ArticleNPJ digital medicine2021
It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US.
Article in NPJ digital medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Spatio-Temporal COVID-19 Modeling: A Global Systematic Review of Data Integration, Equity, and Lessons for Pandemic Preparedness.International journal of environmental research and public health · 2026Pooled it
- Enhancing COVID-19 Screening Models With Epidemiological and Mobility Features: Machine-Learning Model Study.JMIR AI · 2026Article
- Mobility-driven synthetic contact matrices as a scalable solution for real-time pandemic response modeling.Nature communications · 2026Article
- Explaining COVID-19 dynamics through user activity data from digital platforms with Yandex's self-isolation index as a case study.Scientific reports · 2025Article
- Revealing spatiotemporal variations in areas potentially linked to COVID-19 spread using fine-grained population data.Scientific reports · 2025Article
- Comparative evaluation of behavioral epidemic models using COVID-19 data.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Mobile phone data analyses for public health research: a scoping review.Frontiers in public health · 2025Article
- A novel approach to model the role of mobility suppression and vaccinations in containing epidemics in a network of cities.Infectious Disease Modelling · 2024Article
- Impacts of human mobility on the citywide transmission dynamics of 18 respiratory viruses in pre- and post-COVID-19 pandemic years.Nature communications · 2024Article
- A mixture of mobility and meteorological data provides a high correlation with COVID-19 growth in an infection-naive population: a study for Spanish provinces.Frontiers in public health · 2024Article
- Revealing associations between spatial time series trends of COVID-19 incidence and human mobility: an analysis of bidirectionality and spatiotemporal heterogeneity.International journal of health geographics · 2023Article
- The limits of human mobility traces to predict the spread of COVID-19: A transfer entropy approach.PNAS nexus · 2023Article
- Understanding the impact of mobility on COVID-19 spread: A hybrid gravity-metapopulation model of COVID-19.PLoS computational biology · 2023Article
- Effects of non-compulsory and mandatory COVID-19 interventions on travel distance and time away from home, Norway, 2021.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023Article
- Semi-parametric modeling of SARS-CoV-2 transmission using tests, cases, deaths, and seroprevalence data.ArXiv · 2023Article
- Novel estimates reveal subnational heterogeneities in disease-relevant contact patterns in the United States.PLoS computational biology · 2022Article
- The Apple Mobility Trends Data in Human Mobility Patterns during Restrictions and Prediction of COVID-19: A Systematic Review and Meta-Analysis.Healthcare (Basel, Switzerland) · 2022Review
- Inter-prefectural Travel and Network Connectedness During the COVID-19 Pandemic in Japan.Journal of epidemiology · 2022Article
- Mobility was a significant determinant of reported COVID-19 incidence during the Omicron Surge in the most populous U.S. Counties.BMC infectious diseases · 2022Article
- Translational Bioinformatics to Enable Precision Medicine for All: Elevating Equity across Molecular, Clinical, and Digital Realms.Yearbook of medical informatics · 2022Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Restricting in-person interactions is an important technique for limiting the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Although early research found strong associations between cell phone mobility and infection spread during the initial outbreaks in the United States, it is unclear whether this relationship persists across locations and time. We propose an interpretable statistical model to identify spatiotemporal variation in the association between mobility and infection rates. Using 1 year of US county-level data, we found that sharp drops in mobility often coincided with declining infection rates in the most populous counties in spring 2020. However, the association varied considerably in other locations and across time. Our findings are sensitive to model flexibility, as more restrictive models average over local effects and mask much of the spatiotemporal variation. We conclude that mobility does not appear to be a reliable leading indicator of infection rates, which may have important policy implications.
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Registered trials
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.