Partners Develop New Method for Attributing Foodborne Illness
CDC, the U.S. Food and Drug Administration (FDA) and the USDA’s Food Safety and Inspection Service (FSIS) have developed an improved method for analyzing outbreak data to determine which foods are responsible for illnesses related to four major foodborne bacteria.
Today, the Interagency Food Safety Analytics Collaboration (IFSAC), apartnership among the three agencies, released a report entitled“Foodborne Illness Source Attribution Estimates for Salmonella,Escherichia coli O157 (E. coli O157), Listeria monocytogenes (Lm), and Campylobacter using Outbreak Surveillance Data”.
CDC estimates that, together, these four pathogens causes an estimated 1.9 million cases of foodborne illness in the United States each year.
IFSAC analyzed data from nearly 1,000 outbreaks that occurred from 1998 to 2012 to assess which categories of foods were most responsible for making people sick with Salmonella, E. coli O157,Listeria, and Campylobacter. IFSAC experts divided food into 17 categories for the analysis. The pathogens were chosen because of the frequency or severity of the illnesses they cause, and because targeted interventions can have a significant impact in reducing them.
The report presents the methods behind the results and provides details about the amount of uncertainty around the estimates. Some of the findings include:
Due to limitations in outbreak data and uncertainty in the estimates, IFSAC recommends caution in interpreting certain findings, such as the estimates for Campylobacter in dairy and Listeria in fruits. IFSAC suggests that the results be used with other scientific data for risk-based decision making.
IFSAC will describe its methods at a public meeting today in Washington, D.C., as part of the overall federal efforts to improve foodborne illness source attribution. For more information on the IFSAC partnership, its goals and projects, please visit the partnership’s website.
Commodity tree and infographic depicting food categories with examples. Click for larger view.