Attribution of Foodborne Illness
Estimates of burden of illness are designed to give the most accurate counts of illnesses at a specific point in time. Determining the food sources of these illnesses is the next step in developing prevention measures. Food safety experts often call the process of estimating the most common food sources responsible for specific foodborne illnesses, “Foodborne Illness Source Attribution,” or Attribution. Multiple sources of data are needed to make attribution estimates, including data from outbreak investigations, infections not associated with outbreaks, and food product testing.
The 2011 Estimates of Foodborne Illness told us that roughly 48 million people (1 in 6) get sick each year from food eaten in the United States. More than 9 million of these illnesses are accounted for by major pathogens we track.
To prevent foodborne illness, food safety regulators, industry, and consumers need to know the major food sources. By attributing the estimated number of foodborne illnesses to particular categories of foods (or food commodities), we can target measures to prevent food contamination and set goals for improvement.
Estimating the number of illnesses associated with specific food sources is called foodborne illness source attribution 1. These analyses are the logical extension of our prior analyses estimating the number, or burden, of foodborne illnesses, hospitalizations and deaths in the US. Regulators and industry use this information to design, target, and implement more informed measures to prevent food contamination. Consumers can use this information to better apply safe food practices.
Food is Complicated
Visit any grocery store and you will see that there are hundreds of different foods. A person may eat many different types of food in a single meal. For scientists studying food sources responsible for illnesses, it would be simpler if we ate foods one at a time, like eating an apple by itself. But we often mix many different ingredients together from many types of foods and eat them together as one dish, such as an apple pie made with flour, spices, and sugar.
Just as a grocery store has different aisles and sections with related types of foods, individual foods can be categorized into groups. It is important to categorize foods in ways that are helpful to agencies that investigate outbreaks, regulate food safety, and inform consumers. Industries that produce foods also find this useful.
CDC has developed a basic list of 17 food categories, also called commodities, that are logical groupings based on the nature of the food source, like fish, beef, or leafy vegetables 2.
Figure 1. Hierarchy of 17 Food Commodities Used in Outbreak Analysis
Attribution is Challenging
It may seem like it should be straightforward to determine the food sources responsible for illnesses, but it is more complicated than you might think. This is because it is usually not possible to know which food made an individual person sick, or to know if a food was responsible for the illness. People rarely know what made them ill, and it can be difficult or impossible to figure out. When a group of people become ill at the same time in a foodborne outbreak, investigation may sometimes determine which food was responsible, providing a direct link between the foodborne illnesses and a food.
Yet, even in an outbreak it is difficult to determine the contaminated food. This is because:
- People may not know or remember everything they ate;
- Many ingredients went into the dish; and
- Not everyone who ate the same contaminated food becomes ill.
Many different kinds of infections can spread through food. Some infections, like salmonellosis, are common causes of outbreaks, so we understand their sources. Other infections, like toxoplasmosis, do not cause outbreaks, and thus are not reflected in the outbreak data. For these sporadic (non-outbreak) illnesses, it is usually impossible to know what food or other exposure was the source without conducting a special study.
Data Sources and Methods Used for Attribution
There is no single data source or analytic method that is best for estimating attribution for all agents. CDC uses several data sources and combinations of methods to estimate the number of illnesses associated with each type of food. Some are highly specific for one type of infection or one type of food, and others are more general. For example, by comparing the characteristics of Salmonella found in foods and animals with those found in people, we can attribute Salmonella infections back to specific animal sources. The best method may differ for different agents and foods.
- Outbreaks: Outbreak data provide information about the role of various foods in causing illnesses. However, outbreaks contribute only a small proportion (less than 5 percent) of lab-confirmed foodborne illnesses. Only using outbreak data assumes that the food sources are the same for outbreak-related illnesses and the more common sporadic (non-outbreak) illnesses, which is more accurate for some food-pathogen combinations than others.
- The National Outbreak Reporting System (NORS) collects data electronically from state, local, and territorial public health agencies and includes reports of all outbreaks of enteric (intestinal) illness transmitted by food, water, animal contact, or by person-to-person contact that they investigated.
- CDC regularly publishes summaries of foodborne disease outbreaks reported through NORS.
- Sporadic illnesses: Most health departments do not collect detailed data about exposures of individual people with illnesses, such as salmonellosis, that are often foodborne. Because most people do not know what made them sick, illnesses reported to a health department usually do not reveal the likely source. CDC and health departments do intensive studies that compare the exposures of people with sporadic cases of a particular infection, such as E. coli O157 3, with the exposures of other people who are not ill.
- By comparing exposures reported by the two groups, we can determine which foods likely are responsible for some of the illnesses. This approach is called a case-control study.
- Although case-control studies allow us to fill in knowledge gaps, these efforts use many resources and depend on people remembering what they ate.
- Pathogen subtype: Pathogens of the same type are not exactly alike. In the laboratory, small differences between pathogens can be used to subtype them. The subtype is a marker, like a fingerprint, that sometimes can help distinguish strains from different sources.
- Investigators can compare the subtypes of pathogens isolated from animals and foods with the subtypes isolated from infected humans. They can combine this information with data on how often people consume certain foods, and then use mathematical models to estimate the number of illnesses associated with each source.
- CDC and the US Department of Agriculture’s Food Safety and Inspection Service (FSIS) recently collaborated to adapt a pathogen-subtype model for Salmonella infections to US data 4.
Improving Attribution Through Partnership
Interagency Food Safety Analytics Collaboration (IFSAC)
While CDC does not have regulatory authority for many food safety policies, the data that CDC collects and shares can influence policy and programmatic development through FDA and FSIS.
CDC partnered with the Food and Drug Administration (FDA) and the US Department of Agriculture, Food Safety and Inspection Service (FSIS) in 2011 to form the Interagency Food Safety Analytics Collaboration (IFSAC). This tri-agency analytic collaboration focuses on foodborne illness source attribution. The group operates with the understanding that data improvements and development of multiple analytic methods are needed to generate good estimates across the broad range of food commodities and along all points in the food supply chain. More refined estimates will be provided in the future by bringing together additional data from across CDC, FDA and FSIS and evaluating methods for analyzing them.
CDC, FDA, and FSIS held a public meeting and developed a strategic plan for IFSAC that was presented in January 2012 5. Scientists from the three agencies collaborate and hold weekly telephone meetings on select projects to improve attribution estimates.
These ongoing projects focus on:
- Examining the limitations of attribution estimates calculated from outbreak data;
- Evaluating the potential usefulness of a pathogen subtype model to attribute Salmonella infections to food commodities;
- Improving the way foods are classified into food commodities, or categories;
- Developing standard approaches for using outbreak data to attribute illnesses caused by four major pathogens (Salmonella, Listeria, E. coli, and Campylobacter) to food commodities; and
- Determining the best approach to estimate the proportion of Salmonella enterica serotype Enteritidis infections attributable to shell eggs and other major commodities
IFSAC is committed to strong partnerships. Improvements in food safety depend on productive relationships between regulatory and non-regulatory partners—including industry, academia, and consumer groups—for data analysis, interpretation, and application.
IFSAC Webinar: One of the first IFSAC priorities was to improve the way foods implicated in foodborne disease outbreaks are classified. On June 18, 2013 the tri-agency collaboration held its first webinar to discuss the improvements to the food categorization scheme used by regulatory agencies to inform food safety decision-making. Watch the webinar | Presentation slides [PDF - 36 pages] | Presentation transcript [PDF - 6 pages]
- Foodborne Disease Attribution, Oregon Department of Health
This site is an excellent resource highlighting efforts by the Foodborne Diseases Active Surveillance Network, or (FoodNet) to attribute enteric illnesses to food sources. It provides links to other experts in foodborne illness and a select bibliography [PDF - 1 page] .
- Food and Drug Administration’s (FDA) Food Safety Modernization Act
- US Department of Agriculture, Food Safety and Inspection Service (FSIS), 2011-2016 Strategic Plan.
- European Food Safety Authority, Foodborne Zoonotic Diseases
- Hoffmann S, Batz MB, Morris JG Jr. Annual cost of illness and quality-adjusted life year losses in the United States due to 14 foodborne pathogens. J Food Prot. 2012 Jul;75(7):1292-302. doi: 10.4315/0362-028X.JFP-11-417.
- Batz MB, Hoffmann S, Morris JG Jr. Ranking the disease burden of 14 pathogens in food sources in the United States using attribution data from outbreak investigations and expert elicitation. J Food Prot. 2012 Jul;75(7):1278-91. doi: 10.4315/0362-028X.JFP-11-418. Erratum in: J Food Prot. 2012 Aug;75(8):1366.
- Guo C, Hoekstra RM, Schroeder CM, Pires SM, Ong KL, Hartnett E, Naugle A, Harman J, Bennett P, Cieslak P, Scallan E, Rose B, Holt KG, Kissler B, Mbandi E, Roodsari R, Angulo FJ, Cole D. Application of Bayesian techniques to model the burden of human salmonellosis attributable to U.S. food commodities at the point of processing: adaptation of a Danish model. Foodborne Pathog Dis. 2011 Apr;8(4):509-16. doi: 10.1089/fpd.2010.0714. Epub 2011 Jan 16.
- Painter JA, Ayers T, Woodruff R, Blanton E, Perez N, Hoekstra RM,et al. Recipes for foodborne outbreaks: a scheme for categorizing and grouping implicated foods. Foodborne Pathog Dis. 2009;6:1259–64
- Overview of methods for source attribution for human illness from foodborne microbiological hazards, The EFSA Journal (2008) [PDF - 43 pages]
The Interagency Food Safety Analytics Collaboration (IFSAC)
- IFSAC Draft Strategic Plan for Foodborne Illness Source Attribution [PDF - 16 pages] (January 2012)
- IFSAC Charter [PDF - 4 pages] (February 2011)
Partner and Public Meetings with Presentations
- Collaborative Food Safety Forum
- Food Source Attribution Public Meeting, USDA Public Meeting, Jan. 31, 2012
- Communicating About Attribution of Foodborne Illness, FDA Public Meeting, August 15-16, 2011
- FSIS Public Meeting: Attributing Illness to Food [PDF - 20 pages], April 5, 2007
- Food Safety Interventions and Food Attribution Workshop, April 26-27, 2005
- Linking Illness to Food: Summary of a Workshop on Food Attribution, 2004