Your first stop when evaluating a massive and heterdox claim like this should be to double-check their fundamental data against other sources [1].
What you'll find is that other sources do not contain the same data at all. It's not just slightly different, it's _wildly_ different. There is no large jump in mortality in April 2021. There _is_ a large jump in morality 2020.
I don't have time to thoroughly examine their research, because it doesn't come close to passing a sniff test.
On a separate note, it's really discouraging how this stuff gets voted up on HN. Flagged.
The two researchers actually have a number of publications in data science, please sniff again. Your kind of argument is called a an appeal to an irrelevant authority. You also forgot to cite your sources or link to the data you are advocating for. Please consider taking the time to properly advocate your point
Two people who have never published in epidemiology stumble upon a new method for calculating excess deaths, at odds with all the existing sources, whether official sources like the WHO, domestic official government sources, or other independent groups like The Economist which have tracked this closely.
And lo and behold, what do they find? A wildly different result that shows no deaths from Covid and all the deaths from the vaccine.
No, I'm not going to sniff again, because it stinks to the high heavens.
I think we could all appreciate if anyone with an epidemiology background could explain what disqualifies data scientists from working with this dataset.
I'm not an epidemiologist, but I've written code for people in various fields. I knew code, they knew the domain. All of them knew things that I would have fucked up, if I had tried to write the code with just my programming knowledge and my big brain, without their domain knowledge and experience.
A university education teaches you something.
I assume that epidemiology is like the other university fields — when lay people come and show that the epidemiologists are wrong about epidemiology, they're about as likely to be right as the people who write to maths professors claiming to have found a method of trisecting an angle. And the people with the novel claim and the missing education bear the burden of proof.
I dont think that comparison is universally applicable. I wouldnt rule out that this is a lot more similar to a Math Prof telling you that the p-values in for example your psychology paper are nonsense and correcting you.
edit: Not saying studying Math qualifies you to design and run studies in Psychology. But once you break down tasks enough you will often find them to be the area of expertise of another discipline. Often its very easy to tell when the Professor that taught you something in university is from another department.
When we close ourselves off to new information, especially if it's contrary to deeply held beliefs, our opinions devolve from informed to merely dogmatic.
That is absurd, and little more than a platitude. Let's set the stage here:
* I am not an epidemiologist
* The authors of this study are not epidemiologists
* The paper has not been peer-reviewed
* The authors invent a new statistical method for estimating excess deaths, it is at odds with all other sources, and it just so happens to show no excess deaths from Covid until the vaccine is released
In situations like this, you should always default to disbelief.
You are not coming across like you read the paper. Nor does it seem like you are making an argument in good faith.
I see a weird ad-hominem, appeals to authority and tradition, and some knee-jerk criticism. You haven't addressed legitimate criticism of your arguments, and you're all over this thread (6 of 44 comments) trying to convince people to dismiss this out of hand.
Your main criticism seems to be that the paper points out an anathema correlation, therefore warranting immediate disbelief and removal from discussion... Who are you, to make such a strong claim? Since when is that how discussions or science work, even if you were the world's top epidemiology / statistical method specialist?
Extraordinary claims require extraordinary evidence. I'd say that with only reading the abstract, i gave this study a baysian 15% likelyhood. Then i read the first chapter, and it fell to .0015 or something like this.
I actually worked at a cloud provider dedicated to provide a lot of Ram and GPU ressources to researchers, and we worked with 'ARS grand Est' (think local CDC who coordinate hospital response and emergency allocation for all hospital, including private clinics, in a State) in March through june 2020. I've seen the numbers, I've read the rapports firsthand, before the French lockdowns, i imported the data files and seen the different number of reported death at Colmar compared to the biggest hospital of the Area (Strasbourg). There is no way this document is true. Want to be sure? Just look at Bergame vs Sienna, or even just Colmar vs Strasbourg in March/April 2020.
Video i found about my cousin hospital: https://www.dailymotion.com/video/x7sysei (English subtitles). They had to take beds from addictology services and registered two dozen more alcohol related deaths than in 2019.
The link i had on mortality in Grand Est hospital is now dead, but it was quite interesting.
I stopped after the first chapter, because to me, the likelihood of the article being true after that was too low.
If you evaluate this chapter and the abstract differently than I do (let's say 50% after the abstract because your are totally open minded unlike me, and 5% after the first chapter because it's really bad but you don't have the negative prior i have), and continue, maybe what's after is more compelling.
But to me, it's hogwash. Unless they write something better.
You shouldn't be flagging articles simply because you disagree with them, that's not what flagging is for.
Especially because you are wrong - the OurWorldInData link you provide does indeed show German excess mortality climb steeply in April 2021 and then again in March 2022. Current mortality by that data has been at the same level as it spiked to in April 2020 (first wave), but sustained since March. I don't understand how you can look at the graphs there and not see it because the data is so plain.
Remember that after COVID we should be seeing negative excess mortality due to the pull-forward effect. We should not be seeing positive excess mortality after an epidemic that near exclusively takes out the elderly. The pull forward effect can be seen after the winter 2020 wave in the German data but not later.
"On a separate note, it's really discouraging how this stuff gets voted up on HN. Flagged."
It's really discouraging how some people visit a site meant for "intellectual curiosity" and then immediately and incorrectly flag anything that creates cognitive dissonance in their mind, especially when they go on to make misleading statements about the data.
> The high excess mortality in 2021 was almost entirely due to an increase in deaths in the age groups between 15 and 79 and started to accumulate only from April 2021 onwards. A similar mortality pattern was observed for stillbirths with an increase of about 11 percent in the second quarter of the year 2021.
At first I thought that stillbirths would be expected to go up if there were more births recorded as well, but they did control for that and recorded the stillbirth rate per 1000 births.
Can someone how understands this give a quick rundown?
Why did mortality jump 40k deaths from 2019 to 2020? AFAIK covid only started in 2020? Or am I reading the charts wrong?
(Just looked at the figures, did not read the whole paper)
This paper attempts to correct for the inconsistent data and reporting around mortality, excess mortality, and deaths that were actually caused by SarsCoV2.
They use actuarial science (what insurance & risk analysis uses) to predict a baseline for mortality if no pandemic occurred. This should be a fairly accurate representation working of historical data.
It is sad that this submission has been flagged by zealots as it represents an interesting approach to determining the impact of the pandemic and attempts to correct for factors that unfortunately alter the data toward the negative- such as hospital funding contingent on diagnosis.
12.5 BILLION doses have been administered. The datasets are deep and wide, the analysis tools are powerful, and tens of thousands of well-trained epidemiologists have been analyzing the data for many, many months. The opportunity to make one’s mark has never been better.
But it’s these two brainiacs, who are not trained in the science, who have revealed the Shocking Truth that blows the lid off, using weird math and alternative facts.
Don't worry, everyone already understands your complete compliance and apsiration to achieve moral superiority for the sake of something so insignificant as an internet forum slight.
"fremdschamen"
Educating yourself is quite easy once you accept the difficulty in doing so.
I have pity for the lack of control over your personal life you indicate by making such comments. I don't believe there is a German word for this feeling.
"The state-of-the-art method of actuarial science is used to estimate the expected number of all-cause deaths in 2020 to 2022, if there had been no pandemic."
They shall be asked how many people are expected to die tomorrow and then, tomorrow, to explain the difference.
Even if I have been extremely critical of covid vaccine mandates when the mandate is irrespective of age and health condition, I sincerely hope vaccines aren't the cause of this, because the consequences would be terrible in term of public trust. You would end up next time like Russia, with a reasonably efficient vaccine declined by a population who lost any trust in its own government.
Literally all they had to do was make this vaccine optional. Say "hey this vaccine is available. Here is the data we have. We recommend taking it, but of course that is your own decision."
But because of the attempts to force people to take the vaccine (which I did take, btw), trust has already been eroded.
I don't know where you think someone was forced to take the vaccine. It was always optional. It's just that there were additional controls, like going to indoor restaurants -- one of the very highest risk activities for disease spread -- or additional testing requirements.
In the US, nearly a 100 million people still have not taken the vaccine. If there was an effort to force anyone to take it, it sure doesn't seem to have been successful.
Now that the moment has passed, I find it amazing people are still able to maintain the mental gymnastic / reality control that the GP is espousing (unless it's just to be argumentative). You can see how all sorts of human rights abuses get justified once you realize how people can play with language and definitions
There were a few videos of what appeared to be forceful vaccinations but internet videos are hard to cite as real evidence. That officer and medical team could have been forcefully injecting anything into that poor bloke
I'm not familiar with that situation. Many very cowardly and misguided things happen when people are convinced, coerced and congratulated for adherence to dictates.
I would not be surprised at all if it did happen to a large number of people in disadvantaged positions. We know school teachers were bribing children with pizza or attempted to subvert the law and circumvent parental consent.
These people all believe they hold the moral high ground. As does the commenter above. This is "service to the community". Protecting you from something dangerous. With government approval
Section 6.3 claims that the excess deaths coincide with vaccinations. Looking at the graph, I don't buy that there is a clear correlation - for example there is no marked effect for the second shot.
A possible explanation for why the effect isn't linear is that you'd expect the impact to be less for later shots, because people who had bad near-miss reactions to the first will sometimes choose to be "unvaccinated" rather than take the risk of another bad reaction. That then leaves people in the pool whose systems can either take it, or who didn't detect the damage and who then later die unexpectedly (been lots of SADS around lately).
Make an actual falsifiable claim if you want to dispute something.
Do you dispute the paper has not been peer-reviewed? Do you dispute the authors have no background in the field, despite making major heterodox claims? Do you dispute their findings are at odds with all manner of other official sources?
Quickly flagging wild claims from non-experts is a feature, not a bug.
If the data was truly in dispute, it might be a worthwhile debate, but this paper is published by two people that have never published in the field before, and it's riddled with obvious and blatant errors. The fundamental claim, that there was no excess mortality in 2020, is clearly wrong.
This is nothing that is worthy of having a debate over - it's just disinformation spam. It would be like replying to every piece of spam email you receive.
It attributes the excess Covid deaths to the vaccine, not the virus.
The "principle of Abduction" made the front page a while back. Someone made a nice explanation of it, which was essentially that any thinking person needs to have some arguments they investigate and some they dismiss out of hand. This argument is reasonable to dismiss out of hand. What's next flat-earth-ism - but a "serious academic paper"?
Ah, I see people see this argument reasonable to dismiss out of hand.
I wasn’t aware that the C19 vaccines have been scientifically approved safe for use! Since these mRNA applications have passed numerous tests on humans with no significant side effects and harm, it must be indeed a preconceived brief to think otherwise!
In all the statistics I've seen, excess deaths have been driven by Covid variant waves. I'm sure this is no different. Of course, the crazies will go berserk over any temporal coincidence with the vaccination rollout programs.
I'd prefer not to see this kind of nonsense given time of day on HN, as a supposed science/technology based forum.
Its not crazy if we just talk data and statistics. I find the intersection with vax mandates and the overwhelming datasets coming from Germany and Israel and the UK quite interesting. So lets just stick with facts and debate those.
The authors have never published a paper in epidemiology, and trust me, there are plenty of pitfalls even very smart people can fall into when they don't understand the ins and out of a field.
The authors are data scientists. So articulating what exactly the pitfalls are that disqualify them from working with an epidemiological dataset would be really helpful. As a non data scientist, it is not obvious to me what qualification they are lacking when it comes to working with an existing dataset.
I dont think calling published data scientists "yahoos" is such a good look, especially if you at the same time frame the interaction with papers as a matter of trust.
edit: I would also think its also worth reflecting on the fact, that two of the most vocal and derogatory posters in this thread not only share the same opinion but also a show a blatant misconception of how to interact with papers. It is not a matter of trust and not a matter of belief.
Even if you fully believe you are in the right here, is behaving like this really productive? Especially with the major concern most people on the fence on this topic have being the influence of people acting exactly like this on the scientific process?
What you'll find is that other sources do not contain the same data at all. It's not just slightly different, it's _wildly_ different. There is no large jump in mortality in April 2021. There _is_ a large jump in morality 2020.
I don't have time to thoroughly examine their research, because it doesn't come close to passing a sniff test.
On a separate note, it's really discouraging how this stuff gets voted up on HN. Flagged.
[1] https://ourworldindata.org/excess-mortality-covid