Lockdown is going to bankrupt all of us and our descendants and is unlikely at this point to slow or halt viral circulation as the genie is out of the bottle. What the current situation boils down to is this: is economic meltdown a price worth paying to halt or delay what is already amongst us?Tom Jefferson and Carl Heneghan, Centre for Evidence-Based Medicine, March 30th 2020
This is probably the most significant ‘known unknown’ when it comes to trying to understand the crisis and work out how best to respond. Simply put, if the Imperial College modelling by Professor Neil Ferguson and his team is correct and only 3-5% of the UK population has been infected, that’s a powerful argument for prolonging the lockdown. If we start relaxing social distancing measures, tens of millions of people will become infected, the NHS will quickly be overwhelmed and hundreds of thousands will die. This was the assumption built into the March 16th model which estimated the death toll at 510,000 if we took no precautions, 250,000 if we followed a mitigation strategy and 20,000 if we moved to a suppression strategy. In effect, the lockdown is preventing 230,000 unnecessary deaths, although that’s an underestimate if Professor Ferguson’s model is right because his 250,000 figure assumed that all those requiring critical hospital care would receive it when, in fact, the demand for critical care in the mitigation scenario would be eight times greater than the NHS’s emergency surge capacity. And even if we inflate that 250,000 to allow for this, that still doesn’t account for the total number of deaths that pursuing a mitigation strategy would result in because it doesn’t include the increase in the number of people dying from other diseases because the NHS would be overwhelmed.
But what if Professor Ferguson has underestimated the number of people who’ve been infected? A paper written by a team of scientists led by Professor Sunetra Gupta at Oxford University published on March 24th included a range of estimates of the percentage of the UK population that has already been infected, one putting it as high as 68%. (This was widely reported as a claim that half the UK population may have already been infected.) If that’s true, it suggests we’re well on our way to acquiring herd immunity and if we end the lockdown tomorrow the NHS will be able to cope, particularly as it has over 2,000 vacant intensive care beds compared to about 800 before the crisis. As of April 13th, 290,720 UK citizens have had swab tests, of which 88,621 were positive, or about 30%. True, this isn’t a representative sample, but against that some of the people tested will have been negative because they’ve already had it. In general, the fact that only a small minority of the population has been presenting with symptoms doesn’t mean a majority haven’t been infected because data out of China suggests four-fifths of those who get COVID-19 are asymptomatic. (Patrick Vallance, Chief Scientific Advisor to the British Government, thinks the real figure is likely to be closer to 30%.)
The Oxford paper was criticised on the grounds that many of the assumptions made by Professor Gupta were “speculative” and had no “empirical justification”, but the same is true of the Imperial model. The FT’s Jemima Kelly said Oxford’s research should be taken with a large dose of salt because it was “not yet peer reviewed”, but Imperial’s paper hasn’t been peer reviewed either. As John Ioannidis, professor in disease prevention at Stanford University, has pointed out, some of the major assumptions and estimates that are built into the Imperial model “seem to be substantially inflated”. But others are much more sceptical, such as Gregory Cochran, who argues that half the UK population cannot possibly have been infected since, if they had, you’d expect the percentage of people testing positive after being swabbed to be far higher. What if they’ve already had it and flushed it out of their systems? Cochran thinks that’s implausible because the virus is so new.
One of the reasons it’s so important to accurately gauge how many people have been infected is because without knowing that we don’t know what the infection fatality rate (IFR) is. That’s different to the case fatality rate (CFR), which is the number of people who’ve tested positive divided by the number of deaths. The CFR varies enormously from country to country. In Italy, for instance, it’s 11%, while in Germany its 0.79%. In Iceland, which has carried out more testing per capita than any other country (it only has a population of 364,260) it’s 0.2%, just above seasonal influenza. In the UK, the CFR is around 9%. But it’s a safe bet that the IFR, whatever it turns out to be, will be significantly lower than the CFR. If it turns out that 30% of the UK population has been infected and 20,000 people end up dying, that’s an IFR of 0.12%, or just above the IFR of seasonal flue. Knowing the IFR matters because we won’t know how much demand there’ll be for critical care in the NHS if we relax the social distancing measures until we know both what percentage of the population has been infected and what the IFR is. We should start to build up a more accurate picture of both once we start doing large scale serological testing – something like an opinion poll, i.e., a large, nationally representative sample of the UK population. A team at the University of Bonn tested a randomised sample of 1,000 residents of the town of Gangelt in the north-west of the country, one of the epicentres of the outbreak in Germany, and found that 15% either were or had been infected, yielding an IFR of 0.37%. For what it’s worth, Oxford’s Centre For Evidence-Based Medicine (CEBM) estimates the IFR to be between 0.1% and 0.26%.
In the US, research released on April 17th by Dr Ioannidis of Stanford University on actual infection rates in Santa Clara county using a serology approach to test for antibodies on over 3,300 residents suggests that the number of people actually infected is a staggering 50 – 85 times higher than the 956 cases that have been documented (see video link below and the research here). As he goes on to explain, this would make the fatality rate “in the same ballpark as seasonal influenza”. A second report, covering Los Angeles County, was released on April 19th with similar findings, with actual infection rates estimated at 28-55 times higher than the 7,994 documented cases.
One note of caution: we don’t know for sure that people who’ve had COVID-19 are immune, not in perpetuity. There is at least one instance of someone catching it twice – a Japanese woman, although she may have been immunocompromised. Even if you’ve had COVID-19 as a result of being exposed to SARS-CoV-2, coronaviruses have a nasty habit of mutating, so you could catch it for a second time from another strain that you’ve got no immunity to. However, cases of reinfection are extremely rare to date and when viruses do mutate they tend to become less deadly, not more. Why? Because more deadly strains kill off their hosts faster and hence are less successful at replicating themselves. As a rule, the most successful coronaviruses in evolutionary terms are the least harmful, like those associated with the common cold.
‘“Trump Is Right About the Coronavirus. The WHO Is Wrong,” Says Israeli Expert‘ by Oded Carmeli, Haaretz, March 21st 2020
‘Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic‘, Sunetra Gupta et al, MedRxiv, March 24th 2020
‘Coronavirus may have infected half of UK population – Oxford study‘ by Clive Cookson, Financial Times, March 24th 2020
‘How deadly is the coronavirus? It’s still far from clear‘ by Dr John Lee, The Spectator, March 28th 2020
‘Covid-19 – The tipping point?‘, Tom Jefferson, Carl Heneghan, Centre for Evidence-Based Medicine, March 30th 2020
‘It’s very rare to catch Covid-19 twice‘, FullFact, March 31st 2020
‘How likely are you to die of coronavirus?‘ by Tom Chivers, UnHerd, April 1st 2020
‘Covid-19: four fifths of cases are asymptomatic, China figures indicate‘, British Medical Journal, April 2nd 2020
‘Coronavirus, Castiglione d’Adda is a case study: “70% of blood donors are positive”‘ by Monica Serra, La Stampa, April 2nd 2020
‘Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters‘, John Ioannidis et al, medRxiv, April 8th 2020
‘Covid antibody test in German town shows 15 per cent infection rate‘ by Ross Clark, The Spectator, April 10th 2020
‘1-in-7 New Yorkers May Have Already Gotten Covid-19‘ by Justin Fox, Bloomberg, April 15th 2020
‘Has SARS-CoV-2 Fooled the Whole World?‘, Mikko Paunio, LockdownSceptics.org, April 16th 2020
‘COVID-19 Antibody Seroprevalence in Santa Clara County, California‘, John Ioannidis et al, medRixv, April 17th 2020
‘Stanford study suggests coronavirus is more widespread than realized‘ by Ross Clark, The Spectator, April 17th 2020
‘Global Covid-19 Case Fatality Rates‘ by Jason Oke and Carl Heneghan, CEBM, April 17th 2020
‘The end of exponential growth: The decline in the spread of coronavirus‘ by Issac Ben-Israel, The Times of Israel, April 19th 2020
‘Early results of antibody testing suggest number of COVID-19 infections far exceeds number of confirmed cases in Los Angeles County‘, University of Southern California and Los Angeles County Public Health Department, April 20th 2020
‘Getting a handle on asymptomatic SARS-CoV-2 infection‘, Daniel P Oran and Eric J Topol, Scripps Research, April 20th 2020
‘New York antibody study estimates 13.9% of residents have had the coronavirus, Gov. Cuomo says‘, CNBC, April 23rd 2020