Orwell2024🏒 Profile picture
Dec 9, 2021 16 tweets 11 min read Read on X
1/ "Age adjusted all cause mortality trends 2000-2021 in Europe"

This was quite some work, so I hope you appreciate the article. I don't think that this kind of analysis using 5 year age bin granularity over 20 year trends has been done elsewhere.

orwell2024.substack.com/p/age-adjusted…
2/ The age adjustement was done on 5 year age bins.

Some groups @CebmOxford cebm.net/covid-19/exces… report age adjusted mortality for 2020. But the method is inaccurate as too wide age bins are used.
3/ For teaching purpose, we also applied the WHO2015-2025 standard population in some graphs to demonstrate the problem if applying this to an old population.
4/ For 2020, this is the ESP2013 age adjusted full year mortality country ranking obtained.
5/ For reference, the below shows the full pandemic 96 weeks (2020 W1-2021 W44) ESP2013 age adjusted mortality country ranking. Many countries had to be excluded due to limited availability of mortality data for 2021.
6/ An in depth look on the current year 2021 was done as there seems to be some concern about higher excess. To my view, this is mainly a random seasonal effect and maybe the price for lockdowns
7/ We further looked in depth to the NL situation in 2021. Nothing particular is happening in the age group <65. The excess is dominated by the elderly group (like in 2020). Covid is not visible <65.
8/ We further noticed, that using symmetric standard populations for sex is “old men friendly”. It will be less sensitive towards elderly female deaths. EC and @who standardisation groups are advised to adapt and remove this artefact.
9/ We further see that the open approach of Sweden lead to outperforming their lockdown neighbours on the 96 weeks 2020-2021 timeframe.

This is likely an anti-correlation with the cumulative stringency of lockdowns.

Sweden was right.
DNK and FI wrong.
NO is simply rich.
10/ 2021: Neither a positive nor negative impact of the vaccine can be seen. At least it’s not of any relevant dominance. Other causes dominate. Probably lockdown, or random seasonality as also lockdown hardliners like France is doing ok for now.
11/ The observed excess mortality in AT and NL, is dominated by mortality in the elderly age bins. But those are 95 % vaccinated like in SWE and FR. The vaccine doesn’t reduce nor increase all cause mortality. QR passports and the one dimensional C19 health focus has to stop.
12/ I'm adding 2021 interim result for the first 44 weeks. That will certainly change once we look to this in some month or two. The raw mortality data even for the available weeks may still change due to delayed reporting.

France.😀 Didn't have them on the radar. Bah oui 👋
13/ The French paradox. Is it BMI? Anyone who has lived there and in other countries knows their outperformance on food culture although I do prefer the high fat/carb Italian / Spanish kitchen.

🇫🇷 France wins on food category, like it or not. We know their secret now.
For comparison, 2020-2021 96 weeks and the vaccination map in the 60+ age group.

mortality (left)
C19 vaxx 60+ level (mid)
BMI (right).

There is no real correlation with vaccination levels. But there seems to be with BMI. Surprised? Not me.
14/ I downloaded more data.

Here the age standardised mortality on a map next to the obesity map. 2015 - 2020 (Covid "tragedy")

I'm very angry now seeing it like this.

The obese old society is blaming healthy people like me (BMI 20) and my kids = malfeasance.

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More from @orwell2022

Sep 10
They're trolling / insulting. The request was clear: compare ERA5 2km / @meteoblue with @AEMET_CValencia sensor at an hourly level. If they match at night, cloudy days, winter, but the sensor shows higher T in summer clear skies / no wind / day 👉 sensor is heat-biased. So? Go.
Thanks, @meteoblue. Normal conversation can be so easy. If the Spanish gentlemen would now provide access to their hourly station dataset, we can overlay it with the fine-grid ERA5 2km hourly product and see what's going on. Does that sound like a way forward @AEMET_CValencia ?

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@meteoblue @AEMET_CValencia He clearly doesn’t understand their response nor my request. At this stage, I just want him to provide THE HOURLY DATA. What the answer actually means is that the 30 km cell is more representative of the region’s climate—yes, it’s better than the station. Well done @ChGefaell 👍.

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Read 10 tweets
Sep 3
1/ Such places have no credibility for accurate bias free measurements. It's the opposite of a stable environment and per default a diesel powered urban expedition place. We see how the melting starts around the airport and the town.

How to measure? 👉 open.substack.com/pub/orwell2024…


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2/ Here we see another example (Alaska). Russian high-lat regions are among the worst. It's a deception to take measurements from such places and claim that you've done 'science' while actually just picking up dirt. Why not Everest dirt basecamp next?
3/ It escalated quickly. Similar to @BMcNoldy from Miami, master's student @Daaanvdb also used airport data instead of professional equipment, like what's available at @UNISvalbard.

Let's do better and use proper data from a better looking station.


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Read 19 tweets
Jun 27
1/ As mentioned, Europe is too urbanized for climate measurements. Shown below is just the UHI effect. As mentioned, ANY type of urban landscape altering increases surface temperatures as well. The Netherlands and Benelux regions are all fully biased and unfit for climate science
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2/ As mentioned previously, North Sweden is the most credible place for climate measurements due to its development, peace, and ability to capture high-quality data. Besides Sweden, only the US provides reliable historic data. All other regions are not credible and biased today. Image
3/ Source: YCEO Surface Urban Heat Islands: Spatially-Averaged Daytime and Nighttime Intensity for Annual, Summer, and Winter.

It's from 2003. Now it's even more urbanized = worse.

developers.google.com/earth-engine/d…
Read 12 tweets
Jun 18
1/ Remember the scenic document from @NOAA's USCRN. All rural places without man-made objects?



It's 145 pages long, each page one station. They should ALL be there, right?

Nope. How naive to believe that it's done in good faith.

Ready? 🧵 ncei.noaa.gov/pub/data/uscrn…
2/ This finding didn't emerge out of nowhere. Result of me telling @connolly_s that his detailed check of USCRN is a waste of time.

I repeated for weeks...then I swore...

They present the best only and hide urban stations. Bad faith. Consciously.


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3/ So, what do they look like, the ones they don't like to show? Urban areas. Airports...

Remember their requirements: It should be like the Everglades. No man-made environmental alterations. Stable. Representative.


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Read 12 tweets
May 22
1/ Let's do some checks: Compare the SST data model to water (ground) truth, thermometers in the water.

The green dots are the available @CDIPBuoys, a well maintained network. Probably the best buoy network (by @USACEHQ). Haven't seen any better one.

cdip.ucsd.edu/m/deployment/s…

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2/ Florida: the gulf area showing up red at the anomaly chart. The buoy shows nominal at average values. 25C versus +26-27C in the SST model. That's a +1C heat bias. Image
3/ Next - Hawaii. Buoys are below average. SST product is showing heat anomalies there.

14th May: buoy 24.5C vs. 25.5C SST.
+1C heat bias

Interesting. It's apparently too warm, as long as you don't stick a real thermometer into the water to measure and realize: it's cold. Image
Read 7 tweets
May 13
1/ Let's revisit this result from AIRS satellite measurements over 17 years, showing a +0.36W increase in forcing alongside a 40 ppm rise in CO2 concentration.

Does this align with the "observed" (questionable) increase in global temperature anomaly (+0.6C)?

Let’s do a check.
Image
2/The IPCC reports a calculated CO2 forcing of +0.5W, as detailed on the NOAA AGGI page, which you can find here:



The SW calculation overestimates by 40% compared to the +0.36W derived by the AIRS satellite, marking the first significant discrepancy. gml.noaa.gov/aggi/aggi.html
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3/ Now we return to Happer's paper, showing that doubling CO2 from 400 --> 800 ppm results in +3W of forcing.


This is consistent with +3.5W reported by the NOAA AGGI (+3.5W).

arxiv.org/pdf/2006.03098

gml.noaa.gov/aggi/aggi.html

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Read 7 tweets

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