Geospatial Health Data

Paula Moraga is a Lecturer in the Department of Mathematical Sciences at the University of Bath. She received her Master’s in Biostatistics from Harvard University and her Ph.D. in Statistics from the University of Valencia. Dr. Moraga develops innovative statistical methods and open-source software for disease surveillance including R packages for spatio-temporal modeling, detection of clusters, and travel-related spread of disease. Her work has directly informed strategic policy in reducing the burden of diseases such as malaria and cancer in several countries.

• 1. Geospatial health. 2. Spatial data and R packages for mapping. 3. Bayesian inference and INLA. 4. The R-INLA package. 5. Areal data. 6. Spatial modeling of areal data. 7. Spatio-temporal modeling of areal data. 8. Geostatistical data. 9. Spatial modeling of geostatistical data. 10. Spatio-temporal modeling of geostatistical data. 11. Introduction to R Markdown. 12. Building a dashboard to visualize spatial data with flexdashboard. 13. Introduction to Shiny. 14. Interactive dashboards with flexdashboard and Shiny. 15. Building a Shiny app to upload and visualize spatio-temporal data. 16. Disease surveillance with SpatialEpiApp.

"The stress is on practical usage of INLA modelling in a spatial context and hence the author shows the full code for several carefully selected examples. Essentially all the steps from the beginning (necessary data manipulation and preparation) via INLA analysis itself (often in several alternatives) to the results (plots and maps) are explained carefully and commented. This is very useful for anybody who wants to start with the powerful INLA but did not dare to go through the very powerful but notalways- fully-documented environment." ~Marek Brabec, ISCB News