In his critique, Cooper noted that other, more detailed smallpox
models had come to similarly pessimistic conclusions about the
potential for a large outbreak. Despite the additional detail, though,
the models still contained an unrealistic feature: they had assumed
that most transmission occurred before people developed the
distinctive smallpox rash. Real life data suggested otherwise, with the
majority of transmission happening after the rash appeared. This
would make it much easier to spot who was infectious, and hence
control the disease through quarantine rather than requiring
widespread vaccination.
From disease epidemics to terrorism and crime, forecasts can help
agencies plan and allocate resources. They can also help draw
attention to a problem, persuading people that there is a need to
allocate resources in the first place. A prominent example of such
analysis was published in September 2014. In the midst of the Ebola
epidemic that was sweeping across several parts of West Africa, the
CDC announced that there could be 1.4 million cases by the following
January if nothing changed.[62] Viewed in terms of Nightingale-style
advocacy, the message was highly effective: the analysis caught the
world’s attention, attracting widespread media coverage. Like several
other studies around that time, it suggested that a rapid response
was needed to control the epidemic in West Africa. But the CDC
estimate soon attracted criticism from the wider disease research
community.
One issue was the analysis itself. The CDC group behind the
number was the same one that had come up with those smallpox
estimates. They’d used a similar model, with an unlimited number of
susceptible people. If their Ebola model had run until April 2015,
rather than January, it would have estimated over 30 million future
cases, far more than the combined populations of the countries
affected.[63] Many researchers questioned the appropriateness of
using a very simple model to estimate how Ebola might be spreading
five months later. I was one of them. ‘Models can provide useful
information about how Ebola might spread in the next month or so,’ I
told journalists at the time, ‘but it is near impossible to make accurate
longer-term forecasts’.[64]