What are the characteristics of unvaccinated elderly?
Are there shared causes of V status and health outcomes?
Are those unvaccinated elderly (~10%) exchangeable with their vaccinated counterparts (90%) on key health-related variables?
3/ For example, is the proportion of frail elderly similar in those populations?
All these questions convey a single concept in epidemiology: Confounding bias.
Example: if frail elderly make up 20% of unvaccinated but only 10% of vaccinated, true VE is lower.
4/ Next.
Monitoring systems make it clear that
V--> severe side effects/death.
What is the effect of V on all-cause hospitalization/death?
People need to know. That’s the ultimate VE. We die only once
They have the data. They will not be able to hide it forever @MLevitt_NP2013
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2/6 A case-report is part of medical research.
Its weaknesses: very small sample (n=1), no estimated effect.
Nonetheless, it is research.
How come?
It is an observational study and there is “sort of” control.
3/6 The observer sees something “unusual”, “surprising”.
Q: what is “surprising”?
A: contrast with expectation
Q: where does “expectation” come from?
A: from past experience.
That past experience is the “control”
1/ They are at least incompetent.
The analysis in the post is valid. What CDC is doing here corresponds to the proportional mortality ratio (PMR) in epidemiology. (You can read about it in the textbook "Modern Epidemiology").
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"An implicit assumption of a proportional mortality study is that the overall death rate for categories other than the ones under study is not related to the exposure".
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3/ Translation, for AE= death:
An implicit assumption of the CDC computation is that the overall AE rate for categories other than death is not related to COVID vax. Which means that the effect of COVID vax on all other AE is not different from the effect of other vaccines
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4. And it is not just waning, if true. (Ab levels decline after natural infection, too, but protection is not lost. Memory cells play a role in re-infection.)
5. VE for severe disease is currently 70-80% at most (and still possibly biased).
3/ 6. Vaccine has side effects, including deaths. They never report effects on all-cause deaths/hospitalizations. Why?
7. Now 3rd dose vaccination with little to no empirical basis and numerous reasons for concern. Vaccination during a rising wave is a dangerous experiment.
2/ Trying to split a total of 243 (eTable 1) into mutually exclusive categories of vaccinated and reconcile with a flow chart (Figure 2, with additions).
No clear understanding how the numbers are split.
3/ However, it is clear to me that the data are hiding excess risk between dose 1 and one week after dose 2.
Likely >2-fold, (1.3-fold under the most conservative counting).
2/ Here is what we see:
Continued divergence between infected vulnerable and non-vulnerable (by age).
Was fairly parallel in winter.
This divergence is the most important difference between current (summer) wave and winter wave.