The ONS data on vaccine mortality is not fit for purpose
(See 20 Jan 2023 update on this story)
Following on from our latest report highlighting multiple anomalies in the most recent ONS covid vaccine mortality surveillance report we have written the following self-explanatory letter to the Statistics Regulator (email@example.com):
Since the ONS began producing its covid vaccine mortality surveillance reports in 2021, we have been highlighting various anomalies in their datasets. This includes strong evidence that many of those dying shortly after vaccination were being misclassified as unvaccinated (http://dx.doi.org/10.13140/RG.2.2.28055.09124) and systematic undercounting of deaths occurring within first two weeks of vaccination (http://dx.doi.org/10.13140/RG.2.2.12472.42248).
We are especially concerned about the latest ONS dataset (https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/deathsbyvaccinationstatusengland) and have produced a detailed analysis which highlights the multiple glaring anomalies in it (http://dx.doi.org/10.13140/RG.2.2.30898.07362).
We show that, in addition to further definitive evidence of the misclassification and missing deaths, there is: a) gross underestimation of the population proportion unvaccinated, and b) mortality rates that are both nonsensical in various categories and completely incompatible with historical rates.
We believe that there are multiple violations of your code of practice (https://code.statisticsauthority.gov.uk/wp-content/uploads/2022/05/Code-of-Practice-for-Statistics-REVISED.pdf). In particular, the dataset breaches the Quality and Value criteria numbered: Q 1.1, Q1.4 – 1.7, Q 2.4, Q 2.5, Q 3.2 – 3.5, V 1.1, V 3.2 – 3.3.
All of the anomalies in the dataset introduce bias in favour of analyses supporting vaccine ‘safety and efficacy’. The fact that these data are being used as continued justification for the efficacy and safety of the covid vaccines is therefore now a matter of national concern and scandal. We believe that an investigation into how and why the ONS dataset is so flawed and corrupted is required. In the meantime, we call for
1. the public withdrawal of the ONS dataset and
2. the retraction of any claims made by others that are based upon it.
Norman Fenton, Martin Neil, Clare Craig and Scott McLachlan
A slightly updated version of our report (with more detailed reference citations than the version on ResearchGate) is here.