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Some Covid Links

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The Brownstone Institute shares another excerpt from Paul Frijters’s, Gigi Foster’s, and Michael Baker’s 2021 book, The Great Covid Panic [2]. A slice:

Reducing the movements of healthy people was not going to move the needle in terms of stifling virus transmission among the truly vulnerable elements of the population. Worse, the logic of trying to keep movement limited meant there was almost no escape for governments from doing the wrong thing: once they and their health advisors had convinced the population that normal interactions were a serious risk, every move to ‘open up’ was seen as potential endangerment that could be exploited by political opponents.

I’m pleased and honored to have again been a guest, with John Tamny, on The Bill Walton Show [3].

Martin Kulldorff decries the sudden loss of long-held medical knowledge [4].

Noah Carl reports on reasons not to put much confidence in the predictions offered by Neil Ferguson and other “experts. [5]” A slice:

A more recent study [6] reached slightly different conclusions. Earlier this year, the epiforecast group at the London School of Hygiene & Tropical Medicine hosted a forecasting competition in which they invited members of the public to predict weekly case and death numbers in the U.K.

The competition ran from 24th May to 16th August. Both experts and non-experts were eligible to compete, experts being those who declared themselves as such when they signed up (so we’re presumably talking about epidemiologists and people with a background in forecasting).

What did the researchers find? In this case [7], the self-declared experts performed slightly worse than the non-experts, although neither group did especially well.

Why did the two studies reach different conclusions? I suspect the answer lies in the composition of each study’s non-expert group. In the first study, the non-experts were random members of the public, whereas in the second, they were laymen who chose to take part in a forecasting tournament.

The psychologist Philip Tetlock has gathered a large amount of evidence [8] that, when it comes to quantitative forecasting, experts aren’t any better than well-informed laymen (even if they do have an edge over the man on the street).

I suspect the non-experts who took part in the Covid forecasting tournament were the kind of well-informed laymen that Tetlock identified in his research. After all, you’d have to be pretty geeky to find out about such a tournament in the first place.

Overall, the evidence suggests that no one’s particularly good at forecasting the epidemic. Where the ‘experts’ do have an advantage is in making their predictions appear scientific.

Fraser Nelson reports on the “staggering costs” of a possible renewed lockdown in Britain [9].

The higher the rate of testing for SARS-CoV-2 infections, the higher will be the percentage of the population found to be infected [10].

Robert Dingwall criticizes the magical thinking from which much of the case for mask mandates springs [11]. A slice:

The bitter controversy over the use of masks or face coverings in community settings that has erupted in the USA and can also be seen in the UK and Mainland Europe has many of the characteristics of the contest between magic and science. Advocates of masks have struggled to demonstrate a causal connection between face covering and the transmission of the SARS-COV-2 virus. Their critics might well be forgiven for claiming that mask mandates are based on magical thinking and questioning whether the power of the state should be used to enforce this. Surely we have moved on from the Salem witch trials?