, it is assumed that HUS or TTP cases occur only among hospitalized 

patients and that deaths occur only among those patients with HUS or TTP. The data from these 

outbreaks were used as inputs to beta distributions and simulated. 

September 7, 2001 121 
4. Hazard Characterization 

The data inputs estimating the number of hospitalizations were s=968 and n=4,478; the 

number of cases with HUS or TTP, s=228 and n=968; and the number of deaths, s=28 and 

n=228. Recall that s is the number of events of interest and n is the total number observed. 

Applying these proportions to all cases assumes that pathogenicity is similar among strains of E. 

coli O157:H7 and that outcome is independent of dose. 

The median annual estimated number of patients with bloody diarrhea who sought medical 

care was 9,400 (Table 4-8); of these, 2,000 (21.3%) persons were hospitalized. Of the 

hospitalized patients, the model estimates that a median of 460 (23.0%) patients developed HUS 

or TTP and that 50 (10.9%) of these patients died. These estimates are similar to the estimated 

2,168 hospitalizations and 52 deaths annually due to E. coli O157:H7 infection reported by Mead 

et al. (1999). 

The proportion of cases with severe clinical outcomes attributable to ground beef exposure is 

also presented in Table 4-8. The model estimates that a median of 1,800 severe cases (patients 

with bloody diarrhea who sought medical care) are due to ground beef exposure annually. Of 

these 1,800 cases, the model estimates that 400 (22.2%) will be hospitalized and that, of these, 

90 (22.5%) will develop HUS or TTP and 10 (11.1%) HUS/TTP patients will die. 

TABLE 4-8 Number of Severe Outcomes Due to E. coli O157:H7 Infection and the Distributions 

and Inputs Used to Calculate These Outcomes (6,000 Iterations) 

Parameter Distribution 

Proportion of cases hospitalized Beta (968 + 1, 4,478 – 968 + 1)a

Proportion of hospitalized cases progressing to 

HUS/TTP 

Beta (228 + 1, 968 – 228 + 1) 

Proportion of HUS/TTP cases resulting in death Beta (28 + 1, 228 – 28 + 1) 

Severe Health Outcomes Median 2.5th and 97.5th Percentiles 

All exposures 

Severe (patient with bloody diarrhea, seeks 

medical care) 

9,400 6,300 and 12,000 

Hospitalized 2,000 1,300 and 2,600 

HUS/TTP 460 300 and 630 

Deaths 50 30 and 100 

Ground beef exposures 

Severe (patient with bloody diarrhea, seeks 

medical care) 

1,800 1,000 and 4,100 

Hospitalized 400 100 and 900 

HUS/TTP 90 30 and 210 

Deaths 10 1 and 30 

Note: Number of cases has been rounded to two significant digits (one significant digit for numbers less than 100). 

HUS = hemolytic uremic syndrome; TTP = thrombotic thrombocytopenic purpura. 

a

The input format for a beta distribution is (s+1,n–s+1), where s=the number of events of interest and n=total 

number of events measured (e.g., the number of cases with bloody diarrhea [s] and the number of all cases of 

symptomatic E. coli O157:H7 infection [n]). 

September 7, 2001 122 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

SENSITIVE SUBPOPULATIONS 

Certain age groups have a higher reported incidence of E. coli O157:H7 infection. Surveillance 

from FoodNet sites in 1999 shows that 1- to 9-year-olds had the highest incidence among all age 

groups (Figure 4-8, CDC 2000). Nationwide in 1998, 1- to 4-year-olds had the highest incidence, 

at 4.57 reported cases per 100,000 population (CDC 1999). Young children also appear to be 

more susceptible to developing HUS (see Chapter 2). 

0

1

2

3

4

5

6

Age Group

Cases per 100,000 Population

<1 1 to 9 10 to 19 20 to 29 30 to 39 40 to 49 50 to 59 >60

FIGURE 4-8 Number of reported cases of E. coli O157:H7 infection due to all routes of 

transmission, by age group, FoodNet sites, 1999. 

The reason why children have the highest reported incidence of E. coli O157:H7 infection is 

not known. Relative to adults, children may be more likely to receive medical care during an 

episode of diarrhea or bloody diarrhea and be more likely to be tested for E. coli O157:H7. They 

may also have better access to health care, a higher likelihood of being reported to public health 

officials, more opportunities for exposure, increased susceptibility to infection, or some 

combination of all of these factors. Children are more likely than adults to develop HUS as a 

sequela of infection with E. coli O157:H7. Kidney damage that occurs during HUS is a result of 

Shiga toxin binding to specific receptors present on kidney cells. These receptors appear to be 

present in the kidneys of children but not adults (Lingwood et al. 1998). 

Given that children consistently have the highest rate of E. coli O157:H7 infection relative to 

older age groups, it would seem reasonable to conduct a separate dose-response analysis of 

children. However, data on the proportion of E. coli O157:H7 infections due to ground beef, by 

age, are scarce. Also, the epidemiology of E. coli O157:H7 in children is complex, as described 

above. It is not known whether the high incidence in children is due to more children having the 

disease relative to adults or to artifacts of the health care and public health reporting systems, and 

little or no data are available to answer these questions. Therefore, this risk assessment does not

include a separate dose-response analysis for children. 

VALIDATION OF THE E. COLI O157:H7 DOSE-RESPONSE FUNCTION USING 

OUTBREAK DATA 

An epidemiologic investigation traced a 1992 to 1993 outbreak of E. coli O157:H7 to 

consumption of hamburgers at a chain of fast-food restaurants (Chain A) in the Pacific 

September 7, 2001 123 
4. Hazard Characterization 

Northwest (Bell et al. 1994). Data from this investigation were used to develop a separate doseresponse function to validate the dose-response function derived separately in this risk 

assessment. The data were not used directly in this risk assessment because the contamination 

levels of E. coli O157:H7 in the ground beef servings were not directly correlated with the 

severity of illness (i.e., the number of E. coli O157:H7 organisms consumed by each human case 

was not known). 

A total of 501 culture-confirmed cases were documented to occur during this outbreak, 

including 398 (79.4%) primary cases, 48 (9.6%) secondary cases, and 55 (11.0%) cases that 

could not be classified as either primary or secondary. Of the 398 patients with primary disease 

in Washington state, 374 (93.9%) had eaten at Chain A in the previous 10 days. A total of 344 

(92.0%) of 374 primary cases who ate at Chain A reported eating a regular (45-gram) 

hamburger. The median age of cases was 8 years, ranging from 4 months to 88 years. Forty-five 

(9.0%) patients developed HUS and 3 died of complications of HUS. The median age of HUS 

patients was 5 years, ranging from 1 to 68 years. 

In response to the outbreak, approximately 255,000 45-gram hamburger patties were recalled 

from Chain A restaurants in Washington (Bell et al. 1994). These patties had been produced on 

November 19, 1992, at a processing plant in California. The recalled patties represented 43% of 

all regular hamburgers produced for Chain A at the California plant on that day, for a total 

production of 593,023 patties. The processing plant had sent 62% of that day’s production 

(367,673 patties) to Washington. Therefore, the number of hamburger patties sold and consumed 

was equal to the number sent to Washington minus the number recalled (367,673 – 255,000 

patties), or 112,673 patties. 

The number of E. coli O157:H7 organisms per serving that occurred during this outbreak was 

quantified in six raw ground beef samples from implicated lots (Marks et al. 1998). The samples 

were enumerated for E. coli O157:H7 by the most probable number (MPN) method and were 

found to contain 0.3, 0.9, 1.5, 2.8, 4.3, and 15 colony-forming units per gram (CFU/g), 

respectively (Johnson et al. 1995; Tuttle et al. 1999). The distribution for the concentration of E. 

coli O157:H7 in the raw ground beef, d, was modeled by assuming that the quantity 

 {[ln(d)] – m}/[s(1/n)

1⁄2] ~ tn–1

is distributed as a t-distribution with n–1 degrees of freedom, where m is the mean of the n=6 log 

densities and s is the standard deviation of the log densities. Multiplying the distribution for d

(CFU/g) by a serving size of 45 grams yields an estimated median per serving load of 96 CFU of 

E. coli O157:H7 before cooking (90% confidence interval, 5 to 1,844 CFU). This estimate is 

similar to the findings of Tuttle et al. (1999), who calculated a median of 67.5 organisms per raw 

ground beef patty (range, 13.5 to 675 organisms per patty). 

To determine the effect of cooking on the final number of E. coli O157:H7 organisms, Bell et 

al. (1994) reported cooking 16 regular hamburgers according to Chain A’s routine practices. 

After the frozen patties were cooked for 1 minute on each side on a 191°F grill, all of them had 

at least one internal temperature measurement below 68.3°C (155.0°F) (range, 41.7 to 81.1°C 

[107.1 to 177.98°F]). Ten had a measurement below 60.0°C (140°F). The minimum internal 

cooking temperature was modeled as a custom cumulative distribution with a minimum value of 

37.8o

C (100°F), a 6.25th percentile of 41.7oC (107.1°F), a 62.5th percentile of 60.0°C (140.0°F), 

and a maximum of 68.3o

C (155.0°F). 

September 7, 2001 124 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Based on a study by Juneja et al. (1997), Marks et al. (1998) predicted the log reduction of E. 

coli O157:H7 in hamburgers due to cooking to be 

 log10 (Nf/N0) = 13.93 – 0.12*T

where N0 is the number of organisms before cooking, Nf is the number of organisms after 

cooking, and T is cooking temperature (°F). Combining the distributions for the number of 

organisms in a raw patty prior to cooking with the cooking temperatures described above, this 

equation suggests that cooking rendered 50% of the hamburger patties free of E. coli O157:H7. 

From the estimate described above, 112,674 patties were purchased at Chain A restaurants; 

therefore, half of these, or 56,337 patties, were estimated to still be contaminated after cooking. 

The simulated distribution for the amount of viable E. coli O157:H7 per serving that remained 

after cooking has a median value of 23 CFU per serving (1 and 926 CFU per serving, 2.5th and 

97.5th percentiles, respectively). This simulated estimated number of organisms is in agreement 

with a study of 76 recalled ground beef patties from this outbreak (Tuttle et al. 1999), where the 

median most probable number of organisms was determined to be 67.5 per uncooked patty 

(range, 13.5 to 675). 

At this ingested dose, the uncertainty about the attack rate is estimated using a beta 

distribution. Inputs to this distribution were the number of primary cases (374) that had eaten at 

Chain A in the 10 days prior to illness, adjusted for underdiagnosis and underreporting (the 

input, s), and the number of patties contaminated with at least one E. coli O157:H7 organism 

after cooking (n=56,337). To adjust for underdiagnosis and underreporting, the number of 

primary cases that had eaten at Chain A was multiplied by a factor of 1 to 20 using a uniform 

probability distribution. A uniform distribution randomly chooses a value in the specified range 

during a given iteration. Therefore, 374 was multiplied by the randomly drawn value between 1 

and 20 during each iteration of the model, resulting in a list of the possible number of actual 

cases that had occurred during the outbreak. 

Modeling the underreporting factor in this manner accounts for uncertainty in the degree of 

underreporting that had occurred during this outbreak. A factor of 1 indicates no underreporting 

occurred; a factor of 20 indicates that 20 cases occurred for each reported case and is the 

underreporting factor used in Mead et al. (1999) for E. coli O157:H7. Because of the extensive 

publicity about this outbreak, the degree of underreporting is likely to be somewhat less than the 

estimated national average of 20. 

A Monte Carlo simulation of 100,000 iterations resulted in a median value of 70 cases per 

1,000 contaminated servings consumed (10 and 130 cases per 1,000 servings, 2.5th and 97.5th 

percentiles, respectively) at a median of 23 CFU per serving. For the outbreak, the probability of 

illness given a dose is consistent with the E. coli O157:H7 dose-response curve in Figure 4-5. In 

this figure, the outbreak information is represented by the rectangle in the lower left corner of the 

graph. 

REFERENCES 

Bell, B.P., M. Goldoft, P.M. Griffin, M.A. Davis, D.C. Gordon, P.I. Tarr, C.A. Bartleson, J.H. 

Lewis, T.J. Barrett, J.G. Wells, R. Baron, and J. Kobayashi. 1994. A multistate outbreak of 

Escherichia coli O157:H7-associated bloody diarrhea and hemolytic uremic syndrome from 

hamburgers: The Washington experience. JAMA 272(17):1349-1353. 

September 7, 2001 125 
4. Hazard Characterization 

Bieber, D., S.W. Ramer, C.-Y. Wu, W.J. Murray, T. Tobe, R. Fernandez, and G.K. Schoolnik. 

1998. Type IV pili, transient bacterial aggregates, and virulence of enteropathogenic 

Escherichia coli. Science 280:2114-2118. 

Buchanan, R., J. Smith, and W. Long. 2000. Microbial risk assessment: dose-response relations 

and risk characterization. Int J Food Microbiol 58:159-172. 

Cassin, M.H., A.M. Lammerding, E.C.D. Todd, W. Ross, and R.S. McColl. 1998. Quantitative 

risk assessment for Escherichia coli O157:H7 in ground beef hamburgers. Int J Food 

Microbiol 41:21-44. 

Centers for Disease Control and Prevention (CDC). 1997. Foodborne diseases active surveillance 

network, 1996. MMWR 46(12):258-261. 

Centers for Disease Control and Prevention (CDC). 1998. FoodNet Surveillance Report for 

1997. Final Report. (Available at: http://www.cdc.gov/foodnet). 

Centers for Disease Control and Prevention (CDC). 1999. Summary of notifiable diseases, 

United States, 1998. MMWR 47(53):1-94. 

Centers for Disease Control and Prevention (CDC). 2000. FoodNet Surveillance Report for 

1999. Final Report. (Available at: http://www.cdc.gov/foodnet). 

Cieslak, P.R., S.J. Noble, D.J. Maxson, L.C. Empey, O. Ravenholt, G. Legarza, J. Tuttle, M.P. 

Doyle, T.J. Barrett, J.G. Wells, A.M. McNamara, and P.M. Griffin. 1997. Hamburgerassociated Escherichia coli O157:H7 infection in Las Vegas: A hidden epidemic. Am J 

Public Health 87(2):176-180. 

Haas, C., J. Rose, and J. Gerba. 1999. Quantitative Microbial Risk Assessment. New York: John 

Wiley & Sons. 

Hedberg, C., F. Angulo, J. Townes, J. Hadler, D. Vugia, and J. Garley. 1997. Differences in 

Escherichia coli O157:H7 annual incidence among FoodNet active surveillance sites. 5th 

International VTEC Producing Escherichia coli Meeting. Baltimore, MD, July. 

Johnson, J.L., B.E. Rose, A.K. Sharar, G.M. Ransom, C.P. Lattuada, and A.M. McNamara. 

1995. Methods used for detection and recovery of Escherichia coli O157:H7 associated with 

a food-borne disease outbreak. J Food Prot 58(6):597-603. 

Juneja, V.K., O.P. Snyder Jr., A.C. Williams, and B.S. Marmer. 1997. Thermal destruction of 

Escherichia coli O157:H7 in hamburger. J Food Prot 60:1163-1166. 

Kassenborg, H., C. Hedberg, M. Hoekstra, M.C. Evans, A.E. Chin, R. Marcus, D. Vugia, 

K. Smith, S. Desai, L. Slutsker, and P. Griffin. 2001. Farm visits and undercooked 

hamburgers as major risk factors for sporadic Escherichia coli O157:H7 infections—data 

from a case-control study in five FoodNet sites. Manuscript in preparation. 

Levine, M.M., H.L. Dupont, S.B. Formal, R.B. Hornick, A. Takeuchi, E.J. Gangarosa, M.J. 

Snyder, and J.P. Libonati. 1973. Pathogenesis of Shigella dysenteriae 1 (Shiga) dysentery. 

J Infect Dis 127(3):261-270. 

Levine, M.M., E.J. Bergquist, D.R. Nalin, D.H. Waterman, R.B. Hornick, C.R. Young, and 

S. Sotman. 1978. Escherichia coli strains that cause diarrhea but do not produce heat-labile 

or heat-stable enterotoxins and are non-invasive. Lancet 1(8074):1119. 

Lingwood, C.A., M. Mylvaganam, S. Arab, A.A. Khine, G. Magnusson, S. Grinstein, and P.-G. 

Nyholm. 1998. Shiga toxin (verotoxin) binding to its receptor glycolipid. Pp. 92-108 in 

Escherichia coli O157:H7 and Other Shiga Toxin-Producing E. coli Strains, J.B. Kaper and 

A.D. O’Brien, eds. Washington, DC: ASM Press. 

MacDonald, K.W., M.J. O’Leary, M.L. Cohen, P. Norris, J.G. Wells, E. Noll, J.M. Kobayashi, 

and P.A. Blake. 1988. Escherichia coli O157:H7, an emerging gastrointestinal pathogen: 

results of a one-year, prospective, population-based study. JAMA 259(24):3567-3570. 

September 7, 2001 126 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Marks, H.M., M.E. Coleman, C.T. Lin, and T. Roberts. 1998. Topics in microbial risk 

assessment: Dynamic flow tree process. Risk Anal 18(3):309-328. 

Mead, P.S., L. Finelli, M.A. Lambert-Fair, D. Champ, J. Townes, L. Hutwagner, T. Barrett, and 

K. Spitalny. 1997. Risk factors for sporadic infection with Escherichia coli O157:H7. Arch 

Intern Med 157:204-208. 

Mead, P.S., L. Slutsker, V. Dietz, L.F. McCaig, J.S. Bresee, C. Shapiro, P.M. Griffin, and R.B. 

Tauxe. 1999. Food-related illness and death in the United States. Emerg Infect Dis 5(5):1-33. 

Ostroff, S.M., J.M. Kobayashi, and J.H. Lewis. 1989. Infections with Escherichia coli O157:H7 

in Washington State. JAMA 262(3):355. 

Pai, C.H., J.K. Kelly, and G. Meyers. 1986. Experimental infection of infant rabbits with 

verotoxin-producing Escherichia coli. Infect Immun 51(1):16-23. 

Powell, M., E. Ebel, W. Schlosser, M. Walderhaug, and J. Kause. 2000. Dose-response envelope 

for Escherichia coli O157:H7. Quant Microbiol 2(2):141-163. 

Regli, S., J.B. Rose, C.N. Haas, and C.P. Gerba. 1991. Modeling risk for pathogens in drinking 

water. J Am Water Works Assoc 83(11):76. 

Slutsker, L., A.A. Ries, K.D. Greene, J.G. Wells, L. Hutwagner, and P.M. Griffin for the 

Escherichia coli O157:H7 Study Group. 1997. Escherichia coli O157:H7 diarrhea in the 

United States: Clinical and epidemiologic features. Ann Intern Med 126:505-513. 

Slutsker, L., A.A. Ries, K. Maloney, J.G. Wells, K.D. Greene, and P.M. Griffin. 1998. A 

nationwide case-control study of Escherichia coli O157:H7 infection in the United States. J 

Infect Dis 177:962-966. 

Tuttle, J., T. Gomez, M.P. Doyle, J.G. Wells, T. Zhao, R.V. Tauxe, and P.M. Griffin. 1999. 

Lessons from a large outbreak of Escherichia coli O157:H7 infections: Insights into the 

infectious dose and method of widespread contamination of hamburger patties. Epidemiol 

Infect 122:183-192. 

Vose, D. 1996. Quantitative Risk Analysis: A Guide to Monte Carlo Simulation Modeling. West 

Sussex, England: John Wiley & Sons, Ltd. 

World Health Organization/Food and Agriculture Organization (WHO/FAO). 2000. Guidelines 

on Hazard Characterization for Pathogens in Food and Water. Bilhoven, The Netherlands, 

June 13-18, 2000. 

September 7, 2001 127 

5 

Risk Characterization 

In this chapter, the risk characterization integrates the results of the exposure assessment 

(Chapter 3) with the results of the hazard characterization (Chapter 4) to estimate the risk of 

illness from E. coli O157:H7 in ground beef. The exposure assessment describes the probability 

of exposure to various doses of E. coli O157:H7 (e.g., number of E. coli O157:H7 organisms per 

ground beef serving). The hazard characterization derived a dose-response function to describe 

the probability of illness for these various doses. Characterization of the risk of illness from E. 

coli O157:H7 in ground beef is considered from several perspectives based on the following: 

• Level of risk: individual, community, and population; 

• Duration of exposure: per serving, per annum, and lifetime risk; and 

• Population variability of risk: by season, age, or location. 

This risk characterization also includes an analysis to identify factors (model inputs) that 

influence the occurrence and extent of E. coli O157:H7 contamination in combo bins, grinder 

loads, and ground beef servings and the subsequent risk of illness (model outputs). This type of 

analysis is generally referred to as a sensitivity analysis. Two types of sensitivity analyses are 

used in this risk assessment: (1) correlation analysis and (2) dependency analysis. 

DEFINITION OF KEY TERMS 

The following key terms are used throughout this chapter: 

• Risk is the probability of the occurrence of an adverse outcome (e.g., illness or death) 

resulting from exposure to a hazard. In this risk assessment, risk refers to the probability 

of illness (number and severity) resulting from consuming a single ground beef serving 

contaminated with a specific number of E. coli O157:H7 organisms. 

• Scope of the risk estimate refers to whether we are considering the risk of illness for an 

individual, a community, or an entire population. 

September 7, 2001 129 
5. Risk Characterization 

• “Typical” individual risk refers to the probability of illness for an individual consuming a 

single serving of ground beef. In this risk characterization, the “typical” individual is 

defined as someone who purchases ground beef that is contaminated at the median 

concentration and stores and cooks that product in a way that is consistent with the 

median of the growth and cooking distributions (Table 5-1). This type of analysis does 

not apply to specific individuals. 

• Community risk refers to the probability of illness for an entire community under a given 

exposure scenario. In this risk characterization, the risk is illustrated for a community 

exposed to a single grinder load contaminated with E. coli O157:H7. 

• Population risk refers to the probability of illness from E. coli O157:H7 in ground beef 

across the U.S. population. This type of risk estimate is useful for guiding food safety 

policy decision making. 

• Duration of exposure refers to the length of time (e.g., per serving, per annum, or 

lifetime) for which a risk estimate was assessed. 

• Risk per serving refers to the risk of E. coli O157:H7 illness from consuming a single 

serving of ground beef. 

• Risk per annum refers to the risk of E. coli O157:H7 illness from consuming ground beef 

over the course of a year. 

• Lifetime risk refers to the risk of E. coli O157:H7 illness from consuming ground beef 

over the course of a lifetime. 

• Dose is the number of E. coli O157:H7 organisms in a single serving of ground beef. 

• Population risk by season, age, and location refers to the stratified characterization of the 

risk of illness from E. coli O157:H7 in ground beef to provide further insight regarding 

the public health risks to specific subpopulations (e.g., based on seasonal exposure, age, 

and consumption patterns). 

• Factors are model inputs that influence the prevalence and number of E. coli O157:H7 in 

ground beef or, more generally, influence the overall risk of E. coli O157:H7-related 

illness from ground beef. These model inputs may include one or more of the following: 

production practices, time and temperature controls during processing, storage and 

handling practices for ground beef during retail and preparation, or how thoroughly a 

ground beef serving was cooked. 

• Sensitivity analysis refers to the quantitative process of identifying factors (model inputs) 

in the farm-to-table continuum that contribute to the occurrence of E. coli O157:H7 in 

ground beef or the subsequent risk of illness. 

• Correlation analysis is one type of sensitivity analysis used to identify uncertain factors 

(model inputs) that influence either the occurrence of E. coli O157:H7 in ground beef or 

the subsequent risk of illness (model outputs). This type of sensitivity analysis identifies 

important factors quickly but only works for those that are uncertain. 

• Dependency analysis is another type of sensitivity analysis used to identify factors 

(model inputs) that influence either the occurrence of E. coli O157:H7 in ground beef or 

the subsequent risk of illness (model outputs). This type of sensitivity analysis is resource 

intensive but identifies both uncertain and certain factors (model inputs) in the risk 

assessment model. 

September 7, 2001 130 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

RISK OF ILLNESS FROM E. COLI O157:H7 

The estimated risk of illness from E. coli O157:H7 in ground beef varies depending on the level 

at which the risk estimate is focused—that is, whether one considers the risk of illness for an 

individual consuming a single serving of ground beef; a community of individuals experiencing 

similar exposures to E. coli O157:H7 in ground beef that came, for example, from the same 

grinder load; or the risk of illness across the entire U.S. population. The estimated risk of E. coli

O157:H7 illness also varies depending on the duration of exposure—that is, whether one 

considers the risk of illness on a per serving, per annum, or lifetime basis. To characterize the 

risk of illness from E. coli O157:H7 in ground beef, it is important to clearly define the type of 

risk estimate under consideration (e.g., individual lifetime risk of illness versus a population per 

annum risk of illness). The type of risk estimate developed depends on the problem under 

consideration for which the risk assessment was developed: to estimate the median health risk to 

individuals, better understand an outbreak scenario, or develop food safety policy. Several types 

of risk estimates are considered below. 

Risk of Illness for an Individual 

A “typical” individual’s risk of E. coli O157:H7 illness from ground beef can be calculated from 

point estimates taken from output distributions in the exposure assessment combined with the 

median (50th percentile) E. coli O157:H7 dose-response curve (Table 5-1). Using this approach, 

a “typical” individual’s probability of being exposed to a single E. coli O157:H7 organism in 

ground beef is between 1 in 1,500 (6.9 × 10-4) servings and 1 in 1 million (9.2 × 10-7) servings.1

Using the median dose-response curve for E. coli O157:H7, this equates to a lifetime risk of E. 

coli O157:H7 illness from ground beef for the “typical” individual that is between 1 in 8 million 

servings [(6.9 × 10-4)(1.7 × 10-4) = 1.17 × 10-7] and 1 in 6 billion servings [(9.2 × 10-7)(1.7 × 10-4) 

= 1.56 × 10-10].2 Using similar calculations, the annual “typical” individual’s risk of E. coli

O157:H7 illness from ground beef is between 1 in 600 million servings and 1 in 400 billion 

servings. 

This illustration is for the “typical” individual; it assumes that an individual always purchases 

the median product and always stores and cooks ground beef in accordance with the median of 

the population. If such an individual were typical of all individuals in the United States, the risk 

of E. coli O157:H7 would be extremely small for the entire population. Such an individual does 

not, of course, actually exist. The risk of illness for a specific individual from a specific serving 

of ground beef depends on when and where the ground beef was produced, how it was stored and 

handled, and how it was cooked. It also depends on the consumption patterns of the specific 

individual—how much (serving size) and how often (frequency) a specific individual consumes 

ground beef. Moreover, a specific individual may be more or less susceptible to illness or severe 

consequences of illness if exposed to E. coli O157:H7 in ground beef than predicted using the 

median dose-response curve. Consequently, a specific individual’s risk of E. coli O157:H7 

 

1A “typical” individual’s probability of consuming ground beef with at least 1 E. coli O157:H7 organism is 

calculated as follows: 10 (log[number of contaminated ground beef servings purchased over a lifetime) + log(number of organisms per contaminated serving) + 

(decrease in the number of E. coli O157:H7 organisms in a serving of ground beef from storage conditions) + (decrease in the number of E. coli O157:H7 organisms in 

ground beef from cooking)]. The data used in this calculation are presented in Table 5-1. 

2This is calculated based on multiplying the probability of exposure to a particular number of E. coli O157:H7 

organisms in a ground beef serving (dose) by the probability of illness (response) given this exposure (dose) 

(Table 5-1). 

September 7, 2001 131 
5. Risk Characterization 

TABLE 5-1. Data from the Exposure Assessment (Chapter 3) and Hazard Characterization 

(Chapter 4) Are Used to Estimate the Risk of E. coli O157:H7 Illness for a “Typical” Individual 

Information Used to Estimate the Risk of E. coli O157:H7 Illness for a “Typical” Individual 

1. General Information 

• U.S. population: 260 million 

• Annual number of ground beef servings: 18.2 billion (Tables 3-24, 3-25, 

and 3-26) 

2. Typical Individual 

• Average lifetime: 70 years 

• Average serving size of ground beef: 87 grams (Tables 3-24, 3-25, and 

3-26) 

• Average number of ground beef servings purchased annually: 70 servings (18.2 billion 

servings⁄260 million people; 

Tables 3-24, 3-25, and 3-26) 

3. E. coli O157:H7 Contamination in Uncooked Ground Beef 

Servings 

• Probability of a contaminated ground beef serving: 0.2% to 0.5% (5th and 95th 

percentiles) (Figure 3-27 and 

Equation 3-40) 

• Typical level of contamination per serving: 1 to 3 E. coli O157:H7 

organisms (5th and 95th 

percentiles) (Figure 3-27 and 

Equation 3-40) 

• Typical number of contaminated servings purchased in a 

lifetime: 

9 to 23 servings 

4. Typical Growth and Decline in the Number of E. coli O157:H7 

during Storage, Handling, and Cooking 

• Increase in the number of E. coli O157:H7 during storage and 

handling conditions: 

0 logs (Figure 3-23) 

• Decrease in the number of E. coli O157:H7 from freezing: 1 log (Table 3-18) 

• Decrease in the number of E. coli O157:H7 from cooking: 5 to 6 logs (Figure 3-20) 

5. Dose-Response Curve (median) Figure 4-6 

illness may be very different from a “typical” individual’s risk of E. coli O157:H7 illness. 

Characterization of risk of E. coli O157:H7 illness for the “typical” individual, however, is 

useful in understanding that the overall risk is low. However, specific individuals may be at 

greater or lower risk of E. coli O157:H7 illness because of differences in consumer and retail 

behavior practices (storage, handling, and preparation conditions for ground beef); susceptibility 

to illness; or changes in production, slaughter, or retail practices that lead to either 

more contaminated ground beef servings (increased prevalence) or a greater number of E. coli

O157:H7 organisms in contaminated ground beef servings. Some of these influence variables 

will be considered in the “Population Risk by Season, Age, and Location” section. 

September 7, 2001 132 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Risk of Illness for a Community—Simulated Outbreak 

Characterizing the risk of E. coli O157:H7 illness from ground beef for a community is useful in 

evaluating the likelihood of a foodborne outbreak and the factors that would contribute to such 

an outbreak. As an example, consider a community exposed to a large amount of E. coli

O157:H7-contaminated ground beef from a single grinder load that is stored and cooked under 

the same conditions (e.g., it was purchased, handled, and prepared by a single retail 

establishment). 

This E. coli O157:H7 risk assessment indicates that grinder loads of ground beef can have 

concentrations of E. coli O157:H7 as high as 1 organism per 100 grams.3 Given an average 

serving size of 87 grams,4 nearly all servings of ground beef generated from such a grinder load 

would contain at least 1 E. coli O157:H7 organism. This risk assessment predicts growth of E. 

coli O157:H7 in ground beef in only 1% to 2% of storage scenarios (Figure 3-23), and only 

about 1 in 1,000 ground beef servings will have E. coli O157:H7 organisms grow to a level of 

5.5 logs. Nevertheless, if all of the ground beef servings generated from the grinder load in this 

example were stored (e.g., refrigerated) in a manner that allowed growth of E. coli O157:H7, 

then each ground beef serving could contain a substantial number of E. coli O157:H7 organisms 

prior to cooking.5 If all of these ground beef servings were undercooked, reducing the number of 

E. coli O157:H7 organisms in each ground beef serving by only 3 logs,6 then each ground beef 

serving for consumption would be expected to contain about 270 E. coli O157:H7 organisms.7 If 

individuals consume only one serving of E. coli O157:H7-contaminated ground beef, then about 

3,200 people would be expected to become ill from E. coli O157:H7.8 On the other hand, if all 

of these ground beef servings had been subjected to similar cooking conditions that resulted in a 

decrease of 5.5 logs,9 only 12 people would be expected to become ill from E. coli O157:H7. 

This example illustrates how an outbreak might develop in a community. It is not difficult to 

imagine that a single grinder load might be distributed to a single community. In fact, local 

commercial preparers of ground beef might receive, store, and cook volumes of ground beef 

consisting of entire grinder loads. A similar scenario occurred in the northwestern U.S. outbreak 

described in Chapter 4 (Tuttle et al. 1999; Bell et al. 1994). While such outbreaks are 

uncommon, sporadic illness often results from individual ground beef servings following “high 

risk” scenarios (e.g., improper storage, handling during processing, distribution, retail and 

preparation, or undercooking of ground beef servings). Characterizing the per serving risk of E. 

 

3The E. coli O157:H7 risk assessment predicts that ground beef servings from grinder loads containing more than 1 

E. coli O157:H7 organism have a 0.0116% probability of occurring. 

4Calculated as the weighted average of the amount of ground beef (in grams) consumed by an individual for each 

age category. See Tables 3-24, 3-25, and 3-26. 

5About 5.5 logs of E. coli O157:H7 in each ground beef serving. 

6The E. coli O157:H7 risk assessment predicts that this scenario occurs 25% of the time. 

7This is calculated from Equation 3-42: DOSEpop = BACTpop + Growthpop – LRpop, where the number of E. coli

O157:H7 organisms per ground beef serving (dose) is equal to the number of E. coli O157:H7 in an uncooked 

ground beef serving (multiplied by the number of servings) plus the increase in the number of E. coli O157:H7 

organisms during storage and handling minus the decrease in E. coli O157:H7 organisms as a result of cooking. 

In this scenario, DOSEpop = BACTpop + Growthpop – LRpop = log10(0.01 × 87) + 5.5 – 3 = 2.44 logs in each 

cooked ground beef serving (= 275 E. coli O157:H7 organisms in each cooked ground beef serving). 

8Calculated by using the dose-response equation (Equation 4-3) for ground beef servings containing 270 E. coli

O157:H7 organisms and multiplying by the total number of ground beef servings from this grinder load (78,000 

servings). 

9The E. coli O157:H7 risk assessment predicts that this level of cooking (e.g., resulting in a 5 log reduction in E. 

coli O157:H7 organisms in each ground beef serving) occurs about 50% of the time. 

September 7, 2001 133 
5. Risk Characterization 

coli O157:H7 illness from ground beef within a community is useful for evaluating the 

conditions that are likely to lead to a foodborne outbreak. 

Risk of Illness for the U.S. Population 

The annual risk of E. coli O157:H7 illness from ground beef within the U.S. population can be 

estimated by considering the entire exposure assessment distribution (e.g., the probability of 

consuming E. coli O157:H7 in ground beef for all possible doses). When the median exposure 

distribution and the median dose-response function are used, the risk of illness at each exposure 

dose can be calculated as the product of these two distributions (Table 5-2). 

TABLE 5-2 Risk of Illness for U.S. Population Using Median Exposure and Dose-Response 

Distributions 

Log of E. coli

O157:H7 per 

Serving 

Number of E. coli

O157:H7 per 

Serving 

Probability of 

Exposure (Ex) 

Probability of 

Illness Given 

Exposure (DR) 

Risk of Illness 

(Ex × DR) 

0.0 1 5.5×10-05 1.7×10-04 9.5×10-09

0.5 3 2.9×10-05 5.5×10-04 1.6×10-08

1.0 10 6.1×10-06 1.7×10-03 1.0×10-08

1.5 32 1.2×10-06 5.4×10-03 6.5×10-09

2.0 100 7.7×10-07 1.6×10-02 1.3×10-08

2.5 316 5.3×10-07 4.7×10-02 2.5×10-08

3.0 1,000 4.3×10-07 1.2×10-01 5.0×10-08

3.5 3,162 3.4×10-07 2.3×10-01 7.7×10-08

4.0 10,000 2.7×10-07 3.6×10-01 9.7×10-08

4.5 31,623 2.2×10-07 4.8×10-01 1.1×10-07

5.0 100,000 1.8×10-07 5.8×10-01 1.0×10-07

5.5 316,228 1.5×10-07 6.6×10-01 1.0×10-07

6.0 1,000,000 1.2×10-07 7.3×10-01 8.9×10-08

6.5 3,162,278 9.7×10-08 7.8×10-01 7.6×10-08

7.0 10,000,000 7.4×10-08 8.2×10-01 6.1×10-08

7.5 31,622,777 5.4×10-08 8.6×10-01 4.6×10-08

8.0 100,000,000 3.8×10-08 8.9×10-01 3.4×10-08

8.5 316,227,766 2.5×10-08 9.1×10-01 2.3×10-08

9.0 1,000,000,000 1.4×10-08 9.3×10-01 1.3×10-08

9.5 3,162,277,660 4.8×10-09 9.4×10-01 4.5×10-09

10.0 10,000,000,000 8.5×10-10 9.5×10-01 8.1×10-10

10.5 31,622,776,602 5.5×10-11 9.6×10-01 5.3×10-11

11.0 100,000,000,000 2.0×10-12 9.7×10-01 1.9×10-12

Population risk of illness from E. coli O157:H7 per serving 9.6×10-07

September 7, 2001 134 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Table 5-2 shows this population risk to be nearly 1 illness in each 1 million (9.6 × 10-7) 

servings of ground beef consumed annually. At each half-log dose interval, the risk of becoming 

ill depends on the probability of being exposed to that dose and the probability of illness given 

that dose. When the entire exposure distribution is considered, the sum of the risk of illness 

across all doses represents the population risk. This annual U.S. population risk estimate is based 

on the central tendencies (median) of both the exposure distribution and dose-response 

functions.10 

This risk of illness, 9.6 × 10-7 illnesses per serving, is comparable to the findings of Cassin et 

al. (1998) and Marks et al. (1998). Cassin et al. (1998) conducted a quantitative risk assessment 

of E. coli O157:H7 in ground beef hamburgers cooked at home, for Canada, and calculated a 

mean per serving risk of illness of 5.1 × 10-5 for adults and 3.7 × 10-5 for children. The 

probability of illness generated by another risk assessment of E. coli O157:H7 in ground beef in 

the United States ranged from 3 × 10-4 to 7 × 10-8 (Marks et al. 1998). The risk of illness 

predicted from this risk assessment ranges from 1×10-7 to 1.9 ×10-12 per serving (median, 9.6 ×

10-7) (Table 5-2). 

Given approximately 18.2 billion servings of ground beef consumed per year, the risk 

assessment predicts about 17,500 cases of E. coli O157:H7 illness per year (50th percentile). The 

median number of cases per year predicted from public health surveillance data in the hazard 

characterization is approximately 19,000. Because the uncertainty distributions describing the 

exposure distribution (e.g., the probability of an E. coli O157:H7 dose in a ground beef serving) 

and dose-response function (e.g., the probability of illness given a dose of E. coli O157:H7 in a 

ground beef serving) are not symmetrical, these two estimates of illness do not precisely 

correspond (i.e., the median of the product of these two random variables does not equal the 

product of their respective median values because these distributions are asymmetric). 

Risk of Severe E. coli O157:H7 Illness 

Given this population risk of E. coli O157:H7 illness from ground beef, the probability of severe 

illnesses can be estimated. As noted in Chapter 4, about 20% of all cases develop bloody 

diarrhea and 49% of these cases seek medical attention. Of those persons who develop bloody 

diarrhea and seek medical attention, about 21.6% are severe enough to be hospitalized. Of these 

hospitalized cases, about 24% are hemolytic uremic syndrome (HUS) cases and about 12% of 

those cases result in death. The population risk of being hospitalized but recovering is 2.0 × 10-8, 

the population risk of developing HUS but recovering is 4.2 × 10-9, and the population risk of 

death is 5.9 × 10-10 per ground beef serving. These outcomes of E. coli O157:H7 illness, which 

represent the severest forms of this disease for humans, occur very infrequently on a “per 

serving” basis. If 18.2 billion servings of ground beef are consumed per year, these population 

risks imply that, on an “per annum” basis, 370 people are hospitalized but recover, 87 people 

develop HUS but recover, and 11 people die as a result of E. coli O157:H7-contaminated ground 

beef. 

Risk of E. coli O157:H7 Illness as a Function of Exposure (Dose) 

The risk of human illness from E. coli O157:H7 in ground beef is the result of two divergent 

trends: 

 

10Uncertainty about this risk ranges from about 1 illness in every 3 million consumed ground beef servings at the 5th 

percentile to about 2 illnesses in every 1 million consumed ground beef servings at the 95th percentile. 

September 7, 2001 135 
5. Risk Characterization 

1. Consumers are more likely to be exposed to a lower rather than a higher number of E. 

coli O157:H7 organisms (dose) in a ground beef serving ( Figure 3-29; Table 5-2); and 

2. Consumers are more likely to become ill when exposed to a higher rather than a lower 

number of E. coli O157:H7 organisms (dose) (Figure 4-7; Table 5-2). 

These divergent trends are observed in Table 5-2, which shows that increasing dose (e.g., 

number of E. coli O157:H7 organisms) is associated with decreasing probability of exposure and 

increasing probability of illness. Therefore, the change in risk of illness as dose increases is 

dependent on the rate at which exposure probability is declining and the dose-response 

probability is increasing. Figure 5-1 uses the information in Table 5-2 to show how the risk of 

illness from E. coli O157:H7 changes as dose changes. 

Dose

Risk of Illness

0.00000000

0.00000002

0.00000004

0.00000006

0.00000008

0.00000010

0.00000012

1

10

100

1,000

10,000

100,000

1,000,000

10,000,000

100,000,000

1,000,000,000

10,000,000,000

100,000,000,000

FIGURE 5-1 Risk of illness for U.S. population by dose. 

Figure 5-1 shows that the highest risk of illness is associated with doses around 100,000 E. 

coli O157:H7 organisms per serving. Although the probability of exposure is greatest at a dose of 

1 organism per ground beef serving (5.5 × 10-05), the dose-response function predicts a very low 

probability of human illness given an exposure of just 1 E. coli O157:H7 organism (1.7 × 10-04). 

This results in a low risk of illness (5.5 × 10-05 ×1.7 × 10-04 = 9.5 × 10-09). At a dose of 100,000 

organisms per ground beef serving, however, the probability of exposure is much lower (1.8 ×

10-07), but the probability of illness is much higher (0.58). Consequently, the risk of illness from 

exposure to 100,000 E. coli O157:H7 organisms (1.8 × 10-07 × 0.58 = 1.0 × 10-07) is higher than 

from exposure to 1 E. coli O157:H7 organism. 

One interpretation of Figure 5-1 is that reducing the number of E. coli O157:H7-

contaminated ground beef servings, but not the number of E. coli O157:H7 organisms in a 

ground beef serving, would lower the risk of illness at each dose level (i.e., decrease the 

amplitude of the curve). Such a reduction might occur by improved controls in the slaughter 

process that result in fewer contaminated ground beef servings. Alternatively, improved storage 

and/or cooking behavior by consumers and food preparers would decrease the number of E. coli

September 7, 2001 136 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

O157:H7 organisms in contaminated ground beef servings but not change the total number of 

contaminated servings (i.e., shift the curve to the left but leave the amplitude unchanged). Either 

reducing the number of E. coli O157:H7-contaminated ground beef servings or the number of E. 

coli O157:H7 organisms in contaminated ground beef servings would result in a reduction in the 

number of E. coli O157:H7 illnesses occurring per year. 

Figure 5-1 indicates that reducing the number of E. coli O157:H7-contaminated servings 

actually results in a greater reduction in risk relative to reducing the number of E. coli O157:H7 

in contaminated ground beef servings. A tenfold reduction in the number of E. coli O157:H7-

contaminated ground beef servings results in a population risk of 9.6 × 10-08 per serving. A 

tenfold reduction in the number of E. coli O157:H7 organisms in contaminated ground beef 

servings results in a population risk of 5.5 × 10-07 per serving. This suggests that interventions 

focused on reducing the prevalence of E. coli O157:H7 (i.e., improved controls during slaughter 

and processing) are more effective at reducing the risk of illness than those focused on reducing 

the number of E. coli O157:H7 in consumed ground beef servings (i.e., storage and cooking 

conditions). However, this analysis does not suggest which intervention, if either, is more 

feasible to achieve. 

The preceding discussion illustrates that a population estimate of risk is the sum of the risks 

faced by all individuals in the population. Therefore, the population risk estimate should be 

interpreted as a summary measure of risk that can be used for policy analysis or comparison with 

other risk estimates. The population risk is not indicative of the risk for any one individual. In 

other words, it is incorrect to assume that, given a population risk of 1 illness in every 2 million 

servings, each serving a person consumes has this risk of illness. Individual consumer risk is not 

necessarily random. The risk of illness from a serving of ground beef for a specific consumer can 

depend on when and where the ground beef was produced, how it was stored, and how the 

serving was cooked. The specific consumer may also be more susceptible to illness or severe 

consequences of illness if exposed. These factors are not necessarily controllable by the 

individual, but they are also not necessarily randomly occurring. The next sections consider the 

influence of such factors on the risk of illness from E. coli O157:H7 in ground beef. 

POPULATION RISK BY SEASON, AGE, AND LOCATION 

The risk of illness from E. coli O157:H7 in ground beef can vary among U.S. subpopulations 

based on differences in exposure (by seasonal contamination or behavioral differences) or host 

susceptibility (by age). Characterization of the risk of illness from E. coli O157:H7-contaminated 

ground beef can be used to target intervention strategies and risk communication messages. This 

risk assessment considers the risk of illness by seasonal exposure, age of the consumer, and 

location of the meal. 

Variability in the Risk of Illness by Season 

Variability in seasonal exposure may influence the risk of illness from E. coli O157:H7 in 

ground beef. The exposure assessment predicts that consumers are exposed to more E. coli

O157:H7-contaminated ground beef servings during the “high prevalence season” (June to 

September) than during the “low prevalence season” (October to May) (see Chapter 3). This 

seasonal trend in exposure to E. coli O157:H7 in ground beef may be associated with the 

increased number and severity of E. coli O157:H7 cases reported during June through September 

(see Chapter 2). 

September 7, 2001 137 
5. Risk Characterization 

The risk of illness is substantially greater in the high prevalence season at all doses relative to 

the low prevalence season. Figure 5-2 compares the risk of illness between the low and high 

prevalence seasons using the median exposure distribution for each season and the median doseresponse function. For a dose of E. coli O157:H7 in ground beef servings ranging from 1 to 10 

logs, each curve shows the product of the probability of exposure to that dose and the probability 

of illness given that dose. Both high and low prevalence seasons have similar shaped distribution 

curves for illness and are consistent with the shape shown in Figure 5-1. This indicates that the 

risk of illness from E. coli O157:H7 in ground beef servings follows the same trend over the 

same dose range. 

Dose

Risk of Illness

Low prevalence season

High prevalence season

0.00000000

0.00000002

0.00000004

0.00000006

0.00000008

0.00000010

0.00000012

0.00000014

0.00000016

0.00000018

0.00000020

1

10

100

1,000

10,000

100,000

1,000,000

10,000,000

100,000,000

1,000,000,000

10,000,000,000

100,000,000,000

FIGURE 5-2 Risk of illness for U.S. population by dose for low and high prevalence seasons. 

The only influence of season in this risk assessment occurs because live cattle, carcasses, and 

ground beef are more contaminated in the high prevalence season (June to September). No data 

were available on possible seasonal differences in consumer or retail storage and preparation of 

ground beef meals (e.g., grilled hamburgers in July versus baked meat loaf in November). 

Similarly, no data were available on seasonal consumption patterns for ground beef. Seasonal 

consumption data would provide information on how much ground beef was consumed and in 

what form (e.g., ground beef patty, meat loaf, or meatballs) during June to September versus 

other months of the year.11 As a result, the similar shape of the two curves in Figure 5-2 simply 

reflects the assumption of similar consumer behavior practices (storage and cooking) for both 

high and low prevalence seasons. 

 

11The type of ground beef meal consumed is important because ground beef meals are handled and cooked 

differently (e.g., ground beef patties consumed on the Fourth of July may have more time-temperature abuse at a 

picnic and are more likely to be undercooked on a grill than meat loaf consumed in January that may have been 

baked in the oven). 

September 7, 2001 138 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

The greater prevalence of contaminated ground beef servings in the high prevalence season is 

reflected in the greater risk of illness across all doses. When the risk of illness is summed across 

all doses, the population risk of illness is 1.7 × 10-6 in the high prevalence season and 6.0 × 10-7

in the low prevalence season. Therefore, about 1 in every 600,000 servings consumed during the 

high prevalence season is predicted to result in illness, while about 1 in every 1.6 million 

servings consumed in the low prevalence season results in illness. These differences imply that 

risk of illness is about three times greater in the high prevalence season than in the low 

prevalence season. 

The hypothetical linkage between live cattle, ground beef, and human E. coli O157:H7 

illnesses is strongly supported by these seasonal findings. Of the 18.2 billion ground beef 

servings consumed annually, it is assumed that one-third are consumed during the high 

prevalence season and two-thirds are consumed during the remainder of the year. Combining this 

consumption pattern information with the seasonal risk per ground beef serving estimates implies 

that 58% of illnesses occur during the high prevalence season, while 42% occur during the low 

prevalence season. This finding is consistent with FoodNet data that show 64% of illnesses occur 

during June through September. Such consistency is noteworthy because the model only 

accounts for seasonality in live cattle and grinder loads of ground beef. Therefore, without any 

adjustment for seasonal differences in ground beef storage or cooking, these results imply that 

seasonal changes in prevalence on the farm subsequently influence levels of E. coli O157:H7 in 

combo bins, grinders loads, and servings and predict changes in illnesses in a manner consistent 

with human health surveillance data. Furthermore, these results suggest that variability in 

consumer behaviors may contribute to an increased number of E. coli O157:H7 illnesses 

observed in the summer months. Further research on consumer and retail behaviors is needed to 

validate the assumption that improper storage and cooking practices (e.g., time and temperature 

abuses) for ground beef are more likely during the summer months.

Variability in the Risk of Illness by Age of the Consumer 

Age of the consumer has been identified as a risk factor for illness from E. coli O157:H7 in 

ground beef. In hazard characterization (Chapter 4), a higher apparent incidence of E. coli

O157:H7 illnesses was reported for 1- to 9-year-olds. Other data suggest that most of the 

elevated risk occurs in children 0 to 5 years old (Mead et al. 1999). 

The exposure assessment was used to generate an exposure distribution for children 0 to 5 

years old and persons 6 years and older (Figure 5-3). The exposure distribution for 0- to 5-yearolds is shifted slightly to the left, reflecting a smaller average ground beef serving size (44 

grams) compared with the average serving size for all other ages (90 grams). Because of the 

smaller serving size, children under 5 years old are less likely to be exposed to E. coli O157:H7 

organisms in ground beef (i.e., they have a lower probability of consuming an E. coli O157:H7-

contaminated ground beef serving and, if a contaminated serving is consumed, it is likely to have 

a lower number of E. coli O157:H7 organisms). 

Although children 0 to 5 years old are less likely than older persons to be exposed to E. coli

O157:H7 in ground beef, they are disproportionately represented among all reported E. coli

O157:H7 cases. If young children are less exposed to E. coli O157:H7 in ground beef but more 

likely to become ill from E. coli O157:H7, then they may be (1) more susceptible to illness from 

the exposures they experience, (2) more likely to be diagnosed by a physician than other age 

September 7, 2001 139 
5. Risk Characterization 

0.0000000001

0.0000000010

0.0000000100

0.0000001000

0.0000010000

0.0000100000

0.0001000000

0.0010000000

0.0100000000

0.1000000000

1.0000000000

None

0.51.52.53.54.55.56.57.58.59.5

Logs of E. coli O157:H7 during High

Prevalence Season

Frequency of Exposure

0–5 years 6+ years

0.0000000001

0.0000000010

0.0000000100

0.0000001000

0.0000010000

0.0000100000

0.0001000000

0.0010000000

0.0100000000

0.1000000000

1.0000000000

None

0.51.52.53.54.55.56.57.58.59.5

Logs of E. coli O157:H7 during Low

Prevalence Season

Frequency of Exposure

0–5 years 6+ years

FIGURE 5-3 Comparison of predicted seasonal exposure distributions for children 0 to 5 years old 

versus people 6 years and older. 

groups, or (3) more exposed to other sources of E. coli O157:H7 (e.g., daycare, petting farm, 

swimming pool) than the remainder of the population.12

If children ages 0 to 5 are more susceptible to illness from E. coli O157:H7, then a more 

sensitive dose-response curve than that derived for the general population should be used. 

Nevertheless, no data are available to estimate a different dose-response function for young 

children. If the upper bound E. coli O157:H7 dose-response curve derived from Shigella 

dysenteriae surrogates is used, then the risk of illness for children 0- to –5-years-old is estimated 

to be 2.4 × 10-6 per ground beef serving. This is comparable to estimates by Cassin et al. (1998) 

for the average (mean) risk of illness for children of 3.7 × 10-5 per ground beef serving. If young 

children are more susceptible to illness from E. coli O157:H7-contaminated ground beef, then 

their risk may be up to 2.5 times greater than that of the general U.S. population (2.4 × 10-6

versus 9.6 × 10-7). Children 0- to 5-years-old consume only about 7% of all ground beef 

servings, but a more susceptible dose-response curve implies that about 15% of all illnesses 

occur in this age category. 

Young children may be more susceptible to illness when exposed to E. coli O157:H7, but the 

available data do not rule out the possibility that reported illnesses for children are affected by 

various surveillance biases. For example, it is possible that the etiologic fraction of E. coli

O157:H7 cases attributed to ground beef for young children may be lower than that reported for 

the general population. For instance, young children are exposed to E. coli O157:H7 via childcare facilities. This route of exposure may be important for this age group and would reduce the 

etiologic fraction of cases attributed to ground beef. Furthermore, adjustments to reported cases 

used for the general population may overestimate the proportion of cases in young children. It 

seems likely that young children are more likely than older persons to see a health care worker 

when they are sick. For example, young children are also more likely to develop HUS, and such 

a severe illness certainly requires medical attention. Based on the available data, however, the 

existence and magnitude of these biases cannot be ascertained. 

 

12Exposure to other sources of E. coli O157:H7 may confound the etiologic fraction of E. coli O157:H7 cases 

attributable to ground beef (Chapter 4). 

September 7, 2001 140 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

Variability in the Risk of Illness by Location of Meal 

As more meals are consumed outside the home in the United States, there is a growing interest in 

the relative risk of foodborne illness from eating at home versus “away from home” (HRI). The 

1994–1996, 1998 Continuing Survey of Food Intakes by Individuals indicates that 65% of 

ground beef meals are consumed outside the home (e.g., Tables 3-24, 3-25, and 3-26). While this 

risk assessment includes data on where ground beef meals were consumed, data on variability in 

food preparation behavior between consumers (home) and food preparers (HRI) are lacking. 

These data are needed to estimate the amount of E. coli O157:H7 contamination (dose) in ground 

beef servings prepared at home and at HRI. While it is plausible that HRI preparation practices 

for ground beef are more stringent under the Food Code (FDA 1999), data are needed to support 

such an assumption. Storage and cooking time and temperature data are available for ground 

beef meals cooked at home (Audits International 1999). When HRI storage and cooking time and 

temperature data become available, the risk of illness from home-prepared and HRI-prepared 

ground beef servings can be compared. The effects of consumer storage and cooking practices on 

the risk of E. coli O157:H7 illness from ground beef will be further evaluated in the context of 

sensitivity analysis. 

Other Population Risk Variability 

As more data become available, a more detailed picture of the risk of illness from E. coli

O157:H7 in ground beef within the U.S. population can be developed. The level of detail needed 

in a risk characterization depends on the type of problem under consideration. 

SENSITIVITY ANALYSIS 

Sensitivity analysis refers to the quantitative process of identifying factors (model inputs) that 

are most responsible for influencing the occurrence and extent of E. coli O157:H7 in ground beef 

(model outputs). A combination of statistical, algebraic, and graphical techniques is used to 

illustrate the effect of sensitive factors on model outputs. Two types of sensitivity analyses are 

used in this risk assessment: correlation analysis and dependency analysis. 

Correlation Analysis 

Correlation analysis is used to identify “uncertain” factors (i.e., model inputs for which there are 

limited data and information) that influence intermediate and final model outputs. Factors that 

are supported by data and information (i.e., not “uncertain”) are identified by dependency 

analysis (discussed in the next section). Therefore, correlation analysis is but one technique for 

identifying factors most important in influencing the likelihood of exposure or risk of illness. 

Correlation analysis was used to identify “uncertain” factors most important in influencing 

the occurrence and extent of E. coli O157:H7 contamination in ground beef at various points 

along the farm-to-table continuum: 

• E. coli O157:H7 in combo bins created from steer/heifer carcasses, 

• E. coli O157:H7 in combo bins created from cow/bull carcasses, 

• E. coli O157:H7 in grinder loads, 

• E. coli O157:H7 in ground beef servings prior to storage and cooking, and 

• E. coli O157:H7 in ground beef servings after storage and cooking. 

September 7, 2001 141 
5. Risk Characterization 

For each of these outputs, correlation was measured relative to the number of E. coli

O157:H7 organisms within a unit (i.e., combo bin, grinder load, or single serving) and the 

prevalence (%) of E. coli O157:H7-contaminated units (i.e., combo bins, grinder loads, 

servings). The mean number of E. coli O157:H7 organisms in a unit (e.g., combo bin) was 

estimated for each output. Factors were identified as correlated to the output if the Spearman 

rank correlation coefficient was greater than 0.30. 

E. coli O157:H7 in Combo Bins Created from Steer/Heifer Carcasses 

The size of the E. coli O157:H7-contaminated carcass surface area was the only factor correlated 

(coefficient = 0.33) with the number of E. coli O157:H7 organisms in steer/heifer combo bins 

(Table 5-3). This correlation only applied to the high prevalence season (June to September). 

There was no correlation between the extent of carcass contamination and the resulting number 

of E. coli O157:H7-contaminated steer/heifer combo bins. Uncertainty regarding the size of E. 

coli O157:H7 contamination area on carcasses ranged from 40 cm2 (5th percentile) to 900 cm2

(95th percentile). 

TABLE 5-3 Correlations with E. coli O157:H7 Contamination in Steer/Heifer Combo Bins 

E. coli O157:H7 

Contamination in Steer/Heifer 

Combo Bins 

Output Correlations with the Number of E. coli O157:H7 Organisms in a 

Unit and the Percent of Units Contaminated (%) by Season 

June to September 

(High Prevalence Season) 

October to May 

(Low Prevalence Season) 

Model Input (factor) No. % No. % 

Area of carcass contaminated 0.33 

E. coli O157:H7 in Combo Bins Created from Cow/Bull Carcasses 

Factors that most influence the occurrence and extent of E. coli O157:H7 contamination in 

cow/bull combo bins are the size of the E. coli O157:H7-contaminated carcass surface area and 

the average (mean) effect of chilling on contaminated carcasses (Table 5-4). The change in the 

number of E. coli O157:H7 organisms resulting from chilling was modeled as a normal 

distribution with an uncertain mean ranging from –0.5 to +0.5. The effect of chilling the 

carcasses was correlated with the number of E. coli O157:H7-contaminated cow/bull combo bins 

but not with the number of E. coli O157:H7 in these combo bins. 

E. coli O157:H7 in Grinder Loads 

Factors that most influence the prevalence and number of E. coli O157:H7 organisms in grinder 

loads are (1) the size of the E. coli O157:H7-contaminated surface area, (2) the effect of chilling 

on carcasses, and (3) the prevalence and number of E. coli O157:H7 organisms in combo bins 

(both steer/heifer and cow/bull). Table 5-5 shows that E. coli O157:H7 contamination in grinder 

loads is more correlated with the prevalence and number of E. coli O157:H7 organisms in 

steer/heifer combo bins than cow/bull combo bins. Little to no correlation is found between the 

average number of E. coli O157:H7 organisms in combo bins and the number of E. coli O157:H7 

September 7, 2001 142 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

TABLE 5-4 Correlations with E. coli O157:H7 Contamination in Cow/Bull Combo Bins 

E. coli O157:H7 

Contamination in Cow/Bull 

Combo Bins 

Output Correlations with the Number of E. coli O157:H7 Organisms in a 

Unit and the Percent of Units Contaminated (%) by Season 

June to September 

(High Prevalence Season) 

October to May 

(Low Prevalence Season) 

Model Input (factor) No. % No. % 

Area of carcass contaminated 0.33 0.32 0.34 

Mean of chilling distribution 0.37 0.36 

TABLE 5-5 Correlations with E. coli O157:H7 Contamination in Grinder Loads 

E. coli O157:H7 Contamination in 

Grinder Loads 

Output Correlations with the Number of E. coli O157:H7 

Organisms in a Unit and the Percent of Units Contaminated (%) 

by Season 

June to September 

(High Prevalence Season) 

October to May 

(Low Prevalence Season) 

Model Input (factor) No. % No. % 

Cow/bull combos—expected value 0.69 

Cow/bull combos—% contaminated 0.70 0.36 

Area of carcass contaminated 0.32 

Mean of chilling distribution 0.34 

Steer/heifer combos—expected value 0.44 0.81 0.33 0.87 

Steer/heifer combos—% contaminated 0.97 0.99 

organisms in grinder loads. This may be due to the fact that any given grinder load may contain 

E. coli O157:H7 organisms from multiple combo bins, yet the high numbers of E. coli O157:H7 

organisms in grinder loads are likely caused by the introduction of high numbers of E. coli

O157:H7 from just one contaminated combo bin. Therefore, the mixing of combo bins to form 

grinder loads may decrease the influence of combo bin E. coli O157:H7 contamination on the 

average number of E. coli O157:H7 organisms in grinder loads. 

E. coli O157:H7 in Ground Beef Servings Prior to Storage and Cooking 

The number of E. coli O157:H7 organisms in grinder loads is an important factor that greatly 

influences the prevalence and number of E. coli O157:H7 organisms in uncooked ground beef 

servings before storage (Table 5-6). Such a finding is not surprising because the probability of 

selecting a ground beef serving with 1 or more E. coli O157:H7 organisms is dependent on the 

number of E. coli O157:H7 organisms within the grinder load. Table 5-6 indicates that the 

number of E. coli O157:H7-contaminated grinder loads has some influence on the prevalence 

and density of E. coli O157:H7 in uncooked ground beef servings (coefficient: 0.31 to 0.39, 

October to May). Grinder loads are considered contaminated if they contain at least 1 E. coli 

September 7, 2001 143 
5. Risk Characterization 

TABLE 5-6 Correlations with E. coli O157:H7 Contamination in Ground Beef Servings Before 

the Effects of Growth and Cooking Are Considered 

E. coli O157:H7 in Ground Beef Servings 

Before Storage and Cooking 

Output Correlations with the Number of E. coli O157:H7 

Organisms in a Unit and the Percent of Units Contaminated 

(%) by Season 

June to September 

(High Prevalence Season) 

October to May 

(Low Prevalence Season) 

Model Input (factor) No. % No. % 

Grinders—expected value 0.99 0.95 0.99 0.95 

Steer/heifer combos—expected value 0.44 0.40 0.39 

Grinders—% contaminated 0.33 

Steer/heifer combos—% contaminated 0.31 

O157:H7 organism. Because grinder loads are likely to contain 10,000 pounds or more of ground 

beef, the presence of 1 E. coli O157:H7 organism has little effect on whether an individual 

ground beef serving becomes contaminated with E. coli O157:H7. 

In general, the more removed an intermediate output (or input) is from a model output, the 

less influence it has. For example, the occurrence of E. coli O157:H7 in steer/heifer combo bins 

influences the occurrence in grinder loads (Table 5-5). Also, the occurrence of E. coli O157:H7 

in grinder loads influences the occurrence in servings prior to growth and cooking (Table 5-6). 

Therefore, the greater influence of E. coli O157:H7-contaminated grinder loads relative to E. coli

O157:H7-contaminated combo bins on the occurrence and extent of E. coli O157:H7 

contamination in ground beef servings (Table 5-6) simply reflects the closer proximity of ground 

beef in grinders to ground beef servings in the farm-to-table continuum. 

E. coli O157:H7 in Ground Beef Servings After Storage and Cooking 

Factors that most influence the occurrence and extent of E. coli O157:H7 contamination in 

consumed ground beef servings (dose) are the prevalence and number of E. coli O157:H7 

organisms in ground beef servings before storage, the type of storage (e.g., refrigeration versus 

freezing), the average amount of growth (or decline) in E. coli O157:H7 during storage of 

ground beef servings, and the effect of cooking. 

Cooking is notable in its absence from Table 5-7. The effectiveness of cooking is poorly 

correlated with the exposure distribution in this type of sensitivity analysis because it does not 

have a wide range of uncertainty (e.g., uncertainty of less than 1 log). In contrast, there is greater 

uncertainty regarding the growth of E. coli O157:H7 during storage (e.g., uncertainty of as much 

as 2 logs). As a result, the effect of cooking on the amount of E. coli O157:H7 in contaminated 

ground beef servings is revisited in another type of sensitivity analysis (dependency analysis) in 

the next section. 

The uncertainty related to the maximum population density of E. coli O157:H7 in ground 

beef strongly influences the density of E. coli O157:H7 in consumed servings (Table 5-7). 

Uncertainty about the maximum population density for E. coli O157:H7 in ground beef servings 

can range from 5 to 10 logs. This large uncertainty, combined with the importance of this input 

in the model, accounts for the magnitude of the correlation coefficient (coefficient: 0.58 to 0.60). 

September 7, 2001 144 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

TABLE 5-7 Correlations with E. coli O157:H7 Contamination in Ground Beef Servings After the 

Effects of Growth and Cooking Are Considered 

E. coli O157:H7 in Ground Beef Servings 

After Storage and Cooking 

Output Correlations with E. coli O157:H7 Density and 

Percent of Units Contaminated (%) by Season 

June to September 

(High Prevalence Season) 

October to May 

(Low Prevalence Season) 

Model Input (factor) Density % Density % 

Grinders—expected value 0.35 0.79 0.44 0.78 

Max pop density 0.58 0.60 

Growth—expected value 0.82 0.85 

Home/HRI storage temperatures (0.31) 

Servings before growth and cooking—

expected value 

0.36 0.78 0.45 0.76 

Servings before growth and cooking—% 

contaminated 

0.77 0.39 0.78 

Percent ground beef frozen (0.40) (0.43) 

Steer/heifer combos—expected value 0.36 

The percent of ground beef that is frozen is negatively correlated with the prevalence or 

density of E. coli O157:H7 in consumed servings (Table 5-7). Freezing directly reduces E. coli

O157:H7 in servings (Sage and Ingham 1998). However, freezing also makes E. coli O157:H7 

somewhat more heat stable, thereby reducing cooking effectiveness. 

The number of E. coli O157:H7 organisms in consumed ground beef servings is negatively 

correlated with home/HRI storage temperatures (Table 5-7). This distribution is modeled using 

cumulative probabilities. A negative correlation results because lower cumulative probability 

values are associated with increased occurrence of higher storage temperatures and, 

consequently, more growth of E. coli O157:H7 in ground beef servings. 

Previous intermediate outputs, such as grinders, servings before growth and cooking, and 

steer heifer combos, also influence the occurrence of E. coli O157:H7 in consumed ground beef 

servings (Table 5-7). 

Although correlation is one measure of sensitivity, it does not address important inputs that 

are fixed or relatively certain. The correlation analysis completed for this risk assessment 

suggests that the E. coli O157:H7-contaminated carcass surface area (during slaughter), the 

average effectiveness of chilling carcasses (slaughter), the maximum population density for E. 

coli O157:H7 in ground beef servings, and home storage (e.g., refrigeration) temperatures are 

important factors that may influence the occurrence of E. coli O157:H7 in consumed ground beef 

servings and subsequent risk of illness. Nevertheless, some inputs are less uncertain (e.g., 

cooking effectiveness), yet might be very influential on the exposure to E. coli O157:H7 in 

ground beef and the subsequent risk of illness. Therefore, another type of sensitivity analysis is 

conducted to identify other factors important in influencing the occurrence of E. coli O157:H7 in 

ground beef and the subsequent risk of illness. This alternative is termed dependency analysis. 

September 7, 2001 145 
5. Risk Characterization 

Dependency Analysis 

Dependency analysis provides insight into the importance of various factors along the farm-totable continuum that ultimately influence the risk of illness from E. coli O157:H7 in ground beef. 

This type of sensitivity analysis considers the effect of changing parameters for specific factors 

(model inputs) and examines their effect on intermediate model outputs (occurrence and extent 

of E. coli O157:H7 contamination). 

Although some factors (model inputs) do not appear to be correlated (correlation analysis) 

with the occurrence of E. coli O157:H7 in consumed ground beef servings and subsequent risk of 

illness (model outputs), the model outputs might still largely depend (dependency analysis) on 

the values of these inputs. As an example, decontamination steps in slaughter influence the 

number of E. coli O157:H7 organisms remaining on a carcass just prior to trim being generated 

and placed in combo bins. This effect of decontamination is algebraically determined in the 

model. However, the parameters describing how decontamination effectiveness varies between 

carcasses are not very uncertain (varying by only a 0.5 log reduction). In contrast, the most likely 

value for maximum E. coli O157:H7 population density can vary over a 5.0 log range. Therefore, 

uncertainty about decontamination effectiveness is not substantial enough (i.e., correlation 

>0.30) to be identified, through correlation analysis, as an important factor influencing the 

prevalence and number of E. coli O157:H7 in combo bins. Instead, this factor would be 

identified through the use of dependency analysis. 

Because this risk assessment involves complicated relationships among model inputs, 

dependency analysis illustrates the effect of changing model inputs on intermediate model 

outputs (i.e., the occurrence and extent of E. coli O157:H7 contamination in ground beef along 

the farm-to-table continuum). The analysis is conducted by developing different scenarios where 

some model inputs are intentionally changed and the resultant outputs are compared with model 

outputs generated from a baseline scenario (i.e., where all model inputs are unchanged). 

Production and Slaughter Modules 

Because production and slaughter module inputs both influence the E. coli O157:H7 

contamination that occurs in combo bins, their dependency analysis is completed in tandem. 

This analysis is limited to simulating steer/heifer slaughter establishments during the high 

prevalence season (June to September). The simulations only consider cattle contaminated 

during the dehiding step in slaughter. Model inputs that are not evaluated in the dependency 

analysis are held at their median values. 

Although the scope of this dependency analysis is limited, it is reasonable to assume that its 

results will also describe proportional changes occurring in cow/bull slaughter plants, as well as 

in both types of plants during the low prevalence season. Besides feedlot and within-feedlot 

prevalence, no other model inputs to the slaughter module differ dramatically between the 

seasons. 

Simulated Scenarios for Production and Slaughter

Scenarios were simulated that change, in turn, feedlot E. coli O157:H7 prevalence, withinfeedlot E. coli O157:H7 prevalence, decontamination following dehiding, steam pasteurization 

following evisceration, the live cattle to carcass transformation ratio, and the effect of carcass 

chilling. Changes to these model inputs for each scenario were as follows: 

• Feedlot prevalence scenario—changes the value for feedlot E. coli O157:H7 prevalence 

from 88% to 44% (a 50% change). 

September 7, 2001 146 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

• Within-feedlot scenario—changes the value for average within-feedlot E. coli O157:H7 

prevalence from 22% to 11% (50% change). 

• Decontamination following dehiding scenario—changes the effectiveness of 

decontamination from a most likely range of 0.3 and 0.7 logs (baseline) to a uniform 

decontamination effectiveness of 1.2 logs (i.e., assumes there is always maximum 

effectiveness of decontamination following dehiding). 

• Steam pasteurization scenario—changes the effectiveness of decontamination from a 

most likely range of 0.5 to 1.5 logs (baseline) to a uniform decontamination effectiveness 

of 2.5 logs (i.e., assumes there is always maximum effectiveness of steam pasteurization).

• Live cattle to carcass transformation ratio scenario—changes the value of input from 1 

to 2 into a constant of 1 (i.e., this dependency scenario assumes the lowest ratio of E. coli

O157:H7-contaminated carcasses to infected live cattle). This scenario suggests greater 

control of E. coli O157:H7 contamination during the dehiding step when live cattle are 

converted to carcasses. 

• Carcass chilling effect scenario—changes the effect of chilling from –3.0 to +3.0 in the 

baseline scenario to zero (i.e., assumes carcass chilling has no effect in either increasing 

or decreasing the number of E. coli O157:H7 organisms on carcasses). Although 

correlation analysis has already shown that the carcass chilling step is important in 

predicting E. coli O157:H7 contamination in combo bins, a scenario for this input is 

simulated for illustration. 

Results of the Simulated Scenarios for Production and Slaughter

Figure 5-4 shows the results of these scenario analyses. All of the scenarios resulted in a 

lower number of E. coli O157:H7-contaminated combo bins compared with the baseline scenario 

(i.e., no changes). That is, all scenarios resulted in less than 40% (baseline) of combo bins 

containing 1 or more E. coli O157:H7 organisms. 

The most effective decontamination scenario was the assumption of a 2.5 log reduction in the 

number of E. coli O157:H7 organisms on carcasses from steam pasteurization. The steam 

pasteurization scenario resulted in a 90% reduction in the number of E. coli O157:H7-

contaminated combo bins compared with the baseline scenario. The decontamination following 

dehiding scenario results in about an 80% reduction in the number of E. coli O157:H7-

contaminated combo bins compared with the baseline scenario. Both decontamination after 

dehiding and steam pasteurization generally reduced the number of E. coli O157:H7 organisms 

on contaminated carcasses and in subsequent combo bins. Steam pasteurization has a greater 

influence than decontamination after dehiding, with a maximum effectiveness of 2.5 versus 1.2 

logs. 

Reducing feedlot prevalence by 50% results in a 77% reduction in the number of E. coli

O157:H7-contaminated combo bins. A similar reduction in within-feedlot prevalence results in 

only a 70% reduction in the number of E. coli O157:H7-contaminated combo bins. Feedlot 

prevalence determines the proportion of truckloads that arrive with one or more infected cattle. 

Within-feedlot prevalence is variable between contaminated truckloads, and it determines how 

many infected cattle there are among the 40-head capacity of these trucks. Therefore, the 

influence of feedlot prevalence on the incoming prevalence of infected cattle is somewhat more 

direct than the influence of within-feedlot prevalence. 

The distribution for the transformation ratio scenario generally parallels the distribution for 

the within-feedlot prevalence scenario but is slightly less effective. On average, there are about 

1.5 E. coli O157:H7-contaminated carcasses per infected live animal (e.g., cross-contamination). 

September 7, 2001 147 
5. Risk Characterization 

E. coli O157:H7 Organisms per Combo Bin

Cumulative Frequency

Feedlot prevalence Within-feedlot prevalence

Transformation ratio Decontamination post-dehiding

Steam pasteurization Carcass chilling

Baseline

0.60000

0.70000

0.80000

0.90000

1.00000

0 1 3 10 32 100 316 1,000

FIGURE 5-4 Comparison of cumulative distributions of combo bin contamination for six 

scenarios relative to baseline. Feedlot and within-feedlot prevalence scenarios reduce these 

inputs by 50%. The decontamination and steam pasteurization scenarios assume a constant 

maximum effectiveness of these steps. 

Therefore, this scenario assumes about a one-third reduction in this input relative to the baseline 

scenario. This magnitude of reduction is less than that resulting from the 50% reduction in 

within-feedlot prevalence and explains the discrepancy between the respective distributions. It is 

expected that modeling a 50% reduction in the transformation ratio would result in a shift in the 

combo bin contamination distribution similar to that shown for the within-feedlot prevalence 

scenario. However, a 50% reduction in the transformation ratio would be beyond the bounds of 

the current uncertainty distribution. 

Carcass chilling had little effect on the number of E. coli O157:H7-contaminated combo 

bins. However, in this scenario, there was a dramatic reduction in the occurrence of high levels 

of E. coli O157:H7 in combo bins relative to other scenarios. Because the influence of carcass 

chilling on individual combo bins can range from –3 to +3 logs in the baseline scenario, this step 

can result in substantial amplification of E. coli O157:H7 on carcasses and in combo bins. This 

scenario illustrates that high numbers of E. coli O157:H7 organisms in combo bins are primarily 

the result of increases in the number E. coli O157:H7 organisms on carcasses during chilling. 

Furthermore, this scenario illustrates that the high numbers of E. coli O157:H7 organisms in 

combo bins are influenced by the high numbers of E. coli O157:H7 organisms that occur 

occasionally on chilled carcasses. This suggests that chilling carcasses is an important factor that 

greatly influences the number of E. coli O157:H7 in beef trim in combo bins. 

While all of these factors are important in influencing E. coli O157:H7 contamination in 

ground beef, it may be more important to focus mitigation strategies on areas that influence the 

occurrence of E. coli O157:H7-contaminated ground beef servings (i.e., steam pasteurization) 

than on those that influence the number of E. coli O157:H7 in a contaminated serving (i.e., 

carcass chilling). As noted in the “Risk of E. coli O157:H7 Illness as a Function of Exposure 

September 7, 2001 148 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

(Dose)” section, the population risk of illness is influenced more by the prevalence of E. coli

O157:H7-contaminated ground beef servings than by the level of E. coli O157:H7 in 

contaminated servings (dose). 

Preparation Module 

The preparation module primarily consists of creating, storing, and cooking ground beef 

servings. In the correlation analysis, storage temperature, proportion of ground beef that is 

frozen, and the amount of growth during storage were the most influential factors contributing to 

the occurrence and extent of E. coli O157:H7 in consumed ground beef servings (Table 5-7). 

However, there was no demonstrated correlation with cooking temperature or the log reduction 

expected from cooking. Therefore, the effects of cooking temperature and storage conditions on 

the occurrence and extent of E. coli O157:H7 contamination in consumed ground beef servings 

is considered as part of “what if” scenarios (dependency analysis). 

Simulated Scenarios for Preparation

The following scenarios were considered: 

1. No growth during storage scenario—assumes that all ground beef servings are stored to 

ensure that no growth takes place at retail, from retail to the home/HRI, and while stored 

at the home/HRI. 

2. Cooking to 5 log reduction scenario—assumes that all ground beef servings are cooked 

to ensure at least a 5 log reduction in E. coli O157:H7 organisms. In this scenario, the 

median cooking distribution is applied except for those ground beef servings that would 

have less than a 5 log reduction. These ground beef servings are modeled such that a 5 

log reduction occurs. 

3. No growth during storage and 5 log reduction during cooking scenario—assumes all 

ground beef servings are stored to ensure that no growth takes place and, in addition, are 

all cooked to ensure at least a 5 log reduction in E. coli O157:H7 organisms. 

Results of the Simulated Scenarios for Preparation

Figure 5-5 shows the median exposure distribution from the baseline model and the resultant 

exposure distributions from each of the three scenarios in this sensitivity analysis. Each scenario 

results in a reduction in the prevalence of E. coli O157:H7-contaminated servings relative to the 

baseline scenario. The no growth during storage scenario results in a 7% decrease in the number 

of E. coli O157:H7-contaminated ground beef servings. The cooking to 5 log reduction scenario

results in a 93% decrease in the number of E. coli O157:H7-contaminated servings. The third 

scenario, combining the effect of no growth during storage and cooking to a 5 log reduction, 

results in a 99.99% decrease in the number of E. coli O157:H7-contaminated ground beef 

servings. 

Ensuring at least a 5 log reduction from cooking reduces the maximum number of E. coli

O157:H7 organisms per ground beef serving (dose) to which individuals could be exposed. 

Exposures that remain after all servings have at least a 5 log reduction applied demonstrate that 

there can be enough growth to overcome the effect of cooking. Ensuring that no growth takes 

place also reduces the maximum dose of E. coli O157:H7 in ground beef to which individuals 

could be exposed. In this case, there can be no more E. coli O157:H7 organisms in a ground beef 

serving than were originally present when the servings were generated from grinder loads. 

Because a small proportion (4% to 8%) of the U.S. population grossly undercooks (i.e., little or 

September 7, 2001 149 
5. Risk Characterization 

0.5 1.0 1.5 2.0 2.5 3.0

Logs of E. coli O157:H7

Frequency of Exposure

Baseline

No Growth

Cook to 5 Log Reduction

No Growth + 5 Log Reduction

0.999990

0.999991

0.999992

0.999993

0.999994

0.999995

0.999996

0.999997

0.999998

0.999999

1.000000

FIGURE 5-5 Reduction in the number of E. coli O157:H7 organisms per ground beef serving for 

three scenarios relative to a baseline scenario. One scenario assumes no growth of E. coli

O157:H7 during storage. The second scenario assumes that cooking of all products ensures at 

least a 5 log reduction. The third scenario combines no growth and a 5 log reduction from 

cooking. 

no log reduction in the number of E. coli O157:H7) ground beef servings, the no growth during 

storage scenario still allows exposure of up to 2 logs of E. coli O157:H7 per ground beef 

serving. 

Virtually no risk of E. coli O157:H7 illness exists if ground beef servings are handled in such 

a way that no growth occurs and are cooked in such a way as to ensure a minimum of a 5 log 

reduction in the number of E. coli O157:H7 organisms. Such a finding may be reassuring to 

consumers. However, since consumers do not have complete control over the product (i.e., 

storage conditions at retail), it is possible for sufficient growth to take place that a 5 log reduction 

through cooking is not enough to render the product safe.13

Comparing the effects of storage and cooking implied by this analysis suggests that ensuring 

adequate cooking may be more important than controlling the growth of E. coli O157:H7 in 

servings. Cooking was not identified in the correlation analysis. Demonstrating its importance, 

therefore, requires dependency analysis. Furthermore, this dependency analysis has clearly 

shown that controlling both cooking and growth can substantially reduce the probability of 

exposure to E. coli O157:H7 in ground beef. 

 

13FSIS recommends that consumers cook their hamburgers to 160o

F (internal product temperature) and use a meat 

thermometer. 

September 7, 2001 150 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

CONCLUSIONS 

The E. coli O157:H7 risk assessment is a practical tool that can be used to evaluate various 

intervention strategies to control and prevent the occurrence and extent of E. coli O157:H7 

contamination in ground beef. This risk characterization provides information on the risk of 

illness from E. coli O157:H7 in ground beef for an individual, a community, and the entire U.S. 

population. Variability in the population risk of illness from E. coli O157:H7 in ground beef is 

considered based on differences in seasonal exposure and age of the consumer. The risk 

characterization also provides information regarding which factors have the greatest influence on 

the occurrence of E. coli O157:H7 in combo bins, grinder loads, and ground beef servings and on 

subsequent risk of illness. The results of the risk characterization are summarized below. 

Risk of Illness from E. coli O157:H7 in Ground Beef 

• The lifetime risk of illness from E. coli O157:H7 in ground beef for the “typical” 

individual is between 1 in 8 million servings and 1 in 6 billion servings. A “typical” 

individual’s annual risk of illness from E. coli O157:H7 in ground beef is between 1 in 

600 million servings and 1 in 400 billion servings. 

• The E. coli O157:H7 risk assessment was used to evaluate a foodborne outbreak scenario 

for a community in which a grinder load of ground beef was stored improperly and the 

number of E. coli O157:H7 in it reached 5.5 logs per serving. If all of these servings were 

undercooked (e.g., served by the same restaurant) and individuals consume only one of 

these servings, then about 3,200 people would be expected to become ill. On the other 

hand, if all of these contaminated ground beef servings had been subjected to similar 

cooking conditions that resulted in a decrease of 5.5 logs, only 12 people would be 

expected to become ill from E. coli O157:H7. 

• The annual risk of illness from E. coli O157:H7 in ground beef for the general U.S. 

population is nearly 1 illness in 1 million servings of ground beef (9.6 × 10-7). This 

corresponds to a risk of being hospitalized and recovering of 2.0 × 10-8 per serving, 

developing HUS and recovering of 4.2 × 10-9 per serving, and death of 5.9 × 10-10 per 

serving. 

• Most contaminated cooked ground beef servings contain only 1 E. coli O157:H7 

organism (5.5 × 10-5). The probability of illness given an exposure of 1 E. coli O157:H7 

organism in a ground beef serving is low (1.7 × 10-4). This results in a low risk of illness 

(9.5 × 10-9) from E. coli O157:H7 in a ground beef serving. 

• Few contaminated cooked ground beef servings contain 100,000 E. coli O157:H7 

organisms per serving (1.8 × 10-7). The probability of illness at this dose is 0.58. This 

results in the highest risk of illness (1.0 × 10-7) from E. coli O157:H7 in a ground beef 

serving (see Table 5-1 and Figure 5-1). 

• Reducing the number of E. coli O157:H7-contaminated ground beef servings reduces the 

risk of illness more than reducing the amount of E. coli O157:H7 in contaminated 

servings. 

Population Risk Variabilty 

• The risk of E. coli O157:H7 illness is about three times higher during June to September 

than during October to May. 

September 7, 2001 151 
5. Risk Characterization 

• The risk of E. coli O157:H7 illness is estimated to be about 2.5 times higher for children 

ages 0 to 5 (2.4 × 10-6 per serving) than for the general U.S. population (9.6 × 10-7). This 

estimate is based on the assumption that children under 5 years of age are more 

susceptible to illness from exposure to E. coli O157:H7 since they consume only about 

7% of all ground beef servings and smaller serving sizes. 

Sensitivity Analysis 

Correlation Analysis 

• The size of the E. coli O157:H7-contaminated carcass surface area is an important factor 

that most influences the occurrence of E. coli O157:H7 in steer/heifer combo bins (see 

Sensitivity Analysis, Table 5-2). 

• The size of the E. coli O157:H7-contaminated carcass surface area and the effects of 

carcass chilling are factors that most influence the occurrence of E. coli O157:H7 in 

cow/bull combo bins (see Sensitivity Analysis, Table 5-3). 

• The occurrence and extent of E. coli O157:H7 contamination in cow/bull and steer/heifer 

combo bins, the size of the E. coli O157:H7-contaminated carcass surface area, and the 

effects of carcass chilling are factors that most influence the occurrence of E. coli

O157:H7 in grinder loads (see Sensitivity Analysis, Table 5-4). 

• The occurrence of E. coli O157:H7 in grinder loads and in steer/heifer combo bins are 

factors that most influence the occurrence of E. coli O157:H7 in uncooked ground beef 

servings (see Sensitivity Analysis, Table 5-5). 

• The number of E. coli O157:H7 organisms in steer/heifer combo bins and grinder loads 

as well as the maximum population density for E. coli O157:H7 per ground beef serving, 

growth of E. coli O157:H7 during storage and handling, storage temperatures, and the 

percent of ground beef that was frozen are factors that most influence the occurrence and 

extent of E. coli O157:H7 in consumed ground beef servings (see Sensitivity Analysis, 

Table 5-6). 

Dependency Analysis 

• If steam pasteurization was 100% effective (e.g., always resulted in a 2.5 log reduction in 

the number of E. coli O157:H7 organisms on carcasses), then the number of E. coli

O157:H7-contaminated combo bins would decline by 90% compared with the baseline 

scenario. This was the most effective scenario considered in reducing the number of E. 

coli O157:H7-contaminated combo bins. 

• If decontamination following dehiding always maintained a maximum effectiveness of a 

1.2 log reduction in the number of E. coli O157:H7 organisms on carcasses, then the 

number of E. coli O157:H7-contaminated combo bins would decrease 80% (see 

Sensitivity Analysis, Figure 5-4). 

• Reducing feedlot prevalence by 50% results in a 77% reduction in the number of E. coli

O157:H7-contaminated combo bins. A similar reduction in within-feedlot prevalence 

results in only a 70% reduction in the number of E. coli O157:H7-contaminated combo 

bins (see Sensitivity Analysis, Figure 5-5). 

• Carcass chilling had little effect on the number of E. coli O157:H7-contaminated combo 

bins but had a large effect on the amount of E. coli O157:H7 in contaminated combo 

September 7, 2001 152 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

bins. Large numbers of E. coli O157:H7 organisms in combo bins are primarily the result 

of occasionally high numbers of E. coli O157:H7 on chilled carcasses (e.g., improper 

chilling) (see Sensitivity Analysis, Figure 5-6). 

• Both growth of E. coli O157:H7 in contaminated ground beef servings during storage and 

reduction in the number of E. coli O157:H7 organisms during cooking are factors that 

most influence the occurrence and extent of E. coli O157:H7 contamination in ground 

beef servings. The dependency analysis indicates that adequate cooking may be more 

important than controlling the growth of E. coli O157:H7 in ground beef servings. 

Virtually no risk of E. coli O157:H7 illness exists from ground beef servings that are 

stored and handled under conditions that do not allow growth to occur and are 

sufficiently cooked to ensure a minimum of a 5 log reduction in the number of E. coli

O157:H7 organisms (see Sensitivity Analysis, Figure 5-5). 

LIMITATIONS 

When approaching this risk assessment, it is important to understand its scope, purpose, and data 

limitations. First, the scope of this risk assessment was limited to ground beef because 

epidemiological evidence indicated it was the primary foodborne vehicle for exposure to E. coli

O157:H7 (see Chapter 2). Ground beef servings were those from patties, sandwiches, meat loaf, 

and meatballs in which the ground beef could potentially be undercooked and have viable E. coli

O157:H7. Foods consisting of granulated ground beef and intact and nonintact (e.g., tenderized) 

cuts of beef, such as steaks and roasts, were not included in the risk assessment. These foods 

were excluded because the associated risk of exposure to E. coli O157:H7 is thought to be low 

based on epidemiological evidence and input from the National Advisory Committee for 

Microbiological Criteria for Foods (NACMF, December 2000). This risk assessment, however, 

will be used to develop risk assessments for E. coli O157:H7 in other beef products (e.g., 

nonintact beef). 

Second, the effect of differences in the food matrix on E. coli O157:H7 survival and growth 

were not included in this risk assessment because of lack of data. Although the included ground 

beef products are similar, matrix differences such as salt, water activity, pH, and spices likely 

vary between these foods. 

Third, the contribution of cross-contamination to E. coli O157:H7 exposure was also not 

included due to a lack of data. For example, there is little to no information about the proportion 

of foodborne outbreaks or sporadic cases of E. coli O157:H7 infection that are due to exposure to 

a nonbeef food item that was cross-contaminated by beef (e.g., lettuce). Cross-contamination of 

salad bar and other food items was thought to be the cause of four outbreaks that occurred in four 

separate restaurants in two states during 1993–1994 (Jackson et al. 2000). Interestingly, the 

implicated beef item in these outbreaks was not ground beef but was an intact cut of beef that 

was tenderized by maceration at the restaurant. 

Fourth, the derivation of the dose-response function in hazard characterization was based on 

E. coli O157:H7 illnesses in the general population without further differentiation for sensitive 

subpopulations, such as children or the elderly. While it was assumed that children ages 0 to 5 

are more susceptible and might have a dose-response function similar to the E. coli O157:H7 

dose-response upper bound function (derived from Shigella dysenteriae clinical studies), 

supporting foodborne illness surveillance data are needed to validate this assumption. 

Finally, the derived E. coli O157:H7 dose-response function did not take into consideration 

any differences in pathogenicity among E. coli O157:H7 strains. 

September 7, 2001 153 
5. Risk Characterization 

RESEARCH NEEDS 

An important benefit of conducting a risk assessment is the identification of data and knowledge 

gaps. Through the collection and evaluation of data for this risk assessment, it became apparent 

that specific information and data would enhance the certainty of the risk assessment estimates. 

The determination of which data would be most beneficial is based on areas identified as 

important (sensitivity analysis) and for which there is limited information. Food safety research 

needed to fill existing data gaps and enhance this risk assessment is discussed below. 

Hazard Identification 

• Information on the maximum density of E. coli O157:H7 organisms in ground beef 

servings as a result of matrix effects, competitive microflora in ground beef, and 

environmental conditions (e.g., pH, water activity).14

• Predictive microbiological data on the increase and decrease in the number of E. coli

O157:H7 organisms in ground beef under various storage and preparation conditions 

along with frequencies of occurrence of these storage and preparation conditions. 

Exposure Assessment 

• Additional information on E. coli O157:H7 contamination on carcasses following 

dehiding. 

• Data on cross-contamination of E. coli O157:H7 between carcasses during carcass 

splitting. 

• Time-temperature data (quantitative) for chillers in slaughter establishments. 

• Marketing data on the proportion of beef ground at slaughter versus at retail. 

• Data on retail (HRI) and consumer storage, cooking, and consumption (frequency and 

serving size) patterns by type of ground beef meal (e.g., grilled hamburger in July and 

baked meat loaf in October). 

Hazard Characterization (Dose-Response Data) 

• Number and severity of illness among children ages 0 to 5 from E. coli O157:H7 in 

ground beef (response data). These data may come from surveillance data or from 

foodborne outbreak data.15

• Dose-response data from foodborne outbreaks of E. coli O157:H7 in ground beef 

servings (e.g., the number of E. coli O157:H7 organisms in a serving and resulting 

severity of illness). 

 

14There is considerable uncertainty regarding the maximum population density in ground beef servings due to 

competitive microflora (see Chapter 3). The risk assessment includes an uncertainty range of 5 to 10 logs of E. 

coli O157:H7 for the maximum population density in ground beef servings. 

15For all outbreaks, the line listing should include month and year of occurrence and the number of ill persons per 

outbreak. For foodborne outbreaks, the line listing should include month and year of outbreak occurrence, county 

and state of occurrence, number of ill persons, number hospitalized, number with severe outcome (e.g., 

stillbirth/miscarriage for Listeria monocytogenes, HUS/TTP for E. coli O157:H7), number of deaths, specific 

vehicle implicated (e.g., not just “beef” but ground beef, roast beef etc.), and detailed comments about sensitive 

subpopulations, (e.g., immunocompromised persons in an outbreak of L. monocytogenes, ages of persons with 

HUS, age and health status of persons who died). 

September 7, 2001 154 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

• Descriptive epidemiologic information about sporadic cases of E. coli O157:H7 illness, 

including the month of disease onset, age, sex, hospitalizations, summary of clinical 

manifestations including severe disease manifestations, and food vehicles involved (if 

known). 

• Additional case-control studies of sporadic E. coli O157:H7 cases to calculate etiologic 

fraction attributable to ground beef. 

REFERENCES 

Audits International. 1999. U.S. Cold Temperature Evaluation. Unpublished data. 

Bell, B.P., M. Goldoft, P.M. Griffin, M.A. Davis, D.C. Gordon, P.I. Tarr, C.A. Bartleson, J.H. 

Lewis, T.J. Barrett, J.G. Wells, R. Baron, and J. Kobayashi. 1994. A multistate outbreak of 

Escherichia coli O157:H7-associated bloody diarrhea and hemolytic uremic syndrome from 

hamburgers: The Washington experience. JAMA 272(17):1349-1353. 

Cassin, M.H., A.M. Lammerding, E.C. Todd, W. Ross, and R.S. McColl. 1998. Quantitative risk 

assessment of Escherichia coli O157:H7 in ground beef hamburgers. Int J Food Microbiol 

41:21-44. 

Food and Drug Administration (FDA). 1999. 1999 Food Code. (Available at: 

http://vm.cfsan.fda.gov/~dms/foodcode.html). 

Jackson, L.A., W.E. Keene, J.M. McAnulty, E.R. Alexander, M. Diermayer, M.A. Davis, K. 

Hedberg, J. Boase, T.J. Barrett, M. Samadopour, and D.W. Fleming. 2000. Where's the beef? 

The role of cross-contamination in 4 chain restaurant-associated outbreaks of Escherichia 

coli O157:H7 in the Pacific Northwest. Arch Intern Med 160(15):2380-2385. 

Marks, H.M., M.E. Coleman, C.T.J. Lin, and T. Roberts. 1998. Topics in risk assessment: 

Dynamic flow tree process. Risk Anal 18:309-328. 

Mead, P.S., L. Slutsker, V. Dietz, L.F. McCaig, J.S. Bresee, C. Shapiro, P.M. Griffin, and R.B. 

Tauxe. 1999. Food-related illness and death in the United States. Emerg Infect Dis 

5(5):607-625. 

Sage, J.R., and S.C. Ingham. 1998. Survival of Escherichia coli O157:H7 after freezing and 

thawing in ground beef patties. J Food Prot 61(9):1181-1183. 

Tuttle, J., T. Gomez, M.P. Doyle, J.G. Wells, T. Zhao, R.V. Tauxe, and P.M. Griffin. 1999. 

Lessons from a large outbreak of Escherichia coli O157:H7 infections: Insights into the 

infectious dose and method of widespread contamination of hamburger patties. Epidemiol 

Infect 122:183-192. 

September 7, 2001 155 

Appendix A 

Anchoring of Model Parameters 

INTRODUCTION 

The Escherichia coli O157:H7 risk assessment model is essentially a process risk model that 

describes the occurrence and levels of this pathogen across the farm-to-table continuum. All such 

models include parameters that are intended to be deterministic. However, knowledge about 

these parameters is often uncertain. 

The resolution for each model parameter depends on the quantity and quality of the data 

available about that parameter. Different data types and sources are often used to estimate the 

various parameters in the model. As described in this report, each E. coli O157:H7 risk 

assessment model parameter was independently calibrated from available evidence and scientific 

knowledge. During the model development stage, however, parameter calibration did not include 

consideration of the model outputs. 

Because the parameters are independently calibrated from data of varying quality and 

quantity, it is expected that there are combinations of these parameters that, when used in the 

model, predict outcomes that are entirely inconsistent with what has been observed. The 

knowledge used to describe the uncertainty about parameters before running the model is less 

than that available after running the model. After running the model, it becomes clear that some 

parameter values are not feasible given the available evidence about the model’s output. These 

infeasible values, or combinations of values, should be used to improve the resolution of the 

input parameters and, consequently, the model’s predictions. The evidence used to define 

infeasible values is often referred to as validation data. 

One output of the E. coli O157:H7 risk assessment model for which validation data exist is 

the prevalence of E. coli O157:H7-contaminated grinder loads. Since 1994, the Food Safety and 

Inspection Service (FSIS) has treated various raw chopped or ground beef products that contain 

E. coli O157:H7 as adulterated under the Federal Meat Inspection Act unless they are further 

processed in a manner that destroys this pathogen. In October 1994, FSIS initiated a 

September 7, 2001 157 
Appendix A: Anchoring of Model Parameters 

microbiological testing program for E. coli O157:H7 in raw ground beef in meat plants and retail 

stores. The testing program operated under FSIS Notice 50-94, issued December 23, 1994, until 

the agency issued FSIS Directive 10,010.1 on February 1, 1998. Based on the low concentrations 

of E. coli O157:H7 recovered from samples of frozen ground beef patties identified in a 1993 

outbreak, FSIS increased the sample size from 25 grams to 325 grams in FY 1998 to enhance 

efficiency and the likelihood of detecting pathogens in raw ground beef sold to consumers. In 

September 1999, microbiologic testing was changed to include immunomagnetic separation 

methods. 

Approximately 1,900 plants under FSIS inspection produce ground beef. Each month, FSIS 

randomly selects an appropriate number of inspected plants for sample collection. The sampling 

plan is based on information from Centers for Disease Control and Prevention (CDC) sentinel 

sites, historic data on foodborne illness outbreaks, and other information. If a plant initiates its 

own routine sampling program, has a certification from suppliers that the product was tested, or 

uses in-plant validated pathogen reduction interventions on beef carcasses, FSIS will not collect 

samples. 

The ground beef sampling data can only calibrate those parts of the model that describe 

events leading up to the creation of grinder loads. Therefore, most of the parameters described 

for the preparation module are not informed by these data. Nevertheless, because the inputs to 

the preparation module are calibrated, its outputs are influenced by these data. The outputs 

include distributions that describe the frequency of exposure to different doses of E. coli

O157:H7 in ground beef servings. 

METHODS 

Uncertainty about each model input is described in the three exposure assessment modules. 

Various probability density functions are used to capture this input uncertainty. Generically, 

these distributions are summarized by p

⎝

⎛ ⎠⎞ ^

θ | y ^

θ , where ^

θ represents a vector of all i inputs and 

 is the evidence available to estimate each (Green et al. 2000). θ y ˆ θ i

ˆ

Before the production and slaughter modules are run, uncertainty about the prevalence of 

contaminated grinder loads is based on 2000 FSIS ground beef sampling data (Table A-1). These 

data are used because they represent an entire year, incorporate the same sampling and testing 

methods, and are based on very sensitive culture methods. 

Ground beef sampling results depict apparent prevalence. As noted previously, apparent 

prevalence is less than true prevalence because sample size and culture methods do not ensure 

that every sample from a contaminated source contains organisms or that the laboratory methods 

will detect those organisms present in the sample. The FSIS sampling data—when assumed to be 

beta distributed (Vose 1996)—predict the mean annual apparent prevalence as 0.52% with 5th 

and 95th percentile values of 0.36% and 0.71%, respectively. The seasonal results demonstrate 

that there were significantly more positive samples in the high prevalence season (June to 

September) than in the low prevalence season (October to May). 

This output uncertainty can be generically summarized as p(φ|yφ), where φ is the prevalence 

of positive ground beef samples given yφ, the appropriate seasonal sampling evidence. 

September 7, 2001 158 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

TABLE A-1 FSIS Ground Beef Sampling Results for 2000. These 325-gram samples were 

collected in federally inspected ground beef processing plants. 

Season Positive Tested 

5th 

Percentile Mean 

95th 

Percentile 

Low prevalence (October–May) 10 3,139 0.20% 0.35% 0.54% 

High prevalence (June–September) 13 1,447 0.59% 0.97% 1.42% 

Annual 23 4,586 0.36% 0.52% 0.71% 

A method for calibrating process models using input and output uncertainty has been 

reported (Green et al. 2000). Before running the model, the joint probability of the inputs and 

outputs is represented by ( ) ,| ˆ , ˆ = φ θ θφ yyp ( ) φ φ | yp ( ) θ θ ˆ | ˆ × yp . In other words, the probability 

of different combinations of input values and output values is predicted independently from each 

input and output distribution. Before running the model, therefore, the joint probability of a more 

likely input value and a more likely output value is greater than the joint probability of less likely 

values from the input or output distribution or both. 

When simulated in sequence, the production and slaughter modules generate distributions for 

levels of E. coli O157:H7 in combo bins. The preparation module simulates mixing combo bins 

to generate grinder loads with varying levels of E. coli O157:H7. For calibration, the model 

output of interest is the prevalence of positive samples from grinder loads. 

Sampling from grinder loads is simulated to mimic the FSIS methods by assuming 325-gram 

samples and the current FSIS culture methods. The probability that a sample contains x

organisms is predicted by Poisson (325 × GLC), where GLC is the grinder load concentration 

described in the preparation module. The probability of a positive test equals where s

is the probability that laboratory methods detect a single organism in a sample. 

)1(1 ,

x −− s

Evidence concerning the likelihood of detecting E. coli O157:H7 in ground beef comes from 

an experimental study (Okrend et al. 1990). In that study, 25-gram samples of ground beef were 

each inoculated with an average of 18 E. coli O157:H7, and eight of nine samples (89%) were 

positive. The probability of a positive sample was assumed to equal 1 – (1 – s)

18. In this case, s

equaled 0.11. The 2000 FSIS sampling results reflect the use of immunomagnetic separation 

methods in addition to culture. On the basis of discussions with FSIS microbiologists, it is 

assumed that s is four times greater than methods described in Okrend et al. (1990). 

The model selects random combinations of inputs to predict an output. Therefore, the model 

(M) transforms inputs into outputs (i.e., ). Before running the model, all combinations 

of inputs and outputs were possible. After running the model, certain combinations are not 

supported. For example, combinations of inputs that predict high prevalence and high levels of 

E. coli O157:H7 in combo bins cannot result in a model prediction of low apparent prevalence in 

ground beef. The joint probability of these combinations must be zero. The joint probabilities of 

combinations that are supported by the model are proportional to their premodel probabilities. 

Therefore, the most feasible combinations are those that predict apparent prevalence levels 

consistent with the sampling evidence. 

) →φθˆ M (

To calibrate the model, the following steps are taken: 

1. A random draw from each uncertain parameter is taken. 

2. The production, slaughter, and preparation modules are simulated for 10,000 iterations 

each. 

September 7, 2001 159 
Appendix A: Anchoring of Model Parameters 

3. For each grinder load concentration (GLCi) simulated, the probability of a positive test is 

calculated as (+) = , where s = 0.44 and i PGLC )(])1(1[

0

xfs x

xi

∑

∞

=

×−−

!

)GLC325( )(

GLC325

x

e xf i x

i

×− ×× = . 

4. The prevalence of positive ground beef samples is calculated as 

, where is the frequency of each GLC (in halflog increments) predicted by the model. 

=+ ∑ ×+ max

min

GLC

GLC

GLC )( )GLC()( i P fP i GLC( )i f

5. If the calculated P(+) for the simulation is less than the 95th percentile of the FSIS 

ground beef sampling evidence for the appropriate season (Table A-1), then the 

simulation is considered to represent a feasible combination of inputs. Otherwise, that 

combination is considered infeasible. 

6. If the calculated P(+) for the simulation is less than the 5th percentile of the FSIS ground 

beef sampling evidence for the appropriate season (Table A-1), then each GLCi is 

incrementally increased by 0.5 logs until P(+) is as close to the mean of the ground beef 

sampling evidence as possible. This adjustment serves to estimate the effect of the 

fabrication step of the slaughter module. 

7. Steps 1 through 6 are repeated until a sufficient set of feasible combinations is collected. 

The feasible set of production and slaughter inputs is perpetuated through the preparation module 

to predict exposure distributions. 

RESULTS 

Figure A-1 shows the similarity between the distribution for prevalence of positive ground beef 

samples based on FSIS sampling evidence for the low prevalence season and that estimated after 

running the model. The central tendency of the distribution based solely on the sampling 

evidence is slightly less compared with the model distribution’s central tendency. Nevertheless, 

the difference in means from the two distributions is negligible (0.35% vs. 0.36%). 

Figure A-2 shows a similar relationship for the high prevalence season. The FSIS sampling 

evidence and the distribution predicted by the model overlap considerably. The means of the two 

distributions are also very similar (0.96% for the FSIS sampling evidence and 0.94% for the 

model distribution). 

Differences observed between the two distributions are primarily a result of the fabrication 

algorithm wherein half-log increments are added to grinder concentrations. Half-log increments 

were chosen primarily for convenience but can result in substantial shifts in the modeled values. 

More precise overlap between the sampling evidence and model might be achieved by using 

more refined increments. Furthermore, the model output is based on a set of 100 feasible 

simulations. More simulations would also refine the model’s distribution. 

September 7, 2001 160 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

0.00% 0.20% 0.40% 0.60% 0.80% 1.00%

Prevalence of Positive Ground Beef Samples

during Low Prevalence Season (October–May)

Probability

FSIS sampling

evidence

Model distribution

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

FIGURE A-1 Comparison of probability distributions for apparent prevalence of E. coli O157:H7-

contaminated grinder loads using the FSIS sampling evidence (Table A-1) and the risk 

assessment model. These distributions are based on sampling evidence and model simulations 

for the low prevalence season. 

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.00% 0.50% 1.00% 1.50% 2.00% 2.50%

Prevalence of Positive Ground Beef Samples

during High Prevalence Season (June–September)

Probability

FSIS sampling

evidence

Model distribution

FIGURE A-2 Comparison of probability distributions for apparent prevalence of E. coli O157:H7-

contaminated grinder loads using the FSIS sampling evidence (Table A-1) and the risk 

assessment model. These distributions are based on sampling evidence and model simulations 

for the high prevalence season. 

REFERENCES 

Green, E.J., D.W. MacFarlane, and H.T. Valentine. 2000. Bayesian synthesis for quantifying 

uncertainty in predictions from process models. Tree Physiology 20:415-419. 

September 7, 2001 161 
Appendix A: Anchoring of Model Parameters 

Okrend, A.J.G., B.E. Rose, and R. Matner. 1990. An improved screening method for the 

detection and isolation of Escherichia coli O157:H7 from meat, incorporating the 3M 

petrifilm test kit—HEC—for hemorrhagic Escherichia coli O157:H7. J Food Prot 

53(11):936-940. 

Vose, D.J. 1996. Quantitative Risk Analysis: A Guide to Monte Carlo Simulation Modeling. 

West Sussex, England: John Wiley & Sons, Ltd. 

September 7, 2001 162 
Appendix B 

Summary of Human Clinical Trials of Foodborne Pathogens 

Potential Surrogate Pathogens 

for E. coli O157:H7 

(strain or serotype) 

Number 

of Dose 

Groups 

Total Number 

of Human 

Volunteers 

Lowest Dose 

Tested and 

with Illness Reference 

1. S. dysenteriae (M131)a 4 30b 10, 10 Levine et al. 1973 

2. S. dysenteriae (A-1)c 2 10 2x102, 2x102 Levine et al. 1973 

3. S. flexneri (2457T)

d 5 43 104

, 104 DuPont et al. 1969 

4. S. flexneri (2457T) 4 197 105, 105 DuPont et al. 1972 

5. S. sonnei (53G)e 1 20, 38 500, 500 DuPont et al. 1989 

6. Enteropathogenic E. coli

wild type (O111:NM, 

B1718)f

 + bicarbonate 

3 13g 5x108

, 5x108 Bieber et al. 1998 

7. Enteropathogenic E. coli

(O142:H6)h

 + bicarbonate

3 15i 106, 106 Levine et al. 1978 

8. Enteropathogenic E. coli

(O128:H6)j

 + bicarbonate 

3 15 Avirulent at 

106-10

Levine et al. 1978 

9. Enteropathogenic E. coli

(O127:H6)k

 + bicarbonate 

2 9 106

, 1010 Levine et al. 1978 

10. Enterotoxigenic E. coli

(O78:H11)l

 + bicarbonate 

2 14m 106, 106 Evans et al. 1978 

11. Enterotoxigenic E. coli

(non-typable)n

3 14o 106, 108 Levine et al. 1977 

12. Enterotoxigenic E. coli

(O148:H28)p

2 17q 106, 106 Levine et al. 1979 

13. Enterotoxigenic E. coli

(O25:NM)r

1 6o 109, 109 Levine et al. 1979 

September 7, 2001 163 
Appendix B: Summary of Human Clinical Trials of Foodborne Pathogens 

Potential Surrogate Pathogens 

for E. coli O157:H7 

(strain or serotype) 

Number 

of Dose 

Groups 

Total Number 

of Human 

Volunteers 

Lowest Dose 

Tested and 

with Illness Reference 

14. Infant diarrheal E. coli

(O111, B4, H) 

4 46s 106, 106 June et al. 1953 

15. Infant diarrheal E. coli

(O111, B4, H) 

4 46s 108, 108 June et al. 1953 

16. Infant diarrheal E. coli

(O111, B5) 

1 1t 108, 108 Ferguson and June 

1952, citing Neter 1950 

17. Infant diarrheal E. coli

(O111, B5) 

1 6 109, 109 Ferguson and June 

1952, citing Kirby 1950 

18. Infant diarrheal E. coli

(O111, B5) 

1 3 Avirulent at 

1010

Ferguson and June 

1952, citing Kirby 1950 

19. Commensal E. coli 2 19 Avirulent at 

~1010

June et al. 1953 

20. Commensal E. coliu + 

bicarbonate 

1 4 Avirulent at 

1010

Levine et al. 1978 

a

Isolated from feces of patient in Guatemala with severe dysentery from 1970 pandemic and administered in milk. b

Fasting male prison volunteers. 

c

Isolated from feces of patient in Guatemala with mild dysentery and administered in milk. 

d

Isolated from feces of patient in Japan and administered in milk. 

e

Isolated from feces of 5-year-old patient in Japan and administered in milk. f

Isolated and administered in phosphate buffered saline with sodium bicarbonate. g

Fasting volunteers, 18 to 48 years of age. 

h

Isolate infant diarrheal strain from UK hospitals (Glasgow, E851/71) and administered with bicarbonate in saline; 

virulent at each of 3 doses administered. 

i

Healthy adult volunteers, mean age 24 years, 90-minute fast pre- and post-treatment. 

j

Isolate infant diarrheal strain from UK hospitals (Teesside, E74/68) and administered with bicarbonate in saline; 

avirulent in 15 healthy adults tested. k

Isolate infant diarrheal strain from UK residential nursery (Taunton, E2348/69) and administered with bicarbonate 

in saline; virulent at 1 of 2 doses administered. l

Isolated from severe non-Vibrio cholera case in Bangladesh. mMale and female student volunteers, mean age 23. 

n

Isolated from physician traveling in Mexico with traveler’s diarrhea and administered in milk with 2.5 hour fast 

intervals before and after treatment. o

Student volunteers, 18 to 29 years of age. 

p

Isolated from U.S. soldier in Vietnam with diarrhea and administered with bicarbonate in buffer. q

Healthy adult volunteers, mostly students, mean age 25, range 18 to 41 years of age. r

Isolated from physician traveling in Mexico with traveler’s diarrhea and administered in milk with 2.5 hour fast 

intervals before and after treatment. s

Presumably fasting male prison volunteers, 16 to 48 years of age. 

t

Two-month old infant administered 108 organisms and developed diarrhea and weight loss within 24 hours. u

Nonpathogenic isolate from healthy laboratory scientist, administered in bicarbonate at 1010 in saline; avirulent in 

all four volunteers. 

September 7, 2001 164 
Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef 

REFERENCES 

Bieber, D., S.W. Ramer, C.-Y. Wu, W.J. Murray, T. Tobe, R. Fernandez, and G.K. Schoolnik. 

1998. Type IV pili, transient bacterial aggregates, and virulence of enteropathogenic 

Escherichia coli. Science 280:2114-2118. 

Dupont, H.L., R.B. Hornick, A.T. Dawkins, M.J. Snyder, and S.B. Formal. 1969. The response 

of man to virulent Shigella flexneri 2a. J Infect Dis 119:296-299. 

Dupont, H.L., R.B. Hornick, M.J. Snyder, J.P. Libonati, S.B. Formal, and E.J. Gangarosa. 1972. 

Immunity in Shigellosis II. Protection induced by oral live vaccine or primary infection. 

J Infect Dis 125(1):12-16. 

DuPont, H.L., M.M. Levine, R.B. Hornick, and S.B. Formal. 1989. Inoculum size in shigellosis 

and implications for expected mode of transmission. J Infect Dis 159(6):1126-1128. 

Evans, D.G., D.J. Evans, Jr., W.S. Tjoa, and H.L. Dupont. 1978. Detection and characterization 

of colonization factor of enterotoxigenic Escherichia coli isolated from adults with diarrhea. 

Infect Immun 19:727-736. 

Ferguson, W.W., and R.C. June. 1952. Experiments on feeding adult volunteers with Escherichia 

coli 111, B5, a coliform organism associated with infant diarrhea. Am J Hyg 55(2):155-169. 

June, R.C., W.W. Ferguson, and M.T. Worfel. 1953. Experiments in feeding adult volunteers 

with Escherichia coli 55, B5, a coliform organism associated with infant diarrhea. Am J Hyg 

57:222-236. 

Levine, M.M., H.L. DuPont, S.B. Formal, R.B. Hornick, A. Takeuchi, E.J. Gangarosa, M.J. 

Snyder, and J.P. Libonati. 1973. Pathogenesis of Shigella dysenteriae 1 (Shiga) dysentery. 

J Infect Dis 127(3):261-270. 

Levine, M.M., E.S. Caplan, D. Waterman, R.A. Cash, R.B. Hornick, and M.J. Snyder. 1977. 

Diarrhea caused by Escherichia coli that produce only heat-stable enterotoxin. Infect Immun 

17(1):78-82. 

Levine, M.M., E.J. Bergquist, D.R. Nalin, D.H. Waterman, R.B. Hornick, C.R. Young, and 

S. Sotman. 1978. Escherichia coli strains that cause diarrhoea but do not produce heat-labile 

or heat-stable enterotoxins and are non-invasive. Lancet 1(8074):1119-1122. 

Levine, M.M., D.R. Nalin, D.L. Hoover, E.J. Bergquist, R.B. Hornick, and C.R. Young. 1979. 

Immunity to enterotoxigenic Escherichia coli. Infect Immun 23(3):729-736. 

September 7, 2001 165