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Do Lockdowns Save Many Lives? In Most Places, the Data Say No


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Do quick shutdowns work to fight the spread of Covid-19? Joe Malchow, Yinon Weiss and I wanted to find out. We set out to quantify how many deaths were caused by delayed shutdown orders on a state-by-state basis.

To normalize for an unambiguous comparison of deaths between states at the midpoint of an epidemic, we counted deaths per million population for a fixed 21-day period, measured from when the death rate first hit 1 per million—e.g.,‒three deaths in Iowa or 19 in New York state. A state’s “days to shutdown” was the time after a state crossed the 1 per million threshold until it ordered businesses shut down.

We ran a simple one-variable correlation of deaths per million and days to shutdown, which ranged from minus-10 days (some states shut down before any sign of Covid-19) to 35 days for South Dakota, one of seven states with limited or no shutdown. The correlation coefficient was 5.5%—so low that the engineers I used to employ would have summarized it as “no correlation” and moved on to find the real cause of the problem. (The trendline sloped downward—states that delayed more tended to have lower death rates—but that’s also a meaningless result due to the low correlation coefficient.)

No conclusions can be drawn about the states that sheltered quickly, because their death rates ran the full gamut, from 20 per million in Oregon to 360 in New York. This wide variation means that other variables—like population density or subway use—were more important. Our correlation coefficient for per-capita death rates vs. the population density was 44%. That suggests New York City might have benefited from its shutdown—but blindly copying New York’s policies in places with low Covid-19 death rates, such as my native Wisconsin, doesn’t make sense.

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