Testing. The New York Times has a good reference page on covid stats which it keeps updated.
The FDA has warned about a procedural problem that can inflate numbers. If tests are not administered properly. Corona viruses have been around for a very long time and some which are not from this particular version of the disease may show up on tests. Some critics have claimed that the false positives might be 90%+, but that seems to be based on false information.
The administration’s go-to coronavirus expert, Anthony Fauci, MD, may have known since July 2020 that most Covid-19 “cases” are not what they are said to be. He explains that the US routinely uses a PCR testing standard of 42-45 cycles [whatever that is?], but any positive test above 35 cycles is a false positive. There may be bits of virus material detected, but the patient does not have enough to be sick or contagious. Doesn’t that mean that much of the hoopla is misguided? Dr. Fauci discussed the issue in this interview video. There is more detail in this news article. Read what Harvard has to say about tests.
It is a bit of the worry the many if not all the swabs jammed up our noses are from China and are saturated with ethylene oxide which the EPA classified as a human carcinogen in December 2016. It can also cause genetic damage. We can only hope that unless you have to have lots of tests, the amount of exposure is too low to produce these effects.
Case #’s. The New York Times has a good reference page on covid stats which it keeps updated. It is seldom mentioned but obvious and logical that the greater number of tests are performed, the more cases will be identified and counted. Therefore, elevated case numbers do not necessarily mean that the problem is growing. Here are some factors that make case numbers hard to interpret:
- The counts may be low because millions of people were never tested. E.g., they had mild or no symptoms (that can be up to 80% of infections) or they did not have access to testing. If there indeed have been substantially more cases, that might mean we are closer to “herd immunity” than the numbers would suggest.
- On the other hand, the case numbers may be massively overstated because:
- The testing protocol (see Testing above) creates a high rate of false positive results.
- There was no control at the federal level to account for duplication because a person might have had more than one test done at different sites (e.g. one in a drive thru and one at the hospital).
- Hospitals may mistakenly label any upper respiratory ailment (e.g. flu, pneumonia or Tuberculosis) as “covid-19”. (They have a financial incentive to do that, because hospitals are paid more for treating covid cases.)
- People with symptoms who show up at hospitals and clinics can be labeled as “presumed covid-19”.