The Efficacy Illusions, Part II: Engineering Interpretations of Data

The System is More Than the Sum of the Parts

"It is a capital mistake to theorize before one has data." -Sherlock Holmes (Sir Arthur Conan Doyle)

The FDA has released a document describing data from the recent trial testing Pfizer/Biontech's experimental mRNA biologic medical product presumably aimed at COVID-19.

Given that these injections do not confer sterile immunity, and seem to be disrupting general T cell immunity, it seems awfully strange that we are even testing these products on children given that COVID-19 has never been a particularly serious problem among children.

The adverse events report seems disturbing on its own. Given what we know about the mechanisms for heart damage---particularly in young people---

That's a whole lot of fatigue. And headaches and other problems often associated with myocarditis and similar heart problems. Let us pray everyone's heart is okay after this trial.

Source: The Mayo Clinic

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The Second Magic Trick: Excluding Inconvenient Data

Has anyone else ever wondered how conveniently and crisply the efficacy rates of the two mRNA vaccines matched so well? We see dose dependence in associated adverse events, but not in disease prevention? Why would we even keep both vaccines on the market, then, when we could just use the one with lower AE rates? Something seems fishy in the logic...

There is an important and still unexplained statistic that jumps out of the data from the new trial on children ages 5-11: "other important protocol deviations":

While the data exclusions we can understand by description all seem balanced within statistical norms, the lopsidedness of the exclusions due to important protocol deviations looks to be associated (causal?) to the testing itself! This is not the first time we've seen this! It happened in the original Pfizer Trial Report, also:

In the original trial, the numeracy of these exclusions overwhelmed the effect size of the vaccine. That concerned me back then, but I had not yet thought through the naming illusion and the existence of Type II COVID-19.

We can see clearly from the newly released study data for recipients ages 5-11 that the exclusions overwhelm the effect size once again!

To summarize: if vaccine injuries are the reasons for these unexplained exclusions, then absolute efficacy numbers are overwhelmed by vaccine injuries, and the experimental biologic inoculation products are dangerous. However, if any of those injuries simply are Type II COVID-19, then efficacy is being incorrectly measured from the get go. And if all of the excess exclusions describe cases of Type II COVID-19, then the vaccines have negative efficacy rates according to multiple trial reports. 

I strongly suspect that we are looking at intentional manipulation of definitions. And it is disconcerting that I and others have asked for that information from multiple sources, including the FDA, and they simply don't seem interested enough to even answer those emails.

It is telling that in numerous places, the vaccine manufacturers specifically state that their products are designed or approved to prevent "COVID-19 caused by SARS-CoV-2" and not other causes.

I don't make many requests of RTE readers, but I noted the [very likely] existence of Type II COVID-19 months ago at this point. Ignoring it allows all of the public health institutions, not to mention the pharmaceutical industry, plausible deniability in ignoring the many problems associated with the vaccines. Noise needs to be made. Start referencing Type II COVID-19 publicly and often. Force the discussion. It's time.