In the discussion in the main webpage on Covid-19 and fearmongering, there was a discussion started by someone calling him (her) self John Piliger about an interview with Mike Yeadon. This prompted a discussion and I responded in that thread but would like to elaborate a bit more here.
Mike Yeadon’s basic hypothesis is that SAGE got it all wrong, because there is an absence of immunologists and virologists and a preponderance of mathematical modelers and herd psychologists (sorry my term) in SAGE. This has led to a rather skewed discussion and recommendations. I basically agree with this, having discussed the folly of relying on mathematical modelling as a main tool to combat a new pandemic, rather than on reflex applying traditionally tried and tested, pre-prepared plans for dealing with the pandemic. The aim would have been to reduce transmission to near zero, something achieved by China, New Zealand and Australia and others. This would have been a single bite at the cherry as wider transmission make any measures more difficult to implement. Just to recap: an early use of PPI amongst frontline workers, widespread testing and tracking followed by effective supervised isolation was what was needed. The first lockdown was merely effective at ‘flattening the curve’ to buy time, but no more than that, and the time bought has been squandered; not entirely, because the NHS has become more stream lined to deal with cases and some treatments and better management is leading to improved survival. I maintain that it is now too late to apply lockdown, unless it is really draconian, which would be unacceptable- so it is too late to apply another lockdown. Other measures need to be taken. And this highlights the on the hoof nature of the decision making in this pandemic, that our government and its advisers have taken. A detailed long term plan with targets and regular reviews was needed, and strong involvement by all parties and local councils and public health. Instead there was a centralised, inefficient and privatised response.
To return to Mike Yeadon. Of course he has a point but there are also some problems with what he says. He says that SAGE made two errors.
- Error 1: Assuming that 100% of the population was susceptible to the virus and that no pre-existing immunity existed.
- Error 2: The belief that the percentage of the population that has been infected can be determined by surveying what fraction of the population has antibodies.
He then analyses these. He states that the first error assumes that because this is a new virus
It’s ridiculous because while SARS-CoV-2 is indeed novel, coronaviruses are not. There’s no such thing as an ‘ancestor-less virus’. You will recall at least two, then-novel coronaviruses in the recent past: SARS in 2003 and MERS in 2012 (Zhu et al, 2020). While they didn’t spread worldwide, they are very similar, both at a sequence level and at a structural level, to SARS-CoV-2.
But there’s much more than these infamous coronaviruses. For reasons I don’t understand, given the significance of what I’m about to tell you, none of the so-called medical correspondents and science journalists on radio and TV have ever (as far as I know) spoken of the four, endemic, common-cold inducing coronaviruses. It’s well understood by clinicians and scientists who’ve spent any time reading the scientific literature that at least four coronaviruses circulate freely in UK and elsewhere where they’ve been studied. They have names: OC43, HKU1, 229E and NL63 (Zhu et al, 2020). .
There is the assumption therefore that there is some background immunity to SARS Cov2 because of some similarities to other coronaviruses. And even if this cannot be shown by cross reacting antibodies, Yeadon states that this may be due to innate immunity and cross reacting memory T cells and that this has been shown for other viruses. In the case of corona viruses, this cross reactivity may be due to the similarities in the spike protein between the different viruses.
There is some evidence for this cross reactivity in antibody testing as
Sequence similarities of the common viral proteins between SARS-CoV-2 and SARS-CoV, MERS-CoV
or LPH-CoV (229E, NL63, OC43 or HKU1). The polyprotein 1AB, and spike (S), membrane
(M), envelop (E) and nucleocapsid (N) proteins
But the problem arises with inconsistencies with therefore arguing about the rates of antibody positivity, reported by the NHS/Imperial College study of 7%, and that of Ioannides in Santa Barbara of more like 30%. If you argue that one is an underestimate and the other is an overestimate then you will need to explain why. Are there methodological errors? Was the Ioannides test less specific, the NHS less sensitive, or perhaps less cross reacting, or was it a genuine difference in population exposure? If the antibody test is unreliable, why do we believe one set of figures and not the other? Yeadon makes no such attempt at explaining, he merely states that he thinks the NHS figure is wrong. When two sets of studies give different results it is important to know why, rather than to assume that one is right and the other wrong as it suits you.
To turn to the second supposed error by SAGE. Yeadon produces two charts: on the left is one reflecting what SAGE believes that 7% of population is infested and 93% susceptible. On the right is another chart with figures postulated by Mike Yeadon as follows:
- 30 percent prior immunity (assumed)
- As many as 32% infected (presumably from Dr. Ioannides’ figures)
- Only 28% susceptible.
From these figures Mike Yeadon states that he therefore thinks the pandemic is virtually over in the UK and is now just doing its rounds about the country, and there shall be no second wave.
Some of this may be true but we would need more robust reasons to believe this, hard figures, especially about this 30% and 32%. We need to know if there are genuine geographic and ethnic and other genetic susceptibility and many other factors. Measurable antibody T cell and antibody responses may or may not be different or may or may not be protective.
In fact there may be other observational data to suggest that there may be geographic and environmental and ethnic factors that may lead to variability. The pandemic seems to have hit hardest in Europe and North and South America, but much less so in Asia and perhaps also Africa, although the data there may be more difficult to get. Some countries have had very few cases and deaths, notable amongst them are Vietnam, Taiwan and Thailand. I do not have information as to whether these countries applied particularly stringent rules, I could be advised. On the other hand BAME communities seem to suffer more from the burden of the disease in the West, suggesting that the difference is not genetic and that other factors may come into play. Could it perhaps be that there is more prevalent cross immunity with other corona viruses in Asian countries but not in Asian communities in the West where exposure to some of these viruses is less common? I have no idea but this could be looked at.
In conclusion, I agree that the constitution of SAGE should be looked at to be more inclusive, I also think that the public health aspects should be left to experts and not politicians, but I do not believe that this pandemic is over. Only time will tell.