"( p = 0.046 ). This is almost no longer significant,"
We should such p-values in retrospective and purely observational setting not call significant unless the p-value is <0.005. Even then, as the example above tells us, we should remain careful even with p-values as low as 0.00007 (as shown above).
On the "fun" page of my births Excel sheet, I list country name (how about rank by lexicographical order), capital (same), population of capital, population of country, area, and distance between capital and Moscow...
Certainly. However, vax will also correlate with overall mortality and both will correlate with C19 mortality. It's always the same question: cause or coincidence?
These are based on the same data Raimund used (ECDC).
I've stared at these for so long before getting an idea of how these shots affect the waves. I wish I had more experience modeling something like this. It would seem SI models are perfectly suited for the job.
Because we know the mechanism is plausible and to be expected.
It's been known for decades that it is ill-advised to vaccinate into infectious disease outbreaks for this very reason. It will worsen the prognosis when double-exposure occurs.
In absence of a mechanism that supports reverse causation, I think we should describe how unlikely it is for these coincidences to happen in so many places during the second half of 2021.
The effect can be observed in almost every country, but the dynamics are very complex. I've played around with simple SI models to see how vaccinating into various phases of an outbreak affects the shape of the wave and what I am seeing is relatively consistent.
Excellent work! Thanks!
Excellen again, thank you very much!
However, I disagree in
"( p = 0.046 ). This is almost no longer significant,"
We should such p-values in retrospective and purely observational setting not call significant unless the p-value is <0.005. Even then, as the example above tells us, we should remain careful even with p-values as low as 0.00007 (as shown above).
I agree with you. That was also a requirement of Ioannides. I applied the generally accepted standard here.
On the "fun" page of my births Excel sheet, I list country name (how about rank by lexicographical order), capital (same), population of capital, population of country, area, and distance between capital and Moscow...
https://cm27874.substack.com/p/european-births-q2-2023-update
Longitudes of the capitals would be another nice idea. ;-)
And latitudes and altitudes!
https://cm27874.substack.com/p/i-bless-the-brains-down-in-africa
Thank you.
And after controlling for all these factors, I bet the October vax rate is still positively correlated with COVID deaths.
I bet against, as far as C19 vax is concerned.
The C19 vax rate is too low.
https://substack.com/@covdata/note/c-44451019
I've already acquired the indicators Ulf used and will see what happens if integrate them into the model.
When I say vax rate, I mean weekly first doses, not cumulative (first) doses per capita.
Certainly. However, vax will also correlate with overall mortality and both will correlate with C19 mortality. It's always the same question: cause or coincidence?
https://substack.pervaers.com/summer_deaths/supplemental_figures/supplemental_figure_7.pdf
https://substack.pervaers.com/summer_deaths/supplemental_figures/supplemental_figure_7.png
These are based on the same data Raimund used (ECDC).
I've stared at these for so long before getting an idea of how these shots affect the waves. I wish I had more experience modeling something like this. It would seem SI models are perfectly suited for the job.
https://substack.pervaers.com/misc/Figure25.png
Cause ;)
Because we know the mechanism is plausible and to be expected.
It's been known for decades that it is ill-advised to vaccinate into infectious disease outbreaks for this very reason. It will worsen the prognosis when double-exposure occurs.
Worse prognosis => higher viral loads => higher transmission rates
The data merely support this notion.
In absence of a mechanism that supports reverse causation, I think we should describe how unlikely it is for these coincidences to happen in so many places during the second half of 2021.
The effect can be observed in almost every country, but the dynamics are very complex. I've played around with simple SI models to see how vaccinating into various phases of an outbreak affects the shape of the wave and what I am seeing is relatively consistent.