Ebola outbreak severity is 'impossible' to predict, claims researcher

A new study has revealed that a mathematical model which was supposed to predict Ebola outbreaks has now been ruled out to foretell its severity.

ANI| Updated: Sep 17, 2014, 10:20 AM IST

Washington: A new study has revealed that a mathematical model which was supposed to predict Ebola outbreaks has now been ruled out to foretell its severity.

The research by the University of Warwick, titled Epidemiological Dynamics of Ebola Outbreaks, showed that when applying the available data from the ongoing 2014 outbreak to the model that it was, according to Dr Thomas House was now "out of all proportion" and on an unprecedented scale when compared to previous outbreaks.

Dr. House, of the University's Warwick Mathematics Institute, developed the model that incorporated data from past outbreaks that successfully replicated their eventual scale.

Dr House stated that if they analyse the data from past outbreaks they were able to design a model that works for the recorded cases of the virus spreading and can successfully replicate their eventual size, however, the current outbreak does not fit this previous pattern and, as a result, they are not in a position to provide an accurate prediction of the current outbreak.

Chance events are an essential factor in the spread of Ebola and many other contagious diseases. They could include a person's location when they are most infectious, whether they are alone when ill, the travel patterns of those with whom they come into contact or whether they are close to adequate medical assistance.

The Warwick model successfully replicated the eventual scale of past outbreaks by analysing two key chance events; the initial number of people and the level of infectiousness once an epidemic was underway.

Discussing possible causes for the unprecedented nature of the current outbreak, Dr House argued that there could be a range of factors that lead it to be on a different scale to previous cases; it could be as a result of a number of different factors; mutation of virus, changes in social contact patterns or some combination of these with other factors.

The study is published by eLife.