Geospatial health data are essential to inform public health and policy. These data can be used to understand geographic and temporal patterns, identify risk factors, measure inequalities, and quickly detect outbreaks. In this talk, I will give an overview of statistical methods and computational tools for geospatial data analysis and health surveillance. Using dengue surveillance in Brazil as a case study, I will discuss data biases and availability issues in surveillance systems. I will also present modeling advancements to integrate complex health, climate, and digital data from different sources and resolutions to predict disease risk and detect outbreaks. Finally, I will discuss the importance of effective communication and dissemination to inform policymaking and improve global population health.
Zoom link: https://uoc-gr.zoom.us/j/88659969718?pwd=g6bjYPDCuUQo1bzVxjjbgQL4xFN1f3.1
