Automated detection of influenza epidemics with hidden Markov models

Abstract

We present a method for automated detection of influenza epidemics. The method uses Hidden Markov Models with an Exponential-Gaussian mixture to characterize the non-epidemic and epidemic dynamics in a time series of influenza-like illness incidence rates. Our evaluation on real data shows a reduction in the number of false detections compared to previous approaches and increased robustness to variations in the data. © Springer-Verlag Berlin Heidelberg 2003.