Excellent article. Logically presented and well-written.
Now the pushback, questions, and requests. :)
1. The New York data - The theory that models were used to guide the reporting of COVID deaths but were never reflections of what was occurring on the ground is one I've proffered numerous times as one possible explanation for the obviously-manipulated all-cause death curve. For that reason, more than anyone, I would love to be able to embrace the method Thomas Verduyn applied to NYC DOH and the JHU dashboard that led him to claim the results as proof the deaths weren't happening in real time and a model was used.
However, any analysis of the New York data must be mindful of what was being reported by officials at time -- not because the officials were telling the truth, but because it sheds light on the manipulation AND sets parameters for what constitutes proof.
My request is NOT that you adjudicate the conversation between he & myself, but that you offer your own “take” on the implications of what was reported at the time so that I can understand how his method - and your implicit endorsement thereof - is "almost irrefutable proof that the probable death numbers were artificially generated on a computer."
If it is such proof, I am prepared to accept it humbly include it in a letter I’m in the process of writing to relevant elected and appointed officials.
Much more importantly, I believe the adding of “the probables” is representative of something that happened on a much larger scale in locations worldwide, if only to a lesser degree. (NYC is the exception that proves the rules.)
2. FYI, in at least two press conferences in April 2020, Governor Andrew Cuomo said that the COVID death numbers being reported (up until a certain point) were hospital deaths only. I believe this is critical to understanding what may have been done in numerous places worldwide.
3. You cited this link to Dr. Levitt’s DP work. https://heatherrenkel.github.io The name on the site is Heather Renkel. Who is Heather Renkel, i.e., what is her relationship to Dr. Levitt? (grad student?) Is this analysis published elsewhere?
4. Can you provide a direct link to the “Winter Scenarios” graph? I can't find it (which may be user error).
5. As Prof Neil is aware, I agree with your conclusion that “epidemiological models of respiratory pathogens produce hopelessly exaggerated estimates based on assumptions about parameters that are either unknowable or are so difficult to measure that their credibility is highly suspect.” While not the purpose of your article, can at least one of you (the authors) comment on the implications of this conclusion on all-cause death curves for 2020 and beyond? Do you agree with the assertion/assumption of Denis Rancourt & colleagues are necessarily valid & reliable?
Proof is perhaps too strong a word. Strong suspicions? What strength of support do you think his arguments merit? Credible/plausible/possible/.....?
I agree there remain a lot of gaps and questions as you would expect in an ongoing detective story. It's not a closed book by a long chalk. I keenly await to here new views and discoveries.
Winter scenarios....let me try and dig but I'm about to jump on a plane so might forget.
Rancourts work (and that of others) on excess deaths....I've scanned it but haven't had the time to do a deep dive review so can't really comment. I've not posted on it here or anywhere else. Whether I ever find time to do so I'm not too sure to be honest. There are only so many hours in the day.
I'm also happy to hear skepticism about official mortality data. After all if other data is manipulated why not that? Without citizen led inspection of death certificates and double checking with families there will be some room for doubt - how much doubt is warranted I'm not too sure. I know neither Norman nor Scott has looked at it.
Levitt website. I'm assuming it is an honest representation of his work. Who Renkel is I don't know and have not dug deeper. Do you have reason to believe it is not what it purports to be?
The official story is that JHU was following/trying to follow NYC, not vice versa. How then is the method Verduyn used near-proof of a model being used?
I'm asking because I'm not clear on what you believe the implications are of what you're showing about dashboards—either for COVID or all-cause death curves. Were dashboards too zealous and deaths force-fitted to the models? What is the relationship between the dashboard COVID curves and the official/final COVID and all-cause daily death curves in respective jurisdictions?
Two things stick out - 4/3 proportion and smoothness of the curve and it being too close a match to the abstract/perfect theoretical representation.
I don't know the mechanisms. You call fraud on NYC without knowing the mechanism. Yes?
Absolute knowledge isnt a prerequisite here.
I've acknowledged that mortality statistics could be manipulated. I might acknowledge financial fraud in the interbank trading market is a real possibility based on observed market moves but I dont think it would be beholden on me to say how trades and prices were being exactly manipulated.
Not sure why I'm being bracketed with Rancourt.
Can you accept I've no fully formed view of some issues and dont claim anything close to omniscience?
Re: "4/3 proportion and smoothness of the curve and it being too close a match to the abstract/perfect theoretical representation" - I don't disagree with that and have made similar observations about the all-cause curve, especially the rise. The cardiac arrest curve looks engineered to me as well. Indeed, the whole event does.
But - unless I am mistaken - Verduyn's JHU dashboard article used NYC as illustrative of JHU reporting numbers were using models. What I am trying to show you is that NYC isn't a good example of that because ("officially") it was JHU catching up with NYC, not vice versa.
Plus, the 2020 vital statistics report from NYC DOHMH provides a explanation that could further be used to excuse the fact that JHU had a hard time "retro-fitting" the probables into the NYC DOHMH COVID death curve.
I wasn't bracketing you w/Rancourt. I realize I inadvertently left out words in my initial reply. My question should have been, "Do you agree with the assertion/assumption of Denis Rancourt & colleagues that all-cause death numbers are necessarily valid & reliable?"
My intent was to cite Rancourt as an example of someone who (like you) doesn't believe there was a pandemic and doesn't accept the WHO's baloney about a new cause of death, yet holds the view that all-cause death data is legitimate because it isn't susceptible to manipulation.
I believe there is ACM fraud, not just COVID death fraud. The nonsense with the dashboards absolutely helped convince the world that "something wicked this way comes" to a city near you but it was not/is not clear in the present article that and your co-authors hold that view. Thank you for clarifying that you agree with me, i.e., that ACM fraud is possible, not impossible. :)
Math is not my subject but graphs are visual enough to be helpful. What's been most striking is we were told this deadly, novel virus spread so fast it covered the globe in a few months. But the biggest spike in cases followed "safe & effective" countermeasures.
My sympathies lie with folks whose eyes glaze over when numbers become the focus but between your NYC mass casualty chart and the World Data chart at top soaring in 2022 even the dimmest bulbs should be able to look at the big picture & see the spectacular lies.
Big time kudos and thanks for tackling the data translating to impactful images for all! <3
Excellent article. Logically presented and well-written.
Now the pushback, questions, and requests. :)
1. The New York data - The theory that models were used to guide the reporting of COVID deaths but were never reflections of what was occurring on the ground is one I've proffered numerous times as one possible explanation for the obviously-manipulated all-cause death curve. For that reason, more than anyone, I would love to be able to embrace the method Thomas Verduyn applied to NYC DOH and the JHU dashboard that led him to claim the results as proof the deaths weren't happening in real time and a model was used.
However, any analysis of the New York data must be mindful of what was being reported by officials at time -- not because the officials were telling the truth, but because it sheds light on the manipulation AND sets parameters for what constitutes proof.
I draw your attention to what I showed Mr. Verduyn along those lines. https://open.substack.com/pub/pandauncut/p/the-dashboard-that-ruled-the-world?r=jjay2&utm_campaign=comment-list-share-cta&utm_medium=web&comments=true&commentId=54174650
https://open.substack.com/pub/pandauncut/p/the-dashboard-that-ruled-the-world?r=jjay2&utm_campaign=comment-list-share-cta&utm_medium=web&comments=true&commentId=54404997
My request is NOT that you adjudicate the conversation between he & myself, but that you offer your own “take” on the implications of what was reported at the time so that I can understand how his method - and your implicit endorsement thereof - is "almost irrefutable proof that the probable death numbers were artificially generated on a computer."
If it is such proof, I am prepared to accept it humbly include it in a letter I’m in the process of writing to relevant elected and appointed officials.
Much more importantly, I believe the adding of “the probables” is representative of something that happened on a much larger scale in locations worldwide, if only to a lesser degree. (NYC is the exception that proves the rules.)
2. FYI, in at least two press conferences in April 2020, Governor Andrew Cuomo said that the COVID death numbers being reported (up until a certain point) were hospital deaths only. I believe this is critical to understanding what may have been done in numerous places worldwide.
3. You cited this link to Dr. Levitt’s DP work. https://heatherrenkel.github.io The name on the site is Heather Renkel. Who is Heather Renkel, i.e., what is her relationship to Dr. Levitt? (grad student?) Is this analysis published elsewhere?
4. Can you provide a direct link to the “Winter Scenarios” graph? I can't find it (which may be user error).
5. As Prof Neil is aware, I agree with your conclusion that “epidemiological models of respiratory pathogens produce hopelessly exaggerated estimates based on assumptions about parameters that are either unknowable or are so difficult to measure that their credibility is highly suspect.” While not the purpose of your article, can at least one of you (the authors) comment on the implications of this conclusion on all-cause death curves for 2020 and beyond? Do you agree with the assertion/assumption of Denis Rancourt & colleagues are necessarily valid & reliable?
Thank you kindly.
You can call me Martin!
Proof is perhaps too strong a word. Strong suspicions? What strength of support do you think his arguments merit? Credible/plausible/possible/.....?
I agree there remain a lot of gaps and questions as you would expect in an ongoing detective story. It's not a closed book by a long chalk. I keenly await to here new views and discoveries.
Winter scenarios....let me try and dig but I'm about to jump on a plane so might forget.
Rancourts work (and that of others) on excess deaths....I've scanned it but haven't had the time to do a deep dive review so can't really comment. I've not posted on it here or anywhere else. Whether I ever find time to do so I'm not too sure to be honest. There are only so many hours in the day.
I'm also happy to hear skepticism about official mortality data. After all if other data is manipulated why not that? Without citizen led inspection of death certificates and double checking with families there will be some room for doubt - how much doubt is warranted I'm not too sure. I know neither Norman nor Scott has looked at it.
Levitt website. I'm assuming it is an honest representation of his work. Who Renkel is I don't know and have not dug deeper. Do you have reason to believe it is not what it purports to be?
Re: NYC/JHU - It isn't new views that need attention; it's knowledge of the "old" events as they occurred and were reported. :)
Key events for review here: https://substack.com/profile/32813354-jessica-hockett/note/c-56073901?utm_source=notes-share-action&r=jjay2
The official story is that JHU was following/trying to follow NYC, not vice versa. How then is the method Verduyn used near-proof of a model being used?
Rancourt - the question isn't about his work; it's about the assertion that ACM data are necessarily reliable and not subject to manipulation. Do you think ACM data isn’t susceptible to and cannot be altered by observational or reporting biases? (FWIW, yesterday, Rancourt indicated to me that he still holds that view: https://woodhouse.substack.com/p/denis-rancourt-on-the-nyc-spring?r=jjay2&utm_campaign=comment-list-share-cta&utm_medium=web&comments=true&commentId=55981139_)
I'm asking because I'm not clear on what you believe the implications are of what you're showing about dashboards—either for COVID or all-cause death curves. Were dashboards too zealous and deaths force-fitted to the models? What is the relationship between the dashboard COVID curves and the official/final COVID and all-cause daily death curves in respective jurisdictions?
Re: Renkel - I don't know who it is in real life or what the relationship is to Dr. Levitt. Earliest DP article I can find by Dr. Levitt himself is this one https://medium.com/@michael.levitt/the-excess-burden-of-death-from-coronavirus-covid-19-is-closer-to-a-month-than-to-a-year-83fca74455b4
Thanks.
Two things stick out - 4/3 proportion and smoothness of the curve and it being too close a match to the abstract/perfect theoretical representation.
I don't know the mechanisms. You call fraud on NYC without knowing the mechanism. Yes?
Absolute knowledge isnt a prerequisite here.
I've acknowledged that mortality statistics could be manipulated. I might acknowledge financial fraud in the interbank trading market is a real possibility based on observed market moves but I dont think it would be beholden on me to say how trades and prices were being exactly manipulated.
Not sure why I'm being bracketed with Rancourt.
Can you accept I've no fully formed view of some issues and dont claim anything close to omniscience?
Re: "4/3 proportion and smoothness of the curve and it being too close a match to the abstract/perfect theoretical representation" - I don't disagree with that and have made similar observations about the all-cause curve, especially the rise. The cardiac arrest curve looks engineered to me as well. Indeed, the whole event does.
But - unless I am mistaken - Verduyn's JHU dashboard article used NYC as illustrative of JHU reporting numbers were using models. What I am trying to show you is that NYC isn't a good example of that because ("officially") it was JHU catching up with NYC, not vice versa.
Plus, the 2020 vital statistics report from NYC DOHMH provides a explanation that could further be used to excuse the fact that JHU had a hard time "retro-fitting" the probables into the NYC DOHMH COVID death curve.
I wasn't bracketing you w/Rancourt. I realize I inadvertently left out words in my initial reply. My question should have been, "Do you agree with the assertion/assumption of Denis Rancourt & colleagues that all-cause death numbers are necessarily valid & reliable?"
My intent was to cite Rancourt as an example of someone who (like you) doesn't believe there was a pandemic and doesn't accept the WHO's baloney about a new cause of death, yet holds the view that all-cause death data is legitimate because it isn't susceptible to manipulation.
I believe there is ACM fraud, not just COVID death fraud. The nonsense with the dashboards absolutely helped convince the world that "something wicked this way comes" to a city near you but it was not/is not clear in the present article that and your co-authors hold that view. Thank you for clarifying that you agree with me, i.e., that ACM fraud is possible, not impossible. :)
Math is not my subject but graphs are visual enough to be helpful. What's been most striking is we were told this deadly, novel virus spread so fast it covered the globe in a few months. But the biggest spike in cases followed "safe & effective" countermeasures.
My sympathies lie with folks whose eyes glaze over when numbers become the focus but between your NYC mass casualty chart and the World Data chart at top soaring in 2022 even the dimmest bulbs should be able to look at the big picture & see the spectacular lies.
Big time kudos and thanks for tackling the data translating to impactful images for all! <3