Potential Public Health Impact 

of Salmonella and Campylobacter

Performance Guidance for Young 

Chickens and Turkeys

Prepared by:

Risk Assessment Division

Office of Public Health Science

Food Safety and Inspection Service

U.S. Department of Agriculture

January 2011 
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

2 

Table of Contents

Purpose..................................................................................................................................................................... 3

Background............................................................................................................................................................... 3

Methods................................................................................................................................................................... 4

Data sources......................................................................................................................................................... 5

Results...................................................................................................................................................................... 9

Salmonella............................................................................................................................................................ 9

Salmonella on young chickens...........................................................................................................................10

Salmonella on young turkeys.............................................................................................................................11

Campylobacter...................................................................................................................................................11

Campylobacter on young chickens ....................................................................................................................12

Campylobacter on young turkeys......................................................................................................................13

Discussion ...............................................................................................................................................................13

References and Data Sources................................................................................................................................. 15

Table of Tables 

Table 1. Data source and methods used for estimating illnesses from Campylobacter and Salmonella attributed to

young chickens and turkeys in the U.S. population......................................................................................................8

Table 2. Data used to estimate the number of illnesses avoided due to the implementation of the proposed 

Salmonella guidance for young chickens....................................................................................................................10

Table 3. Data used to estimate the number of illnesses avoided due to the implementation of the proposed 

Salmonella guidance for young turkeys......................................................................................................................11

Table 4. Data used to estimate the number of illnesses avoided due to the implementation of the proposed 

Campylobacter guidance for young chickens.............................................................................................................12

Table 5. Data used to estimate the number of illnesses avoided due to the implementation of the proposed 

Campylobacter guidance for young turkeys...............................................................................................................13

Table of Figures 

Figure 1. Change in the proportion of young chicken establishments that pass the existing Salmonella standard of 

12 or fewer positive samples out of a 51-sample set................................................................................................... 7

Figure 2. Estimates of the annual number of Salmonella illnesses avoided (top) and the proportion of production 

establishments that would pass the new guidance based on the YCBS....................................................................... 9

Figure 3. The number of Salmonella illnesses avoided increases linearly with the value of α in the young chicken 

model..........................................................................................................................................................................11

Figure 4. The number of Campylobacter illnesses avoided increases linearly with the value of α in the young 

chicken model.............................................................................................................................................................13
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

3 

Purpose

This document outlines methods and results to estimate the potential public health impact of revised 

performance guidance for Salmonella and new performance guidance for Campylobacter for young chickens and 

turkeys1

This document is not a risk assessment; it is an illustrative example of potential human illnesses that might be 

avoided given implementation of new performance guidance for Salmonella and Campylobacter. At this time, 

FSIS is proposing guidance that does not require a risk assessment to implement. Although the estimates

developed in this document represent part of a risk assessment, there are important elements that are not 

included here that are necessary to complete a risk assessment. In particular, this document does not consider 

uncertainty about the estimates nor does it complete a sensitivity analysis of the underlying model. Therefore, the 

estimates provided should be considered illustrative.

. The Food Safety and Inspection Service (FSIS) also examined the countervailing effect of these 

approaches by estimating the number of slaughter establishments that will initially pass (not pass) the guidance. 

Background

A number of guidance options were considered by FSIS. In general, all guidance options involved sampling finished 

poultry (young chickens and turkeys) carcasses in federally-regulated poultry slaughter establishments for the 

presence of Salmonella and Campylobacter. These options describe different approaches to determining whether 

a tested establishment passes the guidance or not. 

The principal effect of any guidance option is to encourage industry to produce a safer product. Under FSIS’ 

current Salmonella policy, the names of poultry carcass establishments in either Category 2 or Category 3 are 

posted monthly on the FSIS website (FSIS, 2006). Past experience has demonstrated that the disincentives of FSIS 

guidance have persuaded the industry to expend the resources necessary to improve performance.

In general, public health improves as slaughter establishments reduce the occurrence of pathogens on their 

products, and so we assume a stricter guidance option will generate more public health benefits. The stricter the 

guidance (i.e., the fewer positive samples allowed in a set of samples) the more slaughter establishments will 

initially not pass the guidance. A stricter guidance equates to a lower allowable prevalence of contaminated 

carcasses, so the overall prevalence of contaminated carcasses will decline as more establishments pass the 

guidance. 

Among Salmonella-contaminated poultry carcasses, the number of Salmonella organisms (i.e., “level”) is generally 

low. However, human salmonellosis is often attributable to small numbers of Salmonella growing to infectious

doses between production and consumption, due to abusive storage and handling conditions. Therefore, because 

the occurrence of any Salmonella on a carcass poses a potential risk to consumers, guidance relates to prevalence 

i.e., presence or absence of pathogens among samples tested.

Among Campylobacter-contaminated poultry carcasses, there is substantial variability in numbers of 

Campylobacter organisms. Large counts, or “high levels,” of Campylobacter may be more important than its 

prevalence on carcasses, because Campylobacter are not expected to grow between production and consumption 

 

1 This document is a supporting report. It does not review the proposed policy and must be read in the context of the Federal 

Register Notice to which these polices refer.
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

4 

and, therefore, larger initial counts increase the chance that some viable organisms can survive cooking effects or 

cross-contaminate other food products. For this reason, FSIS’ Campylobacter guidance is based, in part, on higher 

levels of Campylobacter demonstrated on samples tested.

Methods

If a policy is expected to change the prevalence of contaminated carcasses at the end of production (as 

determined by a qualitative microbiological test), but is not expected to significantly change the levels of a 

pathogen on these contaminated carcasses, then estimates about public health gains from the policy are 

relatively straightforward. This scenario seems particularly apt in the case of Salmonella and poultry. The levels of 

Salmonella observed on contaminated carcasses are generally low already, so a policy that intends to reduce the 

prevalence of Salmonella among poultry carcasses is unlikely to substantially reduce the already low levels on 

those Salmonella-positive carcasses.

To estimate the annual average number of illnesses avoided (λ Avoided ) by a policy that reduces the prevalence of 

contaminated units, the following equation can be solved (Williams et al. 2011, Section 3.1)

( ) 1 

( )

new

Avoided ill

initial

P exp

P exp

λ λ     =     −

   

In this equation, λill represents the annual average number of illnesses (i.e., cases of salmonellosis or 

campylobacteriosis) occurring before the policy was implemented (i.e., the current “baseline” for the number of 

poultry illnesses). This input to the calculation is estimated from available public health surveillance evidence. In 

this formula, the prevalence of contaminated poultry carcasses prior to implementing the policy is ( ) P exp initial

and the prevalence following successful implementation of a prevalence-reducing policy is ( ) P exp new . 

This approach suggests that illnesses avoided by a prevalence-reducing policy are a simple proportion of the 

number of illnesses that occurred prior to implementing the policy. Such an approach is reasonable for estimating 

changes in sporadic illnesses within populations when prevalence of contamination changes (Vose, 2008; 

Bartholomew et al., 2005). 

FSIS also used the same approach to estimate the public health benefit of the proposed Campylobacter guidance, 

with the caveat that the proposed guidance for Campylobacter on young chickens requires a reduction in the 

prevalence of carcasses contaminated with higher levels of Campylobacter (i.e., detectable in one ml of rinsate). 

For guidance that determines whether an establishment passes or does not pass (based on a set of samples 

collected from the establishment), this analytic approach considers some fraction of establishments (or fraction of 

production volume) that initially pass (ω ). Before the guidance is implemented, 

P exp P exp P exp initial( ) ( )1 ( ) = +− ω ω pass ( ) fail , where ( ) and ( ) P exp P exp pass fail are the prevalence of 

contaminated carcasses among all slaughter establishments (or production volume) that would pass or fail the 

guidance, respectively. In other words, if the prevalence of contaminated carcasses within each of the U.S. poultry 

slaughter establishments was known, then it could be determined whether or not each establishment would pass 

the guidance. Furthermore, if we knew each establishment’s share of total U.S. poultry production (e.g., the 
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

5 

fraction of total young chickens produced per year by each young chicken establishment), then facilities could be 

pooled based on their classification of passing (or not) and the overall prevalence within each pool could be 

determined (e.g., ω is the sum of the fractions of total young chickens produced per year across all passing young 

chicken establishments). 

Once the guidance was implemented and establishments that did not pass were listed on the FSIS website, it is 

likely that some fraction,α , of those establishments not passing the guidance would change their production 

practices in order to pass the guidance. Over time, it is likely that these establishments would ultimately attain a 

prevalence of contaminated carcasses equal to those that pass FSIS’ guidance ( ( ) P exp pass ). Given this expected 

change, the estimated national prevalence of contaminated carcasses can be calculated based on the following 

equation; 

( ) ( ) ( ) ( ) ( )1 1 ( ) P exp new = +− ω α ωα P exp pass +− − ω α P exp fail . 

In other words, a new weighted average of the prevalence among passing and not passing establishments is 

calculated after some fraction of those establishments not passing have changed their practices so that they pass 

FSIS’ guidance (i.e., they are “passing”). 

This approach to estimating potential public health benefits (i.e., average number of human illnesses avoided per 

year by the guidance) requires data regarding the occurrence of pathogens across the poultry industry. These data 

can be analyzed to determine the inputs to this model. Nevertheless, the public health benefits of the guidance 

essentially depend on the perceived magnitude of the disincentive of being listed on the FSIS website to an 

establishment that currently does not pass the guidance. Although FSIS has some historic evidence regarding 

industry behavior in response to previous guidance measures (i.e., Salmonella HACCP verification program data 

and categorization of establishments in that program (FSIS, 2006)), the true behavior of the industry to new 

guidance is unknowable. Therefore, the value of the α parameter in the model is uncertain. Estimates of the 

number of illnesses ultimately avoided for both the Salmonella and Campylobacter guidance are provided across a 

range of possible levels of effectiveness (i.e., α values).

Data sources

Input values for , ( ) and ( ) ω P exp P exp pass fail were determined from FSIS’ Nationwide Microbiological Baseline 

Data Collection Programs: the Young Chicken Survey, which is here referred to here as the Young Chicken Baseline 

Survey, 2007-2008, (YCBS) (FSIS, 2007), the Young Turkey Survey, referred to here as the Young Turkey Baseline 

Survey, 2008-2009, (YTBS) (FSIS, 2008), and/or Salmonella HACCP verification program data from 2008-2009. As 

with past performance standards developed for commodity groups, these guidances are based on analyses of FSIS 

microbiological baseline survey data. For the Campylobacter guidance, only the baseline data were available. For 

the Salmonella guidance, the YCBS and the YTBS data were used to establish criteria for passing the guidance, but 

final estimates were based on the more current Salmonella HACCP verification program data. Estimates are based 

on the HACCP verification dataset because average Salmonella prevalence among young chicken carcasses has 

decreased since the collection of the baseline data in 2007-2008. Using the HACCP data as the starting point for 

examining the effect of the policy should help prevent overestimation of the potential public health benefit. 

The parameterω was defined as the proportion of total poultry carcasses produced per year that originated from 

passing establishments. Because production data were available for each establishment in the YCBS and YTBS data 
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

6 

and Salmonella HACCP verification program databases, calculation of ω was relatively straightforward once all 

establishments were classified as passing or not. Nevertheless, there is interest among decision-makers regarding 

the proportion of establishments (regardless of production volume) that would immediately be classified as 

passing under the new guidance because of their superior performance. This latter proportion is reported and 

denoted asω′ . 

A default value for α is derived from FSIS’ Salmonella HACCP verification program data collected from 2006 

through the third quarter of 2009 (Figure 1). In 2006, FSIS augmented its Salmonella performance standard by 

establishing a system that categorized slaughter establishments into three broad categories based on the 

sampling results of two successive sample sets for each establishment (FSIS, 2006). Category 1 establishments had 

sample results that suggested their carcass prevalence levels were ≤50% of the performance standard (12 or 

fewer positive samples among a 51 sample set for young chickens). Category 1 establishments had 6 or fewer 

positive samples across each of two successive 51 sample sets. Category 3 establishments had more than 12 

positive samples among its last 51 sample set. Category 2 establishments were those that did not meet the 

Category 1 or 3 definitions. Establishments are given a Category 2T status after achieving a single sample set with 

less than or equal to 6 positives.

This classification system encouraged establishments to improve their performance by the posting of names of 

Category 2 or 3 establishments on the FSIS website. Over time, the change in the fraction of establishments in 

Category 3 (or in Categories 2 and 3) provides an estimate of the value ofα . 

Based on the past performance of the program (Figure 1) it was estimated that approximately 55-60% of young 

chicken establishments that initially did not pass the guidance modified their production practices to become 

compliant (i.e., fewer than 12 positive samples out of a 51 sample set). Nevertheless, it is possible that as 

prevalence approaches zero, it will become more difficult for establishments to improve their production 

practices. Given this reasoning, the default assumption for the effectiveness of the guidance will beα = 0.5. 
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

7 

Figure 1. Change in the proportion of young chicken establishments that pass the existing Salmonella standard of 12 or 

fewer positive samples out of a 51-sample set. 

The lower horizontal line in Figure 1 represents the initial level of compliance of roughly 36% of establishments 

passing the standard. The upper horizontal line represents an approximate upper bound for the proportion of 

establishments passing the standard. The level of compliance demonstrates a rapid improvement over the first 24 

months followed by a stable period where between 80 and 85% of establishments are passing the standard.

Finally, the model requires input values for λill for Salmonella and Campylobacter. These values for the current 

“baseline” number of illnesses per year attributed to poultry were derived using data sources and methodology 

given in Table 1.
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

8 

Table 1. Data source and methods used for estimating illnesses from Campylobacter and Salmonella attributed to young 

chickens and turkeys in the U.S. population. Minor discrepancies in final estimates are due to rounding of intermediate 

values. 

Step Input Campylobacter Salmonella Data Source & Time 

Period / Estimation

1 Foodborne illnesses 845,024 1,027,561 Scallan et al., 2011 

2 Poultry attribution 

fraction

0.20 0.17 CDC outbreak data, 

2001-2007 and Pires et 

al., 20092

 

3 Young chicken volume 

adjusted proportion 

positive

0.467 0.075 FSIS Young Chicken 

Baseline Study (2007-

2008)

4 Turkey volume adjusted

percent positive

0.011 0.017 FSIS Young Turkey 

Baseline Study (2008-

2009)

5 Young chicken production 

fraction

0.838 0.838 ERS (2003-2008)

6 Young turkey production 

fraction

0.151 0.151 ERS (2003-2008)

7 Contaminated young 

chicken fraction

0.996 0.961 Step =(3 x 5)/ ((3 x 5) + 

(4 x 6))

8 Contaminated young 

turkey fraction

0.004 0.039 Step = (4 x 6)/ ((3 x 5) + 

(4 x 6))

9 Young chicken attribution 

fraction

0.199 0.163 Step = 2 x 7

10 Young turkey attribution 

fraction

0.001 0.007 Step = 2 x 8

11 Total foodborne illnesses 

from young chickens

168,291 167,831 Step = 1 x 9

12 Total foodborne illnesses 

from young turkeys

714 6,855 Step = 1 x 10

 

2

 An assessment of publically available Centers for Disease Control and Prevention (CDC) outbreak cases, 2001 – 2007 for 

Salmonella gave poultry attribution estimates of 16.9%. This estimate was rounded up to 17%. For Campylobacter poultry 

attribution, a CDC case-control study suggested the “population attributable fraction (PAF) of 24% was related to 

consumption of chicken prepared at a restaurant” (Friedman et al., 2004). This estimate was rounded down to 20%. 
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

9 

Results

Salmonella

Alternative guidance options were considered based on the prevalence of contaminated young chicken carcasses 

among a sample set of 51 samples per slaughter establishment (Figure 2). This analysis proceeded by assuming 

the YCBS (i.e., sampling results pooled by establishment) represented the current state of the industry. It was 

determined whether each establishment had passed or did not pass the various guidance options, and then the 

number of illnesses avoided per year was determined as described under Methods. For example, if the guidance 

was that a maximum of 5 positive samples was allowed, then ~80% of establishments were estimated to pass the 

guidance and ~25,000 illnesses were estimated to be avoided within a year or so following implementation of the 

guidance. 

Figure 2. Estimates of the annual number of Salmonella illnesses avoided (top) and the proportion of production

establishments that would pass the new guidance based on the YCBS. Estimated illnesses avoided per year are lower 

when based on FSIS HACCP verification data.

Figure 2 shows estimates of the annual number of Salmonella illnesses avoided and the proportion of 

establishments that would pass the new guidance based on data from the YCBS. Both values are given as a 

function of the number of allowable positive samples. As the number of allowable positives decrease in a 51-

sample set, the number of illnesses avoided increases. 
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

10

Analysis of Figure 2 demonstrates the trade-off between improved public health (i.e., decrease in the number of 

salmonellosis cases per year) and greater industry compliance required as the guidance becomes stricter. As the 

maximum allowable positive samples decreases from 11 to 2 (i.e., moving right to left), the number of Salmonella

illnesses avoided per year increases while the fraction of establishments that can initially pass the guidance 

decreases. Because fewer establishments initially pass a strict guidance, more establishments (initially 

noncompliant) will have to change their operations so that they can eventually pass the guidance.

Salmonella on young chickens

After examining the information in Figure 2 and the results of the most recent two years of Salmonella HACCP 

verification program data, FSIS decided to propose Salmonella guidance that required 5 or fewer Salmonellapositive samples among a 51 sample set to consider a young chicken slaughter establishment as passing. This 

guidance was then applied to the Salmonella HACCP verification program data collected from 2008 to the present. 

This analysis determined what fraction of establishments and young chicken production would pass (or not pass) 

this guidance. In addition, the values for ( ) and ( ) P exp P exp pass fail were estimated from these data.

Table 2. Data used to estimate the number of illnesses avoided due to the implementation of the proposed Salmonella

guidance for young chickens. Minor discrepancies are due to rounding error.

Proportion of total volume initially compliant ω = 0.907 ( ) P exp pass = 0.035 

Proportion of total volume initially noncompliant 1− = ω 0.093 P exp fail ( ) = 0.153

Proportion of compliant establishments ω′ = 0.85

Proportion of noncompliant establishments 1− = ω′ 0.15

Proportion of establishments that improve α = 0.5 λill = 167,831 λavoided = 20,157

The proposed Salmonella guidance is expected to avoid ~20,000 human cases that otherwise would occur each 

year (Table 2). Introduction of this guidance will initially result in about 15% of establishments not passing, but we 

anticipate that 50% of these establishments will pass the guidance within one or two years and generate the 

potential public health benefits.

To examine the effect that different values for α might have on the human illnesses avoided, we considered a 

range of α values from 0% to 100% (Figure 3). For the guidance (i.e., 5 positives out of 51 samples), the 

maximum number of illnesses that could be avoided is approximately 40,000 if all initially noncompliant

establishments were to become compliant with the guidance.

 
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

11

 

Figure 3. The number of Salmonella illnesses avoided increases linearly with the value of α in the young chicken model.

Salmonella on young turkeys

The guidance for young turkey carcasses reflects the very low prevalence of positive samples observed in the 

YTBS. Ultimately, the guidance was set such that a sample set of 56 samples was classified as passing if 4 or fewer 

samples were Salmonella-positive. The analysis estimates that 100 young turkey-associated Salmonella illnesses 

per year (assumingα = 0.5) can be avoided (Table 3).

Table 3. Data used to estimate the number of illnesses avoided due to the implementation of the proposed Salmonella

guidance for young turkeys. 

Proportion of total volume initially compliant ω = 0.997 ( ) P exp pass = 0.017

Proportion of total volume initially noncompliant 1− = ω 0.003 P exp fail ( ) = 0.188

Proportion of compliant establishments ω′ = 0.82

Proportion of noncompliant establishments 1− = ω′ 0.18

Proportion of establishments that improve α = 0.5 λill = 6,855 λavoided = 100

Campylobacter

In the past, FSIS has not regulated Campylobacter, and two primary factors influenced the decision about the 

proposed guidance:

• A desire to prevent raw poultry products with high levels of Campylobacter from reaching consumers.

• The need to integrate sample collection with the Salmonella testing in order to control costs and 

minimize the sample collection burden on field staff and establishments.
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

12

Campylobacter on young chickens

For young chicken carcasses, the proposed guidance requires a reduction in the prevalence of contaminated 

carcasses with higher levels of Campylobacter organisms. The same 51 young chicken carcass samples collected 

for Salmonella are tested for Campylobacter, with the proposed Campylobacter guidance allowing a maximum of 

8 positives carcasses. 

This analysis of the public health effects of the guidance proceeded by assuming the YCBS represented the current 

state of the young chicken industry. The testing data from each establishment in the baseline study was used to 

determine if the establishment would pass or not pass the proposed guidance, then the illnesses avoided per year 

was determined as described in the Methods section. 

The 51-sample set for Campylobacter on young chicken carcasses has an estimated public health benefit of ~5,000 

illnesses avoided if the policy is 50% effective (similar to that considered for Salmonella). Pertinent values used in 

the calculations are provided in Table 4. 

Table 4. Data used to estimate the number of illnesses avoided due to the implementation of the proposed Campylobacter

guidance for young chickens. Minor discrepancies are due to rounding error.

Proportion of total volume initially compliant ω = 0.87 ( ) P exp pass = 0.430

Proportion of total volume initially noncompliant 1− = ω 0.13 P exp fail ( ) = 0.655

Proportion of compliant establishments ω′ = 0.78

Proportion of noncompliant establishments 1− = ω′ 0.22

Proportion of establishments that improve α = 0.5 λill = 168,291 λavoided = 5,359

The proposed Campylobacter guidance is a semi-quantitative standard that is designed to detect highly 

contaminated carcasses. The method used to estimate the number of Campylobacter illnesses avoided does not 

account for any reduction in Campylobacter levels per contaminated carcass, and is only prevalence-related. As a 

result, the prevalence-related estimator likely underestimates the actual public health benefits of establishments 

meeting the guidance.

FSIS has not previously regulated Campylobacter so no data exist to determine the effectiveness of the policy. 

Figure 4 demonstrates the potential number of illnesses avoided across the range of possible levels of 

effectiveness (α ) and shows that the public health benefit increases linearly with the effectiveness of the 

guidance. 
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

13

Figure 4. The number of Campylobacter illnesses avoided increases linearly with the value of α in the young chicken

model. 

Campylobacter on young turkeys

The Campylobacter guidance for young turkey carcasses took account of the very low prevalence of positive 

samples observed in the YTBS. Ultimately, the guidance was set such that a sample set of 56 samples was 

classified as passing if 3 or fewer samples were Campylobacter-positive. FSIS estimates this guidance will 

ultimately avoid an estimated 20 young turkey-associated Campylobacter illnesses per year (if α = 0.5) (Table 5).

Table 5. Data used to estimate the number of illnesses avoided due to the implementation of the proposed Campylobacter

guidance for young turkeys. 

Proportion of total volume initially compliant ω = 0.99 ( ) P exp pass = 0.010

Proportion of total volume initially noncompliant 1− = ω 0.02 ( ) P exp fail = 0.068

Proportion of compliant establishments ω′ = 0.88 

Proportion of noncompliant establishments 1− = ω′ 0.12 

Proportion of establishments that improve α = 0.5 λill = 714 λavoided = 20

Discussion

Based on the data and information available, several reasonable assumptions were made in this analysis. It was 

assumed that testing data from the YCBS, YTBS, and Salmonella HACCP verification program data are 

representative of current and future industry performance. Given the ongoing improvement in the performance 
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

14

of the industry as a whole with regard to Salmonella, it is possible that some additional reduction in 

Campylobacter levels has occurred since the baseline data were collected. 

An area of considerable uncertainty is the determination of the number of attributed illnesses to these productpathogen pairs. The estimates of illnesses avoided do not account for this source of uncertainty, so it is possible 

that actual benefit from the guidance differs significantly from the point estimates provided here. Regardless of 

these assumptions, however, it would be difficult to argue that a lower prevalence of contaminated products 

would not translate into safer products and less human illness. 

Past experience has demonstrated that the disincentives of FSIS guidance have motivated industries to improve 

performance. Nevertheless, past reductions in Salmonella prevalence do not necessarily imply that the industry 

has the resources and technical ability to further reduce pathogen levels. There is likely a lower limit to pathogen 

levels that can be achieved with current technologies. 

This analysis assumes the Campylobacter and Salmonella guidance have independent effects on public health. 

Nevertheless, it is likely that modifications to production practices that reduce levels of one pathogen would also 

reduce levels of the other. 

The estimated number of illnesses avoided represents roughly 7% of the illnesses attributed to both pathogens. 

These are improvements, representing a small fraction of all illness cases. Year-to-year fluctuations in total cases 

might swamp these effects, and the success of these guidances may not be immediately reflected in public health 

surveillance statistics. However, with more precise attribution data, the effects of regulatory changes for these 

FSIS-regulated products should be demonstrable in the illness incidence data provided by the Centers for Disease 

Control and Prevention.

The trends in Salmonella prevalence since 2006 demonstrate that a substantial number of establishments have 

achieved a Category 1 ranking (i.e., prevalence that is less than or equal to 50% of the current performance 

standard). The willingness and apparent ability of the industry to control pathogen levels is encouraging and 

suggests an opportunity to successfully further increase the stringency of guidance in the future. 

The estimation of potential public health benefits associated with Campylobacter guidance is less certain because 

this pathogen has not been previously the subject of FSIS regulation. By implementing this guidance, FSIS has the 

opportunity to learn more about Campylobacter occurrence. Monitoring pathogen prevalence across time and 

assessing relationships between the occurrences of both pathogens will likely lead to improved knowledge and 

future guidance development. 
Potential Public Health Impact of Salmonella and Campylobacter Performance Guidance

15

References and Data Sources

Bartholomew M.J., Vose D.J., Tollefson L.R., Travis C.C. 2005. A linear model for managing the risk of 

antimicrobial resistance originating in food animals. Risk Analysis, 25, 99–108. 

CDC, 2001-2007. Outbreaknet: Foodborne Outbreak Online Database, 

http://wwwn.cdc.gov/foodborneoutbreaks/. 

ERS, 2003-2008. Economic Research Service. Food Availability: Spreadsheets, 

http://www.ers.usda.gov/data/foodconsumption/FoodAvailSpreadsheets.htm. 

FSIS, 2006. Salmonella Verification Sample Result Reporting: Agency Policy and Use in Public Health Protection, 

http://www.fsis.usda.gov/OPPDE/rdad/FRPubs/04-026N.pdf.

FSIS, 2007. Nationwide Young Chicken Microbiological Baseline Data Collection Program, 

http://www.fsis.usda.gov/PDF/Baseline_Data_Young_Chicken_2007-2008.pdf.

FSIS, 2008. Nationwide Young Turkey Microbiological Baseline Data Collection Program, 

http://www.fsis.usda.gov/PDF/Baseline_Data_Young_Turkey_2008-2009.pdf.

Friedman C.R., Hoekstra R.M., Samuel M., Marcus R., Bender J., Shiferaw B., Reddy S., Ahuja S.D., Helfrick D.L., 

Hardnett F., Carter M., Anderson B., Tauxe R.V. 2004. Emerging Infections Program FoodNet Working Group. Risk 

factors for sporadic Campylobacter infection in the United States: A case-control study in FoodNet sites. Clinical

Infectious Disease, 15, 85-96.

Pires, S.M., Evers, E.G., van Pelt W., Ayers T., Scallan E., Angulo F.J., Havelaar A., Hald T., and the Med-Vet-Net 

Workpackage 28 Working Group. 2009. Attributing the Human Disease Burden of Foodborne Infections to Specific 

Sources. Foodborne Pathogens and Disease, 6, 417-24.

Scallan, E. Hoekstra, R.M., Angulo, F.J., Tauxe, R.V., Widdowson, M-A, Roy, S.L., Jones, J.L. ,Griffin, P.M. 2011. 

Foodborne Illness Acquired in the United States—Major Pathogens. Emerging Infectious Diseases. Jan;17(1):7-15, 

http://www.cdc.gov/eid/content/17/1/7.htm. 

Vose, D., 2008. Risk Analysis: A quantitative guide. 3rd Edition. John Wiley and Sons, Ltd. 2008.

Williams M.S., Ebel, E.D., Vose, D. 2011. Framework for Microbial Food-Safety Risk Assessments Amenable to 

Bayesian Modeling Risk Analysis. (in press). Available online under DOI: 10.1111/j.1539-6924.2010.01532.x.