Scientists at the University of Toronto in Canada have unveiled a new model for epidemic prediction that shows just how easily the Ebola outbreak could explode into something far larger than even the most dire predictions currently estimate.
According to New Scientist, David Fisman and Ashleigh Tuite’s prediction model is one of the first to factor in efforts to fight the epidemic, and what they found shows just how delicate the web of factors holding the disease in check truly is.
Fisman told New Scientist that current prediction models are estimating that 20,000 people will be infected with Ebola by November in Sierra Leone, Liberia and Guinea. By the time the epidemic subsides, which should be some time in 2016, an estimated 700,000 people will have contracted the disease in all.
These numbers are relying on reported cases of Ebola, however, which some experts argue is only part of the picture. Other estimates say the number of unreported cases is 2.5 times higher than current numbers.
According to Fisman, he and Tuite can track not just the spread of the disease, but whether efforts to combat it are growing in proportion to the epidemic. So far, he said, everything is on track, but any slowing of the effort to fight the disease could easily result in millions and millions more cases than are currently expected.
A Yale University team led by Alison Galvani estimates that if treatment centers are opened quickly enough and medical personnel are properly deployed, some 60,000 cases of Ebola infection can be averted in Liberia’s capital city of Monrovia alone.
Galvani told New Scientist that in order to meet that goal, enough isolation and treatment centers must be in place to isolate 70 percent of infected people by Dec. 1. The U.S. military has said that its treatment and isolation wards will take “a few weeks” to set up.
Fisman said that thanks to efforts already in place, each person diagnosed with Ebola is infecting fewer other people. The effort to fight the disease’s spread just isn’t growing fast enough, currently, he said.
So far, he said, his tracking model has worked “freakishly well” at predicting the course of the outbreak.
When he runs scenarios through the model in which any of the many relief efforts falter — which they easily could in cases of extreme civil unrest and hysteria — the predictions for the affected nations become very dire.
The model is currently predicting that the outbreak will peak in 2015 and begin to recede. If vaccines and other experimental drugs work according to plan, Fisman said, the end could come sooner.
It is wildly difficult to predict the course an epidemic will take, noted Fisman, but if his team’s predictive model remains accurate, little changes or lapses in how Ebola is being fought could make a big difference in the epidemic’s ultimate outcome.