Category: COVID 19 deaths and injuries

Debunking Pro-Vaccine Arguments in the Kirsch/Wilf $2M Debate

By BEN

The following is a detailed rebuttal of the arguments presented by Wilf for the pro-vaccine side in this high-stakes discussion.

Steve Kirsch and Wilf are engaged in a multi-round debate with $2 million at stake. The central question: Do the “COVID-19 vaccines” provide a net benefit? Based on the evidence I have reviewed, my position is clear: The covid-19 vaccines have not been shown to have a net benefit. In fact, the data suggests a relatively weak but discernible net harm. This analysis focuses solely on identifying flaws in Wilf’s pro-vaccine position.

General Remarks & Fallacies by Wilf

Later, Wilf remarks that in the past, death signals from vaccination would have been detected. However, concluding that the same would inevitably occur this time is a flawed assumption and represents a logical fallacy.

In addition, he highlights that the mechanism of action causing harm or death would not be unknown. Contrarily, Pfizer explicitly states that ‘the exact immunologic mechanism that confers protection against SARS-CoV-2 is unknown.’ This implies they do not fully understand how their product is even supposed to work.

In contrast, there are at least two plausible mechanisms for harm:

1. Direct cell inflammation and potential cell death caused by lipid nanoparticles (LNP), as described by Ndeupen et al., 2021.
2. The immune system attacks cells that produce the “supposedly foreign” or harmful antigen. This occurs due to the widespread distribution of lipid nanoparticles (LNPs) throughout the body, leading to the destruction of cells in multiple organs, including the heart and brain.

Moreover, vaccine-critical studies have been subjected to significantly more scrutiny, suppression, and even outright banning by journals and certain authors. This double standard raises valid concerns about bias in the academic and scientific discourse surrounding vaccines.

Wilf also overlooks two critical motivations that shape the broader vaccine narrative:

1. Government Objectives: Governments primarily aim to calm the public and maintain order during crises. Tools like masks, tests, and vaccines serve as tangible measures to reassure the public. However, whether these tools are effective is often a secondary concern, as the primary motivation of governments is typically to control the narrative and preserve authority.
2. Pharmaceutical Industry Incentives: The incentives for pharmaceutical companies are clear. With liability protections in place, these companies effectively operate with a blank check, profiting immensely as long as public fear—and thus demand—can be sustained. This is facilitated by significant influence over the media, where the pharmaceutical industry is the major force in advertising spending. Compounding this issue, these companies often conduct their own trials, creating an inherent conflict of interest that undermines trust in the results.

These considerations highlight critical gaps in Wilf’s arguments and underscore the importance of scrutinizing both the evidence and the motivations driving the vaccine narrative.

Establishing the Meaning of Net Benefit

The term Net Benefit implies that the benefits must significantly outweigh the harms, meaning notably more lives are saved than harmed.

There are three main types of evidence to consider to answer the question of net-benefit:

1. Studies that prove causality: These include prospective, double-blind, placebo-controlled trials, which are the gold standard for establishing cause and effect.

2. Confirmed reports and harm statistics: Documented cases and data that provide evidence of adverse outcomes.

3. Post-marketing studies: These studies assess real-world data but can only indicate correlation and cannot definitively establish causation.

So what are the results of the above when it comes to the COVID-19 vaccines:

1. COVID-19 Vaccine Results from Manufacturer RCTs

1. Non-representative study population
2. Testing discouraged <7 days after vaccination
3. Lack of relevant clinical endpoints
4. Early unblinding
5. High dropout rates
6. Possible unblinding via PCR tag
7. Unknown mechanism of immunity
8. Neutralizing antibody timeline mismatch

A detailed article including sources can be found here.

Wilf correctly points out that the studies show no sign. death signal. However, it is important to note that the study population was exceptionally healthy, as individuals at high risk for severe COVID-19 were explicitly excluded. This raises a significant concern: How can a study, primarily designed to evaluate protection against severe illness and death, demonstrate any meaningful effect when the very people most likely to benefit were excluded from participation?

The endpoints used in the studies were inadequate for establishing clinically meaningful efficacy. The only truly relevant endpoint was all-cause morbidity and mortality, yet only mortality was reported, leaving a significant gap in assessing the vaccine’s overall impact. Here’s an overview of the prospective, double-blind, placebo-controlled trials that were conducted for vaccines later administered in the West:

• mRNA Vaccines:
  • All-Cause Mortality: No benefit (RR = 1.03)
  • COVID-19 Mortality: Reduced (RR = 0.4)
  • Non-COVID Mortality: Elevated (RR = 1.16)
• Adenovector Vaccines:
  • All-Cause Mortality: Significant benefit (RR = 0.38).
  • COVID-19 Mortality: Strong reduction (RR = 0.18).
  • Non-COVID Mortality: Unexpected reduction (RR = 0.5), raising concerns of imbalance or trial irregularities.

Evident from the above data, the mRNA vaccines, the most commonly used in the West, show no benefit for all-cause mortality (RR = 1.03) and may increase non-COVID deaths (RR = 1.16). Adenovector vaccines report suspiciously large reductions in non-COVID mortality, raising concerns about potential trial issues. This has been confirmed by a peer reviewed article by Benn et al., 2023.

Notably, all trials were unblinded early, with observation periods lasting less than 3 months (e.g., Pfizer). This limited timeframe is inadequate for detecting medium- to long-term side effects, making it impossible to fully assess potential harms. While follow-up periods were longer, the early unblinding disrupted the balance between groups, rendering proper comparison of all-cause mortality unreliable.

Conclusion: None of the RCTs convincingly demonstrated lives saved, leaving the potential for harm unresolved due to the much healthier population and short observation.

2. Confirmed reports and harm

Individual Case Reports

Myocarditis Autopsy Study

VAERS Data

Official German Cause of Death Statistics

The Statistics Office has confirmed that at least a significant portion of these cases can be directly attributed to COVID-19 vaccination. A more detailed FOIA request by me is currently pending.

Interim Conclusion

3. Observational Studies

Analysis of the entire Hungarian population

• Exclusion of partially vaccinated adults: UK data shows highest mortality in this group.
• Health-related variability: Structural indicators vary across vaccination groups, confounded by general health status.
• Moderna lower survival probability: Highlighted in Figure 2.
• Short observation period: Only 4 months (Apr-Aug 2021), highest mortality observed in partially vaccinated.
• Person-year miscalculation: Potential errors if vaccination date reporting is inaccurate.

Conclusion: The study fails to provide valid evidence of vaccine efficacy due to its very short observation period (4 months), significant confounding, and incomplete cohort comparisons (e.g., ever vaccinated vs. unvaccinated). Similar to the recently published Norwegian study, it cannot demonstrate that mortality rates are indeed equal to or lower in the vaccinated cohort compared to those without the intervention.

Comparing ACM across countries and time

When comparing all-cause mortality across countries, it becomes evident that while vaccines appeared to have an impact in 2021, several other confounders are the primary drivers of excess deaths.

For instance, after adjusting mortality rates for the confounding variable “extreme poverty,” any positive correlation with vaccination disappears entirely.

The significant impact of poverty on mortality has been well-documented, as highlighted by Ioannidis et al. (2023): “Excess deaths (as a proportion of expected deaths, p%) were inversely correlated with per capita GDP (r = -0.60) and positively correlated with the proportion living in poverty (r = 0.66).”

ED of Republicans and Democrats

1. Movement During the Pandemic: Population movement, especially starting in mid 2020, after the initial lockdowns, may have severely affected the AI-based name-matching algorithm used to link voter registration and mortality records. This could lead to significant errors in matching mortality to the individuals.
2. Limited Timeframe: The analysis only extends until 2021. To robustly attribute the observed effects to vaccination, data beyond 2022 is essential. If mortality rates converge after 2021 back to no differences between R/D voters, it would indicate vaccination effectiveness; if not, it could suggest confounding factors or other effects.
3. Societal and Long-Term Factors: Stress, lockdown-related effects, economic hardship, drug overdoses, and other long-term societal impacts cannot be ruled out as contributors to excess mortality, disproportionally affecting R voters.
4. State-Level Discrepancies: The presumed effect is much less visible in Florida but more pronounced in Ohio, suggesting the observed differences may result from factors other than vaccination or party affiliation.
5. Age Adjustment Issues: The study only adjusts for broad age bins. Republican voters, being older on average, may exhibit higher relative effects of mortality impact, which could bias the results.
6. Short Baseline Fit: The baseline is based on a two-year fit (2018–2019) using a Poisson regression model at the county-by-party-by-age level. This short period risks producing artifacts, especially given seasonal or structural trends in mortality. Additionally, no confidence intervals (CIs) are provided for these baseline estimates. This fact alone should immediately dismiss the validity of the study.
7. No Adjustment for Sex or Race: The study does not account for sex or race, both of which are critical factors in mortality and could confound the observed results.
8. Timing of Divergence: The divergence in mortality begins much earlier than the smoothed line suggests, around mid-2020. This timing predates vaccine availability, suggesting that non-vaccine factors played a significant role.
9. Data and Code Not Publicly Available: The lack of public access to the dataset and analysis code prevents independent verification and replication of the study’s findings, reducing transparency and credibility.

The study’s findings are significantly undermined by its methodological flaws. The observed differences in excess mortality, attributed to political affiliation, are likely a proxy for other structural and behavioral factors, such as rural vs. urban residence, socioeconomic disparities, healthcare access, and vaccination behavior. A more robust analysis would require individual vaccination data, adjustments for key demographics, and a longer timeframe to draw valid conclusions. The focus on political affiliation appears overstated and overly politicized.

EDs are Covid

1. COVID-19 Death Classification in Western CountriesMost western countries have incentivized the classification of seasonal respiratory illnesses as COVID-19. Additionally, many apply their own death certificate modeling systems, such as the CDC’s NVSS/MMDS. Source
2. Origin & Clinical Relevance of Found SequenceThe origin & clinical significance of the identified sequence remains unknown to this day. Source
3. PCR Primer Similarity to the Human GenomeThe PCR primers used for COVID-19 testing have a high similarity to the human genome. Source
4. Limitations of Wastewater SurveillanceEven wastewater surveillance cannot substantiate claims that COVID-19 was a novel virus or provide precise assessments of viral levels. The method involves pooling genetic material from multiple strains and individuals, complicating attribution. Furthermore, no pre-2020 data exists to validate these techniques as a reliable control. Source
5. Clinical Validation of COVID-19 PCR TestsThe COVID-19 PCR test has never undergone clinical validation to demonstrate specificity or predictive accuracy for diagnosing COVID-19. In hospitals, many positive results were incidental, meaning individuals tested positive but were not ill with respiratory conditions like COVID-19. Source

All of this raises significant doubts about whether the excess deaths can genuinely be attributed to an assumed novel pathogen.

ED in countries with Zero Covid

The countries cited are predominantly island nations, which may have created the appearance of controlling the virus through border closures and quarantine measures. However, scientific evidence does not conclusively support the effectiveness of these strategies in completely stopping viral spread. Instead, the observed outcomes may have simply sustained an illusion of control within the population.

Notably, after reopening, many of these highly vaccinated countries experienced significant excess mortality over multiple years. For example, Singapore, with a vaccination rate of 94%, recorded substantial excess mortality, especially in the elderly population—but only starting in 2021.

Similarly, Taiwan, another highly vaccinated nation, experienced a comparable trend.

These figures challenge the assumption of a highly effective vaccine. In contrast, some countries with lower vaccination rates—such as Luxembourg, Denmark, and Germany—reported little to no notable excess mortality. A full ranking can be found here.

Wilf should investigate whether these deaths could be linked to mechanisms such as Antibody-Dependent Enhancement (ADE) or other vaccine-related factors that may exacerbate disease outcomes. Alternatively, he should assess whether these excess deaths are genuinely attributable to SARS-CoV-2 or if other contributing factors better explain the observed trends. Data from the Mortality Watch Excess Ranking, based on age-standardized deaths and a conservative 3-year pre-pandemic baseline, reveals at least two dozen countries that did not exhibit statistically significant excess mortality during the 2020–2023 period. These findings challenge the notion of a universally impactful pandemic and warrant further scrutiny into regional disparities and underlying causes.

Saved by the Vaccine

Wilf’s argument regarding “neutralizing antibodies,” which are demonstrated in vitro to neutralize the virus, is fundamentally flawed. Antibodies are not inherently specific to this virus, and their levels are merely determined by concentration (titers). In fact, most antibodies may be found in small quantities across all individuals, rendering their purported specificity questionable.

Moreover, no studies have conclusively shown a correlation between antibody levels and improved clinical outcomes. As such, the argument lacks empirical support and is ultimately moot.

Israeli data

Effect on cases and CFR

Covid Deaths by Vaccination Status

In summary, the chart suffers from at least three major issues:

1. Use of unreliable dataThe analysis relies on biased, uncontrolled, and unvalidated COVID-19 testing data, rather than objective, gold-standard metrics like all-cause mortality.
2. Exclusion of relevant dataVaccinated individuals are only considered “fully vaccinated” 14 days after their second dose. This approach omits at least five critical weeks of data, including the period immediately following vaccination, which could influence outcomes.
3. Misclassification of vaccination statusThe “unvaccinated” group likely includes a significant number of vaccinated individuals whose vaccination status could not be matched or verified. For example, in Germany, approximately 80% of individuals’ vaccination statuses are unknown, leading to severe misclassification.

These issues are not unique to U.S. data; similar problems exist in datasets from other countries. On the other hand, data from New Zealand provides a contrasting perspective. It shows that mortality rates for vaccinated and unvaccinated groups are similar, and the country experienced no statistically significant excess mortality during the pandemic. This, along with Sweden’s experience, serves as evidence that there was no widespread health crisis requiring extraordinary measures to begin with.

Covid Deaths by Vaccination Rates

Calculating Lives Saved

Summary

Hard evidence, including ICD-10 coded vaccine-related deaths, confirmed autopsies, and detailed case reports, clearly demonstrates that these vaccines can cause harm and even death.

Observational studies, despite their volume, are riddled with methodological flaws that render their conclusions unreliable. Issues such as insufficient evidence, methodological weaknesses, and pervasive confounding are pervasive. Additionally, societal and lockdown measures disproportionately impacted unvaccinated individuals, especially from mid-2021, when significant societal pressure and mental stress were placed on them. Social exclusion and related stress led to further disruptions, including relocation (skewing population data/denominators), changes in life routines (e.g., commuting, eating habits), and increased drug use, complicating the interpretation of these studies even further.

These considerations underscore that there is no solid basis to claim that the net effect of vaccines can ever be shown to be causally positive. The belief that “vaccines work” appears to remain a matter of faith rather than scientific evidence.

Original source: https://www.usmortality.com/p/debunking-pro-vaccine-arguments-in

Survey Results: Did Anyone in Your Family Take the COVID Shot?

By STEVE KIRSCH

The survey, once again, confirms these shots likely killed over 1M Americans.

Executive summary

About the survey

1. The survey asked participants to participate if any family member was vaccinated. Injury questions only appeared AFTER they started filling out the form.
2. There was a negative control which was the % seeking medical assistance. We know this number is at least 8% from the v-safe data. It turns out v-safe likely underestimates this.
3. There is selection bias but it is likely not more than a factor of 2 based on the negative control.
4. People were asked their OPINION on whether the deaths were caused by the vaccines. I asked them to detail WHY they believed this. You can make your own assessments as to the reliability by reading the explanations.
5. Additional survey questions were added as the survey went on. This is why some columns are empty at the start.
6. I included the unfiltered responses, but only processed records that were “sanity checked”

The survey and results

Results so far

What the survey found so far

1. Responses: 5,330
2. Average vaccinated people per response: 4
3. % who needed medical care: 20%
4. Death attributed to COVID shot: 47 per 1,000 vaccinated
5. % of ALL deaths observed in the family since 2021 attributed to shot: 61%
6. Average age at time of death: 75
7. Average # days from shot to death: 196

Let’s assume there is responder bias and the v-safe number is accurate. This would reduce the death rate by 2X. Let’s also assume our “non-professional” observers are inaccurate about vaccine-mediated deaths 4 out of 5 times (please read the descriptions and judge for yourself; they all seem pretty accurate to me).

So we can estimate an overall average of 5 deaths per 1,000 vaccinated.

Summary

This survey shows the COVID vaccines were a disaster.

Even if my survey is off by a factor of 50, it still means 250,000 Americans have been killed.

In an honest society, surveys such as the one I just did (which took all of 30 minutes of my time) should be DEMANDED by the medical community.

No academic researcher anywhere in the world is going to try to replicate this survey. It would be career suicide. Look what happened to Mark Skidmore.

If RFK is confirmed, collecting these statistics will likely be a high priority.

Original source: https://kirschsubstack.com/p/survey-results-did-anyone-in-your

More Than 100 Young Children Suffered Seizures After COVID Vaccination: Study

By Zachary Stieber

More than 100 young children suffered seizures after receiving a COVID-19 vaccine, according to a new study.

One hundred and four children under 6 years old suffered a seizure within 42 days of a COVID-19 shot, researchers with the U.S. Centers for Disease Control and Prevention (CDC) and other institutions found.

Others suffered strokes, blood clotting disorders, and appendicitis, the researchers said. They analyzed health records from the Vaccine Safety Datalink (VSD), a CDC-funded network that features sites operated by Kaiser Permanente, Marshfield Clinic, Health Partners, and Denver Health.

The researchers examined events that fit one or more of 23 specified outcomes, including seizures and myocarditis, a form of heart inflammation, following messenger RNA COVID-19 vaccination.

The Pfizer and Moderna COVID-19 vaccines both use messenger RNA technology.

Children were studied if they received a vaccine dose between June 18, 2022, and March 18 of this year; 247,011 doses were administered to children under 6 during that time. Researchers examined the events that occurred within 42 days of vaccination.

Original source: https://www.theepochtimes.com/article/more-than-100-young-children-suffered-seizures-after-covid-vaccination-study-5321835

Former Pfizer Vice President Dr. Mike Yeadon Drops a Bombshell, Claiming that the mRNA COVID “Vaccines” were Deliberately Engineered to Harm, Disable, and Kill, with the Ultimate Goal of Reducing Human Fertility

By Shadow of Ezra

Former Pfizer Vice President Dr. Mike Yeadon drops a bombshell, claiming that the mRNA COVID “vaccines” were deliberately engineered to harm, disable, and kill, with the ultimate goal of reducing human fertility.

Former Pfizer Vice President Dr. Mike Yeadon drops a bombshell, claiming that the mRNA COVID “vaccines” were deliberately engineered to harm, disable, and kill, with the ultimate goal of reducing human fertility. pic.twitter.com/zUtQn6BaSI

— Shadow of Ezra (@ShadowofEzra) December 27, 2024

Original source: https://x.com/ShadowofEzra/status/1872665139213918651

Did the COVID Vaccine Save More People Than It Killed?

By STEVE KIRSCH

Here are the first round of arguments in our high stakes debate. Winner gets the $2M in escrow.

Did the COVID vaccine save more people than it killed?

Kirsch argument

Wilf argument

Let me know what you think in the comments!

Here’s what happens when you ask AI to help you promote this

Original source: https://kirschsubstack.com/p/did-the-covid-vaccine-save-more-people

Peter Hotez Blames “Organized” Anti-vaxxers for Causing 200,000 American Deaths by Convincing People COVID Shots weren’t Safe

By Vigilant Fox

“My estimate is 200,000 Americans needlessly perished because they refused the COVID vaccines. They were victims of this.”

“I still pin most of the blame on an organized anti-vaccine movement that targeted people, that had convinced them that the COVID vaccine wasn’t safe… But most of the blame still goes to this organized anti-vaccine movement.”

Just a reminder: Hotez turned down a $2.6 million offer to debate RFK Jr. on vaccine science, with the money going to the charity of his choice.

Instead of engaging in scientific debate, he preemptively BLOCKS anyone he disagrees with.

Click Here To Play Video

Original source: https://t.me/VigilantFox/14297

Pfizer’s Own Study Shows Their COVID Vaccines Increase Your Risk of Serious Adverse Events (Up to 71% Higher)

The full study results were obtained via a FOIA request because Pfizer and the health authorities won’t voluntarily disclose it. You’re about to find out why.

By STEVE KIRSCH

Executive summary

But for some reason, which I still can’t figure out, they missed it. Again.

So it’s up to your friendly neighborhood misinformation spreaders (such as myself) to bring this to your attention.

The Pfizer study results (CONFIDENTIAL)

Full study
This is marked Pfizer Confidential so it’s important that you don’t tell anyone. We’ll save lives by keeping this quiet, apparently.

Confidential Abstract
This is marked Pfizer Confidential so it’s important that you don’t tell anyone. We’ll save lives by keeping this quiet, apparently.

What the study said

Table 16 of the full study summaries the findings.

First of all, you should note that the unvaccinated are in general far less healthy and die at over 2X the rate that the vaccinated do (see the Deaths (any causes) and Sudden death lines).

So when we look at hazard ratios between vaccinated and unvaccinated and find that they are the same or higher (i.e., >=1), we should be VERY concerned.

Note: The lower death rate of the vaccinated is selection bias: vaccinated people are generally more health conscious and have higher socio-economic status. It has nothing to do with the COVID vaccine saving lives (there is no plausible mechanism of action causing lower death rates; if there was, I’d be the first one to get my shots).

From Table 16, I note the following statistically significant increases:

1. Acute aseptic arthritis: 1.23 (1.11, 1.35)
2. Diabetes mellitus type 1: 1.21 (1.02, 1.45)
3. Acute cardiovascular injury including microangiopathy: 1.38 (1.31, 1.45)
4. Arrhythmia: 1.36 (1.29, 1.44)
5. Heart failure: 1.29 (1.13, 1.47)
6. Coronary artery disease: 1.49 (1.31, 1.69)
7. Myocarditis (7 days): 9.70 (1.24, 75.97) [it may be higher than this but they censor counts <5 to protect privacy because if it was known 1 person got it, everyone would know who it was).
8. Myocarditis or pericarditis (21 days): 1.68 (1.06, 2.66)
9. Secondary amenorrhoea: 1.71 (1.34, 2.18)
10. Hypermenorrhea: 1.40 (1.23, 1.60)
11. Anaphylaxis: 31.95 (7.82, 130.52)

Other articles about the study

Here are Nick’s excellent articles with amazing graphs that Pfizer doesn’t show you:

The Hidden Pfizer Report That Shows Up to 40% More Heart Conditions in the Vaccinated

Revealed: The Hidden Pfizer Report That Shows Heart Conditions in the Vaccinated Getting Worse Over Time
This has stunning graphs

Summary

Original source: https://kirschsubstack.com/p/pfizers-own-study-shows-their-covid

A Study Involving 1.7 Million Children has Found that Myocarditis and Pericarditis only Appeared in Children who had received Covid mRNA Vaccines

By LauraAboli

Original source: https://t.me/LauraAbolichannel/65311

Australian Excess Deaths are Highly Correlated with the Number of Booster Vaccinations

By STEVE KIRSCH

Booster shots correlated strongly with excess deaths. Changing the number of unvaccinated people didn’t change the excess deaths. Who would have guessed?

Executive summary

• a strong correlation between the number of booster shots, total vaccinations, and recent vaccination relative to excess deaths
• the more shots, the more COVID cases
• the booster shots kill approximately 1 person per 1,182 which validates our estimates of 1 per 1,000 killed by the shots.

In short, this paper blows apart the narrative.

The key data from the paper

Bottom line is this:

1. More vaccines —> more excess deaths (estimate 1 death per 1,182 boosters)
2. More vaccines —> more COVID cases

Check out the pinned comment

So let’s assume Jason knows 1,000 people. Here are the probabilities of finding a Jason if the vax kills 1 per million or better (considered to be “safe”) vs. if the vax kills 1 per thousand.

As you can see, Jason can’t exist if the government is telling the truth.

But his story, though a bit rare, is EASILY consistent with the “killed 1 per 1,000” hypothesis.

>>> cum(5, 5e-6)=2.6e-29
>>> cum(5, 1)=0.0037

Summary

These vaccines were truly a disaster and this statistical analysis makes it crystal clear. There is just no other way to explain all the correlations.

Note how they had to tone down their conclusions in order to get their paper published.

Original source: https://kirschsubstack.com/p/australian-excess-deaths-are-highly

Newly Emerged Data has Revealed an Alarming Surge in Major Birth Abnormalities Among Mothers who Have Received Covid mRNA “Vaccines”

The shocking discovery was revealed in Pfizer’s own pregnancy trial data.

Pfizer recently updated the results of their randomized clinical trial of the Covid injections on pregnant women.

The clinical trial, ID NCT04754594, is entitled: “To Evaluate the Safety, Tolerability, and Immunogenicity of BNT162b2 Against COVID-19 in Healthy Pregnant Women 18 Years of Age and Older.”

The results from the trial were analyzed by MIT computer scientist and data expert Steve Kirsch.

Kirsch, the inventor of the optical computer mouse, is the founder of the Vaccine Safety Research Foundation (VSRF).

After breaking down the clinical trial results, Kirsch made a chilling discovery.

Kirsch found that mothers who received a Covid mRNA “vaccine,” before or during their pregnancy, were over four times more likely to give birth to a baby with major congenital abnormalities.

The data reveals that “vaccinated” mothers had a stunning 4.2X higher rate of Adverse Events of Special Interest (AESI) when compared to unvaxxed moms.

The AESI manifests as severe birth defects and developmental delays in just the first 6 months after childbirth.

Kirsch explains that, because the trial enrolled fewer women than planned, the effect size reached only the 90% level of significance.

Based on just this trial, it is 90% certain that the vaccines made things worse, he notes.

However, when you look at other data, the certainty approaches 100%.

4.2 times, or a 320% increase, is a staggering surge for these types of major birth defect adverse events.

In addition, the data shows that pregnant mothers saw not benefit from receiving the injections.

Moms in both groups got the same number of COVID-19 infections – 2 in each group.

Vaccine efficacy was estimated at a measly 3.8 because the groups were different sizes.

A perfect vaccine is 100 and one that does nothing is 0, Kirsch explains.

The 3.8 value is so small that it is statistically insignificant.

It’s entirely possible that the vaccine increased your risk of getting COVID-19 – something the study failed to cover.

This was all known more than 5 months ago when the results were obtained by Pfizer.

Concerns about the risks for vaccinated pregnant women and their children have been growing for some time.

As Slay News reported, official government data emerged earlier this year that shows that a staggering number of pregnant women suffered miscarriages and other reproductive ailments after they received a Covid mRNA shot.

Two sets of data have revealed that both the Canadian and U.S. governments were aware of the harm caused to pregnant women but kept the information hidden from the public while pushing the “safe and effective” narrative.

A Canadian government database was exposed in a new report showing an explosion of horrific side effects among expectant mothers who received the mRNA injections.

In Canada, governments and businesses widely mandated the Covid mRNA shots during the pandemic.

According to the database, the average number of patients assigned the following reproduction-related diagnostic codes increased, on average, in every category from 2021 to 2022 over 2015 to 2019.

It reveals that infertility in both men and women has soared dramatically.

Meanwhile, nations around the world have been raising the alarm over plummeting birth rates and soaring excess deaths among their vaccinated populations.

Experts in the Philippines are warning that birth rates are now falling far below sustainable levels.

Official Filippino government data shows that the country’s population has plummeted by almost 1.3 million people since the mass vaccination program emerged in early 2021.

The alarming figures were revealed in data from the Philippine Statistics Authority.

The nation’s highly-vaccinated population suffered a major drop between 2020 and 2023.

It comes as experts have been alerting the public about a chilling warning regarding the mRNA injections from a leading scientist.

As Slay News reported, Professor Dr. Dolores Cahill, a world-renowned immunology expert, issued an explosive warning to the public that everyone who has been vaccinated with Covid mRNA shots “will die within 3 to 5 years, even if they have had only one injection.”

Since the Covid mRNA shots were rolled out in early 2021, Cahill has been sounding the alarm about the devastating impact they will have on public health.

Not only does Cahill think the shots are dangerous, but she warns that they will eventually kill everybody who has received one or more doses.

During an interview, Cahill explains how mRNA in the injections harms all recipients and acts like a ticking time bomb in the Covid-vaccinated.

After explaining how the shots impact human health, Cahill made this following chilling prediction:

“Everybody who has an mRNA injection will die within 3 to 5 years, even if they have had only one injection.”

Resources:
https://x.com/toobaffled/status/1863095915512582337
https://slaynews.com/news/major-birth-abnormalities-surge-among-covid-vaccinated-mothers/