Study shows Government data provided to Media related to the vaccinations has mis-categorizations and is inaccurate and unreliable.

British Mathematician & Professor of Risk Management, Norman Fenton, who works with mortality and mortality risk data, walks Del through UK data on the incredible peak of excess deaths that occurred in the U.K. at the same time as the covid vaccine rollout.

Study:

“Latest statistics on England mortality data suggest systematic mis-categorization of vaccine status and uncertain Effectiveness of Covid-19 vaccination” N Fenton, et al.

The risk/benefit of Covid vaccines is most accurately measured by all cause deaths of the vaccinated versus the unvaccinated. My team specializes in risk analysis. It became clear that the use of the PCR test was driving confusion of reported data because the PCR test does not accurately categorize such data. Thus, there is no valid Government data for such information. If the virus is dangerous, and the vaccines effective there should be less deaths among vaccinated. Our definition of vaccinated is anyone who has had a covid vaccination, which is not the definition used by the Government.

Data from Public Health England, rates per 100,000.

For each age group, there have been more deaths among vaccinated than the unvaccinated. The death rate is worse among the vaccinated. But this is not what is being reported by the Media based on information supplied by the government.

The data used by the media that public is seeing is comparing apples to oranges- young people against old people and data based on improper definitions and methodology- not a valid analysis.

The data shows: among older age groups, they all had huge peaks in deaths when the vaccines were rolled out with vaccinated dying much more than unvaccinated who had no vaccines. It’s clear the excess deaths were due to the vaccines. No other plausible mechanism has been found.

CDC definition of vaccinated- from their website- people are considered fully vaccinated 2 weeks after their 2^nd vaccination. Anyone who does not meet these conditions are considered to be not fully vaccinated. This is the definition of vaccinated versus unvaccinated in the data given the media, thus that the public is seeing. But since it has been verified that most vaccine related deaths and significant injuries are in the first 2 weeks after a vaccination, that means that most deaths and injuries due to the vaccines are being categorized and reported as unvaccinated.

We have verified that the government data is extremely problematic by comparing it to other known accurate data for non-covid mortality.

As is the government data, there is a huge peak of deaths among non-covid deaths when the vaccines were rolled out. It’s clear the vaccines were responsible, under normal circumstances there would be no such peak.

It’s clear the excess deaths could only be caused by the vaccinations- no other plausible reason found. The government is clearly manipulating the data they are releasing to the public, and the data is totally unreliable.

Similar patterns to that shown here have been verified for U.S. data and other countries by published medical studies.

Pfizer data- 6- month clinical trial data- Of the 21 deaths in the vaccinated group not included by Pfizer in the published trial data, 4 were due to cardiac arrest. Of the 15 deaths in the non-vaccinated group, 1 was due to cardiac arrest. They did not include other than healthy young people in the trials, so these were not serious trials, but the trials showed more deaths and cardiac arrests among vaccinated than unvaccinated. The Pfizer data was also shown to be fraudulent as well as inadequate.

The manipulated data is being used to promote the vaccines,

https://thehighwire.com/videos/mathematician-uncovers-disturbing-mortality-data/

Ep 246