Details

Autor(en) / Beteiligte

• Chin, Taylor
• Kahn, Rebecca
• Li, Ruoran
• Chen, Jarvis T
• Krieger, Nancy
• Buckee, Caroline O
• Balsari, Satchit
• Kiang, Mathew V

Titel

US-county level variation in intersecting individual, household and community characteristics relevant to COVID-19 and planning an equitable response: a cross-sectional analysis

Ist Teil von

• BMJ open, 2020-09, Vol.10 (9), p.e039886-e039886

Ort / Verlag

England: BMJ Publishing Group LTD

Erscheinungsjahr

2020

Link zum Volltext

Quelle

Sociological Abstracts

Beschreibungen/Notizen

• ObjectivesTo illustrate the intersections of, and intercounty variation in, individual, household and community factors that influence the impact of COVID-19 on US counties and their ability to respond.DesignWe identified key individual, household and community characteristics influencing COVID-19 risks of infection and survival, guided by international experiences and consideration of epidemiological parameters of importance. Using publicly available data, we developed an open-access online tool that allows county-specific querying and mapping of risk factors. As an illustrative example, we assess the pairwise intersections of age (individual level), poverty (household level) and prevalence of group homes (community-level) in US counties. We also examine how these factors intersect with the proportion of the population that is people of colour (ie, not non-Hispanic white), a metric that reflects histories of US race relations. We defined ‘high’ risk counties as those above the 75th percentile. This threshold can be changed using the online tool.SettingUS counties.ParticipantsAnalyses are based on publicly available county-level data from the Area Health Resources Files, American Community Survey, Centers for Disease Control and Prevention Atlas file, National Center for Health Statistic and RWJF Community Health Rankings.ResultsOur findings demonstrate significant intercounty variation in the distribution of individual, household and community characteristics that affect risks of infection, severe disease or mortality from COVID-19. About 9% of counties, affecting 10 million residents, are in higher risk categories for both age and group quarters. About 14% of counties, affecting 31 million residents, have both high levels of poverty and a high proportion of people of colour.ConclusionFederal and state governments will benefit from recognising high intrastate, intercounty variation in population risks and response capacity. Equitable responses to the pandemic require strategies to protect those in counties at highest risk of adverse COVID-19 outcomes and their social and economic impacts.