A new paper highlights a newly discovered “alarming source of bias or potential corruption” in the Office for National Statistics (ONS) COVID-19 Vaccine Surveillance report. This has led the authors of the paper to conclude that the ONS should publicly withdraw their dataset and they call for the retraction of any claims made by others that are based upon it.
The Expose – The ONS report is tasked with providing the reported deaths after vaccination data for the whole of 2021, however, they have been said to have displayed systematic undercounting of both covid and non-covid totaled deaths occurring within the first two weeks of Covid-19 vaccination.
The paper published on the 3rd of March 2022, highlights that when comparing the published covid deaths for England as a whole against those in the ONS dataset for covid deaths the bias is evident according to the authors.
These authors are the trusted names now familiar to most of us, including Doctors. Claire Craig – Martin Neil , Norman Fenton, McLachlan, Smalley Guetzkow, Engler, Russell, and Rose, and in the acknowledgments, they mention that the paper has also “benefited from the input of senior clinicians and other researchers who remain anonymous to protect their careers.” (Reflecting the sad fascistic reality of these last two years where experts speaking the factual truth can result in dismissals, doctors being struck off and vilification).
The Office for National Statistics
According to Craig et al, the Office for National Statistics has been under pressure to release a dataset of deaths after vaccination, Although ONS had at first promised a release of this data in March 2021, they did not release any data until six months later and since then there have been updates in November 2021, December 2021 and February 2022 [source].
The reason for the pressure on the ONS to release this data is most likely with the intent to reassure the public that vaccination had caused no harm. Nevertheless, in order to provide that reassurance the accuracy of any data purporting to show covid 19 vaccine effectiveness or safety is critically dependent on the accuracy of four measurements:
- People classified as having the disease;
- Vaccination status;
- Reported deaths; and
- The population of vaccinated and unvaccinated (the so called ‘denominators’).
Errors in any of these could undermine claims of vaccine effectiveness or safety, yet, anomalies have been previously identified in the UK Government’s ONS deaths by vaccination status data (ONS dataset) -specifically that some deaths occurring shortly after vaccination are being wrongly classified as unvaccinated deaths.
Therefore, further problems have been identified in the current report that appears to explain anomalies in the ONS data: the total deaths reported by ONS are significantly lower than should be expected compared to other government datasets, even allowing for the fact that the ONS use only a subset of the population.
A thorough investigation of the rise in non-covid mortality of the unvaccinated which coincides with peak vaccine rollout in each separate age category has been shown to be compatible with a data lag or data miscategorisation [source]. Some (including ONS themselves) claimed the explanation was a “healthy vaccinee” effect. What they found through this analysis was that the data does not support this “healthy vaccinee” effect, This is for two reasons:
- First, because the proportion of the unvaccinated population considered to be in poor health fell during the vaccination rollout and remained low even after the unvaccinated population fell to only a small number.
- Second, the same spike in mortality in the unvaccinated was observed when looking only at deaths of those in very poor health.
The ONS Bias
The Craig et al, analysis, combined data from other data sources, including ONS data on total weekly registered death counts [source], and from the UKHSA NIMS data on numbers vaccinated [source], in order to estimate and compare the mortality pattern in the whole population of England against the ONS dataset.
Undercounted – They found that the scale of undercounting is equivalent to the number of deaths that would have been expected to have occurred within the two-week period immediately after vaccination. Only those deaths that occurred during the third-week post-vaccination match historical expected non-covid death counts and concurrent covid death counts, this is true across the age groups 60-69, 70-79, and 80+.
It was not possible to compare deaths in the period after a second vaccination as these have only been released monthly rather than by week, and the ONS has not released whole population data for deaths by month with an age breakdown.
Missing Millions of vaccinated Deaths – Additionally comparing the population in the ONS dataset and the UKHSA vaccination dataset, NIMS (National Immunisation Management System) [source] they found evidence that the population that appears in the ONS dataset is missing millions of people categorised as within 21 days of first dose vaccination, that are present in the NIMS dataset.
The number missing exceeds what would be expected based on the proportion of the whole population not included in the sample. These biases appear to be systematic and cover covid and non-covid deaths.
The death counts registered for England were also compared [Source] with the ONS dataset and it was found that 13,593 deaths were missing from the ONS dataset(taking account for the fact that the ONS use only a subset of the population).
The mortality rate in the vaccinated and unvaccinated population omitted from the dataset is disproportionately high when compared to historical norms, whilst that reported for the vaccinated are disproportionately low, as previously reported in [source].
In summary, three new key pieces of evidence suggest that the ONS failed to accurately report deaths and omitted deaths that occurred within two weeks of vaccination:
So through simply comparing the ONS dataset expected historical mortality rate, as published by the ONS, with the mortality rates published in the ONS dataset for 2021, for non-covid deaths”, it appeared to be clear that the ONS data reported that deaths of both non- covid and covid deaths respectively for the “within 21 days of first dose vaccination” category tally almost perfectly with the number of deaths that would be expected should they have occurred in the third week alone? Hmm, strange that…
Even stranger when considering that the ONS also seem to have completely omitted two weeks of post-first vaccination deaths from their dataset.
Could it be a reporting lag or errors in the transcription or handing of data? Well, that would be saying the ONS are not too good at doing the job that they are tasked to do.
However, it’s either that or as Craig et al concluded – the “dataset is, therefore corrupted, and that making any inferences about vaccine efficacy or safety that are reliant on the data, “moot.”
What do you think? Should the ONS publicly retract their data and should all claims made by others be retracted?