Mobility Reduction and Covid-19 Transmission Rates
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Abstract
Assessing the contribution of mobility restrictions to the control of Covid-19 diffusion is an urgent challenge of global import. We analyze the relation between transmission rates (estimated effective reproduction numbers) and societal mobility levels using fine-grained daily mobility data from Google and Apple in an international panel of 87 countries and a panel of all states in the United States. Reduced form regression estimates that flexibly control for time trends suggest that a 10 percentage point reduction in mobility is associated with a 0.04-0.09 reduction in the value of the effective reproduction number, R ( t ), depending on geographical region and modelling choice. According to these estimates, to avoid the critical value of R = 1, easing mobility restrictions may have to be limited to below pre-pandemic levels or delayed until other non-mobility related preventative measures reduce R to a level of 0.55–0.7 in Europe, a level of 0.64–0.76 in Asia, and a level of 0.8 in the United States. Given gaps in data availability and inference challenges, these estimates should be interpreted with caution.
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SciScore for 10.1101/2020.05.06.20093039: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The U.S. sample includes all states over the period March 13th - May 2nd when using Google data, and March 13th - May8th when using Apple data. Googlesuggested: (Google, RRID:SCR_017097)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were …
SciScore for 10.1101/2020.05.06.20093039: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The U.S. sample includes all states over the period March 13th - May 2nd when using Google data, and March 13th - May8th when using Apple data. Googlesuggested: (Google, RRID:SCR_017097)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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