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Great work, Fabian! Glad I am not the only one noticing this disturbing trend.

In your "What's next section?" you did not list Covid, do you really not think this is a factor?

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Jan 14, 2023·edited Jan 15, 2023Author

Thank you!

That is the indirect mortality I am talking about. There is a link in that statement to another article:

https://vigilance.pervaers.com/p/modrna-products-caused-the-delta

While people seem to be more interested in the direct toxic effects of the shots, these aren't really news. I am hoping everyone will sooner or later gain awareness of the real crime that has taken place and still is: The shots are creating epidemics.

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And thank you :)

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I just read your "About" page - it's both heart-breaking and inspiring.

That even our friends and families have doubted, questioned, and abandoned us over this can be very dispiriting and disillusioning. I have immense respect for all those who chose to try and walk in the light of truth in the face of such societal pressure. But disillisionment is a good thing! We grow beyond the illusion, we see more clearly, we listen more closely to our inner voice. Charles Eisenstein's writings and others on substack have certainly helped me - https://charleseisenstein.substack.com

Fabian, keep up the good work and I hope we have the chance to meet some day over a good bavarian beer :)

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Jan 15, 2023·edited Jan 15, 2023Author

Yes, I agree. Disillusionment is a painful process, but can be very rewarding if one manages to adapt.

I've repeatedly considered deleting the content of the about page, since it contains very personal information, but I believe our stories need to be told.

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Looking forward to the sequels. Charts are visually very good. Methodology is robust and well-explained. Thank you. Stellar work.

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Thank you!

The article Tagesschau once wrote about you was one of my inspirations to get into data. They rarely write articles that long, so it was very telling in respect to who is perceived as a threat to the narrative.

If ever you feel the desire to add me to your list of recommendations you'd make me very happy, because this is what I am going to dedicate my life to throughout the next few years. :)

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3rd article is up. Idea came yesterday. I think it's extremely damning evidence.

Oh and thanks again, your comment meant a lot to me.

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considering Hamburg came in far below the new average,

it makes one wonder if Tschentscher played with the numbers again.

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Jan 14, 2023·edited Jan 14, 2023Author

Possibly, but if you look at the last 4 reporting weeks, Hamburg has an excess mortality of 14%, putting it on the lower end of our list of federal lands.

Berlin and Hamburg see relatively low mortality because the health care system in metropolitan areas is not collapsing the way it is in rural regions like Mecklenburg-Vorpommern.

There is a negative correlation between population density and excess mortality which is much more pronounced during phases of high mortality. I will dedicate an article to this.

The correlation between population density and excess mortality has been increasing throughout the past 3 years.

However the things I found out about how boosters are playing into this are so much more interesting. Booster doses both increase and decrease mortality at the same time, weakening the correlation between excess mortality and administered booster doses. However if we look at the correlation over time, we find out that it ranges between -0.9 and 0.8.

Both of these aspects are key to understanding German excess mortality.

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appreciate the extra insight!

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Incredible work, Fabian, it forgives your name, pace George B.S. :). I forwarded you to a German friend True Believer in the Injections hoping it will make a prick in his denial defence. We will see. Curious: do you know if 5G has been beaming throughout Germany along with the Injections? Stay safe and free.

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Jan 15, 2023·edited Jan 15, 2023Author

No sorry, I don't know how far we have progressed with 5G deployment. Germany is generally lagging behind other nations when it comes to networking technologies.

Well let's hope we can have an impact on your friend's decision whether or not to get another then.

The next article I am writing will probably be MUCH more interesting to him. "A choice between plague and cholera".

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Thanks. I look forward to sending it to him. Stay safe and free.

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Jan 30, 2023·edited Jan 30, 2023Liked by Fabian Spieker

Hi Fabian. What data do I need to do the same analysis for New Zealand? I have weekly deaths going back to 2011. I can also get Actuarial data from Stats NZ. Also I've noticed that bad flu years are followed by a decline in deaths the following year.

Regards

Terry

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Oh I just saw that. Well I guess we've sorted it out. ;)

Still busy with the US data.

Is there something like a death certificate dataset in NZ?

I made this for the USA: https://cdcwonder.pervaers.com

If there is one, it could tell us the whole story.

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Jan 21, 2023Liked by Fabian Spieker

Btw Bundesland = Federal State in EN.. Otherwise: Thanks! Great job

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Haha thank you. I said state in the first article on this subject, but when Igor Chudov quoted the article he said federal land, so I used that instead, thinking he must've made sure that's the correct version.

Gonna get it right in my next article ;)

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And.. drumroll! Both are correct: https://dict.leo.org/englisch-deutsch/Bundesland

So pardon the false alarm on my part.

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Jan 17, 2023Liked by Fabian Spieker

Dear Fabian,

Many thanks for the effort you put into this.

Have you considered running an (S)ARIMA model on these time series and comparing the results with your methodology?

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I had actually never heard of that. I've always been pretty good with numbers, but I never had any formal education on it, so I have huge gaps in both knowledge and skill. I just pick up whatever I need when I want to accomplish something.

E.g. before I made that website I didn't even know what confidence intervals were, at least not mathematically.

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Jan 15, 2023Liked by Fabian Spieker

Fantastic set of charts!

The seasonal mortality charts are curiously perfect. The periodicity within a chart is like a metronome. And the visually almost identical charts between regions is also curious.

Is the algorithm you are using to adjust for demographics and seasonality identical for each region, such that the only thing that changes to produce each group of charts, is the input data; e.g., deaths by week, age of population, etc.?

I understand that there should be some similarities year-to-year and across regions, but these charts look too perfect, and I would think the population data must have some events that would cause some of these to look different.

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Jan 15, 2023·edited Jan 15, 2023Author

Yes exactly. I do the same thing for all regions. Anything else would be cheating.

I can give you the code, but it's pretty simple to explain it.

After stretching 53-week years to 52 weeks, I am left with:

17x13 arrays of length 52

17 regions

13 years (2010-2022)

I use 2010-2019 as reference, that's the first 10 out of those 13.

For every week 1-52 I calculate the average mortality between 2010-2019.

The result is one array with 52 elements, each representing the average mortality that occurred in that week between 2010 and 2019.

Now to get absolute excess deaths you could just subtract seasonal mortality from trend-corrected mortality.

But since I am displaying relative excess deaths I am dividing trend-corrected mortality by seasonal mortality.

Not sure if this helps, but here is the nodejs code:

bundesland.seasonalshort=weekarrays.map(w=>w.slice(0,10)).map(w=>Math.round(w.reduce((pv,cv)=>pv+cv,0)/w.length));

bundesland.seasonal=[...Array(yearcount)].flatMap(y=>bundesland.seasonalshort).slice(0,bundesland.flat.length);

bundesland.excess=bundesland.trendcorrected.map((e,ei)=>e/bundesland.seasonal[ei]-1);

I looked at these charts for some time, so I can identify most of them with a quick glance which means there definitely are differences. ;D

You probably just have to get more familiar with them. It's just normal for seasonal mortality to follow a similar pattern.

Oh and if you want to I can just send you my entire code block that I use for substack at the moment. It's 3000 lines of chaos though.

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Jan 15, 2023Liked by Fabian Spieker

Minor correction needed: in the 2010-2022 Brandenburg section, your second chart which should be "corrected for demographics" is actually a repeat of the first chart, "mortality".

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Whoops, I must've messed up earlier. Chart has been replaced now though.

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Jan 15, 2023·edited Jan 15, 2023Author

Thank you very much. I will replace it immediately.

...and done :)

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Brilliant as always Fabian.I just want to ask what was happening last quarter of 1017 first quarter of 2018.There seems to be aspike there ,was it as bad flu season ,were hospitals simply overwhelmed because of the influx of immigrants/asylum seekers ,was it a combination of the 2 ? Not to be political but was Merkel's opendooor policy causing the health system to collapse?Asking as an Australian citizen.

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Oh and that was a flu epidemic in early 2018. Flu epidemics have grown increasingly worse and more frequent with every year ever since flu vaccines begun to be promoted aggressively.

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Sorry posted without editing.That was sloppy .I meant to write" last quarter of 2017 ,first quarter of 2018.There seems to be a spike"

Also Merkel's "open door policy"

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Jan 15, 2023·edited Jan 15, 2023Author

No, Merkel's open door policy could have been an attempt to keep the health system from collapsing. I'm not saying it's gonna prove fruitful or there was no better way to handle the issue, but one thing is for sure:

Germany needs immigration like you and me need air to breathe.

The core issue here is a dysbalance between work force and patients due to the age-related demographic changes.

It's a complete disaster on many levels. I will try touching on these subjects.

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Are the deaths broken down by age in the data? The biggest demographic issue would be if the trend is towards more younger people dying in 2022 compared to 20/21

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To some degree. Weekly data for federal states is only stratified into 4 groups:

0-60

60-75

75-85

80+

Pretty ridiculous.

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Absolutely ridiculous but there is still a clear distinction between the cohorts that have high mortality and the 0-60 group which might be enough to identify the trends that would tell us where this is going even if we can't differentiate between different ages in 0-60 to find e.g. the short term effects of the vaccinations in each age range as they were offered/mandated the doses sequentially based on age.

The most important thing to discover would be emerging trends showing whether excess deaths of working age people are rising exponentially, plateauing or reducing.

Thanks for your analysis, I'll pull down the data and have a look if I get a chance this week.

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I will write another article with numbers for national figures, stratified by age! :)

The next article will compare vaccinations with excess deaths (absolute). I will attach the code and data to that one, including the trend calculation which is not included here.

I subtracted the trend for the article. However adding it (reversed) makes more sense. This way I will adjust the old data, not the most recent data.

It makes no difference when I display relative excess mortality. However when I display absolute figures, adding the trend to older figures makes more sense than subtracting from more recent figures. Hope this makes sense.

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Some age stratified mortality data from the life insurance industry in this ZH article today https://www.zerohedge.com/markets/where-did-all-workers-go

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Thank you. I started working on an article that presents German excess mortality stratified by age and gender an hour ago. :)

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