Friedrich August von Hayek, the Austrian-born British economist, titled his 1974 Nobel Prize acceptance speech ‘The Pretence of Knowledge’. A stalwart liberal (in the classical sense), Hayek’s speech criticised the notion that economists have sufficient knowledge to plan the economy.
Those who believed in this notion, he argued, were guilty of “scientism” – of assuming that economics is like the physical sciences, where complex phenomena can be described by simple mathematical laws.
For Hayek, however, economic planners did not have the same knowledge as physical scientists, but merely the pretence of knowledge. Their theories were superficially similar – mathematically complex, couched in symbols and equations. Yet they lacked something vital: the ability to make accurate predictions.
Re-reading Hayek’s speech, I noticed that it could apply just as well to ‘The Science’ of lockdown as it did to the science of economics in the 1970s. For example, if we substitute just a few words in this sentence, it captures the hubris of epidemiological modelling almost perfectly:
… this failure of the [epidemiologists] to guide policy more successfully is closely connected with their propensity to imitate as closely as possible the procedures of the brilliantly successful physical sciences – an attempt which in [their] field may lead to outright error.
As I noted recently, self-described experts appear to be no better at forecasting cases and deaths than well-informed laymen. And when it came to the crucial test-case of Sweden (the only major country in Europe that didn’t lock down last spring), the modellers erred spectacularly.
Researchers at Uppsala University in Sweden predicted 96,000 deaths for Sweden during the first wave. And as Phil Magness has shown, based on some clever detective work, Neil Ferguson’s team forecast almost the same number. As of today, however, Sweden’s official death toll stands at just 15,000.
Contrary to grand claims that lockdowns would allow us to ‘control’ the virus, it’s difficult to discern any effect of lockdowns on the epidemic’s trajectory – except in those few countries that managed to stem the tide of new infections using border controls.
Returning to Hayek’s speech, the bespectacled economist warned of the great harm that “scientism” could end up causing. The following sentence (again altered) sounds particularly prescient:
In the physical sciences there may be little objection to trying to do the impossible; one might even feel that one ought not to discourage the over-confident because their experiments may after all produce some new insights. But in [epidemiology] the erroneous belief that the exercise of some power would have beneficial consequences is likely to lead to a new power to coerce other men being conferred on some authority.
In this regard, it may be no accident that Neil Ferguson, whose report of 16th March 2020 has been described as the “catalyst for policy reversal”, was trained in physics – the most precise, yet abstract, of all the sciences.
Looking at the damage wrought by lockdown, it would now seem appropriate for Ferguson and his colleagues to accept – quoting Hayek once again – that “as a profession we have made a mess of things”.
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The egos and arrogance of the likes of ferguson cannot allow mere reality to disprove their genius theories
I have to disagree that the lockdown had no effect on the trajectory of the epidemic. I think there is clear evidence that the decline (which had started before lockdown did) was sharper than it would otherwise have been, and this goes in large part to explain the start of the second wave in the following Autumn.
The only second wave was a wave of false positive PCR tests
I think that’s true. The lockdown caused the virus to not spread so much in some parts of the country (Scotland, the North, the South-west) which would otherwise have experienced it earlier. Lockdown did have some effect but it mainly involved prolonging the epidemic. Which, it seems, is what at least some of the people in authority wanted.
I agree. See what I said in answer to Adamb.
Really?
Yes really, if you look the second wave had two peaks. The first one was too early to have been a winter infection outbreak, and you can see it was decliningby the end of November. The traditional winter respiratory virus then cut in when it usually does and lasted through the Xmas period and after.
I have done mathematical curve fitting. When using a classic bell-shaped infection curves for the initial outbreak and it is clear that the actual curve did not match the bell shape – it was not symetrical and the second half had a much steeper curve. By comparing the actual with the theoretical it is possible, graphically (area under curves) to calculate how many people had their “classical” infection stopped (actually just postponed) by the lockdown.
If you then consider the second wave as two infection curves superimposed but with a different start time, then you can do the same calculation (area under curves) for each of the two, and within the accuracy of my calculations the first part of the second wave is pretty much the same as the difference between the actual and theoretical.
To put it simply, the first lockdown delayed the infection of a large number of people and did not stop it.
So what about the second part of the second wave. This was a classical winter flu infection much of which was wrongly interpreted as Covid due to the similarity of symptoms and the frankly awful performance of the testing in place at the time.
It followed broadly the same trajectory as all flu epidemics in all previous years.
Had the lockdown not occurred, pretty much the same number of people would have died in total but we would have been over it by last Christmas.
I agree with this analysis. But I would add that the overall area under the first two curves was probably increased by the first lockdown as it pushed the problem into a late autumn/winter period rather than leaving it in late spring/summer. And the ‘flu’ wave after the new year was increased by vaccination in nursing homes.
There are probably a number of compounding factors to my simplistic analysis, including the fact that there will inevitably be more people with underlying problems due to the lack of treatment and the fact that the elderly were 6 months older than at the start.
Look at the graph for Sweden for early 2021 and overlay it on the UK graph – trajectories and timing (up and down) are virtually identical, although Sweden peaked at a lower level.
“Sweden (the only major country in Europe that didn’t lockdown last spring)“
Should not discount the Belarus experience – especially as they didn’t panic last year, somehow nevertheless didn’t all die, and now are being stampeded by the same suspects again this year, quietly ignoring the obvious fact that the predictions of doom failed to come true last year and the refusal to panic over a super-infectious all conquering disease somehow seems to have left enough uninfected unimmunes to allow for warnings of another “worst pandemic in history” this year!
I believe Croatia also abandoned lockdowns at a relatively early stage,
Been through the budget speech and the red book
No mention of ADE
Ooooppps!!!
https://www.zerohedge.com/geopolitical/doug-casey-why-carbon-hysteria-huge-threat-your-personal-freedom-and-financial
The same is true with regard to so called global warming, climate change etc..
Although the element of corruption might be an even bigger driver here than with lockdowns et.al….
Hayeks works were examined in 3 a part BBC documentary ‘The Trap’, by Adam Curtis.
2007 when the BBC still made some decent documentaries. It looks at the results of following or not following his advice and what might yet be to come.
It points in the direction of CCP style Social Credit that was then only looming in the distance.
It was discussed here last summer, including how Scientism had empowered the likes of ferguson.
Part 1 Our Dream Of Freedom is most relevant and is as attached on YouTube.
Modelling isn’t real world data. It’s just fancy guesswork, and which on the evidence of the past two years, has been a catastrophic error of epic proportions. Whether intentional or not of wrongdoing, those responsible have to be held to account.
‘Fortune Telling’ was once a criminal offence
Prophets were executed if their prophecies didn’t come true.
Neil Ferguson should be jailed (for life) for crimes against humanity.
Anthony Fauci should be jailed (then executed) for crimes against humanity.
Two evil men profiting financially from the suffering of other people.
UK & US governments should face military tribunals and the firing squad.
Alas, as with Tony Blair and WMD, nothing will happen to them in this lifetime.
This was posted very late by ‘jmc’ in reply to the article about a California health officials closing down a burger bar.
He(?) explains how when laws were made empowering such officials in Pandemic emergency, they were long standing medics with experience ‘walking fever wards’, the sort of people qualified to make decisions in such circumstances.
jmc then gives his views on those who now wield those powers, for our own good of course.
In my view epidemiologists are not basically scientists any more than economists are basically mathematicians. Basic scientists rigorously and accurately test discoveries, establishing what’s what. Then epidemiologists follow along collecting broad-brush, inaccurate and un-rigorous data; Yellow-card system an example.
Economists use, at best, previous 3 months data to predict next thus their next is now. Epidemiology’s even slower, collecting data from previous years. They’re persisting in rediscovering already well-known wheels while disaster un-folds to our detriment.
From early Feb 20 I was sneered at, jeered at, ridiculed and brick-walled every way I tried to get what I thought vital information published re panic.
In March 20 I added info re. restrictions. First time I managed to get through was May 21 when Iain Davis allowed my comment to appear on his site. No alternate media or ‘expert’ groups have published it themselves despite knowing: –
Due to human reproduction at cellular level, treating all the same murders millions.
It’s been known for years that prolonged fear and restrictions destroy health.
Prolonged fear and restrictions biochemically and physiologically: –
i) Disable thinking; increasing accidents and inhibiting learning.
ii) Cause ‘flight or fight’; increasing verbal and written abuse, aggression and physical violence.
iii) Weaken immune system by disrupting cortisol.
iv) Raise blood pressure, increasing fatal coronaries and incidence of hypertension.
Thus, damaging microcapillaries in lungs, kidneys and brain, exacerbating and increasing incidence of renal and respiratory illness.
v) Change gastrointestinal pH, exacerbating and increasing incidence of ulceration in gut. Some of those ulcers turn cancerous.
vi) Disrupt blood-sugar-level regulating hormones, exacerbating and increasing incidence of obesity and diabetes.
Food, alcohol, drugs instead of socialising further increase obesity, alcoholism, addiction, thence diabetes and liver cirrhosis.
vii) Disrupt endocrine system, causing increased miscarriages, reduced fertility.
viii) Cause muscular wasting and weakness, thence premature ageing and death.
Plus, masks increase immune system’s work-load and, biochemically and physiologically are likely to cause respiratory and cardiovascular illness.
In case prolonged fear and restrictions etc don’t finish us all off within 2 to 5 years, jabs were added. Increased fatal coronaries at home in April 20 were the start. Increased all-cause mortality is now showing – tip of ice-berg after 18 months.
If vital info had not been blocked, each would have been able to choose physical risk from virus or that from panic and restrictions themselves.
Every action of government has been exact opposite of good for our health.
Our good health is bad for Pharma’s profits.
It’s long been known the heathy need more fresh air, bed-rest if necessary, otherwise to continue as per usual when virus crop up.
What we need is to catch small dose, which is what increased fresh air gives us, to help our immune system quickly resolve issue once and for all.
It was known in March 20 that lock-up then would stop it being over and done with by Sept 20, push it into NHS busy season and be spot-on to ruin Christmas.
C. S. Lewis (1955) Narnia Chronicles:
“before you’re an old man and an old woman great nations in your world will be ruled by tyrants who care no more for joy and justice and mercy”
I’d recommend the BBC series (from 2011) “All Watched Over by Machines of Loving Grace” on the subject of using computers to liberate humanity (and the failure thereof). Seems pretty relevant, since Ferguson depends on computer modelling.
https://en.wikipedia.org/wiki/All_Watched_Over_by_Machines_of_Loving_Grace_(TV_series)
It isn’t quite the same.
In economics there are competing theories, none of which are able to predict future economic trajectory very well.
For covid, there are competing theories, some of which might explain current events and be able to predict future trajectory, however all but the orthodox view are quashed.
We’ve even got to the point where the orthodox view has elements with remarkably little scientific evidence behind them (facemasks, lockdowns, etc), yet they remain the ‘mandated’ view. Thus we are in a position where belief trumps evidence. I’d say that this should be called ‘religion’, but apparently it is called ‘follow the science’.
What caused the rate of growth in infections to reduce in February 2020 in the UK (yes that early) and then to turn to negative growth in March before the lockdown, was immunity and the seasonal affect of moving out of Winter.
As a result we could never really know how much related to seasonality and so there was an unwinding of what would have happened in Spring 2020 had it not been the changing of the seasons, and that unwinding happened in the Autumn. In terms of all cause mortality that resulted in some more extra all cause deaths in Autumn 2020 but nothing like what had happened in the Spring of 2020.
And then the vaccines appear, at least looking at the associations between vaccines and death (correlation is not causation) to have caused more deaths around January 2021.
The multiple scientific papers comparing severity of lockdown and deaths showed that lockdown most likely had roughly no effect either way on reducing infections, and if it it did have any effect in other countries it was only to delay the inevitable.
One of the mistakes that has been made is not recognising that we don’t know how this virus spreads and so creating a model of viral spread is very difficult.
Let’s assume going back to late 2019, everyone will subsequently encounter the virus at some point. Many had pre-existing immunity that meant they would never be seriously affected as an individual so let’s exclude them. What is the optimum way for a susceptible individual to encounter the virus and be least affected by it? One theory is that it’s not a case of getting infected or not, it could be that encountering the virus at a lower viral load gives the body a chance to set up some defences even if that’s at a low un-measurable level, so that when they do encounter a higher viral load later they are less likely to be affected by it badly. And as time goes on most people have had at least some low level encounter and so they have lower viral loads when they transmit and the chances of a person first encountering the virus at a high viral load with no protection reduces and the pandemic swiftly ends.
If you think of it that way (and that’s just one theory) then all that lockdowns do is to move the spread into high viral load scenarios such as hospitals and care homes.
But as an approximation if we assume that interventions have next to no affect we can try to model the early spread through a simple SIR type model if we get our pre-existing immunity and infection fatality rate figures rightand come up with an appropriate R, and don’t invent silly nonsense that an intervention will change R by some arbitrary amount rather than have no affect at all. And that works even though we don’t understand viral spread. But these models still have limitations because they don’t reflect reality in terms of assumptions as well as parameterisation.
We don’t know how SARS-C0V-2 spreads because we can’t put a fluorescent marker on each virus particle and follow it’s journey from person to atmosphere to person and into the mucus membranes etc. But given the lack of correlation between lockdowns and cases it’s as good as anything.
However the existing models seem to assume this is a binary situation, you’ve either encountered the virus or not. Some allow for heterogenity of the population in mixing and spreading but none as far as I am aware have moved away from the basic binary infected or not model, and each person infected gets infected at the same dose assumptions.
Back in early 2020 the Michael Levitt type models parameterised through data from the countries encountering the virus first had some value and predictive power. The incorrectly parameterised Ferguson model which was effectively a SIR model (or dressed up back of an envelope calculation) that assumed no prior immunity and a high infection fatality rate were literally worse than useless and out by an order of magnitude at least. And of course we know it ignored seasonality.
But now the affects of the vaccine in terms of original antigenic sin, leads to the possibility of reinfection and viral escape of the variants caused by mass vaccination, and possible susceptibility of the vaccinated to other infections because their immune systems have been unbalanced.
So that any model probably needs to model what has now become a complex adaptive system with a dynamic network of interactions, where we can’t even identify what those interactions are.
We need to accept that it is very difficult to create a good model currently. No harm in trying but we need to be realistic as to it’s likelihood of predictive success
All we can do is to stop these dangerous mass vaccinations rather than make modelling predictions and see what happens, but I can’t see governments doing that.
Any science in which controllable empirical experiments cannot be performed at a high rate to verify its theories is doomed to remain a pseudoscience. We’ve got quite a few of such and epidemiology is one nice example.
”…as a profession, we have made a mess of things.”
This certainly applies to Fergusson and his ilk (although they sought the numbers they produced), but can you think of any professions in the covid scam to whom it doesn’t apply?
I am in the Engineering Design profession and yes we simulate and model various outcomes, and dependent upon various inputs and scenarios etc. But there is no way a design would leave the drawing board and go straight into production. The design would be rigorously tested and only when very confident about the quality of the design would it be released for production.
Contrast this with the drivel that has been produced by the likes of Ferguson with his deranged models and the resultant misery that has been forced upon the UK and Worldwide public. It’s been an utter disgrace.
I think I understand now why the mantra of “testing, testing, testing” was burned into the consciousness of the public by the likes of Hancock, Vallance and Tedros at the outset – we are the test subjects, we will provide the feedback for their experimental gene therapy treatment.
You can put ‘climatologists’ in the sentence with the same effect ( ie computer modellers).
By the way as a physicist I object to being labelled ‘abstract’ and associated by type with Ferguson. Some of physics is abtract but much is based on real repeatable physical experimentation.
A knowledge of advanced mathematics is required, but Ferguson has applied his training to computer modelling and forecasting. As I said previously no-one can forecast accurately something with many variables; computer modelling techniques using statistical theory produce ‘numbers’. Quite often those numbers bear no relationship to the original variables yet the answers pass statistical test so are used. If ever those numbers/answers are close to actual outcome its invariably luck/chance.
This equally applies to medicine.
The fact that people are not all the same, that environments are different and complex makes it very difficult to make predictions about the behaviour of something of which so little is known, i.e. SARS-CoV2. You can add in several different vaccines and their distribution patterns just to make it harder still. There are so many variable I doubt any prediction can have an accuracy greater than 50%.
”Made a mess of things”? It depends who’s weighing up the situation caused. For the people whose mantra is 6uild 6ack 6etter, nothing could be finer. You have to destroy everything before you can rebuild it, after all. And we’re now well on the way.