ArticleProceedings of the National Academy of Sciences of the United States of America2022
A spatiotemporal decay model of human mobility when facing large-scale crises.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 56 citations in OpenAlex.
- Structural inequality shapes the daily rhythm of stationarity and mobility.Nature communications · 2026Article
- Extreme heat reduces and reshapes urban mobility.PNAS nexus · 2026Article
- Faster Uptake, Slower Let-Down: Asymmetric Community Responses to Changing Risks During a Pandemic.Risk analysis : an official publication of the Society for Risk Analysis · 2026Article
- The persistence of behavioral disparities post-pandemic: Insights from activity time series data.Scientific reports · 2026Article
- Distance-amplified power-law distributions better characterize human long-distance travel.Scientific reports · 2026Article
- Predicting schistosome transmission in rural Uganda using water contact data from wearable GPS devices.Nature health · 2026Article
- Identifying delayed human response to external risks: an econometric analysis of mobility change during a pandemic.BMC medical research methodology · 2025Article
- Adaptive mobility responses during Hurricanes Helene and Milton in 2024.medRxiv : the preprint server for health sciences · 2025Article
- Using human mobility data to quantify experienced urban inequalities.Nature human behaviour · 2025Review
- Behavior-driven forecasts of neighborhood-level COVID-19 spread in New York City.PLoS computational biology · 2025Article
- The spatiotemporal scaling laws of urban population dynamics.Nature communications · 2025Article
- Resilience of mobility network to dynamic population response across COVID-19 interventions: Evidences from Chile.PLoS computational biology · 2025Article
- Bias in mobility datasets drives divergence in modeled outbreak dynamics.Communications medicine · 2025Article
- Emergence of shield immunity during spatial contagions.Npj complexity · 2025Article
- Bounded risk disposition explains Turing patterns and tipping points during spatial contagions.Royal Society open science · 2024Article
- Returners and explorers dichotomy in the face of natural hazards.Scientific reports · 2024Article
- Modeling the Impacts of Governmental and Human Responses on COVID-19 Spread Using Statistical Machine Learning.International journal of digital earth · 2024Article
- Resilience patterns of human mobility in response to extreme urban floods.National science review · 2023Article
- Human mobility patterns are associated with experienced partisan segregation in US metropolitan areas.Scientific reports · 2023Article
- Network Science-based Urban Forecast Dashboard.ARIC 2022 : proceedings of the 5th ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities (ARIC 2022) : 1st Nov 2022, Seattle, WA, USA. ACM SIGSPATIAL International Workshop on Advances in Resilient and In... · 2022Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A common feature of large-scale extreme events, such as pandemics, wildfires, and major storms is that, despite their differences in etiology and duration, they significantly change routine human movement patterns. Such changes, which can be major or minor in size and duration and which differ across contexts, affect both the consequences of the events and the ability of governments to mount effective responses. Based on naturally tracked, anonymized mobility behavior from over 90 million people in the United States, we document these mobility differences in space and over time in six large-scale crises, including wildfires, major tropical storms, winter freeze and pandemics. We introduce a model that effectively captures the high-dimensional heterogeneity in human mobility changes following large-scale extreme events. Across five different metrics and regardless of spatial resolution, the changes in human mobility behavior exhibit a consistent hyperbolic decline, a pattern we characterize as "spatiotemporal decay." When applied to the case of COVID-19, our model also uncovers significant disparities in mobility changes-individuals from wealthy areas not only reduce their mobility at higher rates at the start of the pandemic but also maintain the change longer. Residents from lower-income regions show a faster and greater hyperbolic decay, which we suggest may help account for different COVID-19 rates. Our model represents a powerful tool to understand and forecast mobility patterns post emergency, and thus to help produce more effective responses.
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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 Socratic graph.