Sequential Bayesian Inference for Detection and Response to Seasonal Epidemics

Michael Ludkovski, Junjing Lin
2013 Online Journal of Public Health Informatics  
Objective Development of a sequential Bayesian methodology for inference and detection of seasonal infectious disease epidemics. Introduction Detection and response to seasonal outbreaks of endemic diseases provides an excellent testbed for quantitative bio-surveillance. As a case study we focus on annual influenza outbreaks. To incorporate observed year-over-year variation in flu incidence cases and timing of outbreaks, we analyze a stochastic compartmental SIS model that includes seasonal
more » ... cludes seasonal forcing by a latent Markovian factor. Epidemic detection then consists in identifying the presence of the environmental factor ("high" flu season), as well as estimation of the epidemic parameters, such as contact and recovery rates.
doi:10.5210/ojphi.v5i1.4570 fatcat:77n63k6qofevtky2wgwergemdm