Mobility network models of COVID-19 explain inequities and inform reopening
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SciScore for 10.1101/2020.06.15.20131979: (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 S1 Comparison of Google and SafeGraph mobility data: To assess the reliability of the SafeGraph datasets, we measured the correlation between mobility trends according to SafeGraph versus Google.54 Google provides a high-level picture of mobility changes around the world for several categories of places, such as grocery stores or restaurants. Googlesuggested: (Google, RRID:SCR_017097)The high correlations demonstrate that the SafeGraph and Google mobility datasets agree well on the timing and directional changes of mobility over this time period, providing a validation of the reliability … SciScore for 10.1101/2020.06.15.20131979: (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 S1 Comparison of Google and SafeGraph mobility data: To assess the reliability of the SafeGraph datasets, we measured the correlation between mobility trends according to SafeGraph versus Google.54 Google provides a high-level picture of mobility changes around the world for several categories of places, such as grocery stores or restaurants. Googlesuggested: (Google, RRID:SCR_017097)The high correlations demonstrate that the SafeGraph and Google mobility datasets agree well on the timing and directional changes of mobility over this time period, providing a validation of the reliability of SafeGraph data. SafeGraphsuggested: NoneResults from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The cell phone mobility dataset we use has limitations: it does not cover all populations (e.g., prisoners, children under 13, or adults without smartphones), does not contain all POIs (e.g., nursing homes are undercovered, and we exclude schools and hospitals from our analysis of POI category risks), and cannot capture sub-CBG heterogeneity in demographics. Individuals may also be double-counted in the dataset if they carry multiple cell phones. These limitations notwithstanding, cell phone mobility data in general and SafeGraph data in particular have been instrumental and widely used in modeling SARS-CoV-2 spread.15–17,28–32,39 Our model itself is parsimonious, and does not include such relevant features as asymptomatic transmission; variation in household size; travel and seeding between MSAs; differentials in susceptibility due to pre-existing conditions or access to care; age-related variation in mortality rates or susceptibility (e.g., for modeling transmission at elementary and secondary schools); various time-varying transmission-reducing behaviors (e.g., hand-washing, mask-wearing); and some POI-specific risk factors (e.g., ventilation). Although our model recovers case trajectories and known infection disparities even without incorporating these features, we caution that this predictive accuracy does not mean that our predictions should be interpreted in a narrow causal sense. Because certain types of POIs or subpopulations may disproportionately select for certain...
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.
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- No protocol registration statement was detected.
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