Trends in foodborne outbreaks and outbreak-associated illnesses using a Bayesian trend model – United States, 1998–2018

Abstract

Evaluating temporal trends in foodborne outbreak and illness attribution to specific food types is important for understanding which foods may be emerging as sources of illness and whether prevention strategies are working to prevent these illnesses. Evaluating these trends can be difficult because foodborne outbreaks are uncommon, and attribution of these outbreaks to a specific food can be difficult. We present a Bayesian trend model looking at outbreaks and outbreak-associated illnesses linked to four Interagency Food Safety Analytics Collaboration (IFSAC) priority foodborne bacterial pathogens: Campylobacter , Shiga toxin-producing Escherichia coli O157, Listeria monocytogenes , and Salmonella using a categorization scheme IFSAC created to classify foods into 17 categories that closely align with the U.S. food regulatory agencies’ classification needs. Outbreaks and outbreak-associated illnesses of listeriosis increased in dairy products during 1998–2018 while those linked to meat and poultry decreased. Outbreaks of campylobacteriosis linked to both dairy and poultry products also increased. STEC O157 outbreaks and outbreak-associated illnesses linked to meat decreased over the period. Outbreaks and outbreak-associated illnesses of salmonellosis linked to eggs also decreased over the period. This new approach to evaluating temporal changes in outbreaks and outbreak-associated illnesses may be a useful tool in understanding the epidemiology and impacts of prevention strategies for foodborne illness.