Hacker Newsnew | past | comments | ask | show | jobs | submitlogin

You may want to look at this paper to get a better idea of risk and benefits, e.g. Fig 2 and Fig 3: https://www.ahajournals.org/doi/full/10.1161/CIRCULATIONAHA....

One also needs to understand that myocarditis is not uncommon, and especially common after viral including COVID itself. Also "subclinical" means that this includes mild cases and here the 0.1% also included arrhythmia. Looking at the other paper above, they found 1 (!) person with subclinical myocarditis while screening for it in a population of 4928. Also interesting to put this in perspective: "Underlying disease was present in 109 (2.2%) of the patients, with simple congenital heart disease in 33, mitral valve prolapses in 36, arrhythmia in 36, Kawasaki disease in 11, and previous myocarditis in 2"

Your idea that excess mortality is caused by the vaccine rather than COVID itself seems far fetched to me.





Your own link shows 128 cases of myocarditis within 7 days of ~2m vaccinations for 12-17 year old males, against an expected rate of 0-4. That's an overall rate of 1:15,000. And that study is based entirely on people with severe enough side effects for them to end up in the hospital following vaccination and to consequently be diagnosed with myocarditis, and only within 7 days. In other words it's definitely lowballing the figure.

And it's things like this that destroy trust. Because we're already speaking of an unacceptably high rate of severe side effects, based on this single one (amongst many possible), for that demographic. Typical rate of severe side effects from vaccines are in the 1:1,000,000 rate. So why was this recommended, and defacto mandated, for that age group, again? And where's the accountability for those that made this decision, and for the trials that failed to make clear such extremely high rates of side effects?

I realize I'm going on a slight tangent instead of arguing my rather extreme claim. The point I'm making here is that the messaging on these vaccines has not been carried out in good faith, and that they do have clear and severe side effects that should have made them a non-starter for at least certain demographics. And as we continue to see excess mortality rates that are comparable to what it was mid-pandemic (during the lulls between spikes), the possibility of longer term side effects seems to me to be, at the minimum, viable.


"So why was this recommended, and defacto mandated, for that age group, again?" Because by preventing cases or even just reducing the virus load, it decreases the likelihood of spreading the virus to others.

Approximately 100% of people ended up getting COVID, the overwhelming majority - repeatedly. So once again these were claims that, while at least reasonable on the surface, were made without any evidence in support of them and turned out to be, if not false, then misleading.

So people now tend to change the goalposts - okay it didn't stop the spread or stop people from getting it at all, but helped spread out the spread - flatten the curve, and reduce the impact on hospitals. But again that also seems completely false. Here [1] are the data on cases in the US. By August 2021 the wide majority of Americans had taken one of the shots. The biggest surge, by an overwhelmingly large margin, would come on January 2022 where we went from a former peak of ~250k to a new peak of more than 900k daily cases.

So now the goal posts get shifted yet again. Okay it didn't stop the spread and it didn't flatten the curve, but it reduced the rate of severe cases. This one is a bit trickier. It's superficially true, yet subject to extreme biasing. If you look at the overall outcomes of people admitted to hospital by vaccination status, unvaccinated individuals did often have worse outcomes. But there's a rather huge bias - people inclined to vaccinate for COVID are also the type more predisposed to seek healthcare earlier, whereas those disinclined to vaccinate tend to be less inclined to seek healthcare unless it's critical. This bias (one amongst many) was repeatedly listed in the limits of various studies, but people just ignored this (and them) even though it's a major factor. There was never any study (to my knowledge at least) that tried to compensate for these biases.

[1] - https://www.worldometers.info/coronavirus/country/us/


I am not sure how you come to the conclusion. My link goes to paper that is a bit old, I did not do a new literature search, so I am not sure how the risk calculation may have changed since then. But at that point (2021) the benefit of vaccine was very clear also for 12-17 year old males. You seem to massively overestimate the risks of mild myocarditis compared to the risks of a covid infection in unvaccinated people.

The study only considered people who end up being diagnosed with myocarditis after seeking medical treatment at a hospital following vaccination with 7 days, and it "predominantly" resulted in subsequent hospitalization for multiple days; on top of this myocarditis can cause longterm irreparable damage. The paper classified that as mild, and perhaps that is the clinically correct term, but it's certainly not the colloquially correct one. In any case rates of all myocarditis and various cardiovascular issues are obviously going to much higher than 1 in 15,000.

As for the risk:benefit analysis, the paper created a typical false dichotomy. It compared getting the shot vs an aggregate case of getting COVID. The reality is that if you got the shot you still ended up getting COVID, often multiple times. And the aggregate comparisons were disingenuous because COVID had dramatically different typical outcomes dependent upon health status at the time of infection. Those with significant preexisting conditions made up the overwhelming majority of negative outcomes.

But even with this false dichotomy they found that they'd only prevent 1 death from COVID per million cases, which I assume was rather liberally rounded up. So that is known as 1 micromort. [1] That's a fun page because it gives some context to mortality risk. 1 micromort is a bit less than everybody experiences every day in the US of dying from a non-natural cause, excluding suicide.

[1] - https://en.wikipedia.org/wiki/Micromort


This is not a study but a review article, so it seems you are bit confused. The point is very simply and confirmed by many studies: The increased risk from COVID when unvaccinated is much higher than the risk from myocarditis caused by the vaccine in rare cases. And no, I do not see how the paper made the mistake you claim. It compared the increased risk for getting myocardities after the shot to the reduced risk from COVID (and these risks also include myocarditis caused by COVID which is also know to be more severe).

The benefits cited in the paper (and most others) were based on the ultimately false claims from vaccine manufacturers. You can see the CDC slides they based their numbers on here. [1] The CDC removed it from their website, for reasons, which is why I'm linking to an archive.

The CDC is opaque about exactly what numbers they ended up using, but their slides included claims of vaccines being ~95% effective at preventing infection and ~100% effective against hospitalization/death. Obviously those claims were false, and so it completely ruins the risk:benefit analysis, because the benefits were grossly overstated.

Amusingly, you can actually see an immediate error in the study you linked to. Their figure 2 was simply ripped directly from the CDC slides, but they failed to copy/paste the data for 12-17 year old males correctly. You can see it's identical to females. You'd think that have triggered some 'ermmm?' in reviewers, to say nothing of the researchers. Alas, such is the state of science now a days.

[1] - https://web.archive.org/web/20220730093118/https://www.cdc.g... (slide/page 32)


Please specify which numbers you exactly you are referring to. Slides are also irrelevant, all these studies are published. You also need to understand that there are many independent studies confirming this (many I looked at as well as colleagues I know and trust). One also need to understand the effectiveness changes over time, so numbers which are correct in some initial setting may not apply in another setting. This does not imply that somebody "lied". You seem a little bit of a conspiracy theorist interpreting everything which seems suspicious to you as proof for that you are being lied to? Like climate change deniers you assume that all researchers of the world somehow conspired to hide the big lie?

Edit: So one of the original studies cited in slides which you seem to claim was a "lie" is this one: https://www.nejm.org/doi/full/10.1056/NEJMoa2034577 This was a large collaboration of scientists (made doctors that that swore the hippocratic oath). You think the misreported the results of this study?


In order to calculate the benefits of a vaccine, you need to know the efficacy of a vaccine. The study's efficacy figures were using the CDC's data to try to assess this. The CDC, in turn, was basing their estimates on false claims from big pharma. The study then misrepresented the CDC's data (at least in the study's figure 2) through incompetence.

You are right that there seems to be a copy mistake in Figure 2. But the mistake is the wrong direction, i.e. the risk from COVID actually is even higher as shown on the figure. But again, the main problem is that you pick such an inconsistency and mistake (which you will always find somewhere), and take it as "proof" that your conspiracy theory is right, completely missing the big picture that basically all scientists and doctors working in these field would need to be part of it over many years - still faking studies. Pretty unlikely.

My pointing out the mistake is to emphasize the frequently low quality of these studies and their reviewers. Think about the fact that nobody caught a glaring (and self-revealing) mistake on one of the highlight figures. A random anon should not be finding mistakes in peer-reviewed studies in a 5 minute skim for some completely pointless argument on the internet. Yet here we are...

And I think you're increasingly turning to ad hominem and strawman because of cognitive dissonance. You want to believe their claims were true - 95% efficacy, near 100% against hospitalization and effectively 100% against death, yet you obviously know they were not. Basically everybody ended up getting COVID, usually multiple times, and hundreds of thousands of fully vaccinated individuals died of COVID in the US alone.

Why exactly they were ultimately wrong is largely inconsequential. All that matters is that they were.


You say this as if you discovered some major flaw. And is, of course, expected that also some vaccinated people die from COVID. The point is that the risk of dying substantially decreased with vaccination. Something one can only find out by doing a scientific study. And that this risk decreases was confirmed many times in many studies by many independent scientists. For example, here is a recent meta-review summarizing results from 33 studies: https://publications.ersnet.org/content/errev/34/175/240222....

Of course, I am very sure you will also find some flaw or inconsistency in this or in all of the 33 studies that you take as proof as why this is all "ultimately" wrong. But at some point you need to ask yourself: Are basically all scientists that look into this professionally incompetent or correct? Or maybe, just maybe, it is me who got worked up a little bit in a conspiracy theory and not every flaw or inconsistency is clear proof that I am right and science is wrong.


I'm not entirely sure what you're trying to argue at this point. What, if anything, and please be specific, do you even disagree with that I've said?

Basically you linked to a paper showing high rates of myocarditis following injection in the US and claimed it had a net benefit because the paper claimed so. It turns out the papers claimed benefits were based on the early exaggerated claims of vaccine efficacy, and now you're linking to something from Europe that indeed shows dramatically lower benefits than the original paper assumed.




Consider applying for YC's Winter 2026 batch! Applications are open till Nov 10

Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: