Thanks to Lucie Lecomte for sending the link to this report by Kai Kupferschmidt in ScienceInsider: Disease modelers project a rapidly rising toll from Ebola. Excerpt:
Alessandro Vespignani hopes that his latest work will turn out to be wrong. In July, the physicist from Northeastern University in Boston started modeling how the deadly Ebola virus may spread in West Africa.
Extrapolating existing trends, the number of the sick and dying mounts rapidly from the current toll—more than 3000 cases and 1500 deaths—to around 10,000 cases by September 24, and hundreds of thousands in the months after that.
"The numbers are really scary,” he says—although he stresses that the model assumes control efforts aren't stepped up. "We all hope to see this NOT happening," Vespigani writes in an e-mail.
Vespignani is not the only one trying to predict how the unprecedented outbreak will progress. Last week, the World Health Organization (WHO) estimated that the number of cases could ultimately exceed 20,000. And scientists across the world are scrambling to create computer models that accurately describe the spread of the deadly virus. Not all of them look quite as bleak as Vespignani's. But the modelers all agree that current efforts to control the epidemic are not enough to stop the deadly pathogen in its tracks.
Computer models “are incredibly helpful” in curbing an outbreak, says infectious disease researcher Jeremy Farrar, who heads the Wellcome Trust research charity in London. They can help agencies such as WHO predict the medical supplies and personnel they will need—and can indicate which interventions will best stem the outbreak. Mathematical epidemiologist Christian Althaus of the University of Bern, who is also building Ebola models, says both WHO and Samaritan's Purse, a relief organization fighting Ebola, have contacted him to learn about his projections.
But the modelers are hampered by the paucity of data on the current outbreak and lack of knowledge about how Ebola spreads. Funerals of Ebola victims are known to spread the virus, for example—but how many people are infected that way is not known. “Before this we have never had that much Ebola, so the epidemiology was never well developed,” says Ira Longini, a biostatistician at the University of Florida in Gainesville. “We are caught with our pants down.”
To a mathematician, combating any outbreak is at its core a fight to reduce one number: Re, the pathogen’s effective reproductive rate, the number of people that an infected person in turn infects on average. An Re above 1, and the disease spreads. Below 1, an outbreak will stall.
Outbreak models typically assume that there are four groups of people: those who are susceptible, those who have been infected but are not contagious yet, those who are sick and can transmit the virus, and those who have recovered. A model, in essence, describes the rates at which people move from one group to the next. From those, Re can be calculated.
If the disease keeps spreading as it has, most of the modelers Science talked to say WHO’s estimate will turn out to be conservative. “If the epidemic in Liberia were to continue in this way until the 1st of December, the cumulative number of cases would exceed 100,000,” predicts Althaus.
Such long-term forecasts are error-prone, he acknowledges. But other modelers aren’t much more encouraging. Caitlin Rivers of the Virginia Polytechnic Institute and State University in Blacksburg expects roughly 1000 new cases in Liberia in the next 2 weeks and a similar number in Sierra Leone.
Vespignani has analyzed the likelihood that Ebola will spread to other countries. Using data on millions of air travelers and commuters, as well as mobility patterns based on data from censuses and mobile devices, he has built a model of the world, into which he can introduce Ebola and then run hundreds of thousands of simulations.
In general, the chance of further spread beyond West Africa is small, Vespignani says, but the risk grows with the scale of the epidemic. Ghana, the United Kingdom, and the United States are among the countries most likely to have an introduced case, according to the model. (Senegal, which reported its first Ebola case last week, was in his top ten countries, too.)