Definitely, but the main issue was about how to classify it. I'm not sure it's fair to call the estimate a blog post, it's an expert review published on a university website - in this case, my initial thinking was that it is grey literature
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Replying to @GidMK
Fair enough - doesn't solve the original problem I was raising it for: double(triple &c) counting.
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Replying to @hildabast
Ah but I don't think it is double-counting, because the actual IFR estimate that they produce is not a statistical aggregate - it's just their expert opinion
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Replying to @GidMK
Wow. (a) If expert opinions in non-systematic review informal literature are eligible it has major implications for your inclusion criteria. (b) That's not how you describe it in the preprint table. (I'll repeat my advice: you really need a co-author with specialist SR expertise)pic.twitter.com/NBBWAq6NIO
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Replying to @hildabast
Hmmm true. I'll talk to my co-author but I think it's a good point. Probably will exclude in the next update, thanks!
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Replying to @GidMK
You need to talk to someone with more specialist methodological expertise in systematic reviews & meta-analysis, incl about whether meta-analysis is indicated at all. You need to address the point, for which CEBM was just 1 example: how often are Wuhan data counted, for example?
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Replying to @hildabast
Well there were two studies that used Wuhan data, but they were very different datasets (deaths/cases and serology two months apart). Another study inferred IFR from Beijing, and another used exported cases from China as a whole
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Replying to @GidMK @hildabast
In terms of double-counting, the biggest worry was Lombardy data, because two studies used a similar dataset. However, they were two very different models so we thought on balance that it would be appropriate to include them both
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Replying to @hildabast
? In terms of double-counting, one study estimated excess mortality using daily deaths for Lombardia and Bergamo over 5 years. The other used confirmed cases and deaths due to COVID-19 between Feb and March 2020 for the entire country
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And interestingly, the two methods came to very different estimates of IFR - 0.95% vs 1.6%. I'm not sure I can see how including both would be double-counting, even if some of the data used to develop models in both may have overlapped?
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