Using surveillance and monitoring data of different origins in a Salmonella source attribution model: a European Union example with challenges and proposed solutions.

Abstract

Microbial subtyping approaches are commonly used for source attribution of human salmonellosis. Such methods require data on Salmonella in animals and humans, outbreaks, infection abroad and amounts of food available for consumption. A source attribution model was applied to 24 European countries, requiring special data management to produce a standardized dataset. Salmonellosis data on animals and humans were obtained from datasets provided by the European Food Safety Authority. The amount of food available for consumption was calculated based on production and trade data. Limitations included different types of underreporting, non-participation in prevalence studies, and non-availability of trade data. Cases without travel information were assumed to be domestic; non-subtyped human or animal records were re-identified according to proportions observed in reference datasets; missing trade information was estimated based on previous years. The resulting dataset included data on 24 serovars in humans, broilers, laying hens, pigs and turkeys in 24 countries.