Human mobility and COVID-19 transmission: a systematic review and future directions
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SciScore for 10.1101/2021.02.02.21250889: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable 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:There are limitations of these data sources. Some data are country-specific; for example, the Baidu migration data is only available in China (Yuan, Xiao et al. 2020). Second, mobility data retrieved from mobile phones or …
SciScore for 10.1101/2021.02.02.21250889: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable 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:There are limitations of these data sources. Some data are country-specific; for example, the Baidu migration data is only available in China (Yuan, Xiao et al. 2020). Second, mobility data retrieved from mobile phones or mobile app users designed by large companies encounter data biases in population coverage, which may exclude some specific subgroups particularly children and aged populations who may not use mobile phones (Banerjee and Nayak 2020, Lai, Ruktanonchai et al. 2020). The index-based mobility data (e.g., provided by Google, Baidu, and Apple) does not include population inflow to and/or outflow from a given place. Alternatively, user-based social media big data (e.g., geotagged Twitter data) is able to indicate the inter- regional movement to improve the accuracy of models (Gupta, Jain et al. 2020, O’Sullivan, Gahegan et al. 2020, Tsay, Lejarza et al. 2020), although such big data is less used in current studies. With the technological advancements and the emergence of further refined data, it will be interesting in future studies to involve additional data, to use a combination of multi-sourced data, and to compare the reliability and quality of data (Banerjee and Nayak 2020, McGrail, Dai et al. 2020). Moreover, data sharing and information disclosure are encouraged for future studies. Some scholars and institutes have put great efforts into collecting, collating, and sharing data via crowdsourcing and cloud platforms to facilitate cross-disciplinary collaboratio...
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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