ArticleNonlinear dynamics2020
Human mobility and COVID-19 initial dynamics.
Article in Nonlinear dynamics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
44 citing papers in PubMed, 120 citations in OpenAlex.
- The spatiotemporal dynamics of COVID-19 in Europe: time-series clustering maps 5 distinct trajectories to spatial patterns.Population health metrics · 2025Article
- Machine Learning and Artificial Intelligence for Infectious Disease Surveillance, Diagnosis, and Prognosis.Viruses · 2025Review
- Exploring Human Mobility: A Time-Informed Approach to Pattern Mining and Sequence Similarity.International journal of geographical information science : IJGIS · 2025Article
- The economic linkages of Covid-19 across sectors and regions in Europe.SERIEs : journal of the Spanish Economic Association · 2025Article
- Transmission of SARS-CoV-2 among underserved pastoralist communities in Kajiado County, Kenya: 2020-2022.PloS one · 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
- Inference on a Multi-Patch Epidemic Model with Partial Mobility, Residency, and Demography: Case of the 2020 COVID-19 Outbreak in Hermosillo, Mexico.Entropy (Basel, Switzerland) · 2023Article
- Ecosystem degradation and the spread of Covid-19.Environmental monitoring and assessment · 2023Review
- Restricting Human Movement During the COVID-19 Pandemic: New Research Avenues in the Study of Mobility, Migration, and Citizenship.The International migration review · 2023Article
- Systematic literature review on impacts of COVID-19 pandemic and corresponding measures on mobility.Transportation · 2023Article
- Understanding Covid-19 Mobility Through Human Capital: A Unified Causal Framework.Computational economics · 2023Article
- Article
- Evaluating the effectiveness of lockdowns and restrictions during SARS-CoV-2 variant waves in the Canadian province of Nova Scotia.Frontiers in public health · 2023Article
- Sensing dynamic human activity zones using geo-tagged big data in Greater London, UK during the COVID-19 pandemic.PloS one · 2023Article
- Modelling the propagation of infectious disease via transportation networks.Scientific reports · 2022Article
- COVID-19 lockdown introduces human mobility pattern changes for both Guangdong-Hong Kong-Macao greater bay area and the San Francisco bay area.International journal of applied earth observation and geoinformation : ITC journal · 2022Article
- Examining the COVID-19 case growth rate due to visitor vs. local mobility in the United States using machine learning.Scientific reports · 2022Article
- Tracking the transmission dynamics of COVID-19 with a time-varying coefficient state-space model.Statistics in medicine · 2022Article
- Clustering and mapping the first COVID-19 outbreak in France.BMC public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Countries in Europe took different mobility containment measures to curb the spread of COVID-19. The European Commission asked mobile network operators to share on a voluntarily basis anonymised and aggregate mobile data to improve the quality of modelling and forecasting for the pandemic at EU level. In fact, mobility data at EU scale can help understand the dynamics of the pandemic and possibly limit the impact of future waves. Still, since a reliable and consistent method to measure the evolution of contagion at international level is missing, a systematic analysis of the relationship between human mobility and virus spread has never been conducted. A notable exceptions are France and Italy, for which data on excess deaths, an indirect indicator which is generally considered to be less affected by national and regional assumptions, are available at department and municipality level, respectively. Using this information together with anonymised and aggregated mobile data, this study shows that mobility alone can explain up to 92% of the initial spread in these two EU countries, while it has a slow decay effect after lockdown measures, meaning that mobility restrictions seem to have effectively contribute to save lives. It also emerges that internal mobility is more important than mobility across provinces and that the typical lagged positive effect of reduced human mobility on reducing excess deaths is around 14-20 days. An analogous analysis relative to Spain, for which an IgG SARS-Cov-2 antibody screening study at province level is used instead of excess deaths statistics, confirms the findings. The same approach adopted in this study can be easily extended to other European countries, as soon as reliable data on the spreading of the virus at a suitable level of granularity will be available. Looking at past data, relative to the initial phase of the outbreak in EU Member States, this study shows in which extent the spreading of the virus and human mobility are connected. The findings will support policymakers in formulating the best data-driven approaches for coming out of confinement and mostly in building future scenarios in case of new outbreaks.
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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.