This module continues on from Module 4 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. The course assumes all the material in Module 7. The material from Module 2 or 5 would be helpful, but not required.