The Censorship of Mercola — A Timeline

  • While the drug and chemical industries have attacked and tried to discredit me for years, blatant censorship didn’t begin until 2020, after the outbreak of the COVID pandemic

  • The timeline of censorship and free-speech right violations against me began in the summer of 2020, when the Center for Science in the Public Interest (CSPI) called on the U.S. Food and Drug Administration and the Federal Trade Commission (FTC) to take action against me for recommending vitamin D

  • The attacks against me really heated up though after I published a peer-reviewed scientific paper on the benefits of vitamin D at the end of October 2020. Christmas Eve 2020, attorney general Letitia James sent a cease and desist notice, demanding we stop sharing information about how immune-boosting nutritional supplements might lower your risk of COVID. The FDA also issued us a warning letter about the same

  • Fabrications by the Center for Countering Digital Hate (CCDH) have been the primary “evidence” cited by government officials intent on censoring me. The CCDH is linked to a number of technocratic centers within the globalist network through its board members

  • In August 2021, after conducting an internal investigation, Facebook’s content policy director called out the falsehoods in the CCDH “Disinformation Dozen” report. CCDH preselected the 12 individuals listed in the report, and the narrative was based on nothing more than “a narrow set of 483 pieces of content over six weeks from only 30 groups, some of which are as small as 2,500 users”

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While the drug and chemical industries have attacked and tried to discredit me for years, blatant censorship didn’t begin until 2020, after the outbreak of the COVID pandemic.

For legal and historical purposes, I am sharing a timeline of events with you that document a chain of coordinated events and attacks against me and this website. My first article about the pandemic came out February 4, 2020, in which I predicted that it was a grossly exaggerated threat that would enrich pandemic vaccine makers.

March 8, 2020, I published an interview with bioweapons expert Francis Boyle, Ph.D., in which he warned that SARS-CoV-2 had all the hallmarks of a genetically engineered bioweapon. Boyle was among the first, if not the first, to suspect the outbreak was the result of a lab leak.

While every health authority on the planet insisted there was no treatment, and that patients simply go to the hospital to be placed on mechanical ventilation and die, I interviewed medical experts working on early treatment options and published articles detailing the potential benefits of vitamin D, zinc, quercetin and other nutraceuticals that boost immune function, as well as decades-old drugs like hydroxychloroquine.

I also published the testimony of whistleblowers such as Erin Marie Olszewski, a frontline nurse, who warned that patients were being intentionally killed on ventilators as it quickly proved to be a deadly intervention for COVID-19.

Early on, it became apparent that vitamin D levels and spending time outdoors played an important role in the risk of infection and the ultimate outcomes. This has been true for all respiratory infections, so it should come as no surprise it is also true for coronavirus infections. Despite that, health authorities insisted vitamin D was useless.

The only way out of the pandemic, they said, would be a vaccine — and this despite the fact that no previous attempts at creating a safe and effective coronavirus vaccine had ever succeeded because of its rapid ability to mutate.

In June 2020, I launched an information campaign, StopCovidCold, about vitamin D. I released a downloadable scientific report detailing how and why optimizing vitamin D levels among the general population could minimize the impact of the next wave of COVID. Optimizing vitamin D is a rational, safe and inexpensive measure that no sane health official would object to. And yet, they all did.

July 21, 2020, the Center for Science in the Public Interest (CSPI) issued a press release

calling on the U.S. Food and Drug Administration and the Federal Trade Commission (FTC) “to bring enforcement proceedings against Mercola and his companies for their unlawful disease claims that falsely and misleadingly claim to treat, cure or prevent COVID-19 infections.”

CSPI accused me of falsely claiming “that at least 22 vitamins, supplements and other products available for sale on his web site can prevent, treat, or cure COVID-19 infection.” This despite the fact that their Appendix of Illegal Claims

clearly show I made no COVID-19-related claims to any specific products and only referenced published studies and mainstream media articles to support my opinions.

In an August 12, 2020, email, CSPI president Dr. Peter Lurie — a former FDA associate commissioner — also made the spurious claim that I was “profiting from the pandemic” through “anti-vaccine fearmongering:”

“Mercola brazenly has claimed that many of his products are coronavirus treatments or cures, including vitamin C, vitamin D, zinc, selenium, ‘molecular hydrogen,’ licorice, and other substances.

Besides profiting from the pandemic, Mercola has seemingly advised people to contract COVID-19 after taking supposedly ‘immunity boosting’ supplements (which of course he sells). Making matters worse, Mercola is a leading proponent of anti-vaccine conspiracy theories — and has been fearmongering against prospective COVID-19 vaccines even before such vaccines are available!”

By mid-August, a comprehensive campaign to put an end to Mercola.com had been launched, with Laurie asking CSPI members to flood the FDA and FTC with prewritten Tweets, urging them to take action against us. He also urged “state attorneys general to investigate how they may further protect consumers from Mercola’s illegal marketing.”

Not surprisingly, CSPI is funded by the Rockefeller Foundation, the Rockefeller Family Fund, Bloomberg Philanthropies and other billionaire-owned foundations. It’s also partnered with Bill Gates’ agrichemical PR group, the Cornell Alliance for Science. Greg Jaffe, who heads up CSPI’s Biotechnology Project, is also the associate director of legal affairs at Alliance for Science.

The attacks against me really heated up though after I published a peer-reviewed scientific paper

on the benefits of vitamin D at the end of October 2020. With that, I established my medical and scientific merit and my right to a professional opinion, which is something the U.S. Constitution absolutely provides for.

The paper, “Evidence Regarding Vitamin D and Risk of COVID-19 and Its Severity,” published in the journal Nutrients, was coauthored by William Grant, Ph.D., and Dr. Carol Wagner, both of whom are part of the GrassrootsHealth expert vitamin D panel.

As noted in that paper, dark skin color, increased age, pre-existing chronic conditions and vitamin D deficiency are all features of severe COVID disease, and of these, vitamin D deficiency is the only factor that is modifiable. As such, it would be foolish to ignore, especially since vitamin D supplements are readily available and low cost.

Christmas Eve 2020, attorney general Letitia James sent us a cease and desist notice, demanding we stop sharing information about how immune-boosting nutritional supplements might lower your risk of COVID, including vitamin D, zinc, NAC and vitamin C.

After the new presidential administration took over, on February 18, 2021, the Rockefeller-funded CSPI and AG James got their wish, as the FDA sent us a warning letter for “Unapproved and Misbranded Products Related to Coronavirus Disease 2019.”

Laurie even publicly bragged

about his ability to influence the FDA to take action against us.

The FDA’s letter highlighted statements in articles on my website that were fully referenced and supported by published science, and none of the articles cited had any commercial advertising linking the information to my products, as per the law. We had done nothing illegal or irregular in that regard, and my professional opinions are protected under the U.S. Constitution.

Needless to say, we fully addressed both James’ cease and desist notice and the FDA’s warning letter, putting them both on notice that they cannot censor protected speech simply because they don’t like what’s being said.

On a side note, William Correll, the director of the Office of Compliance at the FDA who signed the warning letter, sadly “passed away suddenly” just two months later, on April 18 “after a short battle with COVID-19.”

The agrochemical front group Cornell Alliance for Science (CAS),

the primary funding for which comes from the Bill & Melinda Gates Foundation,

also jumped on the bandwagon, falsely stating

that “pages advertising vitamin C and quercetin as having ‘synergistic effects that make them useful in the prevention and early at-home treatment of COVID-19′” were still available on my website nearly a month after the FDA’s warning letter.

To be clear, we had fully referenced scientific news articles. News articles are NOT “advertising,” as they do not link to any specific products, nor do they refer to or recommend any specific brands. In the case of the warning for vitamin C, the article discussed hospitals utilizing IV vitamin C for the treatment of COVID-19 and sepsis.

Such coordinated attacks are to be expected, though, considering Gates’ influence over the operation, and seeing how CAS and CSPI work closely together — a fact CAS admitted in its hit piece.

Around that same time (February 11, 2021), my book “The Truth About COVID-19” also went up for presale, and by early March, booksellers in the U.S., U.K. and Australia were being pressured not to sell it, or to add some sort of misinformation warning label to it. As reported by Sky News March 5, 2021:

“In the UK, more than 20 million vaccine doses have been administered as part of efforts to defeat COVID-19, but worries continue that misinformation is stopping some people from having the jab. Shadow health minister Alex Norris told Sky News:

‘Getting our population vaccinated is a massive priority and it is very sad to see these things so freely available. We would hope that retailers would act responsibly and have a look at whether they want to be associated with such products and whether they want to be seen to be profiting off such products.'”

March 3, 2021, the Center for Countering Digital Hate (CCDH) — a shady U.K.-based organization with anonymous funding led by Imran Ahmed — also got in on the action, publishing a hit list

of the “Top 10 anti-vaxxers” it wanted permanently silenced and eradicated from public forums. The list showed, by way of crossing out names, which had already been successfully deplatformed, and from which social media.

While precious little was (and still is) know about the CCDH, some digging revealed Ahmed had been appointed to the steering committee of the U.K. government’s Commission on Countering Extremism Pilot Task Force in April 2020, just as fearmongering about the COVID-19 pandemic was ramping up. The CCDH is also linked to a number of technocratic centers within the globalist network through its board members.

A couple of weeks later (March 15), Ahmed somehow managed to get an article titled “Dismantling the Anti-Vaxx Industry”

published in the journal Nature Medicine. In it, Ahmed lied, claiming he’d “recorded a private, three-day meeting of the world’s most prominent anti-vaxxers,” when in fact it was a public, international conference given online, attended by thousands around the world, all of whom had access to the recordings.

He could have done the normal, ethical and truly journalistic thing and admitted he simply attended a public virtual conference, but instead he twisted it into some risky undercover agent mission where he secretly recorded private discussions that revealed the inner workings of “the opposition.”

Then, March 21, 2021, the CCDH published the fabricated “Disinformation Dozen” report,

in which Ahmed falsely claimed 12 people and/or organizations, including yours truly, were responsible for 65% of all anti-vaccine content on social media.

March 24, 2021, 12 attorneys general sent a letter

to the CEOs of Twitter and Facebook, seeking their “cooperation in curtailing the dissemination” of COVID jab “misinformation” — all based on the fabrications of the CCDH. According to the AGs:

“The people and groups spreading falsehoods and misleading Americans about the safety of coronavirus vaccines are threatening the health of our communities, slowing progress in getting our residents protected from the virus, and undermining economic recovery in our states.

As safe and effective vaccines become available, the end of this pandemic is in sight. This end, however, depends on the widespread acceptance of these vaccines as safe and effective. Unfortunately, misinformation disseminated via your platforms has increased vaccine hesitancy …

According to a recent report by the Center for Countering Digital Hate, so-called ‘anti-vaxxer’ accounts on Facebook, YouTube, Instagram and Twitter reach more than 59 million followers … Given ‘anti-vaxxers’ reliance on your platforms, you are uniquely positioned to prevent the spread of misinformation about coronavirus vaccines …”

August 18, 2021, after conducting an internal investigation, Monika Bickert, vice president of Facebook content policy, publicly called out the falsehoods in “The Disinformation Dozen” report, stating:

“In recent weeks, there has been a debate about whether the global problem of COVID-19 vaccine misinformation can be solved simply by removing 12 people from social media platforms. People who have advanced this narrative contend that these 12 people are responsible for 73% of online vaccine misinformation on Facebook.

There isn’t any evidence to support this claim … In fact, these 12 people are responsible for about just 0.05% of all views of vaccine-related content on Facebook. This includes all vaccine-related posts they’ve shared, whether true or false, as well as URLs associated with these people.”

Bickert highlighted the fact that Ahmed had preselected the 12 individuals listed in the report, and that his “faulty narrative” was based on nothing more than “a narrow set of 483 pieces of content over six weeks from only 30 groups, some of which are as small as 2,500 users.”

“Further, there is no explanation for how the organization behind the report identified the content they describe as ‘anti-vax’ or how they chose the 30 groups they included in their analysis,” Bickert noted. “There is no justification for their claim that their data constitute a ‘representative sample’ of the content shared across our apps.”

Apparently, no one in government was smart enough to see the flaws in the CCDH’s report though, and a long list of officials cited the CCDH’s fabricated claims throughout the remainder of 2021, even long after Facebook denounced its claims. What’s more, even though Facebook admitted the CCDH’s claims were bogus, they still took action against accounts by applying penalties and/or bans.

April 8, 2021, attorneys general James and William Tong published an op-ed in The Washington Post,

again calling on social media companies to ban the “disinformation dozen” identified by the CCDH. The lack of acceptance of novel gene therapy technology, they claimed, was all because a small group of individuals with a social media presence — myself included — were successfully misleading the public with lies about nonexistent vaccine risks.

April 27, 2021, Dr. Peter Hotez, president of the Sabin Vaccine Institute

— which has received tens of millions of dollars from the Bill & Melinda Gates Foundation,

— escalated the threat even further in an article published in the journal Nature.

Citing the CCDH’s findings, Hotez called for cyberwarfare experts to be enlisted in the war against vaccine safety advocates and people who are “vaccine hesitant.” He wrote:

“Accurate, targeted counter-messaging from the global health community is important but insufficient, as is public pressure on social-media companies. The United Nations and the highest levels of government must … move to dismantle anti-vaccine groups in the United States.

Efforts must expand into the realm of cyber security, law enforcement, public education and international relations. A high-level inter-agency task force reporting to the UN secretary-general could assess the full impact of anti-vaccine aggression, and propose tough, balanced measures.

The task force should include experts who have tackled complex global threats such as terrorism, cyber attacks and nuclear armament, because anti-science is now approaching similar levels of peril. It is becoming increasingly clear that advancing immunization requires a counteroffensive.”

In short, Hotez called for the use of warfare tactics on law abiding American citizens, and the Nature journal actually published this blatant threat. One day later, April 28, the CCDH published a second report, “Disinformation Dozen: The Sequel,”

which focused on Big Tech’s failure to get rid of us “despite bipartisan calls from Congress.”

To understand the massive reach the CCDH gained, despite no one having heard of them before COVID, consider this: By the end of August 2021, there were 84,700 Google search results for CCDH’s defamatory phrase “disinformation dozen,” including 16,000 news stories in the international press, nearly all of which parroted the CCDH’s defamatory statements verbatim and reported them as fact.

Shortly after the op-ed by AGs James and Tong appeared, our business bank accounts were abruptly shut down and our credit cards canceled. Our business partners also had their PayPal accounts shut down.

This new threat, which I could not defend against in a court of law, led to my May 4 decision to remove all articles related to vitamin D, vitamin C, zinc and COVID-19 from my website.

In mid-July 2021, the White House stepped in to pressure Facebook to purge “anti-vaxxers” from its platform. Then-press secretary Jen Psaki regurgitated the CCDH’s false claims, saying:

“There’s about 12 people who are producing 65% of anti-vaccine misinformation on social media platforms. All of them remain active on Facebook, despite some even being banned on other platforms, including ones that Facebook owns.

Facebook needs to move more quickly to remove harmful, violative posts. Posts that would be within their policy for removal often remain up for days, and that’s too long. The information spreads too quickly.”

In another mid-July press conference, President Joe Biden himself demanded social media take action against “the disinformation dozen,” claiming our “misinformation” was “killing people.”

None of these officials ever questioned the authority of the CCDH. Facebook spokesperson Dani Lever responded to the White House’s demands, saying:

“We will not be distracted by accusations which aren’t supported by the facts. The fact is that more than 2 billion people have viewed authoritative information about COVID-19 and vaccines on Facebook, which is more than any other place on the internet … The facts show that Facebook is helping save lives. Period.”

July 24, 2021, The New York Times named me the No. 1 superspreader of COVID misinformation online.

According to the NYT itself, this was the most-read article of the year up to that point. Penned by Sheera Frenkel, it was so littered with blatant lies, my attorneys sent her a retraction demand.

For example, she claimed the FDA has levied multimillion-dollar fines against me. This is a complete fabrication, as I’ve never been fined by the FDA. She also implied that I misrepresented myself as a published author of a paper on vitamin D for COVID-19, stating she was “unable to verify” my claim. This despite being given a direct link to the paper! My paper can also be located on PubMed.gov in seconds by searching my name.

Frenkel boldly claimed that I am the No.1 spreader of misinformation online, but she didn’t even qualify what “misinformation” actually is. Without qualifying what it is you’re looking for, how can you quantify it? She also provided no proof that I in fact had the greatest reach of all the individuals reporting on COVID injections. My name didn’t even show up in the Top 15 in a Crowdtangle search for anti-vax Facebook posts.

Frenkel’s hit piece was followed up by CNN, which August 4 aired a segment show CNN reporter Randi Kaye stalking me across central Florida. And, of course, Kaye’s primary citation for her accusations against me was the CCDH.

August 4, 2021, I also implemented yet another change on my website. I had already removed all articles relating to COVID-19 and vitamin D. At this point, I deleted over 15,000 articles from the past 20-plus years from my website as the business and personal threats grew out of hand.

After 48 hours, articles were instead migrated over to Substack, where only paid members through a private membership agreement have access to them. This was a painful but necessary workaround, as the paid subscription provides a layer of protection against these threats.

September 9, 2021, U.S. Sen. Elizabeth Warren sent a letter

to Andy Jassy, chief executive officer of Amazon.com, demanding an “immediate review” of Amazon’s algorithms to weed out books peddling “COVID misinformation.”

While she didn’t spell out what laws Amazon might be breaking, she warned Jassy that the company may be held legally responsible for wrongful death and homicide by selling books that “misinform” readers about COVID-19, and she specifically singled out “The Truth About COVID-19” as a prime example of the kinds of books she wanted banned.

Warren again relied on the fabrications of the CCDH, even though Facebook had refuted the CCDH report as baseless three weeks before she sent that letter.

“Dr. Mercola has been described as ‘the most influential spreader of coronavirus misinformation online,'” Warren wrote, adding: “Not only was this book the top result when searching either ‘COVID-19’ or ‘vaccine’ in the categories of ‘All Departments’ and ‘Books’; it was tagged as a ‘Best Seller’ by Amazon and the ‘#1 Best Seller’ in the ‘Political Freedom’ category.

The book perpetuates dangerous conspiracies about COVID-19 and false and misleading information about vaccines. It asserts that vitamin C, vitamin D and quercetin … can prevent COVID-19 infection … And the book contends that vaccines cannot be trusted, when study after study has demonstrated the overwhelming effectiveness and safety of COVID-19 vaccines.

It should come as no surprise that the book is rife with misinformation. One of the authors, Dr. Mercola, is one of the ‘Disinformation Dozen,’ a group responsible for 65% of anti-vaccine content on Facebook and Twitter …”

Warren’s attempt at getting Amazon to ban my book was swiftly followed up by YouTube, which deleted my account September 29, 2021, allegedly for violating community guidelines. The problem was, they’d published and implemented those new guidelines that very morning.

While I disagreed with YouTube’s censorship, when its “COVID-19 misinformation” policy was implemented back in April 2021, I carefully avoided posting any content on YouTube that might violate that guideline. At no point had I ever received a violation notice from YouTube.

On the morning of September 29, 2022, at 9 a.m. EDT, The Washington Post published an article titled “YouTube Is Banning Joseph Mercola and a Handful of Other Anti-Vaccine Activists.” According to the WaPo:

“YouTube is taking down several video channels associated with high-profile anti-vaccine activists including Joseph Mercola … As part of a new set of policies aimed at cutting down on anti-vaccine content on the Google-owned site, YouTube will ban any videos that claim that commonly used vaccines approved by health authorities are ineffective or dangerous.

The company previously blocked videos that made those claims about coronavirus vaccines, but not ones for other vaccines like those for measles or chickenpox.”

In short, as of September 29, 2021, you could no longer post any video discussing or stating that anyvaccine is dangerous or ineffective. Six minutes after the publication of that WaPo article, I received an email from YouTube informing me that my entire channel had been deplatformed, having been found in violation of this new policy.

October 4, 2021, two months to the day after their first attempted hit piece against my book, “The Truth About COVID-19,” CNN aired a follow-up in which they echoed Warren’s call for Amazon to ban the sale of my book.

Like something straight out of George Orwell’s “1984” newsspeak dictionary, CNN host Anderson Cooper said my book is loaded with “mistruths” about COVID. Yet he failed to present a single piece of evidence to back up that claim.

This is one of the oldest propaganda trick in the book. If you just spew out enough derogatory terms about your opponent, people will forget the fact that you provided zero proof to back up your position.

November 7, 2021, just over a year after Warren tried to get my best-selling book “The Truth About COVID-19” banned from Amazon, I, my coauthor Ronnie Cummins, my publisher and Robert F. Kennedy Jr., who wrote our foreword, sued Warren,

both in her official and personal capacities, for violating our First Amendment rights and scaring book sellers into pulling and/or suppressing sales.

As a government official, it is illegal for her violate the U.S. Constitution, and pressuring private businesses to do it for her is not a legal workaround.

In February 2022, former National Institutes of Health director Dr. Francis Collins blamed me personally for the government’s inability to bring the COVID pandemic to a close. This despite the fact that I was by then heavily censored just about everywhere. The only people, really, who could see my information were those who subscribed to my newsletter and received it by email.

Fast-forward to August 2022, The New York Times published the documentary “Superspreader,” featuring yours truly, on FX and Hulu (both of which are owned by Disney). They clearly went through a lot of trouble, trying to dig up dirt from anyone they could find from my past — some going back 40 years, to my medical school days — who would be able to share some tidbit with which they could discredit me with.

But it seems they came up empty handed: After a year of investigation, they couldn’t come up with anything. Surprisingly, they even showed two people who claimed I’d saved their lives. All the other interviews were with people who don’t actually know me. One was with a Chicago journalist who interviewed me once — 13 years ago. Two classmates from med school, whom I haven’t seen in over 40 years, also described their impressions.

Ironically, yet again, just one week before the “Superspreader” program aired, the U.S. Centers for Disease Control and Prevention reversed all of its COVID-19 guidelines, thereby proving my position on COVID was correct all along. Of course, this was never mentioned in their program though.

Next up was a cyberattack that took down my entire website and destroyed our servers. Cyberattacks have been ongoing for the past six years, but the one that took place September 23, 2022, finally got through our defenses. By that time, my reach on social media had been throttled back to next to nothing, and my website was about the only place you could find my articles (with the exception of republications, which I allowed).

Warren isn’t the only one I’ve had to sue to protect my First Amendment right. In September 28, 2022, I also filed a lawsuit

against Google, YouTube and Alphabet Inc. for breach of contract.

As detailed in my complaint, YouTube unilaterally amended the contract without notice, which is a violation of its own terms of service, and then used this last-minute amendment to justify removing my content, which went back to 2005, the same year YouTube was founded. At the time YouTube deleted my content, I had more than 300,000 subscribers, and my videos had collectively garnered more than 50 million views.

The WaPo article was embargoed until the morning of September 29 in order to prevent me (and anyone else affected by this change) from reviewing the new policy, take steps to bring my channel into compliance, or move my content to another platform. Instead, they simply deleted 16 years’ worth of intellectual property, without warning.

This is a clear violation of its own terms of service, which state that YouTube “will provide reasonable advance notice” of any changes to the terms of service, and that users will have “the opportunity to review them” and to remove content if they do not agree to the new terms.

YouTube’s terms of service also include a “three strikes” policy, where users are given three warnings and opportunities to remove content that violates the guidelines before being banned. I had no “strikes” against my channel on the day I was deplatformed and deleted.

I’m also suing YouTube for unjust enrichment, as for the last 16 years, my video content, having generated in excess of 50 million views, has been of great financial benefit to YouTube, allowing them to increase advertising revenue on the site. Additionally, they’ve refused to allow me to retrieve any of this content, which they still have in their possession. So, YouTube has unjustly benefited at my expense.

January 10, 2023, I, along with several other plaintiffs, also filed a lawsuit

against The Washington Post, the BBC, the Associated Press and Reuters — also known as the Trusted News Initiative (TNI),

a self-appointed Pharma and Big Tech industry partner that has spent the past couple years playing judge and jury of news.

It has been doing everything it can to censor what it doesn’t want the public to hear. As noted in the complaint, the TNI has not only censored free speech, it has also engaged in antitrust activity. Specifically, “Federal antitrust law has its own name for this kind of ‘industry partnership’: it’s called a ‘group boycott’ and is a per se violation of the Sherman Act.”

As evidence of this allegation, our complaint references multiple public statements by TNI partners, including a March 2022 statement by Jamie Angus, then-senior news controller for BBC News, who explained TNI’s “strategy to beat disinformation.”

The globalist cabal is extremely coordinated, as you can see. What’s more, they play dirty. But we will not give up, nor give in. Our freedom is far too precious for that, and freedom depends on getting the truth out. So, I will continue doing my part. You can help by sharing articles you think are important with family and friends, in whatever ways are available.

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Can Intermittent Fasting Change How Your DNA Works?

  • A 2023 animal study showed how limiting food to the hours of the day when you are most active may alter up to 80% of genetic expression in multiple organ systems

  • Activation of these pathways may help explain how fasting improves health and longevity. Roughly 40% of genetic expression in the hypothalamus, pancreas and adrenal glands was affected, which may affect hormone regulation

  • Data show restricted eating patterns have a neuroprotective effect and are associated with better cognitive and heart health; data also find it reduces the ability of cancer cells to adapt and survive and may help improve the effectiveness of cancer treatments

  • Fasting promotes pancreatic beta-cell growth in animal studies, which may be another pathway in which it helps markedly improve blood sugar control and affect metabolic health

  • Most people find it easier to skip breakfast instead of dinner to limit the number of hours they consume food, but take care to restrict eating at least three hours before bed. Skipping breakfast before your workout may offer additional benefits throughout the day

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Obesity rates are climbing, along with associated health conditions, such as Type 2 diabetes, metabolic syndrome and cardiovascular disease. According to the CDC,

the rate of obesity in adults rose from 30.5% in 1999-2000 to 41.9% in 2017-2020, and the estimated annual medical costs were $173 billion in 2019 dollars.

There are a variety of reasons that contribute to these rising numbers, including a sedentary lifestyle,

increased consumption of highly processed food,

medications

and psychological triggers.

One beneficial strategy to lower weight gain and improve insulin resistance associated with obesity and Type 2 diabetes is intermittent fasting. A 2023 animal study

demonstrated that restricted feeding schedules affected 80% of how genes were expressed.

Resistance to insulin and leptin signaling drives your blood glucose level high, which is a hallmark symptom of Type 2 diabetes. Conventional medicine treats the symptoms of the condition, which is in fact preventable and in most cases reversible by simply changing your diet and lifestyle habits.

A significant risk factor for insulin resistance is overeating carbohydrates and added sugars, which spike your insulin level and gradually increase cellular resistance to insulin. Overeating carbohydrates and sugar are the primary causes of obesity.

The featured animal study in Cell Metabolism helps explain how fasting benefits these health conditions. Shaunak Deota is the first author of the study and a postdoctoral fellow at the Salk Institute for Biological Studies in San Diego. He is encouraged by the data, saying:

“Molecularly speaking, we saw a lot of pathways which are activated by (the time-restricted diet) in multiple organ systems. And a lot of these pathways actually have been implicated in improving health and leading to a longer, healthy life.”

The results from the 2023 study demonstrated that it’s not only about what you eat, but also about when you eat it. The researchers tested time-restricted feeding in mice. Deota defined the researcher’s use of the term “time-restricted feeding” as “eating consistently in a narrow window of eight to 10 hours”

when a person or animal is most active and fasting during the rest of the day.

Intermittent fasting is one form of time-restricted feeding according to the definitions used by the researchers. The researchers placed two groups of mice on the same high-calorie diet. One group was allowed to eat only during a nine-hour window and the other had free access to food whenever they wanted it.

The researchers found that after seven weeks, the time-restricted fed animals gained less weight than the other group and biopsies showed that the genetic expression of the mice in the intervention group was synchronized to their feeding schedules.

Interestingly, the paper reported that nearly 80% of the animal’s “genes show differential expression or rhythmicity under TRF [time restricted feeding] in at least one tissue.”

Deota explained the importance of this finding, saying, “… these genes will get translated into proteins. Those proteins are helping our body to anticipate that there is food coming.”

The data from the study supports past research that demonstrated the benefits of restricting the number of hours during the day in which you’re allowed to eat. This has included increasing lifespan in animal studies.

The featured study sought to determine how fasting affects multiple organ systems and genetic expression.

The researchers looked at more than 22 areas of the body and brain, finding that by changing what time food was given, the genetic expression in an animal’s body could also be changed. Time-restricted feeding affected nearly 40% of genetic expression in the pancreas, hypothalamus and adrenal glands. This in turn may affect hormone regulation.

It is possible that since hormones coordinate functions throughout the body, and hormonal imbalance is associated with many diseases, fasting may help to improve health along several pathways. The researchers also found that restricting food supply to the most active time of the day helped align circadian rhythms in multiple organ systems. Satchidananda Panda, Ph.D., from the Salk Institute and senior writer of the study, told World Pharma News:

“Circadian rhythms are everywhere in every cell. We found that time-restricted eating synchronized the circadian rhythms to have two major waves: one during fasting, and another just after eating. We suspect this allows the body to coordinate different processes.”

In this short three-minute clip from BBC studios, Michael Mosley discusses the effects of feast or famine feeding with professor Mark Mattson from the National Institute on Aging. Mattson describes the results of their intervention with mice in relation to cognitive impairment and memory loss.

The researchers used mice that were bred to develop Alzheimer-type symptoms. Mattson described one study in which one group was offered food intermittently and the others were fed a diet that resembled fast food. The group that ate intermittently lived significantly longer without memory impairment, in one study by six months to one year. Mosley notes that this is the difference in human life between developing Alzheimer’s at age 50 or age 80.

Researchers have also noted that eating a high-fat, low-carbohydrate diet has a fasting-like effect on the body and the brain.

During fat metabolism, ketone bodies are produced which have a neuroprotective impact on the brain. This could help enhance mitochondrial function and reduce inflammation.

Eating a high-fat diet has been analyzed as a potential adjunctive therapy for neurodegenerative conditions, like Alzheimer’s disease. One paper

reported that some studies have shown modest functional improvement in people with Parkinson’s disease and cognitive benefits in people with Alzheimer’s disease.

Limiting the hours of the day in which you eat also has a beneficial effect on your cardiovascular system. One paper

theorized that the effect may be exhibited through multiple pathways, including optimizing your circadian rhythms and reducing oxidative stress.

An umbrella review

of 11 meta-analyses totaling 130 random controlled trials found a beneficial association between intermittent fasting and cardiometabolic outcomes that was supported by moderate to high-quality evidence. Fasting has also been shown to have a pronounced impact on longevity.

One narrative review of the literature

summarized the impact of restricting calories and protein, and the effect on biomarkers of healthy aging. They predicted that periodic use of low-calorie, fasting-mimicking diets (FMD) and low protein intake could promote health benefits while minimizing the difficulty associated with chronic calorie restriction.

Researchers have also discovered that an FMD influences growth factors and reduces the capacity of cancer cells to adapt and survive. They propose that “combining an FMD with chemotherapy or other cancer treatments is a promising strategy to increase treatment efficacy, prevent resistance acquisition and reduce side effects.”

Research has demonstrated that fasting can improve insulin sensitivity,

reverse Type 2 diabetes

and support your weight management efforts when it’s combined with exercise.

Interestingly, an editorial in the BMJ

by noted research scientist James DiNicolantonio, Pharm.D., discusses the results of several studies that found repeated episodes of fasting may induce cell growth of pancreatic beta cells in an animal model.

The growth was associated with an increased expression of Ngn3,

a protein involved in converting DNA into RNA critical for endocrine cells in the pancreatic islet of Langerhans, the cells responsible for producing insulin. The increase in islet beta cells induced through intermittent fasting was accompanied by a marked improvement in blood sugar control in the animal studies.

This observation is of great interest to individuals who suffer from Type 1 diabetes since they often experience near-complete inflammatory destruction of the islet beta cells. In the latter stages of severe Type 2 diabetes, the same destruction of islet of beta cells can occur.

DiNicolantonio believes these findings may be replicated clinically, which opens the path to reversing Type 2 diabetes in those with “enough discipline and commitment to adopt a lifestyle that would have prevented diabetes in the first place.”

He first recommends practicing a diabetes-preventive lifestyle by eating a diet primarily of whole foods and complemented with regular exercise. This helps to improve insulin sensitivity and may be sufficient for those with a recent diagnosis of diabetes to reduce their condition over time.

In those who fail to respond, he recommends an intermittent fasting protocol and using supplemental measures during the transition back to a health-protective diet to shield the beta cells from toxicity so they retain functional capacity. Reducing oxidative stress may be accomplished using spirulina, NAC and or berberine.

The goal is to achieve normal blood sugar control without drugs and maintain compliance with a diabetic preventive diet and lifestyle.

For many people, restricting food intake to the hours between lunch and dinner feels easier than skipping dinner. A 2019 study

in The Journal of Nutrition found that omitting a meal before your workout increases the effectiveness of your weight loss efforts. Researchers enrolled 12 healthy, physically active young men who completed all three stages of the study in a randomized order separated by over one week.

During the first stage, the men ate a breakfast of oats and milk followed by rest. In the second stage, they ate the same breakfast and then exercised for 60 minutes, and during the third stage, they fasted overnight and exercised in the morning before eating. The researchers then monitored the following 24 hours of calorie intake.

They found that those who fasted and then exercised had a negative 400-calorie intake during the following 24 hours as compared to those who ate and rested or those who ate breakfast before exercising. Javier Gonzalez, Ph.D., from the University of Bath, oversaw the study and suggested working out on an empty stomach will not likely trigger overeating but, instead, may lead to a calorie deficit.

The study was limited in that there was a small number of participants who were all fit young men. There is some question if those results would be comparable in a group of older, overweight, out-of-shape or female participants. The data could not explain why the men who skipped eating before exercise did not continue to eat the rest of the day. Gonzalez hopes to continue work to study these questions.

While it may be easier to skip breakfast as you practice intermittent fasting, it’s also necessary to avoid eating at least three hours before bed. For most Americans, the evening meal is often the largest of the day and usually consists of heavily processed foods. Under the best of circumstances, it takes your stomach several hours to empty after you’ve eaten.

However, as you age, the process can take even longer. As you lie down to sleep, this increases the risk that acid can enter your esophagus and lead to acid reflux. Even if you do not have heartburn, symptoms like hoarseness, chronic throat clearing and even asthma can indicate acid reflux. Additionally, as the featured study demonstrates, eating outside of your most active times of the day can throw off your body’s circadian rhythm.

This in turn has a detrimental effect on your mitochondria as they are “highly regulated by the body’s biological, or circadian, clocks.”

As described in an article in Neuroscience News, offsetting your circadian clock increases your risk of developing metabolic syndrome, obesity and diabetes.

In a follow-up paper,

the same researcher describes how the circadian clocks in your cells respond to a variety of metabolic cues and play a principal role in metabolic control. In the review of the literature, he finds diurnal changes affect mitochondrial biology in mammals. Dysfunction of these little powerhouses located in most of your body cells is a foundational cause of many degenerative diseases.

When the mitochondria receive inappropriate amounts of fuel at the wrong time of the day they can deteriorate and malfunction, laying the groundwork for the subsequent breakdown in a variety of bodily symptoms. As a featured study shows, you can take control of your health through fasting. It is a profoundly effective intervention that can help stimulate mitochondrial biosynthesis.

It is important to understand that as you’re fasting, you may experience symptoms of low salt intake and your body will automatically begin to liberate toxins from your fat stores. It’s recommended to consume some high-quality unprocessed salt each day and use an infrared sauna to help your body rid itself of these toxins.

Binders like modified citrus pectin, cilantro, chlorella or activated charcoal can help eliminate these toxins as well, and prevent their reabsorption. Although it’s highly beneficial for most, fasting is not for everyone. You should not do any type of extended fasting if you’re underweight, pregnant, breastfeeding or have an eating disorder.

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Disclaimer: The entire contents of this website are based upon the opinions of Dr. Mercola, unless otherwise noted. Individual articles are based upon the opinions of the respective author, who retains copyright as marked.

The information on this website is not intended to replace a one-on-one relationship with a qualified health care professional and is not intended as medical advice. It is intended as a sharing of knowledge and information from the research and experience of Dr. Mercola and his community. Dr. Mercola encourages you to make your own health care decisions based upon your research and in partnership with a qualified health care professional. The subscription fee being requested is for access to the articles and information posted on this site, and is not being paid for any individual medical advice.

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Asafoetida: Why This Stinky Herb Is so Beneficial

  • The Indian cooking spice asafoetida is a gum obtained from a type of giant fennel. It has an offensive smell akin to that of rotting garlic and sweaty feet, but an appetizing savory, umami taste

  • With its onion-garlic flavor, you can use it as a substitute for either of those ingredients. Many recommend using it in bean-based dishes, as it helps prevent gassiness

  • Asafoetida has antibacterial, antiparasitic and antiviral properties. In 2009, researchers discovered certain compounds in the herb were more effective at killing the H1N1 influenza virus than the commercial antiviral drug amantadine

  • Asafoetida also has antispasmodic, carminative, expectorant, laxative and sedative properties, just to name a few. Historical uses include the treatment of nervous conditions, bronchitis, asthma, whooping cough and more

  • This smelly herb can also be useful for the prevention and treatment of various gut ailments, and for feminine health issues such as sterility, premature labor, painful and excessive menstruation and leucorrhoea

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The Indian cooking spice asafoetida

— a name that translates into “rotten resin”

— also known as hing, hingu

or heeng,

is a gum obtained from a type of giant fennel. It has an offensive smell akin to that of rotting garlic and sweaty feet, but an appetizing savory, umami taste. In France, the herb is known as devil’s dung.

According to GoodFood.com,

Jain and Brahmin Indians have long used it in lieu of garlic and onions. It’s also popular among those in whom onions cause digestive trouble.

While it is sometimes possible to locate asafoetida in its raw gum form, it’s most commonly sold as a ground powder mixed with flour, starch or turmeric. This is likely a good thing, as eating it raw can cause severe diarrhea and/or vomiting.

It has a very strong odor and should be used in very small amounts. As noted by GoodFood.com:

“Once a container of asafoetida has been opened it’s best to close it as soon as possible. Then, keep it hermetically sealed in an airtight plastic container, or double wrapped — at least. If the aroma escapes you will awake to find a house reeking of yesterday’s garlic …

Generally, the yellow, diluted asafoetida powder is used in about the proportion of a pinch or two to 250g of the main ingredient … longer cooking mellows it …

Asafoetida works best when first fried for five to ten seconds in hot oil until its pungency is dramatically obvious — make sure you have the extractor on or the window open. Then quickly add other ingredients to stop it burning.”

With its onion-garlic flavor, you can use it as a substitute for either of those ingredients. Many recommend using it in bean-based dishes, as it helps prevent gassiness.

Its ability to cut gas is attributed to antibacterial compounds that impede the activity of gut bacteria responsible for flatulence.

It also has a number of other health benefits,

including antibacterial, antiparasitic and antiviral properties.

In 2009, researchers discovered certain compounds in the herb were more effective at killing the H1N1 influenza virus than the commercial antiviral drug amantadine.

Another study

found the ferulic acid in asafoetida has the ability to control fascioliasis,

a zoonotic liver disease (meaning it can spread between animals and people) caused by eating watercress or other water plants contaminated with Fasciola hepatica and/or Fasciola gigantica.

According to a paper

in the Pharmacognosy Review, asafoetida also has antispasmodic, carminative, expectorant, laxative and sedative properties, just to name a few. Historical uses include the treatment of hysteria, nervous conditions, bronchitis, asthma, whooping cough, infantile pneumonia and flatulent colic.

According to the Pharmacognosy Review paper, it’s particularly beneficial for asthma, thanks to volatile oils that are eliminated through the lungs. It’s also been shown to work as a natural blood thinner and helps lower blood pressure. In traditional medicine in India, the herb is taken to help break up and eliminate kidney stones and gallstones.

Historically, it has also been used as an antidote to opium. According to the Pharmacognosy Review, “Given in the same quantity as opium ingested by the patient, it will counteract the effect of the drug.”

Asafoetida also contains a number of chemicals shown to have anti-inflammatory, anticancer and antimutagenic activities.

As reported in the Pharmacognosy Review:

“Dried resin, administered orally to Sprague–Dawley rats at doses of 1.25 and 2.5% w/w of the diet, produced a significant reduction in the multiplicity and size of palpable N-methyl-N-nitrosourea-induced mammary tumors, and a delay in mean latency period of tumor appearance.

Oral administration to mice increased the percentage of life span by 52.9%. Intraperitoneal administration did not produce any significant reduction in tumor growth.

The extract also inhibited a two-stage chemical carcinogenesis induced by 7,12-dimethylbenzathracene and croton oil on mice skin with significant reduction in papilloma formation.”

Similarly, a study

published in the Journal of Ayurveda and Integrative Medicine in 2017 confirmed the asafoetida resin had antitumor effects against breast cancer. According to the authors:

“Our results showed that treatment with asafoetida was effective in decreasing the tumor weight and tumor volume in treated mice. Body weight significantly increased in female BALB/c mice against control.

Apart from the antitumor effect, asafoetida decreased lung, liver and kidney metastasis and also increased areas of necrosis in the tumor tissue respectively.”

Other studies

have also found the isolated ferulsinaic acid in asafoetida has life extending capability, increasing the mean life span of Caenorhabditis elegans by as much as 18.03%, and their maximum life span between 8.33% and 41.6%.

Improved heat stress tolerance and reductions in lipid peroxidation are thought to be responsible for this effect. According to the authors, “Ferulsinaic acid had therapeutic efficacy as an antioxidant with the possibility of its use as an antioxidant drug.”

Asafoetida may also be useful in the treatment of a variety of female health ailments, such as sterility, premature labor, painful and excessive menstruation and leucorrhoea.

The Pharmacognosy Review

suggests taking 12 centigrams of asafoetida gum fried in ghee with 120 grams of fresh goat’s milk and 1 tablespoon of honey, three times a day for four weeks, to increase secretion of progesterone, which can be helpful in these situations.

In male rats, asafoetida at doses between 25 and 200 mg/kg has been shown to significantly increase the number and viability of sperm, thus improving fertility.

Care must be used if you’re pregnant or planning to become pregnant,

however, as asafoetida also has the ability to prevent pregnancy and induce miscarriage. Antifertility effects have been noted in rats at a dosage of 400 mg/kg, preventing pregnancy in 80% of cases.

Breastfeeding women should also avoid asofoetida as it can be transferred via breast milk to their baby, in whom certain chemicals in the herb may contribute to certain blood disorders.

To treat colic, asafoetida is typically applied to the infant’s navel in the form of a paste, opposed to being ingested.

As mentioned, the herb has been shown to lower blood pressure, and appears to be quite effective at this, the Pharmacognosy Review notes.

One of the mechanisms responsible for this hypotensive effect is vasodilation. Tinctures and water extracts of dried gum resin has been shown to have a significant smooth muscle relaxant and anticoagulant effects.

Moreover, certain compounds appear to have the ability to inhibit acetylcholinesterase,

which means it may be useful against Alzheimer’s disease.

In animal trials, asafoetida at doses of 200 to 400 milligrams per kilo has also been shown to improve memory formation.

Another area in which this smelliest of herbs can be useful is for the prevention and treatment of various gut ailments. One study

looking at asafoetida’s effects on functional dyspepsia (FD), a chronic disorder of the upper digestive tract,

found it to be both safe and effective. As reported in this study:

“In the double-blinded, placebo-controlled study, 43 subjects diagnosed to have moderate to severe discomforts of nonulcer FD were randomized to receive hard-shell capsules (250 mg × 2/day) of either placebo or a food-grade formulation of asafoetida (Asafin) for 30 days.

When evaluated by a set of validated indexing tools … almost 81% in the Asafin group showed significant improvement in the overall score and quality of life as compared to the placebo. At the end of the study, 66% of subjects in the Asafin group remained symptoms-free.

Although the symptoms score improved significantly in both the groups … the relative percentage of subjects in the Asafin group with more than 80% reduction in various symptoms were: bloating (58%), appetite (69%), postprandial fullness (74%) motion sickness (75%), and digestion (77%) as compared to less than 10% nonspecific improvement in the placebo group.

All the subjects remained safe with no adverse events or variations in haematological and biochemical parameters.”

If the idea of smelling up your kitchen isn’t a deterrent, consider spicing up your meals with this medicinal herb.

In “Asafoetida Stinks, But It Helps the Cook,”

published in The Seattle Times, Monica Bhide details how to use it in cooking, and provides you with a recipe for savory cheesecake topped with red pepper and green tomatillo chutney to get you started.

Additional cooking tips can be found on NDTV’s Food Channel,

and a recipe for lemon-asafoetida water is given on netmeds.com.

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Disclaimer: The entire contents of this website are based upon the opinions of Dr. Mercola, unless otherwise noted. Individual articles are based upon the opinions of the respective author, who retains copyright as marked.

The information on this website is not intended to replace a one-on-one relationship with a qualified health care professional and is not intended as medical advice. It is intended as a sharing of knowledge and information from the research and experience of Dr. Mercola and his community. Dr. Mercola encourages you to make your own health care decisions based upon your research and in partnership with a qualified health care professional. The subscription fee being requested is for access to the articles and information posted on this site, and is not being paid for any individual medical advice.

If you are pregnant, nursing, taking medication, or have a medical condition, consult your health care professional before using products based on this content.

Britain, Again. Guilty as Charged.

 By Anna Von Reitz

Remember Lord Pirbright?  He was the man who brought the world its first Concentration Camp during the Boer War in Africa.  He was rewarded instead of being hung, so that just encouraged more of it. 
Yes, Concentration Camps were a British invention, not German. 
Adolph Hitler merely borrowed Pirbright’s original concept and employed it some decades later in Germany, Poland, and elsewhere.  The only difference is that the German camps were more efficient and overall, much cleaner. The Nazis offered latrines and sometimes, bedding, to their prisoners.  
Besides being the first Concentration Camps, the camps established during the Boer War boasted another “first”.  Pirbright experimented on his Dutch and African prisoners, injecting them with various substances in the name of medical science.  
Pirbright was a loathsome elitist and proponent of racial purity,  He also championed “eugenics” — the purported science of breeding better human stock, similar to breeding AKC dogs, and generally, treating people like animals.  
It should come as no surprise to anyone that the Pirbright Institute’s fingerprints are all over the origins of the present disastrous genocide. 
Despite their efforts being already outlawed when they began them, these criminals contrived to evade every form of law you can think of, every standard of decency that is customary, and imposed upon their El-ite Peers, (that is, Canaanite members of the Saturnine Brotherhood) who are not very bright, but are very evil and lacking a conscience, to support the mRNA “vaccine” pseudo-scientific medical profiteering scheme, for the sake of money.  Profits.  Just like Henry Kissinger said. 
There isn’t an actual scientist or mathematician among them, but it hardly matters, because they have been able to hire whores with credentials to lie for them and shift the data and misinterpret the data and tweak it however they liked. For a price. 
What they liked, what they have always liked, is the death and dismemberment of “inferiors” for profit.  By war, by disease, by injection — it hardly matters how, so long as people die and they profit from it.
I think it is now irrefutably proven who the inferiors among us really are, and despite their money, they are mentally inferior, morally inferior, and emotionally inferior in every way. 
Here’s one of them, Dr. Mylo Canderian of Pibright UK, under contract with the World Economic Forum and Pfizer, who should already be shoveling coal in Hell.  Take a good look at the Monster under the bed: 

Wouldn’t that give you nightmares, if you found it lurking in your closet?

Dr. Canderian openly claims that even if the mRNA experiment should fail to have the desired effect of reducing the world population by 90%, the poisons (prions, graphene, polyethylene glycol, CF clotting factors, heartworms and other goodies) injected along with it, will kill everyone who took the jab by 2030.  He more or less gleefully guarantees it. 
So, Vaxxed Folks, and Unvaxxed Friends and Family alike, you’ve got nothing to lose by getting organized in vast numbers and bringing all of them to justice, even if its rough justice.  
After all, they want to destroy the inferior and the weak-minded among us, don’t they?  And they have already proven who they are. They insist that the population needs to be culled, so why not begin with them? 
The original Lord Pirbright was the intellectual grandfather of a new generation of pundits like Margaret Sanger, who founded “Planned Parenthood” under the banner of social progress, and who secretly aimed at killing Negroes. 
She succeeded.  The disproportionate preponderance of abortions in this country and around the world are performed on black women.  
She only succeeded because she hid her agenda. Planned parenthood as a concept is preferrable to unplanned parenthood, but like everything else these monsters do, it was used as a “good” storefront to hide the evil agenda behind it. 
Just like the Roman Catholic Church has been used as a storefront, just as the United Nations Organization is being used as a storefront for the UN CORPORATION.  
To say that these Perpetrators are twisted would be an understatement, yet they have been rewarded by governments and left to spread their dangerous quasi-scientific lies for 130 years, without being recognized as criminals and sociopaths. So they have flourished, largely unobserved, like a giant weed hidden behind a rhubarb plant. 
Besides Sanger’s work, which has resulted in the death of millions upon millions of aborted babies, mostly black, brown, and Catholic babies, just as she planned, we have all suffered the idiocy of The Population Bomb, a 1968 book co-authored by Paul and Anne Ehrlich, two more of these cretins, living on the public dole at Stanford. 
Despite having advanced university degrees, neither Paul nor Anne Ehrlich can do math.  According to the Ehrlichs the Earth is a puny place that can’t support the billions of people now more or less successfully living upon it, and though they offer no strong proof of their premise, they nonetheless projected the idea that we would all be dead or eating dirt and straw by sometime in the 1980s. 
Obviously, Mother Nature proved them wrong, but that did not stop them. 
The Ehrlichs continued telling their Big Lie just the same, and bored rich people seeking a disaster to milk, have listened to them. Their nonsense has been used to fuel the whole depopulation agenda and resulted in the genocide of millions of people already.  
No doubt there is a special place in Hell reserved for them, among “all the Liars”.
Other murderous quasi-scientific boondoggles promoted by these cretins include fluoridation of the water, iron supplements, bleaching flour, GMO vegetables that produce their own pesticides (which we then consume along with the vegetable), patent medicines, depletion of atmospheric oxygen (and misrepresenting the results, increase of carbon dioxide, as the problem), Stone Age waste management, metered power grids, Global Cooling Hysteria and Global Warming Hysteria, both, and so much more. 
They are the sons and daughters of the Father of All Lies, and the descendants of Cain— the Canaanites.  It was with good cause that the True God told the Hebrews to destroy them.  They worship idols as a Death Cult and practice cannibalism and drug use and human sacrifice as part of their religion.  Any questions?  Imagine the fellow in the photograph above eating your daughter. 
All the nastiness in the world comes, originally, from Britain; it is always at the bottom of the dogpile, without exception, and here it is, again.  With or without being egged on by Rome, with or without various accomplices including the French, the Germans, the Israelis, and the traitor Tories in America— one thing remains the same: Britain as the instigator.
—————————-

See this article and over 3900 others on Anna’s website here: www.annavonreitz.com

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How you may be able to instantly show whether the vaccines are helpful or harmful

If the CDC was honest, this is what their new ads should look like!

The ratio analysis technique can be applied to death-vax records to instantly assess whether the vaccine shifted deaths to be earlier or later in the period under observation.

However, on its own, without additional data, unless the ratio is around .4 (the intervention moved deaths to be closer to the intervention point), it it cannot be used by itself to ascertain whether the intervention is helpful or harmful.

The bigger point is this: It’s interesting to note that nobody wants to actually publish the record-level death-vax data to prove the vaccines are safe and effective.

We are now over two years into the vaccination program and not only is nobody publishing the data that would prove or not that the vaccines are safe, but nobody is even asking for the data to be published.

It’s almost as if nobody wants to know the truth. That’s the big take away.

If we had the full vaccination records and linked death records for those who have died of a state, the debate would be over.

Nobody is calling for this data.

Instead, we are left with techniques such as this one which can give us educated guesses as to what is going on.

Define our database as anyone who died sometime in Jan 2021-Dec 2022

Let ratio=((sum of records of time in category)/(sum of records of time possible in category)) where time for both the numerator and denominator is measured from the intervention start point, e.g., date of first vax.

If there isn’t an external event that would cause people to die at an uneven rate throughout the period being considered (which we’ll see from the ratio for all death records), then we have:

  1. The intervention had no effect = .5 on the rate of events after the intervention time.

  2. The intervention caused more deaths in the short term than long term <.5

  3. The intervention caused more deaths in the long term than short term > .5

So this allows us to determine if an intervention is having an impact, but not necessarily whether it is harmful or beneficial!

The analysis is independent of the rates people die. The fact that older people die faster than younger people is immaterial. Pre-existing conditions, etc. do not matter.

Here are some examples:

  1. The vaccine uniformly increased the rate people are dying by 50%. In this case, the ratio is .5 because it UNIFORMLY shift the rate (up or down). Thus, the intervention could be strongly positive or strongly negative, but if it is uniform, we’d get a .5.

  2. The vaccine kills people in the near term at a higher rate than average —> <.5

  3. The vaccine kills people over time as people get more and more shots or as you get more and more blood clots —> >.5. This appears to be what is actually happening according to the statewide data I received.

  4. The vaccine saves you from dying from COVID for the first 12 months before wearing off —> >.5. This is a possible explanation but the direct anecdotes from large geriatric practices don’t support it.

  5. The vaccines are unlikely to be given to older people who are going to die very soon —> >.5 (only for older people and its a very small effect lasting a few days)

As you can see, it’s tricky. You need more than just this one statistic if the value is >.5 to disambiguate the cause. But if the value is <.5, it’s a pretty good bet that the vaccine is dangerous because the vaccine is supposed to reduce your death rate in the first year, not increase it.

One thing that is ruled out here is the healthy patient bias. If super healthy people are the only ones vaccinated and they die at a lower rate, this does NOT affect the ratio since the ratio is effectively a self-controlled case study. So it’s a measure of the effectiveness of the intervention on the short and/or long term differential death rate.

Here is the data used in the analysis

The survey was announced here:

The start point can be any point that should be random with respect to the date of death.

So for example, a specific calendar date, the date of vax #N (a specific vax number), the date of the last full moon before the person died, etc. A start point that is dependent on the date of death such as “the date of the last vaccine given before the person died” would not work because it would be biased (e.g., think of the case where the vaccine was given every day until death).

To see if there is an effect, we look at the records associated with various intervention points: Dose 1, Dose 2, etc. For my current death survey, because I didn’t collect the dates of each dose, we are limited to the Dose 1 date for the intervention.

The control is to look at all the death records using quarterly start dates. This will allow us to estimate the statistical noise in the ratio given the various start points. So ideally, we look at Start dates by quarter for each quarter in 2021: Q1, Q2, Q3, and Q4 and also 2022: Q1.

There are always external events that have an uneven effect on mortality throughout the observation period.

The controls account for that variation. So if the Dose 1 data is < all the controls, that would be very strong evidence that the vaccines increased all-cause mortality.

The results from my survey data show the vaccine is causing more deaths in the short term (Dose #1 date) since the alternative explanation (saving lives in the longer term) is unlikely due to the method of action for the shot (which is to save lives in the shorter term):

This shows the numbers for choosing a start point of the date of the FIRST vaccine dose. Numbers <.5 generally mean the intervention is harmful.

The primary control: all deaths in the period regardless of vaccination status:

All death records. This shows that there were more deaths in 2022 which can be due to recall bias or the aggregate effect of all the vaccines. Individual medical practices report greater deaths in 2022 than 2021 so this is most likely explained as due to the vaccine.

What this shows is that the intervention (the vaccine) had lower numbers than the control, indicating the intervention (the vaccine) is harmful.

Lessons learn for future surveys:

  • Allow people to report as many records as they want

  • If they know vax details of several deaths, and don’t want to report all the deaths, pick the person with the last name that appears higher in the alphabet.

  • Tell us the number you are reporting

  • Tell us the number you knew about

  • Start date should be Dec 14, 2020 onwards

  • Proof of death (hyperlink to obit)

  • Proof of vaccination card link (hyperlink to card)

  • Get every vax date and brands used

  • Tell people to double check the dates are right (and use American style date format)

  • Have checkboxes for UK, Australia, New Zealand, Germany, France, and Canada

Even with those corrections, surveys will always have biases because the anti-vaxxers will hear about and learn more about deaths likely to be associated with the vaccine.

This is why I am waiting for state level data before making any conclusions. I now have that data. So these surveys are no longer needed.

It is troubling that record-level death-vax data is not available. This is by far the most important data we have to show whether the vaccines are helpful or harmful.

We should all be concerned that the data isn’t being made available and that the mainstream medical community has no interest in seeing this data.

Those facts alone should cause anyone with a working brain to demand transparency. Nobody should be taking any more shots or requiring or recommending people take the shots until the data is released and can be analyzed.

We have the record-level death-vax data. Why aren’t we making it publicly available?

See A worldwide call for data transparency: Show us the data!

Most people can stop reading here.

The novel time-ratio method in this paper is sound, but certain restrictions apply to the metric that was chosen that I was subsequently made aware of after talking with Norman Fenton and Clare Craig. I am grateful to them for pointing out the limitations.

The big error was using the “date of most recent vaccination” as the “intervention point.” This is biased and will give lower numbers as a result. You can pick anything that is random with respect to the death endpoint, but that point doesn’t qualify because it is dependent on the death endpoint. Here’s the simple reasoning for why “most recent vax” is a bad endpoint. Imagine if you were vaccinated every day… You’d always die exactly one day after your last vaccination!

So I could have picked vax #1 date, vax #2 date, vax #3 day, etc. date for an individual (which would vary for each person), an arbitrary day of the year (assuming nothing external is happening like a Delta surge), date of vax availability, etc. You just can’t pick a start time that has implicit knowledge of the date that the person died (such as “your last vaccination before you died”). I apologize for the error.

Secondly, for the unvaxxed, the ratio is going to be <.5 because people drop out and become vaccinated. Image if EVERYONE got vaccinated in Jan 2022. Then when looking at 2021 - 2022 death reports, it would “appear” like the unvaccinated all die off in the first year which would give a statistic of .25.

Brian Mowrey wrote this critique, but the error is simply picking a biased metric; the methodology is sound. His article could have been simpler: it should have said “just use an unbiased metric such as …” In general, critiques that are constructive and spell out a fix to get to the right answer are more helpful than critiques that merely shoot down attempts to get at the truth and offer no fix. There was a trivial fix which is simply to use a specific shot #.

I also made an error in one of the columns (for the unvaxxed only).

It’s interesting to note that the data appears to be very realistic. So if you pick a random date, for example, you’ll find that the deaths (you must use ALL the deaths, regardless of vaccination status) are random with respect to that date. You can even pick a variable date, such as the date of the last full moon before the person died and that will be random as well. People do this all the time. If you make a bias claim, you should prove it in the data itself, not just make hand-waving arguments.

You can also do a center of gravity analysis using the same restrictions as above. For example, limit the deaths to N days from the selected intervention point and add up the number of days till death and divide by the number of entries. For a neutral intervention, you should calculate a number that is close to N/2.

Sadly, I didn’t collect the date of each vaccination, so I’m unable to use dose #2, etc. as my metric.

But just using the date first vaccinated yields stunning numbers. And they are significantly lower than the values if you pick an arbitrary date such as Jan 1, 2021. I also compared with May 1, 2021 and Jan 1, 2022. All had similar ratios to Jan 1, 2021. Only the COVID First Shot data had lower numbers (i.e., harmful). This means the data is good and the shots are bad.

But as of February 1, 2023 it is now obvious to anyone who wants to look at my data (and validate the entries) that the COVID vaccines should be stopped.

The data can be attacked by postulating that my followers knew about deaths from the vax or were more likely to report deaths caused by vaccination. This is true. There were absolutely people who did not follow instructions and did that.

To check for the impact of this bias, I limited the set of records to only those records for immediate family members. In virtually all cases, this means just 1 death to choose from. The result was 76342/167666=0.45. This is a strong indication that people weren’t out cherry picking the person with the earliest date of death.

When I further limited it to just parent or grandparent, the result was the same ratio: 53740/118030 = 0.45.

So when we filtered the data to eliminate potential bias, the results got worse. This suggests the overall conclusions are correct.

Two important things to note:

  1. The analysis shows that the vaccine is killing people which confirms our other data so this result wasn’t a surprise.

  2. They authorities do NOT want to release ANY data for us to find the truth. If the vaccine is really beneficial, what is their incentive to hide the data? The bottom line is hiding the data is a tacit admission that they know the official data is devastating. So that’s why we have no choice but to use surveys like this to find the truth. The surveys put pressure on public officials to release the statewide data and when they don’t, … well, you know what THAT means!

The numbers on the left are for a start date of first vaccination. The numbers on the right are for a start date of Jan 1, 2021. This looks at deaths from Jan 1, 2021 to the end of 2022. All the data has been in plain sight for a month and can be verified since I have contact info for all the reporters. But the statistical validation is the rightmost column. The data allows you to see that it is legitimate. The differences here are impossible to explain if the vaccine is safe. LOWER value for ratio = more deadly.

You may ask why is the data for Jan 1, 2021 greater than .5? Simple. We included everyone who was vaccinated so anyone in that dataset had to have lived until they got vaccinated which biases the data in favor of living longer.

But there is no bias whatsoever when we use the start date of the first vaccination and all the numbers are <.50. That is very troubling for the safe and effective narrative.

Here is the data for picking a May 2021 starting point (vaccinated only):

Here is the data for picking a Jan 2022 starting point (vaccinated only):

The key here is that the only “odd ball” is shot #1 of the vaccine that is showing up to be deadly (for all age ranges).

However, as I noted above, the fixed date is not fair for the vaccinated (since it will overstate the ratio since you have to be alive to be vaccinated), and it’s not fair for the unvaccinated since it will understate the ratio (since people move out of the unvaxxed category over the 2 years).

To calculate a fair p-value, we’d have to compare with the complete dataset of all people who died, ignoring the vaccination status. This eliminates all biases. It’s basically just people who died in 2021 and 2022. The numbers > .5 reflect two things possible things going on:

  1. In 2022 more people died (remember 2/3 are vaccinated and as they got additional shots over time, they were more likely to die after the latter shots)

  2. A small amount of recall bias where people are more likely to recall a death that happened recently than more than a year ago

  3. For younger people, the vaccines rolled out later. So a young person was more likely to die in 2022 than 2021 because of the shot rollout schedule for young people

Values for everyone who died in the table, ignoring vaccination status. Start date Jan 1, 2021.

The p-value is stunning.

To compute the p-value, I used the days alive, days dead for the vaccinated group (using date of first vaccine given) vs. the entire dataset into a Fisher exact test.

Finally, the important point of this article is this: we have an objective way to judge the safety of an intervention using death and vaccine records. What we lack is the data to use it on. That’s the big problem here: the lack of data transparency. No one will release this data needed to assess vaccine safety voluntarily. It’s a simple JOIN between two tables and there are no privacy issues (since all we need is “an 85 year old died on date xxx and he was vaccinated at these dates using X vaccine”). Why do you think they are hiding this data?

We have a problem of data censorship. If they didn’t censor the data, everyone would know if the vaccines are safe or not. Why are they hiding the data?

John Beaudoin and I have been calling for this data to be set free and made public. Nobody in the mainstream infectious disease or epidemiology community seems to care about seeing the definitive data. Neither does the CDC or FDA or White House or Congress.

The data exists in VSD. But the CDC won’t allow anyone to see it.

The data exists in many state health departments. But you can’t FOIA it because it requires a join to avoid PII problems and FOIA requests are not allowed if they generate effort like that.

So we just have 6 different secret ways to get the data that we can’t talk about. Sooner or later we’ll get it.

Finally, with the above corrections, I’m re-enabling my 10X bet.

This is the most important article I have ever written in my life.

It shows a novel method that anyone can use to prove that the COVID vaccines are leading to premature death in anyone who takes them, no matter what age. So you don’t have to believe me. You can collect the data yourself and do the same analysis I did. It’s very easy. It took me about an hour to collect the data and analyze it.

The methodology is both technically sound and objective. Anyone can collect their own data including any state in the US and many foreign governments. I predict no one will look. That tells you everything you need to know.

I asked UK Professor Norman Fenton to critique the method I used here. More about him in the text below. Bottom line: he loved the method I used (which he hadn’t seen before), he validated the calculations in the figure below, and he wasn’t aware of any way the conclusion could be legitimately challenged. There are always all sorts of hand-waving arguments such as “your study wasn’t IRB approved” or “your study is unethical because you are looking at deaths from the COVID vaccine” but they are just that: hand-waving.

To further prove my article cannot be challenged, I am pioneering a unique approach to that as well that is fair, thorough, and transparent. I’m publicly offering 10X your wager to anyone who believes that the data actually shows the opposite of what I claimed. See details of the offer in the text below.

This article describes how a simple objective analysis of objective death data (age, date died, date of all COVID vaccinations) can be used to prove beyond a reasonable doubt that the COVID vaccines are shortening lifespans and should be immediately halted.

This explains why all the world’s health authorities are keeping their data secret; their data would reveal that all world governments have been killing millions of people worldwide. No government wants that disclosed. They won’t debate me on this. They will try to censor this article because they can’t hide from the truth. Or they will try to create FUD by arguing the survey is biased without describing the bias.

I predict that this article will be ignored by the mainstream press and the medical community. The longer they ignore me, the worse it will look for them. The first rule of holes is that when you find yourself in a hole, stop digging.

Unless there is a serious error in my methodology or someone can explain precisely how surveying “my followers” creates a biased sample that shifts the numbers for the vaccinated or shows us a more comprehensive, trustable data set, the game is now over.

If the vaccines are safe, the CDC should have produced this analysis using statewide data long ago. It is trivial to do. Why didn’t they? The answer is simple: because they know it would blow the narrative and prove to the world that they are incompetent fools.

If you want to prove me wrong, let’s get the statewide data from all states and make it public. All we need is Age, date of death, date of all COVID vaccines. That does not violate HIPAA or a dead person’s privacy because there is no PII.

But states will refuse to release that data because they know if they did, they are finished.

So in the meantime, they will say, “Your survey is biased.” But nobody can explain the “bias” that explains the result because my readers DO NOT CONTROL THE DATE THAT THEIR FRIENDS WERE VACCINATED, their age, or the DATE they died.

My readers may be more affluent than the average American so that’s a bias. But if the vaccine is killing affluent people, we have a problem. My readers might be more intelligent than the average American, so that’s a bias. They may have more intelligent friends. So this survey, it could be argued, just shows that intelligent people are being killed by the vaccine. That SHOULD be a stopping condition.

Or you could argue that my readers are less intelligent than the average person. And once again, unless you are trying to cull a society, that should be a stopping condition as unethical.

ANYONE CAN REPLICATE MY SURVEY if you think it is “biased.” The New York Times could replicate my survey and prove I’m wrong.

But they won’t.

And that tells you everything you need to know, doesn’t it?

If they want to argue with this article, THEY need to show us THEIR data and not engage in hand-waving arguments to create FUD that have no evidentiary basis.

The game is over. We have won. You cannot hide from the truth any longer.

We’ll see if anyone wants to challenge this article and get paid 10X their wager if they are right. Bring it on!

This article is a follow up on my article entitled, “The death records show the COVID vaccines are shortening lifespan worldwide.” That article gives John Beaudoin credit for being the first to realize that linking the death and vaccination records (a table join) is key to ending the false narrative.

In this article, I show a clever new method for analyzing the death/vax records that is simple and objective; it relies on just a simple division of two time measurements.

A month ago, on December 25, 2022, I announced the survey below.

The survey asked people if they knew anyone who died in 2020, 2021, or 2022.

If they did know someone, simply report objective facts about the death: age, date died, and if vaccinated, the date most recently vaccinated.

If people knew >1 person who died in the period, just report the person whose details you are most familiar with (e.g., family member vs. friend).

As of January 29, 2023, I received 1,634 responses. The analysis here looks at the responses.

We only consider OBJECTIVE data and our analysis is OBJECTIVE. It’s all math.

If the vaccines are causing death, the analysis will pick it up.

The analysis is done by looking at “days in category before death” divided by “days possible in category if you had lived to the end of the observation period.”

We do this for both vaxxed and unvaxxed people… across all ages, and also in various age ranges which I arbitrarily chose. You can choose your own if you don’t like the age categories I chose. It won’t change the result.

Here’s how the method works (credit to Clare Craig who suggested this wording):

Imagine a timeline for 2021 and 2022. For the unvaccinated we would expect an even distribution of deaths over time except for seasonal differences. For each person, we can compare how long they did live in that period with how long they could have lived. A few who died early would have lived for only a tiny fraction of their potential and a few that died late for a large fraction. However, most will be in between and the mean will be 0.5.

For the vaccinated, we start the clock on their date of their last vaccine. The timeline will therefore vary for each person but with a harmless vaccine we would still expect exactly the same distribution – a few early, a few late and most in the middle with a mean of 0.5.

If the vaccine killed people we would end up with more deaths early on. The mean ratio of life lived compared with life that could have been lived will fall below .5.

Given ratio=((time in category)/(time possible in category)) and knowing that the person died sometime in Jan 2021-Dec 2022, we have:

  1. If the intervention (i.e., the vax) does nothing, ratio = .5

  2. If the invention shortens life, ratio <.5

  3. If the intervention increases lifespan, ratio > .5

It’s that simple. The important thing is that the ratio tells us if the intervention is helpful, neutral, or harmful.

The analysis is independent of the rates people die. The fact that older people die faster than younger people is immaterial. Pre-existing conditions, etc. do not matter.

There is an argument to be made that people who got vaccinated first were more vulnerable and were more likely to die, and thus the rate in a category changes over time, but that effect isn’t very large. I’ve run the numbers for those who died and were last vaccinated in 2022 and the numbers are all less than .5. You are welcome to prove me wrong, but you’ll need to do it with evidence, i.e., actual queries and not hand-waving arguments. Numbers talk.

To date, everyone who thinks they can debunk this has produced only handwaving arguments and no analysis.

Sorry, but that’s not very convincing.

My survey includes reporters from all over the world, but all the readers speak English and 70% are in the US. The data can be analyzed just for the US and for specific vaccines as well, but below I include all the records to show that I’m not cherry picking and also to get more stability in the numbers (fewer data points creates more noise).

The people who answered are my followers and are most unvaccinated themselves. They are reporting deaths of the person they know the best, whether vaxxed or unvaxxed. I invite fact checkers to validate that people were true to the direction they were given. There are more vaccinated deaths reported simply because 75% of the US population is vaccinated.

The percentage of unvaccinated to total deaths was 29% (222/(222+542)).

So you might think “Ah ha! That proves that the unvaxxed are dying at a higher rate than the vaxxed because it should be only 25% of the deaths that should be vaccinated so this PROVES the vaccines are saving lives!”

No, it just proves that unvaccinated people hang around other unvaxxed people and are slightly more likely to report their deaths.

This is very helpful for our survey for two big reasons:

  1. It gives us enough data in both the vaxxed and unvaxxed buckets so we can do meaningful comparisons between the two buckets

  2. I can’t be accused of bias, e.g., you anti-vaxxers are just reporting vaccinated deaths to make the vax look bad. Clearly this isn’t the case… they are reporting disproportionately more unvaccinated deaths. So it looks very credible because it’s consistent with what you expect to see.

Note that the mix of vaxxed/unvaxxed deaths is immaterial to this analysis. Each cohort is examined independently. If I had 50% vaxxed and 50% unvaxxed deaths, the results would be exactly the same.

It’s important to note that my followers cannot determine the date of death of unvaccinated or vaccinated individuals (unless they have God-like powers). And I have contact info for all the records so they can be “spot checked” to validate that people followed my instructions to report the person they are most familiar with.

There is a recall bias in that people are more likely to report deaths that happened more recently. This shifts the average death time to the right. This is why unvaxxed are > .5 (more about that later).

For vaccinated people, there is also a healthy patient bias. If you are going to die in days due to a fatal cancer, most people would not get vaccinated.

There is some amount of seasonality in deaths that might skew things somewhat. It’s minimal for those <60, and small for the elderly. But we’re looking at a 2 year period so it shouldn’t be much different between vaxxed and unvaxxed.

It wasn’t possible to game the survey because nobody, including myself, knew how I was going to analyze the data until after the data was collected.

There was one person who put in a bogus entry (record #260) but that was easily spotted and removed.

The analysis cut off time was before this article was written so anyone trying to pollute the data will be unsuccessful since any new records aren’t included in the analysis.

The database has been in public view the entire time that the data has been gathered. When a record is submitted, it appears in the public view.

No submissions were deleted (other than record 260 which was clearly gamed) or modified which can be verified by the changelog of the data. The database is hosted by a third party firm.

There is an “integrity check” field indicating which records passed simply sanity check such as date vaccinated < date died. Only those records were processed.

I have the contact information for each reporter. I am looking forward to being contacted by any mainstream “fact check” organization who is willing to be recorded on video as we discuss the article. I’m happy to supply contact info for any line(s) in the survey so the fact checker can verify every record is legitimate.

People who die within 2021 to 2022 should be expected to die evenly throughout the period (there is some seasonality so it isn’t flat over the calendar months). Therefore, with no biases, we’d expect that the average days of life is 1 year in any 2 year observation period. So a ratio of .5. The seasonality cancels out.

But due to recall bias (since we are asking people to recall deaths rather than using government records), we’d expect the number to be skewed to dying more recently so maybe we’d see a ratio of .55 for the unvaccinated.

The vaccinated benefit from both recall bias and the healthy patient bias, so it might be .58 or more.

If the vaccines are safe and effective, the ratio of the vaccinated > ratio of the unvaccinated due to the healthy patient bias.

If the vaccines are killing people, the ratio of the vaccinated <= ratio of the unvaccinated (since the healthy patient bias would give the vaccinated an advantage).

If the vaccines are killing people, the ratio will be <0.5.

If the vaccines are safe, the ratio will be >0.5.

Guess what we found? 🙂

The data couldn’t be more clear: the shots are killing people.

The data is remarkably consistent.

See the section at the start of this article for the results.

For the vaccinated, my Airtable filter looked like this and I used the Vaxxed days died/days available columns.

NOTE: The “Integrity check” is NOT complete. But when coupled with the restrictions of the two filtering conditions, invalid records are all filtered out of the final result.

This is an Occam’s razor analysis. You could get fancier but it wouldn’t change the result. The signal is very very strong that the vaccines should be immediately stopped.

If I have made a mistake, I’d be grateful to see the correct analysis of the data using the same methodology. So if you object, show us the proper analysis.

The data is remarkably consistent for each age range. But there is a huge difference between the vaxxed (.3) and the unvaxxed (.58). This is exactly what I expected to see; no surprises. But it’s IMPOSSIBLE for the blue-pilled medical community to explain how this could possibly happen if the vaccine is so safe since it was supposed to be the other way around.

A simple look at the Notes field confirms the role of the vaccine in these deaths. That’s subjective proof. It shows that the vaccines are not as safe as claimed.

As far as confidence intervals, the numbers are remarkably consistent so the confidence intervals appear to be small. I’ve asked Professor Fenton for the correct way to ascertain these. He’s thinking about it. I’ll update this when I hear back.

But there’s more confirmation…

Is this analysis consistent with reliable evidence? Yes.

It turns out for the COVID vaccines, the best evidence we have is anecdotal evidence where everything is tracked since government data can be badly wrong as we learned in the UK where mistakes led them into thinking the vaccines were safe (see UK ONS admits their data is flawed; the vaccines may not be beneficial after all. Sorry about that).

As it turns out, it’s easy to find failure anecdotes for the COVID vaccines. The anecdotes we generally find show STRONG failures.

By contrast, it is nearly impossible to find a “success anecdote,” even a weak success. I always ask doctors who will talk to me and they’ve never mentioned a single success story. I do this constantly on Twitter Spaces in full public view and NONE of the DOCTORS will EVER be able to cite an example. In fact, I have not found any medical doctor who has ever been able to cite a single geriatric practice or nursing home where deaths dropped after the vaccines rolled out.

If the vaccines were saving lives, there should be THOUSANDS of “poster elderly” success stories, yet there are none. All the anecdotes are strongly negative. That’s simply impossible if the vaccines are saving “tens of millions of lives” as Neil deGrasse Tyson said on YouTube. When I called Neil to ask him for a success anecdote, he hung up the phone on me.

So we have a pretty good sense just from the failure to find a success that the vaccines are an utter disaster. We didn’t even need to do any numerical calculations!

Lots of things confirm our hypothesis:

  1. Lack of success anecdotes, but failure anecdotes easy to find

  2. People switch from pro- to anti- but not the reverse.

  3. Nobody can explain the 15,000 excess deaths in VAERS for the COVID vaccines. It’s not there for other vaccines, the deaths are all consistent with vaccine deaths. What killed all these people if it wasn’t the vaccine?

  4. Ed Dowd’s book “Cause Unknown” contains tons of data. Where is the document debunking everything in that book and showing the cause of all these deaths, especially the increase in child deaths happening right after the vaccines rolled out for kids.

  5. What about the 770 safety signals in VAERS. Why didn’t the CDC tell anyone about any of those signals? They notified the public about the VSD signal for stroke and didn’t even mention that it also triggered in VAERS.

  6. MIT Professor Retsef Levi calls for a halt to the COVID mRNA vaccines based on his study and others.

  7. The vaccine isn’t as effective as the NEJM led you to believe. A key paper is deeply flawed. In fact, it shows very troubling data as people will soon see: that the vaccine makes .

  8. Large Cleveland Clinic study shows the more you vaccinate yourself, the greater the risk of getting COVID. Whoops!

  9. A New Zealand funeral director noticed 95% of his cases died within 14 days of the shot. I spoke directly with Brenton. He lives in the middle of a retirement community. This is the very age that is supposed to be protected by the shots. Average age is 70+. His records can be verified. Any takers?

  10. Embalmer Anna Foster found that 93% of her cases had telltale rubbery clots. How can anyone explain that? She is hardly alone… 80% of embalmers surveyed report seeing these new style blood clots; they have never been seen before the COVID vaccines rolled out.

  11. Southwest airlines: Pilot deaths have increased 5X after the vaccines rolled out and disability shot up by 10X normal. Pilots are among the healthiest people on the planet.

  12. Geriatric practice: I finally found a large geriatric practice of 1,000 patients, 75% are over 65. Their normal death rate is 11 per year (the mean). In 2022, they had 39 deaths for the entire year. They attribute the 28 excess deaths to the vaccine. If it wasn’t the vaccine, someone needs to explain to us what is killing these people because whatever it is, it needs to be IMMEDIATELY stopped. They can’t go public for fear of retribution.

  13. Savo Island Cooperative (Berkeley, CA): Roughly 150 people. No deaths for 5 years before COVID; 0 in 2020; 1 in 2021; 3 in 2022 and they were all vaccinated and boosted (plus 3 strokes and 4 heart attacks). Reported to me by Jane Stillwater last night at an event I spoke at. Nobody at the event could recall any success anecdotes.

  14. Ed Dowd mentioned the vaccines have killed 800K Americans and disabled 4X as many as killed, 3.2M since the vaccine program began.

  15. The peer-reviewed scientific literature published a paper by Mark Skidmore showing over 217,000 deaths in 2021 alone due to the COVID vaccine. But they are looking at retracting the paper because Mark didn’t include a full bio on one of the funders of the study. Also, he asked a question about deaths from the COVID vaccine and that’s unethical (COVID virus questions are OK and ethical).

  16. Josh Stirling looked at how cities in the US did in 2022 vs. 2021. So it’s a longitudinal study where you compare the city with itself one year ago. This is the best way to see what is going on… did your mortality increase or decrease. Check this out: cities with higher vaccination had larger all-cause mortality increases than cities with lower vaccination rates. In other words, the line goes the “wrong way.” This is devastating for the narrative, but of course consistent with what the death reports are saying. The R2 doesn’t need to be .9 for this to be convincing. They are correlated and it’s the slope of the line that is significant. The slope is the wrong way. That’s the point.

    US cities; all ages; compare 2022 vs. 2021 in the same city The line slopes up. In other words, the experts were completely wrong: the vaccines are deadly. This is very compelling proof of harm that is impossible for anyone to explain away with a straight face. When combined with this analysis, it’s not credible to keep claiming the vaccines are safe and effective.

    Ages >65 version of the above

    Ages <65 version of the above

If the CDC doesn’t surface the statewide data for the public to see, then I believe it is time for the CDC to change their ads to look something like this:

I’ve had both the method and the data reviewed by UK Professor Norman Fenton. He’s the guy that proved the UK government data was fraudulent and cannot be used to prove the vaccines work (see the official full response at the bottom). Nobody else in the world had been able to do that. Nobody wants to debate Norman on any of his work because it is so impeccable. The top medical journals also hate him because he finds serious errors in key papers published in their journals (such as The Lancet and Science). He validated it as sound and reliable.

Others, such as Clare Craig of the HART Group, called the method described here “genius.”

How about a novel fully open peer review process for this analysis that is not subject to the whims of the scientific journals and shows to the public that the article cannot be attacked by anyone in the world?

You send me your wager via Solana blockchain and I’ll give you 10X your wager if you can show we got it wrong and the data shows the opposite conclusion.

Professor Fenton will judge your entry. He has high integrity and is on the side of truth.

The way it works is that you send me your wager ($5K to $10K worth of Solana) as your entry fee to: 9BBhGEfAMSHg8Mxyb4x67VKMhyomJ3MAPa9mqXtaP8xZ
with a comment with your contact info (or the contact info of your lawyer if you want to remain anonymous).

You can use Ledger Live or Phantom which supports adding a note to the transfer.

This will create a public record for all to see that you are accepting my offer. If you win, you get 10X your wager sent back to the address you sent your funds from. If you lose, you lose your deposit. This ensures people aren’t wasting my time with non-serious challenges.

Also, the size of the wagers tells you how confident people are in their analysis. I predict no one will wager anything. If I’m wrong, I lose a lot of money.

I’m kept honest by the public nature of this. People could legitimately discredit me if I don’t honor my offer. That would be a first.

Your burden is to show that my analysis of the data is flawed and that the data that was submitted to me actually shows the opposite: that the vaccines are saving lives.

People can look at Solscan to see the entries so that everything is in full public view. No gaming is possible. If there is a transaction, you can look at the “Memo Program V2” to see the notes for who is challenging me.

Fenton’s decision will be in writing as well and subject to public scrutiny. He has no history of not following the science. If you can produce evidence of this, I’m happy to pick another judge.

So if there are no challenges at my 10:1 odds, it’s de facto proof that I’m right.

It’s a novel method of public peer-review that is impossible to game or censor. It is open to anyone worldwide.

Make my day. Or as data scientist Joel Smalley might say, “Put up or shut up.”

My offer is open to the drug companies as well or any other institution.

Terms:

  1. Offer terms can be changed at any time (e.g., I may want to raise or lower the min/max bet).

  2. Send wager to: 9BBhGEfAMSHg8Mxyb4x67VKMhyomJ3MAPa9mqXtaP8xZ

  3. Min/max wager is currently:

  4. First come, first served. The Solana blockchain is the source of truth for the entry timing.

  5. Maximum of only one winner. If someone wins, any deposits received after that person will be refunded to the address of the sender.

  6. Disputes will be settled by JAMS mediation.

  7. Your sending me the Solana with the contact info signifies your acceptance of the offer.

  8. Professor Norman Fenton will judge your submission in a live Zoom call that is recorded and publicly broadcast. You will have 1 hour to present your argument. He will put his decision in writing and post it to his Substack.

  9. To win, you must show that the data shows, for all age cohorts, that the vaccines are neutral or beneficial. You can show this using my data (preferred), or, if you can convince Fenton that my data is unfairly biased, you can use it on your own dataset provided you can convince him that your data was fairly collected in a neutral manner (which includes complete state data joining the death and vaccination database tables). If the data is privately collected, prospective collection by a neutral party is preferred since otherwise the provenance of the data would be hard to prove.

  10. You can attack the method, the data, or both to prove your point and make your case.

  11. Offer expires March 30, 2023 to encourage submission.

  12. You can request a written, legally enforceable definitive agreement if you don’t trust me. Use the Contact Me link and include the name and phone number of your attorney so we can work out the details.

  13. Anyone can enter, individuals, corporations, etc. including, but not limited to:

    1. CDC Director Rochelle Walensky

    2. All the vaccine makers

    3. Tom Shimabukuro and his pal John Su of the CDC (these are the guys who hid the 700+ safety signals from the world; see this article on the death safety signal and this article on 700+ safety signals)

    4. The people at the CDC and FDA who put me on the email block list so that I was not able to speak at the public comment section of the FDA or CDC meetings which violates my rights to free speech… I get it ….. if you can’t argue based on the data, you censor your opposition. That’s the way science works at the FDA and CDC.

    5. Tedros from the WHO who just declared COVID to still be an emergency…what a fruitcake!

    6. UCSF, Stanford, Harvard, MIT, …

    7. Executives at YouTube, especially those involved in censoring truthful content

    8. All LinkedIn executives involved in the decision to ban me for life on LinkedIn

    9. Medium CEO Ev Williams for supporting the decision to ban me for life

    10. All Wikipedia executives for supporting the decision to ban me for life and supporting the efforts to trash my Wikipedia profile to make me look like a menace to society. And how dare you remove my National Caring Award from my Wikipedia profile. You are a truly evil and corrupt organization.

    11. Stanford Professor and ACIP Chair Grace Lee who would rather call the Palo Alto Police on me than watch the video from the Israeli Ministry of Health proving the vaccines are not safe. Watch the video; it is a classic (Pierre Kory loved it).

    12. CDC

    13. ACIP and VRBPAC committee members

    14. The comedy team of US Surgeon General Vivek Murthy and Ashish Jha

    15. ZDoggMD

    16. Dr. Susan Oliver (along with her dog Cindy Oliver)

    17. Your Local Epidemiologist (YLE)

    18. David Gorski

    19. Jonathan Jarry

    20. UPenn Professor Jeffrey Morris

    21. Paul Offit

    22. Peter Hotez

    23. Truth warrior Dr. Angela Rasmussen

    24. Eric Topol

    25. Anthony “I am the Science” Fauci

    26. “Debunk the Funk” aka Daniel Wilson

    27. Bob Wachter, Dean of Medicine, UCSF

    28. Lloyd Minor, Dean of Medicine, Stanford University

    29. Harvey Cohen, Stanford University

    30. 60 Minutes

    31. The New York Times

    32. The Wall St. Journal

    33. The Washington Post

    34. The BBC

    35. Reuters Fact Check and any other so-called “fact checker”… and even Dr. Adrian Wong

    36. All of the members of the CETF SAB… the ones who said I was wrong and that they never wanted to speak to me again

    37. Any member of US Congress

    38. Any world leader who is pushing these vaccines

    39. Any health official anywhere in the world who is pushing these vaccines

    40. Neil deGrasse Tyson… who hung up on me when I challenged him on his bullshit statement that the vaccines have saved millions of lives. Give me a break.

    41. Their champion (if I can find him/her)

What a joke. None of these people can show I got it wrong.

Not a single one of them has publicly called for exposing the data so the public can learn the truth.

They are all afraid of the truth, the whole lot of them.

And if they can’t show I got it wrong, they should publicly admit I got it right. That would be the right thing to do.

The burden of proof is on the authorities to show that the vaccine is safe especially now since most people are not taking the shots.

They should produce the death data and make it publicly available for analysis. That would end the debate.

Ideally, for every person who died in 2019 to the end of 2022:

  1. Age

  2. Date died

  3. Date of each vaccine

  4. The vaccine type for each shot

  5. The total number of doses given

Image

The elephant in the room that nobody wants to talk about is that it is primarily the vaccinated that are “dying suddenly.” In fact, did you know it is unethical for papers submitted to technical journals to talk about vaccine deaths? Wait till you hear about Mark Skidmore’s paper showing over 200K killed by the COVID vaccines in year 1 and the objections they are raising.

The method presented in this article is a simple, straightforward analysis that can be used with death records to reveal the truth about the vaccines.

The results I obtained from over 1,500 death records are self consistent and are consistent with other data we have collected. I wasn’t surprised at all to get this result.

If anything, the vaccinated should have done better than the unvaccinated in this survey because of the healthy patient bias effect. But, as we found, it did far worse. Reading the comments in the death submissions confirms that a large number of cases are vaccine related.

Also, it is remarkable that the #1 feature of a vaccine death is “died suddenly.” Does that sound familiar?

The study cannot be attacked as “biased” unless you can explain how my followers can either 1) cause the premature death of vaccinated friends OR 2) deliberately ignored instructions to report the person they knew the best and instead they all followed a different set of instructions that they magically all agreed on.

That’s far fetched because:

  1. Most people who reported a death only knew one person who died. So it’s not like they can choose the “best” answer.

  2. Because they are my followers, they’ll want to help me and that means following my instructions which was to choose the friend whose details they knew the best

  3. At the time the survey was done, nobody knew how the data would be analyzed, not even me. They would have to ignore the instruction they were given and instead follow the “proper algorithm” in massive numbers. Why would they ignore my instructions? They are my followers and want to help me! And how would they know the “correct” instructions?

So where’s the evidence of bias?

There are only three ways to legitimately attack this study:

  1. Show an error in the methodology and show us our data that is correctly analyzed and where the medical community agrees you have the CORRECT analysis.

  2. Show an error in the data. I’m happy to have someone contact random people who answered the survey to ask those people if they followed the instructions to report the person they knew the best or not and if not why not.

  3. Show us a larger dataset showing the opposite result where we can verify every record with the primary data source. For some reason, no government will show us the record level data where the death age and date of death is tied to the vaccination records. Critical thinkers want to know: if the vaccine is so safe, why is this data being hidden from public view?

The bottom line: the COVID vaccines increase your chance of dying for every age group (that we had sufficient data on) and should be immediately halted. They are the biggest mistake in modern medical history. This analysis is completely objective, the data is very consistent, there is no evidence of bias that could explain the outcome, and there is no escaping the truth.

The medical community needs to take sides on my article and stop sitting on the sidelines. They have an ethical obligation to immediately either:

  1. call for a halt to the COVID vaccines or

  2. show us how we got it wrong by either showing the correct analysis or by producing a more comprehensive dataset.

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How you can instantly show whether the vaccines are helpful or harmful

If the CDC was honest, this is what their new ads should look like!

A new analysis technique can be applied to death-vax records to instantly assess whether the vaccine is helpful or harmful.

When applied to to the somewhat biased survey data I gathered from my followers, it shows that the vaccines should be immediately stopped for all ages. When limiting the dataset to records that are unlikely to be biased, the signal is still present and equally strong.

This method can be applied to any death-vax data: mine, yours, and data from governments.

The point is this: It’s interesting to note that nobody wants to actually produce the record-level death-vax data to prove the vaccines are safe and effective.

We are now over two years into the vaccination program and not only is nobody publishing the data that would prove or not that the vaccines are safe, but nobody is even asking for the data to be published.

It’s almost as if nobody wants to know the truth.

Define our database as anyone who died sometime in Jan 2021-Dec 2022

Let ratio=((sum of records of time in category)/(sum of records of time possible in category)) where time for both the numerator and denominator is measured from the intervention start point, e.g., date of first vax.

If there isn’t an external event that would cause people to die at an uneven rate throughout the period being considered, then we have:

  1. Neutral = .5

  2. Harmful <.5

  3. Beneficial > .5

It’s that simple. The important thing is that the ratio tells us if the intervention is helpful, neutral, or harmful.

The analysis is independent of the rates people die. The fact that older people die faster than younger people is immaterial. Pre-existing conditions, etc. do not matter.

The technique basically will show whether the chosen start time is associated with prolonging or shortening life.

Here is the data used in the analysis

The survey was announced here:

The start point can be any point that should be random with respect to the date of death.

So for example, a specific calendar date, the date of vax #N (a specific vax number), the date of the last full moon before the person died, etc. A start point that is dependent on the date of death such as “the date of the last vaccine given before the person died” would not work because it would be biased (e.g., think of the case where the vaccine was given every day until death).

To see if there is an effect, we look at the records associated with various intervention points: Dose 1, Dose 2, etc. For my current death survey, because I didn’t collect the dates of each dose, we are limited to the Dose 1 date for the intervention.

The control is to look at all the death records using quarterly start dates. This will allow us to estimate the statistical noise in the ratio given the various start points. So ideally, we look at Start dates by quarter for each quarter in 2021: Q1, Q2, Q3, and Q4 and also 2022: Q1.

There are always external events that have an uneven effect on mortality throughout the observation period.

The controls account for that variation. So if the Dose 1 data is < all the controls, that would be very strong evidence that the vaccines increased all-cause mortality.

The intervention under test (Dose #1 date):

This shows the numbers for choosing a start point of the date of the FIRST vaccine dose. Numbers <.5 generally mean the intervention is harmful.

The primary control: all deaths in the period regardless of vaccination status:

All death records. This shows that there were more deaths in 2022 which can be due to recall bias or the aggregate effect of all the vaccines. Individual medical practices report greater deaths in 2022 than 2021 so this is most likely explained as due to the vaccine.

What this shows is that the intervention (the vaccine) had lower numbers than the control, indicating the intervention (the vaccine) is harmful.

Lessons learn for future surveys:

  • Allow people to report as many records as they want

  • If they know vax details of several deaths, and don’t want to report all the deaths, pick the person with the last name that appears higher in the alphabet.

  • Tell us the number you are reporting

  • Tell us the number you knew about

  • Start date should be Dec 14, 2020 onwards

  • Proof of death (hyperlink to obit)

  • Proof of vaccination card link (hyperlink to card)

  • Get every vax date and brands used

  • Tell people to double check the dates are right (and use American style date format)

  • Have checkboxes for UK, Australia, New Zealand, Germany, France, and Canada

Even with those corrections, surveys will always have biases because the anti-vaxxers will hear about and learn more about deaths likely to be associated with the vaccine.

This is why I am waiting for state level data before making any conclusions. I now have that data. So these surveys are no longer needed.

It is troubling that record-level death-vax data is not available. This is by far the most important data we have to show whether the vaccines are helpful or harmful.

We should all be concerned that the data isn’t being made available and that the mainstream medical community has no interest in seeing this data.

Those facts alone should cause anyone with a working brain to demand transparency. Nobody should be taking any more shots or requiring or recommending people take the shots until the data is released and can be analyzed.

We have the record-level death-vax data. Why aren’t we making it publicly available?

See A worldwide call for data transparency: Show us the data!

Most people can stop reading here.

The novel time-ratio method in this paper is sound, but certain restrictions apply to the metric that was chosen that I was subsequently made aware of after talking with Norman Fenton and Clare Craig. I am grateful to them for pointing out the limitations.

The big error was using the “date of most recent vaccination” as the “intervention point.” This is biased and will give lower numbers as a result. You can pick anything that is random with respect to the death endpoint, but that point doesn’t qualify because it is dependent on the death endpoint. Here’s the simple reasoning for why “most recent vax” is a bad endpoint. Imagine if you were vaccinated every day… You’d always die exactly one day after your last vaccination!

So I could have picked vax #1 date, vax #2 date, vax #3 day, etc. date for an individual (which would vary for each person), an arbitrary day of the year (assuming nothing external is happening like a Delta surge), date of vax availability, etc. You just can’t pick a start time that has implicit knowledge of the date that the person died (such as “your last vaccination before you died”). I apologize for the error.

Secondly, for the unvaxxed, the ratio is going to be <.5 because people drop out and become vaccinated. Image if EVERYONE got vaccinated in Jan 2022. Then when looking at 2021 - 2022 death reports, it would “appear” like the unvaccinated all die off in the first year which would give a statistic of .25.

Brian Mowrey wrote this critique, but the error is simply picking a biased metric; the methodology is sound. His article could have been simpler: it should have said “just use an unbiased metric such as …” In general, critiques that are constructive and spell out a fix to get to the right answer are more helpful than critiques that merely shoot down attempts to get at the truth and offer no fix. There was a trivial fix which is simply to use a specific shot #.

I also made an error in one of the columns (for the unvaxxed only).

It’s interesting to note that the data appears to be very realistic. So if you pick a random date, for example, you’ll find that the deaths (you must use ALL the deaths, regardless of vaccination status) are random with respect to that date. You can even pick a variable date, such as the date of the last full moon before the person died and that will be random as well. People do this all the time. If you make a bias claim, you should prove it in the data itself, not just make hand-waving arguments.

You can also do a center of gravity analysis using the same restrictions as above. For example, limit the deaths to N days from the selected intervention point and add up the number of days till death and divide by the number of entries. For a neutral intervention, you should calculate a number that is close to N/2.

Sadly, I didn’t collect the date of each vaccination, so I’m unable to use dose #2, etc. as my metric.

But just using the date first vaccinated yields stunning numbers. And they are significantly lower than the values if you pick an arbitrary date such as Jan 1, 2021. I also compared with May 1, 2021 and Jan 1, 2022. All had similar ratios to Jan 1, 2021. Only the COVID First Shot data had lower numbers (i.e., harmful). This means the data is good and the shots are bad.

But as of February 1, 2023 it is now obvious to anyone who wants to look at my data (and validate the entries) that the COVID vaccines should be stopped.

The data can be attacked by postulating that my followers knew about deaths from the vax or were more likely to report deaths caused by vaccination. This is true. There were absolutely people who did not follow instructions and did that.

To check for the impact of this bias, I limited the set of records to only those records for immediate family members. In virtually all cases, this means just 1 death to choose from. The result was 76342/167666=0.45. This is a strong indication that people weren’t out cherry picking the person with the earliest date of death.

When I further limited it to just parent or grandparent, the result was the same ratio: 53740/118030 = 0.45.

So when we filtered the data to eliminate potential bias, the results got worse. This suggests the overall conclusions are correct.

Two important things to note:

  1. The analysis shows that the vaccine is killing people which confirms our other data so this result wasn’t a surprise.

  2. They authorities do NOT want to release ANY data for us to find the truth. If the vaccine is really beneficial, what is their incentive to hide the data? The bottom line is hiding the data is a tacit admission that they know the official data is devastating. So that’s why we have no choice but to use surveys like this to find the truth. The surveys put pressure on public officials to release the statewide data and when they don’t, … well, you know what THAT means!

The numbers on the left are for a start date of first vaccination. The numbers on the right are for a start date of Jan 1, 2021. This looks at deaths from Jan 1, 2021 to the end of 2022. All the data has been in plain sight for a month and can be verified since I have contact info for all the reporters. But the statistical validation is the rightmost column. The data allows you to see that it is legitimate. The differences here are impossible to explain if the vaccine is safe. LOWER value for ratio = more deadly.

You may ask why is the data for Jan 1, 2021 greater than .5? Simple. We included everyone who was vaccinated so anyone in that dataset had to have lived until they got vaccinated which biases the data in favor of living longer.

But there is no bias whatsoever when we use the start date of the first vaccination and all the numbers are <.50. That is very troubling for the safe and effective narrative.

Here is the data for picking a May 2021 starting point (vaccinated only):

Here is the data for picking a Jan 2022 starting point (vaccinated only):

The key here is that the only “odd ball” is shot #1 of the vaccine that is showing up to be deadly (for all age ranges).

However, as I noted above, the fixed date is not fair for the vaccinated (since it will overstate the ratio since you have to be alive to be vaccinated), and it’s not fair for the unvaccinated since it will understate the ratio (since people move out of the unvaxxed category over the 2 years).

To calculate a fair p-value, we’d have to compare with the complete dataset of all people who died, ignoring the vaccination status. This eliminates all biases. It’s basically just people who died in 2021 and 2022. The numbers > .5 reflect two things possible things going on:

  1. In 2022 more people died (remember 2/3 are vaccinated and as they got additional shots over time, they were more likely to die after the latter shots)

  2. A small amount of recall bias where people are more likely to recall a death that happened recently than more than a year ago

  3. For younger people, the vaccines rolled out later. So a young person was more likely to die in 2022 than 2021 because of the shot rollout schedule for young people

Values for everyone who died in the table, ignoring vaccination status. Start date Jan 1, 2021.

The p-value is stunning.

To compute the p-value, I used the days alive, days dead for the vaccinated group (using date of first vaccine given) vs. the entire dataset into a Fisher exact test.

Finally, the important point of this article is this: we have an objective way to judge the safety of an intervention using death and vaccine records. What we lack is the data to use it on. That’s the big problem here: the lack of data transparency. No one will release this data needed to assess vaccine safety voluntarily. It’s a simple JOIN between two tables and there are no privacy issues (since all we need is “an 85 year old died on date xxx and he was vaccinated at these dates using X vaccine”). Why do you think they are hiding this data?

We have a problem of data censorship. If they didn’t censor the data, everyone would know if the vaccines are safe or not. Why are they hiding the data?

John Beaudoin and I have been calling for this data to be set free and made public. Nobody in the mainstream infectious disease or epidemiology community seems to care about seeing the definitive data. Neither does the CDC or FDA or White House or Congress.

The data exists in VSD. But the CDC won’t allow anyone to see it.

The data exists in many state health departments. But you can’t FOIA it because it requires a join to avoid PII problems and FOIA requests are not allowed if they generate effort like that.

So we just have 6 different secret ways to get the data that we can’t talk about. Sooner or later we’ll get it.

Finally, with the above corrections, I’m re-enabling my 10X bet.

This is the most important article I have ever written in my life.

It shows a novel method that anyone can use to prove that the COVID vaccines are leading to premature death in anyone who takes them, no matter what age. So you don’t have to believe me. You can collect the data yourself and do the same analysis I did. It’s very easy. It took me about an hour to collect the data and analyze it.

The methodology is both technically sound and objective. Anyone can collect their own data including any state in the US and many foreign governments. I predict no one will look. That tells you everything you need to know.

I asked UK Professor Norman Fenton to critique the method I used here. More about him in the text below. Bottom line: he loved the method I used (which he hadn’t seen before), he validated the calculations in the figure below, and he wasn’t aware of any way the conclusion could be legitimately challenged. There are always all sorts of hand-waving arguments such as “your study wasn’t IRB approved” or “your study is unethical because you are looking at deaths from the COVID vaccine” but they are just that: hand-waving.

To further prove my article cannot be challenged, I am pioneering a unique approach to that as well that is fair, thorough, and transparent. I’m publicly offering 10X your wager to anyone who believes that the data actually shows the opposite of what I claimed. See details of the offer in the text below.

This article describes how a simple objective analysis of objective death data (age, date died, date of all COVID vaccinations) can be used to prove beyond a reasonable doubt that the COVID vaccines are shortening lifespans and should be immediately halted.

This explains why all the world’s health authorities are keeping their data secret; their data would reveal that all world governments have been killing millions of people worldwide. No government wants that disclosed. They won’t debate me on this. They will try to censor this article because they can’t hide from the truth. Or they will try to create FUD by arguing the survey is biased without describing the bias.

I predict that this article will be ignored by the mainstream press and the medical community. The longer they ignore me, the worse it will look for them. The first rule of holes is that when you find yourself in a hole, stop digging.

Unless there is a serious error in my methodology or someone can explain precisely how surveying “my followers” creates a biased sample that shifts the numbers for the vaccinated or shows us a more comprehensive, trustable data set, the game is now over.

If the vaccines are safe, the CDC should have produced this analysis using statewide data long ago. It is trivial to do. Why didn’t they? The answer is simple: because they know it would blow the narrative and prove to the world that they are incompetent fools.

If you want to prove me wrong, let’s get the statewide data from all states and make it public. All we need is Age, date of death, date of all COVID vaccines. That does not violate HIPAA or a dead person’s privacy because there is no PII.

But states will refuse to release that data because they know if they did, they are finished.

So in the meantime, they will say, “Your survey is biased.” But nobody can explain the “bias” that explains the result because my readers DO NOT CONTROL THE DATE THAT THEIR FRIENDS WERE VACCINATED, their age, or the DATE they died.

My readers may be more affluent than the average American so that’s a bias. But if the vaccine is killing affluent people, we have a problem. My readers might be more intelligent than the average American, so that’s a bias. They may have more intelligent friends. So this survey, it could be argued, just shows that intelligent people are being killed by the vaccine. That SHOULD be a stopping condition.

Or you could argue that my readers are less intelligent than the average person. And once again, unless you are trying to cull a society, that should be a stopping condition as unethical.

ANYONE CAN REPLICATE MY SURVEY if you think it is “biased.” The New York Times could replicate my survey and prove I’m wrong.

But they won’t.

And that tells you everything you need to know, doesn’t it?

If they want to argue with this article, THEY need to show us THEIR data and not engage in hand-waving arguments to create FUD that have no evidentiary basis.

The game is over. We have won. You cannot hide from the truth any longer.

We’ll see if anyone wants to challenge this article and get paid 10X their wager if they are right. Bring it on!

This article is a follow up on my article entitled, “The death records show the COVID vaccines are shortening lifespan worldwide.” That article gives John Beaudoin credit for being the first to realize that linking the death and vaccination records (a table join) is key to ending the false narrative.

In this article, I show a clever new method for analyzing the death/vax records that is simple and objective; it relies on just a simple division of two time measurements.

A month ago, on December 25, 2022, I announced the survey below.

The survey asked people if they knew anyone who died in 2020, 2021, or 2022.

If they did know someone, simply report objective facts about the death: age, date died, and if vaccinated, the date most recently vaccinated.

If people knew >1 person who died in the period, just report the person whose details you are most familiar with (e.g., family member vs. friend).

As of January 29, 2023, I received 1,634 responses. The analysis here looks at the responses.

We only consider OBJECTIVE data and our analysis is OBJECTIVE. It’s all math.

If the vaccines are causing death, the analysis will pick it up.

The analysis is done by looking at “days in category before death” divided by “days possible in category if you had lived to the end of the observation period.”

We do this for both vaxxed and unvaxxed people… across all ages, and also in various age ranges which I arbitrarily chose. You can choose your own if you don’t like the age categories I chose. It won’t change the result.

Here’s how the method works (credit to Clare Craig who suggested this wording):

Imagine a timeline for 2021 and 2022. For the unvaccinated we would expect an even distribution of deaths over time except for seasonal differences. For each person, we can compare how long they did live in that period with how long they could have lived. A few who died early would have lived for only a tiny fraction of their potential and a few that died late for a large fraction. However, most will be in between and the mean will be 0.5.

For the vaccinated, we start the clock on their date of their last vaccine. The timeline will therefore vary for each person but with a harmless vaccine we would still expect exactly the same distribution – a few early, a few late and most in the middle with a mean of 0.5.

If the vaccine killed people we would end up with more deaths early on. The mean ratio of life lived compared with life that could have been lived will fall below .5.

Given ratio=((time in category)/(time possible in category)) and knowing that the person died sometime in Jan 2021-Dec 2022, we have:

  1. If the intervention (i.e., the vax) does nothing, ratio = .5

  2. If the invention shortens life, ratio <.5

  3. If the intervention increases lifespan, ratio > .5

It’s that simple. The important thing is that the ratio tells us if the intervention is helpful, neutral, or harmful.

The analysis is independent of the rates people die. The fact that older people die faster than younger people is immaterial. Pre-existing conditions, etc. do not matter.

There is an argument to be made that people who got vaccinated first were more vulnerable and were more likely to die, and thus the rate in a category changes over time, but that effect isn’t very large. I’ve run the numbers for those who died and were last vaccinated in 2022 and the numbers are all less than .5. You are welcome to prove me wrong, but you’ll need to do it with evidence, i.e., actual queries and not hand-waving arguments. Numbers talk.

To date, everyone who thinks they can debunk this has produced only handwaving arguments and no analysis.

Sorry, but that’s not very convincing.

My survey includes reporters from all over the world, but all the readers speak English and 70% are in the US. The data can be analyzed just for the US and for specific vaccines as well, but below I include all the records to show that I’m not cherry picking and also to get more stability in the numbers (fewer data points creates more noise).

The people who answered are my followers and are most unvaccinated themselves. They are reporting deaths of the person they know the best, whether vaxxed or unvaxxed. I invite fact checkers to validate that people were true to the direction they were given. There are more vaccinated deaths reported simply because 75% of the US population is vaccinated.

The percentage of unvaccinated to total deaths was 29% (222/(222+542)).

So you might think “Ah ha! That proves that the unvaxxed are dying at a higher rate than the vaxxed because it should be only 25% of the deaths that should be vaccinated so this PROVES the vaccines are saving lives!”

No, it just proves that unvaccinated people hang around other unvaxxed people and are slightly more likely to report their deaths.

This is very helpful for our survey for two big reasons:

  1. It gives us enough data in both the vaxxed and unvaxxed buckets so we can do meaningful comparisons between the two buckets

  2. I can’t be accused of bias, e.g., you anti-vaxxers are just reporting vaccinated deaths to make the vax look bad. Clearly this isn’t the case… they are reporting disproportionately more unvaccinated deaths. So it looks very credible because it’s consistent with what you expect to see.

Note that the mix of vaxxed/unvaxxed deaths is immaterial to this analysis. Each cohort is examined independently. If I had 50% vaxxed and 50% unvaxxed deaths, the results would be exactly the same.

It’s important to note that my followers cannot determine the date of death of unvaccinated or vaccinated individuals (unless they have God-like powers). And I have contact info for all the records so they can be “spot checked” to validate that people followed my instructions to report the person they are most familiar with.

There is a recall bias in that people are more likely to report deaths that happened more recently. This shifts the average death time to the right. This is why unvaxxed are > .5 (more about that later).

For vaccinated people, there is also a healthy patient bias. If you are going to die in days due to a fatal cancer, most people would not get vaccinated.

There is some amount of seasonality in deaths that might skew things somewhat. It’s minimal for those <60, and small for the elderly. But we’re looking at a 2 year period so it shouldn’t be much different between vaxxed and unvaxxed.

It wasn’t possible to game the survey because nobody, including myself, knew how I was going to analyze the data until after the data was collected.

There was one person who put in a bogus entry (record #260) but that was easily spotted and removed.

The analysis cut off time was before this article was written so anyone trying to pollute the data will be unsuccessful since any new records aren’t included in the analysis.

The database has been in public view the entire time that the data has been gathered. When a record is submitted, it appears in the public view.

No submissions were deleted (other than record 260 which was clearly gamed) or modified which can be verified by the changelog of the data. The database is hosted by a third party firm.

There is an “integrity check” field indicating which records passed simply sanity check such as date vaccinated < date died. Only those records were processed.

I have the contact information for each reporter. I am looking forward to being contacted by any mainstream “fact check” organization who is willing to be recorded on video as we discuss the article. I’m happy to supply contact info for any line(s) in the survey so the fact checker can verify every record is legitimate.

People who die within 2021 to 2022 should be expected to die evenly throughout the period (there is some seasonality so it isn’t flat over the calendar months). Therefore, with no biases, we’d expect that the average days of life is 1 year in any 2 year observation period. So a ratio of .5. The seasonality cancels out.

But due to recall bias (since we are asking people to recall deaths rather than using government records), we’d expect the number to be skewed to dying more recently so maybe we’d see a ratio of .55 for the unvaccinated.

The vaccinated benefit from both recall bias and the healthy patient bias, so it might be .58 or more.

If the vaccines are safe and effective, the ratio of the vaccinated > ratio of the unvaccinated due to the healthy patient bias.

If the vaccines are killing people, the ratio of the vaccinated <= ratio of the unvaccinated (since the healthy patient bias would give the vaccinated an advantage).

If the vaccines are killing people, the ratio will be <0.5.

If the vaccines are safe, the ratio will be >0.5.

Guess what we found? 🙂

The data couldn’t be more clear: the shots are killing people.

The data is remarkably consistent.

See the section at the start of this article for the results.

For the vaccinated, my Airtable filter looked like this and I used the Vaxxed days died/days available columns.

NOTE: The “Integrity check” is NOT complete. But when coupled with the restrictions of the two filtering conditions, invalid records are all filtered out of the final result.

This is an Occam’s razor analysis. You could get fancier but it wouldn’t change the result. The signal is very very strong that the vaccines should be immediately stopped.

If I have made a mistake, I’d be grateful to see the correct analysis of the data using the same methodology. So if you object, show us the proper analysis.

The data is remarkably consistent for each age range. But there is a huge difference between the vaxxed (.3) and the unvaxxed (.58). This is exactly what I expected to see; no surprises. But it’s IMPOSSIBLE for the blue-pilled medical community to explain how this could possibly happen if the vaccine is so safe since it was supposed to be the other way around.

A simple look at the Notes field confirms the role of the vaccine in these deaths. That’s subjective proof. It shows that the vaccines are not as safe as claimed.

As far as confidence intervals, the numbers are remarkably consistent so the confidence intervals appear to be small. I’ve asked Professor Fenton for the correct way to ascertain these. He’s thinking about it. I’ll update this when I hear back.

But there’s more confirmation…

Is this analysis consistent with reliable evidence? Yes.

It turns out for the COVID vaccines, the best evidence we have is anecdotal evidence where everything is tracked since government data can be badly wrong as we learned in the UK where mistakes led them into thinking the vaccines were safe (see UK ONS admits their data is flawed; the vaccines may not be beneficial after all. Sorry about that).

As it turns out, it’s easy to find failure anecdotes for the COVID vaccines. The anecdotes we generally find show STRONG failures.

By contrast, it is nearly impossible to find a “success anecdote,” even a weak success. I always ask doctors who will talk to me and they’ve never mentioned a single success story. I do this constantly on Twitter Spaces in full public view and NONE of the DOCTORS will EVER be able to cite an example. In fact, I have not found any medical doctor who has ever been able to cite a single geriatric practice or nursing home where deaths dropped after the vaccines rolled out.

If the vaccines were saving lives, there should be THOUSANDS of “poster elderly” success stories, yet there are none. All the anecdotes are strongly negative. That’s simply impossible if the vaccines are saving “tens of millions of lives” as Neil deGrasse Tyson said on YouTube. When I called Neil to ask him for a success anecdote, he hung up the phone on me.

So we have a pretty good sense just from the failure to find a success that the vaccines are an utter disaster. We didn’t even need to do any numerical calculations!

Lots of things confirm our hypothesis:

  1. Lack of success anecdotes, but failure anecdotes easy to find

  2. People switch from pro- to anti- but not the reverse.

  3. Nobody can explain the 15,000 excess deaths in VAERS for the COVID vaccines. It’s not there for other vaccines, the deaths are all consistent with vaccine deaths. What killed all these people if it wasn’t the vaccine?

  4. Ed Dowd’s book “Cause Unknown” contains tons of data. Where is the document debunking everything in that book and showing the cause of all these deaths, especially the increase in child deaths happening right after the vaccines rolled out for kids.

  5. What about the 770 safety signals in VAERS. Why didn’t the CDC tell anyone about any of those signals? They notified the public about the VSD signal for stroke and didn’t even mention that it also triggered in VAERS.

  6. MIT Professor Retsef Levi calls for a halt to the COVID mRNA vaccines based on his study and others.

  7. The vaccine isn’t as effective as the NEJM led you to believe. A key paper is deeply flawed. In fact, it shows very troubling data as people will soon see: that the vaccine makes .

  8. Large Cleveland Clinic study shows the more you vaccinate yourself, the greater the risk of getting COVID. Whoops!

  9. A New Zealand funeral director noticed 95% of his cases died within 14 days of the shot. I spoke directly with Brenton. He lives in the middle of a retirement community. This is the very age that is supposed to be protected by the shots. Average age is 70+. His records can be verified. Any takers?

  10. Embalmer Anna Foster found that 93% of her cases had telltale rubbery clots. How can anyone explain that? She is hardly alone… 80% of embalmers surveyed report seeing these new style blood clots; they have never been seen before the COVID vaccines rolled out.

  11. Southwest airlines: Pilot deaths have increased 5X after the vaccines rolled out and disability shot up by 10X normal. Pilots are among the healthiest people on the planet.

  12. Geriatric practice: I finally found a large geriatric practice of 1,000 patients, 75% are over 65. Their normal death rate is 11 per year (the mean). In 2022, they had 39 deaths for the entire year. They attribute the 28 excess deaths to the vaccine. If it wasn’t the vaccine, someone needs to explain to us what is killing these people because whatever it is, it needs to be IMMEDIATELY stopped. They can’t go public for fear of retribution.

  13. Savo Island Cooperative (Berkeley, CA): Roughly 150 people. No deaths for 5 years before COVID; 0 in 2020; 1 in 2021; 3 in 2022 and they were all vaccinated and boosted (plus 3 strokes and 4 heart attacks). Reported to me by Jane Stillwater last night at an event I spoke at. Nobody at the event could recall any success anecdotes.

  14. Ed Dowd mentioned the vaccines have killed 800K Americans and disabled 4X as many as killed, 3.2M since the vaccine program began.

  15. The peer-reviewed scientific literature published a paper by Mark Skidmore showing over 217,000 deaths in 2021 alone due to the COVID vaccine. But they are looking at retracting the paper because Mark didn’t include a full bio on one of the funders of the study. Also, he asked a question about deaths from the COVID vaccine and that’s unethical (COVID virus questions are OK and ethical).

  16. Josh Stirling looked at how cities in the US did in 2022 vs. 2021. So it’s a longitudinal study where you compare the city with itself one year ago. This is the best way to see what is going on… did your mortality increase or decrease. Check this out: cities with higher vaccination had larger all-cause mortality increases than cities with lower vaccination rates. In other words, the line goes the “wrong way.” This is devastating for the narrative, but of course consistent with what the death reports are saying. The R2 doesn’t need to be .9 for this to be convincing. They are correlated and it’s the slope of the line that is significant. The slope is the wrong way. That’s the point.

    US cities; all ages; compare 2022 vs. 2021 in the same city The line slopes up. In other words, the experts were completely wrong: the vaccines are deadly. This is very compelling proof of harm that is impossible for anyone to explain away with a straight face. When combined with this analysis, it’s not credible to keep claiming the vaccines are safe and effective.

    Ages >65 version of the above

    Ages <65 version of the above

If the CDC doesn’t surface the statewide data for the public to see, then I believe it is time for the CDC to change their ads to look something like this:

I’ve had both the method and the data reviewed by UK Professor Norman Fenton. He’s the guy that proved the UK government data was fraudulent and cannot be used to prove the vaccines work (see the official full response at the bottom). Nobody else in the world had been able to do that. Nobody wants to debate Norman on any of his work because it is so impeccable. The top medical journals also hate him because he finds serious errors in key papers published in their journals (such as The Lancet and Science). He validated it as sound and reliable.

Others, such as Clare Craig of the HART Group, called the method described here “genius.”

How about a novel fully open peer review process for this analysis that is not subject to the whims of the scientific journals and shows to the public that the article cannot be attacked by anyone in the world?

You send me your wager via Solana blockchain and I’ll give you 10X your wager if you can show we got it wrong and the data shows the opposite conclusion.

Professor Fenton will judge your entry. He has high integrity and is on the side of truth.

The way it works is that you send me your wager ($5K to $10K worth of Solana) as your entry fee to: 9BBhGEfAMSHg8Mxyb4x67VKMhyomJ3MAPa9mqXtaP8xZ
with a comment with your contact info (or the contact info of your lawyer if you want to remain anonymous).

You can use Ledger Live or Phantom which supports adding a note to the transfer.

This will create a public record for all to see that you are accepting my offer. If you win, you get 10X your wager sent back to the address you sent your funds from. If you lose, you lose your deposit. This ensures people aren’t wasting my time with non-serious challenges.

Also, the size of the wagers tells you how confident people are in their analysis. I predict no one will wager anything. If I’m wrong, I lose a lot of money.

I’m kept honest by the public nature of this. People could legitimately discredit me if I don’t honor my offer. That would be a first.

Your burden is to show that my analysis of the data is flawed and that the data that was submitted to me actually shows the opposite: that the vaccines are saving lives.

People can look at Solscan to see the entries so that everything is in full public view. No gaming is possible. If there is a transaction, you can look at the “Memo Program V2” to see the notes for who is challenging me.

Fenton’s decision will be in writing as well and subject to public scrutiny. He has no history of not following the science. If you can produce evidence of this, I’m happy to pick another judge.

So if there are no challenges at my 10:1 odds, it’s de facto proof that I’m right.

It’s a novel method of public peer-review that is impossible to game or censor. It is open to anyone worldwide.

Make my day. Or as data scientist Joel Smalley might say, “Put up or shut up.”

My offer is open to the drug companies as well or any other institution.

Terms:

  1. Offer terms can be changed at any time (e.g., I may want to raise or lower the min/max bet).

  2. Send wager to: 9BBhGEfAMSHg8Mxyb4x67VKMhyomJ3MAPa9mqXtaP8xZ

  3. Min/max wager is currently: $5/10K

  4. First come, first served. The Solana blockchain is the source of truth for the entry timing.

  5. Maximum of only one winner. If someone wins, any deposits received after that person will be refunded to the address of the sender.

  6. Disputes will be settled by JAMS mediation.

  7. Your sending me the Solana with the contact info signifies your acceptance of the offer.

  8. Professor Norman Fenton will judge your submission in a live Zoom call that is recorded and publicly broadcast. You will have 1 hour to present your argument. He will put his decision in writing and post it to his Substack.

  9. To win, you must show that the data shows, for all age cohorts, that the vaccines are neutral or beneficial. You can show this using my data (preferred), or, if you can convince Fenton that my data is unfairly biased, you can use it on your own dataset provided you can convince him that your data was fairly collected in a neutral manner (which includes complete state data joining the death and vaccination database tables). If the data is privately collected, prospective collection by a neutral party is preferred since otherwise the provenance of the data would be hard to prove.

  10. You can attack the method, the data, or both to prove your point and make your case.

  11. Offer expires March 30, 2023 to encourage submission.

  12. You can request a written, legally enforceable definitive agreement if you don’t trust me. Use the Contact Me link and include the name and phone number of your attorney so we can work out the details.

  13. Anyone can enter, individuals, corporations, etc. including, but not limited to:

    1. CDC Director Rochelle Walensky

    2. All the vaccine makers

    3. Tom Shimabukuro and his pal John Su of the CDC (these are the guys who hid the 700+ safety signals from the world; see this article on the death safety signal and this article on 700+ safety signals)

    4. The people at the CDC and FDA who put me on the email block list so that I was not able to speak at the public comment section of the FDA or CDC meetings which violates my rights to free speech… I get it ….. if you can’t argue based on the data, you censor your opposition. That’s the way science works at the FDA and CDC.

    5. Tedros from the WHO who just declared COVID to still be an emergency…what a fruitcake!

    6. UCSF, Stanford, Harvard, MIT, …

    7. Executives at YouTube, especially those involved in censoring truthful content

    8. All LinkedIn executives involved in the decision to ban me for life on LinkedIn

    9. Medium CEO Ev Williams for supporting the decision to ban me for life

    10. All Wikipedia executives for supporting the decision to ban me for life and supporting the efforts to trash my Wikipedia profile to make me look like a menace to society. And how dare you remove my National Caring Award from my Wikipedia profile. You are a truly evil and corrupt organization.

    11. Stanford Professor and ACIP Chair Grace Lee who would rather call the Palo Alto Police on me than watch the video from the Israeli Ministry of Health proving the vaccines are not safe. Watch the video; it is a classic (Pierre Kory loved it).

    12. CDC

    13. ACIP and VRBPAC committee members

    14. The comedy team of US Surgeon General Vivek Murthy and Ashish Jha

    15. ZDoggMD

    16. Dr. Susan Oliver (along with her dog Cindy Oliver)

    17. Your Local Epidemiologist (YLE)

    18. David Gorski

    19. Jonathan Jarry

    20. UPenn Professor Jeffrey Morris

    21. Paul Offit

    22. Peter Hotez

    23. Truth warrior Dr. Angela Rasmussen

    24. Eric Topol

    25. Anthony “I am the Science” Fauci

    26. “Debunk the Funk” aka Daniel Wilson

    27. Bob Wachter, Dean of Medicine, UCSF

    28. Lloyd Minor, Dean of Medicine, Stanford University

    29. Harvey Cohen, Stanford University

    30. 60 Minutes

    31. The New York Times

    32. The Wall St. Journal

    33. The Washington Post

    34. The BBC

    35. Reuters Fact Check and any other so-called “fact checker”… and even Dr. Adrian Wong

    36. All of the members of the CETF SAB… the ones who said I was wrong and that they never wanted to speak to me again

    37. Any member of US Congress

    38. Any world leader who is pushing these vaccines

    39. Any health official anywhere in the world who is pushing these vaccines

    40. Neil deGrasse Tyson… who hung up on me when I challenged him on his bullshit statement that the vaccines have saved millions of lives. Give me a break.

    41. Their champion (if I can find him/her)

What a joke. None of these people can show I got it wrong.

Not a single one of them has publicly called for exposing the data so the public can learn the truth.

They are all afraid of the truth, the whole lot of them.

And if they can’t show I got it wrong, they should publicly admit I got it right. That would be the right thing to do.

The burden of proof is on the authorities to show that the vaccine is safe especially now since most people are not taking the shots.

They should produce the death data and make it publicly available for analysis. That would end the debate.

Ideally, for every person who died in 2019 to the end of 2022:

  1. Age

  2. Date died

  3. Date of each vaccine

  4. The vaccine type for each shot

  5. The total number of doses given

Image

The elephant in the room that nobody wants to talk about is that it is primarily the vaccinated that are “dying suddenly.” In fact, did you know it is unethical for papers submitted to technical journals to talk about vaccine deaths? Wait till you hear about Mark Skidmore’s paper showing over 200K killed by the COVID vaccines in year 1 and the objections they are raising.

The method presented in this article is a simple, straightforward analysis that can be used with death records to reveal the truth about the vaccines.

The results I obtained from over 1,500 death records are self consistent and are consistent with other data we have collected. I wasn’t surprised at all to get this result.

If anything, the vaccinated should have done better than the unvaccinated in this survey because of the healthy patient bias effect. But, as we found, it did far worse. Reading the comments in the death submissions confirms that a large number of cases are vaccine related.

Also, it is remarkable that the #1 feature of a vaccine death is “died suddenly.” Does that sound familiar?

The study cannot be attacked as “biased” unless you can explain how my followers can either 1) cause the premature death of vaccinated friends OR 2) deliberately ignored instructions to report the person they knew the best and instead they all followed a different set of instructions that they magically all agreed on.

That’s far fetched because:

  1. Most people who reported a death only knew one person who died. So it’s not like they can choose the “best” answer.

  2. Because they are my followers, they’ll want to help me and that means following my instructions which was to choose the friend whose details they knew the best

  3. At the time the survey was done, nobody knew how the data would be analyzed, not even me. They would have to ignore the instruction they were given and instead follow the “proper algorithm” in massive numbers. Why would they ignore my instructions? They are my followers and want to help me! And how would they know the “correct” instructions?

So where’s the evidence of bias?

There are only three ways to legitimately attack this study:

  1. Show an error in the methodology and show us our data that is correctly analyzed and where the medical community agrees you have the CORRECT analysis.

  2. Show an error in the data. I’m happy to have someone contact random people who answered the survey to ask those people if they followed the instructions to report the person they knew the best or not and if not why not.

  3. Show us a larger dataset showing the opposite result where we can verify every record with the primary data source. For some reason, no government will show us the record level data where the death age and date of death is tied to the vaccination records. Critical thinkers want to know: if the vaccine is so safe, why is this data being hidden from public view?

The bottom line: the COVID vaccines increase your chance of dying for every age group (that we had sufficient data on) and should be immediately halted. They are the biggest mistake in modern medical history. This analysis is completely objective, the data is very consistent, there is no evidence of bias that could explain the outcome, and there is no escaping the truth.

The medical community needs to take sides on my article and stop sitting on the sidelines. They have an ethical obligation to immediately either:

  1. call for a halt to the COVID vaccines or

  2. show us how we got it wrong by either showing the correct analysis or by producing a more comprehensive dataset.

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