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UK Statistics Regulator Admits that the Claims Made About COVID "Vaccine" Effectiveness are Unfounded

Report here from Prof Norman Fenton, appearing on NTD News.

I recently committed a cardinal sin of letting myself get drawn into a “debate” on Twitter. Inevitably, it very quickly attracted the trolls with ad hominem attacks but even before that, it seems there are still people out there who haven’t realised that the studies “proving” vaccine effectiveness are flawed and biased.

It’s impossible to have a reasonable discussion with anyone who hasn’t done their research properly, especially if they are simply hell bent on defeating you, rather than seeking to draw out the truth of the situation.

Thankfully, the UK statistics regulator has finally gone on record to admit what we first reported over a year ago and published on ResearchGate1. The ONS data is so riddled with flaws, bias and confounding factors that it cannot be used to substantiate claims of vaccine effectiveness.

Ed Humpherson, Director General for Regulation, Office for Statistics Regulation

The damage done as a result of mainstream media and the Government itself, promoting the “vaccine” on the back of these flawed analyses is irreparable.

To continue to rely on these studies to argue that the product is Safe and Effective™ is beyond ignorant. And you can’t reason with ignorance.

ICYMI, here’s a summary of the main flaws and biases in pretty much all the studies of “vaccine effectiveness”:

  1. Undercounting the unvaccinated population due to erroneously low estimate of the total population;

  2. Overcounting the unvaccinated events due to misclassification, i.e. considering people as unvaccinated within 14-21 days of their first injection;

  3. Undercounting the vaccinated events by only considering those events that occur 14 days after the “primary” course and simply ignoring everything that happens in between [my favourite - think foxhole and bunker analogy];

  4. Survivorship bias - those vaccinated who survived to the “fully vaccinated” endpoint may well have health and immunological qualities that are superior to those who did not and are therefore not a matched cohort to the unvaccinated. Indeed, it might even be the case that the vaccinated who avoided getting infected in the weeks between jab 1 and “full protection” might simply have acquired natural immunity from infection before the jab campaign. Imagine that!

  5. Aggregating or averaging data across time periods with significantly variable levels of mortality and vaccination rates. In other words, claiming there are more unvaccinated people infected over a period that starts with more COVID incidence before most people got vaccinated.

Original video: COVID-19 Vaccine Mortality Data Flawed: Expert

By Malcolm Hudson

January 27, 2023



With well over 350k reads, 23 recommendations and 5 citations, it’s not possible for any responsible government agent or journalist not to know about this. ResearchGate states: “This item's Research Interest Score is higher than 99% of research items on ResearchGate.”.

Dead Man Talking
Dead Man Talking
Joel Smalley