When it’s a coronavirus one or to give it its incorrect but government-sponsored nomenclature of fear ‘the coronavirus’ (there are 23 species of coronavirus and that’s without further serotypes, so it is ‘a’ not ‘the’).
Recognition to John Lee (retired professor of pathology and former NHS consultant pathologist, clue: this man knows what he is talking about) for his source article around this issue. The normal position in this country when someone when an underlying health condition acquires a secondary infection, is admitted to hospital and dies, is that the underlying health condition is recorded as the cause of death. Unless the secondary infection is a notifiable disease. Not surprisingly (although one could argue slightly surprisingly given that other illnesses that can cause secondary infection such as seasonal flu are not notifiable diseases), COVID-19 was made a notifiable disease which gives the appearance of there being a higher number of deaths. Except these are mainly deaths with and not of/or from the disease itself.
For example someone with severe pericardial effusion contracts the virus and is admitted to hospital where unfortunately they die, is their cause of death pericardial effusion or COVID-19? Under the current basis of reporting, it is the latter whereas normally it would be the former.
As patients are being tested on admission to hospital, then it follows that any subsequent death of someone who tested positive for SARS-CoV-2 will be recorded as death from COVID-19. This oversimplification is based upon an apparently logical but immensely flawed assumption: testing positive for Y = death from Y, completely ignoring condition X which the person was suffering from in the first place. As Professor Lee so succinctly sums it up “there is a big difference between Covid-19 causing death, and Covid-19 being found in someone who died of other causes.”
To obtain a more accurate picture of how many deaths are actual COVID-19 deaths you have to adjust the total deaths figure to separate and identify those who would have died anyway from underlying condition X or from any other condition Y being introduced that caused a secondary infection, whether that other condition is Coronavirus SARS-CoV-2 or Influenza A(H1N1) or pneumonia.
The level of adjustment is open to debate but it would not be unreasonable to discount one half to two-thirds. This puts the death toll in a rather different light, one of context and greater accuracy.
Add to this the fact that the other side of the equals sign is the number of people with the virus. Say 1,000 people are admitted to hospital with symptoms and are tested for SARS-CoV-2: you would expect the vast majority, if not all, of them to test positive. Say 10 of them die with COVID-19. The death rate is 10 out of 1,000 so 1%. Now adjust based upon the above and the deaths of/from reduces to, say, 4. The death rate falls to 0.4%. Except the population is far greater than the 1,000 people admitted to hospital and tested.
Given that many with the virus are asymptomatic or suffer mild symptoms, in order to assess the death rate accurately you have to look at a much bigger number. Recognition to Oxford University’s Evolutionary Ecology of Infectious Disease group for their research here, which assesses that by 19th March between 38% and 40% of the UK population had had the virus. The central basis for their research was that SARS-CoV-2 has been around for longer than people give it credit and people were merrily contracting it and either not knowing or ‘feeling a bit under the weather’ for weeks, maybe even a couple of months, before the hysteria set in.
Using the above example, say 50x times more people out in the wider population have had the virus and been asymptomatic or experienced mild symptoms of the disease (in fact it’s everyone who contracted the virus but wasn’t admitted to hospital): on this basis you would have 4 deaths out of (1,000×50)= 50,000 people, which is 0.008%.
Based upon the latest data from Johns Hopkins Coronavirus Research Center, the UK’s death rate per 1million population is 132. That is 0.0132%. If you adjust for the of/from not with distortion using the same factor as above, the percentage reduces to 0.0053%.
These are very, very small percentages. Lower than seasonal or winter flu. The power of context not hysteria.