Modelling infectious diseases: what can branching processes tell us?

Mathematical descriptions of infectious disease outbreaks are fundamental to understanding how transmission occurs. Reductively, two approaches are used: individual based simulators and governing equation models, and both approaches have a multitude of pros and cons. This talk connects these two worlds via general branching processes and discusses (at a high level) the rather beautiful mathematics that arises from them and how they can help us understand the assumptions underpinning mathematical models for infectious disease. This talk explains how this new maths can help us understand uncertainty better, and shows some simple examples. This talk is somewhat technical, but focuses as much as possible on intuition and the big picture.