Mobile phone data and COVID-19: Missing an opportunity?

Abstract

This paper describes how mobile phone data can guide government and public health authorities in determining the best course of action to control the COVID-19 pandemic and in assessing the effectiveness of control measures such as physical distancing. It identifies key gaps and reasons why this kind of data is only scarcely used, although their value in similar epidemics has proven in a number of use cases. It presents ways to overcome these gaps and key recommendations for urgent action, most notably the establishment of mixed expert groups on national and regional level, and the inclusion and support of governments and public authorities early on. It is authored by a group of experienced data scientists, epidemiologists, demographers and representatives of mobile network operators who jointly put their work at the service of the global effort to combat the COVID-19 pandemic.

References in corpus (2)

• From mobile phone data to the spatial structure of cities
• Apps Gone Rogue: Maintaining Personal Privacy in an Epidemic

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• Disparate Patterns of Movements and Visits to Points of Interests Located in Urban Hotspots across U.S. Metropolitan Cities during COVID-19
• Resource Management and Quality of Service Provisioning in 5G Cellular Networks
• Deep Learning for Virus-Spreading Forecasting: a Brief Survey
• A Tale of Two Countries: A Longitudinal Cross-Country Study of Mobile Users' Reactions to the COVID-19 Pandemic Through the Lens of App Popularity