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The latest data released by the UK Office for National Statistics (“ONS”) regarding deaths by vaccination status artificially inflates mortality rates of unvaccinated people and also reduces rates of death for vaccinated people.  It’s unlikely this is merely due to sloppiness or error.

Last week we published an article showing that, according to ONS’s latest ‘Deaths by Vaccination Status’ data for England, 9 in every 10 covid deaths over the past two years were among the vaccinated.  For our article, we simply considered the number of deaths with no calculation or comparison to the overall or total population size.

The Office for National Statistics (“ONS”), however, myopically focused on covid age-standardised mortality rates (“ASMR”) or deaths per 100,000 person-years. The number of “person-years” is the denominator for ONS’s calculation.  But, as we noted in a previous article, the determination of this denominator is flawed because, for example, ONS had not included data for males after September 2022 even though the latest data is up to December 2022.

In a Substack article, Dr. Clare Craig explained a further problem, a bias within the denominator used by ONS.  The bias involves what Dr. Craig calls the “ghost population.”  These are people not included as part of ONS’s total population because their NHS or National Immunisation Management System (“NIMS”) data (representing people registered with a GP) and census records do not exactly match.   To demonstrate the enormity of the problem, Dr. Craig noted that in England, the number of people over 5 years old registered with a GP is 59.5 million.  However, according to census records, only 53.4 million people over 5 years old are recorded.  A difference of 5.9 million.

“The kinds of people most likely to end up as ghosts are those who did not complete the census forms, those with names where spelling can vary such that matching may not have been possible, and people using a different name on the census to the one on their medical record. You could be in all the datasets and still be a ghost because of matching problems,” Dr. Craig wrote.

Of the adult population, Dr. Craig calculated that there are 4.7 million “ghost population” vaccinated and 8.4 million “ghost population” unvaccinated.

“The ONS claim to have included only 40.8 million adults in their sample where census and NHS number data matched,” Dr. Craig wrote. “Compared to all the people included in the NIMS vaccination database there is a good representation of vaccinated people in the ONS sample but only a small fraction of the unvaccinated are represented … There is, therefore, a bias towards inflating a mortality rate (fraction of deaths over population) by not including the entire population in the denominator.”

Professor Norman Fenton agrees. “There is still gross underestimation of the proportion of unvaccinated in the population. This artificially inflates mortality rates of unvaccinated and reduces rates of vaccinated,” he wrote.  Adding, “none of the core limitations and flaws of the previous report have been resolved. The ONS appear to have ignored the UK statistics regulator who required them ‘to address some of the sampling issues present in the first six iterations of the publication’.”

In November 2022 Prof. Fenton, Professor Martin Neil, Dr. Craig and Scott McLachlan wrote a formal letter of complaint to the Statistics Regulator about the ONS data on vaccine mortality. “All of the anomalies in the dataset introduce bias in favour of analyses supporting vaccine ‘safety and efficacy’ … We believe that an investigation into how and why the ONS dataset is so flawed and corrupted is required,” the letter stated. 

On 20 January the researchers received a response from the regulator. “While there are aspects of the response that we are unhappy with, the crucial point is that they have completely accepted our main recommendation [that ONS’ Deaths by Vaccination report cannot be used to support vaccine ‘safety and efficacy’],” Profs. Fenton and Neil wrote.

John Campbell discussed the latest data with Prof. Fenton who pointed out the flaws, biases and inconsistencies of the previous report that have not been fixed.

Further reading:

• The new UK ONS data is out and it’s worse than before by El Gato Malo
• The latest ONS data on deaths by covid vaccination status by Professors Martin Neil and Norman Fenton

John Dee has also been reviewing the latest ONS ‘Deaths by Vaccination Status’ report.  Dee is a former UK government PSO/G7 scientist and section leader for a policy area whose work “sometimes pushed [him] in the direction of the ONS.” The following are a few extracts from a much longer article, the third part of his analysis, which adds to the findings of those above.  You can read Dee’s full Part 3 article HERE, Part 1 HERE and Part 2 HERE.

ONS Vaccination Deaths Analysis (Part 3)

By John Dee

We’re on the fifth day of the new ONS file of files with a revision for outright bloopers already released but with a bunch of issues remaining.

Big Time Mess

I think it fair to say that the Office for Nobbled Statistics (“ONS”) has messed-up big time with arguably the most important dataset they’re going to churn out this year. One commentator declared that the dataset has “more holes than Swiss cheese” and another asked why a pathologist – Dr Clare Craig – can spot multiple errors in a file that took a team of trained officers 7 months to prepare. How is it even possible to get males and females mixed up, and what’s with the missing entries?

By now some of you will have gathered that the latest release omits Jan, Feb and Mar 2021 these being critical early months in which the first vaccine-induced deaths would have been recorded. ONS are also ignoring all teenagers and children under the age of 18, so we don’t get to analyse those tragic deaths of youngsters that have been making headlines.

On the technical side, they’ve resorted to using ASMR (age standardised mortality rate) in breakdowns by age group that don’t need standardisation, and they decided to run with the overly coarse bin of 18 – 39 years. There are issues with ASMR that I might cover in a later article; suffice it to say that this doesn’t always do what it is supposed to do and can obfuscate a great deal.

Neither is the cohort used representative of the nation of England as a whole, it being a subset of people whose data records have been successfully and unambiguously linked to the ONS 2021 census. That is to say, they left a whole bunch of people out simply because they couldn’t link them via their NHS number (not everybody has an NHS number) – Dr Clare Craig seriously digs into this in her fabulous Substack, ‘Deaths Among The Ghost Population’. A consequence of this is that unvaccinated souls are under-represented in the database and this distorts derived ASMRs. As if that wasn’t sufficient, they’ve also ignored people who died very quickly after receiving their injection. I wonder why?

Can all this be attributed to sheer sloppiness and error? I think not …

Missing in Action

[Looking at the chart below] I think we can see now why the ONS cohort should really be called a sample and a biased one at that. That great leap from just under 40 million individuals to just under 46 million individuals between March and April 2021 is going to have an effect, and that alone may well skew derivation of ASMR depending on who was included and how the ONS went about this.

[In the chart below] we now see in terms of raw head counts just what sort of individual was excluded from the ONS cohort over time compared to the altogether more robust NIMS cohort. In the first few months both series play see-saw, with the first big period of bias alarm popping up May 2021 – October 2021 in which vaccinated folk were going missing in comparison to unvaccinated. This bias swings into reverse from November 2021 through to October 2022 when we observe consistent under-sampling of the unvaccinated. These swings are bound to mess up derivation of ASMRs to the point where I consider them useless.