Hey 'Orwell'. Stefan Noordhoek hier, ik werd op jouw excellente werk gewezen door Dimgrrr en Fritsander L. en besloot vrijdag (?) om verder te werken op een kopie van jouw Tableau project. Was a first voor mij :)) in het visualiseren liep ik tegen een paar vragen op... o.a. over de "per 10k" maar omdat de datafiles voor mij niet in te zien zijn, kan ik dat niet goed checken.
Hoe kan ik met je in contact treden? Ik volg je op twitter, maar jij volgt mij (nog) niet, daar zou ik je (dan) een DM kunnen sturen. Mijn Twitter handle is (nadat ik in december met een aantal mensen waaronder Marc Vegt opeens werd verwijderd) nu @johnnyriver_020.
Danke für die Arbeit! Für Dummies: ist die standardisierte Sterblichkeit der jeweiligen Altersgruppen bezogen auf den Anteil der Altersgruppen an der Gesamtpopulation? Schönen Gruss! Jens
I have two question on population data from.my own attempts to pin down excess.
First population data's are estimates anchored on surveys . what errors may creep in between surveys? Which may have largest effect and in which age groups. Are these,effect same in different countries?
Second mortality had a lot of variability absolute and directional in my set.
What are the effects of using simple averages , different base years and averaging periods, and of using SD or variance measures vs simple average on output?
I wouldn't know. The biggest error is done when averaging over an exponential function (mortality) by large age bins (or a single one like most stuff in OWID). That’s why I go as granular as possible on age.
Your whole analysis depends on the assumption that the virus/disease stayed constant over the whole time but it wasn't. Also Vaccine efficacy wanes but is existent so your analysis is respectable but wrong. This is because all the variables which you didn't confound create huge artifacts. You can see it in your "surprising" results. The big work on age adjustment does not conceal the fact that your big factor "obesity" didn't come out of population obesity data and analysis but only by mentioning "food culture" - not convincing.
Heads up: unprecedented non-covid excess mortality highs for 25-44 yr old group are being seen in US data starting April 2021 and noted by insurance players.
18-44 yrs already saw 77% of excess mortality in 2020 being non-covid as I understand.
Running ACM for 3 years 2019-2021 could bring SWE well out in front I presume.
Dramatic effect on ACM from 2008 economic downturn was seen in Greece for at least a decade. Now, EU printing money and creating monstrous debt 2020-2021 also pushes some of effect ahead to future years.
And yes could say lockdown ACM farmed out to less-developed countries.
And how do we class a dramatic drop in births? In earlier times this would be seen as extremely sad. Like death to a community or nation. And isn't it?!
How do we quantify the effect on vitality/lives from the loss of small-medium companies and personal savings and concentration into fewer, large corporations, thru lowered competition, lower choice, lowered quality, higher prices, less channels for innovation and addressing new market needs, increased govt-corporate cronyism, and less opportunity for individual upliftment and enrichment through entrepeneurship, in short a less democratic economy and a weaker general population?
Nice job but fix the map in 3.5. You misplaced Lithuania LT, Latvia LV and Liechtenstein LI numbers from the diagram. Lithuania is 30.4 and Latvia 30.92 and now Latvia has Lithuanian data and Lithuania has the one from Liechstenstein
Wow. China is envious of Germany deals with its information.
1. We don't need German's data
2. The Singaporean MOH first published back in May 2020 - yes, 2020 - that CT > 25 does NOT detect "culturable" virions. Others studies point to CT = 24 as the max. Professor Henegan of Oxford EBM said 24 back in May 2020.
3. PCR does not determine Q1. Since we know that CT > 25 is useless, it follows that CT = 24 is the max limit as a mere guide since PCR cannot detect infection anyway - or tell rowuhan from the flu.
No. Z-score is used to avoid the high intrinsic spread in small populations. It's a non linear measure for excess and can't be compared across countries nor in time. It's a signal catching feature. A first stop, not a last stop.
Outstanding job! I really appreciate it.
Well done that is excellent. Hope it goes a long way to dispelling the fearmongering and help people look at reality objectively again. Thank you!
Hey 'Orwell'. Stefan Noordhoek hier, ik werd op jouw excellente werk gewezen door Dimgrrr en Fritsander L. en besloot vrijdag (?) om verder te werken op een kopie van jouw Tableau project. Was a first voor mij :)) in het visualiseren liep ik tegen een paar vragen op... o.a. over de "per 10k" maar omdat de datafiles voor mij niet in te zien zijn, kan ik dat niet goed checken.
Hoe kan ik met je in contact treden? Ik volg je op twitter, maar jij volgt mij (nog) niet, daar zou ik je (dan) een DM kunnen sturen. Mijn Twitter handle is (nadat ik in december met een aantal mensen waaronder Marc Vegt opeens werd verwijderd) nu @johnnyriver_020.
Alvast veel dank,
Groet, Stefan
It's maybe a bit messy my dashboard. Like open source code. Be careful with aggregations.
Danke für die Arbeit! Für Dummies: ist die standardisierte Sterblichkeit der jeweiligen Altersgruppen bezogen auf den Anteil der Altersgruppen an der Gesamtpopulation? Schönen Gruss! Jens
Genau!
I have two question on population data from.my own attempts to pin down excess.
First population data's are estimates anchored on surveys . what errors may creep in between surveys? Which may have largest effect and in which age groups. Are these,effect same in different countries?
Second mortality had a lot of variability absolute and directional in my set.
What are the effects of using simple averages , different base years and averaging periods, and of using SD or variance measures vs simple average on output?
I wouldn't know. The biggest error is done when averaging over an exponential function (mortality) by large age bins (or a single one like most stuff in OWID). That’s why I go as granular as possible on age.
Your whole analysis depends on the assumption that the virus/disease stayed constant over the whole time but it wasn't. Also Vaccine efficacy wanes but is existent so your analysis is respectable but wrong. This is because all the variables which you didn't confound create huge artifacts. You can see it in your "surprising" results. The big work on age adjustment does not conceal the fact that your big factor "obesity" didn't come out of population obesity data and analysis but only by mentioning "food culture" - not convincing.
https://twitter.com/orwell2022/status/1472210608607186945?s=20&t=xcRJXpSfG-GiX4vBH7ETbg
https://twitter.com/orwell2022/status/1470858406873468939?s=20&t=xcRJXpSfG-GiX4vBH7ETbg
Heads up: unprecedented non-covid excess mortality highs for 25-44 yr old group are being seen in US data starting April 2021 and noted by insurance players.
18-44 yrs already saw 77% of excess mortality in 2020 being non-covid as I understand.
Running ACM for 3 years 2019-2021 could bring SWE well out in front I presume.
Dramatic effect on ACM from 2008 economic downturn was seen in Greece for at least a decade. Now, EU printing money and creating monstrous debt 2020-2021 also pushes some of effect ahead to future years.
And yes could say lockdown ACM farmed out to less-developed countries.
And how do we class a dramatic drop in births? In earlier times this would be seen as extremely sad. Like death to a community or nation. And isn't it?!
How do we quantify the effect on vitality/lives from the loss of small-medium companies and personal savings and concentration into fewer, large corporations, thru lowered competition, lower choice, lowered quality, higher prices, less channels for innovation and addressing new market needs, increased govt-corporate cronyism, and less opportunity for individual upliftment and enrichment through entrepeneurship, in short a less democratic economy and a weaker general population?
Good work, just get a copyeditor.
Sure, send me money and I will hire one.
Nice job but fix the map in 3.5. You misplaced Lithuania LT, Latvia LV and Liechtenstein LI numbers from the diagram. Lithuania is 30.4 and Latvia 30.92 and now Latvia has Lithuanian data and Lithuania has the one from Liechstenstein
Thanks. I will check. Maybe an error in my table with country codes.
Excellent work, brother! Amazing!
Thank for this detailed work.
Off-topic:
I am STILL looking for infor on two fundamental questions:
1. What the mechanisms of action of rowuhan?
2. What is the minimum infectious viral load? (They know (CT> 24); but they won't tell us.)
Can you, or anyone else, provide light on them?
Without raw data on PCR it's impossible to move on this. Germany: They even hide the calibration data and deleted the file. https://t.co/Hryg9luTV9
Wow. China is envious of Germany deals with its information.
1. We don't need German's data
2. The Singaporean MOH first published back in May 2020 - yes, 2020 - that CT > 25 does NOT detect "culturable" virions. Others studies point to CT = 24 as the max. Professor Henegan of Oxford EBM said 24 back in May 2020.
3. PCR does not determine Q1. Since we know that CT > 25 is useless, it follows that CT = 24 is the max limit as a mere guide since PCR cannot detect infection anyway - or tell rowuhan from the flu.
Below 25, one probably doesn't need test as people will have symptoms. And as in old days, stay at home and come back once gone. No magic needed.
Reminder:
1. China, yes, China, requires TWO clinical symptoms and PCR 30 (?) before a case is +ve.
2. Likewise with Pfizer and the other vax pimps!
Rowuhan is different. Get on the meds before or early.
Interesting how France had no improvement in healthcare over the past 20 years, while FI, NL and NO improved a lot year on year.
France: there is only data from 2013 availabe. That's why it appears so...
nice
But doesn't the Z-score used to track excess mortality adjust for age didtribution?
No. Z-score is used to avoid the high intrinsic spread in small populations. It's a non linear measure for excess and can't be compared across countries nor in time. It's a signal catching feature. A first stop, not a last stop.