Social vulnerability and county stay-at-home behavior during COVID-19 stay-at-home orders, United States, April 7–April 20, 2020

Abstract

Purpose Early COVID-19 mitigation relied on people staying home except for essential trips. The ability to stay home may differ by sociodemographic factors. We analyzed how factors related to social vulnerability impact a community's ability to stay home during a stay-at-home order. Methods Using generalized, linear mixed models stratified by stay-at-home order (mandatory or not mandatory), we analyzed county-level stay-at-home behavior (inferred from mobile devices) during a period when a majority of United States counties had stay-at-home orders (April 7–April 20, 2020) with the Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI). Results Counties with higher percentages of single-parent households, mobile homes, and persons with lower educational attainment were associated with lower stay-at-home behavior compared with counties with lower respective percentages. Counties with higher unemployment, higher percentages of limited-English-language speakers, and more multi-unit housing were associated with increases in stay-at-home behavior compared with counties with lower respective percentages. Stronger effects were found in counties with mandatory orders. Conclusions Sociodemographic factors impact a community's ability to stay home during COVID-19 stay-at-home orders. Communities with higher social vulnerability may have more essential workers without work-from-home options or fewer resources to stay home for extended periods, which may increase risk for COVID-19. Results are useful for tailoring messaging, COVID-19 vaccine delivery, and public health responses to future outbreaks.

Comparison of National Vulnerability Indices Used by the Centers for Disease Control and Prevention for the COVID-19 Response

“…13 The CCVI adds 4 themes to the CDC-SVI themes that address population density and epidemiological, health care systems, and high-risk environment factors that may affect COVID-19 outcomes ( To create the composite CCVI measure, percentiles of each variable are summed for each CCVI theme. 11 CCVI data can be classified by quartiles (Figure 2).…”

Business Shifting During the Outbreak; Impulsive or Contrived? Generation Cohort Perspective

“…Changes during COVID-19 is unavoidable since the restriction and jeopardized situation is traumatized people. It is not only change people risk perception, social vulnerability and change of lifestyle (Aebli et al, 2022;Fletcher et al, 2021;Shafran et al, 2021;Wang et al, 2021). The use of smartphone is increased exponentially since people have limited choice of activity during the outbreak even for accessing the updated news of COVID -19 or general matter such as social media (Mahmood et al, 2021).…”

“…As they get older, they focus on a balance between work and family. (Wilska 2004;Markert, 2004Jackson et.al, 2011Williams andPage, 2011 in Marjanen et. al, 2019) This generation prefers to be involved with marketing, rather than endure it (Ritchie, 2002in Chaney et.…”

“…Gen X is often described as the neglected and forgotten generation, the generation between the Boomers and Gen Y. More recent studies describe them as well educated, family oriented, and multicultural (Wilska 2004;M arkert, 2004M arkert, Jackson et.al, 2011 13 Williams andPage, 2011 in Marjanen et. al, 2019).…”

Auditing completion of nursing records as an outcome indicator for identifying patients at risk of developing pressure ulcers, falling, and social vulnerability: An observational study

“…Downton scale is a suitable tool for identifying this risk (Choi et al, 2021). There are different tools available for the identification of patients at risk of being socially vulnerable, who are susceptible to health problems as a result of sociodemographic problems (Abeliansky et al, 2021; Fletcher et al, 2021), such as the Gijón scale, which is properly adapted to the care model existing in Spain.…”