Jay Bonnar’s anecdote is statistically impossible if the COVID vaccines are safe

August 7 | Posted by mrossol | Critical Thinking, Mandates, SADS, Science, Transparency[non], Vaccine

Source: Jay Bonnar’s anecdote is statistically impossible if the COVID vaccines are safe

Jay lost 15 of his friends who all “died suddenly.” All were vaccinated. Four dropped dead within 24 hours of the shot. 3 of the 4 were ~30 years old, perfectly healthy before their death. Whoa.

High tech sales executive Jay Bonnar, age 57, had 15 of his direct friends (not “friends of friends”) die unexpectedly since the COVID vaccine rolled out. All his friends who died were vaccinated. In his entire life, he’s never had any friends die unexpectedly. Zero. If the vaccines are safe, the chances of this happening are near zero. In other words, Jay’s experience is proof that the vaccines are causing people to die unexpectedly. Think I’m wrong? Where is your anecdote showing that the vaccinated are dying unexpectedly at the same rate as the vaccinated? Sure, those anecdotes should be TRIVIAL to find!

Executive summary

Most people who call themselves “scientists” are dismissive of anecdotes, especially if the numbers are small (such as less than 20). They are fond of educating people that “the plural of anecdote is anecdotes, not data.”

This is simply untrue.

A single, independently-verifiable anecdote can be extremely powerful. It can totally destroy the scientific consensus and prove beyond any reasonable doubt that the CDC is lying.

I’m going to show you an example of this in this article.

One guy whose verifiable story completely blows the “safe and effective” narrative.

I’ll show how we can apply various statistical analyses to Jay’s story to show convincingly that what Jay observed cannot happen by chance and cannot happen if the vaccines are as safe as the FDA claims.

The only way to explain Jay’s story is that the COVID vaccines are killing around 1 person per 1,000 doses as I’ve said before.

Jay’s story aligns with my estimate and is impossible if the vaccines are safe.

Jay’s story at a glance

  1. Jay is a 57 year old sales executive in Seattle, WA
  2. Jay has 7500 direct friends that he knows personally; he estimates 75% have taken the COVID vaccine: 5,625 vaxxed and 1,875 unvaxxed.
  3. 0 unexpected deaths in Jay’s history prior to the vax rollout; this includes during COVID, but before the vaccine.
  4. Since the COVID vaccines rolled out, Jay has lost 15 friends, all vaccinated, who died “unexpectedly.” None of his unvaccinated friends died.
  5. 4 of his 15 friends who died died within 24 hours of their COVID vaccine. I’d call this a smoking gun. It’s a clue as to what might have killed them.
  6. 3 of the 4 “same day” deaths were in people who were 30 years old
  7. None of them had COVID at the time they died or just before they died. Everyone who got vaccinated and died had COVID at least once. Jay estimates his vaccinated friends are getting COVID at a rate easily 4X more than his unvaccinated friends.
  8. Jay estimates he has roughly 7,500 friends (email contacts, LinkedIn contacts, etc). These are all direct relationships where Jay has spoken directly to that person.
  9. Before the COVID vaccines rolled out, Jay had never, in his entire life, known anyone who died unexpectedly. This means when he heard of the death, he would react as “wow, that was totally unexpected.” So someone who is involved in a traffic accident isn’t unexpected because accidents happen. Someone who has a long history of heart disease who dies from heart disease isn’t unexpected. Someone who is very old dying from natural causes or an accident isn’t unexpected. An unexpected death means the person was fine the day before they died and then, was dead the next day. For example, a 20 year old who is totally fit dies in his sleep. Or a 40 year old develops a “turbo cancer” and dies a couple of months later.
  10. Jay is the very first person I’ve talked to who personally knew more than 10 people who died unexpectedly and who was willing to disclose their names so that third party fact-checkers could verify the information was true. This makes his story unique. So Jay wasn’t cherry picked from thousands of anecdotes. He was simply the first person who spoke to me who had a large enough sample to be statistically interesting and who could reveal names so that his story could be verified.
  11. However, even if I talked to everyone in the world, I wouldn’t be able to find anyone with Jay’s story if the vaccines were perfectly safe and not causing unexpected deaths (I’d have to chat with at least 2e21 people to find such a person which is 12 orders of magnitude more people than on planet Earth).

The interview

You can watch the interview with Jay here. I summarize all the key points below.

Key takeaways

The key takeaways are:

  1. The COVID vaccine is killing people at the rate of 1 per 1,000 doses. Jay’s data is exactly aligned with this. There were 14,000 estimated doses among his vaccinated friends and 15 of them died unexpectedly.
  2. The CDC and FDA are lying to you by claiming the COVID vaccine is safe (which means kills 1 in 1M). The probability the FDA is right is poisson.sf(14, .014)=

    1.2e-40 which basically says there is no way the FDA is right (14,000 doses should yield .014 deaths per the FDA, and Jay observed 15; we have to subtract 1 because the survival function is >X rather than >=X).

  3. There is no other way to explain away this data. For example, even if Jay is “more aware” of deaths now which accounts for the dramatic rise in unexpected deaths he observed post-vaccine, the sheer number of unexpected deaths Jay experienced relative to the size of his friend network make this an anecdote that cannot be dismissed with hand-waving arguments about heightened perception; it just means that one of the many mathematical analyses (rate before COVID vs. after COVID) could be attacked.
  4. The rate of unexpected deaths is probably around 100X higher than it was before the COVID vaccines (which was very small). Virtually all the increase in this category has been driven by the COVID vaccine. So, for example, in the last 55 years, Jay never had an unexpected death. But say he’s only noticing this since age 35. So 20 years, no events. Now he’s averaging 6 per year. So if he had one death in the 30 years, that would be a 120X increase.
  5. Note that athlete sudden deaths increased by just 19X (538/yr vs. an average of 29 per year per GoodSciencing.com), but there was a baseline of 29 expected deaths per year; the number of unexpected deaths (where people just died unexpectedly was likely <20% per year so 6 deaths that were truly unexpected, so the net new number of unexpected deaths is 509/yr vs 6/year is nearly a 100X increase).
  6. The only way to explain Jay’s evidence is that the COVID vaccine caused the 15 excess deaths.

Jay Bonnar saw a lot more black swans than is humanly possible if the CDC is telling the truth

Basically, Jay Bonnar saw 15 black swans recently even though the CDC claimed that black swans (people who died unexpectedly from the COVID vaccine) are really rare.

There is no way that the CDC can gaslight this by pointing to studies claiming that there are a small number of black swans out in the wild.

It happened and it’s verifiable: Jay saw 15 black swans.

In fact, it’s even worse. Four of the people who died were double-black swans (died on the same day as the vaccine); these are 180X rarer than just black swans!

The CDC essentially said the vaccines are safe which means they kill fewer than 1 person per million doses. So Jay’s vaccinated friends, with 14,000 doses, should have experienced .014 deaths according to the CDC, but instead ended up with over 1,000 times that number of deaths. The chance of that happening just by random “bad luck” to Jay is 1.2e-40 for Jay to see 15 or more black swans (this is given by the survival function poisson.sf(15-1, .014)).

Jay’s story is basically unexplainable if the CDC is telling the truth and the COVID vaccines are perfectly safe. \

The CDC is lying. The COVID vaccines are unsafe. It’s a mathematical certainty.

In short, Jay saw way too many black swans for us to believe the CDC that black swans are really as rare as they claim.

Anyone can verify his anecdote (because he lists all the names) and anyone can do the math.

Conversely, based on my estimates of 1 death per 1,000 doses, we get poisson.sf(14, 14)=0.42956328717262765 which means my explanation is perfectly reasonable whereas the FDA’s is statistically impossible.

If I’m wrong, simply explain how Jay could see so many black swans among his 7,500 friends.

How I met Jay

Jay subscribes to my Substack. He filled out a survey and I called him to verify his survey entry. It was then he mentioned his story to me.

Jay’s friends who have died

Died within 24 hours of COVID vaccination (4):

  1. Scott Plutko, 53, – work colleague, SVP of Global Channels, Saviynt; talked of getting boosted “to do the right thing” and 24 hours later had a massive heart attack and dropped dead in front of a live audience in London during a tech presentation.
  2. Alexander Nuber, 31 y.o. Man, worked out at my gym, perfectly fit and  healthy. We spoke in person about how eager he was to get the C19 injection. He received it and four hours later dropped dead at home. Doctors were baffled. No obituary.
  3. Zach Briton, 30, personal trainer, worked at my gym. Had a heart attack on the same day as the shot and died just days before his 31st birthday. He told other people at the gym he had received C19 injections.
  4. Andrew Titus (nephew) – 28, perfectly healthy collegiate lacrosse athlete, died suddenly in sleep right after getting the shot; had received both injections and several boosters. Doctors were baffled as to the cause.

Other unexpected deaths (11)

  1. Alejandrino Taculad (former father-in-law), 78, received injections and boosters. 60 days later was diagnosed with stage 4 lung cancer. Never smoked or drank alcohol a day in his life; died 90 days after getting the jab.
  2. Matt Runte, 44, Seattle firefighter; I knew Mark through friends in the first-responder community. Mandated to get the jab. Was out for a jog and just dropped dead.
  3. Jessica Wilson, early 30’s  – Seattle mom, my kids attended the same school where hers did; couldn’t volunteer as room mom w/out the jab per Gov Inslee mandate, blood clots in lungs weeks after injection and died suddenly one week later.
  4. Dori Monson, 61, radio talk show host, met through friends – died of “cardiac event”; he was vaccinated and spoke of his regret for getting it prior to death.
  5. Chloe Nuttbrock, 18, Mukilteo HS student – aneurysm, daughter of a friend/neighbor, vaccinated. Had migraines after covid vax. Died 1 week later.
  6. Gabriel Jungmann, 20, of Bellevue – died suddenly while showering; vaccinated.
  7. Chris Smith, 31, heart attack – XFL athlete, went to my church, vaccinated per league requirements.
  8. Rachel Marshall, 42, owner of Rachel’s Ginger Beer – died suddenly (cardiac arrest). I was a customer at her shop (but stopped going after they required vaccines). Vocal vaccine and mask proponent.
  9. David Black, 55, work colleague (Boeing), died suddenly (cardiac arrest); no known health problems; Boeing has mandatory vax requirement.
  10. Steven Hahn, 54, church member, died suddenly and unexpectedly from “heart problems” – wife said he had been vaccinated. Nobody can explain this. No known health problems. Super-healthy guy.
  11. Michael Howland, early 40’s, died from a heart attack just walking on the beach while on vacation in Cancun, Mexico with family, super fit. Triathlete. Company had a C19 injection mandate.

Injured (7)

  • Rosalinda Taculad (former mother-in-law), 70, had a massive stroke just 1 week after her second injection. She is permanently disabled now; her husband Alejandrino died 120 days after his injections.
  • Hannah, friend of my wife – 25, perfectly healthy, stroke and paralysis, permanently disabled a few months after getting the jab. Told me how excited she was to get the C19 vaccine so she could “get on with life.” Refuses to admit it was the vaccine. Believes she was injured because she was working too hard (50 hours/week). Doctors baffled as to how a 25 year-old could be disabled. Her vertigo is so bad that she can’t work. Tinnitus. Paralysis. Constant pain. Thousand needles. No relief.
  • Steve, former manager at work – VP Sales, 52, heart attack 1 week after his booster; Steve was a vocal advocate of the injections, tried to convince me to take it “to do the right thing” and stated everyone in his family would be vaccinated (see below).
  • Steve’s 16 yo daughter – HS soccer star, full scholarship to Univ of UT, heart attack after booster and permanently disabled; had to have a pacemaker installed for the rest of her life. Her heart attack happened while Steve was in the hospital recovering from his heart attack.
  • Steve’s daughter’s 16 year-old boyfriend – HS football star, heart attack after 2nd injection, can never play sports again. The boyfriend had his heart attack 2 weeks after Steve’s daughter. All three of them (Steve, daughter, boyfriend) all went to the same doctor to get injected together. They all had cardiac injuries within 1 to 2 weeks of each other.
  • Ryan, friend in Canada – His perfectly healthy 16 y.o. daughter had a heart attack just one day after she got the booster. Diagnosed with Type 1 diabetes one month post injection. Previously perfectly healthy. Now has an implant in her kidneys. She’s now 17. The parents divorced over this incident.
  • Gary – 52 y.o. Man, perfectly healthy and extremely fit. MMA fighter. Runs a security company in the Seattle area. Didn’t want to do it, but was forced to get jabbed by his employer. Gary got the shot at noon and that night had a heart attack. Had to be rushed to the ER. After 3 weeks, he had to get the second shot to remain employed. Today he can’t exercise. Can’t do a push up or walk up a flight of stairs. He can no longer work.

Last names in some instances are withheld since Jay doesn’t have family permission to speak about them. The rest of the injured are 2nd hand accounts (over a dozen), friends of friends, and I don’t have last names or details other than the victims being mRNA injected and are severely or permanently disabled, cancer, diabetes, etc., with no previous medical issues pre-injection.

Analysis by Professor Norman Fenton: there is only a 1 in 75 million chance the vaccine is “safe” (i.e., doesn’t raise the mortality rate)

Evidence used: Only the vaccinated died, none of the unvaxxed died, and 4 of the vaccinated died on the same day as the shot was given.

Conclusion: the combined evidence results in a probability of only 1 in 75 million that the vaccine is safe (i.e., that the vaxxed mortality rate is no greater than the unvaxxed mortality rate).

Here’s why:

Let H be the hypothesis: “vaxxed mortality rate is no greater than the unvaxxed mortality rate” (i.e. vaccine is safe)

By Bayes if we start with the assumption that P(H)= 0.5 (i.e. 50%) (strictly speaking we assume the mortality rates of the vaxxed and unvaxxed are uniformly distributed between 0 and 100%) then if we observe 0 deaths from 1875 unvaxxed and 15 dead from 5625 vaxxed the posterior probability of H becomes 0.011 (i.e. 1.1%)

So we now have a revised probability P(H)=0.011

But Let E be the evidence of at least 4 out of 15 deaths on day 1 of the vaxxed.

Now if H is true we know that the probability of observing a death on day 1 (of the 182 days) is 1/182 which is 0.0055.

Using the Binomial theorem the probability of at least 4 deaths out of 15 on day is approx 0.0000012 (about 1 in 833,333)

So we know that P(E given H) = 0.0000012

By Bayes theorem

P(H given E) = P(E given H)*P(H) / [ P(E given H)*P(H) + P(E given not H)*P(not H)

But we know P(H) = 0.011 and P(E given H) = 0.0000012

We can also assume P(E given not H) = 1 and we know P(not H) = 0.989

So plugging these values into Bayes Theorem gives a result of the posterior probability of H

P(H given E) = 0.000000013347

Which is about 1 in 75 million.

Poisson analysis: Jay saw 15 deaths, but the CDC said there should only be .014 deaths among his friends

Chance of seeing 15 or more deaths when the CDC predicted .014 (1 death per 1M doses and there were 14,000 doses estimated):

>>> poisson.sf(14, .014)
1.1741428985146716e-40

In other words, the CDC is lying. There is no way the vaccine is as safe as the CDC claims.

Could the vaccine not be as dangerous as I think? Could it only be killing, say, 1 person per 10,000 doses (i.e., 10X lower than I estimate)? Let’s find out:

>>> poisson.sf(14, 1.4)
3.2132609254362016e-11

Nope! This is quite stunning.

It’s basically a certainty that the COVID vaccines kill at least 1 person per 10,000 doses at a bare minimum.

Which means that the vaccines aren’t even close to being safe.

And it means that giving a vaccine to a child who has a 1 in 1M chance of dying is insane.

You’ll easily be killing 100 kids or more for every kid you might potentially save if the vaccine worked.

Poisson analysis: unexpected death rate pre-vax vs. post-vax

How about the observation that Jay never observed any unexpected deaths in his entire life and now, just in the last 2.5 years, observed 15?

Let’s estimate the rate of unexpected deaths in Jay’s life. Suppose he wasn’t paying attention to this until age 35. Also the death rates of his friends should double every 10 years.

He had zero deaths until age 55. So let’s say we call this 1 death in 10 years to be conservative.

So that is .25 deaths in a 2.5 year period.

So to see 15 or more deaths in 2.5 years would be:

>>> poisson.sf(14, .25)
5.634558720450966e-22

which is of course never going to happen. This means that Jay’s observations of sudden deaths didn’t happen by chance.

Could it be that all of Jay’s friends are anti-vaxxers and making him aware of sudden deaths that he would have been aware of before if they were paying attention pre-vaccine? Yes, it’s possible and this makes this analysis the most suspect since “heightened awareness” can influence the outcome. But unexpected deaths are fundamentally just that: unexpected and would be expected to happen at a very low rate in normal times.

Poisson analysis: 4 deaths within 24 hours of the vaccine

If the vaccines are perfectly safe, then observing 4 deaths out of 15 deaths within 24 hours of a vaccine is pretty unlikely. So this analysis is just using the deaths… we can see how unlikely this is.

We have 15 deaths within a 6 month period between vaccines (to make life easier in our estimate). We can think of the 6 month period as days after vax.

We expect to see 15/180= .083 deaths in a day on average after a vaccine shot assuming that people get vaccinated every 180 days and 15 people died.

Given that average daily rate of deaths, the chance of 4 or more deaths within a day is given by the survival function:

>>> poisson.sf(3, .083)
1.8505637692983056e-06

which is very unlikely. But since we didn’t factor in the other key factor (all the deaths were in the vaccinated group), this is just a lower bound estimate.

This again confirms that the COVID vaccines caused the deaths of his friends within 24 hours of the shot; Jay didn’t get “unlucky.”

Fisher exact test analysis

This is using people rather than person-years to make it easy.

We had 5,625 vaxxed with 15 deaths and 1,875 unvaxxed with no deaths.

A Fisher exact test on this gives:

p=.013

95% CI for the odds ratio(1.197265283117275 to infinity)

which means we are 95% certain that the vaccine is elevating deaths and that there is only a 1% chance this result happened by random chance.

So of all the tests, this is the weakest because it makes the fewest assumptions.

How do you explain the Pfizer Phase 3 trial where only 21 deaths in the vaccine group and 17 in the placebo group

Some people claim that the vaccine has to be safe. If it really killed 1 person per 1,000 doses, there would be 44 excess deaths in the vaccine group.

Not necessarily. See this explanation.

Jay isn’t an isolated example

I asked if anyone else had seen 10 or more deaths on Twitter. Not surprisingly, I got a number of stories similar to Jay’s. Here are some of the responses when I asked if anyone knew more than 10 people who died suddenly in 2021 or later. I didn’t ask for the breakdown of vaxxed vs. unvaxxed.

What I got were stories consistent with what Jay observed:

After I DM’ed him, one of the messages he sent me was this:

More responses (you can click on each response to see the original post and replies):

There’s a very consistent pattern here. Can you see it? It’s the vaccinated who are mysteriously dying, not the unvaccinated.

Why it isn’t COVID

It’s very unlikely it was the COVID virus because:

  1. None of his unvaccinated friends died unexpectedly (and Jay is not alone) in the entire 3.5 year period since 2000.
  2. None of his friends died unexpectedly in 2020 (post-covid, pre-vaccine).
  3. COVID isn’t a factor in any of the stories, but the vaccine is common to all of them.

Fact checker notice

I welcome fact checking this article. All the names of the dead are listed. If you have trouble verifying any of the stories, please let me know. I’m happy to cooperate so that this story gets mainstream media coverage like it deserves.

It’s important to get the truth out to people.

Summary

Jay’s anecdote cannot be explained if the vaccines are safe.

We are left with the conclusion that the vaccines are not safe.

Jay can’t be credibly accused of making this story up. The names of those who died are revealed and how he knows them. Jay will assist any fact checker with verification of vaccination status for those who died.

All the deaths he cited were people he knew. And all died unexpectedly.

The statistics for just this one anecdote are consistent with the statistics I’ve found in earlier investigations and yet again confirm what we’ve known for a long time: the CDC is lying to people. The COVID vaccines are unsafe. Nobody should take them.

The reality simply doesn’t match the rhetoric. When that happens, reality should always win.

Yet in our society, the medical community prioritizes rhetoric ahead of reality. That’s a big problem.

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