Background#R##N#Detecting outbreaks is a crucial task for public health officials, yet gaps remain in the systematic evaluation of outbreak detection protocols. The authors’ objectives were to design, implement, and test a flexible methodology for generating detailed synthetic surveillance data that provides realistic geographical and temporal clustering of cases and use to evaluate outbreak detection protocols.
['Bryan Lewis', 'Stephen Eubank', 'Allyson M. Abrams', 'Ken Kleinman']
in silico Surveillance: evaluating outbreak detection with simulation models