[origin_path]

Two problems:

1. That wasn't a controlled experiment. Observational data < RCTs.

2. You are mixing up mortality and mortality attributed to COVID. It's a common error. For overall mortality the picture is far less clear. For example in the Pfizer trials there were more deaths overall in the vaccinated arm than the unvaccinated arm i.e. RCT evidence = no mortality benefit.

Also, we now have excess deaths above the expected baseline for long periods in 2022, which is unprecedented. Governments are highly reluctant to split these deaths out by vaccine status, but the increase seems mostly attributed to heart and blood clotting related deaths. So the data from the "experiment" is not obviously positive.

[zionic]

>You are mixing up mortality and mortality attributed to COVID.

There's also the problem of governments playing funny games around deaths and "vaccinated". Someone who died from an adverse reaction immediately following their shot would not count as a vaccinated death, because the _definition_ of "vaccinated" meant you completed the vaccine schedule which was multiple shots over time.

[Izkata]

Not just after the last shot, you're not counted as fully vaccinated until two weeks after the last shot: https://www.cdc.gov/coronavirus/2019-ncov/vaccines/faq.html

(look under "Am I still considered fully vaccinated if I don't get a booster?")

[peter422]

Please show any evidence of this claim.

In trials the vaccines were tested in tens of thousands of people where adverse reactions were meticulously recorded and there just isn’t any evidence that the vaccines caused immediate death in anybody.

Then beyond that there isn’t any evidence that there also is a government conspiracy following the first dubious claim.

[Sohcahtoa82]

> For example in the Pfizer trials there were more deaths overall in the vaccinated arm than the unvaccinated arm i.e. RCT evidence = no mortality benefit.

> Governments are highly reluctant to split these deaths out by vaccine status, but the increase seems mostly attributed to heart and blood clotting related deaths.

[citation needed]

[stoneglyph]

There were approximately 40k people in the vaccinated and the placebo groups. One group had 17 deaths, and the other one had 21. If you are not aware of this information, how can you consider yourself informed on the topic?

[importantbrian]

There is a pretty good reason that the Pfizer RCT doesn't show excess mortality benefit. It wasn't designed to study that. The recruited population is mostly healthy as individuals with multiple risk factors were excluded. For example the proportion of the study group over 65 and the proportion with at least 1 comorbidity is much smaller than the population as a whole. The studied group was very unlikely to experience mortality in the first place so a much larger study would be needed to show any evidence of an effect on mortality. The difference between 17 and 21 is not statistically significant.

In the absence of a large enough RCT we're left with observational studies and there are a ton of these now. The observational data shows a large mortality benefit in the vaccinated population and I'm not aware of a single observational study that shows the opposite, but I suppose there could be one out there that I have missed.

The preponderance of the evidence is pretty strongly in favor of the vaccinated population experiencing lower mortality than the unvaccinated population.

[stoneglyph]

Can you lead us to this preponderance of evidence that is out there?

[importantbrian]

Sure. I'm not going to do a full lit review for you. You can search PubMed and do that on your own if you like. But here are a few good ones.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8556631/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8553028/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8513403/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8162901/

https://pubmed.ncbi.nlm.nih.gov/35901091/

https://pubmed.ncbi.nlm.nih.gov/35891173/

https://pubmed.ncbi.nlm.nih.gov/35891151/

https://pubmed.ncbi.nlm.nih.gov/35855494/

https://pubmed.ncbi.nlm.nih.gov/35821984/

https://www.covid-datascience.com/ also has some helpful discussions of this stuff if you don't want to have to dig through a bunch of studies.

[Sohcahtoa82]

17 vs 21 in a study of 40K is not statistically significant.

[stoneglyph]

And yet, this is the "science" that was used to push the vaccines on the entire population. It just so happens that the group with the larger number of deaths was the vaccinated group, but we aren't allowed to talk about that. A question: why was this not discussed?

[Sohcahtoa82]

> And yet, this is the "science" that was used to push the vaccines on the entire population.

Yes. It's sound science. What problem do you have?

> It just so happens that the group with the larger number of deaths was the vaccinated group, but we aren't allowed to talk about that. A question: why was this not discussed?

It wasn't discussed because 17 vs 21 in a sample size of 40K is not a statistically significant difference. I don't know how to make that more clear without going into a lesson in high school-level statistics.

[manwe150]

So, really, it was discussed, as indicated since you and they heard of the discussion. It is indeed quite simple to discuss even, since the conversation should end with learning that this is covered in high-school stats class.

What is more ironic to me is that this is the total deaths number, without any regards to cause. And in a large population of 40k healthy individuals, is is expected for a few to unexpectedly die over 6 months. This is ironic, since skeptics also often seem to claim that 10-50% excess all-causes death in the population was just random noise.

[origin_path]

Lack of statistical significance does not mean you get to assume the outcome you want, it means you can't say for sure if the effect exists or not. Therefore if you see more people who take the vaccine die than those who didn't, you need more data. End of story.

This should be obvious, indeed, obvious from high school statistics classes. If the effect does in fact exist and you roll out the vaccine on a global scale, you will end up creating a truly enormous number of deaths that should have never happened. Therefore you must be sure that the number of deaths will reduce. Their data couldn't prove this so it should never have been approved. But of course the whole thing was on rails from the start. The idea that governments would have rejected the vaccine trials when they were telling people vaccines were the only way out of lockdowns and buying up millions of doses before the trials even completed, is naive in the extreme.

The core problem for COVID vaccines is of course that COVID just isn't very deadly and many of the so-called COVID deaths were in people dying anyway of other reasons where the cause of death was spuriously mis-assigned, i.e. not people who will join trials. That's why they struggled to show any impact on death.

[origin_path]

OK. Deaths in the RCTs:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4072489

[edit: fixed typo in link]

"To examine the possible non-specific effects (NSEs) of the novel COVID-19 vaccines, we reviewed the randomised control trials (RCTs) of mRNA and adenovirus-vector COVID-19 vaccines ... For overall mortality, with 74,193 participants and 61 deaths (mRNA:31; placebo:30), the relative risk (RR) for the two mRNA vaccines compared with placebo was 1.03 (95% CI=0.63-1.71)"

Excess deaths in the UK. Useful because (a) it's all in English and (b) the UK authorities do split out deaths by vaccine status unlike most places:

https://www.telegraph.co.uk/news/2022/08/18/silent-crisis-so...

"For 14 of the past 15 weeks, England and Wales have averaged around 1,000 extra deaths each week, none of which are due to Covid. If the current trajectory continues, the number of non-Covid excess deaths will soon outstrip deaths from the virus this year – and be even more deadly than the omicron wave. The Government has admitted that the majority of the excess deaths appear to be from circulatory issues and diabetes – long-term, chronic conditions that can be fatal without adequate care."

Increases by cause of death:

https://dailysceptic.org/wp-content/uploads/2022/09/image-5....

Dashboard that lets you explore the data directly from the source:

https://app.powerbi.com/view?r=eyJrIjoiYmUwNmFhMjYtNGZhYS00N...

UK data at first appears to show that the unvaccinated die at a higher rate. However, this is only because they're using incorrect population figures. Although it may seem absurd the government population figures in the UK are officially labelled "experimental" because they are universally acknowledged to be far too low. In some age groups the official population is lower than the number of people who came forward for immunization, so these figures cannot be used and indeed the UK HSA didn't use the official population stats when computing their own effectiveness rates, but rather estimates from NIMS (National Immunization Service). If the same methodology is used then you can calculate chart 4 on this page from officially released data:

https://bartram.substack.com/p/deaths-by-vaccination-status-...

"The ONS data is interesting because it also includes data on non-Covid deaths by vaccination status ... Using this alternative estimate of the population of England [from NIMS] now suggests that the vaccines substantially increase the risk of death for reasons other than Covid."

Unfortunately and worryingly, even the NIMS estimates are likely to be seriously off. According to NIMS about 9% of the British population refused vaccination but a few months ago the BBC commissioned a professional survey from a polling firm, to ask people questions about their vaccine status and if they didn't take it, why not. They were surprised to discover that 25% of people said they were unvaccinated.

> To examine the possible non-specific effects (NSEs) of the novel COVID-19 vaccines, we reviewed the randomised control trials (RCTs) of mRNA and adenovirus-vector COVID-19 vaccines

[importantbrian]

Did you bother to click on that first link? It's broken because the authors retracted the paper. This kind of stuff is the reason it's hard to take vaccine skeptics seriously.

[origin_path]

Yes, that's how I quoted from it. The link had a number deleted from the end, a mistake whilst editing the post. I fixed it. The authors haven't retracted the paper.

[Sohcahtoa82]

> For overall mortality, with 74,193 participants and 61 deaths (mRNA:31; placebo:30)

31 deaths with mRNA and 30 deaths with placebo with over 74K people in the trial to me means that mRNA carries zero risk. In a sample size that large, 1 additional death means essentially zero correlation.

> https://www.telegraph.co.uk/news/2022/08/18/silent-crisis-so...

Article is subscribe-walled. Not subbing.

> Dailysceptic

I'm not going to accept "Daily Sceptic" as a source.

> PowerBI

I don't find the data in this dashboard to be very incriminating. Excess deaths are still highly attributed to COVID.

> https://bartram.substack.com/p/deaths-by-vaccination-status-...

This article is very painfully committing the Base Rate Fallacy.

See https://twitter.com/sailorrooscout/status/154723580144821043... for a good explanation on that.

[origin_path]

"This article is very painfully committing the Base Rate Fallacy."

You didn't read past the first sentence, did you? Embarrassing, because the article starts by explaining the base rate fallacy and pointing out that the social media meme it starts by highlighting is wrong. Then it goes on to do correct analysis, which shows the conclusions I gave. You'd have known this if you read my post properly too, because I have a whole paragraph about the stats involved in correctly calculating base rates. If you think there are mistakes in the rest of the article please explain them, but you do need to actually read it first.

"I'm not going to accept "Daily Sceptic" as a source."

Again you didn't even click the link and look, did you? The image is a table of data from official government statistics, they simply happen to host the screenshot. But I knew I'd get a response like that from someone. Lack of intellectual curiosity around this topic is extreme - for obvious and understandable reasons of course. But still.

Re: PowerBI

Where do you see that? There are virtually no COVID deaths (a.k.a. "had a positive test a month before death") since the end of the winter in the UK. Look at the data for the various kinds of heart failure, for example. You see clear excess where COVID isn't implicated starting around the end of April.

"1 additional death means essentially zero correlation."

After incorrectly snarking about not understanding statistics, you're now demonstrating a mis-understanding yourself (albeit a very common one).

You can't simply look at a small difference and say "not statistically significant therefore there is no risk". That's not how statistics works. Firstly, the overall sample size was very large, it was an RCT. So we can say with great certainty that the vaccines have no effect on mortality, yet, that was the entire purpose of developing them. I see up thread some people are now trying to deny this, claiming that the vaccine trials were never meant to even study death rates! Truly Orwellian stuff. Death is the endpoint that motivated everything.

What we can't say with great certainty is if the vaccines are truly more deadly than the placebo. But statistical significance is not the same thing as significance. This is a really common logic error you see even amongst scientists themselves (when badly motivated). This result means the vaccines might be more deadly than the placebo or might not, and therefore the correct response is to gather more data. The incorrect answer is to say "eh, yolo, let's assume the optimistic result", especially if you're about to force people to take it on a massive scale.

But of course they didn't gather this data. The people who created and run the COVID vaccine programmes think that any expression of doubt about vaccine safety is immoral anti-science anti-vaxx insanity, which in turn means they can't neutrally measure or act on data. Their conclusions are chosen before they even do a single experiment, so they just went ahead and did it.

At any rate, the placebo in these trials was incorrect. They gave the placebo arm vaccines too, just different ones, so this is actually not comparing against reality (=no vaccine) and therefore overly generous to the vaccine under test.