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A comparison of Salmonella serotype incidence in FSIS-regulated products and 

salmonellosis cases 

Introduction

On May 14, 2010, FSIS published a Federal Register notice (FSIS, 2010a) that detailed revised

performance standards for Salmonella species on young chicken (broiler) carcasses measured at 

post-chill. Public comments on the notice asserted that FSIS did not present evidence that 

reductions of Salmonella incidence on young chicken carcasses at post-chill would offer public 

health benefits. The comments noted that the Centers for Disease Control and Prevention (CDC)

FoodNet data sets did not correlate to FSIS percentages of positive chicken samples. In response to 

these and other comments, FSIS published the March 21, 2011 Federal Register notice (FSIS, 2011)

using CDC outbreak data and case-control studies as evidence for such a relationship. CDC 

summarized these data in a Memorandum to the Record (CDC, 2011a) that concluded “Poultry 

products are an important vehicle for human Salmonella and Campylobacter infections in the United 

States.” 

The material presented below continues the discussion by demonstrating a weight-of-evidence1

approach that includes 1) reasons why it is not appropriate to compare CDC FoodNet salmonellosis 

rates data directly to trends of Salmonella incidence in foods, 2) an analysis of CDC outbreaks from 

chicken products compared with Salmonella contamination rates in young chickens, and 3) an

analysis of serotype-specific salmonellosis rates and Salmonella serotype incidences in young 

chickens. In conjunction with the data presented in the CDC Memorandum to the Record, FSIS

provides further evidence of the connection between Salmonella incidence in young chickens and 

salmonellosis. 

Making the appropriate comparison

To begin, it is important to distinguish the two surveillance datasets available from the CDC to 

analyze outbreak trends and foodborne illness. First, the CDC Foodborne Disease Outbreak 

 1 Weight-of-evidence is a form of plausible reasoning. Support for a hypothesis is provided by observations of phenomena 

when such observations can be “explained” by the hypothesis. However, it is possible other factors could explain the 

observations, and that the hypothesis is not an actual (true) explanation. Yet by examining many sets of observations and 

determining that most support the hypothesis, in the above-described manner, we can say with greater confidence that 

the hypothesis is true and provides an actual explanation. If we assert the truth of the hypothesis through such a set of 

examinations, we say that the weight-of-evidence supports the hypothesis. In this case, weight-of-evidence is not a 

formal statistical approach based on controlled sets of observations within a scientific setting (experiments or surveys 

designed explicitly to “test” a hypothesis). 
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Surveillance System (FDOSS) (CDC, 2011b), referred to here as outbreak data, provides information 

on reported outbreaks (defined as two or more illnesses caused by a common source). Various 

authorities investigate the source (the pathogen and food product responsible for the outbreak) of 

the contamination − for about 50 percent of confirmed Salmonella outbreaks the investigation does 

not lead to an identifiable food vehicle. Second, the Foodborne Diseases Active Surveillance 

Network, referred here as FoodNet (CDC, 2011c), produces annual case rates for several major 

foodborne pathogens, including Salmonella. FoodNet data tracks salmonellosis cases in 10 states, 

presently covering about 46 million people (approximately one-seventh of the U.S. population). The 

majority of reported FoodNet salmonellosis cases reflect sporadic cases of Salmonella (only about 

six percent of 2007 reported FoodNet cases were outbreak-related (CDC, 2007)). Importantly, unlike 

outbreak data, there is no information regarding the food product that might have been associated 

with the illness. Therefore, FoodNet data are only available as aggregated information from cases 

due to all potential food sources. Thus, it would not be appropriate to infer a relationship between 

Salmonella occurrence in chicken carcasses at post-chill and FoodNet salmonellosis from all food 

sources. That is, salmonellosis rates for all products might not reflect a possible reduction of 

salmonellosis due to one food product, such as chicken, because there might be at the same time 

increases in salmonellosis due to other food products. Consequently, the absence of a positive 

correlation between salmonellosis rates and the incidence of contamination rates on young chicken 

carcasses over time does not permit dismissing the likelihood that Salmonella occurrence in chicken 

and salmonellosis are causally connected.

Outbreaks and Salmonella spp. incidence in young chickens

The CDC outbreak data can include information about the food product suspected to have caused 

an outbreak but are equivocal regarding relationships between Salmonella incidence on a product 

and salmonellosis rates. Accuracy of product identification and the small number of known 

outbreaks associated with specific product types create problems in drawing a relationship between 

human illness and chicken contamination rates. 

Figure 1 presents two plots: FSIS estimated year-specific percentages of Salmonella positive young 

chicken Hazard Analysis and Critical Control Points (HACCP) verification samples (FSIS, 2000-2008); 

and the yearly number of outbreaks associated with chicken products (CDC, 2000-2008) (simple 

food sources only, for a review see Pires et al., 2009). FSIS adjusted the calculations for the year-
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specific HACCP percentages of positive results by volume, within three volume classes (small, 

medium, large) (FSIS, 2010b; see below for method description). This adjustment, thus, accounted 

for the differences of class-specific percentage of positive results, where chickens produced within 

smaller volume class establishments had greater percentage of positive results. 

Figure 1. FSIS Volume-Weighted Percent Positive Results from HACCP Salmonella Verification Data 

and the Number of Outbreaks (simple) Associated with Chicken Product from 2000–2008.

Figure 1 shows that the numbers of yearly outbreaks range from 4–9 and seem relatively stable over

time. There is an apparent decrease, however, between the years 2005–2008. The decreasing 

trend in the Salmonella contamination on young chicken carcasses covers nearly the same period. 

The general depicted relationship, however, is not sufficient for asserting that the correlation is 

positive; the small number of attributed outbreaks per year does not permit an unequivocal 

statistical relationship to be established. 

Salmonellosis cases and Salmonella incidence by serotype 

A closer review of FoodNet data, at the serotype level, revealed a more definitive relationship. 

FoodNet often contains serotype information for Salmonella associated with human illness. 

Examining serotypes is a step closer to a direct comparison between Salmonella product 

contamination and salmonellosis attributed to the product because certain Salmonella serotypes are 

mostly associated with particular animal species. For example, FSIS finds S. Enteritidis (SE) more 
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commonly in chicken than in products from other species. FSIS HACCP data indicate that S. 

Enteritidis is found in ground chicken at a rate greater than 100 times that of ground beef2

. 

FSIS found that, through examining relationships involving trends of serotype-specific positive 

results, the weight-of-evidence supports the existence of a relationship between Salmonella in a 

product and illnesses. This relationship requires that for a product, for which a specific serotype is 

found frequently, a significant positive correlation exists between the serotype-specific FoodNet 

salmonellosis rate and the serotype-specific percentage of FSIS estimated positive samples for that 

product (adjusted for volume, as described below). This, however, is not a “deductive” type of 

conclusion drawn from a “controlled” experiment. Positive correlations for this situation only

support the existence of a connection and thus an inferred cause and effect relationship between 

Salmonella contamination on chicken and human illnesses from consumption of contaminated 

chicken. 

Below, FSIS presents an analysis of the top five Salmonella serotypes from the 20 most frequently 

reported Salmonella serotypes from human sources identified in the Laboratory-based Enteric 

Disease Surveillance (LEDS) system by CDC in 2009 (LEDS, 2009). FSIS selected these data because

they cover a large percentage of the total confirmed Salmonella illnesses, about 60 percent

(FoodNet, 2009), provide a manageable amount of data to present, and produce a relatively more 

accurate method for measuring and comparing trends compared to other serotypes with fewer 

numbers of cases. 

In the following analyses, “FoodNet Relative Rate” is the population-adjusted relative rate versus 

the 1996–1998 baseline years. Each year is the ratio of the number of confirmed FoodNet cases 

associated with a serotype, divided by the population-adjusted catchment covered by FoodNet. 

CDC provided these data to FSIS3

. CDC adjusted raw data estimates using a negative binomial model 

to account for increases in number of participating sites (different times of initial participation) and 

to reduce estimated site-to-site variation in disease incidence (Henao et al., 2010)4

.

 2 Ground products are used for this comparison given that the sampling methodologies can be compared more easily.

3 Personal communication, CDC February 08, 2011; http://www.cdc.gov/foodnet/factsandfigures/trends.html. 4 This model assumes that the disease process is similar for those combinations of years and states not observed and are 

therefore representative of the portion of the U.S. not participating in FoodNet surveillance (Henao et al., 2010).
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The “Volume-Weighted (VW) Percent Positive” by serotype and product (FSIS, 2000-2009) for a 

given year is 100 percent times the volume of contaminated product divided by the total volume for 

the specified year. We estimate the numerator (volume of contaminated product) by stratifying the 

establishments that produce the product during the specified year into three strata defined by 

establishment-specific volumes (for the specified year) and then estimate the volume of 

contaminated product produced from the establishments within each stratum. Each stratum 

consists of a set of establishments with production volumes between two specified volume 

boundaries. For the ith stratum, i = 1, 2 and 3, we designate vi to represent the sum of the 

establishment – specific volumes for establishments within the ith stratum. To estimate the volume 

of contaminated product for the ith stratum, we computed the proportion of Salmonella positive 

samples, pi, from the FSIS HACCP Salmonella Verification program5 collected from the 

establishments assigned to the ith stratum during the specified year, and then multiplied pi by the 

ith stratum-specific volume. We sum the values vipi over the three strata to estimate the total 

contaminated volume. We then divided this sum by the total volume of product produced during 

the year. In the formula, where is the volume-weighted percent positive for the 

specified year, i is the index for volume stratum, i = 1, 2, 3; vi is the volume for stratum i; and pi is the 

proportion of positive samples in stratum i. 

FSIS collects and analyzes HACCP verification samples for eight product classes. For some of these 

product classes the data are relatively sparse. For example, there were few samples, relatively 

speaking, for ground chicken (approximately 300 per year compare to approximately 9,000 per year 

for young chickens), and thus there is large variability of serotype-specific percentages over time. 

Because there were few Salmonella positive results for the steer/heifer carcass class, we combined 

these data with the cow/bull carcass class. Official collection of young turkey data began in 2006. 

With the exception of young turkey carcasses, we computed Spearman correlations of the yearly 

percentages of serotype-specific positive results for HACCP verification samples with the 

corresponding serotype-specific negative binomial FoodNet-adjusted relative rate for illnesses.

 5 In 2006, FSIS changed its algorithm for determining sampling frequencies of establishments. This could compromise 

comparison before and after the change. The number of establishments sampled and the number of samples, though, 

were large before and after the change, and thus we consider these data as “representative” of general trends with 

respect to Salmonella and serotype incidences in FSIS products. Thus, both sets of data are not clearly defined data, in a 

statistical sense, regarding “representing” well-defined populations. Such data conditions are consistent with a weight-ofevidence approach; in fact necessitate weight-of-evidence approaches based on plausible reasoning.
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S. Enteritidis is currently both the most common cause of foodborne salmonellosis (FoodNet, 2009) 

and the most frequently identified serotype of human health significance among young chickens and 

ground chicken (FSIS, 2009). Figure 2 compares the CDC estimated S. Enteritidis-confirmed FoodNet 

cases/100,000 with FSIS’ adjusted volume-weighted S. Enteritidis incidence data for the eight FSISregulated product classes. The Spearman correlation of yearly percentages of S. Enteritidis in young 

chickens and S. Enteritidis FoodNet illness rate was 0.81 (p-value = 0.0049); the correlation was 0.73

(p-value = 0.016) for ground chicken; other product classes were not significantly correlated with S.

Enteritidis human cases. While information for S. Enteritidis trends in eggs is missing, the significant 

positive correlations for young chicken and ground chicken provide support that S. Enteritidis 

incidence in chicken are a contributing source of foodborne salmonellosis due to S. Enteritidis

exposure. 

Figure 26

. Illness Rates of S. Enteritidis in FoodNet and Volume-Weighted Percent Positive Results 

from HACCP Verification Data from 2000–2009. Note the ground chicken data are divided by 10 to 

fit on the primary y-axis; for example, 2005 reads 0.98 indicating a Salmonella incidence of 9.8 

percent in ground chicken.

S. Typhimurium is currently the second most common Salmonella serotype associated with 

foodborne illness (FoodNet, 2009) and the third most frequently identified serotype of human 

health significance among young chickens and ground chicken (FSIS, 2009). This serotype is 

 6 Broilers = young chicken carcasses; Turkey = young turkey carcasses; Beef = steer/heifer and cow/bull/bull carcasses; Grd 

= ground
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associated with, and found in, pork, beef, and poultry products. S. Typhimurium-associated illnesses 

have been decreasing since the Agency began its HACCP regulatory approach in the late 1990s. 

Illness rates associated with S. Typhimurium have shown the greatest reduction compared to illness 

rates associated with single Salmonella serotypes among those reported in the most recently 

completed FoodNet final surveillance report; the report indicates a 52 percent reduction from the 

combined 1996–1998 baseline (Table 13; FoodNet Surveillance Report, 2007). Unlike the S.

Enteritidis analysis, the S. Typhimurium analysis uses a two-year moving average to smooth out 

some of the variability in the data (Figure 3). S. Typhimurium contamination rates decrease in all the 

product classes with the possible exception of ground chicken, which can possibly be attributed to 

variability due to the small numbers of samples analyzed per year. The Spearman correlation of the 

yearly S. Typhimurium illness rates with yearly percentages of S. Typhimurium for beef carcasses 

was 0.66 (p-value = 0.038); the correlation for ground turkey was 0.86 (p-value = 0.0012); the 

correlation for market hogs was 0.60 (p-value = 0.068); and on the correlation for young chicken

carcasses was 0.57 (p-value = 0.083). These relationships provide weight-of-evidence support that 

further reductions of S. Typhimurium incidence in meat and poultry products could result in further 

reduction of S. Typhimurium associated FoodNet illnesses. 

Figure 3. Illness Rates of S. Typhimurium7 in FoodNet and Volume-Weighted Percent Positive Results 

from HACCP Verification Data from 2000–2009, two-year moving average.

S. Newport is currently the third most common Salmonella serotype associated with foodborne 

illness (FoodNet, 2009). The Agency compared S. Newport-confirmed FoodNet cases with volume-

 7 Includes S. Typhimurium var 5-.
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weighted S. Newport incidence data for the eight FSIS-regulated product classes using a two-year 

moving average (Figure 4). This serotype is rare in young chicken samples while FSIS finds it

somewhat frequently in ground turkey (approximately on 1 percent of samples, on average), and to 

a lesser extent in ground beef (approximately 0.2 percent of samples, on average). Thus, it is 

unsurprising that the percentages of this serotype in young chickens are not correlated with changes 

in illness rates (yearly-specific Spearman correlation = 0.017, p-value = 0.96). Ground turkey, 

however, is more frequently contaminated with S. Newport and trended better over time with S. 

Newport-associated foodborne illnesses; the correlation was 0.47 (p-value = 0.17). FSIS believes 

that the relationships provide weight-of-evidence support for the premise that decreases in 

incidence of Salmonella serotypes of human health significance in products would have a positive

impact on public health. 

Figure 4. Illness Rates of S. Newport in FoodNet and Volume-Weighted Percent Positive Results 

from HACCP Verification Data from 2000–2009, two-year moving average.

S. Javiana is currently the fourth most common Salmonella serotype associated with foodborne 

illness (FoodNet, 2009). Of more than 500,000 HACCP samples analyzed between 1998 and 2009, 

FSIS identified only about 30 S. Javiana positives from the eight FSIS-regulated product classes, 

suggesting that S. Javiana is not typically associated with FSIS-regulated product classes. Spearman 

correlation analysis found no significant correlations with the FSIS-regulated products analyzed and 

human illnesses from S. Javiana. However, it appears that this serotype is associated with other 

foods given the two-fold increase of S. Javiana-associated FoodNet illnesses from 2000 to 2009 
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(Figure 5). This result provides an example of the problem of drawing conclusions regarding the 

impact of any single food product on illnesses from all found sources.

Figure 5. Illness Rates of S. Javiana in FoodNet and Volume-Weighted Percent Positive Results from 

HACCP Verification Data from 2000–2009.

S. Heidelberg is currently the fifth most common Salmonella serotype associated with foodborne 

illness (FoodNet, 2009) and the second most frequently identified Salmonella serotype of human 

health significance found on young chickens and ground chicken (FSIS, 2009). Salmonellosis illness

rates associated with S. Heidelberg have decreased from this serotype since 2000 (Figure 6). S.

Heidelberg is found often in poultry products, to a lesser extent in market hogs, and, recently,

infrequently in beef products. Figure 6 presents comparisons of S. Heidelberg-confirmed FoodNet 

cases with S. Heidelberg incidence data using a two-year moving average. The Spearman correlation 

of the yearly S. Heidelberg illness rates and the yearly percentages of S. Heidelberg found on young 

chickens was 0.82 (p-value = 0.004); it was 0.84 for ground turkey (p-value = 0.0022); and it was 0.57

(p-value =0.083) for market hogs. These relationships provide weight-of-evidence support that

decreased S. Heidelberg contamination on poultry has been a contributing factor for the reduction 

of salmonellosis associated with S. Heidelberg.
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Figure 6. Illness Rates of S. Heidelberg in FoodNet and Volume-Weighted Percent Positive Results 

from HACCP Verification Data from 2000–2009, two-year moving average.

Summary and Conclusion

This analysis stems from comments that claim FSIS did not present data to support the premise that 

reducing Salmonella contamination rates on chicken would reduce human illnesses. For the two 

serotypes (S. Enteritidis and S. Heidelberg) that occur commonly in young chickens, the trends in the 

illness rates attributed to the serotypes and the trends in the percentages of serotype-specific 

positive results were significantly correlated, with p-values less than 0.005. Illness rates associated 

with S. Typhimurium have decreased the most since 2000, which follows the general decrease of S. 

Typhimurium contamination rates for most FSIS-regulated meat and poultry products. 

Other product-specific rates rather than that of young chickens may correlate with the illnesses 

rates; these products’ Salmonella could be contributing to the positive correlation and not those 

specifically found on chicken carcasses. Following an examination of serotypes that may or may not 

be associated with chicken, a pattern appears where, for a serotype associated with certain product 

types, the percentage of serotype-specific positive results that FSIS found in that product type has a 

positive correlation with the salmonellosis rate associated with the particular serotype. It is the 

combination of these patterns, as well as the additional data presented, that provides the weight-ofevidence for the conclusion that reductions of Salmonella serotypes associated with illnesses in 

products lead to reductions of human illnesses in the population.
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The five Salmonella serotypes discussed represent about 60 percent of the known human 

Salmonella FoodNet cases (FoodNet, 2009); further efforts to reduce the presence of these 

serotypes, excluding S. Javiana, on all FSIS-regulated products should reduce human exposure to 

disease causing Salmonella and thus reduce illnesses. The remaining 40 percent still represent a 

sizable portion of salmonellosis that is caused by a diverse number of Salmonella serotypes 

(FoodNet Reports, 1998–2009). Many of these serotypes are also found on FSIS-regulated products. 

FSIS believes that it is entirely reasonable to hold the position that continued efforts to reduce all 

Salmonella serotypes in chicken and turkey carcasses would have a significant impact on reducing or 

averting illnesses, and thus such efforts are an important part of protecting public health.
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References

CDC, 2000-2008. http://wwwn.cdc.gov/foodborneoutbreaks/.

CDC, 2007. http://cdc.gov/foodnet/annual/2007/2007_annual_report_508.pdf. 

CDC, 2011a. http://www.fsis.usda.gov/PDF/Salmonella_Campylobacter_011811.pdf.

CDC, 2011b. http://www.cdc.gov/outbreaknet/surveillance_data.html.

CDC, 2011c. http://cdc.gov/foodnet/.

Henao, O.L., E. Scallan, B. Mahon, and R.M. Hoekstra. 2010. Methods for monitoring trends in the 

incidence of foodborne diseases: Foodborne Diseases Active Surveillance Network 1996-2008. 

Foodborne Pathog Dis. 7:1421-6.

FoodNet, 2009. http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5914a2.htm

FoodNet Reports, 1998-2009. http://www.cdc.gov/foodnet/reports.htm.

FoodNet Surveillance Report, 2007. 

http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5914a2.htm.

FSIS, 2000-2008. PR/HACCP Salmonella Verification, 2000-2008. 

http://www.fsis.usda.gov/PDF/Serotypes_Profile_Salmonella_2010.pdf.

FSIS, 2000-2009. PR/HACCP Salmonella Verification, 2000-2009.

FSIS, 2009. PR/HACCP Salmonella Verification, 2009.

FSIS, 2010a. http://www.fsis.usda.gov/OPPDE/rdad/FRPubs/2009-0034.pdf.

FSIS, 2010b.Technical paper attached to the FSIS May 14, 2010 Federal Register Notice.

http://www.fsis.usda.gov/PDF/Technical_Paper_Performance_Guidance_Broilers.pdf.

FSIS, 2011. http://www.fsis.usda.gov/OPPDE/rdad/FRPubs/2010-0029.pdf.

LEDS, 2009. http://www.cdc.gov/ncezid/dfwed/PDFs/SalmonellaAnnualSummaryTables2009.pdf.

Pires, S. M., E. G. Evers, W. van Pelt, T. Ayers, E. Scallan, F. J. Angulo, A. Havelaar, T. Hald, and MedVet-Net Workpackage 28 Working Group. 2009. Attributing the human disease burden of foodborne 

infections to specific sources. Foodborne Pathog Dis. 6:417-24.