So proud of my @UNGlobalPulse team and collaborators that step by step and over the years have managed to bring 🤖 science closer to humanitarian and development work. We now have a library!! 📚 📚📚 https://t.co/rOxXQRllo5 Some peer-reviewed highlights in this thread 👇
More from Science
@mugecevik is an excellent scientist and a responsible professional. She likely read the paper more carefully than most. She grasped some of its strengths and weaknesses that are not apparent from a cursory glance. Below, I will mention a few points some may have missed.
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The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
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The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/
The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
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The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
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I've recently come across a disinformation around evidence relating to school closures and community transmission that's been platformed prominently. This arises from flawed understanding of the data that underlies this evidence, and the methodologies used in these studies. pic.twitter.com/VM7cVKghgj
— Deepti Gurdasani (@dgurdasani1) February 1, 2021
The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
2/
The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/
The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
4/
The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
5/
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his name might sound familiar because the new cortellucci vaughan hospital at mackenzie health, the one doug ford has been touting lately as a covid-centric facility, is named after him and his family
but his name also pops up in a LOT of other ford projects. for instance - he controls the long term lease on big parts of toronto's portlands... where doug ford once proposed building an nfl stadium and monorail... https://t.co/weOMJ51bVF
cortellucci, who is a developer, also owns a large chunk of the greenbelt. doug ford's desire to develop the greenbelt has been
and late last year he rolled back the mandate of conservation authorities there, prompting the resignations of several members of the greenbelt advisory
his name might sound familiar because the new cortellucci vaughan hospital at mackenzie health, the one doug ford has been touting lately as a covid-centric facility, is named after him and his family
but his name also pops up in a LOT of other ford projects. for instance - he controls the long term lease on big parts of toronto's portlands... where doug ford once proposed building an nfl stadium and monorail... https://t.co/weOMJ51bVF
cortellucci, who is a developer, also owns a large chunk of the greenbelt. doug ford's desire to develop the greenbelt has been
and late last year he rolled back the mandate of conservation authorities there, prompting the resignations of several members of the greenbelt advisory