The big news on the virus today is that the models are now projecting a higher death toll than they were a week ago. The rise is not very big, but it's the first move towards a higher number in any model updates. Still, the models are nonsensical, truly nonsensical.
The models predict new infections, hospitalizations and deaths. But here's the problem: we know that the number of cases is drastically undercounted. There are huge numbers of asymptomatic cases across the country as well as large numbers of people with very mild symptoms who don't get tested. What good is predicting new cases when we know that all of those predictions aren't even close to being correct. On top of that, as the number of daily tests continue to rise, the number of people discovered with symptoms will include more and more asymptomatic or lightly symptomatic people. Since the models say more cases mean more deaths, better testing results ultimately in higher death projections.
Then there's the question of why the models don't consider the huge numbers who test positive for antibody tests that indicate a prior infection by the virus. The "experts" tell us that they can't use the antibody tests because they aren't accurate enough. Huh? That's ridiculous. For example, antibody testing in New York City found 25% showing the antibodies that indicate prior infection. If we assume that one-third of those tests are wrong, the, at the very least, a minimum of 17% of New Yorkers have been infected. Since the testing rates previously indicated only between 1 and 2% of the city residents had the virus, continuing to rely on those outdated results means that the models are hopelessly wrong.
Even more bizarre is the fact that some models now are predicting on what day individual states can reopen. Think about that. We know the models are wrong because they don't consider the antibody test results. Projecting total national deaths in this manner is not going to get us a meaningful result. The data is not good enough or accurate enough to predict total deaths. But now the modeling gurus want to tell us on exactly which day each state should reopen? Are they kidding. Even in the best of times, models of this sort couldn't tell us the date in the future for reopening. Given the improper construction and data used by the modelers, these models might as well have been done on a Ouija Board.
Hopefully, these models will be ignored by policy makers. To give them credence is to accept obviously incorrect projections based upon corrupt data. My guess is that the media will love these models.
The models predict new infections, hospitalizations and deaths. But here's the problem: we know that the number of cases is drastically undercounted. There are huge numbers of asymptomatic cases across the country as well as large numbers of people with very mild symptoms who don't get tested. What good is predicting new cases when we know that all of those predictions aren't even close to being correct. On top of that, as the number of daily tests continue to rise, the number of people discovered with symptoms will include more and more asymptomatic or lightly symptomatic people. Since the models say more cases mean more deaths, better testing results ultimately in higher death projections.
Then there's the question of why the models don't consider the huge numbers who test positive for antibody tests that indicate a prior infection by the virus. The "experts" tell us that they can't use the antibody tests because they aren't accurate enough. Huh? That's ridiculous. For example, antibody testing in New York City found 25% showing the antibodies that indicate prior infection. If we assume that one-third of those tests are wrong, the, at the very least, a minimum of 17% of New Yorkers have been infected. Since the testing rates previously indicated only between 1 and 2% of the city residents had the virus, continuing to rely on those outdated results means that the models are hopelessly wrong.
Even more bizarre is the fact that some models now are predicting on what day individual states can reopen. Think about that. We know the models are wrong because they don't consider the antibody test results. Projecting total national deaths in this manner is not going to get us a meaningful result. The data is not good enough or accurate enough to predict total deaths. But now the modeling gurus want to tell us on exactly which day each state should reopen? Are they kidding. Even in the best of times, models of this sort couldn't tell us the date in the future for reopening. Given the improper construction and data used by the modelers, these models might as well have been done on a Ouija Board.
Hopefully, these models will be ignored by policy makers. To give them credence is to accept obviously incorrect projections based upon corrupt data. My guess is that the media will love these models.
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