April 1, 2015
In an article recently published in Proceedings of the Royal Society B, researchers argued that many of the simpler statistical models used to forecast the spread of infectious diseases may not appropriately account for random elements or uncertainty, and thus resulted in inflated early estimates of Ebola virus disease transmission.
“In the early days of the Ebola outbreak, a lot of people got into the forecasting business,” Aaron A. King, PhD, of the University of Michigan, said in a press release. “They did it using appealingly simple mathematical models, and the result was a series of warnings that alerted the world, quite rightly, to the seriousness of the situation … but in the end, most of those predictions turned out to be overstated.”