I created a database of the actual deaths of two cohorts that I selected at random from a larger database. Is epidemiology capable of determining which cohort was vaccinated?
If you are an epidemiologist or data scientist and you want to enter the contest, post your answer here. No prize money, but you get bragging rights. Please see the newly added caption on the figure.
I'm a mathematician, not epidemiologist. It's clear that you cannot tell which cohort has vaxed persons, since the lines are so closely matching in shape. Death rates are essentially the same for both groups. Cohort A obviously has more people.
I would like to recommend to your attention a publication by a Hungarian research group, which was written in the city where Katalin Karikó's career began.
The researchers not only tracked the patients’ laboratory results and survival outcomes, but also analyzed the entire pattern of proteins circulating in the blood. This is what is called a proteomic analysis—like creating a biological “fingerprint” of the body at a given moment.
I'm a mathematician, not epidemiologist. It's clear that you cannot tell which cohort has vaxed persons, since the lines are so closely matching in shape. Death rates are essentially the same for both groups. Cohort A obviously has more people.
Steve, it fascinates me that once one starts breaking down the logical fallacies one step at a time, one can turn the lie on its head. Quite simple and elegant. It seems the truth, like a lion, needs no defense…
"The committee concluded the evidence convincingly supports 14 spe-cific vaccine–adverse event relationships. In all but one of these relation-ships, the conclusion was based on strong mechanistic evidence with the epidemiologic evidence rated as either limited confidence or insufficient."
I focused on mechanistic evidence.
Vaccines and Biologics injury table based on mechanistic evidence – Feb 2020 Covering over 125 conditions
After thinking about this for a couple days, I'm thinking this amounts to a 'Rorschach Test for Determining the Underlying Root-level Assumptions Epidemiologists Commonly Make'.
Please correct me if I am wrong. Also feel free to amend or extend this determination of mine.
(The key to all this is to ignore the MacGuffin existing in the form of the data and plot of data represented in the Excel spreadsheet -which I did download and examine in this determination as stated in my opening paragraph.)
I must be missing something. Since one line is labelled Unvaccinated, the other must be the one that got the shots. Regardless, epidemiology is not science. It may suggest possible avenues for true scientific exploration, but proves nothing about cause and effect.
When people say correlation does not mean causation i tell them smoking correlates to lung cancer, Alcohol to liver cirrhosis, and Asbestos to mesothelioma. Covid jabs to......................too many to count or list here.
Can't wait to find out how your work with HHS is going using your KCOR data. Bring all these bastards down Steve. Good luck on the debate coming up with Dr. K! Smash them to the floor.
If you are an epidemiologist or data scientist and you want to enter the contest, post your answer here. No prize money, but you get bragging rights. Please see the newly added caption on the figure.
1. Which cohort is older?
Cohort A
2. Which cohort got the COVID vaccine?
Cohort B
3. How many total lives were saved in the cohort who got the vaccines?
Approximately negative 15,000.
4. Which cohort has more people?
Cohort B
5. How many epidemiologists will be able to answer all 4 questions correctly and agree?
Range of (no idea, we all know how many).
1. Which cohort is older? Cohort A
2. Which cohort got the COVID vaccine? Cohort B
3. How many total lives were saved in the cohort who got the vaccines? -13.4k (0 lives saved, more died than expected)
4. Which cohort has more people? Cohort A
5. How many epidemiologists will be able to answer all 4 questions correctly and agree? 0
I am not an epidemiologist or data scientist.
If allowed, I'd like to change my answer to:
1. Which cohort is older? They are the same age
2. Which cohort got the COVID vaccine? Cohort B
3. How many total lives were saved in the cohort who got the vaccines? -13.4k (0 lives saved, more died than expected)
4. Which cohort has more people? same sizes
5. How many epidemiologists will be able to answer all 4 questions correctly and agree? 0
I'm a mathematician, not epidemiologist. It's clear that you cannot tell which cohort has vaxed persons, since the lines are so closely matching in shape. Death rates are essentially the same for both groups. Cohort A obviously has more people.
It's a trick-question, right?
What's the trick?
It just looks obvious that Cohort A keeps dying more than Cohort unvaccinated.
What am I missing?
;-}
you need to actually download the spreadsheet rather than look at the illustrative graphic
Well, that's the answer.
I tried to download, but did not succeed in getting files or graphics; perhaps format incompatability.
hit the download button on the page.
This is what I had found and it did not get me anything I could open:
"a test file with a challenge" ,hence I wondered about format incompatability.
I had no problem downloading the Excel file using something as archaic as Windows Xp SP3 and Excel 2007 / MS Office 2007 suite.
Great Post!!!
🇦🇺💉Senator Alex Antic, Australia (Facebook screenshot) - just in, 28 August 2025: https://substack.com/@meshwork3232/note/c-149858907?r=20pd6j&utm_medium=ios&utm_source=notes-share-action
I would like to recommend to your attention a publication by a Hungarian research group, which was written in the city where Katalin Karikó's career began.
The researchers not only tracked the patients’ laboratory results and survival outcomes, but also analyzed the entire pattern of proteins circulating in the blood. This is what is called a proteomic analysis—like creating a biological “fingerprint” of the body at a given moment.
https://karikor.substack.com/p/covid-vaccination-organ-damage-instead
Indeed
I'm a mathematician, not epidemiologist. It's clear that you cannot tell which cohort has vaxed persons, since the lines are so closely matching in shape. Death rates are essentially the same for both groups. Cohort A obviously has more people.
Steve, it fascinates me that once one starts breaking down the logical fallacies one step at a time, one can turn the lie on its head. Quite simple and elegant. It seems the truth, like a lion, needs no defense…
No. The IOM/NAM found epidemiology was useless 93% of the time but mechanistic evidence was correct those 93% of the time.
Institute of Medicine: Most epidemiological vaccine safety studies are useless
https://zenodo.org/records/3248520
"The committee concluded the evidence convincingly supports 14 spe-cific vaccine–adverse event relationships. In all but one of these relation-ships, the conclusion was based on strong mechanistic evidence with the epidemiologic evidence rated as either limited confidence or insufficient."
I focused on mechanistic evidence.
Vaccines and Biologics injury table based on mechanistic evidence – Feb 2020 Covering over 125 conditions
https://zenodo.org/records/3647593
After thinking about this for a couple days, I'm thinking this amounts to a 'Rorschach Test for Determining the Underlying Root-level Assumptions Epidemiologists Commonly Make'.
Please correct me if I am wrong. Also feel free to amend or extend this determination of mine.
(The key to all this is to ignore the MacGuffin existing in the form of the data and plot of data represented in the Excel spreadsheet -which I did download and examine in this determination as stated in my opening paragraph.)
That’s an easy question to answer. Cohort A is the vaccinated! So sad! 😞
Every Single "Vaccine" in history is at best a fraud.. and almost certainly "population control"
Every Single mRNA "Vaccine" is willful Murder.. a demonic "culling"..
Don't get me started on "Viruses"
All being exposed in real time.
God Won! God Bless
😂🥰👏
I must be missing something. Since one line is labelled Unvaccinated, the other must be the one that got the shots. Regardless, epidemiology is not science. It may suggest possible avenues for true scientific exploration, but proves nothing about cause and effect.
When people say correlation does not mean causation i tell them smoking correlates to lung cancer, Alcohol to liver cirrhosis, and Asbestos to mesothelioma. Covid jabs to......................too many to count or list here.
Can't wait to find out how your work with HHS is going using your KCOR data. Bring all these bastards down Steve. Good luck on the debate coming up with Dr. K! Smash them to the floor.
Shouldn't the lines be labeled Cohort A and Cohort B?
I know. The ones that took the shot got to go to heaven sooner... if they were born again.
Which is it? Go to heaven, or reincarnate?