A prominent epidemiologist suggested I do a Risk Ratio computation comparing those who got 3 shots with those who go 2 shots. So I did a fixed cohort comparison and it knocked my socks off.
What can be expected, when people are injected with toxic matter that destroys the body and brain? The only thing that belongs in the human bloodstream are nutrients from healthy unprocessed foods...not lab-created elements, which 'scientists' have designed to profit their employers.
That's three years of data, whose members must be fixed, and tracked through, are they?
Each group has that two week window after their second shot before they jump from the un-vaccinated to the vaccinated. Apparently 70% of the vaccine induced deaths occur in that window. The survivors in both groups for this comparison are obviously healthier.
Those that choose the booster are likely the healthiest from the beginning. HVE.
Is the coding giving a two week window for the booster? If so, those deaths would be attributed to the 2 shot group.
There is a time offset of 3 to 6 months between the 2 shot vs 3 shot. Any relative risk change can only be detected 3 months to 6 months on.
As with a lot of your postings, I have a very hard time trying to figure out what the lines measure?
RR = Risk Ratio .. that is spelled out in the text.
But, what is HR? What is MR? What is d2? What is d3? what is CMR rate?
is D2 the number of Dose 2 shots? Or, the number of folks that died after dose 2?
is D3 the number of Dose 3 shots? Or, the number of folks that died after dose 3?
One place you say it's the "people who received exactly x doses by a given date"
Where does the mortality data come into play?
So MR is number of Dose 3 divided by Dose 2 recepients on a specific date?
Is MR mortality ratio?
So, over time there are more and more Dose 3 recepients compared
to those only with Dose 2?
As time marches on, there are still folks that are stupid or ignorant to not see that mRNA shots do more damage than they help? I don't get the premise of what the data is attempting to show.
Are you comparing how many folks received a shot or how many folks died from the shot?
I need to know what the symbols represent. I frankly can't tell where the mortatlity data is in the charts?
Please include a legend to charts with unlabeled variables, showing what each symbol relates to. It makes the flow of information very disjointed and it's difficult to follow any argument.
Steve, if this were a peer reviewed article it would be sent back to you for "major revisions"! Mainly, because you do not label your charts adequately or define your abbreviations. Yes, I can figure them out eventually but for five bucks a month I expect more clarity! :)
In VICP there are cases of “challenge/ rechallenge.” Wherein the first reaction is considered a coincidental correlation (to negate a preponderant of the evidence finding/ more likely than not by a feather on the scale). But the same reaction with exposure to the same vaccine is strong evidence of causation. The issue is when there are combined vaccines, or even different manufacturers. I did not study COVID vaccines in my research as I am a conflict Resolution scholar. However, I have “heard” some of the vaccines are correlated with higher adverse reactions. I did not specifically delve into the different manufacturers in my research but I am sure others have. There should be an evaluation with lot numbers as well for tracking. As for selection bias, the challenges of this kind of research is the requirement of specific subject matter experts (pediatric specialists in the case of the research I focused on). Focusing on key words in VICP meant other cases that had a correlation with a particular condition but did not articulate it in the search terms (filing type) would be overlooked. Statistics can be skewed, just like tobacco science evidence when there are so many potential confounding factors that it is nearly impossible to control for all of them.
E=IR P=IE (writing this for a bunch of Double E's is fine, but, writing this for a General Audience would be confusing)
If I rephrased it as Volts=(Amps x Ohms) and Watts=(Amps x Volts), I'd get a few more folks on board. If I said an Electric Field (measured in Volts) = Current (measured in Amps) x Resistance (measured in Ohms) and Power (measured in Watts) = Current (measured in Amps) x Electric Field (measured in Volts), I'd think I'd appeal to a larger Audiance.
Gert Vanden Boosche is a DVM who studies Viruses. He seems to have a good grasp of Virology, and writes quite extensively on the subject, but, I have a difficult time trying to read his writings.
(I hope, someone like Jessica Rose can come along and translate some of his articles)
He sounds like he has some very important explainations of what is happening with viruses, but, because of his literally thinking in a different language (Belgium?) and his personal terminology, I can only decipher every
5th word. It frustates me. I think he is probably, postively brilliant, and trying to explain some very important issues on some important topics, but, it's very difficult for me to follow, partly because of his thinking in a different language and writing in English, but, also because I have to have a lexicon of his terminology next to me when I try and read his material.
It sounds like he's saying something very worthwhile, but, I can't grasp it easily, and it frustates me. For example I try and follow this article and I have a lot of trouble understanding it. I know he's saying something
Compare his writing for a General audiance, US reader to Jessica Rose's writing style for example, how she breaks down this medical study with a ton of complex medical jargon into a very understandable, easy to read, article for those of us without Ph.D's in Applied MicroBiology etc.
She has a Bachelors Degree in Applied Mathematics, a Masters Degree in Immunology, a PhD in Computational Biology, and Two Post Doctoral degrees, (one in Molecular Biology and one in Biochemistry).
But, she's able to write in a flowing style, using simple words, that us mere mortals can easily read and understand the basic concepts of the study. That took a lot of effort on her part, but, it made the general reader population able to understand a lot more of the important medical writings of today.
(I strongly suggest following her substack to grasp some
complex technologies broken down into more, instantly understandable, plain English) I learn a lot more from her writings than trying to grasp Dr Vanden Boosche, who's very smart, but, because of the language barrier and terminolgy, I find difficult to follow.
I very much appreciate your repeated deep dive into emerging data and your dogged push to document and illuminate the truth. So perhaps I'm just S L O W or maybe just tired.. but what is your conclusion? I might try reading again later.
Each morning I look at the times of Israel news site checking on what’s going on over there and a story popped up that they’re finding polio in waste waters in the area. A comment in the story referred back to this one from about a year ago detailing how things went bad And I wanted to share it with you as a reminder and possibly you can discuss this in a Substack post.
What can be expected, when people are injected with toxic matter that destroys the body and brain? The only thing that belongs in the human bloodstream are nutrients from healthy unprocessed foods...not lab-created elements, which 'scientists' have designed to profit their employers.
Just some thoughts:
That's three years of data, whose members must be fixed, and tracked through, are they?
Each group has that two week window after their second shot before they jump from the un-vaccinated to the vaccinated. Apparently 70% of the vaccine induced deaths occur in that window. The survivors in both groups for this comparison are obviously healthier.
Those that choose the booster are likely the healthiest from the beginning. HVE.
Is the coding giving a two week window for the booster? If so, those deaths would be attributed to the 2 shot group.
There is a time offset of 3 to 6 months between the 2 shot vs 3 shot. Any relative risk change can only be detected 3 months to 6 months on.
Lots of confounders in there.
no confounders at all. these are exact dates.
Its good to have the exact dates. That means that a death that occurs one day after a shot is just that, not "unvaxxed".
Anyone who dies after the first shot is not included.
We are now studying the first shot "survivors".
After the second shot, anyone who dies cannot get a booster.
Thus the boosted cohort do not include those dying from 3 months to 6 months after the first two shots.
The relative risk of dying should only start after 3 months to 6 months.
No, I don't know what this all means.. just some thoughts.
I assume "FIUXED group" is a typo?
As with a lot of your postings, I have a very hard time trying to figure out what the lines measure?
RR = Risk Ratio .. that is spelled out in the text.
But, what is HR? What is MR? What is d2? What is d3? what is CMR rate?
is D2 the number of Dose 2 shots? Or, the number of folks that died after dose 2?
is D3 the number of Dose 3 shots? Or, the number of folks that died after dose 3?
One place you say it's the "people who received exactly x doses by a given date"
Where does the mortality data come into play?
So MR is number of Dose 3 divided by Dose 2 recepients on a specific date?
Is MR mortality ratio?
So, over time there are more and more Dose 3 recepients compared
to those only with Dose 2?
As time marches on, there are still folks that are stupid or ignorant to not see that mRNA shots do more damage than they help? I don't get the premise of what the data is attempting to show.
Are you comparing how many folks received a shot or how many folks died from the shot?
I need to know what the symbols represent. I frankly can't tell where the mortatlity data is in the charts?
Please include a legend to charts with unlabeled variables, showing what each symbol relates to. It makes the flow of information very disjointed and it's difficult to follow any argument.
Steve, if this were a peer reviewed article it would be sent back to you for "major revisions"! Mainly, because you do not label your charts adequately or define your abbreviations. Yes, I can figure them out eventually but for five bucks a month I expect more clarity! :)
this isn't a formal paper submitted for peer review.
i guess I have to redefine the abbreviations in every article. These are all standard abbreviations.
In VICP there are cases of “challenge/ rechallenge.” Wherein the first reaction is considered a coincidental correlation (to negate a preponderant of the evidence finding/ more likely than not by a feather on the scale). But the same reaction with exposure to the same vaccine is strong evidence of causation. The issue is when there are combined vaccines, or even different manufacturers. I did not study COVID vaccines in my research as I am a conflict Resolution scholar. However, I have “heard” some of the vaccines are correlated with higher adverse reactions. I did not specifically delve into the different manufacturers in my research but I am sure others have. There should be an evaluation with lot numbers as well for tracking. As for selection bias, the challenges of this kind of research is the requirement of specific subject matter experts (pediatric specialists in the case of the research I focused on). Focusing on key words in VICP meant other cases that had a correlation with a particular condition but did not articulate it in the search terms (filing type) would be overlooked. Statistics can be skewed, just like tobacco science evidence when there are so many potential confounding factors that it is nearly impossible to control for all of them.
E=IR P=IE (writing this for a bunch of Double E's is fine, but, writing this for a General Audience would be confusing)
If I rephrased it as Volts=(Amps x Ohms) and Watts=(Amps x Volts), I'd get a few more folks on board. If I said an Electric Field (measured in Volts) = Current (measured in Amps) x Resistance (measured in Ohms) and Power (measured in Watts) = Current (measured in Amps) x Electric Field (measured in Volts), I'd think I'd appeal to a larger Audiance.
Gert Vanden Boosche is a DVM who studies Viruses. He seems to have a good grasp of Virology, and writes quite extensively on the subject, but, I have a difficult time trying to read his writings.
(I hope, someone like Jessica Rose can come along and translate some of his articles)
He sounds like he has some very important explainations of what is happening with viruses, but, because of his literally thinking in a different language (Belgium?) and his personal terminology, I can only decipher every
5th word. It frustates me. I think he is probably, postively brilliant, and trying to explain some very important issues on some important topics, but, it's very difficult for me to follow, partly because of his thinking in a different language and writing in English, but, also because I have to have a lexicon of his terminology next to me when I try and read his material.
It sounds like he's saying something very worthwhile, but, I can't grasp it easily, and it frustates me. For example I try and follow this article and I have a lot of trouble understanding it. I know he's saying something
profound, but, I just can't follow it.
===
http://www.geertvandenbossche.org/post/a-last-word-of-caution-to-all-those-pretending-the-covid-19-pandemic-is-toning-down/
===
Compare his writing for a General audiance, US reader to Jessica Rose's writing style for example, how she breaks down this medical study with a ton of complex medical jargon into a very understandable, easy to read, article for those of us without Ph.D's in Applied MicroBiology etc.
===
https://jessicar.substack.com/p/a-new-multiple-sclerosis-study-is
===
She has a Bachelors Degree in Applied Mathematics, a Masters Degree in Immunology, a PhD in Computational Biology, and Two Post Doctoral degrees, (one in Molecular Biology and one in Biochemistry).
But, she's able to write in a flowing style, using simple words, that us mere mortals can easily read and understand the basic concepts of the study. That took a lot of effort on her part, but, it made the general reader population able to understand a lot more of the important medical writings of today.
(I strongly suggest following her substack to grasp some
complex technologies broken down into more, instantly understandable, plain English) I learn a lot more from her writings than trying to grasp Dr Vanden Boosche, who's very smart, but, because of the language barrier and terminolgy, I find difficult to follow.
I very much appreciate your repeated deep dive into emerging data and your dogged push to document and illuminate the truth. So perhaps I'm just S L O W or maybe just tired.. but what is your conclusion? I might try reading again later.
it's all selection bias. healthier people opt for the next shot.
Each morning I look at the times of Israel news site checking on what’s going on over there and a story popped up that they’re finding polio in waste waters in the area. A comment in the story referred back to this one from about a year ago detailing how things went bad And I wanted to share it with you as a reminder and possibly you can discuss this in a Substack post.
https://www.timesofisrael.com/behind-gaza-polio-case-experts-see-horrible-who-decision-fueling-outbreaks-worldwide/
I sense a bit of cynicism creeping in!
Thank you Steve for the excellent post!!