A Bayesian approach for detecting a disease that is not being modeled

Aronis, John M.; Ferraro, Jeffrey P.; Gesteland, Per H.; Tsui, Fuchiang; Ye, Ye; Wagner, Michael M.; Cooper, Gregory F.

An activity monitoring operator characteristic (AMOC) curve is a graph that characterizes the timeliness of a detector [4]. It plots the expected time to detection as a function of the false-positive rate. AMOC curves can be used to compare the timeliness of different detectors. We can illustrate the performance of DUDE with an AMOC curve that plots the number of days to detection versus the number of false alarms for various threshold values. However, to generate an AMOC curve we need to define the start of an outbreak. It is also helpful to average over several outbreaks to measure performance under various circumstances. Since this is not practical to do with unmodeled outbreaks, we used data for outbreaks of known diseases and pretended to be ignorant of them, thus making them unmodeled.