U.S. regional differences in physical distancing: Evaluating racial and socioeconomic divides during the COVID-19 pandemic

Abstract

Health varies by U.S. region of residence. Despite regional heterogeneity in the outbreak of COVID-19, regional differences in physical distancing behaviors over time are relatively unknown. This study examines regional variation in physical distancing trends during the COVID-19 pandemic and investigates variation by race and socioeconomic status (SES) within regions. Data from the 2015–2019 five-year American Community Survey were matched with anonymized location pings data from over 20 million mobile devices (SafeGraph, Inc.) at the Census block group level. We visually present trends in the stay-at-home proportion by Census region, race, and SES throughout 2020 and conduct regression analyses to examine these patterns. From March to December, the stay-at-home proportion was highest in the Northeast (0.25 in March to 0.35 in December) and lowest in the South (0.24 to 0.30). Across all regions, the stay-at-home proportion was higher in block groups with a higher percentage of Blacks, as Blacks disproportionately live in urban areas where stay-at-home rates were higher (0.009 [CI: 0.008, 0.009]). In the South, West, and Midwest, higher-SES block groups stayed home at the lowest rates pre-pandemic; however, this trend reversed throughout March before converging in the months following. In the Northeast, lower-SES block groups stayed home at comparable rates to higher-SES block groups during the height of the pandemic but diverged in the months following. Differences in physical distancing behaviors exist across U.S. regions, with a pronounced Southern and rural disadvantage. Results can be used to guide reopening and COVID-19 mitigation plans.

Location matters: Regional variation in association of community burden of COVID-19 with caregiver and youth worry

“…In short, location matters. Given regional differences in COVID-19 incidence and response ( Udalova, 2021 ; Zang et al, 2021 ; Lyu and Wehby, 2020 ), these region-specific associations highlight that although there are overall relationships between community burden and caregiver and youth worry, the most salient community-level COVID-19-related conditions, in terms of worry, differ by location. For example, per the population-level random-effects patterns ( Fig.…”

“…Beyond the influence of family- and neighborhood-level socioeconomic status on COVID-19-related health outcomes, behaviors, and perceptions, different U.S. regions and metropolitan areas have been differentially affected by COVID-19. For example, COVID-19 infection/death rates and the concurrent economic impact has varied widely across the US ( Udalova, 2021 ), partially due to disparate responses to the pandemic (e.g., stay-at-home policies/behaviors, mask mandates, vaccination rates) ( Zang et al, 2021 ; Lyu and Wehby, 2020 ). Further, individuals’ worry about COVID-19 was related to self-reported community factors (general perceived sense-of-community, strictness of COVID-19 lockdown policies) ( Zhou and Guo, 2021 ), and anxiety levels in adults in China were greater if they knew of more COVID-19-related deaths and cases among friends/family or in their neighborhood ( Zhong et al, 2020 ; Liu et al, 2020a ).…”

Explaining the higher COVID-19 mortality rates among disproportionately Black counties: A decomposition analysis

“…Within the category of social distancing, two sub-indicators were identified from recent literature ( Kamis et al, 2021 ; Zang et al, 2021 ): Proportions of residents staying at home and household units with greater than 1 occupant per room. Proportions of residents staying at home is a measure of the social distancing environment constructed using microdata from the SafeGraph Social Metrics Dataset ( https://docs.safegraph.com/docs/social-distancing-metrics ), which relies on GPS information from anonymous mobile devices.…”

“…Several media sources and political figures have argued that the disparities in COVID-19 outcomes may be a result of differential adherence to social distancing across counties ( Dreher, 2020 ; Eligon et al, 2020 ; Kendi, 2020 ). For example, Black individuals were less likely to be able to work from home and were more likely to live in and be exposed to overcrowded areas relative to White individuals, and thus were less likely to practice social distancing ( Bureau of Labor Statistics, 2019 ; Kamis et al, 2021 ; Selden & Berdahl, 2020 ; Zang et al, 2021 ). In addition, limited access to testing due to socioeconomic status and lack of testing centers near Black neighborhoods may have also contributed to the COVID-19 mortality disparity between Black and non-Black counties ( Egede & Walker, 2020 ; Rader et al, 2020 ).…”

Mediating Effect of Viral Anxiety and Perceived Benefits of Physical Distancing on Adherence to Distancing Among High School Students Amid COVID-19

“…Previous studies reported that country, race, income, education, and health service availability can influence adherence to physical distancing. 7 8 9 Individual factors such as health-related beliefs and perceived social norms can also influence adherence to physical distancing. 10 …”