FEW things from the covid-19 era seem to have penetrated the public mind more effectively than the myth of vaccine effectiveness. Specifically, the ‘covid-19 vaccines saved millions of lives’ myth.
This myth is like the last refuge of scoundrels; all else clearly failed including lockdown, masks and social distancing. But had it not been for the vaccines, we would never have emerged from the ‘pandemic’. Here at TCW we have never been convinced and have been at pains over recent years to indicate why. However, we have lacked a comprehensive account of how the myth arose and why it is false. Until now.
Recently published by three Israeli scientists, Yaakov Ophir, Yaffa Shir-Raz, Shay Zakov and United States cardiologist Peter McCullough ‘A Step-by-Step Evaluation of the Claim That COVID-19 Vaccines Saved Millions of Lives’ does the job admirably. The study is currently in pre-print form on ResearchGate® which is a site where academics may share their work.
Given the contents of the article, it is unlikely to progress beyond the pre-print stage and that will undoubtedly be compounded by the fact that one of the authors is Peter McCullough. His name on any covid study usually sounds the death knell for any hopes of publication.
Indeed, the authors recount their experience of submitting a previous manuscript countering the covid orthodox narrative to ten leading medical journals. All were ‘desk-rejected’, meaning they were not even sent out for review. The authors refer to the ‘perceived moral boundary’ encountered whenever anyone produces evidence that does not support vaccine efficacy.
Taking the 2021 Lancet Infectious Diseases modelling study as the origin of the ‘millions of lives saved’ myth, the authors first explain the limitations of the modelling approach. Modelling is based not on real-world data but rather on speculative or unverified assumptions about vaccine efficacy, natural immunity, and covid death reporting accuracy. In fact, many of these assumptions are just plain wrong as Ophir et al go on to explain.
The assumptions supporting such modelling include ‘exaggerated infection rates and case fatality ratios’, underestimating the ‘waning of vaccine effectiveness over time’ and the ‘Healthy Vaccinee Bias’. They also include ‘unresolved conflicts of interest’ which are not declared. Of course, Heaven forbid those developing and testing covid vaccines could be biased. In the same vein, inconvenient decisions are ignored such as those by the Australian Department of Health which recommended against covid vaccination for healthy children and adolescents due the risk of extreme illness being very low and the potential benefits of the vaccines in this group not outweighing the potential harms.
Early in the article, the authors state: ‘Existing studies on COVID-19 vaccines have yet to provide a robust, long-term comparison between potential benefits and harms.’ Even in the key trial by Pfizer, used to promote vaccine effectiveness, it is conveniently overlooked ‘for every case of severe COVID-19 potentially prevented by the vaccine, approximately two to three additional serious adverse events were reported in the vaccine group’.
It is not news that the covid orthodox exaggerate the lethality of covid-19. It is their stock-in-trade. The likely risk was always inflated and the ‘pandemic’ phenomenon of excess deaths is always pointed to as a ‘howzat?’ They ignore the effective closure of health services across the world, the patent neglect verging on abuse of older people in nursing and residential homes and the likelihood that the covid vaccines themselves could be contributing to these deaths. Similarly, the poor distinction between deaths ‘with’ as opposed to ‘of’ covid, referred to by the authors, augments the perception of the risks associated with covid-19.
Regarding the waning effectiveness of covid vaccines over time, this issue has largely been sidestepped both by having short follow-up periods or, where follow-up was sufficient and reduced vaccine effectiveness was observed, the exact opposite was reported. They lied.
The phenomenon of healthy vaccinee bias is well illustrated by Ophir et al using data from Israel which clearly demonstrate the uptake of covid vaccines was much less in frail older people confined to home than amongst the younger, healthier and ambulant. The consequence of this well-known bias is that vaccine effectiveness is exaggerated.
Also referred to the authors is the misattribution of vaccination status. Although they do not explain this further or what the consequences are, they refer to another Israeli study carried out at the national airport which has profound consequences of the ‘millions of lives saved’ myth.
The importance of the study lies in its more realistic comparison of the covid-vaccinated versus the unvaccinated. Whereas other studies tended to underrepresent the unvaccinated compared with the vaccinated, the airport required everyone, regardless of vaccination status, to be tested for covid-19.
The covid tests are poor, we know, and prone to false positives. But the same tests are used in the airport as are used in other studies, so the comparison is valid. The myth-building studies are based on studies where the unvaccinated are underrepresented but in the airport study, where they are not, the likely benefit of the vaccines is much reduced.
In the words of the authors of the study: ‘The relative protection of the booster shot against infection is likely to be significantly smaller than the initial estimates.’ Moreover, at one point in the study, the vaccinated group had a ‘significantly higher positivity rate’ than the unvaccinated, although the obverse was observed later.
Related to the above was the definition of vaccination status. To be considered vaccinated, ‘individuals who received the initial 2 doses more than 6 months ago were required to receive the booster vaccine’. This brings us to a phenomenon, not considered in the study, but described by Norman Fenton and colleagues as the ‘cheap trick’.
The trick involves, in most covid vaccine studies, classifying vaccinated people as unvaccinated within a period (commonly two weeks) of receiving a vaccine. The cheap trick thereby exaggerates the effectiveness of the vaccines. Anyone in the vaccinated group who inconveniently becomes infected, hospitalised or dies can, conveniently, be classified as unvaccinated.
By means of the cheap trick Fenton et al show it is quite possible to conclude a vaccine is highly effective, even when it has no effectiveness whatsoever. It should be noted, the cheap trick and the healthy vaccinee bias are synergistic. Both phenomena are likely to be operating at the same time in most covid-19 vaccine studies.
A final consideration is that Ophir et al, given the percentages cited for effectiveness of covid-19 vaccines, are almost certainly using relative risk reduction (RRR) rather than the recommended absolute risk reduction (ARR). If the present study and those they cite had used ARR over RRR it is quite likely they would conclude that, far from saving millions of lives, the covid-19 vaccines are virtually useless at best and positively harmful at worst.
