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Complete data from COVID-19 testing sites in low-income areas, such as this one at Interbay Village in Seattle, are crucial to fighting the pandemic. 


‘Huge hole’ in COVID-19 testing data makes it harder to study racial disparities

Science's COVID-19 reporting is supported by the Pulitzer Center and the Heising-Simons Foundation.

At a virtual meeting last month, cardiologist Garth Graham shared data that shine a narrow flashlight beam into a vast, shadowy crisis. As vice president of community health at CVS Health, he oversees nine centers offering free, rapid COVID-19 tests in low-income neighborhoods with high proportions of racial and ethnic minorities. From those sites, the view of the pandemic is dire. Roughly 35% of tests performed at a center in Phoenix and 30% in Atlanta had come back positive as of 23 June, he said. Nationwide, only 8.8% of tests were positive last week, according to the U.S. Centers for Disease Control and Prevention (CDC), although last week Arizona reported a 21% positive rate.

The CVS test results suggest that “the pandemic is unfolding very differently in Black and brown communities,” Graham said.

“Those were extraordinary numbers,” agrees Gary Gibbons, director of the U.S. National Heart, Lung, and Blood Institute, who also spoke at the meeting—a workshop on COVID-19 and Black communities organized by the National Academies of Science, Engineering, and Medicine (NASEM). The results are “a yellow flag that those areas ought to be targeted for more intense testing and tracing.”

To understand which neighborhoods and communities face raging outbreaks and why, researchers need demographic information both on who gets tested and who tests positive, including their race and ethnicity. But even as the U.S. testing infrastructure improves, testing remains sparse in many low-income and minority neighborhoods, and race and ethnicity information is missing for about half of reported COVID-19 cases nationwide.

“It’s a huge hole in my research,” says Sarita Shah, an epidemiologist at Emory University who is studying racial disparities in rates of severe COVID-19.

Hospital and death records show that Black people, Latinos, and Native Americans are disproportionately suffering and dying from severe disease; nationwide, Black people are dying at 2.5 times the rate of whites. But without knowing the race of everyone tested, Shah can’t say whether high death rates among Black people in the United States are driven primarily by more exposure and infection, diagnosis at a later stage of disease, or a higher risk of severe illness once infected.

Understanding these drivers might inform solutions, whether boosting accessibility to testing, improving public health messaging in hard-hit communities, or aiming for earlier diagnosis and more supportive care. “The lack of data speaks a lot to whose lives we value and whose lives we don’t,” says Richard Besser, president and CEO of the Robert Wood Johnson Foundation, and another presenter at the NASEM meeting.

Some of the missing testing data might be on the way. Federal guidance released last month will require laboratories to report race and ethnicity, along with age, sex, and ZIP code, to the government alongside COVID-19 test results starting 1 August. “Those data should have been collected from the start,” says Nancy Krieger, a social epidemiologist at the Harvard T.H. Chan School of Public Health. She notes that the form used to report COVID-19 cases to CDC already has fields for race and ethnicity, but they’re frequently left blank. It’s not clear whether and how the new mandate will be enforced, she says.

Even when test sites do collect detailed demographic information, barriers to testing in vulnerable communities can be high, Besser notes. Low-income people who lack health insurance may fear unexpected fees from testing; they may also worry about losing income if they test positive and can’t go to work.

And test sites may simply be scarce in their communities. Data from New York City suggest that early in the pandemic, testing failed to reach those who needed it most. Among the city’s 177 ZIP codes, the number of tests performed between 2 March and 6 April rose with the percentage of white residents in a ZIP code, while the proportion of positive tests decreased with white population, epidemiologist Emanuela Taioli and colleagues at the Icahn School of Medicine at Mount Sinai reported on 25 June in the American Journal of Preventive Medicine (AJPM).

In unpublished follow-up analyses, Taioli has seen progress as the city set up more test sites in underserved areas. By mid-May, Taioli says, testing rates didn’t correlate with the racial makeup of a ZIP code. But when her team looked to expand its analysis of testing equity beyond New York, they learned that many states don’t publish how many people they test—just how many test positive. That makes it harder to know whether some groups are undercounted.

Many states now have efforts underway to bring mobile testing sites to neglected neighborhoods. And a National Institutes of Health initiative called RADx-UP will devote $300 million in its first phase to setting up and coordinating data collection across test sites in underserved and minority communities.

Other teams are finding ways to work around the data gaps, combining census data with whatever location data are available for positive cases. On 18 June, a team at Emory released a “health equity interactive dashboard” that displays each U.S. county’s case and death counts alongside existing government records, including the racial and ethnic makeup of the county, how many residents are uninsured or live in poverty, and how many are obese or have diabetes. Nationwide, the dashboard shows a strong correlation between African American populations and COVID-19 deaths; and between Latino populations and confirmed cases, says Shivani Patel, an Emory epidemiologist who leads the project.

The reasons for the disease’s uneven burden trace back to systemic racism, which creates a web of disadvantages for Black and brown people. They face higher rates of diabetes, heart disease, and other conditions that worsen the COVID-19 prognosis. People of color are also more likely to live in crowded neighborhoods and have low-wage, essential jobs where social distancing is difficult or impossible.

Vulnerable communities aren’t all vulnerable in the same way, Ibraheem Karaye, an epidemiologist at the University of Delaware, found in his own county-by-county analysis. In a study published 26 June in AJPM, he and University of Delaware epidemiologist Jennifer Horney compared each U.S. county’s COVID-19 case count with its score on CDC’s 15-factor social vulnerability index. In Northeastern states, residents’ minority status and language best explained infection rates. In Gulf Coast states, in contrast, factors related to housing and transportation—such as lacking a vehicle or living in multiunit structures—predicted infections better than ethnic factors did. Karaye doesn’t know why those differences exist, but says they hold clues about the kind of help communities in these regions might need.

Still, mashups of census data and test results can only go so far. Without knowing the race of the individuals tested, Patel notes, she can’t say whether it’s really the Latinos getting hit hardest in a majority-Latino area. Nor can she capture a situation where African Americans living in a majority-white county are sickened disproportionately.

Shah, who has been volunteering with Fulton County’s health department, sees the data collection problem firsthand. After doing nasal swabs at a drive-up testing site, she calls those who test positive to fill in personal information, including race. Even after multiple attempts, the team reaches only about half of these people. Shah says she’d love to note a person’s race when they’re sitting in front of her at the test site, but so far, the forms provided by labs that process the samples don’t have a place to note it. “I wish it was something more complex than that,” she says, “but it’s not.”