Monitoring the COVID-19 epidemic with nationwide telecommunication data
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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, spatio-temporal analysis of human mobility during the COVID-19 epidemic. We derive human mobility from anonymized, aggregated telecommunication data in a nationwide setting (Switzerland; February 10 - April 26, 2020), consisting of 1.5 billion trips. In comparison to the same time period from 2019, human movement in Switzerland dropped by 49.1 people, which is estimated to have decreased mobility by 24.9 venue closures (stores, restaurants, and bars) and school closures. As such, human mobility at a given day predicts reported cases 7-13 days ahead. A 1 reduction in human mobility predicts a 0.88-1.11 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.
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