A few days ago, I gave a presentation at the Isaac Newton Institute for Mathematical Sciences in Cambridge on inferring disease dynamics from viral sequence data. This was intended as an accessible introduction to the coalescent, a mathematical model originally developed in the context of population genetics to infer population-level parameters from genetic data. It describes the effects of population size and demography on the genetic relationships among individuals in an evolving population. In our case, given epidemiological state variables *S*, *I*, *R*, etc... we can compute distributions of waiting times for lineages to find common ancestors as we walk backwards along a phylogeny. Slides and video from the presentation are available here. This talk forms a nice companion to the tutorial on phylodynamic methods I posted on GitHub a few months ago.