Background: Foodborne illness is a continuing public health problem in the United States. Although outbreak-associated illnesses represent a fraction of all foodborne illnesses, foodborne outbreak investigations provide critical information on the pathogens, foods, and food-pathogen pairs causing illness. Therefore, identification of a food source in an outbreak investigation is key to impacting food safety.
Objective: The objective of this study was to systematically identify outbreak-associated case demographic and outbreak characteristics that are predictive of food sources using Shiga toxin–producing Escherichia coli (STEC) outbreaks reported to Centers for Disease Control and Prevention (CDC) from 1998 to 2014 with a single ingredient identified.
Materials and Methods: Differences between STEC food sources by all candidate predictors were assessed univariately. Multinomial logistic regression was used to build a prediction model, which was internally validated using a split-sample approach.
Results: There were 206 single-ingredient STEC outbreaks reported to CDC, including 125 (61%) beef outbreaks, 30 (14%) dairy outbreaks, and 51 (25%) vegetable outbreaks. The model differentiated food sources, with an overall sensitivity of 80% in the derivation set and 61% in the validation set.
Conclusions: This study demonstrates the feasibility for a tool for public health professionals to rule out food sources during hypothesis generation in foodborne outbreak investigation and to improve efficiency while complementing existing methods.
Food source prediction of Shiga toxin–producing Escherichia coli outbreaks using demographic and outbreak characteristics, United States, 1998–2014
White Alice, Cronquist Alicia, Bedrick Edward J., and Scallan Elaine.
Foodborne Pathogens and Disease. October 2016, 13(10): 527-534. doi:10.1089/fpd.2016.2140.