From the very beginning of the Wuhan plague, a huge question mark has hung over the panicked rush to lock down entire populations. Such a policy has never been used in response to a disease outbreak before – not even for Ebola or SARS – and there was no evidence to support the policies apart from “statistical modelling” which had been shown previously to be grossly exaggerated.
Lockdowns have delivered unimagined power to the hands of politicians and bureaucrats. Unsurprisingly, then, they show no inclination to give up their sudden, absolute power.
A year on, does the real-world evidence support lockdowns?
In short: no.
It never did, and it still doesn’t.
As far back as April, The BFD was warning that not only would lockdowns cause more problems than they might conceivably solve, but that the evidence was already mounting that they did nothing to stop the spread of the virus. For months, the evidence just kept getting stronger.
A year later, the evidence is even clearer: lockdowns do not work.
The question is whether lockdowns worked to control the virus in a way that is scientifically verifiable. Based on the following studies, the answer is no and for a variety of reasons: bad data, no correlations, no causal demonstration, anomalous exceptions, and so on. There is no relationship between lockdowns (or whatever else people want to call them to mask their true nature) and virus control.
Despite the feeble efforts of some supposedly “scientific” publications, let alone the endless, lickspittle bloviating of clownish media tarts in labcoats, the real-world evidence for lockdowns (as opposed to computer models) is heavily outweighed by the observed evidence against.
The pro-lockdown evidence is shockingly thin, and based largely on comparing real-world outcomes against dire computer-generated forecasts derived from empirically untested models, and then merely positing that stringencies and “nonpharmaceutical interventions” account for the difference between the fictionalized vs. the real outcome. The anti-lockdown studies, on the other hand, are evidence-based, robust, and thorough, grappling with the data we have (with all its flaws) and looking at the results in light of controls on the population.
Data engineer Ivor Cummins has assembled a list of some 26 peer-reviewed scientific papers which demolish the myth of lockdowns.
Typical comments from the papers include:
“[F]ull lockdowns and wide-spread COVID-19 testing were not associated with reductions in the number of critical cases or overall mortality”[…]
“Official data from Germany’s RKI agency suggest strongly that the spread of the coronavirus in Germany receded autonomously, before any interventions became effective. Several reasons for such an autonomous decline have been suggested. One is that differences in host susceptibility and behavior can result in herd immunity at a relatively low prevalence level.”
“[pro lockdown claims] involve circular reasoning. The purported effects are pure artefacts, which contradict the data. Moreover, we demonstrate that the United Kingdom’s lockdown was both superfluous and ineffective.”
“Comparing weekly mortality in 24 European countries, the findings in this paper suggest that more severe lockdown policies have not been associated with lower mortality. In other words, the lockdowns have not worked as intended.”
There’s also this poke in the eye for New Zealand’s self-annointed COVID Queen:
According to the lockdown narrative, Taiwan did almost everything ‘wrong’ but generated what might in fact be the best results in terms of public health of any country in the world.”
“The apparent ineffectiveness of lockdowns suggests that New Zealand suffered large economic costs for little benefit in terms of lives saved.”
Several analyses show that the arguments claiming that lockdowns such as New Zealand’s “eliminated the virus” are nonsense, based on faulty, post-hoc reasoning. Just because infections declined after lockdowns were imposed does not in fact prove that lockdowns caused it. In fact, comparing lockdown and non-lockdown jurisdictions shows an almost identical pattern:
“It turns out that a similar pattern – rapid increase in infections that reaches a peak in the sixth week and declines from the eighth week – is common to all countries in which the disease was discovered, regardless of their response policies.”
The American Enterprise Institute
The full list of studies is here.
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