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

link: http://arxiv.org/abs/1003.4466
Abstract

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