Quantitative and mechanistic principles of virus ecology and evolution

Abstract

Controlling virus epidemics requires generalizable understanding. This thesis takes a mechanistic, quantitative, model-based approach to studying viruses across scales of biological organization. There are three research chapters. In the first, I present a model of enveloped RNA virus environmental stability as a function of ambient temperature and humidity. Parametrized from virus inactivation data, the model can be used to extrapolate to unobserved conditions and to predict observations from other viruses. In the second, I introduce a model for the antigenic evolution of influenza viruses within and between hosts. With the model, I show how virus and immune dynamics within hosts and transmission dynamics between hosts constrain virus antigenic evolution. In the third, I model epidemic control at the population scale. Specifically, I study non-pharmaceutical interventions for minimizing peak epidemic prevalence, and show that while optimal and near-optimal strategies exist, they are not robust to implementation error. From the scale of virions to the scale of populations, mechanistic modeling can reveal general principles of virus ecology and evolution and helps us assess strategies for virus control.