Predictions with a purpose

THE Ebola epidemic in west Africa appears to be nearing its end. The number of new cases per week has averaged around 120 for the past three weeks in Guinea, Liberia and Sierra Leone, the lowest level since July. A trial of a potential treatment has been halted for lack of patients. The last embers will be difficult to extinguish; the numbers ticked back up in the latest weekly data. But the World Health Organisation (WHO) is now focused, not on control, but on snuffing it out.

With more than 22,000 people infected, nearly 9,000 of whom died, this outbreak was the gravest ever. But it confounded experts who had feared much worse. In September the WHO predicted more than 20,000 cases by November (there were actually about 13,000). Around the same time, a worst-case prediction by America’s Centres for Disease Control and Prevention (CDC) of up to 1.4m cases (reported and unreported) by January 20th made the headlines. Others were similarly bleak. So where did models and reality diverge?

For a start, the models relied on old and partial figures. These were plugged into equations whose key variable was the rate at which each case gave rise to others. But this “reproduction number” changed as outside help arrived and those at risk went out less, avoided physical contact and took precautions around the sick and dead. So difficult are such factors to predict that epidemiologists modelling a disease often assume that they do not change at all.

The CDC produced several projections, some of which tried to account for effective interventions. But it was the “very unlikely” worst-case scenario that grabbed the headlines. This assumed not only a stable reproduction number, but that known cases were just 40% of the total (based on the gap between the baseline model and figures for the number of people in treatment on a single day in August).

By presenting such grim projections, the experts arguably made it less likely that they would come to pass. One of their purposes, says Neil Ferguson, a member of the WHO’s Ebola response team, was “to wake up the world and say that this could be really bad if we don’t do anything”. They succeeded, and resources poured in. Subsequent predictions seemed aimed at keeping the disease in the headlines. Although the outbreak began to level off at around 1,000 new cases per week in October, WHO officials warned there could be up to 10,000 per week two months later.

No big study focused on changes in behaviour, such as a rise in safe burials, now credited with checking the outbreak. And the CDC’s attempt to estimate the number of unreported Ebola cases now appears far too pessimistic. In December researchers at Yale University showed that Ebola tends to cluster in small social groups, making it easier to find. They reckon that for each known case, fewer than had been thought lurk undiagnosed.

If that is right, not only were the numbers behind many projections wrong, but interventions such as isolating cases were more useful than expected. Other studies found that victims were most likely to transmit Ebola in its later stages, so finding cases early was more likely to disrupt transmission. In other ways, too, Ebola defied the prophets of doom. It never went airborne, and its economic effects were less painful than expected. Being wrong rarely feels this good. But it will be harder to catch the world’s attention next time.