Epidemic modelling at different stages of infectious disease outbreaks

Abstract

Mathematical models are useful tools for guiding control measures throughout infectious disease outbreaks. Early in an outbreak, key questions for policy advisors include whether or not initial cases will lead on to a major epidemic or fade out as a minor outbreak. When a major epidemic is ongoing, models can be used to track pathogen transmissibility and inform interventions. And towards the end of an outbreak, models can be used to estimate the probability that the outbreak is over and that no cases will be detected in future, with implications for when interventions can be lifted safely. In this talk, I present work from different stages of infectious disease outbreaks. This includes approaches for inferring the risk that introduced cases will lead to major epidemics (including the impact of a changing climate on the epidemic risk for vector-borne diseases) and a method for inferring the time-dependent reproduction number in real-time during outbreaks. I also suggest areas for future research, allowing interventions to be planned with more precision at different stages of outbreaks.