SARS-CoV-2 testing in North Carolina: Racial, ethnic, and geographic disparities.

SARS-CoV-2 testing in North Carolina: Racial, ethnic, and geographic disparities.
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DOI:
10.1016/j.healthplace.2021.102576
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发表时间:
2021-05
期刊:
影响因子:
4.8
通讯作者:
Boyce RM
Boyce RM
中科院分区:
医学2区
文献类型:
--
作者:
Brandt K;Goel V;Keeler C;Bell GJ;Aiello AE;Corbie-Smith G;Wilson E;Fleischauer A;Emch M;Boyce RM

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对北卡罗来纳州 COVID-19 大流行前三个月的 SARS-CoV-2 检测数据进行了分析,以确定身份交叉轴之间是否存在差异,包括种族、拉丁裔、年龄、城乡居住地以及医疗服务匮乏地区的居住地。人口统计和居住数据被用来分别重建种族群体和城乡人口的检测指标模式(包括人均检测数、人均阳性检测数和检测阳性率(检测充分的指标))。在整个样本中,13.1%(295,642 例中的 38,750 例)检测呈阳性。在种族族裔群体中,非拉丁裔 (NL) 白人的所有测试结果呈阳性的比例为 11.5%,NL 黑人为 22.0%,拉丁裔为 66.5%。居住在农村地区的所有种族群体的检测阳性率均较高。这些结果表明,在 COVID-19 大流行的前三个月,北卡罗来纳州获得 COVID-19 检测的机会在不同种族群体中分布并不均匀,特别是在拉丁裔、北卡罗来纳州黑人和其他历史上被边缘化的人群中,而且这些群体中因性别、年龄、城乡状况和居住在医疗服务不足地区而存在进一步的差异。
SARS-CoV-2 testing data in North Carolina during the first three months of the state's COVID-19 pandemic were analyzed to determine if there were disparities among intersecting axes of identity including race, Latinx ethnicity, age, urban-rural residence, and residence in a medically underserved area. Demographic and residential data were used to reconstruct patterns of testing metrics (including tests per capita, positive tests per capita, and test positivity rate which is an indicator of sufficient testing) across race-ethnicity groups and urban-rural populations separately. Across the entire sample, 13.1% (38,750 of 295,642) of tests were positive. Within racial-ethnic groups, 11.5% of all tests were positive among non-Latinx (NL) Whites, 22.0% for NL Blacks, and 66.5% for people of Latinx ethnicity. The test positivity rate was higher among people living in rural areas across all racial-ethnic groups. These results suggest that in the first three months of the COVID-19 pandemic, access to COVID-19 testing in North Carolina was not evenly distributed across racial-ethnic groups, especially in Latinx, NL Black and other historically marginalized populations, and further disparities existed within these groups by gender, age, urban-rural status, and residence in a medically underserved area.
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