Geospacial data science for public health surveillance

Recently Dr. Paula Moraga gave a talk on Geospacial data science for public health surveillance. She is an Assistant Professor of Statistics at King Abdullah University of Science and Technology (KAUST) and the Principal Investigator of the GeoHealth research group.

 

Recently Dr. Paula Moraga gave a talk on Geospacial data science for public health surveillance. She is an Assistant Professor of Statistics at King Abdullah University of Science and Technology (KAUST) and the Principal Investigator of the GeoHealth research group.

Paula's research focuses on the development of innovative statistical methods and computational tools for geospatial data analysis and health surveillance, and the impact of her work has directly informed strategic policy in reducing disease burden in several countries. She has worked on projects examining malaria in Africa and leptospirosis in Brazil, and the models she develops rely on in-depth knowledge about each disease.

In her talk she focused on Geospatial data and methods, case studies on tropical disease mapping, statistical software and her current research.

Geospatial data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities.

Extract of the contents presented were from her book on Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny (2019, Chapman & Hall/CRC).