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.

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 US

SUBMITTER: Schaber K 

PROVIDER: S-EPMC11344868 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature