Bayesian analysis for inference of an emerging epidemic: citrus canker in urban landscapes.

ABSTRACT: Outbreaks of infectious diseases require a rapid response from policy makers. The choice of an adequate level of response relies upon available knowledge of the spatial and temporal parameters governing pathogen spread, affecting, amongst others, the predicted severity of the epidemic. Yet, when a new pathogen is introduced into an alien environment, such information is often lacking or of no use, and epidemiological parameters must be estimated from the first observations of the epidemic. This poses a challenge to epidemiologists: how quickly can the parameters of an emerging disease be estimated? How soon can the future progress of the epidemic be reliably predicted? We investigate these issues using a unique, spatially and temporally resolved dataset for the invasion of a plant disease,

SUBMITTER: Neri FM 

PROVIDER: S-EPMC3998883 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature