Predicting the SARS-CoV-2 effective reproduction number using bulk contact data from mobile phones
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Abstract
Numerous COVID-19 studies used mobile phone data but with limited power in accounting for infection numbers. We have evaluated deidentified Global Positioning System (GPS) data from over 1 million devices in Germany and inferred contacts from coproximity of devices. Through calculating the contact graphs, we derived a contact index (CX) that exhibits a high correlation with the incidence-based reproduction number R so that changes in CX precede those in R by more than 2 wk. CX thus is an early indicator for outbreaks and can be used to guide social-distancing policies. Further questions, including those for the efficacy of vaccination, can be addressed with our method. We discuss limitations, e.g., transmission on international travel, and the relation to superspreading.
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SciScore for 10.1101/2020.10.02.20188136: (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: 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 …
SciScore for 10.1101/2020.10.02.20188136: (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: 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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