1. Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle
- Author
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Oliver, Nuria, Lepri, Bruno, Sterly, Harald, Lambiotte, Renaud, Deletaille, Sébastien, De Nadai, Marco, Letouzé, Emmanuel, Salah, Albert Ali, Benjamins, Richard, Cattuto, Ciro, Colizza, Vittoria, de Cordes, Nicolas, Fraiberger, Samuel P., Koebe, Till, Lehmann, Sune, Murillo, Juan, Pentland, Alex, Pham, Phuong N., Pivetta, Frédéric, Saramäki, Jari, Scarpino, Samuel V., Tizzoni, Michele, Verhulst, Stefaan, Vinck, Patrick, Sub Social and Affective Computing, Data-Pop Alliance, University of Vienna, Alan Turing Institute, Rosa, Fondazione Bruno Kessler, Open Algorithms (OPAL), odiseIA, Orange, Sorbonne Université, Dalberg Data Insights, Danmarks Tekniske Universitet, BBVA S.A., Massachusetts Institute of Technology, Professorship Saramäki J., Northeastern University, University of Turin, New York University, Department of Computer Science, Aalto-yliopisto, and Aalto University
- Subjects
medicine.medical_specialty ,Economic growth ,Science Policy ,Location intelligence ,Movement ,education ,COVID-19 ,Coronavirus Infections ,Humans ,Infection Control ,Interpersonal Relations ,Pneumonia ,Viral ,SARS-CoV-2 ,Travel ,Betacoronavirus ,Cell Phone ,Pandemics ,Public Health ,Psychological intervention ,02 engineering and technology ,Civil liberties ,COVID-19 (Malaltia) ,Mobile data analysis ,Pneumonia, Viral ,03 medical and health sciences ,SDG 3 - Good Health and Well-being ,Pandemic ,medicine ,General ,Information exchange ,030304 developmental biology ,0303 health sciences ,Multidisciplinary ,Public health ,021001 nanoscience & nanotechnology ,Salut pública ,Coronavirus ,Editorial ,Telèfon mòbil ,Mobile phone ,Scale (social sciences) ,SciAdv editorial ,Communicable Disease Control ,Business ,0210 nano-technology ,New Zealand - Abstract
The coronavirus 2019–2020 pandemic (COVID-19) poses unprecedented challenges for governments and societies around the world ( 1 ). Nonpharmaceutical interventions have proven to be critical for delaying and containing the COVID-19 pandemic ( 2 – 6 ). These include testing and tracing, bans on large gatherings, nonessential business and school and university closures, international and domestic mobility restrictions and physical isolation, and total lockdowns of regions and countries. Decision-making and evaluation or such interventions during all stages of the pandemic life cycle require specific, reliable, and timely data not only about infections but also about human behavior, especially mobility and physical copresence. We argue that mobile phone data, when used properly and carefully, represents a critical arsenal of tools for supporting public health actions across early-, middle-, and late-stage phases of the COVID-19 pandemic. Seminal work on human mobility has shown that aggregate and (pseudo-)anonymized mobile phone data can assist the modeling of the geographical spread of epidemics ( 7 – 11 ). Thus, researchers and governments have started to collaborate with private companies, most notably mobile network operators and location intelligence companies, to estimate the effectiveness of control measures in a number of countries, including Austria, Belgium, Chile, China, Germany, France, Italy, Spain, United Kingdom, and the United States ( 12 – 21 ). There is, however, little coordination or information exchange between these national or even regional initiatives ( 22 ). Although ad hoc mechanisms leveraging mobile phone data can be effectively (but not easily) developed at the local or national level, regional or even global collaborations seem to be much more difficult given the number of actors, the range of interests and priorities, the variety of legislations concerned, and the need to protect civil liberties. The global scale and spread of the COVID-19 pandemic highlight the need for a more harmonized or coordinated approach. In the …
- Published
- 2020
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