ArticleProceedings of the National Academy of Sciences of the United States of America2021
Monitoring the COVID-19 epidemic with nationwide telecommunication data.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The methodologies to assess the effectiveness of non-pharmaceutical interventions during COVID-19: a systematic review.European journal of epidemiology · 2022Pooled it
- Monitoring changes in vitamin D levels during the COVID-19 pandemic with routinely-collected laboratory data.Nature communications · 2025Article
- Local effects of non-pharmaceutical interventions on mitigation of COVID-19 spread through decreased human mobilities in Japan: a prefecture-level mediation analysis.Scientific reports · 2024Article
- Optimizing the detection of emerging infections using mobility-based spatial sampling.International journal of applied earth observation and geoinformation : ITC journal · 2024Article
- The limits of human mobility traces to predict the spread of COVID-19: A transfer entropy approach.PNAS nexus · 2023Article
- The impact of national and international travel on spatio-temporal transmission of SARS-CoV-2 in Belgium in 2021.BMC infectious diseases · 2023Article
- Effectiveness assessment of non-pharmaceutical interventions: lessons learned from the COVID-19 pandemic.The Lancet. Public health · 2023Review
- Predicting mobility using limited data during early stages of a pandemic.Journal of business research · 2023Article
- The Gendered Consequences of COVID-19 for Internal Migration.Population research and policy review · 2023Article
- Development of forecast models for COVID-19 hospital admissions using anonymized and aggregated mobile network data.Scientific reports · 2022Article
- Unraveling the dynamic impacts of COVID-19 on metro ridership: An empirical analysis of Beijing and Shanghai, China.Transport policy · 2022Article
- SARS-CoV-2 suppression and early closure of bars and restaurants: a longitudinal natural experiment.Scientific reports · 2022Article
- Article
- Capturing spatial dependence of COVID-19 case counts with cellphone mobility data.Spatial statistics · 2022Article
- Novel mobility index tracks COVID-19 transmission following stay-at-home orders.Scientific reports · 2022Article
- Accelerated biological aging in COVID-19 patients.Nature communications · 2022Article
- Estimating the effect of mobility on SARS-CoV-2 transmission during the first and second wave of the COVID-19 epidemic, Switzerland, March to December 2020.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2022Article
- Comparing SARS-CoV-2 case rates between pupils, teachers and the general population: results from Germany.European journal of public health · 2022Article
- Article
- COVID-19: Estimation of the transmission dynamics in Spain using a stochastic simulator and black-box optimization techniques.Computer methods and programs in biomedicine · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.