Coalescent inference for infectious disease

Today my student Bethany Dearlove has her first paper published, called Coalescent inference for infectious disease: meta-analysis of hepatitis C. In this paper, published in Philosophical Transactions of the Royal Society B, we have developed coalescent-based population genetics methods for popular, deterministic, epidemiological models known as SI (susceptible-infectious), SIS (susceptible-infectious-susceptible) and SIR (susceptible-infectious-recovered). By implementing these methods in BEAST, we were able to re-analyse previously published hepatitis C virus datasets and directly estimate epidemiological parameters. Our results show that, in the absence of co-infection, the widely-used exponential growth and logistic growth models of changing population size correspond directly to SI and SIS dynamics. We were also able to examine the limitations to genetic approaches to reconstructing epidemiological dynamics.

This paper appears as part of an issue on Next-generation molecular and evolutionary epidemiology of infectious disease, which accompanies a Royal Society discussion meeting organized by Oli Pybus, Christophe Fraser and Andrew Rambaut. The Royal Society has made audio recordings of the talks at this meeting, and the accompanying satellite meeting, available online, including my talk on Bethany's paper.