The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology

Kyra H. Grantz, Hannah R. Meredith, Derek A. T. Cummings, C. Jessica E. Metcalf, Bryan T. Grenfell, John R. Giles, Shruti Mehta, Sunil Solomon, Alain Labrique, Nishant Kishore, Caroline O. Buckee and Amy Wesolowski ()
Additional contact information
Kyra H. Grantz: Johns Hopkins Bloomberg School of Public Health
Hannah R. Meredith: Johns Hopkins Bloomberg School of Public Health
Derek A. T. Cummings: University of Florida
C. Jessica E. Metcalf: Princeton University
Bryan T. Grenfell: Princeton University
John R. Giles: Johns Hopkins Bloomberg School of Public Health
Shruti Mehta: Johns Hopkins Bloomberg School of Public Health
Sunil Solomon: Johns Hopkins Bloomberg School of Public Health
Alain Labrique: Johns Hopkins Bloomberg School of Public Health
Nishant Kishore: Harvard TH Chan School of Public Health
Caroline O. Buckee: Harvard TH Chan School of Public Health
Amy Wesolowski: Johns Hopkins Bloomberg School of Public Health

Nature Communications, 2020, vol. 11, issue 1, 1-8

Abstract: Abstract The ongoing coronavirus disease 2019 (COVID-19) pandemic has heightened discussion of the use of mobile phone data in outbreak response. Mobile phone data have been proposed to monitor effectiveness of non-pharmaceutical interventions, to assess potential drivers of spatiotemporal spread, and to support contact tracing efforts. While these data may be an important part of COVID-19 response, their use must be considered alongside a careful understanding of the behaviors and populations they capture. Here, we review the different applications for mobile phone data in guiding and evaluating COVID-19 response, the relevance of these applications for infectious disease transmission and control, and potential sources and implications of selection bias in mobile phone data. We also discuss best practices and potential pitfalls for directly integrating the collection, analysis, and interpretation of these data into public health decision making.

Date: 2020
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DOI: 10.1038/s41467-020-18190-5

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