Department of Humanities and Sciences, Stanford University, Stanford, California, USA.
Department of Surgery, Stanford University School of Medicine, Stanford, California, USA.
Eur J Clin Invest. 2021 Nov;51(11):e13669. doi: 10.1111/eci.13669. Epub 2021 Aug 27.
In 2020, early U.S. COVID-19 testing sites offered diagnostic capacity to patients and were important sources of epidemiological data about the spread of the novel pandemic disease. However, little research has comprehensively described American testing sites' distribution by race/ethnicity and sought to identify any relation to known disparities in COVID-19 outcomes.
Locations of U.S. COVID-19 testing sites were gathered from 16 April to 28 May 2020. Geographic testing disparities were evaluated with comparisons of the demographic makeup of zip codes around each testing site versus Monte Carlo simulations, aggregated to statewide and nationwide levels. State testing disparities were compared with statewide disparities in mortality observed one to 3 weeks later using multivariable regression, controlling for confounding disparities and characteristics.
Nationwide, COVID-19 testing sites geographically overrepresented White residents on 7 May, underrepresented Hispanic residents on 16 April, 7 May and 28 May and overrepresented Black residents on 28 May compared with random distribution within counties, with new sites added over time exhibiting inconsistent disparities for Black and Hispanic populations. For every 1 percentage point increase in underrepresentation of Hispanic populations in zip codes with testing, mortality among the state's Hispanic population was 1.04 percentage points more over-representative (SE = 0.415, p = .01).
American testing sites were not distributed equitably by race during this analysis, often underrepresenting minority populations who bear a disproportionate burden of COVID-19 cases and deaths. With an easy-to-implement measure of geographic disparity, these results provide empirical support for the consideration of access when distributing preventive resources.
2020 年,美国早期的 COVID-19 检测点为患者提供了诊断能力,是有关新型大流行疾病传播的流行病学数据的重要来源。然而,几乎没有研究全面描述了美国检测点的种族/族裔分布,并试图确定与 COVID-19 结果已知差异的任何关系。
从 2020 年 4 月 16 日至 5 月 28 日收集了美国 COVID-19 检测点的位置。通过将每个检测点周围邮政编码的人口统计数据与蒙特卡罗模拟进行比较,评估了地理检测差异,并将其汇总到州和全国各级。使用多变量回归,在控制混杂差异和特征的情况下,将州检测差异与 1 至 3 周后观察到的全州死亡率差异进行了比较。
在全国范围内,与各县内随机分布相比,COVID-19 检测点在 5 月 7 日在地理上过度代表了白人居民,在 4 月 16 日、5 月 7 日和 5 月 28 日过度代表了西班牙裔居民,5 月 28 日过度代表了黑人居民,随着时间的推移,新增加的检测点对黑人和西班牙裔人口的差异表现出不一致。在有检测的邮政编码中,西班牙裔人口的代表性每降低 1 个百分点,该州西班牙裔人口的死亡率就会增加 1.04 个百分点(SE=0.415,p=0.01)。
在本分析中,美国的检测点在种族分布上并不均衡,经常代表少数族裔,而少数族裔承担着不成比例的 COVID-19 病例和死亡负担。这些结果通过一个易于实施的地理差异衡量标准,为在分配预防资源时考虑获取途径提供了经验支持。