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My colleagues and I are formally seeking a retraction of the recently published “Identifying airborne transmission as the dominant route for the spread of COVID-19.” The full text of our letter to the PNAS editorial board can be found here. 1/
https://metrics.stanford.edu/PNAS%20retraction%20request%20LoE%20061820
https://metrics.stanford.edu/PNAS%20retraction%20request%20LoE%20061820
It is important that science, especially now, be as rigorous and methodologically sound as possible. However, this paper suffers from numerous and fundamental errors that undermine the foundation of its conclusions. The paper is linked here. 2/ https://www.pnas.org/content/early/2020/06/10/2009637117
Masks help in the fight against COVID-19. Our call for one study to be retracted should not detract from that important message. Indeed, a recently published meta-analysis showed that mask use (N-95 esp), could result in large risk reduction. 3/ https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)31142-9/fulltext#%20
We do not call for a retraction lightly. The letter was written by @NoahHaber @KateGrabowski Nikolas Wada, @goodmanmetrics @JustinLessler and me, & signed by 39 other scientists across many fields. If you read the paper & letter, and agree, please write to PNAS too, or RT. 4/
Finally, this article was Contributed to PNAS. NAS members can contribute 2 articles/yr to PNAS & choose their own reviewers. This subverts strong peer review. Mid-crisis studies, on key topics, in prestigious journals should follow the scientific community’s best practices. 5/5
Additional notes:
1. JHU review notes on the paper https://ncrc.jhsph.edu/research/identifying-airborne-transmission-as-the-dominant-route-for-the-spread-of-covid-19/
2. Gelman's @StatModeling comments with @adamrpearce https://statmodeling.stat.columbia.edu/2020/06/17/the-point-here-is-not-the-face-masks-its-the-impossibility-of-assumption-free-causal-inference-when-the-different-treatments-are-entangled-in-this-way/
3. An interactive explorable from @adamrpearce that allows you to do your own sensitivity analysis. https://roadtolarissa.com/regression-discontinuity/
1. JHU review notes on the paper https://ncrc.jhsph.edu/research/identifying-airborne-transmission-as-the-dominant-route-for-the-spread-of-covid-19/
2. Gelman's @StatModeling comments with @adamrpearce https://statmodeling.stat.columbia.edu/2020/06/17/the-point-here-is-not-the-face-masks-its-the-impossibility-of-assumption-free-causal-inference-when-the-different-treatments-are-entangled-in-this-way/
3. An interactive explorable from @adamrpearce that allows you to do your own sensitivity analysis. https://roadtolarissa.com/regression-discontinuity/
