ArticleThe Science of the total environment2021
Social-distancing fatigue: Evidence from real-time crowd-sourced traffic data.
Article in The Science of the total environment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 29 citations in OpenAlex.
- Societal values versus individual rights with respect to public health related practices during the COVID-19 pandemic in the U.S.PloS one · 2026Article
- Human mobility under disasters: a systematic review and framework for equitable and resilient mobility governance.npj natural hazards · 2025Article
- Social dilemma of nonpharmaceutical interventions: Determinants of dynamic compliance and behavioral shifts.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Variation in the Impact of New York on Pause on Traffic Congestion by Racialized Economic Segregation and Environmental Burden.GeoHealth · 2024Article
- The paradox of pandemic mitigation? Moderating role of pandemic severity on the impact of social distancing policies: a cultural value perspective.Globalization and health · 2024Article
- Impact of traffic congestion on asthma-related hospital visits in major Texas cities.PloS one · 2024Article
- Built environment factors moderate pandemic fatigue in social distance during the COVID-19 pandemic: A nationwide longitudinal study in the United States.Landscape and urban planning · 2023Article
- Quantifying COVID-19 recovery process from a human mobility perspective: An intra-city study in Wuhan.Cities (London, England) · 2023Article
- Does Pandemic Fatigue Prevent Farmers' Participation in the Rural Tourism Industry: A Comparative Study between Two Chinese Villages.International journal of environmental research and public health · 2022Article
- Green spaces, especially nearby forest, may reduce the SARS-CoV-2 infection rate: A nationwide study in the United States.Landscape and urban planning · 2022Article
- Quantifying diurnal changes in NOHygiene and environmental health advances · 2022Article
- Assessing Neighborhood-scale Traffic from Crowd-sensed Traffic Data: Findings from an Environmental Justice Community in New York City.Environmental science & policy · 2022Article
- Patterns of compliance with COVID-19 preventive behaviours: a latent class analysis of 20 000 UK adults.Journal of epidemiology and community health · 2022Article
- The dynamical formation of ephemeral groups on networks and their effects on epidemics spreading.Scientific reports · 2022Article
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4 authors at 1 institution in 1 country.
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Abstract
introductionTo mitigate the COVID-19 pandemic and prevent overwhelming the healthcare system, social-distancing policies such as school closure, stay-at-home orders, and indoor dining closure have been utilized worldwide. These policies function by reducing the rate of close contact within populations and result in decreased human mobility. Adherence to social distancing can substantially reduce disease spread. Thus, quantifying human mobility and social-distancing compliance, especially at high temporal resolution, can provide great insight into the impact of social distancing policies.
methodsWe used the movement of individuals around New York City (NYC), measured via traffic levels, as a proxy for human mobility and the impact of social-distancing policies (i.e., work from home policies, school closure, indoor dining closure etc.). By data mining Google traffic in real-time, and applying image processing, we derived high resolution time series of traffic in NYC. We used time series decomposition and generalized additive models to quantify changes in rush hour/non-rush hour, and weekday/weekend traffic, pre-pandemic and following the roll-out of multiple social distancing interventions.
resultsMobility decreased sharply on March 14, 2020 following declaration of the pandemic. However, levels began rebounding by approximately April 13, almost 2 months before stay-at-home orders were lifted, indicating premature increase in mobility, which we term social-distancing fatigue. We also observed large impacts on diurnal traffic congestion, such that the pre-pandemic bi-modal weekday congestion representing morning and evening rush hour was dramatically altered. By September, traffic congestion rebounded to approximately 75% of pre-pandemic levels.
conclusionUsing crowd-sourced traffic congestion data, we described changes in mobility in Manhattan, NYC, during the COVID-19 pandemic. These data can be used to inform human mobility changes during the current pandemic, in planning for responses to future pandemics, and in understanding the potential impact of large-scale traffic interventions such as congestion pricing 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.