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This episode from the podcast 99 Percent Invisible reflects on how the COVID-19 pandemic exposed the American public to a long-standing problem: the disjointed nature of the U.S. health system. Because state and local health departments largely operate independently and use their own data collection and analysis tools, health systems across the country lack standardized data definitions and systems. These inconsistencies made it nearly impossible to collect and analyze comprehensive, standardized data on COVID-19 cases, deaths, and vaccines administered amid the pandemic. Health experts featured on this episode believe that the pandemic made the need for an overhaul of America’s informatics system very apparent. When rebuilding this system, it’s important to focus on remedying existing inequalities in data collection and classification that in some cases render the health status of certain populations – think Native American communities and other communities of color – completely invisible in the data. By virtue of being small populations, it can be difficult for health departments to collect sufficient and/or statistically significant data on minority communities. Another issue discussed in this episode is the use of broad racial categories like “other,” “multiple races,” or even “Asian American,” which, if not disaggregated, obscures the health status of diverse populations who are grouped under the same category. Without comprehensive and inclusive health data, it’s difficult to identify disparities and implement policies and programming that promote social mobility and health equity.

This article discusses the resilience of Indigenous communities in the Arctic during the COVID-19 pandemic. Despite facing vulnerabilities such as limited access to healthcare and infrastructure, these communities had lower COVID-19 death rates compared to southern regions. The article highlights the importance of Indigenous health-care sovereignty and self-determination in controlling the spread of the virus. Indigenous-led decision-making, community-centered approaches, and cultural relevance played a crucial role in mitigating the impact of the pandemic. Recognizing and promoting Indigenous Peoples’ self-determination in healthcare is essential for developing sustainable health-care systems and addressing future health crises.

This review of state data collection and reporting practices during the COVID-19 pandemic found inconsistencies and gaps in data collected by race and ethnicity. Improved standardization across the U.S.–which may come in the form of a federally-operated centralized database–would address some of the concerns in data representation of all Americans.

This brief lists interventions to support state public health efforts to address rural disparities and racial discrimination. It emphasizes the importance of localized data on social determinants of health and improving systemic and structural underpinnings of racial disparities. Suggested interventions address data collection and workforce issues, including representativeness and paid family leave.

This article seeks to assess COVID-19 case and mortality rates in non-Hispanic American Indian and Alaska Natives (AI/AN) through an analysis of laboratory-reported COVID-19 data from January 22-July 3, 2020, for 23 U.S. states. The results show that AI/AN individuals are 3.5 times more likely to contract COVID-19 than White individuals, and more accurate race/ethnicity data must be reported by all states to more accurately represent this population.

This study uses COVID-19 death data by racial/ethnic group and age, along with US Census population data to explore variations in mortality risk by calculating age-specific mortality measures. The results found that minority groups such as non-Hispanic Black, Hispanic, and non-Hispanic American Indian or Alaska Native populations experience more COVID-19 mortality than White patients, but also experience more years of potential life lost due to racial/ethnic disparities.

This is an assessment of the association between hospitalization for illness from COVID-19 infection and chronic conditions among Medicare beneficiaries (MBs) with fee-for-service (FFS) claims by race and ethnicity for January 1–September 30, 2020. Racial/ethnic disparities in hospitalization rates persist among MBs with COVID-19, and associations of COVID-19 hospitalization with chronic conditions differ among racial/ethnic groups in the U.S.

This blog highlights how the Pennsylvania Department of Human Services is addressing algorithm bias as part of a larger strategy to improve equity across all of the agency’s programs and activities, which were recently detailed in the state’s comprehensive Racial Equity Report.

To help policymakers and other stakeholders identify opportunities to improve health equity in their states, SHADAC has produced a set of data resources for the 50 states and the District of Columbia. Using the Behavioral Risk Factor Surveillance System (BRFSS) Survey — combining the three most recent years of data (2018–2020) to improve our ability to develop reliable state-level estimates for smaller population subgroups — SHADAC created maps and charts showing how states compare to the U.S. average in measures of people’s self-reported physical and mental health, and how people’s physical and mental health varies depending on their race and ethnicity, level of income, and age within each state.

This study uses data from the COVID Tracking Project’s Racial Data Tracker, which aggregates state-level COVID-19 reporting and tracking databases to determine racial/ethnic trends of COVID-19 incidence and evaluate the racial/ethnic distribution of COVID-19 related mortality in the US. Results found that disparities are more apparent at the county and city level, and discusses the importance of transparent, local data in order to allow for greater precision in resource allocation and effective policy changes aimed at reducing disparities. The study includes choropleth maps of the results by state.