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Fine scale human mobility changes within 26 US cities in 2020 in response to the COVID-19 pandemic were associated with distance and income.
Arambepola, Rohan; Schaber, Kathryn L; Schluth, Catherine; Huang, Angkana T; Labrique, Alain B; Mehta, Shruti H; Solomon, Sunil S; Cummings, Derek A T; Wesolowski, Amy.
Afiliación
  • Arambepola R; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
  • Schaber KL; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
  • Schluth C; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
  • Huang AT; Department of Genetics, Cambridge University, Cambridge, United Kingdom.
  • Labrique AB; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
  • Mehta SH; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
  • Solomon SS; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
  • Cummings DAT; Department of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, MD, United States of America.
  • Wesolowski A; Department of Biology and the Emerging Pathogens Institute, University of Florida, Gainesville, FL, United States of America.
PLOS Glob Public Health ; 3(7): e0002151, 2023.
Article en En | MEDLINE | ID: mdl-37478056
ABSTRACT
Human mobility patterns changed greatly due to the COVID-19 pandemic. Despite many analyses investigating general mobility trends, there has been less work characterising changes in mobility on a fine spatial scale and developing frameworks to model these changes. We analyse zip code-level within-city mobility data from 26 US cities between February 2 -August 31, 2020. We use Bayesian models to characterise the initial decrease in mobility and mobility patterns between June-August at this fine spatial scale. There were similar temporal trends across cities but large variations in the magnitude of mobility reductions. Long-distance routes and higher-income subscribers, but not age, were associated with greater mobility reductions. At the city level, mobility rates around early April, when mobility was lowest, and over summer showed little association with non-pharmaceutical interventions or case rates. Changes in mobility patterns lasted until the end of the study period, despite overall numbers of trips recovering to near baseline levels in many cities.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Risk_factors_studies Idioma: En Revista: PLOS Glob Public Health Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Risk_factors_studies Idioma: En Revista: PLOS Glob Public Health Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos