Lots of media reports are citing the results of an epidemiological model developed by researchers at Oxford University that suggests that half the population of the United Kingdom may already have been infected by the novel coronavirus that causes COVID-19. If this is true, that would be great news! Why? Because it would mean that the coronavirus is vastly less lethal than many researchers fear that it is and that lockdowns can be lifted soon. But let's take a look at what the model is actually saying before you rush out into the streets to hug strangers in celebration of the impending end of quarantine.
There are two big assumptions in the model that basically determine its projections of the percentage of the population who will eventually die of the infection. The first is the basic reproduction number (R0), that is, the average number of people to which an infected person will pass along the disease. The other crucial assumption is that the fraction of the population who are vulnerable to severe disease and death is small.
The researchers explain, "Our overall approach rests on the assumption that only a very small proportion of the population is at risk of hospitalisable illness." How small? In one scenario, only 1 in 1,000. In two others, 1 in 100 are susceptible to severe disease.
The researchers run three scenarios based on the assumption that the first reported death occurred one month after the infection began spreading unnoticed throughout the U.K. They fit their model to the data on deaths from the disease reported after the first 15 days following the first recorded death. They argue that this is a way to avoid any potential effects of control strategies in slowing death rates.
Combining an assumed susceptibility to severe disease rate of 1 in 100 with R0s 2.25 and 2.75, the researchers project respectively that 36 and 40 percent of the U.K.'s population was already infected by March 19. If the susceptibility risk is only 1 in 1,000, then 68 percent of Britons must have been infected by March 19. If these infection rates are true, then the U.K. is approaching herd immunity, making the spread of this disease from person to person less and less likely, thus providing protection for even the more vulnerable segments of the population.
The researchers do acknowledge that "these results underscore the dependence of the inferred epidemic curve on the assumed fraction of the population vulnerable to severe disease." Well, yes.
This is basically a circular argument: If the disease is not particularly severe then that means a larger percentage of the population must have already have been infected to yield the observed number of deaths. On the other hand, if the disease risk is severe then the observed deaths suggest that very few people must currently be infected.
Of course, all models, including those projecting epidemiological doom, are only as good as their assumptions and data that drive them.
The researchers suggest that the way to test their model is to begin an immediate campaign of population screening using serology tests for coronavirus antibodies. If a significant proportion of people tested positive for exposure to the virus, that would confirm their model's projections. This would mean that the disease is relatively mild for the vast majority of people and substantial herd immunity has already been established. If few people test positive, then that would mean the worst of the epidemic still lies ahead.
As it stands, the public, policy makers and public health officials don't have the data that can tell them which course of the epidemic is more likely—the Imperial College model's dire coronavirus projection or the Oxford model's rosier one? The Oxford researchers are right that massive testing would resolve this vital issue, so let's get started sooner rather than later.