I assume it has been claimed on FB that this is proof that the flu didn't disappear but just got misdiagnosed as Covid, and/or that the Covid tests results couldn't be trusted at all, hence they have been withdrawn.
If that’s true, then, how can we be sure that flu hasn’t been misdiagnosed?
What percentage of Covid cases were classified using PCR tests?
Because I haven't seen anything on Facebook, or self-censoring HN for that matter, validating those claims. So they must be but only false but really out-there wacky conspiracy theories.
The original could not detect, so therefore differentiation is a moot point.
Also, the test for flu was a separate test. So it would have had no effect on the lower flu incidence assuming we didn't test for flu at a lesser rate.
Do we have any numbers on this? I would imagine a lot of people who went to the doctor or whoever complaining of flu like symptoms would have been tested for covid.
In 2020-21 there were 1.11M flu tests over 33 weeks.
Results: Essentially a 0% positive test rate vs a peak of over 25%. A peak of about 125 cases vs 20,000 cases.
1: https://stacks.cdc.gov/view/cdc/54973 2: https://www.cdc.gov/flu/weekly/weeklyarchives2020-2021/data/...
> Isn’t implying that the test can’t tell the difference between flu and covid?
they are strongly convinced that this is the case, quoting papers or research showing that in some rare cases with some methods you could have tests which could sometimes confuse Covid with other Corona Viruses (not flu, completely ignoring that this might not apply to the tests they are speaking about or that the probabilities are negligible.)
I had to realize that the majority of people (which haven't studied something where they had to learn it) do not understand stochastic at all, but believe they have some basic understanding of probabilities (which they don't have).
Furthermore it's not uncommon for people to reject truth which do not fit into their world view.
Not to long ago I realized that a relative of mine does not understand the difference between false positives and false negatives and that they are not equally likely. They knew the (fast, non PCR) test can be wrong and as such believed it can be equally wrong in all directions including false positives. So because it was confirmed that the test have many false negative they believed that they also must have many false positives and as such the increase in cases must be because of this false positives...
I tried to reach out to them and explain them that false positives and false negatives are not the same and just because something can likely fail in one way it doesn't mean it will also fail likely in another way. But I completely failed to reach them, they insisted on their opinion being correct and went very fast into a defensive mode where it's impossible to reach them no matter what how reasonable and convincing your arguments are.