Based on 13 published estimates, which ranged from formal scientific studies to unpublished serosurveys, we arrived at a best guess of ~0.75% (0.53-1.01%) of people will die if they get COVID-19
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HOWEVER, importantly, estimates varied WIDELY This could be because the studies were of very variable quality It could be because different places have very different IFRs It's hard to know at this point
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And thanks to
@peripatetical who helped improve the review! I still haven't made the graphs prettier but will keep working on that for final submission
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Good work
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New preprint - might be of interest
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I really liked the original blog post, thank you very much for turning it into a paper. After reading the post, I explored a bit, what the largest factor could be among diff. countries that would affect the ifr. This too can be done systematically to assess init. vulnerabilities.
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The pop. distr. for +65 seems to be the largest factor, which could affect the outcome between the youngest and oldest countries up to 3x, for a rough hazard factor of 10x for +65. Comorb. rel. health prob. seem to have roughly half that effect combined, at least what I couldfind
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Did you include the most recent preprint from Prof. Streeck regarding the German town Gangelt which had a superspreading event? German news are all over it right now discussing the infection-fatality rate observed by it.
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Underlying data is a meta-study of minor meta-studies as seen in the list of citations and methodology. In these scenarios, errors tend to propagate from biased interpretations of minor studies. Primary example is the high powered NY state seroprevalence study.
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