Attribution of Salmonella enterica serotype Hadar infections using antimicrobial resistance data from two points in the food supply system

Abstract

A challenge to the development of foodborne illness prevention measures is determining the sources of enteric illness. Microbial subtyping source-Attribution models attribute illnesses to various sources, requiring data characterizing bacterial isolate subtypes collected from human and food sources. We evaluated the use of antimicrobial resistance data on isolates of Salmonella enterica serotype Hadar, collected from ill humans, food animals, and from retail meats, in two microbial subtyping attribution models. We also compared model results when either antimicrobial resistance or pulsed-field gel electrophoresis (PFGE) patterns were used to subtype isolates. Depending on the subtyping model used, 68-96% of the human infections were attributed to meat and poultry food products. All models yielded similar outcomes, with 86% [95% confidence interval (CI) 80-91] to 91% (95% CI 88-96) of the attributable infections attributed to Turkey, and 6% (95% CI 2-10) to 14% (95% CI 8-20) to chicken. Few illnesses (<3%) were attributed to cattle or swine. Results were similar whether the isolates were obtained from food animals during processing or from retail meat products. Our results support the view that microbial subtyping models are a flexible and robust approach for attributing Salmonella Hadar.