The effect of population mobility on COVID-19 incidence in 314 Latin American cities: a longitudinal ecological study with mobile phone location data
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SciScore for 10.1101/2021.04.13.21255413: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
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: We detected the following sentences addressing limitations in the study:This study has several limitations. Because of the lack of individual-level data, we were unable to examine the association between individual mobility, education, and COVID-19 incidence. We are limited to contextual factors reflecting the sociodemographic …
SciScore for 10.1101/2021.04.13.21255413: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
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: We detected the following sentences addressing limitations in the study:This study has several limitations. Because of the lack of individual-level data, we were unable to examine the association between individual mobility, education, and COVID-19 incidence. We are limited to contextual factors reflecting the sociodemographic composition of sub-cities. Additionally, Grandata mobility datasets are metrics of the total number of out-of-home events that occur in a particular sub-city unit at a particular moment in time, regardless of travelers’ sub-city unit of residence. This means that we were unable to measure the mobility levels of residents of a particular sub-city unit, but instead we measured mobility that occurred by anyone in a particular sub-city at a given moment in time. However, this sub-city level analysis remains highly relevant to policymakers, who may be similarly focused on regulating all mobility within certain geographic areas versus regulating mobility based on an individual’s location of residence. Furthermore, because the mobility data is available at the sub-city level only, we were unable to examine mobility at a city level to evaluate the relative importance of city-level versus sub-city level mobility reductions on COVID-19 incidence. Finally, while other non-pharmaceutical interventions (NPIs), such as face-coverings, social distancing, and handwashing, play substantial roles in mitigating community-level COVID-19 incidence, these behaviors are challenging to measure.29 We expect that mobility and other NPIs are correlat...
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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