The COVID-19 pandemic has given populations around the globe first-hand experience with the volatility of opinions and their effect on prophylactic behaviour and, in turn, on disease prevalence. It is clear that disease models need to include human behaviour as a factor. In cases where opinions are fairly stable, or switch between well-defined stable states, behaviour can be captured by one or more model parameters. In other cases however, human opinions evolve on a timescale comparable to that of the epidemic, and so should be modeled as an additional dynamic variable. In this talk, we review models of opinion dynamics, and then couple these to disease models and see how the interaction between the two yields new insights into the evolution of epidemics in a human population.