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— KittyPooh (@KittyPo80176717) January 17, 2022
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The #CCP has likely understated the #COVID19 death toll by as much as a 17,000% in a systematic data suppression campaign to sustain its political image, an analysis found.
— The Epoch Times – China Insider (@EpochTimesChina) January 13, 2022
That would put the COVID death count in #China at 1.7 million rather than 4,636. https://t.co/1iMov1cRyv
https://t.co/1l7NbWaHk8 pic.twitter.com/kF7XkBfn7q
— KittyPooh (@KittyPo80176717) January 17, 2022
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The #economist is publishing a regularly-updated model of excess deaths due to COVID, which is being used to tell just-so stories about countries the Economist doesn’t like. Let’s talk about the dangers of using machine learning for analysis when you don’t have data. pic.twitter.com/wyHUkVnNMn
— Stuart Gilmour (@drStuartGilmour) November 7, 2021
This data is simply wrong. So how is it possible the economist got it so wrong? And why do they publish anyway? The answer to this question is also relevant to other projects that aim to estimate health data where that data is missing, like the #globalburdendisease studies.
— Stuart Gilmour (@drStuartGilmour) November 7, 2021
They then build a massive model based on this data to estimate what the true excess mortality might be using a machine learning method called gradient boosting. They predict deaths in other countries based on the countries with data.
— Stuart Gilmour (@drStuartGilmour) November 7, 2021
There are many other problems with the Economist’s work. First, they seem to apply a linear regression model to deaths, rather than over-dispersed Poisson regression. This allows the prediction of negative deaths in a country! pic.twitter.com/e8EwysGRLc
— Stuart Gilmour (@drStuartGilmour) November 7, 2021
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weehingthong 