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
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-sta...
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| Format: | Article |
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BMJ Publishing Group
2024-07-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/14/7/e077153.full |
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| author | Alain B Labrique Amy Wesolowski Derek A T Cummings Shruti H Mehta Sunil S Solomon Rohan Arambepola Kathryn Schaber Catherine Schluth |
| author_facet | Alain B Labrique Amy Wesolowski Derek A T Cummings Shruti H Mehta Sunil S Solomon Rohan Arambepola Kathryn Schaber Catherine Schluth |
| author_sort | Alain B Labrique |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-733de6d2f2ac4d969c1d0b1fef600408 |
| institution | DOAJ |
| issn | 2044-6055 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-733de6d2f2ac4d969c1d0b1fef6004082025-08-20T02:48:23ZengBMJ Publishing GroupBMJ Open2044-60552024-07-0114710.1136/bmjopen-2023-077153Geography 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 areasAlain B Labrique0Amy Wesolowski1Derek A T Cummings2Shruti H Mehta3Sunil S Solomon4Rohan Arambepola5Kathryn Schaber6Catherine Schluth72 Department of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA1 Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA4 Department of Biology and the Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA1 Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA1 Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA1 Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA1 Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA1 Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USAObjective 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.https://bmjopen.bmj.com/content/14/7/e077153.full |
| spellingShingle | Alain B Labrique Amy Wesolowski Derek A T Cummings Shruti H Mehta Sunil S Solomon Rohan Arambepola Kathryn Schaber Catherine Schluth 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 BMJ Open |
| title | 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| url | https://bmjopen.bmj.com/content/14/7/e077153.full |
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