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美国马萨诸塞州的种族隔离、检测点可及性与 COVID-19 发病率

Racial Segregation, Testing Site Access, and COVID-19 Incidence Rate in Massachusetts, USA.

机构信息

Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA.

Geocomputation Center for Social Science, Wuhan University, Wuhan 430079, China.

出版信息

Int J Environ Res Public Health. 2020 Dec 19;17(24):9528. doi: 10.3390/ijerph17249528.

Abstract

The U.S. has merely 4% of the world population, but contains 25% of the world's COVID-19 cases. Since the COVID-19 outbreak in the U.S., Massachusetts has been leading other states in the total number of COVID-19 cases. Racial residential segregation is a fundamental cause of racial disparities in health. Moreover, disparities of access to health care have a large impact on COVID-19 cases. Thus, this study estimates racial segregation and disparities in testing site access and employs economic, demographic, and transportation variables at the city/town level in Massachusetts. Spatial regression models are applied to evaluate the relationships between COVID-19 incidence rate and related variables. This is the first study to apply spatial analysis methods across neighborhoods in the U.S. to examine the COVID-19 incidence rate. The findings are: (1) Residential segregations of Hispanic and Non-Hispanic Black/African Americans have a significantly positive association with COVID-19 incidence rate, indicating the higher susceptibility of COVID-19 infections among minority groups. (2) Non-Hispanic Black/African Americans have the shortest drive time to testing sites, followed by Hispanic, Non-Hispanic Asians, and Non-Hispanic Whites. The drive time to testing sites is significantly negatively associated with the COVID-19 incidence rate, implying the importance of the accessibility of testing sites by all populations. (3) Poverty rate and road density are significant explanatory variables. Importantly, overcrowding represented by more than one person per room is a significant variable found to be positively associated with COVID-19 incidence rate, suggesting the effectiveness of social distancing for reducing infection. (4) Different from the findings of previous studies, the elderly population rate is not statistically significantly correlated with the incidence rate because the elderly population in Massachusetts is less distributed in the hotspot regions of COVID-19 infections. The findings in this study provide useful insights for policymakers to propose new strategies to contain the COVID-19 transmissions in Massachusetts.

摘要

美国仅占世界人口的 4%,却拥有全球 25%的 COVID-19 病例。自美国 COVID-19 疫情爆发以来,马萨诸塞州的 COVID-19 病例总数一直位居各州之首。种族居住隔离是造成健康方面种族差异的根本原因。此外,获得医疗保健的机会差异对 COVID-19 病例有很大影响。因此,本研究估计了马萨诸塞州城市/城镇层面的种族隔离和检测点准入差异,并采用了经济、人口和交通变量。空间回归模型用于评估 COVID-19 发病率与相关变量之间的关系。这是第一项应用空间分析方法研究美国社区 COVID-19 发病率的研究。研究结果表明:(1)西班牙裔和非西班牙裔黑人和非洲裔美国人的居住隔离与 COVID-19 发病率呈显著正相关,表明少数群体感染 COVID-19 的风险更高。(2)非西班牙裔黑人和非洲裔美国人前往检测点的驾车时间最短,其次是西班牙裔、非西班牙裔亚裔和非西班牙裔白人。前往检测点的驾车时间与 COVID-19 发病率呈显著负相关,这表明所有人群都能方便地获得检测点对控制疫情的重要性。(3)贫困率和道路密度是重要的解释变量。重要的是,每间房居住人数超过一人的拥挤程度是一个与 COVID-19 发病率呈正相关的显著变量,这表明保持社交距离对减少感染的有效性。(4)与之前研究的结果不同,老年人口比例与发病率没有统计学上的显著相关性,因为马萨诸塞州的老年人口在 COVID-19 感染热点地区的分布较少。本研究的结果为决策者提供了有用的见解,以提出新策略来遏制马萨诸塞州的 COVID-19 传播。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b37/7766428/99f09abadffd/ijerph-17-09528-g001.jpg

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