Empirical analysis of symptomatic COVID and COVID deaths in England reveals no positive impact of any interventions but 100% concurrency between vaccinations and COVID "outbreaks" in late 2021.
It is quite extraordinary that pretty much the entire sequence can be explained by expressing viral waves using Gompertz distributions, which itself tells us that each wave is strictly self-limiting (and, as you show, immune to practical intervention - what a surprise for an airborne virus when there is already a high degree of natural immunity ), and recognising that vaccines are, in fact, key explanatory variables.
Even allowing for the distortion of many of the target variables, for example, "infections" and "CV-19 deaths", the analysis is compelling.
One thought; with regard to the full impact of the vaccines on mortality, it would be interesting to use all-cause deaths as the target variable, not least because that is less easily manipulated than flakily defined (manipulated) "CV-19 deaths". That would also make it easy to trace sequential vaccine impact by age group since that is how they were rolled out.
Finally, it might be interesting to include the data for the widespread use of the euthanasia drug of choice, Midazolam (something like two years supply used up in just three months, largely targeting the elderly), one of the other great scandals in this very sad saga.
First off, thank you for writing out this unfolding disaster. There is so much here to think about but the most important thing I wish people paid attention to right now is taking this hypothesis very seriously because it has consequences right now!
"The youth are also much more at risk of damage to their innate immune system due to vaccination and they rely on that more than their under-developed adaptive system⁶."
I posted just a little bit of "evidence" (raw data abused through regression modeling) from Nick Andrew et al.'s Supplementary (suppressed) Appendix showing epidemic spread during vaccination of 12-15 and 16-17.
Excellent. Clear, precise, well laid out and easy to follow for those of us not trained in statistical analysis. My personal take is malfeasance. Occam's razor gets me there.
Fascinating and convincing - or is that just my confirmation bias? So many interesting concepts I never heard of before this pandemic.
If you have time Sir, I'd appreciate if you could clarify something in figure 5. It looks to me like the third Gompertz wave has an offset relative to 0 on the y-axis. Is that an artifact of my screen or if real, what does it mean?
I can mathematically grasp the concept that a function with just 2 parameters would be an unlikely outcome of a system exposed to impulses (like lock-down and masking) midway through the curve (well provided the impulses had any significant impact that is).
If I try to interpret the meaning of the Gompertz curve in a pandemic context its derivative would be something like: (R0-1)/k, correct? Mitigations that are instantaneous like lock-down, mask mandates etc, should (if they worked) cause a step reduction in the R0, while vaccination which is gradual should be less sudden.
There are a lot of pandemic simulators and had my SW skills been on par with my curiosity, I would have liked to see how much difference a -N% step in R0 should generate in a Gompertz curve for (N=10, 25, 50), depending on when the step is introduced. I guess one needs to account for the delay between the step and the time to symptoms.
I believe such an exercise would make the argument for using Gompertz curves as proof of the mitigations being useless even more compelling.
Thank you Sir for this and all your previous equally interesting posts!
Great article. I guess one of the things that could be done is to map the typical flu curves for previous years as you should see the same school then university outbreaks in autumn as well as the typical winter deaths. The distributions in spring and summer themselves appear to be a break from the norm that looks likely to be vaccine induced.
The fact that these overall curves can be modelled as a sum of simple functions is fascinating. The fact that these simple functions themselves can be temporally related to specific events is more fascinating still. It's almost like you've found the fundamental "modes of oscillation" here - akin to being able to resolve a complex sound into a set of simpler fundamental "pure" oscillations.
Just a thought here - the Swedish mortality data does appear to be quite tightly "correlated" with the UK data - at least on a cursory visual examination. Could you use the comparison of the "fundamental modes" for the 2 countries to shed light on whether the lifting of lockdown 2 (2nd dec 2020) was in fact responsible for the triggering of another infection (another "mode")?
Sweden (I think) wouldn't have had any triggering due to either lifting of lockdown (they didn't lockdown), or vaccines (I think they started vaccinating later). Comparing the fundamental "modes" of different countries - and tying them into various measures could be a really powerful way of understanding what's gone on - especially if a consistent causality pattern is found across countries who adopt different measures at different times.
I'm not sure how seasonality will play into any of this though?
Life insurance company OneAmerica’s ceo told the Indiana Chamber of Commerce January 3rd that deaths among working age people is off the charts.
A $100 billion Indiana based life insurance co. saw 3rd quarter and now 4th quarter 2021, death rates up 40% ages 18-64. “Most of the filed claims are not Covid deaths” the ceo said. “40% is unheard of”. Covid policy, adverse events post vaxx, suicides?
This is another deadly sin that will prove even more expensive when the truth comes out.
"Conversely, in addition to the death distribution that follows the infection wave triggered by the start of mass vaccination (which prioritised healthcare workers), we can observe a new distribution contained entirely within it which starts exactly when the most elderly and frail were vaccinated. "
I have evidence from Denmark, New York, UK, Kerala (Indian State) of strong suggestion hospital infections after vaccinations started in the respective countries.
Good work Joel.
It is quite extraordinary that pretty much the entire sequence can be explained by expressing viral waves using Gompertz distributions, which itself tells us that each wave is strictly self-limiting (and, as you show, immune to practical intervention - what a surprise for an airborne virus when there is already a high degree of natural immunity ), and recognising that vaccines are, in fact, key explanatory variables.
Even allowing for the distortion of many of the target variables, for example, "infections" and "CV-19 deaths", the analysis is compelling.
One thought; with regard to the full impact of the vaccines on mortality, it would be interesting to use all-cause deaths as the target variable, not least because that is less easily manipulated than flakily defined (manipulated) "CV-19 deaths". That would also make it easy to trace sequential vaccine impact by age group since that is how they were rolled out.
Finally, it might be interesting to include the data for the widespread use of the euthanasia drug of choice, Midazolam (something like two years supply used up in just three months, largely targeting the elderly), one of the other great scandals in this very sad saga.
First off, thank you for writing out this unfolding disaster. There is so much here to think about but the most important thing I wish people paid attention to right now is taking this hypothesis very seriously because it has consequences right now!
"The youth are also much more at risk of damage to their innate immune system due to vaccination and they rely on that more than their under-developed adaptive system⁶."
I posted just a little bit of "evidence" (raw data abused through regression modeling) from Nick Andrew et al.'s Supplementary (suppressed) Appendix showing epidemic spread during vaccination of 12-15 and 16-17.
https://www.gettr.com/comment/cfky3g2daf
The vaccination of children is going to blow up everything very soon. UK will find out, India will find out, so will Israel.
Thanks, Joel.
I have "briefed" my pen pal the NSW Australia Health Minister on it.
Excellent. Clear, precise, well laid out and easy to follow for those of us not trained in statistical analysis. My personal take is malfeasance. Occam's razor gets me there.
This is an excellent piece of work Joel, thank you.
Fascinating and convincing - or is that just my confirmation bias? So many interesting concepts I never heard of before this pandemic.
If you have time Sir, I'd appreciate if you could clarify something in figure 5. It looks to me like the third Gompertz wave has an offset relative to 0 on the y-axis. Is that an artifact of my screen or if real, what does it mean?
I can mathematically grasp the concept that a function with just 2 parameters would be an unlikely outcome of a system exposed to impulses (like lock-down and masking) midway through the curve (well provided the impulses had any significant impact that is).
If I try to interpret the meaning of the Gompertz curve in a pandemic context its derivative would be something like: (R0-1)/k, correct? Mitigations that are instantaneous like lock-down, mask mandates etc, should (if they worked) cause a step reduction in the R0, while vaccination which is gradual should be less sudden.
There are a lot of pandemic simulators and had my SW skills been on par with my curiosity, I would have liked to see how much difference a -N% step in R0 should generate in a Gompertz curve for (N=10, 25, 50), depending on when the step is introduced. I guess one needs to account for the delay between the step and the time to symptoms.
I believe such an exercise would make the argument for using Gompertz curves as proof of the mitigations being useless even more compelling.
Thank you Sir for this and all your previous equally interesting posts!
Thanks Joel. Brilliant as always. Although horrendous at the same time.
Great article. I guess one of the things that could be done is to map the typical flu curves for previous years as you should see the same school then university outbreaks in autumn as well as the typical winter deaths. The distributions in spring and summer themselves appear to be a break from the norm that looks likely to be vaccine induced.
All Hail Metatron!
Another fabulous piece of work Joel.
The fact that these overall curves can be modelled as a sum of simple functions is fascinating. The fact that these simple functions themselves can be temporally related to specific events is more fascinating still. It's almost like you've found the fundamental "modes of oscillation" here - akin to being able to resolve a complex sound into a set of simpler fundamental "pure" oscillations.
Just a thought here - the Swedish mortality data does appear to be quite tightly "correlated" with the UK data - at least on a cursory visual examination. Could you use the comparison of the "fundamental modes" for the 2 countries to shed light on whether the lifting of lockdown 2 (2nd dec 2020) was in fact responsible for the triggering of another infection (another "mode")?
Sweden (I think) wouldn't have had any triggering due to either lifting of lockdown (they didn't lockdown), or vaccines (I think they started vaccinating later). Comparing the fundamental "modes" of different countries - and tying them into various measures could be a really powerful way of understanding what's gone on - especially if a consistent causality pattern is found across countries who adopt different measures at different times.
I'm not sure how seasonality will play into any of this though?
Life insurance company OneAmerica’s ceo told the Indiana Chamber of Commerce January 3rd that deaths among working age people is off the charts.
A $100 billion Indiana based life insurance co. saw 3rd quarter and now 4th quarter 2021, death rates up 40% ages 18-64. “Most of the filed claims are not Covid deaths” the ceo said. “40% is unheard of”. Covid policy, adverse events post vaxx, suicides?
This is another deadly sin that will prove even more expensive when the truth comes out.
"Conversely, in addition to the death distribution that follows the infection wave triggered by the start of mass vaccination (which prioritised healthcare workers), we can observe a new distribution contained entirely within it which starts exactly when the most elderly and frail were vaccinated. "
I have evidence from Denmark, New York, UK, Kerala (Indian State) of strong suggestion hospital infections after vaccinations started in the respective countries.