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Over the span of 3 years. To put this in perspective a typical flu year claims ~40K people each year. So Covid over this time span killed about 10X as many people as a typical flu year.

If you told people "hey, this year the flu is going to be very bad, probably killing 10 times as many people" would the average response be to close schools and many businesses for over a year? Or would the response be to limit lockdowns to vulnerable populations, rather than blanket lockdowns on most of society?




If hospitals said "we're about to run out of room and stop treating everyone" then I would go with whatever prevents that scenario.

edit: COVID placed a 20x burden on hospitals versus the flu even with lockdowns. That's without counting the increased difficulty of treating a novel disease, and increased time in hospitals for covid vs flu.


The notion that hospital capacity had a significant effect on the fatality rate is not so strong. Even early into the pandemic, hospitals stopped putting people on ventilators since it didn't improve health outcomes. So "flattening the curve" just meant extending lockdowns and probably not saving any lives.


So what you are saying is that it was known how many people will be killed by covid-19 before any measures have been put in to affect and that those measures had no influence on the number of those who died? If not, what is the point of your post?


Before March, sure no we did not. But by mid-late 2020, yes we did. But lockdowns continued well into 2021. We had studies to determine the infection fatality rates in mid-late 2020: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7947934/

Ionnadis was slammed for claiming such a low IFR of 0.27%. But later studies have since reaffirmed his estimates: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613797/ Even when restricting the analysis to the period before vaccinations, the IFR was between 0.3% and 0.4%. Ionnadis was way closer to the mark than the claims of 1.0 or 1.5% IFR that were common at the time.




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