Open Letter: Responding to Fake Vaccine Efficacy Research

Srečko Šorli sent a letter to the editor of The Lancet, a scientific journal that published an article claiming that covid-19 vaccines saved lives.

A scientific study published in The Lancet in 2022 estimates that 14.4 million lives could be saved worldwide as a result of mass vaccination with covid-19 vaccines. Srečko Šorli, a researcher, responded to the study and drew the attention of Ursula Hofer, editor of the journal, to its major methodological flaws. You can read their letters below.

Subject: Concerns Regarding the Mathematical Model in the Article Global impact of the first year of COVID-19 vaccination: a mathematical modelling study (Lancet Infect Dis 2022; 22: 1293–302)

Dear Editor,

The article Global impact of the first year of COVID-19 vaccination: a mathematical modelling study by Watson et al. [1], published in September 2022, presents a hypothesis that is widely used by advocates of mRNA vaccination to support its efficacy. However, there are significant concerns regarding the appropriateness of the mathematical model employed in the study. The model only considers the vaccinated subset of the population (subset A) while completely neglecting the unvaccinated subset (subset B). From a mathematical standpoint, this is methodologically inadmissible, as the population is composed of both subsets. To accurately assess the impact of vaccination, a comprehensive model that includes both subsets A and B is necessary.

The article's assertion that COVID-19 vaccination saved 14.4 million lives in 2021 is based on the assumption that the death rate in subset A was lower than in subset B—a hypothesis that remains unproven due to the exclusion of subset B. By September 2022, sufficient data were available to incorporate subset B into the model and provide a robust analysis. Moreover, dividing the population into five age groups: 0-20, 21-40, 41-60, 61-80, and above 80 would help to avoid Simpson's paradox, where aggregated data may hide critical differences within specific subgroups. According to the statistical law of large numbers, for each group, the following equation is valid: .

vaccinated/alive = vaccinated dead/dead

The study fails to address the crucial comparison between the calculated number of vaccinated deaths and the actual statistical number of vaccinated deaths for each month in 2021. According to the authors' claim that vaccinations saved lives, the statistical number of vaccinated deaths should be lower than the calculated number based on proportional mortality. Without this comparison, the central argument of the study remains speculative. To illustrate, consider a scenario where 30% of individuals are given red bracelets in January 2021; if by February only 20% of the deceased were wearing red bracelets, it would suggest a reduction in mortality due to the bracelets. A similar approach should be used for COVID-19 vaccination to determine how much, in percentage, vaccination reduced mortality within subset A compared to subset B.

In conclusion, the authors should revise their model to account for the unvaccinated population and perform a thorough analysis of mortality rates across both subsets. This would provide a more accurate and scientifically rigorous assessment of how many lives were truly saved by vaccination. Including this data would substantiate the claim of 14.4 million lives saved, turning it from an unproven hypothesis into a verifiable fact. Furthermore, a transparent breakdown of the impact across different age groups would strengthen the credibility of the study’s conclusions and eliminate the risk of misinterpretation.

It is essential to include the unvaccinated population to gain a complete understanding of the vaccine's efficacy in reducing mortality. Excluding such a critical subset may lead to flawed conclusions that undermine the study’s validity. By refining the mathematical model and including the missing calculations, the article could significantly contribute to the scientific debate on the global impact of COVID-19 vaccination.

Finally, public health policy decisions should be based on comprehensive and transparent data that includes all subsets of the population. Only through such rigor can we ensure that the conclusions drawn are reliable and serve the best interests of society. Revisiting the model and addressing these concerns would substantially enhance the value of the study and ensure it withstands scientific scrutiny.

Thank you for your attention to these points.

Sincerely, prof. Amrit Srečko Šorli, physicist

24 of September: LANCET EDITOR RESPONSE

Dear Prof. Šorli,

Thank you for your recent submission to The Lancet Infectious Diseases. We have now had time to consider your manuscript and unfortunately, on this occasion, we have decided not to publish it. The paper chose a counterfactual scenario for the model. As you correclty point out, other models could be used to look at the question; that would be different paper though. Please note that we try to keep our correspondence section timely, thus we aim to consider correspondences that have been submitted within 6 weeks of the original publication.

Although this decision has not been a positive one, I thank you for your interest in the journal and hope it does not deter you from considering us again in the future.

Yours sincerely,

Ursula Hofer
Editor in Chief, The Lancet Infectious Diseases

25 of September: MY RESPONSE

Dear Editor Ursula Hofer,

according to official data, 6,3M people more died in 2021 than in 2020. 

SOURCE

Where are 14,4 M saved lives with COVID-19 vaccination in 2021, even God does not know. The article “Global impact of the first year of COVID-19 vaccination: a mathematical modelling study” is the biggest scientific fraud in the history of medicine and should be immediately retracted. 

Sincerely Yours, prof. Amrit Srečko Šorli