2/n Paper is here, it's a pretty simple ecological study comparing countries on their deaths/million from COVID-19 and Google mobility datahttps://www.nature.com/articles/s41598-021-84092-1#Sec5 …
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13/n What this means is that by comparing "residential" mobility, you are the most likely to find no difference by default. This is called a bias towards the null, and it's not ideal
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14/n Furthermore, remember my asterisk from above? Yeh, turns out that it's really hard to find out what "residential" actually means, how it's calculated, or what the raw figures are based on, presumably because this is proprietary Google analysis
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15/n So the conclusions about staying at home make no sense at all. "Residential" mobility data might not have been different between places, but for all we know that's a meaningless measure anyway that has very little to do with how much people stay at homepic.twitter.com/6BZyfOXqj7
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16/n On top of that, this study suffers from the same drawbacks that most ecological trials do. To their credit, the authors acknowledge this in the discussion, but it certainly hasn't filtered through to the publicpic.twitter.com/XMeDYJanin
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17/n Limitations inherent in this sort of research are many and varied, but as one example it's hard to make any realistic inferences about individuals staying at home when your unit of study is Spain vs the United States of America
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18/n Even within Australia, which was included, the massive Victorian outbreak/lockdown skew the figures enormously, because one state with 1/4 of the population locked down while the rest of the country opened up
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19/n We might actually expect null findings from an ecological trial of this sort, because at the country level heterogeneity in local policy irons out a lot of the impact
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20/n It's also worth noting that the study literally does not address the question of whether government orders influenced COVID-19 deaths. Even if you ignore all the other issues, "residential" mobility data simply can't answer that question!
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21/n There are many reasons that people stay at home, and given the opacity of "residential" data it's hard to say much about the results other than that this is a hard question that we may never answer well
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22/n That being said, the idea that this study disproves staying at home as a driver of COVID-19 mortality is obviously wrong - at best, it is an example of how difficult answering that question can be
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