All of it, The New York Times assumes.
Americans have been debating
the effectiveness of COVID-19 lockdowns for months now. To what extent
did broad business closure and stay-at-home orders—as opposed to
narrower interventions and voluntary precautions—reduce virus
transmission, thereby avoiding hospital crises, buying time to develop
testing and tracing capacity, and preventing deaths that otherwise would
have occurred? Conversely, to what extent can loosening those
restrictions be expected to increase transmission, leading to more
infections and deaths?
According to The New York Times, that debate has now been settled. "Data show," the Times reports,
that "lockdown delays cost at least 36,000 lives." Researchers at
Columbia University "found" that "even small differences in timing would
have prevented the worst exponential growth," the Times says.
"If
the United States had begun imposing social distancing measures one
week earlier than it did in March, about 36,000 fewer people would have
died in the coronavirus outbreak," the paper reports. "And if the
country had begun locking down cities and limiting social contact on
March 1, two weeks earlier than most people started staying home, the
vast majority of the nation's deaths—about 83 percent—would have been
avoided, the researchers estimated." The "cost of waiting to take
action," the Times concludes, was "enormous."...........To Read More....
My Take - Once again. Computer models aren't science. They're a component of science, but real science is based on real observation. This is especially true when the algorithms that determine the outcomes aren't made public. Transparency in science is paramount, otherwise it’s nothing more than a faith based initiative, and the conclusions these computer models have poured out over the years have not only been wrong – they have been startlingly wrong, being off to the tune of millions. Especially so since real observations are showing a different story, as the article points out.
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