Participatory Approaches to Addressing Missing COVID-19 Race and Ethnicity Data

Abstract

Varying dimensions of social, environmental, and economic vulnerability can lead to drastically different health outcomes. The novel coronavirus (SARS-CoV-19) pandemic exposes how the intersection of these vulnerabilities with individual behavior, healthcare access, and pre-existing conditions can lead to disproportionate risks of morbidity and mortality from the virus-induced illness, COVID-19. The available data shows that those who are black, indigenous, and people of color (BIPOC) bear the brunt of this risk; however, missing data on race/ethnicity from federal, state, and local agencies impedes nuanced understanding of health disparities. In this commentary, we summarize the link between racism and COVID-19 disparities and the extent of missing data on race/ethnicity in critical COVID-19 reporting. In addition, we provide an overview of the current literature on missing demographic data in the US and hypothesize how racism contributes to nonresponse in health reporting broadly. Finally, we argue that health departments and healthcare systems must engage communities of color to co-develop race/ethnicity data collection processes as part of a comprehensive strategy for achieving health equity.

Modeling the Potential Impact of Missing Race and Ethnicity Data in Infectious Disease Surveillance Systems on Disparity Measures: Scenario Analysis of Different Imputation Strategies

“…Although standardized recommendations exist for collecting race and ethnicity information [ 27 ], demographic data collection is incomplete and inconsistent across jurisdictions and health care systems [ 28 , 29 ]. Incomplete collection of race and ethnicity information might result from individuals not disclosing information about their race and ethnicity because of mistrust or if they are provided with limited response options that do not match their self-identity [ 30 ]. Local health agencies’ efforts to follow up on reported diagnoses to collect additional demographic information can be costly and inefficient [ 31 ].…”

“…A past assessment of race and ethnicity information across different disease registries found that inconsistencies occurred more frequently among Hispanic populations and populations categorized as being in an “other” racial and ethnic group, suggesting that a more granular coding system for collecting demographic information might improve data completeness [ 32 ]. Furthermore, requiring race and ethnicity information in the initial data collection and simultaneously working with communities to improve surveillance instruments has been previously recommended to reduce the incompleteness of race and ethnicity information [ 30 ].…”

Anti-Asian Attitudes in the Context of the COVID-19 Pandemic: an Exploratory Study

“…Education on health disparities still over-emphasizes individual factors rather than structural ones, both with regard to medical education [ 22 ] and in American culture more broadly [ 21 ]. Furthermore, social groups that are impacted by structural health disparities are currently less likely to be represented in research; for example, several data on COVID-19 outcomes and vaccine administration are already known to be missing race/ethnicity identifiers, thus obscuring the extent of such disparities [ 36 ]. Education, media coverage, and research are all clear areas of improvement that might lead to greater structural literacy of the public, and thus a potential reduction in anti-Asian and racist attitudes.…”

Health Disparity Measurement Among Asian American, Native Hawaiian, and Pacific Islander Populations Across the United States

“…Still, data can be rolled up into the more familiar categories that include AANHPIs 20 and these standards are not required for state reporting. 24 …”

“…Even when numbers are small, state and local jurisdictions can benefit from counting distinct subgroups whose risk for health disparities may vary. 24 …”