In yesterday’s post, I indicated that I was very disappointed with Dr. Brix’s answers in a TV interview with Bret Baer.
One particular question & answer still has me scratching my head:
What is the key statistic that you track?
Birx’s answer: Test positivity (i.e. ratio of positive test results to total tests). It’s the most sensitive indicator and best early warning.
With all due respect, I think that Dr. Birx is confusing “positivity” with “prevalence”.
I’m way more interested in the latter prevalence: the percentage of the population that is currently infected with the virus.
Prevalence indicates how widespread the virus is at any point in time in a selected locale.
That gives me a sense of how safe it is to leave my house: How many people am I likely to run into who have the virus and may be contagious.
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Determining prevalence requires periodic random sampling of the population.
That’s not what’s being done now.
A representative sample of the local populations is not being tested.
Why is that a problem?
The positivity rate (Birx’s key metric) is a function of who shows up to be tested.
If only people with covid-like symptoms are being tested, then of course, the positivity rate will be high.
If there’s a groundswell of asymptomatic people, the positivity rate will likely be relatively low.
My hunch: The testing “sample” is skewed to people with symptoms.
In a prior post, we reported that “Asymptomatics” are not rushing to get tested and provided some subjective reasons why that might be (e.g. no doctor referral, high hassle factor, privacy concerns).
So, positivity is, at best, a very crude measure of prevalence.
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To that point, keep in mind…
The Homa Files 