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美国冠状病毒发病率和死亡率的空间差异:截至 2020 年 5 月的生态分析。

Spatial Disparities in Coronavirus Incidence and Mortality in the United States: An Ecological Analysis as of May 2020.

机构信息

Department of Geography & Geosciences, University of Louisville, Louisville, Kentucky.

Department of Population Health, School of Medicine & Health Sciences, University of North Dakota, Grand Forks, North Dakota.

出版信息

J Rural Health. 2020 Jun;36(3):433-445. doi: 10.1111/jrh.12476. Epub 2020 Jun 16.

Abstract

PURPOSE

This ecological analysis investigates the spatial patterns of the COVID-19 epidemic in the United States in relation to socioeconomic variables that characterize US counties.

METHODS

Data on confirmed cases and deaths from COVID-19 for 2,814 US counties were obtained from Johns Hopkins University. We used Geographic Information Systems (GIS) to map the spatial aspects of this pandemic and investigate the disparities between metropolitan and nonmetropolitan communities. Multiple regression models were used to explore the contextual risk factors of infections and death across US counties. We included population density, percent of population aged 65+, percent population in poverty, percent minority population, and percent of the uninsured as independent variables. A state-level measure of the percent of the population that has been tested for COVID-19 was used to control for the impact of testing.

FINDINGS

The impact of COVID-19 in the United States has been extremely uneven. Although densely populated large cities and their surrounding metropolitan areas are hotspots of the pandemic, it is counterintuitive that incidence and mortality rates in some small cities and nonmetropolitan counties approximate those in epicenters such as New York City. Regression analyses support the hypotheses of positive correlations between COVID-19 incidence and mortality rates and socioeconomic factors including population density, proportions of elderly residents, poverty, and percent population tested.

CONCLUSIONS

Knowledge about the spatial aspects of the COVID-19 epidemic and its socioeconomic correlates can inform first responders and government efforts. Directives for social distancing and to "shelter-in-place" should continue to stem the spread of COVID-19.

摘要

目的

本生态分析调查了与描述美国各县的社会经济变量相关的美国 COVID-19 疫情的空间模式。

方法

从约翰霍普金斯大学获得了美国 2814 个县的 COVID-19 确诊病例和死亡数据。我们使用地理信息系统(GIS)来绘制这一大流行病的空间方面,并调查大都市和非大都市社区之间的差异。使用多元回归模型探索美国各县感染和死亡的背景风险因素。我们将人口密度、65 岁以上人口比例、贫困人口比例、少数民族人口比例和未参保人口比例作为自变量。使用州级的 COVID-19 检测人口比例来控制检测的影响。

结果

美国 COVID-19 的影响极其不均衡。尽管人口稠密的大城市及其周边大都市区是该大流行病的热点地区,但令人感到意外的是,一些小城市和非大都市区的发病率和死亡率与纽约市等中心地区相近。回归分析支持 COVID-19 发病率和死亡率与人口密度、老年居民比例、贫困和受检人口比例等社会经济因素之间存在正相关关系的假设。

结论

了解 COVID-19 疫情的空间方面及其社会经济关联可以为急救人员和政府提供信息。保持社交距离和“就地避难”的指令应继续遏制 COVID-19 的传播。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78cc/7323165/115ddde90d6d/JRH-36-433-g001.jpg

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