They’re talking about false positives.
If a test had a 50% false positive rate, I’d consider it worthless, and I think most others would to. For example, you could then test a population where absolutely no one had, or ever had, the virus and conclude that 50% had been infected and you were close to herd immunity.
How can the CDC say this?
Manufacturers have been claiming 95 to 99% accuracy. I’d say its extremely important to have some accuracy here.
How do you know that the concept of “herd immunity” exists for this virus?
It is important to for the WHO and CDC to squash hopes of those who test positive for antibodies. If this test is valid, then you don’t need a vaccine. Trillions at stake here for the ghouls imprisoning the serfs until the vaccine (heavenly choir singing) that everyone must take and must be certified after elections.
Is the CDC playing politics again?
I think CDC is saying that the rate of false positives can be high relative to the number of positives in a large sample of tests. For example, if 1% of a population has the virus, but the test has a false positive rate of 1%, then 2% of the people tested will get a positive result - those actually positive and the false positives. In this case 50% of the positives are false.
But if 20% of the population actually has the virus, an additional 1% false positive is only 1/21 of the total number of positives (less than 5% of the positives are false positives)
What they are saying is that in populations with low infection rates a large percentage of positive tests will be false positives.
Of course that is true. If a population has a true infection rate of 0%, then the false positives will constitute 100% of the reported positives.
If a population has a 1% true infection rate and the test has a 1% false positive, then the testing will report about 2% positives and the false positives will constitute about 1/2 of the reported positives.
If the accuracy rate is 95-99% and the actual incidence rate is 1-5%, it’s going to falsely identify cases at about the same rate it “accurately” identifies cases.
it doesn’t mean the test has a 50% false positive rate.
If the test yields a false positive 5% of the time, in a population with 5% actual frequency, then it would mean that half of the folks testing positive wouldn’t actually have the disease. If the actual frequency were 2%, then the false positives would be over 70% of those getting positive results.
The first papers showing high detection rates without false positives were done under specific conditions with fewer than 10 examples.
Even if the tests themselves were perfectly accurate, there are always potential issues with executing the tests which could result in false positives, such as environmental contamination.
In the real world of In Vitro Diagnostic Kits and other text kits, a 50% false positive rate would have a rather difficult time being approved by the FDA.