> higher than the risk reduction for COVID-19 hospitalization relative to the placebo group (6.4 per 10,000 participants).
This is a deceptive statistic.
They're only reporting adverse events due to COVID-19 hospitalization in the window of the study.
This will miss adverse events due to undiagnosed COVID-19 and it should be using the participants who contracted COVID-19 as a denominator, since essentially everyone will be infected by the virus eventually and the lifetime-horizon risk in the placebo group is much longer than the window of the study, while the vaccination risk obviously starts with the introduction of the antigen and then drops off rapidly after 3-6 months.
To make it more accurate the placebo groups should have been followed longitudinally for 5-10 years until nearly everyone had seroconverted or tested positive, and compare that against the vaccine group, and compare all outcomes and not apply the diagnosed COVID-19 hospitalization filter to only one arm.
Really bad "study" that is just some bad undergrad-level number crunching and misapplication of statistics to the vaccine trial numbers.
This. Every vaccination-is-dangerous paper I've seen suffers from this flaw. They always seriously downplay the risk of actually getting the infection, especially the risk of getting it for the first time.
There usually are no long term risks of vaccination. Drugs rarely have consequences that don't show up while taking them--and you don't keep taking a vaccine.
More importantly: when the spike protein and everything related to the vax has left your body, it's theoretically impossible for it to cause damage. It could be lingering damage that was undetected when first jabbed, but name a vax that discovered serious events years later.
This study answers a simple question: "If I deploy this treatment to x people, how will this affect the outcomes of those people over the next y months (where y is roughly the same as the study length)?" And this sort of study, when impartially carried out, can provide a reasonably accurate answer to that question.
I fully agree that there are plentiful problems with this. Such a study would conclude that smoking cigarettes is perfectly healthy! But going beyond that is generally not possible in any meaningful way, because one cannot see into the future. For instance you now claim, with hindsight, that effectively 100% of people will be infected by COVID. Yet at the same time these studies were happening, we were carrying out actions, ostensibly well informed and in good faith, that promised to be able to effectively eliminate COVID if we just e.g. shut down the country for 'x' weeks.
And so you now want to compare risk(COVID) vs risk(vaccine), but these vaccines ultimately proved themselves unable to meaningfully prevent COVID infection or spread. So instead you need to compare risk(COVID) vs risk(COVID + vaccine). And similarly the vaccines also ended up with brief periods of efficacy, so again you need to factor in yet another variable: risk(COVID + vaccine + boosters x time).
And that's really just getting started. Imagine trying to factor in completely unknowable, yet inevitable, viral mutations. Ultimately, these long term models are more likely to reflect the biases of the person building them than any actual relationship to expected outcomes. And when there are tens of billions of dollars at stake for a model to give the "right" answer, I don't think this is anything we ought ever aim for. Like in software, KISS. [1]
> Yet at the same time these studies were happening, we were carrying out actions, ostensibly well informed and in good faith, that promised to be able to effectively eliminate COVID if we just e.g. shut down the country for 'x' weeks.
I don't think that's true. Pretty much within a month or two, most of the conversation was around "flatten the curve", which is explicitly not about stopping the total number of cases, but rather lowering the peaks of simultaneous cases.
And when the vaccines came out, it was clear fairly quickly (though maybe after this study? I don't know) that the major benefit of them would be to the severity of the illness, not to prevention of spread.
This study is looking at the data from the trials upon which the emergency authorization was granted. So you need to warp back to somewhere around August 2020 to December 2020. Extreme views at the time were more the norm than the exception at the time, both in terms of the potentially negative impact of the virus, and the potentially positive impact of various measures to combat it.
The suggestion here is very clearly that the study can answer the question of the relative safety of the vaccines vs. the virus. Which it cannot. Which you absolutely do need a time machine to answer correctly. Which was exactly my point.
Insinuating that this study answers that question is just pure bullshit.
What I'm trying to emphasize is that by your standard of evidence, no study could ever answer anything. And that's not an entirely unreasonable position to take. For instance I know of one scientist, who is part of the National Academy of Sciences no less, who believes that the studies against smoking are insufficiently compelling. And it's for, more or less, similar rational to what you're putting forth here.
On the other hand, the viable ability to set up an insurmountable standard of proof does not really change the picture here. The data available, under the time frames studied, do not paint a positive picture of the safety or efficacy of these drugs. If you get into section 5 of the study, you can see how both the FDA and the pharmaceutical companies worked to pad the numbers to make them look better, including things like lumping thousands of individuals into the experimental group even though there had been no follow up on these individuals, meaning they had no idea of their outcomes.
> To make it more accurate the placebo groups should have been followed longitudinally for 5-10 years until nearly everyone had seroconverted or tested positive
Geez, you’re raging against the authors for not seeing into the future? The virus has only been here for less than 3 years This is worse than the job requirements that demand 20 years experience in node.js
I'm raging against the people here who are using it to suggest that this study answers the question of relative safety of the vaccine vs the virus.
This study doesn't do that, it can't do that, so it can't answer that question, so it really isn't worth posting that little nugget.
Those are the requirements for answering that question. The study cannot meet those requirements. The study cannot answer that question. Dunno why this math is so difficult.
This is a deceptive statistic.
They're only reporting adverse events due to COVID-19 hospitalization in the window of the study.
This will miss adverse events due to undiagnosed COVID-19 and it should be using the participants who contracted COVID-19 as a denominator, since essentially everyone will be infected by the virus eventually and the lifetime-horizon risk in the placebo group is much longer than the window of the study, while the vaccination risk obviously starts with the introduction of the antigen and then drops off rapidly after 3-6 months.
To make it more accurate the placebo groups should have been followed longitudinally for 5-10 years until nearly everyone had seroconverted or tested positive, and compare that against the vaccine group, and compare all outcomes and not apply the diagnosed COVID-19 hospitalization filter to only one arm.
Really bad "study" that is just some bad undergrad-level number crunching and misapplication of statistics to the vaccine trial numbers.