Evolutionary epidemiology: preparing for an age of genomic plenty

The fields of infectious disease epidemiology and molecular evolution have a surprising amount in common. At the most fundamental level they aim to describe and explain basic biological processes of transmission and loss, of pathogens and parasites in one case, and of genetic polymorphisms in the other. Both disciplines are rigorously quantitative and are underpinned by a mature framework of dynamical mathematical models. These frameworks were derived logically from first principles and survived mostly intact as empirical data of sufficient accuracy to examine them became available: a situation far more common in the physical sciences than in biology. Furthermore, stochastic models are common in mathematical epidemiology and molecular evolution, and progress in both fields has been accelerated in recent decades by the rapid and sustained growth in computer processing power and concomitant advances in methods of statistical inference.