BCAM Scientific Seminar: Spatio-Temporal Hierarchical Models for Vector-Borne Disease Risk

Abstract: 
This work presents the first comprehensive spatio-temporal analysis that links reported and suspected cases of Denguefever with weather variables collected at different stations and land use satellite data. Dengue and Zika are mosquito-borne tropical diseases, reported with increasing rates in the last decade. Early warning systems help in predicting outbreaks and allow public health decision-makers to implement preventive measures. Several factors have been linked to the increase in reported cases: changes in temperature, precipitation, urbanization, and other spatial variables. Several space-time CAR specifications are implemented in a Bayesian framework to assess the relative risk of these factors, as well as to set a predictive framework. The modeling strategy involves a two-stage approach to account for the different spatial supports of predictors and response, and it allows identification of localized patterns. 

Click to see the poster