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We propose a method to generate a warning system for the early detection oftime clusters applied to public health surveillance data. This new methodrelies on the evaluation of a return period associated to any new count of aparticular infection reported to a surveillance system. The method is appliedto Salmonella surveillance in France and compared to the model developed byFarrington et al.

An Extreme Value Theory approach for the early detection of time clusters with application to the surveillance of Salmonella