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

By K. Grantz, Hannah Meredith, Derek A. T. Cummings, C. Metcalf, B. Grenfell, J. Giles, S. Mehta, S. Solomon, Alain B. Labrique, N. Kishore and 2 more. Nature Communications, 2020

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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. In this Perspective, the authors review the different applications for mobile phone data to support COVID-19 pandemic response, the relevance of these applications for infectious disease transmission and control, and potential sources and implications of selection bias in mobile phone data.

Subfields: Epidemiology, Information Systems, Modeling and Simulation

View Paper: https://www.semanticscholar.org/paper/8630e797063b1eb3a5901156a69a1dd492dd1f7f

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