Despite widespread anecdotal and research evidence of severe disease and death closely associated with COVID-19 injections, their link to COVID mortality has been dismissed as rare and coincidental, because comprehensive statistical evidence has not been obvious in official mortality data.
A recent paper [1] solves this puzzle by identifying a systemic data flaw in the reporting convention which obscures the immediate fatal impact of COVID-19 injections, where substantial “vaccine” deaths have been wrongly attributed to the “unvaccinated”.
Recently, Deborah Birx, coordinator of the White House Coronavirus Task Force (WHCTF), who set the strategies for early US COVID responses copied by much of the world, has publicly lamented the poor quality of US COVID data and said [2] “It was a pandemic driven by assumptions and perceptions, rather than data and science”.
On health agencies, she also said: “Data for publication, not data for implementation change.” That is, COVID data are collected, not to inform, guide and implement policy changes, but to manage public perception, which could mean that data may be manipulated to mislead the public, as will be shown below.
The official claim that “policy follows the science” is the opposite to reality: “science follows the policy” i.e., policy first then supported later by fake science and manipulated data. Data analysts may not realize that they could be aiding and abetting misinformation by publishing misleading statistics of manipulated data. We provide evidence for the dramatic consequences of the flaw in COVID data reporting [3] specified by the US CDC.
The CDC defines “vaccination status” with a 14-day lag from the last COVID injection, with the rationale that it takes at least 14 days for the injection to take effect. For example, a “breakthrough case” of a person “vaccinated with a primary series” is specified by:
“Vaccinated case with a primary series: SARS-CoV-2 RNA or antigen detected in a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine.”
Such data collected are not the raw data, but manipulated data because the adjusted data may distort interpretation of the results. The adjusted data is a data flaw in plain sight, because the adoption of a time-lag of 14 days, while widely accepted, has not been justified by scientific research or by debate on its potential to mislead.
Scientifically, the concept of “vaccination status” is quite unnecessary in the raw data; all that is needed is simply to record the “Date of injection” [4]. It has been impossible to determine scientifically when the injections actually take effect, when it is already pre-judged by the “vaccination status” of the collected data.
The important distinction between raw data and manipulated data in this case comes from the fact that adverse events and deaths have occurred frequently soon after COVID injections, much less than 14 days, as the CDC’s Vaccine Adverse Event Reporting System (VAERS) database reported by…
Read full story here: Data flaw hiding lethality of COVID-19 injections in plain sight | Principia Scientific Intl.