差距变得不可见：美国印第安人和阿拉斯加原住民群体的新冠疫情数据缺口
Disparities Made Invisible: Gaps in COVID-19 Data for American Indian and Alaska Native Populations.
作者信息
Skinner Alexandra, Raifman Julia, Ferrara Elizabeth, Raderman Will, Quandelacy Talia M
机构信息
Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, Massachusetts, USA.
Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado, USA.
出版信息
Health Equity. 2022 Mar 8;6(1):226-229. doi: 10.1089/heq.2021.0129. eCollection 2022.
INTRODUCTION
Complete COVID-19 data for American Indian/Alaska Native (AI/AN) populations are critical to equitable pandemic response.
METHODS
We used the COVID-19 U.S. State Policy database to document gaps in COVID-19 data reporting for AI/AN people.
RESULTS
Sixty-four percent of states do not report AI/AN data for at least one COVID-19 health metric: cases, hospitalizations, deaths, or vaccinations.
DISCUSSION
The lack of AI/AN-specific data masks the disproportionate burden of COVID-19 and presents challenges to COVID-19 prevention, policy implementation, and health equity.
CONCLUSIONS
Public-facing data disaggregated by race may facilitate rapid response COVID-19 research and policymaking to support AI/AN communities.
引言
美国印第安人/阿拉斯加原住民（AI/AN）群体的完整新冠病毒疾病（COVID-19）数据对于公平应对疫情至关重要。
方法
我们使用COVID-19美国州政策数据库记录AI/AN人群在COVID-19数据报告方面的差距。
结果
64%的州未报告至少一项COVID-19健康指标的AI/AN数据，这些指标包括病例、住院、死亡或疫苗接种情况。
讨论
缺乏特定于AI/AN群体的数据掩盖了COVID-19造成的不均衡负担，并给COVID-19预防、政策实施和健康公平带来挑战。
结论
按种族分类的公开数据可能有助于COVID-19的快速应对研究和政策制定，以支持AI/AN社区。
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