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What can be learned from the unreliability of COVID-19 testing?


The writer recently had a discussion on Twitter about an article by a Dr. Sherri Tenpenny. She concludes in the article that COVID-19 tests would not testify because they are not 100% reliable. Her reasoning is that the tests would give both false positive and false negative results. She also claims in the article that “The detection of viral RNA by RT-PCR does not necessarily equate with an infectious virus”. She then calls for resistance to COVID-19 testing, protective masks and vaccination. The whole thing culminates in the statement: “I understand that an asymptomatic carrier is a normal (someone without any noticeable symptoms), healthy person, and I will not take on board the fear that I might “catch something” from a normal, healthy person”. That is, the author doubts that a virus carrier without symptoms can infect others.

Photo by visuals on Unsplash

While the latter statement is clearly dangerous nonsense, as is the assertion in the article that Sars-CoV-2 mutates too quickly, so that neither tests nor vaccination could keep up, the text does, however, contain correct information, especially on the reliability of the tests (at least as far as we can judge). In the following, we will discuss why false conclusions are so dangerous. It is then half-knowledge with a reputable sender that is perceived as correct.

Ultimately, the discussion on the article revolved around the question of whether, based on the correct information, one can assume that the conclusions are also correct. The answer to this question is clearly no.

Because describing information correctly and drawing conclusions from it are not only two different activities, they also require different knowledge.

Presenting information correctly requires a minimum of expertise. Drawing conclusions from it requires methodological knowledge: i.e. the knowledge of how to interpret information correctly in the scientific sense.

For a layperson, it may be obvious that if someone writes that a COVID 19 test is not 100% reliable, one cannot rely on the tests and should stop testing altogether. But such a test is nothing more than a measurement and every scientist will confirm that no measurement has ever been 100% reliable. There are always measurement inaccuracies. If you repeat measurements, they never give exactly the same result. Scientists therefore learn in their training to deal with such measurement errors and to take them into account when interpreting the data in order not to draw wrong conclusions. They learn which statements can still be made under the given accuracy and which not.

Correct is: yes, the tests are not 100% reliable. If the goal were to know exactly who is infected with SARS-CoV-2, the tests would fail. But that is not the point. The point is to reduce the probability of infection, not to rule it out completely and 100% reliably. Because any reduction in the probability of infection helps in the fight against the pandemic and, because of the large number of tests, actually leads to fewer infections. Not measuring it at all would mean letting the virus run free.

The goal of a measurement must therefore not be disregarded when interpreting the results of a measurement, but is quite crucial. Dr. Tenpenny is making a cardinal mistake here: she bases her measurements on another goal that has nothing to do with the actual goal and evaluates her new goal. In the vernacular, one says: compare apples with pears.

This can also be seen in the criticism “The detection of viral RNA by RT-PCR does not necessarily equate with an infectious virus”. – For here, too, it is based on a goal – or a purpose – that does not even exist. It is not necessary to know whether a positively tested person is really infectious or not. To be on the safe side, you simply assume it, which is certainly safer than assuming that someone without symptoms is certainly not infectious.

It is also not necessary to know whether a positive test person is infectious or not in order to interrupt a possible chain of infection. Sending him to quarantine is a safe bet. This may seem unfair for someone who is only positive but not infectious, but how much more unfair would it be to let him walk around freely, for those who are infected by such asymptomatic virus carriers and die or have to deal with the consequences for the rest of their lives?

So, if you follow the logic of Dr. Sherri Tenpenny, you would have to shut down all scientific work and you could do nothing about the pandemic.
So you see: Many people, even those with doctorates, make the mistake of turning a measurement inaccuracy into a complete uselessness of measurement.

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