Christof Kuhbandner,  professor of psychology at the University of Regensburg, writes on the illusion of drastically increasing numbers of the corona-infected. In Germany, he writes, the numbers are rising but the disease was at its peak in March. (In related news, a German laboratory claims the tests trigger false positives for other corona viruses.)

Kuhbandner writes:

This can be illustrated by a simple everyday example: Let us assume that ten eggs are hidden in a garden every day (the true number of new infections). On the first day, the children are only allowed to search for one minute and they find one egg, on the second day two minutes and they find two eggs, and on the third day they are allowed to search four minutes and they find four eggs (increasing the number of tests over the time). The children could now get the misleading impression that they are exponentially more eggs (new infections) hidden in the garden every day because they find exponentially more eggs every day. But of course this is a problematic interpretation, because in reality there were always the same number of eggs (new infections) hidden in the garden.

So if there is a high number of unreported eggs (new infections) that are hidden but not found due to the small number of search attempts, you will automatically find more and more eggs (new infections) when increasing the number of tests, but nothing about the true number of eggs per day hidden eggs (new infections) testifies. You can make one interesting point clear from this example: What would actually happen if more eggs (new infections) were actually hidden in the garden every day? Then you would have to find more eggs (new infections) than is caused by increasing the number of tests. For example, if ten eggs were hidden on the first day, 20 eggs on the second day, and 40 eggs on the third day, you would find not just two but four eggs on the second day, and not just four on the third day, but 16 eggs. If you double the number of tests, you will always find more than twice as many eggs.

There is now a relatively simple statistical method to determine the true course of new infections: You simply have to divide the number of new infections found with a certain number of tests by the number of tests. This can be illustrated by the example of eggs: The children could simply divide the number of eggs (new infections) found each day by the number of search minutes (number of tests). If the number of hidden eggs (new infections) remained the same, the value 1 would be obtained for all three days. If the number of hidden eggs (new infections) doubled every day, the values ​​1, 2 and 4 would be obtained. This would then reflect the true course of the increase relatively accurately. In other words, this method is used to estimate what would have happened.

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