ArticleInternational journal of environmental research and public health2021
Participatory Approaches to Addressing Missing COVID-19 Race and Ethnicity Data.
Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 15 citations in OpenAlex.
- Counting Demographics: Patient Trust in the Era of Deportation.Journal of immigrant and minority health · 2026Article
- Fairness Correction in COVID-19 Predictive Models Using Demographic Optimization: Algorithm Development and Validation Study.Online journal of public health informatics · 2026Article
- Making Oneself "Fit": Community Perspectives on Disaggregated Race and Ethnicity Data Collection and Reporting in Healthcare Settings.Journal of racial and ethnic health disparities · 2025Article
- Article
- Ethnic inequalities in positive SARS-CoV-2 tests, infection prognosis, COVID-19 hospitalisations and deaths: analysis of 2 years of a record linked national cohort study in Scotland.Journal of epidemiology and community health · 2023Article
- Anti-Asian Attitudes in the Context of the COVID-19 Pandemic: an Exploratory Study.Journal of racial and ethnic health disparities · 2023Article
- Article
- Modeling the Potential Impact of Missing Race and Ethnicity Data in Infectious Disease Surveillance Systems on Disparity Measures: Scenario Analysis of Different Imputation Strategies.JMIR public health and surveillance · 2022Article
- The Mutually Reinforcing Cycle Of Poor Data Quality And Racialized Stereotypes That Shapes Asian American Health.Health affairs (Project Hope) · 2022Article
- Health Disparity Measurement Among Asian American, Native Hawaiian, and Pacific Islander Populations Across the United States.Health equity · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.