Develop a shared understanding and statement of needs for foodborne illness source attribution
Objective: Through a series of discussions, accomplish the following goals:
- Reach a shared understanding among the three agencies of historic and current methods and data sources used for foodborne illness source attribution.
- Identify short- and long-term needs of IFSAC partners.
- Review, compare, and select method(s) for estimating foodborne illness source attribution in the short term.
- Develop plans for applying the method(s) to each prioritized pathogen.
Project Results: During an April 2011 workshop held by the IFSAC Steering Committee and Technical Workgroup, team members developed a shared statement of needs and identified several analytic projects.
Improve the food categories used to estimate attribution
Objective: To expand the food categorization scheme used by CDC to classify foods implicated in foodborne disease outbreaks to include:
- More specific food categories.
- Useful categories for regulatory agencies and stakeholders.
Project Results: Expanded the previously used food categorization scheme to include more specific food categories that:
- Are more botanically correct.
- Better reflect production practices and postharvest handling systems.
- More readily distinguish FDA- and FSIS- regulated products.
After the new categorization scheme was determined, the IFSAC team assigned all applicable food items in the CDC outbreak surveillance database to these new categories. Additionally, the IFSAC team developed a food glossary with examples of foods for each food category.
The revised scheme has six distinct levels to which foods can be assigned, depending upon the type of food. First, foods are assigned to one of four food groups (aquatic animals, land animals, plants, and other). Food groups include increasingly specific food categories; dairy, eggs, meat and poultry, and game are in the land animal food group, and the category meat and poultry is further subdivided into more specific categories of meat (beef, pork, other meat) and poultry (chicken, turkey, other poultry). Finally (not shown in graphic below), foods are differentiated by differences in food processing (such as pasteurized fluid dairy products, unpasteurized fluid dairy products, pasteurized solid and semi-solid dairy products, and unpasteurized solid and semi-solid dairy products.
Commodity tree depicting food categories with examples. Click for larger view.
Infographic depicting food categories with examples. Click for larger view [PDF - 1 page].
The new food categorization scheme was shared during a June 2013 webinar, available on our Activities and Events page.
Determine sources of uncertainty and variability in estimated attribution fractions
Objective: Determine the best approach to estimate source attribution using outbreak surveillance data while exploring the uncertainties and variability associated with computing attribution estimates using outbreak data.
Project Results: There are several sources of uncertainty associated with using foodborne disease outbreak data to estimate the proportions of illnesses caused by the pathogens Salmonella, Listeria monocytogenes, Campylobacter, and E. coli O157:H7 in the population. A review of the literature confirmed that attribution estimates derived from outbreak data can vary depending on:
- Unit of analysis (i.e., outbreak counts or outbreak-associated illnesses).
- Food classification scheme used to categorize foods implicated in outbreaks.
- Time period of analysis.
- Amount of missing data and the number of foods with unknown contaminated ingredients.
Additionally, attribution estimates generated from outbreak data are different from those calculated using data from other surveillance populations. These differences highlight another important source of uncertainty regarding the representativeness of outbreaks of the foods and pathogens causing foodborne illness in the general population. These findings have provided the foundation for pursuing a tri-agency approach to estimating foodborne illness source attribution using outbreak data.
Estimate the proportion of Salmonella serotype Enteritidis illnesses attributable to shell eggs and other major commodities
Objective: To help assess the public health impact of the Egg Rule, an FDA regulation enacted in 2010 (“the Egg Rule”), this project sought to determine the proportion of illnesses attributable to shell eggs and other common sources before implementation of the rule.
Project Results: Developed a new method to estimate the proportion of foodborne SE illnesses attributable to shell eggs and other major food commodity reservoirs of SE during the baseline period (2007-2009).
Among the included sources, shell eggs were estimated to be responsible for the highest proportion of foodborne SE infections (40%; 95% CI: 30-51%) during the baseline period (2007-2009). This estimate is required for the Department of Health and Human Services’ Agency Priority goal, which is part of a government-wide Office of Management and Budget (OMB) performance management effort. This estimate will help improve our ability to assess the public health impact of the Egg Rule over time.
- Page last reviewed: February 24, 2015
- Page last updated: February 24, 2015
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