The key hypothesis of asymptomatic spread is finally tested
by Bruce O’Hara
September 26, 2023
Epidemiologists typically track two key mortality statistics. The first is the case fatality rate, which is the number of deaths caused by a disease divided by the number of known cases. Early in the COVID pandemic, the WHO and most of the mainstream media in the West trumpeted a horrendous case fatality rate for COVID of 3.4 percent.
Competent epidemiologists know that case fatality rates are notorious for overstating the actual death rate, for the simple reason that they typically include only those cases of disease severe enough to land a person in hospital. To determine the true death rate of a disease, it is necessary to do widespread community testing to add in an accurate measure of all the mild and asymptomatic cases, giving an immensely more reliable statistic known as the infection fatality rate.
Knowing they lacked this crucial data about the actual prevalence of COVID, the US Center for Disease Control should have immediately issued contracts for widespread community COVID testing programs. They did not – which was an inexcusable oversight.
There was one American epidemiologist who did do that key research – independently, and on a shoe-string budget. In April of 2020, Dr. Jay Bhattacharya’s research found that the actual number COVID infections in Santa Clara County, California, was an order of magnitude higher than what official case numbers showed. An astounding 2.81% of those tested already had COVID antibodies in their blood.
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