Thursday, March 26, 2020

Half of United Kingdom Already Infected With Coronavirus, Says Oxford Model, But ...


From Reason:
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.

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