The course assumes all the material in Module 8: MCMC I for Infectious Diseases or the equivalent knowledge of MCMC. The material from Module 2: Mathematical Models of Infectious Diseases and Module 5: Stochastic Epidemic Models with Inference would be helpful, but not required. Students should had a working knowledge of R.

This module continues on from Module 8 by looking in detail at practical implementation issues for MCMC methods when applied to data from infectious disease outbreaks. The main focus will be towards inference for the SIR (susceptible-infected-removed) model. Topics include parameterisation, methods for improving convergence, assessing MCMC output, and data augmentation methods. Programming will be carried out in R.