** A novel online access to this important event**
*A new low student rate is also now available*
Using R for Bayesian Spatial and Spatio-Temporal Health Modeling
Parts I, II
March 4th - 5th 2024
COURSE CONTENT
These courses are designed to provide a comprehensive introduction to the area of Bayesian disease mapping using R in applications to Public Health and Epidemiology: Part I will run on March 4th and Part II on March 5th 2024.
Part I consists of sessions dealing with:
AM
• Basic concepts of Bayesian methods and disease mapping
• Bayesian computation: MCMC and alternatives
PM
• R graphics for spatial health data
• Bayesian Hierarchical Models for disease mapping (BHMs):
Simple models: Poisson-gamma; log-normal, convolution.
Variants: Leroux, mixture, BYM2.
• Model goodness of fit
• Demonstration of risk estimation and using R2OpenBUGS
Part II consists of sessions dealing with
AM
• Nimble
• CARBayes
• INLA
PM
• Space-time modelling with McMC (Nimble)
• Space-time modelling with INLA
• Clustering in space and space-time
• Infectious disease modelling and surveillance
THE SPEAKER
Andrew B. Lawson (Department of Public Health Sciences, College of Medicine, Medical University of South Carolina) is a MUSC Distinguished Professor Emeritus and a World Health Organization (WHO) advisor
on Disease Mapping and organized with WHO an international workshop on this topic which has led to an edited volume "Disease Mapping and Risk Assessment for Public Health".
He recently acted as chief editor of the CRC Handbook of Spatial Epidemiology (2016).
He has published a number of books focused on disease mapping and spatial epidemiology. In particular, the 3rd edition of the book: Lawson, A. B. Bayesian Disease Mapping CRC Press, appeared in 2018.
The recent addition:
Lawson, A. B. (2023) Using R for Bayesian Spatial and Spatio-Temporal Health Modeling. CRC Press.
will be a course text for the workshop. A copy of this book is included in the fee for the in-person course. A e-book version is included in the online registration. Paperback version available at an added cost.
COURSE FEE AND REQUIREMENTS
Booking of the two-day course sequence is $500.
**Early Bird rate of $400 before February 20th**
Student rate (With proof of status): $300
A variety of R packages will be used in the workshop. The main R packages used will be R2OpenBUGS, Nimble, CARBayes, and INLA.
The graphics libraries maptools, sp, spdep, sf, tmap, and ggplot2 will also be used.
Registration queries can be made with Mary Grace Strickland (stricmar@musc.edu).
Technical queries can be made to Andrew Lawson (lawsonab@musc.edu)
Registration form at :
https://medicine.musc.edu/departments/phs/news-and-events/upcoming-events/bayesian-workshop
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Andrew Lawson
Distinguished Professor Emeritus
Medical University of South Carolina - Dept of Public Health Sciences
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