The Lancet released two papers (in 2022 and 2024) entirely based on mathematical and statistical deception. These two articles are influencing the current public health policies globally. To protect public health, they must be retracted without delay.
In the article "Global impact of the first year of COVID-19 vaccination: a mathematical modelling study" [1], Lancet claims that 14 million lives were saved in 2021 with COVID-19 vaccination. The average mortality in 2015-1019 was 56,78 million people, and the sample standard deviation σ was 0.83585.
Our World Data Mortality 2015-2022
In 2020 6.3 more people died than the average mortality in 2015-2019. In 2021, 6.08 million more people died than in 2020. If 14 million people were saved with the vaccination in 2021, then in 2021 14 million people fewer would die than in 2020 [2]. The discrepancy is 20 million people.
In the article Estimated number of lives directly saved by COVID-19 vaccination programs in the WHO European Region from December, 2020, to March, 2023: a retrospective surveillance study [3], Lancet claims that excess mortality caused by COVID-19 virus in 2020 diminished in 2021 by 63%. Statistical data confirm excess mortality in 2021 was in respect to 2020 higher for 6.08 million people, which is 96.5% [2]. The discrepancy is 159.5%.
None of the articles that are referenced in these two articles compared the mortality rate of the vaccinated population with the mortality rate of the unvaccinated population, which is the only statistical method to measure COVID-19 vaccination effectiveness objectively [4]. This means that all references used in these two articles which claim that COVID-19 vaccination savedlives also are statistical fraud. In 2021 mortality rate of the vaccinated part of the population was higher by 14.5% compared with the unvaccinated part of the population [4].
Reference [1] has in the title term “mathematical modelling”, but in this article, there is no one mathematical or statistical equation. In reference [3] on the page 717, is an equation:
The equation above has no statistical or mathematical meaning. The authors and reviewers of these articles were mathematics and statistics illiterate or wrote and reviewed these articles intentionally, to cover the immense damage that the COVID-19 vaccination has done to public health.
In articles [1,3] there is no real mathematics and statistics. The term "mathematical modelling studies" is a complete misuse of mathematics, the greatest intellectual achievement of human civilization. In reference [1], there is no single mathematical equation. The equation in the reference [3] has no mathematical meaning and is disconnected from statistical data.
Two articles in the Lancet [1,3], with all their references, claim that COVID-19 vaccines saved lives. In both articles, the most commonly used term is 'we estimate', but their estimates lack mathematical backing and are not supported by statistical data. They are the biggest mathematical-statistical fraud in the history of science. This is the reason why these two articles need to be retracted immediately.
Literature:
1. Global impact of the first year of COVID-19 vaccination: a mathematical modelling study https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(22)00320-6/fulltext
2. The Discrepancy Between the Number of Saved Lives with COVID-19 Vaccination and Statistics of Our World Data https://www.longdom.org/open-access/the-discrepancy-between-the-number-of-saved-lives-with-covid19-vaccination-and-statistics-of-our-world-data.pdf
3. Estimated number of lives directly saved by COVID-19 vaccination programs in the WHO European Region from December, 2020, to March, 2023: a retrospective surveillance study https://www.thelancet.com/journals/lanres/article/PIIS2213-2600(24)00179-6/fulltext
4. Rigorous Statistical Analysis of COVID-19 Vaccination Assures Appropriate Public Health Policy https://www.preprints.org/manuscript/202503.0796/v1
All articles are available in PDF format here.
Prof. Amrit Srečko Šorli
Bijective Physics Institute, Slovenia
https://www.webofscience.com/wos/author/record/ABH-6270-2020
