US-county level variation in intersecting individual, household and community characteristics relevant to COVID-19 and planning an equitable response: a cross-sectional analysis
US-county level variation in intersecting individual, household and community characteristics relevant to COVID-19 and planning an equitable response: a cross-sectional analysis
复制标题
DOI：
10.1136/bmjopen-2020-039886
复制
发表时间：
2020-01-01
期刊：
影响因子：
2.9
通讯作者：
Kiang, Mathew, V
中科院分区：
文献类型：
--
作者：
Chin, Taylor;Kahn, Rebecca;Kiang, Mathew, V
目的：阐明影响COVID-19对美国各县及其应对能力的个人、家庭和社区因素的交叉点和县际差异。我们以国际经验为指导，并考虑了重要的流行病学参数，确定了影响COVID-19感染和生存风险的关键个人、家庭和社区特征。利用可公开获得的数据，我们开发了一个开放获取的在线工具，允许对特定国家的风险因素进行查询和绘图。作为一个说明性的例子，我们评估了美国各县年龄（个人水平）、贫困（家庭水平）和集体之家（社区水平）的两两交叉。我们还研究了这些因素如何与有色人种（即非西班牙裔白人）的人口比例相交，这是一个反映美国种族关系历史的指标。我们将“高风险”县定义为高于第75个百分位数的县。该阈值可以通过在线工具修改。设置美国县。参与者的分析基于地区卫生资源档案、美国社区调查、疾病控制和预防中心地图集文件、国家卫生统计中心和RWJF社区卫生排名等公开可用的县级数据。结果我们的研究结果表明，影响COVID-19感染、严重疾病或死亡风险的个人、家庭和社区特征分布在县间存在显著差异。大约9%的县，影响了1000万居民，在年龄和群体方面都处于高风险类别。大约14%的县，影响着3100万居民，贫困率高，有色人种比例高。结论：联邦政府和州政府将从认识到州内、县间人口风险和应对能力的高度差异中受益。公平应对大流行需要制定战略，保护那些面临COVID-19不良后果及其社会和经济影响风险最高的县的人。
Objectives To 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. Design We 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. Setting US counties. Participants Analyses 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. Results Our 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. Conclusion Federal 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.