Quote:
The initial studies looked solid, the observed impact does not match.
You've argued in a circle now. The premise of your bayesian post was that we can't measure efficacy outside of clinical trials. He says "this is WHY randomized controlled trials are used. you need to get all the bias out and equalized BEFORE you start. there is a reason that study design and enrollment randomization and balance are a whole separate subfield. once the data starts getting confounded in complex ways, you cannot untangle it. you're lost." That's before an accusation of more or less study design fraud, of course. But the point stands - and is correct. Outside of a study, you can't untangle the complexities of confounders in the data.
So you're saying that it doesn't matter what we see in studies, because our observed impact doesn't match, but we can't observe the impact correctly because of the definition of vaccination, which was observed in a controlled study, which doesn't matter.
He makes a completely unfounded argument later that "you do not count the boosted as boosted until 2 weeks after the shot. this is the definition everyone has been using. it was used in the drug trials for these vaccines as well. and doing this is full blown bayesian datacrime." Bullcrap. I showed the graph. They didn't arbitrarily pick two weeks, they picked two weeks because that's when the observed (dramatic) deviation between the vaccinated and control group happened. I genuinely don't understand how anyone can look at the graph in my previous post and say - yeah, that's not a real effect.
You can't have it both ways. The 14 days is a real thing that we observed in the studies AND you can't make reliable observations outside of trials. You can't use the second statement to malign the first.
Quote:
In any case "taking the vax" has no benefit to anyone other than the user.
Several test-negative studies have shown vaccinations to have efficacy both against infection and severe disease. I linked one for you two posts ago, and I linked a recent one earlier for Omicron showing ~70% efficacy. Therefore we can conclude from the evidence that vaccinations reduce both the chance of infection and the likelihood of severe disease. There has been no study done that shows otherwise. If you have one, please share it.
Based on that, the only way this sentence can be true is if there is no second-order risk due to an increased number of total infections in a population. This seems to me to be false by inspection. Reducing the total number of infections reduces each individual's risk of infection. It also reduces the total number of infections which go on to be severe, which reduce hospital loads, which lower risk of harm to anyone who has the potential to need any service at a hospital. Which is to say, everyone.