Adequacy of Existing Surveillance Systems to Monitor Racism, Social Stigma and COVID Inequities: A Detailed Assessment and Recommendations.

The populations impacted most by COVID are also impacted by racism and related social stigma; however, traditional surveillance tools may not capture the intersectionality of these relationships. We conducted a detailed assessment of diverse surveillance systems and databases to identify characteristics, constraints and best practices that might inform the development of a novel COVID surveillance system that achieves these aims. We used subject area expertise, an expert panel and CDC guidance to generate an initial list of N > 50 existing surveillance systems as of 29 October 2020, and systematically excluded those not advancing the project aims. This yielded a final reduced group (n = 10) of COVID surveillance systems (n = 3), other public health systems (4) and systems tracking racism and/or social stigma (n = 3, which we evaluated by using CDC evaluation criteria and Critical Race Theory. Overall, the most important contribution of COVID-19 surveillance systems is their real-time (e.g., daily) or near-real-time (e.g., weekly) reporting; however, they are severely constrained by the lack of complete data on race/ethnicity, making it difficult to monitor racial/ethnic inequities. Other public health systems have validated measures of psychosocial and behavioral factors and some racism or stigma-related factors but lack the timeliness needed in a pandemic. Systems that monitor racism report historical data on, for instance, hate crimes, but do not capture current patterns, and it is unclear how representativeness the findings are. Though existing surveillance systems offer important strengths for monitoring health conditions or racism and related stigma, new surveillance strategies are needed to monitor their intersecting relationships more rigorously.

Tools to Promote Equity and Best Practices

This is the second volume of a two-volume special issue of the American Indian Culture and Research Journal dedicated to the indirect impact of COVID-19 on Indigenous Peoples. The first, 44.2, reports on COVID-19's extensive impact on Indigenous Peoples and the resulting variety of responses at community and local levels. This second volume, 44.3, provides specific research and insights for improving reporting, identification, and prevention of COVID-19 cases and deaths. Several contributors to this issue respond to the urgent need to ensure, for small populations, and Indigenous Peoples in particular, that data collection provides detailed information on race and tribal nation identifiers. Like this lack of data disaggregation, data inaccuracy also impedes understanding of the impact of a pandemic. Other researchers find that a hallmark of this pandemic-the shift from in-person to virtual interactions in many aspects of life-has clarified that innovative telehealth and virtual methods already underway for Indigenous Peoples may represent the frontiers of better health care, access, and service. "Moving Forward: No Scientific Integrity without an Acknowledgment of Past Wrongs," a commentary emphasizing the necessary actions the US government must take if progress is to be made, concludes this special issue.

Identifying Disparities in Health Outcomes and Mortality for American Indian and Alaska Native Populations Using Tribally Disaggregated Vital Statistics and Health Survey Data

Objectives. To determine the impact of disaggregated mortality and health surveillance data on the ability to identify health disparities for American Indian and Alaska Native (AI/AN) subpopulations. Methods. We conducted a systematic review of reporting categories for AI/AN decedents on official death certificates for all 50 US states. Using public data from the 2017-2018 California Health Interview Survey (CHIS), we conducted bivariate and multivariate analyses to assess disparities in health conditions and outcomes for tribally enrolled and non-tribally enrolled AI/AN persons compared with non-Hispanic Whites. Results. There was no standard for the collection of tribal enrollment data or AI/AN race on death certificates across all 50 states. There were stark differences in the incidence and prevalence of various health risk factors and chronic diseases for the tribally enrolled AI/AN subpopulation, non-tribally enrolled AI/AN subpopulation, and non-Hispanic White comparison group. Conclusions. The collection of tribal enrollment data in vital statistics and health surveillance systems is necessary to identify and respond to health disparities among AI/AN subpopulations. These efforts must be conducted in partnership with tribal nations and consider Indigenous data sovereignty. (AmJ Public Health. 111 (S2):S126-S132. https://doi.org/10.2105/AJPH.2021.306427)

Indigenous Peoples' Data During COVID-19: From External to Internal.

Global disease trackers quantifying the size, spread, and distribution of COVID-19 illustrate the power of data during the pandemic. Data are required for decision-making, planning, mitigation, surveillance, and monitoring the equity of responses. There are dual concerns about the availability and suppression of COVID-19 data; due to historic and ongoing racism and exclusion, publicly available data can be both beneficial and harmful. Systemic policies related to genocide and racism, and historic and ongoing marginalization, have led to limitations in quality, quantity, access, and use of Indigenous Peoples' COVID-19 data. Governments, non-profits, researchers, and other institutions must collaborate with Indigenous Peoples on their own terms to improve access to and use of data for effective public health responses to COVID-19.