Maybe they should also look up the median age for death from cancer. I believe it is around 75. Does anybody think that we make too big a deal about cancer?
The argument there is that we don't shut down the economy to prevent people from getting cancer. Though economics do play a role there, too. A major reason the economy grew so much under Trump is that he loosened many environmental and safety regulations. This has consequences--many people get sick and die as a result of this. When all is said and done, it's possible that more people will die from changes in these regulations than from COVID.
Wherever politics is involved, there is hypocrisy and irony. When Obamacase was being developed, conservatives accused progressives of advocating death panels--letting older people die to save medical costs. It is a fact that something like 50-60%--i don't know the exact figures--of medical care involve people in their last years of life. But now the argument is being flipped around, as it tends to be conservatives arguing that we should let older people die for economic reasons. The reversal, of course, is because in one case the economics involve a social cost, while in the other, it's more of an individual cost.
At least this surge has stuck a fork in some theories of the spread of the virus, such as that by Michael Levitt. Levitt, a Nobel Prize winner in Chemistry, but not an epidemiologist, claimed that by examining the early rise in cases, he could see that even from the beginning, numbers did not rise exponentially. He had some obscure explanation that this was due to infected people quickly running out of others they could infect. He also said that spread of the virus would stop by the time one in a thousand people had died.
That latter prediction is definitely wrong. Eight states in the U.S., numerous smaller communities, and two countries (likely to be joined by the U.S. and half a dozen or so more nations by the end of the year), have exceeded overall mortality rates of one in a thousand. The first hypothesis also fails when applied to the current surge.
Levitt supported his theory originally by comparing the % increase in cases each day. He found that while cases increased, the % increase was less each day, a sign that there was not exponential spread. This led to his conclusion--welcomed by people opposed to lockdowns and other social restrictions--that the effects of the virus would die down, even if we did pretty much nothing (though he himself did not advocate that).
You can’t compare cases day by day for the U.S., at least not using the Worldometer, because reporting is less on weekends; numbers fall off at that time. But you can compare the weekly numbers, beginning and ending on the same day. When you do that, and look at the weekly cases since the beginning of October, you get this:
| Cases | % increase | | |
| Oct 1-7 | 320,879 | | | |
| Oct 8-14 | 374,059 | 16.6 | | |
| Oct 15-21 | 436,564 | 16.7 | | |
| Oct 22-28 | 530,869 | 21.6 | | |
| Oct 29-Nov 4 | 652,370 | 22.9 | | |
| Nov 5-11 | 912,367 | 39.9 | | |
| Nov 12-18 | 1,159,422 | 27.1 | | |
| Nov 19-25* | 1,459,159 | 25.9 | | |
- Nov. 25 data not in yet, so I took the 6 day total and multiplied by 7/6 (the estimate is a little low, as the last day will be higher than the average of the preceding six)
These values plot out as a good exponential curve, with r2=.9864. I think the reason we’re now seeing classic exponential spread is because people are maxxing out. They are doing everything they can, or are willing to, do to slow the spread. Whereas earlier in the year, people were changing their behavior during the first surge, resulting in slowing down of the spread. Thus a lot of people may wear masks and keep their distance in public, but continue to gather privately, without masks. There may be other reasons, but what I see from the data is an R0, or average number of other people infected by someone who is infected, that is not only above the magic line of 1.0, but is fairly constant over time.
Notice, too, that the spread shows no sign of peaking or even slowing down. It will eventually, but we’re not there yet. During this entire period, the number of cases on any particular day of the week has always been higher than the number of cases on the same day the week before.
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