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Professor: ‘Lockdowns Are the Greatest Policy Failure in History’

Ordinary Americans are protesting against elite lockdowns. The BFD.

Dave Pellowe
goodsauce.news

Professor Doug Allen has examined over 80 Covid-19 academic studies and data sites to discover that many of the models and cost/benefit studies which governments and their ‘experts’ relied on to arrive at their restricted freedom & lockdown policies were deeply flawed.

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That’s right — the opaque ‘science’ we were all told to trust blindly was bad science. They relied on false assumptions, which tended to over-estimate the benefits of lockdown and under-estimate the costs.

In the introductory summary of his ground-breaking report, “Covid Lockdown Cost/Benefits: A Critical Assessment of the Literature” (April 2021, Department of Economics, Simon Fraser University, Burnaby, Canada), Professor Allen explains:

“As a result, most of the early cost/benefit studies arrived at conclusions that were refuted later by data, and which rendered their cost/benefit findings incorrect. Research done over the past six months has shown that lockdowns have had, at best, a marginal effect on the number of Covid-19 deaths.”

“…It is possible that lockdown will go down as one of the greatest peacetime policy failures in Canada’s history.”

Professor Allen undertook his critical research to help his family and friends see past the curtain of big tech, media, bureaucracy and government brazenly censoring information and critical thinking which cast doubts upon their agreed responses.

Cracks are starting to appear in the public facade of certain regimes. But for a long time now, public announcements being dished up sensationally by the Lying Harlot Media every day conflicted with basic facts, if you only knew where to look.

I had an hour long conversation with the professor which Good Sauce supporters have “behind the scenes” access to, and above is the edited version, also available on podcast. Below is a summary of four major areas of assumption government experts made in the modelling which lead to their zealous commitment to failed policy.

Of the 40,000 or so papers published in the last year related to Covid, Professor Doug Allen sought out studies which dealt with lockdown and were related to the costs or benefits thereof. To be clear, lockdown means non-pharmaceutical state interventions like closing businesses, schools, outdoor spaces, and churches; social distancing and mask mandates, and restrictions on movement and private gatherings. It doesn’t refer to international border closures.

The report’s major conclusions are:

  • a proper cost/benefit analysis of a specific policy must consider all, and not just some cherry picked costs or benefits of implementation,
  • all analyses depend on assumptions, and many of the studies relied on false assumptions which over-estimated benefits and under-estimated costs of lockdown,
  • most of the early studies were proven incorrect by global experience and objective data,
  • advanced models with the benefit of real data have showed the benefits of lockdowns in preventing Covid deaths to be at best trivial, generally due to voluntary changes in behaviour by people most at risk while failing to prevent non-compliance by others,
  • death tolls in various countries is not correlated to lockdowns.

Economists are trained experts in modelling human behaviour and testing those models with real world data. Hundreds of papers have been written dealing with the costs and benefits of lockdown, and Professor Allen summarised their major findings.

The Faulty Assumptions in COVID Models

The Imperial College London’s modelling, led by Neil Ferguson, was relied on by most nations who reflexively hit the big red lockdown button no one knew was built into every president’s and prime minister’s desk. Their dire predictions included half a million deaths in Great Britain and more than 2 million in the US by July 2020, plus collateral deaths resulting from overburdened health systems. They dramatically recommended governments attempt to suppress the epidemic, and acknowledged the profound costs of doing so.

They actually acknowledged one of their key false assumptions, namely that individual behaviour would not change without government mandates, was probably unlikely.

Other problems with the Imperial College’s model which resulted in significantly over-estimating the costs of no lockdown were quickly pointed out.

  • Their assumed reproduction rate (Rt) was far too high,
  • Their assumed infection fatality rate (IFR) was too high and not age-dependent,
  • They assumed hospital capacities were unable to be increased, and
  • They assumed citizens wouldn’t change their social behaviour at all in the midst of a pandemic.

All of these assumptions lent themselves to exaggerate the model’s results in one direction only: over-estimating the number of cases and deaths.

When this model’s drastically overstated predicted deaths did not eventuate, comparisons of reality to it looked deceptively like remarkable success from the extreme state actions taken. Politicians take credit for low deaths by continuing to assume individual behaviour doesn’t change without mandated restrictions. Any cost/benefit model assuming no individual responses to a viral threat,  Professor Allen argues, must be discounted. Any work failing to separate mandatory effect from voluntary effect will mistakenly attribute all change to mandated lockdown.

How Much Is a Life Worth?

To do a cost/benefit analysis, economists will have to generally convert an expressed benefit like lives saved into a dollar amount to compare with predicted costs, or vice versa. How much one is willing to sacrifice to keep or acquire something is what it can be reasonably said to be worth to one.

Early models used to justify the costs of a lockdown assumed, falsely, that a life with less than a year remaining was the same value as one with many decades remaining. In our interview, Professor Allen pointed out the different level of grief at a funeral for someone in their 80s or 90s compared to a funeral for a very young child. We instinctively place different values on lives at different stages.

For these models to assume someone losing one day of potential future life is indifferent to someone with potentially eighty more years was unreasonable. Once again, this had the effect of greatly overestimating the benefits of lockdown so much that is was reasoned any and all other costs were justified.

I still, too frequently observe small-thinking people condemning any one questioning the costs and benefits of lockdowns as callous ‘granny-killers’, as if the whole world would not be a price too dear to save the life today of someone who would die tomorrow anyway.

If it was assumed that each life was worth ten million dollars, and the Imperial College’s model predicted 150,000 deaths in Australia, anything less than one and a half trillion dollars would be a net benefit if we could prevent them all. Hundreds of billions in lockdown costs seems, comparatively, cheap.

But most of the fatalities were always going to be in their seventies and eighties. Now, how many of you would actually pay ten million dollars (even if you had it) to live for another year or another three months at the most? It’s more than fair to say ten million dollars is not an objective value for every octogenarian’s life, and the economic justifications for lockdown alone were wildly overestimated, even if all the other assumptions about weren’t proven false.

Please note I am not making arguments for a utilitarian moral value of life, unlike those pushing for liberal abortion and euthanasia policies.

Lost GDP (national productivity) is another false assumption of the early cost/benefit analyses and models justifying lockdown. But this grossly underestimates the many other very real costs. Delayed health screening and deferred treatments have had an immeasurable,  negative impact on life years lost already and in coming years. Increases in unemployment with correlating increases in diabetes and obesity also have a real cost not measured by the immediate impacts on GDP.

The overestimation of benefits of lives saved by mandatory lockdown and the overestimated value of nearly all of those lives, combined with the gross underestimation of the costs of lockdown, made the governments’ cost/benefit analysis and modelling an incredibly poor basis for determining inevitably destructive public policy.

There’s So Much More.

Professor Doug Allen’s report is 55 pages summarising 80 different academic papers and data sources and can hardly be done any justice with even this long an article. The link is at the top of this article, but here it is again. If you have any remaining confidence in government experts and policies I highly recommend you open it and have a read for yourself.

The coordinated efforts of media, big tech, bureaucrats and politicians to obscure dissenting experts, contradicting data and unapproved opinions has made it essential to know where to find reliable, credible information for yourself. Watch the interview, and judge for yourself if this is a tinfoil conspiracist with an axe to grind, or an intellectually honest academic wanting to help people think for themselves and peer behind the curtain.

Let me conclude here by quoting excerpts from Professor Doug Allen’s conclusion:

A review of the Covid-19 lockdown cost/benefit literature shows that the early cases made for lockdown rested on several unrealistic assumptions. These assumptions included that the virus continues to spread exponentially until herd immunity is reached, that individuals never change behavior in light of a viral threat, and that the value of lives lost is independent of age and around $10M.

Over the course of the last year research has revealed that simple SIRS models fail to predict the progression of the virus, that individual reactions to the virus are important, and that the costs of blanket lockdowns are far reaching and large. Lockdowns have some effect on cases, transmissions, and deaths, but these effects are marginal. As a result, lockdowns fail to pass a cost/benefit test.

…By late April [2020] it was already known that i) the empirical predictions of the SIRS based models were wrong, ii) that the models made a number of questionable assumptions, iii) that the deaths were highly skewed to the elderly, and iv) that the costs were large.

The progression of understanding about the virus has improved over time, but it has not fundamentally changed. By August [2020] there was enough information available to show that any reasonable cost/benefit analysis would show that lockdown was creating more harm than good. It is unreasonable to suggest that a proper decision could not have been made in [September 2020] when [Canada’s] second wave of infections hit.

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