I watched this explanation from a couple of Dr's in California and it has made me look at things differently...
Bottomline, is they conclude the time is right for targeted reopening with testing based on the data they have analyzed.
This is nonsense masquerading as science.
But, don't accept my opinion.
Read what an expert has to say.
"Statistician Carl took these doctors on. Sadly, they are talking pure junk."
Note: Carl T. Bergstrom is a professor of biology at the University of Wisconsin.
Twitter Feed Response by Carl T. Bergstrom
Unfortunately the
misleading claims of those two doctors in Bakersfield keep making the rounds, so I want to very briefly address the problem with what they are saying. I won't get into their possible motives, past political activity, etc.
What they did was simple: they looked at the fraction of patients who tested positive for #COVID19 at the clinics they own. They found 340 out of 5213 tests were positive, about 6.6%. Then they assume the same fraction of the whole population are infected.
From there, they scale up to the state level and claim 12% incidence statewide. The news story says it is using the same calculation, but it can't be—how did they get from 6.6% to 12%? Perhaps they estimating infected *ever* versus infected *currently*. It's not clear.
Using that 12% infected figure, and a known 1400 deaths in California, they assume 1400 out of 4.7 million have died. That gives them an infection fatality rate of 0.03%. That is, they think that if 10,000 are infected, 3 will die on average.
The problem with this approach is that during a pandemic, the people who come into an urgent care clinic are not a random sample of the population. A large fraction of them are coming in precisely because they suspect that they have the disease. This generates sampling bias.
Estimating that fraction infected from patients at an urgent care facility is a bit like estimating the average height of Americans from the players on an NBA court. It's not a random sample, and it gives a highly biased estimate.
Moreover the estimate does not pass even a basic plausibility check. In New York City, 12,067 people are known to have died from the virus, out of a population of 8.4 million. This is a rate of 0.14% of all people. Not just infected people. All people.
That gives us a lower bound on the death rate in New York. Not an estimate, a lower bound. The death rate for infected people is obviously higher than 0.14%, because not everyone in New York has been infected.
And yet that 0.14% lower bound is nearly *five times as high* as the 0.03% that the Bakerfield duo are claiming. They've used absurd methodology to arrive at an implausible number. If the pandemic were not so severely politicized, this would be a non-issue from the start."