There’s been a lot of recent media speculation based on a pre-preprint of a paper which you can read here: https://www.dropbox.com/s/oxmu2rwsnhi9j9c/Draft-COVID-19-Model%20%2813%29.pdf?dl=0

The paper had one eye-catching figure which essentially implied up to half of the UK could already have coronavirus. Naturally, this has been reported in the FT, Daily Mail, and other major news outlets, and was even mentioned by the PM in his press conference today.

So what’s really going on here? Does the paper somehow update what we thought before, which was that there were only a few hundred thousand cases?

In short, no. The paper explores what happens if you make different assumptions about the fraction of people who get seriously sick from coronavirus. “Our overall approach rests on the assumption that only a very small proportion of the population is at risk of hospitalisable illness.”

The paper essentially points out that *if you assume that a very low fraction of people with coronavirus need to be hospitalised*, perhaps just 0.1%, then a disease that is mild in 99.9% of people would give you similar numbers of deaths to what we’ve seen so far — if it had infected half the population.

Alternatively (as we currently expect) you would see these deaths from a severe disease that hospitalises maybe 5% of people if you only had 1% of the population infected.

The paper points out that it’s difficult to tell the difference between these two cases just based on what you see in the hospitals, which is true. It urges “serology” — widespread antibody testing — which will determine what percentage of people in the UK have had coronavirus. When we know that, we’ll know how severe the disease is, based on how many deaths and hospitalisations we’ve seen. And this test is being developed and should be distributed next week.

So is it likely that the disease is only severe in 0.1% of people? Sadly, no. We have population samples, like the Diamond Princess cruise ship, where the whole population was tested, so we know the exact figures. On that ship, 700 were sick, 35 ended up in intensive care, and 10 died. That gives a death rate of 1.4% and a severe illness rate of 5% — more than 50x the assumption in the Oxford paper. Similar data where whole populations were tested, such as a village in Italy that tested 3000 inhabitants, or Iceland which found a 1% infection rate in its population, also suggest that the rate of severe illness is likely much higher than 0.1%.

The Oxford paper is essentially saying: “well, hypothetically, the disease might have infected many more people in a mild way.” Then it plucks that 0.1% severity rate, which implies a 50% infection rate, out of the air to illustrate the point. In no way does it justify this number, anywhere in the paper… if you can find where it does in the paper I linked to you, why not read it and see?

I agree with the authors that there may be a lot of undetected cases, which would be great news for the severity of this virus. I hope that is the case. But until we see real evidence of that, this is basically just an imaginary scenario that demonstrates the value of widespread testing, and not any kind of scientific prediction. Yes, there is uncertainty in how severe the disease is. But it should come as no surprise that assuming it’s 50x less severe than the mainstream scientific community will give you an outlandish result.

To the best of our knowledge, most people have not had coronavirus yet. To the best of our knowledge, it can cause severe illness and death in many people. We must continue with the lockdown and social distancing measures. It’s the only safe thing to do.

I go into more detail here:

http://physicalattraction.libsyn.com/coronavirus-serology-misinformation-uncertainty

If the authors of the paper want to justify their figure of 0.1% severity as an *actual prediction* for how covid behaves, rather than an imaginary-world model assumption to illustrate a point, they must provide evidence.