Countrywide population movement monitoring using mobile devices generated (big) data during the COVID-19 crisis
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Abstract
Mobile phones have been used to monitor mobility changes during the COVID-19 pandemic but surprisingly few studies addressed in detail the implementation of practical applications involving whole populations. We report a method of generating a “mobility-index” and a “stay-at-home/resting-index” based on aggregated anonymous Call Detail Records of almost all subscribers in Hungary, which tracks all phones, examining their strengths and weaknesses, comparing it with Community Mobility Reports from Google, limited to smartphone data. The impact of policy changes, such as school closures, could be identified with sufficient granularity to capture a rush to shops prior to imposition of restrictions. Anecdotal reports of large scale movement of Hungarians to holiday homes were confirmed. At the national level, our results correlated well with Google mobility data, but there were some differences at weekends and national holidays, which can be explained by methodological differences. Mobile phones offer a means to analyse population movement but there are several technical and privacy issues. Overcoming these, our method is a practical and inexpensive way forward, achieving high levels of accuracy and resolution, especially where uptake of smartphones is modest, although it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring.
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SciScore for 10.1101/2020.09.21.20194019: (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 Although both use data from mobile phones, they differ in that the Google data track individuals continuously, either via satellites, cellular base stations or both, but only as long as their location function is turned on, whereas CDR automatically register the location data, but only when someone interacts with the telephony provider. Googlesuggested: (Google, RRID:SCR_017097)Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Nevertheless, both approaches have strengths and …
SciScore for 10.1101/2020.09.21.20194019: (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 Although both use data from mobile phones, they differ in that the Google data track individuals continuously, either via satellites, cellular base stations or both, but only as long as their location function is turned on, whereas CDR automatically register the location data, but only when someone interacts with the telephony provider. Googlesuggested: (Google, RRID:SCR_017097)Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Nevertheless, both approaches have strengths and limitations. The advantage of smartphone-generated, satellite-based location data, such as that collected by Goggle, is that the temporal and spatial resolution is extremely high for any individual,38 which is impossible to achieve with CDR. In addition, by linking its mobility data to the vast amount of customer data owned by Google and similar companies it is possible to study mobility by characteristics of the phone owner, including by socio-economic position or employment, whose feasibility is limited using CDR only. However, a serious disadvantage is that only some users are included. Google see only Android users, and among them only those, whose location history is turned on. In general, any smartphone-based location tracking solution is blind to individuals, who do not have a smartphone, or not willing to share their location. In contrast, by combining the data from all mobile phone operators, generated automatically, as part of the routine administration of calls, the CDR-based mobility index captures all active mobile phone users. This property makes its implementation relatively easy and inexpensive, and can be especially important in settings where early versions of phones are still widely used. In Hungary, out of roughly 8.6 million mobile phone users, 5.3 million have smart phones, further broken down to 4.5 million Android users and 0.8 million using some other operating system.39 Therefore, the mobility index us...
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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