“Vaccine” killed 3.5X more Americans than COVID virus

Original article: https://kirschsubstack.com/p/vaccine-killed-35x-more-americans

Executive summary

The irresponsible attacks by an LA Times journalist 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 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.

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:

1. The announcement

2. The survey

3. The survey responses (over 10,000)

4. 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 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 20 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.

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).

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 3 other powerful validators in addition to Jay’s anecdote:

1. 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.

2. 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.

3. 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.”

1. 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 that 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 suvey 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.”

Summary

My latest survey shows 3.5X as many 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 5 entirely different methods for validating the results.

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. Even though they have no clue what the ratio is, there is one thing that they are absolutely confident of: I can’t be right and my survey MUST be wrong.

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 numbers, show me at least 5 independent ways you got to the same number, 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 who is right and who is wrong.

Not showing up with any data or any willingness to resolve this issue is unacceptable.