B0181
Title: Spatial analysis of measles in Colombia using a Bayesian model that allows for risk estimation and cluster detection
Authors: Ana Corberan-Vallet - University of Valencia (Spain) [presenting]
Karen C Florez - Universidad del Norte (Colombia)
Ingrid Carolina Marino - Universidad del Norte - University of Valencia (Colombia)
Jose D Bermudez - University of Valencia (Spain)
Abstract: A Bayesian hierarchical Poisson model with an underlying cluster structure is applied to describe measles incidence in Colombia. Concretely, the proposed methodology provides relative risk estimates at department level and identifies clusters of disease. We also show how socio-demographic factors can be included in the model to describe disease incidence better. Since the model does not impose any spatial correlation at any level of the model hierarchy, it avoids the spatial confounding problem and provides a suitable framework to estimate the fixed-effect coefficients associated with spatially-structured covariates. This analysis will facilitate the implementation of targeted public health interventions, which are essential to restrict the expanse of the epidemic that reemerged in Venezuela in 2017
