The present disconnect between the science of Covid-19 and the status quo's complacency is truly crazy-making, as we face a binary situation: either the science is correct and all the complacent are wrong, or the science is false and all the complacent are correct that the virus is no big deal and nothing to fret about. [...] So let's look at some data and consider what science can tell us about the potential consequences of the Covid-19 virus spreading as widely as conventional flu viruses.
The fallacy made by the complacent is that the number of cases will remain small (in the dozens or hundreds) and so the number of deaths will also remain small.
Since the evidence suggests the Covid-19 virus is more contagious than conventional flu viruses, a reasonable assumption is that it will eventually infect more people than a conventional flu, which according to the CDC infects up to 45 million Americans annually. [...] Given the scientific evidence that Covid-19 is highly contagious, let's do a Pareto Distribution (80/20 rule) projection and estimate that 20% of the the U.S. population gets Covid-19. That's 66 million people, roughly 50% higher than the 45 million who catch a flu virus in a "bad flu" season.
Data suggests between 2% and 3.4% of all Covid-19 cases end in death, but the deaths are concentrated in the 20% of cases that become severe, and in the vulnerable populations within the 20% severe cases that require hospitalization.
Using the lower CFR (case-fatality rate) rate, 2% of 66 million is 1.3 million, so if Covid-19 infects only 20% of the U.S. populace, current data suggests 1.3 million people will die.
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