There has been surprisingly little mention in the news (ie none that I have seen) of the first major analysis of the world data from the COVID-19 pandemic, published in The Lancet on July 21st, before H.M. Government started to panic over increased positive PCR tests, executed local lockdowns, and threatened national ones if the “R-number” virtual canary begins to look green around the gills.
Perhaps, though, it’s not surprising we have not heard about it from the BBC, given what we have come to expect, since the paper seems to undermine much of what the governments of the world have been doing from the start.
The paper repays careful reading, and isn’t too technical to make sense, so I won’t discuss the details too much. Basically, morbidity and mortality were closely related with the risk factors with which we are all now familiar – age, obesity, rates of various illnesses like cardiovascular disease and diabetes, and so on. Analysis seems to show that, although the overall pattern of the disease looks similar across nations, the complication and death rates match the different incidences of these factors pretty closely. They also map, as one might expect, to the availability of health resources and organisation, and certain other criteria for, in effect, the “good order” of nations.
What they don’t match, with certain provisos, is the degree to which society was shut down by governments. As the abstract says:
Rapid border closures, full lockdowns, and wide-spread testing were not associated with COVID-19 mortality per million people.
Let the significance of that sink in. Lockdowns did not, in the end, save lives, nor did banning international travel, nor did the frantic rush to ramp up testing. On the other hand, there is incontrovertible proof that lockdowns have caused many deaths, and that through their damage to the economy they will cause many more for years to come. Quarantine restrictions have damaged world trade and ruined the travel industry, not to mention their psychological and financial effect on stranded and quarantined travellers. And testing with PCR, as I explained recently, may mainly be serving to prolong an epidemic that ended weeks ago.
The most confusing aspect of the paper, to me, is an apparent contradiction of this conclusion, expressed in the very next sentence of the abstract:
However, full lockdowns (RR=2.47: 95%CI: 1.08 5.64) and reduced country vulnerability to biological threats (i.e. high scores on the global health security scale for risk environment) (RR=1.55; 95%CI: 1.13 2.12) were significantly associated with increased patient recovery rates.
On the face of it, it is hard to see how lockdowns would increase recovery rates if they didn’t improve mortality. Indeed, it is hard to see how lockdowns, which were designed to prevent infection, would help anyone recover. But I think the answer is partly that lockdowns, in some countries, did help health services cope with the initial surge of patients, and so help ensure optimal care. Another possible explanation is that, since most western countries dutifully pledged to follow WHO guidelines, and were for the most part equally panicked by the Ferguson non-peer-reviewed terror models, “full lockdown” correlations might simply be a proxy for ability to organise, as reflected in the phrase “reduced vulnerability to biological threats.”
But the bottom line in the abstract is that all the things we didn’t like about our governments’ responses, that is to say the hubristic attempts to “defeat the virus” rather than cope with it as has always been the case previously, did no good anyway:
Interpretation: In this exploratory analysis, low levels of national preparedness, scale of testing and population characteristics were associated with increased national case load and overall mortality.
That’s not to say we have to be fatalistic about such novel diseases and await our inevitable demise. The actual causes of avoidable death, from obesity to inadequate planning, are things we knew about before. Some of them (like the rates of heart and lung disease and diabetes) appear to be the results of previous government interference in individuals’ lives, if the falsity of the “animal fats bad, carbohydrates good” dietary hypothesis we’ve all been pushing for decades is indeed the case. But it’s not earth-shattering to say that if we sort out chronic health problems, eliminate extreme poverty, organise health services well and do some contingency planning, we’ll cope best when viruses arrive.
Paradoxically, the study seemed to confirm an earlier impression that smoking might be somewhat protective against COVID mortality, so we can blame public health efforts at cutting smoking too – though that would, I think, be rather unfair since smoking causes nearly everything else, including the heart and lung disease.
Joking aside, even good policies can have unforeseen downsides under special circumstances like this. But lockdowns are a different kettle of fish. They were always a vast, unprecedented, uncontrolled and unvalidated experiment on the world’s population. They could be reliably predicted to have severe untoward effects (and were, even in this blog, from the start).
This paper gives strong evidence that that experiment failed in every important way. Given the gung-ho way lockdown and the rest were adopted, every government that enforced them is morally culpable, as are the scientific bodies that advocated them – and, of course, the “world authorities” that lubricated and facilitated the whole business, of which the corrupt UN and WHO are at the forefront.
Others may draw some other useful lessons from this paper. Work of this kind has its limitations, in that looking at such a wide range of parameters was bound to show multiple correlations which may be entirely fortuitous, or at least only proxies for the real causes. There’s always the danger that it’s a case of “chasing p-values.” (Remember William Briggs helpful statistical principle: “Die, p-value, Die Die Die.”)
But non-correlation is pretty significant, and that is what the study shows between the acute policy responses to COVID-19, and the one figure that really matters, the overall mortality.
It’s nice when the data confirms ones initial instincts, even as bodies like BioLogos still appear to be suggesting we ditch them in favour of trusting the models that failed to predict the actual outcomes.
But hey – science is self-correcting, and in the meantime it’s only damaging 7 billion people.