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After mounting evidence, FDA, CDC now admit that coronavirus tests are faulty

Posted by $ BobCat 3 months ago to News
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The FDA stated that the accuracy of rapid tests depends almost totally on the amount of COVID-19 in the population being tested, stating: “As disease prevalence decreases, the percent of test results that are false positives increase.”
In recent months, both agencies have begun to concede that the testing methods that they’re using may not be as accurate as they would want them to be. They acknowledge that an increasing number of so-called positive test results are actually false positives.
SOURCE URL: https://www.distributednews.com/479269.html


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  • Posted by $ Abaco 3 months ago
    At the early stage of this pandemic I really marveled at how the media would continually grille Trump on "When will we get more tests?" It was an interesting dynamic because:

    1- Testing isn't prevention.
    2- They knew getting enough tests designed, produced and distributed for everybody was impossible and were just using this to zing him - because they seem to hate him.
    3- He'd actually play into their trap by trying to paint a rosy picture on the "issue" on not enough testing - promising the test kits.

    When I see how testing is done - see all those lines of cars where everybody lines up and gets funneled through one stop where a small team of technicians runs the test on the citizens - I can't help but say out loud, "I hope the testers are being very sanitary for each person coming through." This is because it looks more like a COVID spreading exercise to me than a testing program. Looks scary. But, I work in infection control...what the hell do I know?
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  • Posted by $ pixelate 3 months ago
    I have been following this news as well. From the G. Edward Griffin "Need to Know" site, there is more evidence that the C19 tests have little merit:
    Kary Mullis, the Inventor of the PCR Test, Explains Why Its Results Are Meaningless (Summary & Story)
    https://needtoknow.news/2020/12/kary-mullis-the-inventor-of-the-pcr-test-explains-why-its-results-are-meaningless/?utm_source=rss&utm_medium=rss&utm_campaign=kary-mullis-the-inventor-of-the-pcr-test-explains-why-its-results-are-meaningless

    Team of Experts Finds Flaws and Conflicts of Interest in PCR Test for Covid-19 (Summary & Story)
    https://needtoknow.news/2020/12/20252/?utm_source=rss&utm_medium=rss&utm_campaign=20252

    Will there be any negative consequences for the individuals that pushed the panic narrative regarding the increasing number of cases? I suspect that is about as likely as finding a blue-state-governor following their own covid-compliance-mandates.
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  • Posted by $ blarman 3 months ago
    What? The Federal Government has been lying to us about all this? But, but, but... [/sarcasm]

    I stopped listening to these guys the moment they changed the rules to make all COVID-related deaths as if they were actually caused by COVID.
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  • Posted by $ brightwriter 3 months ago
    If you have the algebra, many of us would be interested.

    Sensitivity and specificity of a test do not vary with prevalence. Predictive values do. Definitions follow.

    Sensitivity = true positive / (true positive + false negative). It is the likelihood that a test will identify someone with the disease. The number of people without the disease is not part of the calculation.

    Specificity = true negative / (true negative + false positive). It is the likelihood that the test will identify someone without the disease. The number of people with the disease is not part of the calculation.

    But predictive values DO depend on prevalence!

    Predictive value positive = true positive / (true positive + false positive). It’s the likelihood that a positive test result really means it and is not a false positive. Conversely for false negative, which is almost irrelevant because the prevalence is so low.

    Prevalence = all positive / all positive + all negative.

    With some effort, it’s possible to show that with imperfect specificity (false positives exist) and a low prevalence the predictive value positive is actually very low. Should I upload the whole bunch of equations?
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