CE_12C: Using R for Bayesian Spatial and Spatio-Temporal Health Modeling (Added Fee)

R is commonly use now for advanced Biostatistical applications. Bayesian spatial and spatio-temporal modeling of health data is an important topic which can be addressed using tools in R. This course is designed for those who want to cover mapping methods, and the use of a variety of software and variants in application to small area health data. The course will include theoretical input, covering selected Bayesian spatial models, but also practical elements and participants will be involved in hands-on in the use of R, Nimble, and CARBayes in disease mapping applications. Various spatial examples will be covered in the course as well as simple space-time modelling. Examples will range over county level respiratory cancer incidence (spatial and spatio-temporal) and influenza and Covid-19 space-time modeling in South Carolina. The course would be suitable for those with some R experience, but limited experience of spatial modeling in health applications. A recently published book by the presenter, entitled Using R for Bayesian Spatial and Spatio-Temporal Health Modeling (2021) CRC Press, is the source of many examples in the course.