Prerequisites: This module assumes knowledge of the material in Module 1: Probability and Statistical Inference, though not necessarily from taking that module.

The course first studies some basic stochastic models for the spread of an infectious disease and presents large population results for them including threshold phenomenon (Ro), distribution of the final number infected, and the critical vaccination coverage (the fraction needed to vaccinate to avoid future epidemics). Several extensions towards realism are then discussed: different types of individuals and social structures in the community including households and networks.

Then focus shifts towards statistics and how to obtain estimates of relevant model parameters from epidemic data. The course will give the theoretical background but also numerous examples from empirical situations including estimation of various vaccine efficacies. There will be class exercises during the course.