Enough about the Stanford study. Now as to your analysis. I do not know if this is your original extrapolation or you read it elsewhere but it is so wrong.
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As of this morning, 4/20, the CDC count is 760,000 people have, at some point, tested positive. If the count is off 50 fold then the true positive count is at least 38 million. If off 85 fold then 64.6 million. Why is this important? Two reasons, first it means we may be approaching "herd" immunity without which we'll never get off this merry go round. Second, it means the true death percentage from positive cases may very well be .1% to .2% and not 5, 8 10, or what ever number you see in the media.
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You cannot use the national numbers the way you did. And the Stanford study which you are claiming supports your contention, refutes you directly. If the highest estimate of COVID in the study is accurate being 85 times the figures reported, that only applies to a community with the population and incidence reported that is similar to Santa Clara. So use their top number of 85 times, that percentage in Santa Clara is 4.16 % of the population. Stop, read it again.
If the study is perfect, the highest calculated number of people who are immune to COVID in Santa Clara is 4.16% of the population. If you want to use a multiple for the USA that is the one to focus on. 4.16 times 330 million = 14 million. And 96% of the US is not immune if only 4.16% are immune. Nationally today 750,000 positives are reported, out of 330,000,000. That is a rate of 0.23 % If the real rate is 85 times you get 19.2% of Americans have been infected. This still is nowhere near your figure and it completely ignores the huge fraction that is represented by the NYC metro epidemic. If you apply the 85 times figure to hard hit Westchester county NY, population 1 million, known cases 24,000, times 85 = 200,000 which is still only 20% of the people, nowhere near herd immunity. Apply it to Sumter FL, cases 147 * 85 = 12,500, less than 10% of our population. And all of these are using Stanford's highest numbers.