This is not going to work right: CDC would like to test “virtually everyone”

The false positives will overwhelm the true positives – how will they detect this?

Testing has so far been used in the United States mostly to diagnose people who are sick or have been exposed to someone with a confirmed Covid-19 case. Screening would test virtually everyone in a given community, looking for potentially infectious people.

Source: CDC is developing new coronavirus testing guidance for screening at schools, businesses

Here’s the problem.

  • We test everyone.
  • The actual prevalence of the disease in the community is 1 in 500 people (as an example).
  • Our screening test is 99% accurate (in reality, the full test process may have a much higher error rate).
  • We test 500 people and find 1 person who actually has Covid-19, plus we find 1% of the 500 or 5 people who are tagged as false positives.
  • We’ve now found six people testing positive but only 1 of the six actually has the disease; the other five are false positives.
  • Public health authorities tell us that six people tested positive and “new coronavirus cases” go up by six.
  • The community, however, has a population of  50,000 people.
  • Our testing “virtually everyone” finds 100 actual new cases (1/500 x 50,000) and 500 false positives (5 for every 500 or 10 for every 1,000, times 50 or 500).
  • Public health tells us there are 600 new cases (100 actual + 500 false positives).
  • 500 people are placed in two week quarantines unnecessarily.
  • Because we are testing everyone and because of this problem, we can never “flatten the epicurve” – we will always have a large number of false positives when we test everyone while the prevalence of the disease is low. Even a high accuracy test – or high specificity – still results in this problem. No test – including lab and handling – is 100% accurate.

And oh, the actual test they are proposing to use has a false positive rate of 3% – three times worse than the 1% I used above.

What am I missing? This sounds like insanity – unless your goal is purposely maintain high numbers.

Update: Based on data for my county, it appears the prevalence may be 1 in 800. And the actual false positive rate is 3%, not 1%, as in my example, above.  This means if they greatly expand testing, nearly all of the positive results will be false positives in this County. Unless they take measures to address this (such as double testing all positive results, and not using too many cycles in the PCR process), this is another disaster in the making.

To illustrate 3% of 800 is 24 false positives for each actual case they find. In a 50,000 person community, that is 63 actual cases and 1,500 false positives if they test everyone. I asked OHA about this and they have not answered; another person tells me he has asked OHA also and they have not answered.

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