In my three previous posts (1, 2, 3) on the Covid-19 response and statistical reasoning, I deliberately sidestepped a deeper, more uncomfortable truth that emerges from such analysis: that ideologically driven academic and institutional experts – credentialed, celebrated, and deeply embedded in systems of authority – played a central role in promoting flawed statistical narratives that served political agendas and personal advancement. Having defended my claims in two previous posts – from the perspective of a historian of science – I now feel I justified in letting it rip. Bad science, bad statistics, and institutional arrogance directly shaped a public health disaster.
What we witnessed was not just error, but hubris weaponized by institutions. Self-serving ideologues – cloaked in the language of science – shaped policies that led, in no small part, to hundreds of thousands of preventable deaths. This was not a failure of data, but of science and integrity, and it demands a historical reckoning.
The Covid-19 pandemic exacted a devastating toll: a 13% global GDP collapse in Q2 2020, and a 12–15% spike in adolescent suicidal ideation, as reported by Nature Human Behaviour (2020) and JAMA Pediatrics (2021). These catastrophic outcomes –economic freefall and a mental health crisis – can’t be blamed on the pathogen. Its lethality was magnified by avoidable policy blunders rooted in statistical incompetence and institutional cowardice. Five years on, the silence from public health authorities is deafening. The opportunity to learn from these failures – and to prevent their repetition – is being squandered before our eyes.
One of the most glaring missteps was the uncritical use of raw case counts to steer public policy – a volatile metric, heavily distorted by shifting testing rates, as The Lancet (2021, cited earlier) highlighted. More robust measures like deaths per capita or infection fatality rates, advocated by Ioannidis (2020), were sidelined, seemingly for facile politics. The result: fear-driven lockdowns based on ephemeral, tangential data. The infamous “6-foot rule,” based on outdated droplet models, continued to dominate public messaging through 2020 and beyond – even though evidence (e.g., BMJ, 2021) solidly pointed to airborne transmission. This refusal to pivot toward reality delayed life-saving ventilation reforms and needlessly prolonged school closures, economic shutdowns, and the cascading psychological harm they inflicted.
At the risk of veering into anecdote, this example should not be lost to history: In 2020, a surfer was arrested off Malibu Beach and charged with violating the state’s stay-at-home order. As if he might catch or transmit Covid – alone, in the open air, on the windswept Pacific. No individual could possibly believe that posed a threat. It takes a society – its institutions, its culture, its politics – to manufacture collective stupidity on that scale.
The consequences of these reasoning failures were grave. And yet, astonishingly, there has been no comprehensive, transparent institutional reckoning. No systematic audits. No revised models. No meaningful reforms from the CDC, WHO, or major national agencies. Instead, we see a retrenchment: the same narratives, the same faces, and the same smug complacency. The refusal to account for aerosol dynamics, mental health trade-offs, or real-time data continues to compromise our preparedness for future crises. This is not just negligence. It is a betrayal of public trust.
If the past is not confronted, it will be repeated. We can’t afford another round of data-blind panic, policy overreach, and avoidable harm. What’s needed now is not just reflection but action: independent audits of pandemic responses, recalibrated risk models that incorporate full-spectrum health and social impacts, and a ruthless commitment to sound use of data over doctrine.
The suffering of 2020–2022 must mean something. If we want resilience next time, we must demand accountability this time. The era of unexamined expert authority must end – not to reject expertise – but to restore it to a foundation of integrity, humility, and empirical rigor.
It’s time to stop forgetting – and start building a public health framework worthy of the public it is supposed to serve.
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The Multidisciplinarian 
#1 by Anonymous on May 20, 2025 - 8:15 am
Your history of the statistical approaches is interesting and as far as I can judge some of the criticisms of them valid. I find you more polemical criticism of policy much less convincing however. My sense is you are doing what you criticise others of – attempting to use a position of knowledge and authority in one area to proclaim what should be (or should have been) done in much wider areas of policy.
For example, you point to the large loss of economic output, which was obviously bad, but don’t suggest what an alternative might have been. Health services were on the brink of collapse, certainly in Italy and here in the UK. Politicians had days (possibly hours) to decide what to do, balancing many different priorities, and huge uncertainties. Doing something other than lock-down may well have led to health-service collapse followed by sequential collapse of other parts of society. At the time it was entirely unknown whether the next mutation would be far worse. Or whether vaccines would prove effective at all (not quibbles over 85 vs 95% effectiveness). I struggle to believe that even with perfect, unbiased statistical analysis policy decisions would have been significantly different, or should have been.
#2 by Bill Storage on May 20, 2025 - 1:12 pm
Thanks for reading and replying to my post. I’d like to respond to your concerns about the policy dimensions of the post, particularly the suggestion, as I read it, that I may be stepping outside my disciplinary lane.
True, I have no policy or clinical training. But my perspectives in the history and philosophy of science (HPS) are directly relevant to questions of how scientific knowledge is constructed, legitimized, and put to work. One of the central concerns of HPS is precisely this: how epistemic authority is translated into political authority, and how methodological assumptions shape action. I gave strong evidence of how flawed statistical approaches came to dominate decision-making processes – to the exclusion of uncertainty and public deliberation.
You rightly point out that decision-makers faced extraordinary pressures, including the threat of health system collapse. My aim is not to deny the dire times, but to show that the way statistical models were constructed, presented, and interpreted greatly narrowed the range of policy options.
Better institutional handling of uncertainty would have allowed for different options to be at least on the table. The issue is not that one could have known the “right” course of action, but that the policy narrative conveyed a level of certainty that was epistemically unwarranted and socially consequential.
That perfect statistical analysis may not have changed policy decisions is a fair point, valid in the abstract. However, the question is not whether perfect knowledge was available, but whether decision-making structures were responsive to the known limitations of available knowledge. They were not. Criticism on these grounds isn’t an academic luxury: it is essential if we are to learn from the experience and improve institutional readiness.
Lastly, your concern about polemics. This was a short commentary, clearly identified as such. And it built on a ton of analyses taken directly from medical journals and the like.
The snake probably needing to be put on the table here is Fauci, who I left out of the discussion. While there’s no smoking gun showing he refused expert participation – as many claim – the selection and exclusion of certain voices in key discussions raises questions about the breadth of expertise considered. The rapid shift in virologists’ stances and seemingly covert communications (e.g., Morens’ use of personal email to avoid FOIA requests) could suggest a controlled narrative. We’ll likely never get to the bottom of that, and doing so would be a waste of time. Instead (as I called for in the post), recalibrating risk models and ruthless commitment to sound use of data over doctrine before the next emergency seems prudent. Regardless of what actually transpired with Fauci, the lack of transparency (his and many others) was inexcusable – bad science and broken trust.
Thanks again for the detailed comments. Let me know what I got wrong here.
#3 by Atty at Purchasing on May 31, 2025 - 11:03 am
As we are having this conversation in 2025 and not five years ago in 2020, there is no excuse not to know that (1) As an alternative to ‘health system collapse’ the purveyors of ‘standards of care’ could have encouraged doctors instead of threatening them with flawed/fraud studies to support their ‘proscription’ of beneficial therapeutics such at HCQ, IVM, Vitamin D….[too many to name – too many hidden {the worst lie is the truth not told}], (2) which would have avoided many patients illness and induction into the ICU and unnecessary need for the # of ventilators put to use – for naught, (3) lockdowns whether for weeks, months, or years merely postponed the population exposure but not the number of infections. So we lockdown only to adjust the timing of the illness. The lockdowns aren’t the only injection of institutional and government oppression while we witnessed (if I am not witless) widespread censorship at a time when competing ideas should have been heard and debated. Faith in “science” = zippo! There’s too much to be said here, so I close with those that were suppressed such as Pierre Kory, Robert McCullough, Jay Battacharya (replaced Fraudchi) were right about the things the experts and institutions lied about:
Herd Immunity / Natural Immunity / Lies about Masks / Lies about social distancing / Lab origins of the virus / Illegal funding of labs in North Carolina and Wuhan / Too many to list
#4 by alphaandomega21 on August 9, 2025 - 2:50 am
I am in the UK. In 2020 they rebranded the ‘flu as COVID 19. This was why the ‘flu almost disappeared from statistics to be replaced by COVID 19. Rebranding is the common exercise of business when profits are falling.
In this case the pharmaceutical industry had the government to advertise it at our expense.
Vaccines are designed to insert the alleged cause of a specific named disease into a body.
It is then stated without justification except with a statistical manipulation that this trains the body to recognise the cause of the disease next time and hopefully resist it better.
It is a clever deceit for which people fall time and time again.