Spatially-dependent epidemiological models of infectious respiratory disease transmission

DAMIAN KNOPOFF

Conferencia; 21th International Conference on Computational and Mathematical Methods in Science and Engineering; 2021

While explicitly including a spatial component in an epidemiological model could be an unnecessarycomplication to answer many important ecological and public health questions, some degree of spatialresolution is indeed essential when wanting to differentiate transmission patterns across geographical regionsand when considering spatially heterogeneous intervention measures.Cellular automata epidemiological models typically rely on simplified computational grids but can pro-vide valuable insight into the spatial dynamics of transmission within a population by suitably accountingfor the connections between individuals in the considered community.In this talk, I will describe a stochastic cellular automata disease model based on the SHAR compart-mentalisation of the population, present some simulation results, and relate these results to real-life dataprovided by the Health Department and the Health Services of the Basque Country.