IFSAC released their 2024 report that looks at data through 2022. This is a distillation of that report to show the highlights. I think that the charts were the most informative part of this report.
Each year in the United States an estimated 9 million people get sick, 56,000 are hospitalized, and 1,300 die of a foodborne disease caused by known pathogens.
Overall - Key results [per the report]
- The results are based on 1,010 outbreaks caused or suspected to be caused by Salmonella, 281 by E. coli O157, and 64 by Listeria.
- Estimated Salmonella illnesses were more evenly distributed across food categories than illnesses from E. coli O157, and Listeria; most of the illnesses for the latter pathogens were attributed to one or two food categories.
- The credibility intervals overlap for the Salmonella and Listeria categories with the highest attribution percentages, indicating no statistically significant difference between them.Salmonella
Key results
E. coli O157
Listeria monocytogenes
- Over 75% of illnesses were attributed to seven food categories: chicken, fruits, seeded vegetables (such as tomatoes), pork, other produce (such as nuts), beef, and turkey.
- The credibility intervals for each of the seven food categories that account for 79.7% of all illnesses overlap with the intervals of other categories.
E. coli O157
Key results
- Over 85% of E. coli O157 illnesses were attributed to vegetable row crops (such as leafy greens) and beef.
- Vegetable row crops had a significantly higher estimated attribution percentage than all other categories.
- Beef had a significantly higher estimated attribution percentage than all categories other than vegetable row crops.
- No illnesses were attributed to eggs or oils-sugars.
Listeria monocytogenes
Key results
- Over 75% of illnesses were attributed to dairy, vegetable row crops, and fruits.
- The credibility intervals for the dairy, vegetable row crops, fruits, and other produce categories were wide, partly due to the small total number of outbreaks (64).
- No illnesses were attributed to other meat/poultry, game, other seafood, grains-beans, oils-sugars, and seeded vegetables.
Campylobacter
Attribution estimates for Campylobacter are not presented in this year's report. Evidence suggests the sources of Campylobacter outbreaks likely differ considerably from the sources of non-outbreak-associated illnesses caused by this pathogen.
https://www.cdc.gov/ifsac/php/data-research/annual-report-2022.html
Foodborne Illness Source Attribution Estimates – United States, 2022
At a glance
Each year in the United States an estimated 9 million people get sick, 56,000 are hospitalized, and 1,300 die of a foodborne disease caused by known pathogens. These estimates help highlight the scope of this public health problem. However, to develop effective prevention measures, food safety agencies and partners need to understand the types of foods contributing to the problem.
Attribution estimates for Campylobacter are not presented in this year's report. Evidence suggests the sources of Campylobacter outbreaks likely differ considerably from the sources of non-outbreak-associated illnesses caused by this pathogen.
https://www.cdc.gov/ifsac/php/data-research/annual-report-2022.html
Foodborne Illness Source Attribution Estimates – United States, 2022
At a glance
- This report presents annual estimates of the percentages of foodborne illness attributed to 17 food categories for Salmonella, Escherichia coli O157, and Listeria monocytogenes.
- These estimates can inform food safety decision-making and provide pathogen-specific direction for reducing foodborne illness.
- Data come from 48,735 illnesses linked to 1,355 foodborne disease outbreaks that occurred from 1998 through 2022.
Each year in the United States an estimated 9 million people get sick, 56,000 are hospitalized, and 1,300 die of a foodborne disease caused by known pathogens. These estimates help highlight the scope of this public health problem. However, to develop effective prevention measures, food safety agencies and partners need to understand the types of foods contributing to the problem.
The Interagency Food Safety Analytics Collaboration (IFSAC) is a tri-agency group created by the Centers for Disease Control and Prevention (CDC), the U.S. Food and Drug Administration (FDA), and the U.S. Department of Agriculture's Food Safety and Inspection Service (USDA-FSIS). By bringing together data from CDC, FDA, and USDA-FSIS, and by developing sound analytical methods, IFSAC scientists can improve estimates of the sources of foodborne illness.
Using outbreak surveillance data from 1998 through 2022, this report presents annual estimates of the percentages of foodborne illness attributed to 17 food categories for Salmonella, Escherichia coli O157, and Listeria monocytogenes.
Salmonella illnesses came from a wide variety of foods.
More than 75% of Salmonella illnesses were attributed to seven food categories: chicken, fruits, seeded vegetables (such as tomatoes), pork, other produce (such as nuts), beef, and turkey.
Escherichia coli (E. coli) O157 illnesses were most often linked to two categories.
Over 85% of Escherichia coli (E. coli) O157 illnesses were linked to vegetable row crops (such as leafy greens) and beef.
Listeria monocytogenes (Listeria) illnesses were most often linked to dairy products, vegetable row crops, and fruits.
More than 75% of illnesses were attributed to these three categories, but the rarity of Listeria outbreaks makes these estimates less reliable than those for other pathogens.
Attribution estimates for Campylobacter are not presented in this year's report. Evidence suggests the sources of Campylobacter outbreaks likely differ considerably from the sources of non-outbreak-associated illnesses caused by this pathogen. IFSAC is exploring alternative approaches for estimating the sources of Campylobacter illnesses.
Using outbreak surveillance data from 1998 through 2022, this report presents annual estimates of the percentages of foodborne illness attributed to 17 food categories for Salmonella, Escherichia coli O157, and Listeria monocytogenes.
Salmonella illnesses came from a wide variety of foods.
More than 75% of Salmonella illnesses were attributed to seven food categories: chicken, fruits, seeded vegetables (such as tomatoes), pork, other produce (such as nuts), beef, and turkey.
Escherichia coli (E. coli) O157 illnesses were most often linked to two categories.
Over 85% of Escherichia coli (E. coli) O157 illnesses were linked to vegetable row crops (such as leafy greens) and beef.
Listeria monocytogenes (Listeria) illnesses were most often linked to dairy products, vegetable row crops, and fruits.
More than 75% of illnesses were attributed to these three categories, but the rarity of Listeria outbreaks makes these estimates less reliable than those for other pathogens.
Attribution estimates for Campylobacter are not presented in this year's report. Evidence suggests the sources of Campylobacter outbreaks likely differ considerably from the sources of non-outbreak-associated illnesses caused by this pathogen. IFSAC is exploring alternative approaches for estimating the sources of Campylobacter illnesses.
IFSAC derived the estimates for 2022 using the same method used for previous estimates, with some modifications. The original method, dating back to the estimates from 2012, was described in a report, a peer-reviewed journal article, and at a public meeting.
The data in this year's report came from 48,375 illnesses linked to 1,355 foodborne disease outbreaks that occurred from 1998 through 2022 and for which each confirmed or suspected implicated food was assigned to a single food category. The method relies most heavily on the last five years of outbreak data (2018–2022).
The data in this year's report came from 48,375 illnesses linked to 1,355 foodborne disease outbreaks that occurred from 1998 through 2022 and for which each confirmed or suspected implicated food was assigned to a single food category. The method relies most heavily on the last five years of outbreak data (2018–2022).
Foods are categorized using a scheme IFSAC created that classifies foods into 17 categories that closely align with the U.S. food regulatory agencies' classification needs. Examples of foods included in each food category can be found in the Appendix. Caution should also be exercised when comparing estimates across years, as a decrease in a percentage may result, not from a decrease in the number of illnesses attributed to that food, but from an increase in illnesses attributed to another food.
This collaborative effort to provide annual attribution estimates continues IFSAC's work to improve foodborne illness source attribution, which can help inform efforts to prioritize food safety initiatives, interventions, and policies for reducing foodborne illnesses. These consensus estimates allow all three agencies to take a consistent approach to identifying food safety priorities to protect public health.
Introduction
Each year in the United States, an estimated 9 million people get sick, 56,000 are hospitalized, and 1,300 die of foodborne disease caused by known pathogens1 — these estimates help highlight the scope of this public health problem. However, to develop effective prevention-oriented measures, food safety agencies and partners need to understand the percentage of foodborne illnesses associated with specific foods; we call this work foodborne illness source attribution.
With the creation of IFSAC in 2011, CDC, FDA, and USDA-FSIS agreed to improve data and methods used to estimate foodborne illness source attribution and provide timely estimates of the food sources of four priority foodborne pathogens: Salmonella, Escherichia coli O157 (E. coli), Listeria monocytogenes (Listeria), and Campylobacter. IFSAC considers these four pathogens to be priorities because of the frequency and severity of illness they cause, and because targeted interventions can significantly reduce these illnesses. Consistent with the 2021 report, attribution estimates for Campylobacter are not presented due to observed limitations of using outbreak data to attribute Campylobacter illnesses to food sources. IFSAC is exploring alternative approaches for estimating the sources of Campylobacter illnesses.
IFSAC developed a method for analyzing outbreak data to estimate which foods are responsible for illnesses related to the four priority pathogens, using a scheme IFSAC created to classify foods into 17 categories that closely align with the U.S. food regulatory agencies' classification needs2. Examples of foods included in each food category can be found in the Appendix. IFSAC described this method and the resulting estimates for the year 2012 in a report, a peer-reviewed article3, and at a public meeting4.
IFSAC derived the estimates for 2022 using the same method, with some modifications. IFSAC publishes annual estimates of the sources of foodborne illness for the priority pathogens while continuing to work on methods to further improve these estimates.
The consensus among the three agencies on methods and attribution estimates can help inform efforts to prioritize food safety initiatives, interventions, and policies for reducing foodborne illnesses. The 2022 estimates achieve IFSAC's goals of using improved methods to develop estimates of foodborne illness source attribution for priority pathogens and of achieving consensus that these are the best current estimates for the agencies to use in their food safety activities.
These estimates can also help scientists; federal, state, and local policymakers; the food industry; consumer advocacy groups; and the public to assess whether prevention-oriented measures are working.
Methods
We analyzed data extracted from CDC's Foodborne Disease Outbreak Surveillance System (FDOSS)56 on outbreaks (defined as two or more illnesses with a common exposure)7 that were confirmed or suspected to be caused by three priority pathogens — Salmonella, E. coli O157, and Listeria — from 1998 through 2022. We excluded outbreaks that met one or more of the following conditions: occurred in a U.S. territory; had no identified food vehicle or contaminated ingredient; were caused by more than one pathogen (including pathogens not included in this report). Given our method of running two separate models for Enteritidis and non-Enteritidis Salmonella outbreaks3 and because this analysis does not include non-O157 STEC, we excluded outbreaks that were caused by both Salmonella serotype Enteritidis and any other Salmonella serotype and those that were caused by both E. coli O157 and any other E. coli serogroup, because these were difficult to classify for modeling purposes. We included outbreaks caused by multiple serotypes of Salmonella if none were Enteritidis.
Each outbreak was assigned to a single food category using the IFSAC food categorization scheme2 based on confirmed or suspected implicated foods and ingredients (i.e., a single ingredient was confirmed or suspected to be implicated or all ingredients in the food were assigned to the same food category). We excluded outbreaks that could not be assigned to a single food category, as the food was often complex (i.e., composed of ingredients belonging to more than one category) and the contaminated ingredient in the complex food could not be identifiedA.
We developed pathogen-specific analysis of variance (ANOVA) models using our previously described method3 to mitigate the impact of large outbreaks and control for epidemiological factors. We estimated the number of log-transformed illnesses associated with each outbreak based on three factors deemed to be important during exploratory analyses: food category, type of preparation location (e.g.; restaurant, home), and whether the outbreak occurred in one or more states.
These model estimates were then back-transformed and down-weighted with a function that declines exponentially for outbreaks older than the most recent five years (2018–2022) because we considered foods more recently implicated to be the most relevant for estimating current attribution. For Salmonella and E. coli O157, we assigned outbreaks to the year in which the first illnesses occurred. For Listeria, we used the adjusted method first used in the 2021 report to assign model-estimated illnesses for Listeria outbreaks proportionally to the years in which illnesses in that outbreak occurred because about half (52%) of Listeria outbreaks in our data span multiple years.
We used the resulting down-weighted model-estimated illnesses to calculate each estimated attribution percentage: the sum of illnesses associated with a pathogen-food category pair was divided by the sum of illnesses associated with that pathogen across all food categories. We calculated 90% credibility intervals and considered non-overlapping credibility intervals an indication of statistical significance at the p<0.10 level. After down-weighting, 63% of overall information came from the most recent five years, 32% from the next most recent five years (2013–2017), and 5% from the oldest data (1998–2012).
In the graphs and tables, food categories appear in descending order of their estimated attribution percentage, and those that contributed to a cumulative attribution of approximately 75% of illnesses are indicated.
Results
We identified 3,996 outbreaks that occurred from 1998 through 2022 and that were confirmed or suspected to be caused by Salmonella, E. coli O157, or Listeria including 211 outbreaks that were confirmed or suspected to be caused by multiple pathogens or serotypes. Of these, we excluded 106 outbreaks according to our pathogen exclusion criteria, leaving 3,890 outbreaks. We further excluded 1,656 outbreaks without a confirmed or suspected implicated food, 873 outbreaks for which the food vehicle could not be assigned to one of the 17 food categories, and six that occurred in a U.S. territory.
Each year in the United States, an estimated 9 million people get sick, 56,000 are hospitalized, and 1,300 die of foodborne disease caused by known pathogens1 — these estimates help highlight the scope of this public health problem. However, to develop effective prevention-oriented measures, food safety agencies and partners need to understand the percentage of foodborne illnesses associated with specific foods; we call this work foodborne illness source attribution.
With the creation of IFSAC in 2011, CDC, FDA, and USDA-FSIS agreed to improve data and methods used to estimate foodborne illness source attribution and provide timely estimates of the food sources of four priority foodborne pathogens: Salmonella, Escherichia coli O157 (E. coli), Listeria monocytogenes (Listeria), and Campylobacter. IFSAC considers these four pathogens to be priorities because of the frequency and severity of illness they cause, and because targeted interventions can significantly reduce these illnesses. Consistent with the 2021 report, attribution estimates for Campylobacter are not presented due to observed limitations of using outbreak data to attribute Campylobacter illnesses to food sources. IFSAC is exploring alternative approaches for estimating the sources of Campylobacter illnesses.
IFSAC developed a method for analyzing outbreak data to estimate which foods are responsible for illnesses related to the four priority pathogens, using a scheme IFSAC created to classify foods into 17 categories that closely align with the U.S. food regulatory agencies' classification needs2. Examples of foods included in each food category can be found in the Appendix. IFSAC described this method and the resulting estimates for the year 2012 in a report, a peer-reviewed article3, and at a public meeting4.
IFSAC derived the estimates for 2022 using the same method, with some modifications. IFSAC publishes annual estimates of the sources of foodborne illness for the priority pathogens while continuing to work on methods to further improve these estimates.
The consensus among the three agencies on methods and attribution estimates can help inform efforts to prioritize food safety initiatives, interventions, and policies for reducing foodborne illnesses. The 2022 estimates achieve IFSAC's goals of using improved methods to develop estimates of foodborne illness source attribution for priority pathogens and of achieving consensus that these are the best current estimates for the agencies to use in their food safety activities.
These estimates can also help scientists; federal, state, and local policymakers; the food industry; consumer advocacy groups; and the public to assess whether prevention-oriented measures are working.
Methods
We analyzed data extracted from CDC's Foodborne Disease Outbreak Surveillance System (FDOSS)56 on outbreaks (defined as two or more illnesses with a common exposure)7 that were confirmed or suspected to be caused by three priority pathogens — Salmonella, E. coli O157, and Listeria — from 1998 through 2022. We excluded outbreaks that met one or more of the following conditions: occurred in a U.S. territory; had no identified food vehicle or contaminated ingredient; were caused by more than one pathogen (including pathogens not included in this report). Given our method of running two separate models for Enteritidis and non-Enteritidis Salmonella outbreaks3 and because this analysis does not include non-O157 STEC, we excluded outbreaks that were caused by both Salmonella serotype Enteritidis and any other Salmonella serotype and those that were caused by both E. coli O157 and any other E. coli serogroup, because these were difficult to classify for modeling purposes. We included outbreaks caused by multiple serotypes of Salmonella if none were Enteritidis.
Each outbreak was assigned to a single food category using the IFSAC food categorization scheme2 based on confirmed or suspected implicated foods and ingredients (i.e., a single ingredient was confirmed or suspected to be implicated or all ingredients in the food were assigned to the same food category). We excluded outbreaks that could not be assigned to a single food category, as the food was often complex (i.e., composed of ingredients belonging to more than one category) and the contaminated ingredient in the complex food could not be identifiedA.
We developed pathogen-specific analysis of variance (ANOVA) models using our previously described method3 to mitigate the impact of large outbreaks and control for epidemiological factors. We estimated the number of log-transformed illnesses associated with each outbreak based on three factors deemed to be important during exploratory analyses: food category, type of preparation location (e.g.; restaurant, home), and whether the outbreak occurred in one or more states.
These model estimates were then back-transformed and down-weighted with a function that declines exponentially for outbreaks older than the most recent five years (2018–2022) because we considered foods more recently implicated to be the most relevant for estimating current attribution. For Salmonella and E. coli O157, we assigned outbreaks to the year in which the first illnesses occurred. For Listeria, we used the adjusted method first used in the 2021 report to assign model-estimated illnesses for Listeria outbreaks proportionally to the years in which illnesses in that outbreak occurred because about half (52%) of Listeria outbreaks in our data span multiple years.
We used the resulting down-weighted model-estimated illnesses to calculate each estimated attribution percentage: the sum of illnesses associated with a pathogen-food category pair was divided by the sum of illnesses associated with that pathogen across all food categories. We calculated 90% credibility intervals and considered non-overlapping credibility intervals an indication of statistical significance at the p<0.10 level. After down-weighting, 63% of overall information came from the most recent five years, 32% from the next most recent five years (2013–2017), and 5% from the oldest data (1998–2012).
In the graphs and tables, food categories appear in descending order of their estimated attribution percentage, and those that contributed to a cumulative attribution of approximately 75% of illnesses are indicated.
Results
We identified 3,996 outbreaks that occurred from 1998 through 2022 and that were confirmed or suspected to be caused by Salmonella, E. coli O157, or Listeria including 211 outbreaks that were confirmed or suspected to be caused by multiple pathogens or serotypes. Of these, we excluded 106 outbreaks according to our pathogen exclusion criteria, leaving 3,890 outbreaks. We further excluded 1,656 outbreaks without a confirmed or suspected implicated food, 873 outbreaks for which the food vehicle could not be assigned to one of the 17 food categories, and six that occurred in a U.S. territory.
The resulting dataset included 1,355 outbreaks in which the confirmed or suspected implicated food or foods could be assigned to a single food category: 1,010 caused or suspected to be caused by Salmonella, 281 by E. coli O157, and 64 by Listeria. These included 46 outbreaks caused by multiple serotypes of Salmonella. Due to down-weighting, the last five years of outbreaks provided most information for the estimates; outbreaks from 2018 through 2022 provided 63% of model-estimated illnesses used to calculate attribution for Salmonella, 68% for E. coli O157, and 34% for Listeria.
The overall results and those for each pathogen are shown in Figures 1–4.
Overall
Figure 1
Estimated percentage (with 90% credibility intervals) for 2022 of foodborne Salmonella, Escherichia coli O157, and Listeria monocytogenes illnesses attributed to 17 food categories[A] based on outbreak data from 1998 through 2022, United States
Chart with estimated percentages of foodborne illnesses caused by Salmonella, E. coli, and Listeria attributed to specific food categories. Data available for download.
Based on a model using outbreak data that gives equal weight to each of the most recent five years of data (2018–2022), and exponentially less weight to each earlier year (1998–2017).
Key results
The results are based on 1,010 outbreaks caused or suspected to be caused by Salmonella, 281 by E. coli O157, and 64 by Listeria.
Estimated Salmonella illnesses were more evenly distributed across food categories than illnesses from E. coli O157, and Listeria; most of the illnesses for the latter pathogens were attributed to one or two food categories.
The credibility intervals overlap for the Salmonella and Listeria categories with the highest attribution percentages, indicating no statistically significant difference between them.
Salmonella
Estimated percentage of foodborne Salmonella illnesses (with 90% credibility intervals) for 2022, in descending order, attributed to each of 17 food categories, based on outbreak data from 1998 through 2022, United States
Chart with estimated percentages of foodborne illnesses caused by Salmonella attributed to specific food categories. Data available for download.
Based on a model using outbreak data that gives equal weight to each of the most recent five years of data (2018–2022), and exponentially less weight to each earlier year (1998–2017).
Key results
Over 75% of illnesses were attributed to seven food categories: chicken, fruits, seeded vegetables (such as tomatoes), pork, other produce (such as nuts), beef, and turkey.
The credibility intervals for each of the seven food categories that account for 79.7% of all illnesses overlap with the intervals of other categories.
E. coli O157
Key results
Over 85% of E. coli O157 illnesses were attributed to vegetable row crops (such as leafy greens) and beef.
Vegetable row crops had a significantly higher estimated attribution percentage than all other categories.
Beef had a significantly higher estimated attribution percentage than all categories other than vegetable row crops.
No illnesses were attributed to eggs or oils-sugars.
Listeria monocytogenes
Key results
Over 75% of illnesses were attributed to dairy, vegetable row crops, and fruits.
The credibility intervals for the dairy, vegetable row crops, fruits, and other produce categories were wide, partly due to the small total number of outbreaks (64).
No illnesses were attributed to other meat/poultry, game, other seafood, grains-beans, oils-sugars, and seeded vegetables.
Discussion
This report uses data from 1998 through 2022 to provide outbreak-based attribution estimates for 2022 of the percentages of illnesses caused by three (Salmonella, E. coli O157, and Listeria) of four priority pathogens, attributing illnesses to each of the 17 food categories. Data from foodborne disease outbreaks are the foundation of many foodborne illness source attribution analyses, in part because outbreak investigations often link illnesses to a specific food, and the data are captured nationally. These estimates can inform food safety decision-making and provide pathogen-specific direction for reducing foodborne illness.
In this year's report, we assigned down-weights to Listeria outbreaks based on the proportion of cases that occurred during each year of the outbreak. Weighting cases across the years of the outbreak proportionally gives an improved representation of the impact of that food category on the 2022 estimates. In future iterations of the report, we plan to apply this weighting scheme to the other pathogens.
The attribution of Salmonella illnesses to multiple food categories suggests that interventions designed to reduce illnesses from these pathogens need to target a variety of food categories. In contrast, most E. coli O157 illnesses were attributed to two food categories: vegetable row crops and beef. These data suggest that interventions for E. coli O157 focusing on these two food categories may be most effective in reducing illnesses. Similar to prior reports, vegetable row crops had a significantly higher estimated E. coli O157 attribution percentage than all other food categories8.
Most Listeria illnesses were attributed to three food categories: dairy, vegetable row crops, and fruits. Although the limited number of outbreaks and wide credibility intervals dictate caution in interpreting the attribution percentage for dairy, the risk to pregnant women and people with weakened immune systems of consuming soft cheese made from unpasteurized milk or in unsanitary conditions is well-recognized9, and outbreaks from fruits contaminated by Listeria have been observed in recent years.
Attribution estimates for Campylobacter are not presented in this year's report due to continued concerns about the limitations of using outbreak data to attribute Campylobacter illnesses to sources. As described in the 2021 IFSAC Annual Attribution Report, these concerns are largely due to the outsized influence of outbreaks in certain foods that pose a high individual risk for Campylobacter infection but do not represent the risk to the general population. Most of the reported Campylobacter outbreaks related to dairy were associated with unpasteurized milk (156/172, 91%) and most reported Campylobacter outbreaks related to chicken were due to chicken liver products (52/80, 65%), both of which are not widely consumed8.
A lack of representativeness heightens the likelihood that the sources of reported Campylobacter outbreaks differ considerably from the sources of non-outbreak-associated illnesses. In response to these limitations, IFSAC analysts are developing other methods to estimate the sources of Campylobacter infection. IFSAC is currently exploring methods using data associated with sporadic infections, including genomic information from patient isolates and case exposure data collected by FoodNet sites. IFSAC is also working to develop a sustainable approach to case-control studies that would provide unbiased estimates of risk. Additional information on IFSAC's priorities and activities are described in the 2024–2028 strategic plan10.
This 2022 analysis includes one Listeria outbreak that spanned multiple years and was not included in prior reports because the investigation had not been completed. Multi-year outbreaks are solved in large part because whole-genome sequencing (WGS) is used to link human and food isolates across multiple years. In some outbreaks, recent nonclinical isolates (such as food isolates) are subsequently linked to clinical cases from the past11.
Our approach addresses several issues with outbreak-based foodborne illness source attribution, yet limitations associated with generalizing outbreak data to sporadic illnesses remain and are well-documented56. Our analysis is also subject to other uncertainties and biases. For pathogens with a small number of outbreaks, outbreaks with a very large illness count can have substantial influence on the attribution point estimate. Further, this analysis only included 34% (1,355 of 3,996) of reported outbreaks caused by the three priority pathogens because we excluded those outbreaks that occurred in a U.S territory, those in which the implicated food could not be assigned to a single food category, and those that did not meet our pathogen inclusion criteria. The ones we included might not be representative of all outbreaks caused by these pathogens. Finally, our analysis includes illnesses that occurred among institutionalized populations, such as those in prisons, hospitals, and schools; these populations are easier to identify and collect complete data from, have fewer food options, more likely to have documentation of what was served, and are not representative of the general population.
These estimates should not be interpreted as suggesting that all foods in a category are equally likely to transmit pathogens. Caution should also be exercised when comparing estimates across years, as a decrease in a percentage may result, not from a decrease in the number of illnesses attributed to that food, but from an increase in illnesses attributed to another food. This is especially true for Listeria, as the attribution percentages might vary widely from year to year due to the limited number of outbreaks and the zero-sum nature of the attribution percentages. The analyses show relative changes in percentage, not absolute changes in attribution to a specific food. Therefore, we advise using these results with other scientific data for decision-making.
Conclusions
IFSAC's work to provide a harmonized analytic approach for estimating foodborne illness source attribution from outbreak data can provide consistency in the use and interpretation of estimates across public health and regulatory agencies. As more data become available and methods evolve, attribution estimates may improve. Annual updates to these estimates will enhance IFSAC's efforts to inform and engage stakeholders, and further their ability to assess whether prevention-oriented measures are working.
IFSAC continues to enhance attribution efforts through projects that address limitations identified in this report.
IFSAC Projects
Suggested citation
Interagency Food Safety Analytics Collaboration. Foodborne illness source attribution estimates for Salmonella, Escherichia coli O157, and Listeria monocytogenes – United States, 2022. GA and D.C.: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Food and Drug Administration, U.S. Department of Agriculture's Food Safety and Inspection Service. December 13, 2024.
Acknowledgements
Expand All
The methods used for this report were developed by members of the Interagency Food Safety Analytics Collaboration (IFSAC), which includes the Centers for Disease Control and Prevention (CDC), the U.S. Food and Drug Administration (FDA), and the U.S. Department of Agriculture's Food Safety and Inspection Service (USDA-FSIS).
The overall results and those for each pathogen are shown in Figures 1–4.
Overall
Figure 1
Estimated percentage (with 90% credibility intervals) for 2022 of foodborne Salmonella, Escherichia coli O157, and Listeria monocytogenes illnesses attributed to 17 food categories[A] based on outbreak data from 1998 through 2022, United States
Chart with estimated percentages of foodborne illnesses caused by Salmonella, E. coli, and Listeria attributed to specific food categories. Data available for download.
Based on a model using outbreak data that gives equal weight to each of the most recent five years of data (2018–2022), and exponentially less weight to each earlier year (1998–2017).
Key results
The results are based on 1,010 outbreaks caused or suspected to be caused by Salmonella, 281 by E. coli O157, and 64 by Listeria.
Estimated Salmonella illnesses were more evenly distributed across food categories than illnesses from E. coli O157, and Listeria; most of the illnesses for the latter pathogens were attributed to one or two food categories.
The credibility intervals overlap for the Salmonella and Listeria categories with the highest attribution percentages, indicating no statistically significant difference between them.
Salmonella
Estimated percentage of foodborne Salmonella illnesses (with 90% credibility intervals) for 2022, in descending order, attributed to each of 17 food categories, based on outbreak data from 1998 through 2022, United States
Chart with estimated percentages of foodborne illnesses caused by Salmonella attributed to specific food categories. Data available for download.
Based on a model using outbreak data that gives equal weight to each of the most recent five years of data (2018–2022), and exponentially less weight to each earlier year (1998–2017).
Key results
Over 75% of illnesses were attributed to seven food categories: chicken, fruits, seeded vegetables (such as tomatoes), pork, other produce (such as nuts), beef, and turkey.
The credibility intervals for each of the seven food categories that account for 79.7% of all illnesses overlap with the intervals of other categories.
E. coli O157
Key results
Over 85% of E. coli O157 illnesses were attributed to vegetable row crops (such as leafy greens) and beef.
Vegetable row crops had a significantly higher estimated attribution percentage than all other categories.
Beef had a significantly higher estimated attribution percentage than all categories other than vegetable row crops.
No illnesses were attributed to eggs or oils-sugars.
Listeria monocytogenes
Key results
Over 75% of illnesses were attributed to dairy, vegetable row crops, and fruits.
The credibility intervals for the dairy, vegetable row crops, fruits, and other produce categories were wide, partly due to the small total number of outbreaks (64).
No illnesses were attributed to other meat/poultry, game, other seafood, grains-beans, oils-sugars, and seeded vegetables.
Discussion
This report uses data from 1998 through 2022 to provide outbreak-based attribution estimates for 2022 of the percentages of illnesses caused by three (Salmonella, E. coli O157, and Listeria) of four priority pathogens, attributing illnesses to each of the 17 food categories. Data from foodborne disease outbreaks are the foundation of many foodborne illness source attribution analyses, in part because outbreak investigations often link illnesses to a specific food, and the data are captured nationally. These estimates can inform food safety decision-making and provide pathogen-specific direction for reducing foodborne illness.
In this year's report, we assigned down-weights to Listeria outbreaks based on the proportion of cases that occurred during each year of the outbreak. Weighting cases across the years of the outbreak proportionally gives an improved representation of the impact of that food category on the 2022 estimates. In future iterations of the report, we plan to apply this weighting scheme to the other pathogens.
The attribution of Salmonella illnesses to multiple food categories suggests that interventions designed to reduce illnesses from these pathogens need to target a variety of food categories. In contrast, most E. coli O157 illnesses were attributed to two food categories: vegetable row crops and beef. These data suggest that interventions for E. coli O157 focusing on these two food categories may be most effective in reducing illnesses. Similar to prior reports, vegetable row crops had a significantly higher estimated E. coli O157 attribution percentage than all other food categories8.
Most Listeria illnesses were attributed to three food categories: dairy, vegetable row crops, and fruits. Although the limited number of outbreaks and wide credibility intervals dictate caution in interpreting the attribution percentage for dairy, the risk to pregnant women and people with weakened immune systems of consuming soft cheese made from unpasteurized milk or in unsanitary conditions is well-recognized9, and outbreaks from fruits contaminated by Listeria have been observed in recent years.
Attribution estimates for Campylobacter are not presented in this year's report due to continued concerns about the limitations of using outbreak data to attribute Campylobacter illnesses to sources. As described in the 2021 IFSAC Annual Attribution Report, these concerns are largely due to the outsized influence of outbreaks in certain foods that pose a high individual risk for Campylobacter infection but do not represent the risk to the general population. Most of the reported Campylobacter outbreaks related to dairy were associated with unpasteurized milk (156/172, 91%) and most reported Campylobacter outbreaks related to chicken were due to chicken liver products (52/80, 65%), both of which are not widely consumed8.
A lack of representativeness heightens the likelihood that the sources of reported Campylobacter outbreaks differ considerably from the sources of non-outbreak-associated illnesses. In response to these limitations, IFSAC analysts are developing other methods to estimate the sources of Campylobacter infection. IFSAC is currently exploring methods using data associated with sporadic infections, including genomic information from patient isolates and case exposure data collected by FoodNet sites. IFSAC is also working to develop a sustainable approach to case-control studies that would provide unbiased estimates of risk. Additional information on IFSAC's priorities and activities are described in the 2024–2028 strategic plan10.
This 2022 analysis includes one Listeria outbreak that spanned multiple years and was not included in prior reports because the investigation had not been completed. Multi-year outbreaks are solved in large part because whole-genome sequencing (WGS) is used to link human and food isolates across multiple years. In some outbreaks, recent nonclinical isolates (such as food isolates) are subsequently linked to clinical cases from the past11.
Our approach addresses several issues with outbreak-based foodborne illness source attribution, yet limitations associated with generalizing outbreak data to sporadic illnesses remain and are well-documented56. Our analysis is also subject to other uncertainties and biases. For pathogens with a small number of outbreaks, outbreaks with a very large illness count can have substantial influence on the attribution point estimate. Further, this analysis only included 34% (1,355 of 3,996) of reported outbreaks caused by the three priority pathogens because we excluded those outbreaks that occurred in a U.S territory, those in which the implicated food could not be assigned to a single food category, and those that did not meet our pathogen inclusion criteria. The ones we included might not be representative of all outbreaks caused by these pathogens. Finally, our analysis includes illnesses that occurred among institutionalized populations, such as those in prisons, hospitals, and schools; these populations are easier to identify and collect complete data from, have fewer food options, more likely to have documentation of what was served, and are not representative of the general population.
These estimates should not be interpreted as suggesting that all foods in a category are equally likely to transmit pathogens. Caution should also be exercised when comparing estimates across years, as a decrease in a percentage may result, not from a decrease in the number of illnesses attributed to that food, but from an increase in illnesses attributed to another food. This is especially true for Listeria, as the attribution percentages might vary widely from year to year due to the limited number of outbreaks and the zero-sum nature of the attribution percentages. The analyses show relative changes in percentage, not absolute changes in attribution to a specific food. Therefore, we advise using these results with other scientific data for decision-making.
Conclusions
IFSAC's work to provide a harmonized analytic approach for estimating foodborne illness source attribution from outbreak data can provide consistency in the use and interpretation of estimates across public health and regulatory agencies. As more data become available and methods evolve, attribution estimates may improve. Annual updates to these estimates will enhance IFSAC's efforts to inform and engage stakeholders, and further their ability to assess whether prevention-oriented measures are working.
IFSAC continues to enhance attribution efforts through projects that address limitations identified in this report.
IFSAC Projects
Suggested citation
Interagency Food Safety Analytics Collaboration. Foodborne illness source attribution estimates for Salmonella, Escherichia coli O157, and Listeria monocytogenes – United States, 2022. GA and D.C.: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Food and Drug Administration, U.S. Department of Agriculture's Food Safety and Inspection Service. December 13, 2024.
Acknowledgements
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The methods used for this report were developed by members of the Interagency Food Safety Analytics Collaboration (IFSAC), which includes the Centers for Disease Control and Prevention (CDC), the U.S. Food and Drug Administration (FDA), and the U.S. Department of Agriculture's Food Safety and Inspection Service (USDA-FSIS).
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