The issue of covid jabs appearing more effective than they are is now largely moot. They don’t even appear effective anymore, with negative efficacy worsening as the number of doses increases, best exemplified by the Cleveland Clinic study. However, their initial supposed success against the original Wuhan (Institute of Virology) strain in the older age groups is still grimly quoted by vax mandarins, to justify the continued slow motion train wreck of getting a jab into every shoulder, not least here in excessively dying NZ.
Covid-19 Vaccines and Healthy Vaccinee Bias
Applied Statistician Mathew Crawford writes at Rounding the Earth Substack and presented at a Panda Open Science Session in January 2023 on the topic of healthy vaccinee bias in relation to Covid-19 injectables. His article series, Shattering the Efficacy Illusion provides an in-depth examination of the subject: see Part 5 which links to the full series. Other articles on the topic include Professor of Public Health Eyal Shahar, Covid Vaccines, the Frail Elderly, and “Healthy Vaccinee” Bias and Healthy vaccinee bias: loud and clear in an ONS analysis (UK); and journalists Alex Berenson, How bad is healthy vaccinee bias in observational data? and Will Jones (also a mathematician), Vaccinated Over-Represented in All-Cause Deaths, ONS Data Show.
Jones’ article specifically highlights the dishonesty that public servants such as Sarah Caul, Head of Mortality Analysis at the UK Office of National Statistics engage in with regards to their use of statistics to promote pharmaceutical products and downplay the harms being seen. This is happening in lockstep across the globe, including in New Zealand as we have shown.
Berenson’s article discusses a retrospective cohort study from Hungary, where the public health academic authors had access to a comprehensive national vaccine database. Amongst a range of interesting findings, the study found that in the summer of 2021, when there were almost no covid infections or covid-related deaths, and the overall death rate was normal, the vaccinated population had a 55% lower death rate than the unvaccinated population, who were also a younger cohort.
This makes absolutely no sense unless there are confounders in the unvaccinated population, listed by the study authors as smoking, obesity, chronic diseases, and attitudes towards collaborating with health services. We agree with Berenson’s conclusion that the many observational studies promoted by public health officials as showing effectiveness of the covid-19 injectable products are rendered invalid by this stunning revelation.
Professor Shahar draws similar conclusions in his articles on healthy vaccinee bias, highlighting the implausibility of the observed phenomenon in the data that covid-19 vaccines appear to prevent all cause mortality. He provides a simple way to adjust for healthy vaccinee bias, by calculating the all-cause mortality rates in the unvaccinated, and in the vaccinated. The difference between the two provides the adjustment required to determine the expected rate of covid mortality if the vaccinated were “just as unhealthy as the unvaccinated”.
Crawford’s article series offers many insights into healthy vaccinee bias and demonstrates the complexities of epidemiology and the many ways data can be misconstrued either purposely or unintentionally. Healthy vaccinee bias is closely associated with socio-economic confounders whereby the wealthier, healthier and higher educated someone is, the less likely they are to die and the more likely they are to be vaccinated.
An existing dataset in the USA, the Vaccine Safety Datalink (VSD) has shown that the covid-vaccinated are as much as 72% less likely than the unvaccinated to die of non-covid causes, which is a strong signal for healthy vaccinee bias. Complaints in 2005 about a lack of transparency in this dataset have never been addressed, and Crawford identifies that the data does not correct for important socio-economic confounders which explain away their flawed results.
He demonstrates that vaccine effectiveness across US counties closely tracks median household income. “In fact, more income seems to be more protective from COVID-19 for a county than vaccines. Maybe lockdowns weren’t such a good idea…“
Crawford’s ultimate conclusion, supported by an array of evidence, is that healthy vaccinee bias and some other biases, fully explain the totality of vaccine effectiveness calculations. Interestingly, he notes the complete lack of consideration for this and other biases in many vaccine studies, showing the marketing role that public health departments now appear to play over sharing objective data.
He even refers to New Zealand vaccinologist Helen Petousis-Harris as an example of “employed researchers with the ability to see around [healthy vaccinee bias] to propose magical effects of vaccines, such as in curing completely unrelated diseases“. In a 2017 study she co-authored, vaccination against Neisseria meningitidis type B (Meningococcal B) suggested possible protection against a “taxonomic cousin”, Neisseria gonorrhoeae (Gonorrhoea). In correspondence to The Lancet, American vaccinologists responded to this claim, suggesting that the study “findings are not robust, even by the standards of observational studies“, and offering a number of biases and confounders that the authors failed to consider. We suspect similar claims are being made about covid vaccination data.
Authorities in New Zealand and across the democratic world are rapidly doubling-down on ‘fact checking‘, and censoring those who dare to question or challenge the prevailing narrative. It seems germane to have observed here that in epidemiology and the sciences, as with democracy (and life in general), divergent perspectives serve a crucial function in the mechanisms for error correction. Robust science depends on it. Ethical medicine depends on it. Genuine democracy depends on it. Why, instead, are dissident voices being marginalised and censored?