A Critical Analysis of Covid-19 Vaccine Impact Claims

This article was co-authored by Dr. Timothy Kelly.

Introduction

“Do you think there would have been less deaths overall if we hadn’t had a vaccine?”

This question was posed to Dr. Aseem Malhotra by Steven Bartlett during an interview on Bartlett’s podcast Diary of a CEO. To which Dr. Malhotra responded simply “Yes.”

Full Fact, a fact-checking organization, has written a verdict on Malhotra’s answer, claiming: “False. There is clear evidence that the vaccines saved far more lives than they cost.”

While we appreciate Full Fact’s attention to this important question, their verdict is premature, given that the true answer has not yet been conclusively determined by medical science.

Part I: The Illusion of Certainty – Deconstructing Claims of Vaccine Efficacy

The assertion that “There is clear evidence” of Covid-19 vaccines’ benefits outweighing their harms” exemplifies a dangerous oversimplification of complex medical realities. This claim, often propagated by fact-checkers and mainstream narratives, fails to acknowledge the fundamental limitations in our current understanding and the methodological flaws inherent in much of the existing research.

The Missing Gold Standard: Randomized Controlled Trials (RCTs)

In evidence-based medicine, properly conducted RCTs measuring all-cause mortality are the gold standard for determining an intervention’s overall impact. For Covid-19 vaccines, no such trials have demonstrated an all-cause mortality benefit. The original trials were not designed or powered to detect differences in all-cause mortality, and follow-up periods were too short to capture long-term effects. Without this crucial evidence, claims of clear benefit are premature at best and misleading at worst.

The Pitfalls of Observational Studies

In the absence of robust RCT data, fact-checkers often turn to observational studies. However, these studies are fraught with potential biases that consistently overestimate benefit and underestimate harm:

Selection Distortion: Healthy user bias and time-dependent effects inflate apparent vaccine benefits and mask potential harms due to inherent differences in vaccinated groups and changing study conditions.

Temporal Misclassification: Survivorship bias and miscategorization of vaccination status in early post-injection periods artificially inflate efficacy estimates and underestimate potential harms.

Classification Bias: Vaccine status classification errors occur in a single direction, with the vaccinated often misclassified as unvaccinated. This results in infections and harms in the vaccinated being misattributed to the unvaccinated group, overestimating benefit and underestimating harms.

Reporting Bias: Systematic underreporting of adverse events following vaccination due to factors like lack of recognition, dismissal of potential vaccine-related causes, or fear of professional repercussions leads to underestimation of vaccine risks and overstates safety.

Publication Bias: The preferential publication and promotion of studies showing positive vaccine effects, coupled with the suppression or non-publication of studies showing no effect or negative effects, skews the overall body of evidence and public perception.

The Modeling Mirage

Fact-checkers often rely on modeling studies to support dramatic claims of lives saved, compounding the issues of observational studies:

• Amplification of Errors: Small inaccuracies in input data or assumptions lead to wildly inaccurate projections
• Oversimplification: Complex real-world dynamics are reduced to equations that may not capture crucial nuances
• Confirmation Bias: Models can be inadvertently (or deliberately) tuned to produce expected or desired results
• Lack of Falsifiability: Unlike controlled experiments, many model predictions are not truly testable
• Overconfidence: Precise-looking numbers create a false sense of certainty

In conclusion, modeling studies often use overestimates of benefit taken from observational studies to create oversimplified models tuned to further amplify these overestimated benefits. By extrapolating across millions, they produce unrealistic estimates that can never be verified by proper scientific experimentation.

The magnitude of benefit from Covid-19 vaccines is likely much smaller than portrayed by observational and modeling studies. To determine the net effect of the vaccines, both known harms and potential yet unknown harms must be carefully considered against this uncertain benefit.

Part II: Evaluating the Evidence of Harm

Given the uncertain and likely overestimated magnitude of benefit, it is crucial to consider the potential harms of the Covid-19 vaccines. Dr. Malhotra’s expert opinion that the vaccines may have resulted in a net loss of life for society is justifiable and defensible based on various studies and their logical implications.

Reanalysis of Clinical Trial Data

A re-analysis of the original clinical trials of the mRNA Covid-19 vaccines revealed an increased rate of serious adverse events of 1 in 800. Serious adverse events are defined as either death, hospitalization, or prolonged disability, most of which would certainly reduce life expectancy. Considering that billions of doses have been administered worldwide, this suggests millions may have suffered serious vaccine-induced harms. This rate is orders of magnitude higher than the typically accepted rate of serious harm from other vaccines (approximately 1-2 in a million).

Observational Studies and Autopsy Findings

The high rate of serious harm identified in clinical trials has been corroborated by observational studies from surveillance systems in the US and European Union. Additionally, autopsy studies have confirmed that a significant percentage of deaths occurring within 30 days after Covid-19 vaccination were caused by the vaccine, unequivocally demonstrating that the vaccines can cause death.

It’s worth noting that while observational studies consistently overestimate benefits, they simultaneously underestimate harms due to factors such as healthy user bias, publication bias, reporting bias, and classification bias.

Population-Level Mortality Trends

If the Covid-19 vaccines offered more benefit than harm, we would expect to see decreased excess deaths in highly vaccinated populations after 2021 compared to 2020. However, nearly all nations with high mRNA vaccine uptake experienced higher excess mortality in 2021 than in 2020, contrary to the typical pattern following a pandemic. These elevated excess deaths have persisted beyond 2021, raising concerns about the vaccines’ ongoing impact.

Moreover, since 2022, an overall mortality benefit from the Covid-19 vaccines has become less likely, given that variants have become less deadly, most of the population has been infected, and vaccine efficacy appears greatly reduced. Yet, the serious harm caused by the vaccines likely remains constant, suggesting a worsening harm-benefit ratio over time.

Part III: Current Harm-Benefit Analysis

While uncertainty remains without a Covid-19 vaccine clinical trial testing all-cause hospitalization or mortality, we can attempt an informal harm-benefit analysis using existing data:

• Re-analysis of clinical trials found that within the original clinical trials the rate of serious adverse events in the vaccinated was greater than the protection offered against Covid-19 hospitalization
• Using UK Health Security Agency observational data on vaccine effectiveness and the rate of serious harm from clinical trials, they found for people over 90 (the highest risk group), vaccinating 7,000 people would prevent one Covid-19 hospitalization that requires oxygen but cause about 7 serious adverse events
• The benefit-to-harm ratio becomes increasingly unfavorable for younger age groups based on the UKHSA data, with those under 45 requiring nearly a million vaccinations to prevent one hospitalization

Ethical Considerations in Continued Vaccination

Even if the initial introduction of Covid-19 vaccines offered a net mortality benefit (which remains uncertain), it is much less likely that they offer a net benefit today and moving forward. Without a proper clinical trial, we will remain uncertain about the true harm-benefit balance. Continuing to offer a prophylactic intervention with an unknown and potentially negative harm-benefit profile is unethical.

Conclusion: The Call for Reassessment

The complex nature of mRNA vaccine risk-benefit analysis underscores the need for ongoing, rigorous scientific inquiry and open, honest dialogue about the impacts of large-scale medical interventions. Dr. Malhotra’s position that the Covid-19 vaccines may have had a net negative impact is justifiable based on the available evidence and the significant uncertainties that remain. In response to these concerns, the Hope Accord was created. This petition, of which Dr. Malhotra and the authors of this article are founding co-signers, calls for the suspension of Covid-19 vaccines and a return to fundamental ethical principles that were abandoned during the pandemic.

Tens of thousands of individuals have already signed the Accord, reflecting growing concerns about the continued use of these vaccines without comprehensive safety data. We invite all who share our concerns to join us in signing the Hope Accord and supporting a thorough reassessment of Covid-19 vaccine policies.

To conclude, the complex medical question of Covid-19 vaccine’s impact on all-cause mortality across society remains one of profound uncertainty. In this context, Full Fact’s unequivocal verdict demonstrates a concerning level of hubris in scientific interpretation. When contacted about their scientifically invalid verdict, Full Fact maintained confidence in their position, citing the same synthetic modeling studies and unreliable observational data from their original article. This case illustrates a broader concern: fact-checking organizations often oversimplify complex medical questions and present certainty where none exists. The public deserves more rigorous and truthful evaluation of such complex scientific questions.