This is a long, interesting thread on how much more transmissible B.1.1.7 (aka "the UK variant") really is.https://twitter.com/phl43/status/1380513950832414723 …
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One thing I'd add is that contact-tracing data from the UK found an advantage of ~33% (as compared to the 50-70% that you sometimes see cited elsewhere) and I can imagine contact-tracing is more robust than methods based on statistical extrapolation. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/959426/Variant_of_Concern_VOC_202012_01_Technical_Briefing_5.pdf …pic.twitter.com/S6OAe4sYRX
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As a non-expert on this stuff, I don't necessarily trust my judgment to sort out competing expert claims. However, I do find it interesting when there's a range of expert opinion and only a certain portion of that range tends to make it into popular media coverage about COVID.
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You see something similar now where the mainstream press treats it as all but inevitable that the US will experience a new surge. Certainly possible and *some* experts do expect one. And yet, the models tracked by the CDC are *all over the place*; there's no consensus at all.pic.twitter.com/xzBFcRk38w
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There's something analogous here to the "wet bias" in meteorology, where TV meteorologists semi-deliberately overpredict rain because reputationally they tend to get more criticism for false negatives (it rains when they say it won't) than false positives.https://www.nytimes.com/2012/09/09/magazine/the-weatherman-is-not-a-moron.html …
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Vastauksena käyttäjälle @NateSilver538
As a recovering scientist and engineer, it is a source of great frustration to me that more people can't understand stats for themselves, and that the media consistently reports the top end of a 2-sigma to make a more sensationalist story.
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Luckily, professional meteorologists (i.e vast majority of those on the tv) don’t do this. 
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