1. Geography versus sociodemographics as predictors of changes in daily mobility across the USA during the COVID-19 pandemic: a two-stage regression analysis across 26 metropolitan areas.
- Author
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Schaber K, Arambepola R, Schluth C, Labrique AB, Mehta SH, Solomon SS, Cummings DAT, and Wesolowski A
- Subjects
- Humans, United States epidemiology, Regression Analysis, SARS-CoV-2, Pandemics, Sociodemographic Factors, Cities epidemiology, Geography, COVID-19 epidemiology
- Abstract
Objective: We investigated whether a zip code's location or demographics are most predictive of changes in daily mobility throughout the course of the COVID-19 pandemic., Design: We used a population-level study to examine the predictability of daily mobility during the COVID-19 pandemic using a two-stage regression approach, where generalised additive models (GAM) predicted mobility trends over time at a large spatial level, then the residuals were used to determine which factors (location, zip code-level features or number of non-pharmaceutical interventions (NPIs) in place) best predict the difference between a zip code's measured mobility and the average trend on a given date., Setting: We analyse zip code-level mobile phone records from 26 metropolitan areas in the USA on 15 March-31 September 2020, relative to October 2020., Results: While relative mobility had a general trend, a zip code's city-level location significantly helped to predict its daily mobility patterns. This effect was time-dependent, with a city's deviation from general mobility trends differing in both direction and magnitude throughout the course of 2020. The characteristics of a zip code further increased predictive power, with the densest zip codes closest to a city centre tended to have the largest decrease in mobility. However, the effect on mobility change varied by city and became less important over the course of the pandemic., Conclusions: The location and characteristics of a zip code are important for determining changes in daily mobility patterns throughout the course of the COVID-19 pandemic. These results can determine the efficacy of NPI implementation on multiple spatial scales and inform policy makers on whether certain NPIs should be implemented or lifted during the ongoing COVID-19 pandemic and when preparing for future public health emergencies., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
- Published
- 2024
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