Indigenous Peoples in the United States have been experiencing disproportionate impacts of COVID-19. American Indian and Alaska Native persons are more likely to be infected, experience complications, and die from coronavirus. Evidence suggests that Indigenous persons have 3.5 times the incidence rate of non-Hispanic/Latinx whites. Unfortunately, this is likely a gross underestimate because of a lack of reliable and accurate COVID-19 data for American Indian and Alaska Native populations. Multiple factors contribute to poor data quality including the lack of Indigenous representation in the data and rampant racial misclassification at both the individual and group levels. The current pandemic has shed light on multiple pre-existing issues related to Indigenous data sovereignty in data collection and management. We discuss the importance of centring Indigenous data sovereignty in the systemic efforts to increase COVID-19 data availability and quality. The federal and state governments must support and promote Tribes’ rights to access data. Federal and state governments should also focus on bolstering their data availability and quality for aggregated data on AIAN populations and for providing disaggregated Tribal data to Tribes. Given the pivotal moment in the United States with ongoing and parallel pandemics of coronavirus and racism, we urge demographers and population scientists to reflect on the role of structural racism in data, data collection and analysis.

美国的土著人民一直在经历 COVID-19 的不成比例的影响。美洲印第安人和阿拉斯加原住民更有可能被感染、出现并发症并死于冠状病毒。有证据表明，土著人的发病率是非西班牙裔/拉丁裔白人的 3.5 倍。不幸的是，由于缺乏针对美洲印第安人和阿拉斯加原住民的可靠和准确的 COVID-19 数据，这可能被严重低估了。多种因素导致数据质量不佳，包括数据中缺乏土著代表以及个人和群体层面上猖獗的种族错误分类。当前的大流行揭示了与数据收集和管理中的土著数据主权相关的多个预先存在的问题。我们讨论了在提高 COVID-19 数据可用性和质量的系统性努力中以土著数据主权为中心的重要性。联邦和州政府必须支持和促进部落访问数据的权利。联邦和州政府还应专注于提高其数据可用性和质量关于 AIAN 人口的汇总数据，并用于向部落提供分类的部落数据。鉴于美国正处于冠状病毒和种族主义持续和平行流行的关键时刻，我们敦促人口统计学家和人口科学家反思结构性种族主义在数据、数据收集和分析中的作用。