"Vaccine" Killed 3.5X More Americans Than Covid

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 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.

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