Gavin J Gibson abstract
School of Mathematical & Computer Sciences, Heriot-Watt University
Latent processes and functional models for partially observed epidemics
This talk will describe new developments in Bayesian model assessment, parameter estimation, and the design of control strategies for epidemic models for partially observed outbreaks. The unifying theme will be the way in which unobserved, or latent processes play a central role in the development of the methods. In the case of model assessment, we will show how functional-model representations of epidemic models can be selected so as to facilitate the construction of latent residual processes, with fixed sampling distributions, which can be used in order to test structural assumptions of the fitted model. We will also demonstrate how such representations can be exploited when attempting to design optimal control strategies for emerging epidemics. Finally we will describe recent developments towards the joint estimation of phylogenetic and epidemic processes in cases where genetic data on pathogens are available in addition to data on disease incidence. The methods will be illustrated using both simulated and real-world data sets. The work is joint with Max Lau, Hola Adrakey, and George Streftaris (HWU), and with Glenn Marion (BioSS).