UK's Office of National Statistics data screams of Covid vaccine harm

Are you "Data Driven"? If so, how do you know the data is accurate?

Photo by Alexander Sinn on Unsplash

Emeritus Professor of Risk at Queen Mary University,

Norman Fenton

co-authors the substack “Where are the Numbers” with

Martin Neil

(professor of Computer Science and Statistics also at Queen Mary). He was interviewed by John Campbell on his extremely popular YouTube channel earlier this week.

Fenton explained the work he and his colleagues have been doing to expose the erroneous data with regard to all cause mortality in the vaccinated and unvaccinated British population as published by the Office of National Statistics (ONS).

The Office for National Statistics is the UK's largest independent producer of official statistics and the recognised national statistical institute of the UK. It is responsible for collecting and publishing statistics related to the economy, population and society at national, regional and local levels.

The ONS is the UK’s largest independent producer of official statistics.

This story is vitally important because it demonstrates the depth of deception around what is happening in our world right now. If you cannot trust official statistics, what can you trust? It also highlights the problem the medical orthodoxy is having in seeing beyond their own blinders. Though they encourage everyone to “do their own research” and “think critically”, according to them researching and critical thinking means going to our respective agencies of public health and accepting what they say as the truth. What are we to do if they are being disingenuous or deliberately misleading?

There is no good solution. They have the data. They can spin it however they wish.

The Matrix

Mainstream media sources will lap it up and spit it out as undeniable truth. Moreover, they will label anyone who has the audacity to question their reporting as unhinged extremists who refuse to accept reality and instead choose to spread dangerous “misinformation”.

How do we know that the data is fudged?

It begins with healthy skepticism.

As I explained in a series of articles (Safe and Effective? Parts 1-4), the Pfizer/BioNTech vaccine trials were fraudulent. Allegations from a whistleblower like Brook Jackson was not required to see this. Evidence of fraud is in the memoranda between Pfizer and the advisory committee of the FDA.

Pfizer investigators were unblinded and only tested 5% of symptomatic trial participants. It is likely that they were able to exaggerate the protective benefit of their formulation by selectively testing the unvaccinated and establishing an astonishing 95% efficacy in preventing symptomatic Covid infection.

However soon after the vaccine was deployed in the United States, the CDC and mainstream media immediately touted its protective benefit. In the summer of 2021, Drs. Fauci and Walensky appeared on mainstream platforms proclaiming that nearly all Covid deaths were occurring in the unvaccinated. 

At the time the CDC was not publishing the vaccination status of those dying from Covid-19. Six month results from Pfizer’s adult trial demonstrated that in order to prevent a single Covid death, 20 thousand people would need to receive the primary series. Even so, all cause mortality was higher in the vaccinated cohort. How could nearly all Covid deaths be among the unvaccinated?

Then, in the early autumn of 2021, a stunning statistic came out of the UK’s Health Security agency:

The rate of Covid-19 infections were higher in the fully vaccinated population over the age of 40! At the time, we were beginning to accept the fact that the protective benefit of the vaccine was “waning” and that boosters would likely be necessary. However the UK was reporting that if you were over 40 and were vaccinated you were more likely to get Covid. This wasn’t just a vaccine that was wearing off–-it was eventually harming those who got it.

Neither was it an aberrant blip in a trend. Subsequent UK HSA Covid-19 surveillance reports showed that the harm was growing month by month. A few months later nearly every age group in the UK that was fully vaccinated had a greater risk of contracting Covid than the unvaccinated. Yet here in the U.S., CDC data continues to paint a rosy picture:

What could explain such a disparity in outcomes? Was the CDC publishing corrupted data?

Personally, I could not think of a reason why the UK would intentionally inflate infection rates in the vaccinated. Then, in the spring of 2022, UK HSA announced that they would no longer be publishing this data. By that time, infection rates in the vaccinated were 4 to 5 times higher than in the unvaccinated.

This is when I stopped trusting CDC PSAs and focused on the British numbers. This is where the ONS comes in.

The ONS began releasing large data sets tracking deaths and mortality rates by vaccination status in the summer of 2021. I did not examine the data until I stumbled upon a YouTube channel called “Back to the Science” where a scientist by the name of Susan Oliver claimed that the ONS data proved that the Covid vaccines were not harmful and could not be contributing to excess mortality.

The basis of her claim was simplistic. She merely compared the Age Standardized All Cause Mortality between the unvaccinated and vaccinated and got this:

Whole Period is the time window of January 2021 and May 2022. The y-axis is deaths per 100,000 person years. Clearly, the mortality rate among the unvaccinated is nearly three times higher than in those who have received at least one jab (Ever Vaccinated).

This “fact” was corroborated by this plot (taken from the same data set) which compares Covid mortality rates over time between the unvaccinated and those who have been given at least one shot:

It seems obvious that the vaccine offers a substantial protective benefit against Covid-19 deaths. Why else would there be a striking rise in Covid-19 mortality in the unvaccinated at the beginning of 2021? This is as far as Dr. Oliver, mainstream media sources and popular substack authors like Dr.

Katelyn Jetelina

(who writes under the name Your Local Epidemiologist) take it.

Unfortunately, there are numerous problems with this approach. The biggest is the distortion that arises from age standardization. The unvaccinated population is much younger than the vaccinated. Age standardized numbers attempt to correct for this by weighting the contribution of mortality rates in different age groups to a “standardized” population. This will necessarily decrease the contribution of mortality rates in the young and increase that in the older unvaccinated people. The opposite happens in the vaccinated.

If we instead add up the number of deaths in the unvaccinated and divide by the unvaccinated person years and do the same for the vaccinated, i.e. calculate the true mortality rates, we get something much different. 

The left graph is the All Cause Mortality, age standardized. The right is the unstandardized, or true mortality rate comparison.

Are the vaccinated dying at a greater rate? The answer is yes, but not necessarily due to the vaccine. The vaccinated mortality rate is higher primarily because they are older.

The difference in age between the two groups is called a confounder. In fact, there are many confounders present in the data besides age. More affluent people are more likely to get vaccinated and they are historically healthier and live longer. Level of education is also a confounder. The more educated have lower mortality rates and are also more likely to get vaccinated because they “trust the science” more or because they were compelled to by their employer.

Nevertheless, the relative youthfulness of the unvaccinated trumps the other confounders in the data. The point of this illustration is not to prove that the vaccine is harmful but to demonstrate how difficult it is to get to the bottom of things and how misleading simplified explanations from self-appointed “experts” can be.

In any case, age-standardization is not required if the ONS provides us with age-stratified data. They do. It tells an interesting story if one cares to look (see below).

The “miraculous” benefits of Covid vaccines?

Let us now take a closer look at mortality rates over time. As shown above, it seems that the unvaccinated were dying from Covid at a substantially higher rate than the vaccinated at the beginning of 2021. However, when we examine mortality from causes other than Covid we get this:

What’s wrong with this picture? It should prompt us to ask the obvious question: why would getting a Covid vaccine protect against deaths from causes other than Covid? Shouldn’t the mortality from non Covid causes be about the same whether you were vaccinated or not? Does the Covid vaccine also prevent deaths from suicide? Cancer? Car crashes and homicides? As the graph above demonstrates, non-covid mortality in the two groups eventually approach each other, but why the enormous disparity at the beginning of 2021?

Drs. Oliver and Jetelina would have you believe that this is due to “long Covid” deaths that were prevented by vaccination. However there is very little evidence to support this in the medical literature. Moreover, if the large difference in mortality was due to long Covid amongst the unvaccinated, why was it occurring during the first months of 2021 when people were first getting jabbed?

It is nonsensical to maintain that getting vaccinated after having contracted Covid would somehow protect against “long Covid”. But Covid vaccine proponents seem to have little problem in attributing any perceived association with a favorable outcome to the vaccine itself.

The ONS misclassified deaths

Fenton et al went further. They separated the unvaccinated mortality rates by age group. This what the ONS data showed, if one bothered to look:

Mortality rates are higher the older you are, but look at the time at which mortality peaked in each group. If deaths among the unvaccinated were occurring primarily from the winter wave of Covid they should have been happening at roughly the same time. They weren’t. They were staggered. What else was staggered? Answer: the availability of the Covid-19 vaccine to the British population (older age groups were eligible earlier).

We now have a reasonable hypothesis for why there was a big jump in mortality among the unvaccinated at the same time the vaccines became available. Deaths among the recently vaccinated were being misclassified as unvaccinated deaths.

Getting around the confounders

What happens when we examine the mortality rates in those who received the jab by comparing those who recently (within three weeks) got the first dose? I found something startling:

By looking only at the vaccinated, we eliminate the confounding in the propensity to seek vaccination. I also broke it down by age group. The blue is the mortality rate in every age group for those who were in receipt of the first dose within three weeks. The red is after three weeks. Mortality rate is normalized to the unvaccinated, meaning “1” is the mortality rate in the unjabbed.

The ONS data shows that after three weeks of receiving the first dose, people were dying from causes other than Covid-19. Why did non Covid-19 mortality jump in each cohort after three weeks??

The same thing happened with the second dose:

Six months after getting the second dose (red) non-Covid mortality in every age group is higher than soon after receiving the second dose (blue). Notice that people between the ages of 55 and 80 quadruple their mortality rate from non-Covid causes six months after getting their second dose. Is this really the case? Or did the ONS move deaths from those recently vaccinated with the first dose into the unvaccinated group and move those recently vaccinated with the second dose to the “one dose, greater than 21 days” group? In other words, this is more proof that deaths were being misclassified. The large jump in mortality occurs because deaths in those recently jabbed were thrown into other cohorts, which is why the mortality rates are so low.

If vaccine proponents and the mainstream media insist that the large bump in unvaccinated mortality was due to Covid-19 they have to explain

• Why are unvaccinated, non-Covid deaths staggered by age group coinciding with vaccine roll-out?

• Why did they suffer a jump in Non Covid deaths too?

• Why was the vaccine causing a significant jump in mortality after a few weeks to a few months?

The Matrix

The ONS has either (deliberately or not) misclassified deaths or the vaccine is causing fatalities after a few weeks to months. It’s one or the other.

I invite you to listen to Dr. Fenton’s interview with John Campbell (linked above) where he explains the implications of these numbers and how, despite multiple requests for clarification and correction the ONS statisticians have yet to make good on what should be their mission of transparently providing the public accurate data.

Let us be clear. If any scientist inadvertently made such errors in a paper it would be cause for an immediate retraction and a source of public embarrassment. If it was done knowingly, it would forever compromise their reputation in the scientific community and end their career as a legitimate researcher. In this situation we cannot confirm what the intentions of the statisticians at the ONS were. We can definitively say that their dubious reports supported the vaccine campaign that has affected millions of lives.

We are at a precarious time. If we cannot trust the statisticians at our public institutions, who can we trust? Professor Fenton? “Your Local Epidemiologist”? What is your intuition telling you?