"Vaccine" killed 3.5X more Americans than COVID virus
The data is clear and consistent. I challenge any qualified scientist to challenge this data in an open public debate.
Executive summary
The irresponsible attacks by an LA Times journalist Michael Hiltzik (see Column: Why anti-vaxxers are pretending a flawed study on vaccine deaths has been vindicated) on MSU Professor Mark Skidmore’s paper motivated me to run my own survey of my readers to see what the actual harm numbers really are.
Over 10,000 readers responded.
The results were not anonymous. To respond and be counted, you had to include your contact information.
This is a huge benefit compared to a “scientific survey.” In a “scientific survey,” you normally aren’t allowed to collect the identity of the responder, so it must be anonymous. So in a “scientific survey,” the peer-reviewers cannot verify whether the research was telling the truth or not. In my survey, they can. Which one is more trustable? After all a key attribute of “scientific evidence” is that is can be independently verified. Mine can. Relatively few published studies (on most topics) cannot be because they never disclose the record level data.
The survey clearly showed that the COVID vaccines have killed 3.5 times as many people as COVID. This is a disaster.
I’ve had expert statisticians and epidemiologists review the survey, the methodology, and the results. None could find any errors.
I’m willing to put a million dollars on the table that this is right and that the vaccines have killed more people than COVID. Any takers? If not, why not?
When I called Professor Norman Fenton and informed him of the 3.5X figure he calmly replied “I’m not surprised.”
The results of this survey are entirely consistent with the surveys by others as well as individual anecdotes that would have been very unlikely for me to have located if the vaccine didn’t kill at least 3.5X more people than the virus.
Therefore accusations of “the survey was biased” are simply “hand-waving” arguments with absolutely no evidentiary basis of support. Could there be bias? Of course. Is the bias significant is the question! Since these people are anti-vaxxers, they are simply less likely to vaccinate and so the number of vaccine injuries will be LOWER than an unbiased group who vaccinates. So yes, there may be bias, but if anything the bias suggests that the actual ratio is higher than 3.5. I’m happy to have that discussion. Bring it on.
The best way to challenge these results is to show data that is 100% independently verifiable (which government statistics are not). So they will have to show us their survey and their verifiable anecdotes supporting their hypothesis. No one has any interest in doing that for some reason. These people are all perfectly content with having the number be “unknown.” I have a big problem with that.
Finally, if any epidemiologist(s) with a h-index of 20 or more wants to publicly challenge the 3.5X result in an open public discussion, it’s easy to contact me. The h-index is simply a way to ensure we have a meaningful level of discourse. The people on my side of the debate table will have a combined h-index of over 100.
Important statement by UK Professor Norman Fenton concerning this research
Professor Fenton’s h-index is 65.
Professor Fenton’s research on the UK government data revealed their data was flawed and it still is today. The UK ONS, the government agency responsible for the data, publicly acknowledged that they were mistaken and that Professor Fenton was correct.
Fenton’s group was the only team in the world to publicly call out the data as flawed and get a confirmation from the government authority that they were correct.
So it is safe to say that Professor Fenton is more qualified than most people to opine on data quality issues.
Here’s what he said about this research:
The data
Having record level data available where every record can be independently verified is critical. The other critical thing is making all the record level data publicly available.
I’ve done both. The health authorities NEVER do either.
Here are the links:
The survey responses (over 10,000)
The Excel analysis of the first 9,620 responses which shows the responses are consistent with a Poisson distribution and also that hundreds of random 10% draws from the data do not change the outcome that the vaccines have killed at least 2.5X more people than COVID.
The survey had 10,000 responses.
Analysis of the first 9,620 responses found 804 deaths from COVID and 2,830 deaths from the COVID vaccine. Those results were generated from a minimum of 108,000 people covered by the survey (some extended families were over 25 people and the survey didn’t track this so the number of total family members covered by the survey is a lower bound). We also didn’t ask about the age of each family member as this would have made the survey unmanageable. We were primarily interested in simply the ratio of COVID deaths to vaccine deaths in the extended family (excluding the immediate household). The reason for excluding the immediate household is to reduce the bias effect since most of the respondents didn’t vaccinate themselves or their household. This is reflected in the lower ratio for the household statistics (and even then, the vaccines killed more people than COVID which is astonishing).
The analysis
No fancy math is needed to calculate the ratio: 2830/804=3.5X.
It is simple and straightforward. No sleight of hand. No trickery. No Cox Proportional Hazard manipulation. It’s all verifiable raw data.
We did other tests to see if the data looked like it was generated from a Poisson distribution (which is what deaths look like statistically) and we took random 10% draws to ensure that the data was consistent throughout all 10,000 responses. We found that was the case.
Fact checkers welcome here… come on in… I have nothing to hide
I’m happy to have independent fact checkers validate each of the entries with the submitter directly (subject to their consent of course).
The deal though is that if you want to validate the data, you have to agree to publish your findings.
Independent validation / Sanity checks
At first, you may think “3.5X… that’s way too high. Surely these anti-vaxxers are misclassifying normal deaths as “vaccine deaths.”
There are 10,000 different people making these assessments. We can randomly draw 100 names and check on the details of each death to assess whether this is the case.
But there is a much easier method to validate that the 3.5X number is sane: a single anecdote that is 100% verifiable.
Jay Bonnar anecdote (method #1)
I reported earlier on a high tech sales executive Jay Bonnar who told me 15 of his friends “died suddenly” after getting the vax. His life experience otherwise is devoid of deaths. The stories are all in the public domain and are verifiable. They were all his friends; they all died suddenly after the vaccine. Jay also had 1 friend who died in the hospital from COVID after receiving Remdesivir (which is probably what really killed his friend, but let’s just give the COVID virus a death).
Jay’s observations are all objective counts of deaths. He did not make any subjective assessment as to cause. In the 10 years prior to the vaccine rollout, he had lost only 1 friend. Post vaccine he lost 15 friends, several of whom died within 1 week of being vaccinated. There’s a big signal there.
So if Jay saw one COVID death, with a 3.5 multiple, Jay should have seen 3.5 vaccine deaths. But he saw 15. The probability of that happening is 4.26e-6 which means that only 1 person in 234,515 would have observed a story like Jay’s.
This would mean that I’d have to have chatted with nearly 250K people to find Jay. I can assure you, that was not the case. Jay is one of my Substack readers (a typical article has around 100K readers) and Jay responded to a survey about something I was asking at the time. Only around 10K people respond to surveys. I called only 10 people to validate the survey results from the 10K respondents. When Jay and I were talking, he let me know about the 15 friends and that got my attention and resulted in an article about Jay’s friends.
Jay’s story is a powerful anecdote that simply would not have been found if the ratio of vaccine deaths to COVID deaths wasn’t at least 3.5x.
So that is a powerful validation that my survey, if it is wrong, is underestimating the factor, rather than over estimating it.
There are other powerful validators in addition to Jay’s anecdote:
#2: Wayne Root has numbers that are even more skewed: 30 to 1. The probabilities here are so astronomical that if the ratio isn’t at least 3.5X, a Wayne Root example couldn’t exist even if I interviewed every person on earth.
#3: The Rasmussen survey found the COVID vaccine killed as many people as COVID. This was done by an independent firm with an impeccable reputation. But this was done on the American public and 75% of the public believes the narrative, took the jab, and wouldn’t be able to spot a vaccine death (they would be gaslit by their doctors into believing it was just a coincidence, even if the death happened on the same day as the vaccine). So the deaths should be multiplied by around 4X so we are in the same 3.5:1 ballpark after the “blue pill” correction.
#4: I’ve done surveys on both Gab and Twitter, four months apart. These are on different platforms, done at different times, I have different followers on each platform, but the results of the surveys were nearly identical, finding a 3X to 4X higher death count for the vaccine deaths vs. COVID deaths.
So why are the Gab results lower than the X numbers?
The answer is simple: my Gab followers are mostly unvaccinated as you can clearly see below. If you don’t take the vaccine, it’s really hard to die from the vaccine. This anti-vax bias extends to family members so the numbers are lower than “reality.”
#5: Denis Rancourt’s recent work (180 pages) shows that the vaccine kills about 1.2K people per 1M doses. “He found no evidence that the Covid-19 vaccine has reduced overall deaths in any of these countries. In fact, the opposite seems to be true.” There have been 650M doses in the US, which would imply 780K deaths which is close to my 650K death estimate. The number of COVID deaths in America is vastly over inflated. A recent JAMA paper showed COVID is about 2X deadlier than the flu, and since flu deaths per year average 37,800 (which I got from Bard so I can’t be accused of cherry picking the number), an estimate of actual COVID deaths over 3 years (since Omicron is very mild), we can estimate that around 226,800 people (37800×3 years ×2 the death rate) were actually killed by COVID, so 780K/226800 = 3.44 which is remarkably close to the 3.5X factor from our surveys.
More on bias
All surveys have bias.
In my case, there is a bias for lower numbers because my followers are very under vaccinated and in many cases, their families are too. So this can result in lower vaccine deaths.
But there might also be a bias in assessing a death to be from the vaccine when it wasn’t caused by the vaccine. Experts can adjudicate these deaths and we can apply a correction factor that might correct in either direction. Here’s the interesting thing about this bias: I don’t think anyone knows which direction this bias is! I don’t. Do you? Were my readers more astute than trained professionals in assessing vaccine deaths? Or less astute? We can adjust for this bias, but the problem will be: who do you trust to make the professional assessments of the death? Any medical expert I suggest who I think is astute can be accused of being biased. So the bias accusation can always be made.
The simplest approach is the Occam’s razor method and assume that the assessments are “close” and consider this as one experiment that generates a value.
Or we can invite our critics to show us their data that properly corrects for all these biases (as if that is possible).
Then you look at the other experiments and look at the values that they produce. If you have 9 values that all strongly agree and 1 that doesn’t, you then can spend more time on the outlier trying to find a source of error. Failing that, maybe it is the 9 that agree that have the error, but that’s less likely.
In my case the numbers lined up well… all the approaches showed that the vaccine killed more people than COVID and should be halted. The numbers I got in this survey didn’t surprise me, they didn’t surprise my colleagues, and the anecdotes are consistent with the numbers. I love anecdotes because you can verify all the facts whereas you cannot do that with government data (the UK data being the perfect example of totally useless and misleading data). For every person who claims “your survey is biased” I can say in response that “your government data is biased.”
Biases are a part of life. You try to adjust for them when you can do so accurately.
Why is nobody taking my $1M bet? Answer: Because none of them believe their bullshit claims about the vaccine being safe
I’ve offered to bet anyone in the world $1M who thinks that COVID has killed more than the vaccine. What I continue to not understand is why nobody wants to take my money if the case is so obvious that the vaccines have killed fewer people than COVID. The most I got is a $500K bet from one person in Israel. That’s it.
Is he the only guy in the entire world willing to bet me? How come Pfizer and Moderna aren’t taking my challenge? How come none of the experts aren’t raising the funds for this “no risk” opportunity?
The reason nobody will bet me is that they don’t want to lose their money. It’s OK if you lose your life taking their advice, but they are so unsure they are right, they won’t risk their own money on their beliefs. It’s really that simple. They say it, but they don’t believe it. It’s all “big hat, no cattle.”
Verification method #6: How about the seriously injured who required medical care? The estimate from that data is that over 2M people were killed by the COVID vaccine.
Here is the OFFICIAL CDC data. It took over 1 year of legal work before the CDC would release this. Why? Because the CDC doesn’t want you to learn the truth. They kept this hidden from view. Why? Because it shows the vaccine is a train wreck.
What they couldn’t measure is deaths because dead people don’t fill out polls!
But our survey showed (looking at the HOUSEHOLD data (where people would have first hand knowledge of serious injury), that there were 8X as many household serious vaccine injuries (requiring hospitalization) as vaccine deaths.
So let’s take the V-safe data, 783K * 25 is nearly 20M deaths. Now divide that by 10X (just to be very conservative) and you get 2M deaths from the COVID vaccine.
So once again, we showed that there were more deaths from the COVID vaccine than from COVID, using a very conservative analysis.
There is no survey data anywhere to dispute this because the authorities do not want you to know the survey data. It took over a year for ICAN to convince the CDC to release the data (basically the CDC was finally “convinced” they were wrong to keep the health data secret by two lawsuits and a court order to release the data). Even today, the CDC still refuses to release the free-form data. There is a reason for that. If the data showed the vaccine was safe, do you think the CDC would be withholding that? Of course not!!!! They’d be giving it to CNN to parrot every night. They’d be mandating that every person download it and read it.
So when the CDC doesn’t want to disclose public health data, you know it is really bad.
#7: funeral directors
I verified with funeral directors that business is up significantly after the vaccines rolled out. And that the embalmers they work with are seeing these “clots” that they’ve never seen before in their career (but not all embalmers are noticing this).
All of these people were afraid to speak out.
One of the funeral directors said that people who got the COVID vaccine are getting COVID over and over… but not the unvaccinated. I told him I wish I had a nickel for every person who has told me that… I could retire!
One funeral director I talked to recently said in the span of 1 week in September, he had 3 very odd deaths: two 15 year olds and a 4 month old. Each of these is a rare event, he sees only 1 per year. So he got three “rare events” in just 1 week.
He also mentioned that child deaths are way up. There is a foundation that funds the funerals for young kids and he said the executive director had told him she was seeing a huge uptick in requests after the vaccines rolled out. I’ve reached out to the executive director.
#8: embalmers
There’s already been a lot written about this. For example, how can anyone explain this story: EXCLUSIVE: Embalmer reveals 93% of cases died from the vaccine.
If this wasn’t true, why would she lie?
In fact, her telling the truth cost her her livelihood. Her business dried up after the story was posted.
#9: Jay’s friends
Jay told me after his story appeared, he was contacted on one of his social networks by half a dozen other high tech executives who told Jay, “Yeah, we’re seeing the same thing.” After Jay encouraged them to talk to me, they all declined saying that they didn’t want to lose their jobs.
The sheer number of these “black swan” anecdotes has got to be very troubling.
It makes you wonder what kind of society we are living in, doesn’t it? People are afraid to speak the truth if it goes against popular beliefs.
#10: John Beaudoin’s analysis of the Massachusetts death data showed a 70x man-years mortality ratio of the vaccine vs. the virus. FULLY OBJECTIVE.
John agrees with the 3.5X number, but points out that if you look at the man-year impact, the vaccine has killed 70x more people-years than the virus.
John uses death certificate data from two states (Massachusetts, Minnesota) combined with Medicare data. He used 100% objective data from government sources 100% objectively processed.
This will be explained in his new book The real CdC which will be available on Amazon soon.
“Your survey isn’t scientific evidence, it’s anecdotal evidence”
This is just plain bullshit that is espoused by people who are not trained in science.
I am a scientific researcher. I devised an experiment to collect data. Each response is a data point, and when these data points are collected and analyzed, they can provide valuable information about a population.
Some of the questions are objective such as the number of people in their household. That is unambiguously scientific evidence. But some of the questions are less objective such as “How many people in your household died from COVID?” which calls for an opinion.
This is a limitation of the survey and is noted as a limitation. All scientific studies have limitations.
However, in my survey each of the responses can be verified independently by a team of independent scientific adjudicators because I collected contact information for each of the respondents. Independent verifiability is a key criteria for “scientific evidence.” In this case, we can obtain medical records, detailed case histories, etc. for each of the respondents. Each death can be judged by a panel of qualified experts.
So adding this extra step satisfies the most rigorous definition of “scientific evidence.”
Science is all inclusive. In science, all data is important. Science is all about explaining the data and making a determination which hypothesis better fits the available evidence. In many cases, data considered to be “high quality data” such as data from government sources such as the UK ONS can be much less reliable than data collected from surveys as Norman Fenton pointed out above.
There is an excellent op-ed by Norman Doidge that I highly recommend reading entitled, “Medicine’s Fundamentalists: The randomized control trial controversy: Why one size doesn’t fit all and why we need observational studies, case histories, and even anecdotes if we are to have personalized medicine” which points out the value of not discarding any data. If you got it right, all the evidence will be explainable and consistent.
At the end of the day, people should be much more concerned about getting the right answer and seeking truth than whether the data fit someone’s definition of a specialized term. Finding truth is the goal of science.
In short, for people who are skeptical of the raw data, there is a path to scientifically validate their concerns. This validation can be done on a random sampling basis.
It is interesting to note that not a single person expressed any interest in validating the data I collected. They all just want this study to go away. They do not know what the ratio is. Nor do they want to know. They simply want to create permission for themselves to rationalize ignoring the data so they can avoid the cognitive dissonance.
The first Community Note
This is the very best that the entire X community could muster in response:
I have addressed the issue of “anecdotal survey” in the section above. It was nothing of the sort! It didn’t ask “Tell me what happened after each family member was vaccinated.” It asked for objective data (a body count) about how many people died from COVID vs. the vaccine.
As for the second part, the CN refers to this paper which makes the claim that “the authors find very little evidence of an association between vaccination and mortality.”
The authors are from the UK ONS.
So the authors said that the mRNA COVID vaccine hasn’t killed anyone. That’s the essence. “Here, we show there is no significant increase in … all-cause mortality…”
Also, from the paper:
Let’s examine the latest UK ONS data which shows that their conclusion is wrong.
My article does that; it shows that fully vaccinated 18-39 year olds died at a rate 3.7X higher than their unvaccinated peers and how you can replicate this yourself. That’s what the data shows. This isn’t debatable.
That’s why they stopped publishing the data after that data came out!
I said, if the 3.5X figure is wrong, you need to tell me the CORRECT value. The CN ignores that. Come on. If you claim my number is wrong, you need to come to the table with the correct number. They failed to do this.
They also failed to explain the probability distribution function of the poll responses. It was consistent no matter how you randomly drew the samples. And it was also in the statistical form of a Poisson distribution. That’s really hard for them to explain. If these people are making up causality, it won’t have a Poisson distribution. You can only get a Poisson distribution by observation of a random event. How do they explain that? They don’t!!!!!!!!
Please go vote this community note and rate it as “Not Helpful.”
Thanks.
Other proposed CNs
I’m including these for completeness to show how weak their counterarguments are.
For the first CN, it claims that anti-vax people cannot accurately assess whether a death following a vaccination was caused by the vaccine. It claims that all of my followers “forget” that correlation isn’t causation.
In other words, if 15 of your relatives get the vaccine and then all die 3 hours later, this is simply correlation… it doesn’t mean the vaccine caused the death.
The author of the CN cites no evidence to back up his handwaving argument. It’s speculation.
Here’s my question: do my followers overestimate the attribution? By how much? Or do they underestimate the attribution? By how much? And how do you know?
This can be assessed by anyone wanting to do the assessment. But then we have to agree on who the gold standard assessors are? Peter McCullough? Paul Offit? See, even if there are professional assessors, you can’t know. That’s why you cite this as a limitation of the study.
And that’s why we rely on independent data to confirm the result. And the independent methods do that. The CN note does NOT explain how 6 independent methods reached the same conclusion.
The second CN says this is just a survey. But the problem is the CN does not explain how we can consistently get the same numbers, even on surveys done LONG ago with a different audience. How can they get the same numbers?
The latest CN (10/27/23)
The community voted to take down the first CN. So they replaced it with another CN that contradicts the first one (which claimed there were NO vaccine deaths).
Here it is:
Here are the problems with the “new, improved” CN:
This was not an “anonymous survey.” People had to supply their contact info. So the CN is factually wrong and deliberately misleading. They didn’t read the article.
It references this CDC page saying that page says there were only 9 vaccine deaths (I couldn’t find it on the page)! Which is it? 0 or 9? These numbers are preposterous. I personally can give you the contact info of the family members of 2,878 people who died from the COVID vaccine. Will any fact checker take me up on my offer? No possible way. As of August 4, 2023, the CDC has received 1,146 reports of death in people who have received a COVID-19 vaccine. That’s less than were reported to me. My reach is tiny, only covering the deaths from a base of around 100,000 people. Lets say my survey covered just 10M people without overlap. That would mean about 287,800 vaccine deaths. At 100M people (there are 330M people in the US), that would be 2.8M people who should have been reported to the CDC for investigation at a minimum.
The second reference in the CN is the ONS data. It is IMPOSSIBLE to get the vax:virus death ratio from this data. Nobody has ever done this for the simple reason it is impossible. So this is not a viable reference to dispute my claim.
How do I know these answers are likely to be valid assessments? See the next section. Nobody can explain the consistency in the data if people are randomly making up numbers.
So this is a second epic fail. They cannot attack this. I showed 10 different ways that confirmed my result.
Where is their survey?
#11: Ed Dowd’s book “Cause Unknown”
It lists 550 cases of people who died suddenly. That was the only criteria. He never researched vaccination status for any of these cases.
Only one person was found to be not vaccinated on the list. The AP fact checkers didn’t find any unvaccinated people on the list.
If the vaccine doesn’t kill anyone, around 25% of the people would have been unvaccinated.
If the vaccine didn’t cause these deaths, then how do you explain the correlation?
This does not show the vax:virus death ratio, but it does validate that the CDC is lying that only 9 people have died from the vaccine.
The “family members are not experts in cause of death” argument
A limitation of the study is that family members reported on the cause of death. Some over estimate. Some under estimate.
But there is uncanny consistency in the numbers no matter what samples you draw from.
What is the correct explanation for how the ratio between covid deaths and vaccine deaths can be so consistent if they are based on random guesses???
The ratios are not based on any single person’s observations, but on the statistics of the crowd.
Nobody could see how the other people voted because the survey results so nobody could know how other people voted. So how could they all independently choose the exact same probability of reporting a vaccine death if they didn’t collaborate??
Nobody is able to explain how the ratios can be so consistent if people are randomly guessing.
And the final validation is your own personal observations…
It’s a good bet that if you are reading this story, you know of friends who died at a much higher rate after the vaccine rollout than before and that they are all vaccinated. Compare that to the number of people you know who died from COVID.
Check with your friends and see what their experience was.
Special acknowledgment
I would like to thank LA Times reporter Michael Hiltzik for providing the motivation for my running the survey and doing the validation research to find the truth.
It certainly appears that Professor Skidmore has underestimated the number of deaths caused by the vaccine!
It also appears that nobody wants to run their own surveys to assess the truth.
I could not find anyone who could cite a ratio of vaccine/virus deaths. None of them knew, none had any data, none had any interest in doing any kind of survey to collect the data.
Summary
My latest survey shows 3.5X more people were killed by the vaccine as by the virus. That is a train wreck.
Professor Norman Fenton was not at all surprised by this number based on his research. When I told him the number, he didn’t even raise an eyebrow.
In this article, I showed 10 different methods that yield data consistent with the survey.
Not a single pro-vax person, as far as I know, has any clue as to what they think the number is. Whenever I ask, they throw up their hands and say that they don’t know. Nor do any of them want to know. They want to remain in the dark.
Yet, even though they have no clue what the ratio is, there is one thing that they do know for sure: Steve’s number can’t be right because it can’t be the vaccine.
This reminds me of physicians who say, “We don’t know what killed you, but the one thing we do know for sure is that it wasn’t the vaccine.” Have you heard that before?
It’s time for the vaccine advocates to put up or shut up. Show me your survey, show me the records from your responses, allow me to contact the respondents, show me at least 10 independent ways you validated it, and show me the similar extreme anecdotes showing that your number must be right and mine is wrong (like show me the guy who knows 30 people who died from COVID and only 1 person who died from the vaccine), and let’s get to the bottom of this and find out the correct number. Or is it better not to look and not to discuss it? Will that save more lives?
Not showing up with any data or any willingness to resolve this issue is unacceptable.
The link the spreadsheet was broken. It has been fixed. Sorry about that!
I asked a friend who recently had a heart attack to ask her doctor if she thought the covid vaxxes caused her heart attack. Without a moments hesitation, the doctor responded “yes”. Many more doctors appear to be waking from their long sleep. Thank goodness.