Calculating Amidst the Fog of War

When the CDC’s top modeler Martin Meltzer overestimated the reach of the Ebola outbreak in Africa last fall by over 65 times worse, some critics pointed to how such numbers can be overdramatized or misreported. But in an article in the Bellingham Herald, Associated Press medical writer Mike Stobbe argues that there are important business continuity lessons to be learned from Meltzer’s overestimation. “Modelers have become critical in the world of infectious diseases,” writes Stobbe. “Epidemics often have a ‘fog of war’ aspect to them, in which it’s not clear exactly what just happened or what’s about to happen next.”

Although Meltzer’s prediction of 500,000 to 1.4 million Ebola cases within a few months in West Africa turned out to be overshooting the actual 21,000 reported cases, he was asked to provide a worst-case estimate; a number which Stobbe says is valuable to get people to care enough to pay attention to risk. “The worst-case figures got the most attention,” writes Stobbe. “The media focused on them in headlines. Health officials highlighted them in their push to get more money and manpower devoted to the epidemic. And interestingly, those are the numbers health officials describe as the most successful part of Meltzer’s prediction paper.”

Stobbe cites Dr. Keiji Fukuda, assistant director-general of the World Health Organization and former colleague of Meltzer’s as saying that the report “galvanized countries – and people – to put in more effort” to combat Ebola.

The role of the CDC, says Stobbe, is to “prepare America for the worst,” and as such, modelers should look at extreme scenarios. “If Meltzer’s estimates push policymakers to bolster public health defenses, it’s all to the greater good.”

Some experts disagree, says Stobbe, who cites David Ozonoff, an environmental health professor at Boston University. “The way risk assessment is done in this country is the policy makers shoot the arrow and the risk assessors paint a target around it. There’s a flavor of this with modeling, too. If you say the purpose [of a modeling estimate] is motivational, that’s another way it’s not scientific.”