Spatio-temporal Modelling of Measles Risk in the Provinces of Central Luzon, CALABARZON, and MIMAROPA – Linking the Impact of Climate-based Factors

This study utilizes Bayesian spatio-temporal modeling techniques to assess the risk of measles in the provinces of Central Luzon, CALABARZON, and MIMAROPA, the Philippines. Using Integrated nested Laplace approximation, various model structures were explored to capture the spatial, temporal, and interaction components underlying measles incidence patterns. The analysis also revealed a linkage between measles risk and warm days, highlighting the seasonal nature of measles transmission. The findings also offer valuable insights for public health interventions, indicating the necessity for targeted interventions in identified high-risk areas and during specific periods.