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新冠大流行初期的邻里生态、案例和死亡:对当前和未来疫情的教训?

Neighborhood Ecologies, Cases, and Deaths during the Beginning of the COVID-19 Pandemic: Lessons for Current and Future Epidemics?

机构信息

From the Morehouse School of Medicine, Atlanta, Georgia.

Case Western Reserve Medical School, Cleveland, Ohio.

出版信息

South Med J. 2024 Nov;117(11):640-645. doi: 10.14423/SMJ.0000000000001757.

Abstract

OBJECTIVES

The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected Black and Latinx communities. Ecologic analyses have shown that counties with a higher percentage of Latinx and Black people have worse COVID-19 outcome rates. Few ecologic analyses have been published at the neighborhood (census tract) level. We sought to determine whether certain sociodemographic neighborhood ecologies were associated with COVID-19 case and death rates in metropolitan Atlanta, Georgia.

METHODS

We used census data and principal-component analysis to identify unique neighborhood ecologies. We then estimated correlation coefficients to determine whether the neighborhood profiles produced by a principal-component analysis were correlated with COVID-19 case and death rates. We conducted geographically weighted regression models to assess how correlation coefficients varied spatially for neighborhood ecologies and COVID-19 outcomes.

RESULTS

We identified two unique neighborhood profiles: (1) high percentage of residents, Hispanic ethnicity, without a high school diploma, without health insurance, living in crowded households, and lower percentage older than 65 years; and (2) high percentage of residents, Black race, living in poverty, unemployed, and households receiving Supplemental Nutrition Assistance Program benefits. Profile 1 was associated with COVID-19 case rate (Pearson = 0.462, < 0.001) and profile 2 was associated with COVID-19 death rate (Spearman = 0.279, < 0.001). Correlations between neighborhood profiles and COVID-19 outcomes varied spatially.

CONCLUSIONS

Neighborhoods were differentially at risk of COVID-19 cases or deaths depending on their sociodemographic ecology at the beginning of the COVID-19 pandemic. Prevention methods and interventions may need to consider different social determinants of health when addressing potential cases and deaths during future emergent epidemics.

摘要

目的

2019 年冠状病毒病(COVID-19)大流行对黑人和拉丁裔社区的影响不成比例。生态分析表明,拉丁裔和黑人比例较高的县 COVID-19 预后率较差。发表的关于邻里(普查区)层面的生态分析很少。我们试图确定在佐治亚州亚特兰大都会区,某些社会人口统计学邻里生态是否与 COVID-19 病例和死亡率相关。

方法

我们使用人口普查数据和主成分分析来确定独特的邻里生态。然后,我们估计相关系数,以确定主成分分析产生的邻里概况是否与 COVID-19 病例和死亡率相关。我们进行了地理加权回归模型,以评估邻里生态和 COVID-19 结果的相关系数在空间上的变化。

结果

我们确定了两个独特的邻里概况:(1)居民比例高,西班牙裔,没有高中文凭,没有医疗保险,居住在拥挤的家庭中,65 岁以上的比例较低;(2)居民比例高,黑人,生活贫困,失业,家庭接受补充营养援助计划(SNAP)福利。概况 1 与 COVID-19 病例率相关(Pearson = 0.462,<0.001),概况 2 与 COVID-19 死亡率相关(Spearman = 0.279,<0.001)。邻里概况与 COVID-19 结果之间的相关性在空间上有所不同。

结论

在 COVID-19 大流行开始时,邻里的社会人口统计学生态不同,其 COVID-19 病例或死亡的风险也不同。在应对未来突发传染病的潜在病例和死亡时,预防方法和干预措施可能需要考虑不同的健康决定因素。

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