If the CDC was honest, this is what their new ads should look like!
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. If you think I got it wrong, you can turn $25K into $250K in days!
This article describes how a simple objective analysis of objective death data (age, date died, date of last COVID vaccination) 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 last COVID vaccine. 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:
- If the intervention (i.e., the vax) does nothing, ratio = .5
- If the invention shortens life, ratio <.5
- 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.
