A1158
Title: Directionally dependent spatial infectious disease models
Authors: Rob Deardon - University of Calgary (Canada) [presenting]
Abstract: In many epidemic systems, the disease can be prone to spread in some directions more than others. This can be due to migration and behavior patterns or due to prevailing wind patterns. Individual-level models (ILMs) are commonly used for modelling spatial risk in infectious disease transmission but have not traditionally considered these directional tendencies. A class of ILMs that allow for the directional dynamics of disease transmission is introduced. In these directionally dependent ILMs, the probability of an individual being infected depends on both the direction and distance between susceptible and infectious individuals. The characteristics of these directionally dependent ILMs are discussed, and how they can be fitted in a Bayesian Markov chain Monte Carlo (MCMC) framework are shown, as well as results for both simulated and real data for crop and livestock diseases.
