ArticleThe Lancet. Digital health2022
Evaluating the reliability of mobility metrics from aggregated mobile phone data as proxies for SARS-CoV-2 transmission in the USA: a population-based study.
Article in The Lancet. Digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- 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
- Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Human mobility and sewage data correlate with COVID-19 epidemic evolution in a 3-year surveillance of the metropolitan area of Bologna.BMC infectious diseases · 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
- Evaluating the association between COVID-19 transmission and mobility in omicron outbreaks in China.Communications medicine · 2025Article
- Behavior-driven forecasts of neighborhood-level COVID-19 spread in New York City.PLoS computational biology · 2025Article
- Mobile phone data analyses for public health research: a scoping review.Frontiers in public health · 2025Article
- Spatial scales of COVID-19 transmission in Mexico.PNAS nexus · 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
- Assessing internal displacement patterns in Ukraine during the beginning of the Russian invasion in 2022.Scientific reports · 2024Article
- Age-specific transmission dynamics of SARS-CoV-2 during the first 2 years of the pandemic.PNAS nexus · 2024Article
- Advancing Population Health Through Open Environmental Data Platforms.Current topics in behavioral neurosciences · 2024Review
- Infectious disease surveillance needs for the United States: lessons from Covid-19.Frontiers in public health · 2024Review
- Assessing the utility of COVID-19 case reports as a leading indicator for hospitalization forecasting in the United States.Epidemics · 2023Article
- The limits of human mobility traces to predict the spread of COVID-19: A transfer entropy approach.PNAS nexus · 2023Article
- Mass gatherings for political expression had no discernible association with the local course of the COVID-19 pandemic in the USA in 2020 and 2021.Nature human behaviour · 2023Article
- A comparison of COVID-19 outbreaks across US Combined Statistical Areas using new methods for estimating REpidemics · 2022Article
- What Heterogeneities in Individual-level Mobility Are Lost During Aggregation? Leveraging GPS Logger Data to Understand Fine-scale and Aggregated Patterns of Mobility.The American journal of tropical medicine and hygiene · 2022Article
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7 authors.
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Abstract
backgroundIn early 2020, the response to the SARS-CoV-2 pandemic focused on non-pharmaceutical interventions, some of which aimed to reduce transmission by changing mixing patterns between people. Aggregated location data from mobile phones are an important source of real-time information about human mobility on a population level, but the degree to which these mobility metrics capture the relevant contact patterns of individuals at risk of transmitting SARS-CoV-2 is not clear. In this study we describe changes in the relationship between mobile phone data and SARS-CoV-2 transmission in the USA.
methodsIn this population-based study, we collected epidemiological data on COVID-19 cases and deaths, as well as human mobility metrics collated by advertisement technology that was derived from global positioning systems, from 1396 counties across the USA that had at least 100 laboratory-confirmed cases of COVID-19. We grouped these counties into six ordinal categories, defined by the National Center for Health Statistics (NCHS) and graded from urban to rural, and quantified the changes in COVID-19 transmission using estimates of the effective reproduction number (R
findingsWe show that the reproduction number is most strongly associated with mobility proxies for change in the travel into counties (0·757 [95% CI 0·689 to 0·857]), but this relationship primarily holds for counties in the three most urban categories as defined by the NCHS. This relationship weakens considerably after the initial 15 weeks of the epidemic (0·442 [-0·492 to -0·392]), consistent with the emergence of more complex local policies and behaviours, including masking.
interpretationOur study shows that the integration of mobility metrics into retrospective modelling efforts can be useful in identifying links between these metrics and R
fundingThere was no funding source for this study.
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