New computer model that takes into account, not only features of the virus and how it transmits, but also what is being done to halt its spread, predicts that the Ebola epidemic in Liberia could end by June if current high rates of hospitalization and surveillance continue. “That’s a realistic possibility but not a foregone conclusion,” says John Drake, an ecology professor at the University of Georgia (UGA), who led the project to develop the model with other ecologists at UGA and also at Pennsylvania State University.

The team reports how they developed the model and ran some scenarios through it, in the open access journal PLOS Biology. Prof. Drake says their epidemic model is probably the first to take into account factors such as where infections occur, where patients are treated, growth in hospital bed numbers, and the adoption of safe burial practices. He and his colleagues hope the tool will help public health authorities fight the Ebola epidemic, because unlike many other models, it offers realistic forecasts. New Ebola model captures what is most important and ‘ignores the rest’

Public health officials use epidemic modeling to help them devise and implement disease controls. Several models of the 2014 Ebola epidemic in West Africa have been published. For example, in September 2014, a Centers for Disease Control and Prevention (CDC) model predicted Ebola cases could exceed half a million by January if efforts to contain the spread did not improve dramatically.

Prof. Drake says many of the models that have been published seek to estimate Ebola’s reproductive number – the number of new infections that a single infected person can generate. He says that while this is useful – and their model does it too – to get a realistic picture, it is also necessary to take other things into account, but not to the point of making it too complicated. He says their model “aims to be intermediate in complexity – it captures all the things we think to be most important and ignores the rest.”

In their paper, the team describes how back in the fall of 2014 – after a period of great uncertainty about the Ebola epidemic in West Africa – they ran five different scenarios through the model, each with a different set of assumptions about hospital capacity. In the worst case scenario – which assumed no increase in hospital beds – the model predicted there would be around 130,000 total cases of Ebola by the end of 2014.

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