Excess mortality in Germany 2020-2022(researchgate.net)
researchgate.net
Excess mortality in Germany 2020-2022
https://www.researchgate.net/publication/362777743_Excess_mortality_in_Germany_2020-2022
74 comments
>There is no large jump in mortality in April 2021.
Eurostat reports a 16.1% increase between March and April 2021:
https://ec.europa.eu/eurostat/statistics-explained/index.php...
Europe overall: "Excess mortality levels reached a third peak in April 2021 (20.9 %)"
Euromomo shows a progression from baseline level in March to "substantial increase" in April:
https://www.euromomo.eu/graphs-and-maps
Eurostat reports a 16.1% increase between March and April 2021:
https://ec.europa.eu/eurostat/statistics-explained/index.php...
Europe overall: "Excess mortality levels reached a third peak in April 2021 (20.9 %)"
Euromomo shows a progression from baseline level in March to "substantial increase" in April:
https://www.euromomo.eu/graphs-and-maps
This guy apparently took the time to propose counter arguments: https://www.researchgate.net/publication/362959885_A_note_on...
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.
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.
edit: Not a data scientists myself obviously
edit: Not a data scientists myself obviously
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.
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.
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
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?
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.
This is hugely unlikely.
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.
This is hugely unlikely.
Fair enough.
I've been in healthcare analytics and population health for over ten years.
Data analysis and analytics for going on 30.
I've also crunched a lot of numbers on this, and looked at the glaring issues with the data.
FWIW, I think that the analysis done in this paper is worth consideration.
I've been in healthcare analytics and population health for over ten years.
Data analysis and analytics for going on 30.
I've also crunched a lot of numbers on this, and looked at the glaring issues with the data.
FWIW, I think that the analysis done in this paper is worth consideration.
Data i found: https://www.insee.fr/en/statistiques/4641454
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.
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.
You are discussing about France not Germany, right?
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.
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.
> In situations like this, you should always default to disbelief.
Thats some really unfortunate wording. None of this should be a matter of belief.
Thats some really unfortunate wording. None of this should be a matter of belief.
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.
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.
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.
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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)
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.
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.
On a side note, sites that only don't work without javascript but also block you for not enabling javascript are "something special".
It may be an annoyance but it's also covered in the guidelines under "Please don't complain about tangential annoyances" https://news.ycombinator.com/newsguidelines.html
There will be many stories like this in the days, weeks, and months to come. But not years from now.
What is it you mean by this?
I hope it is that we won't find ourselves in such a quandary, where lack of trust in public institutions is at an all time high.
I hope it is that we won't find ourselves in such a quandary, where lack of trust in public institutions is at an all time high.
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.
Pull the other one, it has bells on!
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.
Pull the other one, it has bells on!
Among the other detractors, you miss a fairly important distinction.
Not being an epidemiologist stands in their favor.
Most other scientists are taking the data they receive at face value instead of taking the time to evaluate if the underlying assumptions are valid.
You respond emotionally and preemptively assume they are wrong.
It wasn't "anti-vaxxers" that employed hundreds of thousands of social media posters to disseminate the official message.
I feel genuinely sorry for people so deep in the wool.
Edit: At the present moment, it is impossible to determine if such vehement opposition is not also paid
Not being an epidemiologist stands in their favor.
Most other scientists are taking the data they receive at face value instead of taking the time to evaluate if the underlying assumptions are valid.
You respond emotionally and preemptively assume they are wrong.
It wasn't "anti-vaxxers" that employed hundreds of thousands of social media posters to disseminate the official message.
I feel genuinely sorry for people so deep in the wool.
Edit: At the present moment, it is impossible to determine if such vehement opposition is not also paid
There must be a German word for the embarrassment I feel for you.
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.
"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.
They shall be asked how many people are expected to die tomorrow and then, tomorrow, to explain the difference.
It's going to be very difficult for some people to admit that they made such an obvious mistake.
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.
But because of the attempts to force people to take the vaccine (which I did take, btw), trust has already been eroded.
We actually had a term for that, informed consent.
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.
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.
Yes it merely cost them their livelihood.
Cheers to you, you are factually correct. No one physically, with force, injected anyone with a vaccine against their will.
Cheers to you, you are factually correct. No one physically, with force, injected anyone with a vaccine against their will.
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
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
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I expect this garbage on Uncle Bill's Facebook feed, not HN.
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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.
There's clearly a temporal correlation.
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).
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).
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.
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.
And just the same, it happens within a field of expertise. Biases, groupthink, egos, etc. None of us, including science, is immune to such things.
Science is the system of questioning things through a repeatable methodology.
Is that not exactly what is happening here?
Science is always in a state of flux, as it should be until we know everything. Don’t get religious about it.
Is that not exactly what is happening here?
Science is always in a state of flux, as it should be until we know everything. Don’t get religious about it.
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> I'd prefer not to see this kind of nonsense given time of day on HN, as a science/technology based forum.
Then why did you make a comment that's mostly about it?
Then why did you make a comment that's mostly about it?
Those two researchers have never published a paper in epidemiology. Why should I trust these yahoos anti-vax propaganda?
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?
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?
This exactly. The opinion is the wrong one and must be smashed!
Notice how they are "yahoos" or some other derogatory framing?
(*disregard whoever they may be, they aren't established, well known, approved, epidemiology experts employedby the government!)
Notice how they are "yahoos" or some other derogatory framing?
(*disregard whoever they may be, they aren't established, well known, approved, epidemiology experts employedby the government!)
This was flagged and dead but somehow revived. Jeesh.
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