Real-time forecasting of infectious disease dynamics with a stochastic semi-mechanistic model.

ABSTRACT: Real-time forecasts of infectious diseases can help public health planning, especially during outbreaks. If forecasts are generated from mechanistic models, they can be further used to target resources or to compare the impact of possible interventions. However, paremeterising such models is often difficult in real time, when information on behavioural changes, interventions and routes of transmission are not readily available. Here, we present a semi-mechanistic model of infectious disease dynamics that was used in real time during the 2013-2016 West African Ebola epidemic, and show fits to a Ebola Forecasting Challenge conducted in late 2015 with simulated data mimicking the true epidemic. We assess the performance of the model in different situations and identify strengths and shortcomi

SUBMITTER: Funk S 

PROVIDER: S-EPMC5871642 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature