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Bayesian Workshop 2023

The Department of Public Health Sciences is excited to offer its annual Bayesian Workshop: Using R for Bayesian Spatial and Spatio-Temporal Health Modeling, Parts I and II.  The workshop is being offerd in-person and online.  The workshop is designed to provide a comprehensive introduction to the area of Bayesian Disease mapping using R in applications to Public Health and Epidemiology.   This course sequence 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.

Part I

June 1, 2023

  • Basic concepts of bayesian methods and disease mapping
  • Bayesian computation: MCMC and alternatives
  • R graphics for spatial health data 
  • Bayesian hierarchical models for disease mapping (BHMs):

Simple models: poisson-gamma: long-normal, convolution

Variants: leroux, mixture, BYM2

  • Model goodness of fit
  • Demonstration of risk estimation and using BRugs/OpenBUGS

Part II

June 2, 2023

  • Nimble
  • CARBayes
  • INLA
  • Space-time modeling with McMC (Nimble)
  • Space-time modeling with INLA
  • Clustering in space and space-time
  • Infectious disease modeling and surveillance


Registration Information

In-Person Workshop

Two-day course sequence is $1,000.00

Early bird rate of $600.00 before May 20, 2023

Online Workshop

Two-day course sequence is $ 500.00

Student rate for online workshop is $250.00

Registration Deadline is May 26, 2023


Please see the "Using R for Bayesian Spatial and Spatio-Temporal Health Modeling" Information Packet for more information.

To Register:

1. Complete the registration form (PDF) and send to Paula Talbot at

2. Complete the billing information below and click submit.


For more information about the Bayesian Workshop contact Paula Talbot at

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