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- David Champredon, Michael Li, Benjamin M Bolker, and Jonathan Dushoff.
- McMaster University, Hamilton, Ontario, Canada; York University, Toronto, Ontario, Canada. Electronic address: david.champredon@gmail.com.
- Epidemics. 2018 Mar 1; 22: 36-42.
AbstractWe use two modelling approaches to forecast synthetic Ebola epidemics in the context of the RAPIDD Ebola Forecasting Challenge. The first approach is a standard stochastic compartmental model that aims to forecast incidence, hospitalization and deaths among both the general population and health care workers. The second is a model based on the renewal equation with latent variables that forecasts incidence in the whole population only. We describe fitting and forecasting procedures for each model and discuss their advantages and drawbacks. We did not find that one model was consistently better in forecasting than the other.Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.
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