Monitoring the COVID-19 epidemic with nationwide telecommunication data

Joel Persson (), Jurriaan F. Parie and Stefan Feuerriegel
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Joel Persson: Department of Management, Technology, and Economics, ETH Zurich (Swiss Federal Institute of Technology), 8092 Zurich, Switzerland
Jurriaan F. Parie: Department of Management, Technology, and Economics, ETH Zurich (Swiss Federal Institute of Technology), 8092 Zurich, Switzerland
Stefan Feuerriegel: Department of Management, Technology, and Economics, ETH Zurich (Swiss Federal Institute of Technology), 8092 Zurich, Switzerland

Proceedings of the National Academy of Sciences, 2021, vol. 118, issue 26, e2100664118

Abstract: In response to the novel coronavirus disease (COVID-19), governments have introduced severe policy measures with substantial effects on human behavior. Here, we perform a large-scale, spatiotemporal analysis of human mobility during the COVID-19 epidemic. We derive human mobility from anonymized, aggregated telecommunication data in a nationwide setting (Switzerland; 10 February to 26 April 2020), consisting of ∼1.5 billion trips. In comparison to the same time period from 2019, human movement in Switzerland dropped by 49.1%. The strongest reduction is linked to bans on gatherings of more than five people, which are estimated to have decreased mobility by 24.9%, followed by venue closures (stores, restaurants, and bars) and school closures. As such, human mobility at a given day predicts reported cases 7 to 13 d ahead. A 1% reduction in human mobility predicts a 0.88 to 1.11% reduction in daily reported COVID-19 cases. When managing epidemics, monitoring human mobility via telecommunication data can support public decision makers in two ways. First, it helps in assessing policy impact; second, it provides a scalable tool for near real-time epidemic surveillance, thereby enabling evidence-based policies.

Keywords: COVID-19; epidemiology; human mobility; telecommunication data; Bayesian modeling (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (8)

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