The Watson et al. “modeling study”: did “COVID vaccinations” really prevent 14 million deaths?

COVID vaccinations have "substantially altered" the course of the pandemic and "prevented 14.4 million deaths during the first year of COVID-19 vaccination." Whenever a drug achieves the impossible, it is worth examining the underlying data a little more closely and comparing reality.

What requirements must normally be met for the approval of a drug or vaccine?

• For full approval, a pharmaceutical company has to submit all of the following: documentation on the drug’s manufacturing quality, preclinical studies (animal studies), phase 1 and phase 2 studies in humans, and 12 months worth of phase 3 trial results that prove beyond doubt the efficacy and the safety of a candidate drug.
• Once a drug is approved, the manufacturer is required to further investigate its efficacy and safety under real-world conditions

What does the reality of "COVID vaccines" show?

• The internationally available "Real World Evidence" data confirm what the registration studies had already indicated: The "vaccines" are not associated with any relevant benefit, but on the contrary with a negative effect.
• Worldwide daily deaths attributed to COVID-19, March 2020-December 2021
• For 145 countries, "vaccine" use correlates positively with the number of COVID cases and, far more worryingly, with COVID deaths
• Almost all countries experienced more infections and deaths than if "vaccination" had not been given
• Increases in excess mortality were correlated in time with vaccination drives

On what data do Watson et al. base their conclusion that COVID "vaccination" has prevented 14 million deaths?

• The study in question is a mathematical modeling exercise which depends on the underlying data.
• They used previously published models to calculate their projections of the hypothetical COVID mortality that would have occurred without vaccination. The problem with these published models is that they date from the early days of the "pandemic" and are based on data and assumptions which were out of date by 2021 at the latest.

Watson et al. used inflated "COVID death" rates

• "Confirmed cases" are counted based on matching (yet non-specific) clinical symptoms together with a positive RT-PCR test result, whereas with "probable" cases no corroborating PCR test result is available.
• The practice of counting “probable COVID cases” based only on generic symptoms of an upper respiratory tract infection makes no sense from a medical point of view and can serve only to inflate the case count in an unscientific manner.

No relevant excess mortality in the 2020 pandemic winter

• No relevant long-lasting increase in deaths from any cause was observed for the winter of 2020
• Immediately after the declaration of the pandemic, there occurred a sharp peak in all-cause mortality in some jurisdictions, but not in others
• Common sense and historic precedents suggest that the spread of a deadly virus would not be stopped by international or state borders

False assumptions serve as the basis for the calculations

• The data used in the Watson et al. "modeling study" were based on hypotheses related to the Corona pandemic that have since been shown to be clearly wrong
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• There is no preexisting immunity and that the pandemic will affect everyone
• Its effect can only be mitigated by political measures
• More than 90 studies prove that a past infection with SARS-CoV-2 protects better against a recurrence of the disease than the vaccines
• Over 400 studies show that non-pharmaceutical interventions such as lockdowns or school closures to prevent a pandemic are associated with no benefit, only harm

The claim of "vaccination success" is based on unscientific calculations

• Watson et al. use completely unrealistic and demonstrably false figures for their calculations to supposedly prove the efficacy of the COVID “vaccines."
• This leads them to estimate an excessively high mortality which allegedly would have occurred without ‘vaccination.’
• From these inflated hypothetical death counts, they then subtract the officially reported deaths to obtain the “success of vaccination” (Figure 8).

Serious conflicts of interest

• It is imperative to find out how this research was financed

Conclusion

• The hypothesis that the COVID "vaccinations" prevented 14 million COVID deaths and significantly mitigated the severity of the pandemic is based on unrealistic figures and demonstrably false calculations
• To date, the experimental "vaccines", for which an integration into the human genome cannot be safely ruled out, have not been able to prove a relevant benefit
• Real world evidence shows that the "COVID vaccination" is associated with a negative effect overall and positively correlates with an increase in morbidity and mortality associated with SARS-CoV-2 infection as well as in all-cause mortality

References

• Watson, O.J. et al. (2022) Global impact of the first year of COVID-19 vaccination: a mathematical modelling study. Lancet Microbe 2:e279-e280
• Beattie, K.A., et al (2021) Worldwide Bayesian Causal Impact Analysis of Vaccine Administration. Lancet Infect. Dis. 120:146-149
• ResearchGate, Ioannidis, J.P., Rancourt, D.G., and Anonymous (Italy) (2020) report sulle caratteristiche dei pazienti deceduti positivi ancora in Italia. Il presente report è basato sui dati aggiornati al 17 Marzo 2020.

https://doctors4covidethics.org/the-watson-et-al-modeling-study-did-covid-vaccinations-really-prevent-14-million-deaths/