Covid: Cause v correlation, prevention v protection

February 8, 2022. The true Covid pandemic has been the viral action of tyrannical politicians, bureaucrats, pundits and mainstream media, all saying one thing and then doing the other, setting mandates for the public while ignoring those mandates. The "story" they tell is a jumble of, "trust us, we represent science," while all the time placing their opinions and self-interests above science. "Experts" continue to confuse us with massive death counts, claims of single causes, and assertions about vaccines. Clearly, the death counts are not that clear, nor are the causes or the explanations for the causes of Covid deaths, and nor are the claims as to vaccine efficacy. Even a casual review of the complexity of "Covid" death counts show overwhelming evidence of the idea that the vast majority of deaths are "with" Covid rather than due to Covid alone. Having changed the definition of a vaccine, from prevention to protection, the CDC provided ammunition for progressive commentators to claim that the vaccine "stopped" the spread of Covid while also preventing deaths among any of those vaccinated.

We have a traditional problem of consulted 'experts' misinterpreting, misrepresenting, or over interpreting cherry-picked, often non-representative data to confirm their biases and self-interests with conclusions unwarranted or disproven by a full analysis of the data, usually because there has not been full analyses of the data. Most often, and expert of progressive politician or pundit will see a mathematical mean, or a bar graphs, or a trend line and draw speculative inferential, causal conclusions and cloaking those conclusions under an aura of expertise that buttresses their conclusions. For instance, they'll express shock or alarm at "overcrowded" hospitals or ICU's, while rarely looking as to why people are in the hospital, or acknowledging the overcrowding is due to staff having been fired for not following useless mandates.

Interestingly, those doing the most complicated mathematical modeling often fail to see that their assumptions are clouded by these false inferences, as the modelers build their biases, described as assumptions, into their models. Even then, their projections carry more weight than the actual results, often showing th models or the modelers to be fraudulent, incompetent, or simply biased towards a pre-determined conclusion. "Climate change" modelers have perfected this way of forecasting, now adopted by the Covid modelers.

Here’s what I have in mind. First, separate all those (American ‘residents’) who died with two or more co-morbidities from those who died with one or none. Do the following analysis on both of these groups, separately: Divide those deaths between those with no evidence of Covid present at death and those with clear evidence (not assumption by symptoms) of Covid in their system at death. Then divide again by vaccination status. To wit, how often do people with two or more pre-existing co-morbidities die in the absence of Covid? Do only the vaccinated die with excessive co-morbidities and if they do, why discount Covid as a possible cause of death? How often were people transferred to the hospital or to the ICU to get them out of their nursing home?

It is quite possible that the ‘experts’ assume or infer too much from the data when claiming Covid as the cause of death when there are multiple co-morbidities that alone might have caused or explained death. And I think that the same can be said inferring that those vaccines prevent deaths simply because there is a lower death rate among the vaccinated, especially when many unvaccinated deaths occurred before there was a vaccine. Even the CDC has changed its definition of a ‘vaccine’ from a treatment that prevents infection to one that sees the vaccine as a protection, not a prevention.

There are too many claims of cause from correlation and too much discounting of other factors, including natural immunity and re-purposed drugs. Bottom line is that when CDC gets to set the definition of a vaccine and the cause of death in such a subjective and non-traditional fashion, it is difficult to trust the data. It reminds me of the military recording their count of Viet Cong deaths as a measure of the effectiveness of the military operation, as today General Fauci uses the ‘Covid’ death count as a measure of the importance of his office. At least the Hanke report has syrfaced some broader issues.