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Fine scale human mobility changes in 26 US cities in 2020 in response to the COVID-19 pandemic were associated with distance and income.

Rohan ArambepolaKathryn L SchaberCatherine SchluthAngkana T HuangAlain B LabriqueShruti H MehtaSunil S SolomonDerek A T CummingsAmy Wesolowski
Published in: medRxiv : the preprint server for health sciences (2022)
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 mobility data from 26 US cities between February 2 â€" 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.
Keyphrases
  • endothelial cells
  • physical activity
  • air pollution
  • machine learning
  • electronic health record
  • artificial intelligence
  • big data