The health inequities exposed by COVID-19 underscored the importance of collecting race-stratified data to inform local policymakers. For the public health researchers trying to provide that, the pandemic also revealed some major pitfalls, especially about relying on open-source data. Information is almost never neutral: What gets collected, how it is analyzed, reported, contextualized, and used—all that reflects pre-existing assumptions and biases.

All of these became factors when RAND, the Black Equity Coalition (BEC), and Surgo Ventures collaborated on a tool to report on COVID-19 vulnerability and disparities using publicly-available data in Allegheny County, Pennsylvania. The goal was to help decision-makers identify geographic areas and racial/ethnic populations most at risk of infection and complications from the novel coronavirus.

Researchers can't measure demographic inequities without data on race and ethnicity that has been collected consistently and accurately. In early May 2020, as the BEC developed a data dashboard and identified racial disparities in COVID-19 outcomes, they had to scrape data from state data systems. They later advocated for the public availability of the Allegheny County Health Department dataset used for our tool. This early work to make county-level data disaggregated by race and geographic area available was critical to our collaborative's ability to draw granular, interactive insights and recommendations on vulnerability and equity in the county.

As a nation we are still far from universal reporting of COVID-19 testing and case rates by race/ethnicity. This reflects a more widespread problem of a lack of disaggregated data, which January 2021's Federal Executive Order On Advancing Racial Equity and Support for Underserved Communities Through the Federal Government aims to address for federal data sources.

Read the full article about equitable data on COVID-19 by Linnea Warren May, Jason Beery, Tiffany L. Gary-Webb, Evan D. Peet, Jared Kohler at RAND Corporation.