Community Susceptibility and Resiliency to COVID-19 Across the Rural-Urban Continuum in the United States
Community Susceptibility and Resiliency to COVID-19 Across the Rural-Urban Continuum in the United States
复制标题
DOI：
10.1111/jrh.12477
复制
发表时间：
2020-06-16
影响因子：
4.9
通讯作者：
Peters, David J.
中科院分区：
文献类型：
--
作者：
Peters, David J.
目的本研究创建了县级COVID-19易感性量表，描述了其组成部分，然后评估了城乡连续体中易感地区的健康和社会经济弹性。方法采用因子分析法，将美国3,079个县的11个指标分为7个不同的敏感因子。使用多变量一般线性模型评估无条件平均差异。2018年的数据主要来自美国人口普查局和CDC。约33%的农村县高度易感COVID-19，这是由老年人和健康受损的人群以及老年人护理设施驱动的。农村县的主要脆弱性包括医生较少，缺乏心理健康服务，残疾程度较高，以及更多的人没有保险。互联网接入条件差限制了远程医疗。缺乏社会资本和社会服务可能会阻碍当地大流行病的恢复。肉类加工设施在小城市县推动风险。虽然大都市县由于更健康和更年轻的人口而不太容易受到影响，但由于人口稠密的社区传播，约有6%的人处于危险之中。大都市的脆弱性包括健康和糖尿病风险较高的少数民族，语言障碍，作为有助于传播感染的交通枢纽，以及严重的住房困难。结论有一个迫切需要提前知道具体类型的脆弱性和脆弱性，让地方和州卫生官员相应地计划和分配资源。在农村地区，必须为脆弱人口提供就地避难所，而在大都市地区，则需要发布全面关闭令，以阻止社区传播。大流行病应对计划应针对脆弱性。
Purpose This study creates a COVID-19 susceptibility scale at the county level, describes its components, and then assesses the health and socioeconomic resiliency of susceptible places across the rural-urban continuum. Methods Factor analysis grouped 11 indicators into 7 distinct susceptibility factors for 3,079 counties in the conterminous United States. Unconditional mean differences are assessed using a multivariate general linear model. Data from 2018 are primarily taken from the US Census Bureau and CDC. Results About 33% of rural counties are highly susceptible to COVID-19, driven by older and health-compromised populations, and care facilities for the elderly. Major vulnerabilities in rural counties include fewer physicians, lack of mental health services, higher disability, and more uninsured. Poor Internet access limits telemedicine. Lack of social capital and social services may hinder local pandemic recovery. Meat processing facilities drive risk in micropolitan counties. Although metropolitan counties are less susceptible due to healthier and younger populations, about 6% are at risk due to community spread from dense populations. Metropolitan vulnerabilities include minorities at higher health and diabetes risk, language barriers, being a transportation hub that helps spread infection, and acute housing distress. Conclusions There is an immediate need to know specific types of susceptibilities and vulnerabilities ahead of time to allow local and state health officials to plan and allocate resources accordingly. In rural areas it is essential to shelter-in-place vulnerable populations, whereas in large metropolitan areas general closure orders are needed to stop community spread. Pandemic response plans should address vulnerabilities.