Automated early warning system for the surveillance of Salmonella isolated in the agro-food chain in France.

ABSTRACT

Non-typhic Salmonella is one of the major bacterial pathogens that cause foodborne infections as well as economic losses for the food production industry. There is therefore a need to improve early detection to prevent the emergence and spread of Salmonella within the agro-food chain. The passive laboratory-based surveillance system of the Salmonella network has been integrated into the French Food Safety Agency's working plan. The objective of this study was to evaluate the ability of this network to detect unusual Salmonella contamination as early as possible in the agro-food chain. Three statistical methods were used to detect unusual events from the time-series of counts. After an experimental period of more than 1 year, this approach detected several unusual events linked to contamination in the agro-food chain that were confirmed in a timely manner at national or regional levels. This evaluation also reinforced the position of the Salmonella network as an integral part of the national public health surveillance system.