A sub-exponential branching process to study early epidemic dynamics with application to Ebola

Abstract

Abstract Exponential growth is a mathematically convenient model for the early stages of an outbreak of an infectious disease. However, for many pathogens (such as Ebola virus) the initial rate of transmission may be sub-exponential, even before transmission is affected by depletion of susceptible individuals. We present a stochastic multi-scale model capable of representing sub-exponential transmission: an in-homogeneous branching process extending the generalised growth model. To validate the model, we fit it to data from the Ebola epidemic in West Africa (2014–2016). We demonstrate how a branching process can be fit to both time series of confirmed cases and chains of infection derived fr..