This book shows how to model disease risk and quantify risk factors using areal and geostatistical data. It also shows how to create interactive maps of disease risk and risk factors, and describes how to build interactive dashboards and Shiny web applications that facilitate the communication of insights to collaborators and policy makers.
This book shows how to model disease risk and quantify risk factors using areal and geostatistical data. It also shows how to create interactive maps of disease risk and risk factors, and describes how to build interactive dashboards and Shiny web applications that facilitate the communication of insights to collaborators and policy makers.
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.
Inhaltsangabe
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.
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.
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