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Scott briefly observes, "The only thing about COVID nobody talks about anymore is the 1.2 million deaths.
A better comparison for 1.2 million Americans dying would be the Spanish Flu: An estimated 675,000 Americans died, while the total population was estimated to be round 106,000,000. (The 2020 estimated population was around 331,500,000.)
One problem I have with the online debates about covid policy is there's no clear counterfactual: 2021 deaths were higher than 2020 deaths, which is bad for arguments that containment policies were only protecting the most vulnerable at the expense of the general population, because the most vulnerable had disproportionately died in 2020 and management had improved. It's possible that a different set of policies would have resulted in disproportionately more QALYs lost by lower-risk demographics, due to the non-linear dynamics of disease transmission (don't forget rates of mutation). I don't really care to defend any policy, since there were a lot of avoidable mistakes, but I think the criticism should be more specific and measured.
(Edit: Scott's Lockdown Effectiveness: Much More Than You Wanted To Know, published July 1, 2021 - anyone know if there's been much change in the understanding of NPI effectiveness?)
It's difficult to talk about covid deaths without also talking about how the data was recorded.
For example, if someone was in a nasty car accident and died in the hospital. They would be considered a covid related death if they tested positive for covid.
There are other examples I could give (data taken during protests, etc) and we can talk about how often this actually happened but once data becomes suspicious, it's difficult to take it seriously.
Does anyone have a citation for a policy of counting everyone who tests positive for covid shortly before death as "a covid related death?" How should causes of death like "two illnesses, one of which is symptomatic covid" or "respiratory distress a positive covid test, but no other clear covid symptoms" have been counted?
I'm starting to feel like AI use is the new "just google it" for basic factual questions. This says:
After all that the citations are the BBC (reporting on the change from "anyone who has ever had COVID, regardless of whether it contributed to their death or not" to "anyone who has had COVID in the past 28 days, regardless of whether it contributed to their death or not"), and Colorado Public Radio ("Deaths from" vs. "deaths with").
The insistence on this conflation is probably one of the worse policy mistakes of national health authorities during the COVID years, not least because of (a) how upstream it was for justifying later (bad) policies on the basis of risk-severity, and (b) how obvious the implications of this could be to anyone already inclined towards skepticism with even a passing knowledge of statistical smuggling.
There are absolutely valid reasons to be very concerned about a potentially highly mutable pathogen in a population. You can absolutely believe a quarantine model could be necessary to protect at-risk people. But if you want to retain public trust and deference from a high-skepticism, low-trust, and literate population, you cannot smuggle in nakedly bad data to pad your numbers for public, population-level urgency. Too many discontents will read the data categories, recognize the issue, and spread the awareness. And too many people would be able to find examples of systemic incentives to miscount- even at the level of how some medical institutions could get more money for classifying patients as with-COVID. Which validates concerns / lack of trust in medical objectivity.
This was a (predictable) aspect of the pandemic response, as was the circle-the-wagons response and the partisan appeals to trusting the science. Except it was not science when it was being pushed, but Science. And those who insisted on championing The Science, or that people were bad for not believing policy proscribed on the basis of The Science, or even just that others should defer to those with The Science despite any misdirection from the authorities with The Science, have no basis for their own [current statistic] to be believed.
And a consequence of the inflated numbers is that they lost claim for establishing a shared understanding of what a 'true' number of deaths could be. 1.2 millions Americans died of Covid? Why should anyone believe that? How many 'died with' are smuggled into that? Does the argument from excess deaths also give credit for 'deaths saved' in later years from the people who died earlier but not later, or is it a one-way rachet to imply an above-average death rate in the area of scrutiny but not a lower-than-average death rate afterwards?
And why should anyone be concerned, without a baseline of comparison to establish relative rates? Is 1.2 million 1%, 5%, 100% more than expected? Especially if you use 'during Covid' as a span of time. Okay- what was that span of time, and what would be the 'normal' number of deaths during it? And how are you separating [deaths from COVID] from [deaths from COVID policy]?
Without such a baseline, of distinction between the consequences of bad policy and a bad disease, the main reason to defer to someone's statistic is trust. But trust is precisely what is lost when you conflate [with] and [from].
Is it a 'mistake', if it's designed to obfuscate and mislead?
That the same bad actors then use their obfuscation for
I have difficulty seeing these as 'mistakes'.
Wasn't their a rhyming obfuscation with the vaccinated? You did not count as vaccinated and dead unless you died > 2 weeks after your vaccination?
Sure. The phrase 'it was worse than a crime; it was a mistake' comes to mind.
I am all on board that acts and/or policies can both be morally wrong and mistakes in the sense that they do not achieve the ends they were taken to achieve.
Going by Fauci's public statements for why he changed various positions over the course of the pandemic to 'nudge' people into 'better' options, I am fully prepared to believe he was both a bad actor and that he believed doing so would provide a net good on the pandemic outcome.
I think he was generally incompetent in that regards, as I do most people who believe national policy-level lies to be 'white lies' with no bearing on later credibility. I even say this as someone who has a far greater degree of acceptance of state secrets and such than others- part of public credibility is that you need a public's buy in to recognize that you might not share all information, but that what you do share needs to be fundamentally honest/accurate. Failures to maintain this are what lose the trust of those willing to extend tolerance to withholding 'true' information. Fauci's (and other's) technocratic approach to professional credibility is part of why I find him incompetent- he behaved as if the legitimacy and public trust derived from his position, rather than was bestowed by the public he tried to obfuscate and mislead.
People- individually and collectively- have some tolerance for O&M. But it is narrowed, and subject to revocation if abused.
The execution of the Duc d’Enghien was used to further the proximate goal of deterring royalist opposition and consolidating Napoleon’s power, much like COVID data obfuscation was used to justify policies by amplifying risk-severity. Both achieved short-term goals—suppressing dissent or driving compliance.
Both are 'mistakes' that appear to have met their indended near-term goals? Nearly all current year politics eschews the long term.
While you quote an enduring witicism I have difficulty finding an error or fault resulting from defective judgment, deficient knowledge, or carelessness, a misconception or misunderstanding, in either. Traditional markers of mistakes.
That trust in institutions may now be diminished, is only a result of the 'mistake' if the trust had been warrented or well-placed before. The 'mistake' is that the public trusted them to begin with.
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