Bayesian Markov Switching Space-Time Model for Zika in Colombia

Explore a Bayesian Markov switching space-time model for analyzing Zika virus transmission in Colombia through this 13-minute conference talk. Delve into the study of Zika epidemics between 2014 and 2016, focusing on four Colombian departments. Learn about the zero-state Markov-switching space-time model used to examine disease presence, emergence, transmission intensity, and persistence. Discover how environmental factors like temperature, vegetation index, and precipitation influenced Zika transmission, while population density affected disease persistence. Gain insights into the complex interplay of environmental and sociodemographic factors in the spread of Zika, providing valuable information for understanding and potentially predicting future outbreaks of vector-borne diseases.