Share this page!

Enter URL or ID to Unroll

You can paste full URL like: https://x.com/threadreaderapp/status/1644127596119195649
or just the ID like: 1644127596119195649

How to get URL link on X (Twitter) App

  1. On the Twitter thread, click on or icon on the bottom
  2. Click again on or Share Via icon
  3. Click on Copy Link to Tweet
  4. Paste it above and click "Unroll Thread"!
  5. More info at Twitter Help
Orwell2024🏒 Profile picture
@orwell2022
Nov 24, 2021 • 25 tweets • 13 min read • Read on X
Scrolly
1/ Yesterday we had a poll on mortality vs. vaxx rate for the young (15y-29y).

Result (data): no obvious correlation. Not even for the 20-24 year old males, the group with the known (mRNA) myocarditis risk. See e.g. the map.

Today: The elderly (65+). But first a poll 😀
2/ So for the above 65 years olds (where vaxxing is claimed being the most urgent thing apparently), what are your expectations?

Results are ready, but let's give you some time to reflect😀

@jens_140081 @mr_Smith_Econ @OS51388957 @connolly_s @SHomburg @USMortality
3/ Like yesterday:

first the EC all cause mortality raw data 2020 vs. 2021 (no aggregation: each point is one week).

age: (left) 65-69, (mid) 70-74, (right) 75-79
males (bottom), females (top)
colour by vaxx rate 65+, symbol by country

Pretty diagonal. No💉 correlation. 🧐
4/ No we aggregate this into sum of week 19 to 45. So 10th May to now.

The trend line indicates no correlation to slighly worse in 2021. Where is the 98% VE agains death?
5/ Interestingly, there is nothing to see, to a slightly worse situation in 2021 compared to novaxx times in 2020. See trend line which is slightly above the diagonal (not shown, but it would cross the top right corners).
6/ Now the all cause excess defined as

2021 (sum W19 to W45) - 2021 (sum W19 to W45).

age: (left) 65-69, (mid) 70-74, (right) 75-79
males (bottom), females (top)
colour by vaxx rate 65+, size by abs_value(excess).

➡️No💉correlation.
7/ Now the all cause excess defined as

2021 (sum W19 to W45) - 2021 (sum W19 to W45).

age: (left) 80-84, (mid) 85-89, (right) 90+
males (bottom), females (top)
colour by vaxx rate 65+, size by abs_value(excess).

➡️No 💉correlation.
8/ A map view of this excess

2021 (sum W19 to W45) - 2021 (sum W19 to W45).

age: (left) 70-74, (right) 75-79+
males (bottom), females (top)
colour by excess (0 is transition green/red)

➡️ 2021 is worse than novaxx 2020 in general. 🧐
9/ A map view of this excess

2021 (sum W19 to W45) - 2021 (sum W19 to W45).

age: (left) 80-74, (mid) 85-89, (right) 90+
males (bottom), females (top)
colour by excess (0 is transition green/red)

➡️ looks random. No 💉correlation.🧐
10/ Last experiment: vaxx map and excess side by side.

left: vaxx rate 65+

right 4 maps:
excess 2021 vs 2020.
(left) 65y-69y, (right) 70y-74y
males (bottom), females (top)
colour by excess (0 is transition green/red)

➡️ looks random. No 💉correlation.
11/ Conclusion: Other risks than vaxx/novaxx dominate everything on all cause death. But reducing all cause is the ultimate goal, or not? It seems not 😌.

Answer B ❌
Answer A, B both possible ✅

Well done followers🏆

12/ Sorces:

Morality: ec.europa.eu/eurostat/datab…
Vaxx rate: vaccinetracker.ecdc.europa.eu/public/extensi…
Dashboard for download:
public.tableau.com/app/profile/or…
13/ DYI instruction:

1) Query EC DB for 2020 W19-W45, download query SMDX-CSV--> file 2020 (add week and year columns rename OBS column to 2020)
2) Query EC DB for 2020 W19-W45-->download query SMDX-CSV--> file 2021 (add week and year columns, rename OBS column to 2021)
14 DYI instruction (continued):

3) Create vaxx rate country file (see picture left)
4) Add 2021 and 2021 files in Tableau: left join by age=age, week=week, sex=sex, geo=geo
5) add vaxx rate country file, inner join by geo=geo
2) Query EC DB for 2021 W19-W45-->download query SMDX-CSV--> file 2021 (add week and year columns, rename OBS column to 2021)
Answer A, C I meant 😅
15/ Update (correction): I overlooked that the end week of reporting for 2021 varies for countries. Not all have W45. All have W38.

So this UNDERESTIMATED the 2021 excess for some countries (as the sum for 2020 went to W45).

Again for W19-W38.

➡️Answer C, may have it.
16/ Here again the raw correlations:

Filter on: W19 to W38
17/ And here again the excess defined as

2021 (sum W19 to W38) - 2021 (sum W19 to W38).

age: (left) 65-69, (mid) 70-74, (right) 75-79
males (bottom), females (top)
colour by vaxx rate 65+, size by abs_value(excess).
18/ And here the excess defined as

2021 (sum W19 to W38) - 2020 (sum W19 to W38).

age: (left) 80-84, (mid) 85-89, (right) 90+
males (bottom), females (top)
colour by vaxx rate 65+, size by abs_value(excess)
19/ Last one, the corrected map for the above 80 years.

Well...Sweden shines green. The rest doesn't look good compared to 2020.

Lockdowns are not good for health. The 💉doesn't improve anything (so far, up to W38). Tbc...
20/ Dashboard
public.tableau.com/app/profile/or…
21/ Next: normalization by population.

ec.europa.eu/eurostat/datab…
2019 is available by age, sex, country by 1 year bins.

I created a new set to match the EC 5 year bins of the mortality table. Cc @OS51388957 @USMortality

public.tableau.com/authoring/EC_p…

files.catbox.moe/rjn918.csv
22/ Yep, good to check things. I forgott about M/F.
files.catbox.moe/y1eclz.csv
@OS51388957
I will start a new thread once I have cross checked the dashboard.
23/ Finally: crosscheck.
1) Manual excel check and Tableau ✅
2) Population in ec.europa.eu/eurosta (after aggregation to 5 year bins) seem to fit with populationpyramid.net/austria/2019/
@OS51388957

• • •

Missing some Tweet in this thread? You can try to force a refresh
　

Keep Current with Orwell2024🏒

Orwell2024🏒 Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @orwell2022

Orwell2024🏒 Profile picture
Aug 6
A +14 W/m² total solar increase over 50 years is realistic. Japan alone shows +20 W/m². That’s 10× larger than the minuscule additional CO₂ forcing (~1W). And nearly 50× greater than the impact of sunspot cycles (±0.5 W).

So why is the climate scam still lying? Image
Image
Japan has one of the best measurement data. The analysis is clear. The brightening amount to almost 20 W. That is a lot. But the main and dominant effect is still urbanization, which makes up to 6°. Image
Link 1: the brightening. It explains why the climate scam likes to start in the maximum smog dimming period of 1970. It is a shameless bad faith deception. The effect is ball part of +1°C. In dry areas up to 3°C.
Read 9 tweets
Orwell2024🏒 Profile picture
Jul 6
UAH is a model inference, not a measurement. It can’t be tested, yet many treat it like real raw. Calling that a ‘measurement’ is wrong. Neither Lindzen nor us take it seriously. It starts in a cold period, with no long-term data — adjusted, multi mission stitched SW composite.🚮
UAH is not measurement — it’s model-driven inference. Satellites detect radiance, not temperature. The ‘trend’ is built through weighting functions, drift corrections, and stitched instruments. It’s untestable, synthetic, and not suitable for long-term climate baselines. Image
Image
Image
It’s astonishing how confidently some treat satellite-based inferences as god in heaven like truth. These are SW model outputs, not reliable measurements. Treating them as accurate fact is scientifically indefensible. If you do so, expect your credibility to be challenged. Image
Read 4 tweets
Orwell2024🏒 Profile picture
Jul 1
London is glowing today. Wide urban heat plume. Not “climate change.” Just real estate and concrete. The effect is visible. Quantifiable. Known. This should be a good study day to quantify UHI in more detail once the IR satellite pictures come in. Image
Image
2/ We start low tech. Actually nothing more is needed. There is over 6°C urban heat. It's embarrassing to pretend today's 33°C are comparable to 100 years ago. Subtract 6–8°C for UHI and you get... 25–27°C. Welcome back to reality. Image
3/ Nighttime, Tmin. Watch how they flatten the colors. You’re not supposed to notice the 7°C UHI. We unflatten the colors. Look again: you see it now? Image
Read 6 tweets
Orwell2024🏒 Profile picture
Jun 29
Stockholm downtown: Where’s the UHI correction?

QCU = raw data
QCF = adjusted data

Same numbers.

C A N -- Y O U -- S E E -- IT

Fredrik? Show us.
We can’t see it.

Where exactly is the downward adjustment of 2C-4C? That's the bias you have in 2025. Image
We can also do from SE raw. And we can also show how rural stations look. Frederik does like them. Climate agenda is measured in downtowns of the capitals? Image
Not sure if it’s normal that amateurs now have to lecture academics…?

The downtown station logs hourly=no need for even Ekholm, no need for re-sampling. Does Frederik even know what we mean? Nothing is adjusted. Also PHA leaves it as is as it only detects breakpoints (not UHI). Image
Read 5 tweets
Orwell2024🏒 Profile picture
Jun 27
1/ +++🚨BREAKING🚨+++

Yes. Hausfather & Berkeley Earth are pushing it.
But it’s not a measurement. Not one station shows that.
It’s what you get when you aggregate rot over time.

On the left: 8 pristine USCRN sites. Same y-scale.
Now look what they did.👇 Image
2/ 🚨 BREAKING 🚨

We overlay. Do you see it now?

👉 They erased the real past.
👉 They had no data to do so.
👉 It's pure statistical deception—and wrong.

How? All exposed in the Wickham et al. (2013) audit thread.🧵

Image
3/ AI to fraud is what DNA was to criminals.

Not optional. Not stoppable.

🧠 Fraud — exposed
📺 MSM — vanished
📄 Journals — obsolete
🎓 Academia — imploded
🏰 Ivory towers — rubble

Resistance is pointless.

github.com/orwell2024/usc…
orwell2024.github.io/GHCN-tools/Wic…
Read 6 tweets
Orwell2024🏒 Profile picture
Jun 23
1/ Weil’s beliebt ist: Hohenpeissenberg-Daten – fallen zwar schon nach BU-Filter raus, aber gut: Dr. Connolly war schlau.

Oben: Wie stark sich die Temperatur verändert hat.
Unten: Wie „unrund“ die Messwerte wurden – Entropie der Kommazahlen (h/t Connolly) Image
2/ Was wir hier sehen: Die Datenreihe ist ein Komposit (sehr beliebt, wenig seroes, in der Klima-„Wissenschaft“).
Die Messmethode (und mehr) hat sich verändert – von analogen zu digitalen Sensoren. Die Entropie der Nachkommastellen zeigt das – deutlich.
Image
3/ Diese Wetterstation ist NICHT standortstabil:
praktisch 100 % vom Menschen genutzte Fläche.

🟥 MODIS Urban (Klasse 13)
🟧 MODIS Agrarfläche (12 + 14)
🩸 GHSL Bebauung (2020)

Wer hier „Klima messen“ sagt, betreibt Täuschung.
Blamage für DWD.

Image
Read 12 tweets

Did Thread Reader help you today?

Support us! We are indie developers!

This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

Send Email!

:(