Mathematics of Life and Death: How Disease Models Shape National Policies
upstart writes in with an IRC submission for Bytram:
Jacco Wallinga's computer simulations are about to face a high-stakes reality check. Wallinga is a mathematician and the chief epidemic modeler at the National Institute for Public Health and the Environment (RIVM), which is advising the Dutch government on what actions, such as closing schools and businesses, will help control the spread of the novel coronavirus in the country.
[...] COVID-19 isn't the first infectious disease scientists have modeled-Ebola and Zika are recent examples-but never has so much depended on their work. Entire cities and countries have been locked down based on hastily done forecasts that often haven't been peer reviewed. "It has suddenly become very visible how much the response to infectious diseases is based on models," Wallinga says. For the modelers, "it's a huge responsibility," says epidemiologist Caitlin Rivers of the Johns Hopkins University Center for Health Security, who co-authored a report about the future of outbreak modeling in the United States that her center released yesterday.
Just how influential those models are became apparent over the past 2 weeks in the United Kingdom. Based partly on modeling work by a group at Imperial College London, the U.K. government at first implemented fewer measures than many other countries-not unlike the strategy the Netherlands is pursuing. Citywide lockdowns and school closures, as China initially mandated, "would result in a large second epidemic once measures were lifted," a group of modelers that advises the government concluded in a statement. Less severe controls would still reduce the epidemic's peak and make any rebound less severe, they predicted.
But on 16 March, the Imperial College group published a dramatically revised model that concluded-based on fresh data from the United Kingdom and Italy-that even a reduced peak would fill twice as many intensive care beds as estimated previously, overwhelming capacity. The only choice, they concluded, was to go all out on control measures. At best, strict measures might be periodically eased for short periods, the group said (see graphic, below). The U.K. government shifted course within days and announced a strict lockdown.
Epidemic modelers are the first to admit their projections can be off. "All models are wrong, but some are useful," statistician George Box supposedly once said-a phrase that has become a clichi(C) in the field.
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