Dodgy data: COVID cases in the jabbed undercounted via 'the 14 days'
Our last entry concerned the theme of ‘dodgy data, with COVID-19 infections/hospitalisations/deaths being exaggerated, and COVID-19 vaccine deaths being undercounted. Now we have more on dodgy data, specifically relating to differences in how data is handled based on vaccination status, due to an article published in the Journal of Evaluation in Clinical Practice. The authors (Fung, Jones, Doshi [an editor of the prestigious BMJ]) discuss several biases that indicate (if these biases are not always accounted for in observational studies, and they most definitely are not) that the effectiveness of the mRNA COVID-19 vaccines in observational studies is being heavily exaggerated.
The most important appears to be one many of us have worried about from the beginning, the dubious “case-counting window bias”, which concerns the 7 days, 14 days, or even 21 days after the jab where we are meant to overlook jab-related issues (the focus here is COVID infections; I am working on a similar journal article which also discusses adverse effects) as “the vaccine has not had sufficient time to stimulate the immune system”. In an example using some data from Pfizer’s clinical trial, the authors show that thanks to this bias, a vaccine with effectiveness of 0%, which is confirmed in the hypothetical clinical trial, could be seen in observational studies as having effectiveness of 48%. Source.
Okay then.
Extra: While it may be appropriate to take this ‘not fully vaccinated’ window into account when giving advice around behaviour after the jab, is it really appropriate to ignore a significant chunk of COVID infections, as well as hospitalisations and deaths, after the jab when the same is not done for the unjabbed? Going further, is there any sound reason to ignore adverse effects from the jab that occur within the first 1-3 weeks, when measuring safety? This should all be relevant when weighing up risks and benefits, right?
Very old hat. Statistically-minded Substack denizens such as El Gato Malo and Prof Norman Fenton have been exposing this statistical chicanery (which goes back to Pasteur) for the past two years.
In fact Professor Fenton has shown that, in any normal viral epidemic situation, inclusion of the 0-14 day vaccinated in the unvaccinated category will inevitably lead to the initial appearance of a high degree of vaccine efficacy, even for a placebo. This arithmetical effect diminishes over time (as it must) - exactly as the supposed benefits of vaccines were seen to diminish over time.
The efficacy is negative in the first weeks.
The mass injections are kicking off waves.
Older vaccinations and previous infections protect to some degree.
Since vaccination rates and daily injections correlate highly across regions, you need to look for times when new daily injections p.c. and total adminstered injections p.c. diverge.
In the USA this happened during Delta, Q3 2021.
That's where you can see the real dynamics. The rest of the time these dynamics are masked by collinearity.
https://q3deathwave.pervaers.com/