ArticlePloS one2021
Analysis of mobility data to build contact networks for COVID-19.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 44 citations in OpenAlex.
- VIBES: A multiscale modeling approach integrating within-host and between-hosts dynamics in epidemics.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- From crisis to new routine: shifts in urban shopping mobility and socioeconomic inequality during and after the COVID-19 shock.Frontiers in big data · 2026Article
- Identifying Areas with Low Access to the COVID-19 Vaccine: A New Objective Framework Incorporating Mobility Data.Healthcare (Basel, Switzerland) · 2025Article
- Work-related connectivity between Boston Logan international airport and urban communities with high social vulnerability during the COVID-19 pandemic.Tropical diseases, travel medicine and vaccines · 2025Article
- Dynamic Contact Networks in Confined Spaces: Synthesizing Micro-Level Encounter Patterns through Human Mobility Models from Real-World Data.Entropy (Basel, Switzerland) · 2024Article
- Optimizing the detection of emerging infections using mobility-based spatial sampling.International journal of applied earth observation and geoinformation : ITC journal · 2024Article
- A New Paradigm for Pandemic Preparedness.Current epidemiology reports · 2023Article
- Change of urban park usage as a response to the COVID-19 global pandemic.Scientific reports · 2023Article
- Volume of Care for Primary Care Physicians in Integrated vs Independent Practices Through the COVID-19 Pandemic.JAMA health forum · 2023Article
- Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model.Scientific reports · 2023Article
- How contact patterns during the COVID-19 pandemic are related to pre-pandemic contact patterns and mobility trends.BMC infectious diseases · 2023Article
- Spatial Optimization to Improve COVID-19 Vaccine Allocation.Vaccines · 2022Article
- Variability in Opioid-Related Drug Overdoses, Social Distancing, and Area-Level Deprivation during the COVID-19 Pandemic: a Bayesian Spatiotemporal Analysis.Journal of urban health : bulletin of the New York Academy of Medicine · 2022Article
- Modelling the dynamic relationship between spread of infection and observed crowd movement patterns at large scale events.Scientific reports · 2022Article
- COVID Student Study: A Year in the Life of College Students during the COVID-19 Pandemic Through the Lens of Mobile Phone Sensing.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2022Article
- Prioritizing vaccination based on analysis of community networks.Applied network science · 2022Article
- Simulating the impacts of interregional mobility restriction on the spatial spread of COVID-19 in Japan.Scientific reports · 2021Article
- A network-based group testing strategy for colleges.Applied network science · 2021Article
- A 2-year pandemic period analysis of facility and county-level characteristics of nursing home coronavirus deaths in the United States, January 1, 2020-December 18, 2021.Geriatric nursing (New York, N.Y.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As social distancing policies and recommendations went into effect in response to COVID-19, people made rapid changes to the places they visit. These changes are clearly seen in mobility data, which records foot traffic using location trackers in cell phones. While mobility data is often used to extract the number of customers that visit a particular business or business type, it is the frequency and duration of concurrent occupancy at those sites that governs transmission. Understanding the way people interact at different locations can help target policies and inform contact tracing and prevention strategies. This paper outlines methods to extract interactions from mobility data and build networks that can be used in epidemiological models. Several measures of interaction are extracted: interactions between people, the cumulative interactions for a single person, and cumulative interactions that occur at particular businesses. Network metrics are computed to identify structural trends which show clear changes based on the timing of stay-at-home orders. Measures of interaction and structural trends in the resulting networks can be used to better understand potential spreading events, the percent of interactions that can be classified as close contacts, and the impact of policy choices to control transmission.
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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.