Is COVID-19 an Equal Opportunity Disease?

Understanding COVID-19 Health Disparities: Who Is Most at Risk and Why

Is COVID-19 an equal opportunity disease?

The short answer is no. COVID-19 health disparities show that some communities face significantly higher risks than others. Data suggest that older people are more affected than younger people, men more than women,¹ and people of color more than white people.

COVID-19 cases and deaths fall unevenly across racial and ethnic groups. Cases are disproportionately high among Black, Latino, and multiracial populations relative to their share of the U.S. population, while rates are lower for white, Asian, and non-Latino populations. A similar pattern appears for deaths.

COVID-19 Cases and Deaths by Race and Ethnicity, Relative to U.S. Population Share.²ᐟ³ᐟ⁴ Some source charts use "Hispanic" or "Hispanic/Latino" as reported in the data; in the text we use "Latino" for populations broadly, while retaining the original chart labels for accuracy.

The chart above shows that COVID-19 cases (in orange) are disproportionately high among Black, Latino, and multiracial populations relative to their share of the U.S. population. In contrast, case rates are lower for white, Asian, and non-Latino populations. A similar pattern appears for deaths (in gray).

Why does this disparity exist? Part of the answer lies in unequal levels of exposure, susceptibility to the virus, and access to health care. It also reflects a legacy of structural inequities—economic, environmental, and systemic—that have increased underlying health conditions in some communities, raising vulnerability to COVID-19 and other diseases.

This crisis offers a moment to reexamine how we invest in public health. It highlights the need for more targeted, equitable strategies to prevent and respond to infectious disease. The following sections explore these themes through the lens of the COVID-19 pandemic.

1. Exposure at Home. An infectious disease moves from person to person when we are exposed to each other. Factors that increase exposure in the home include:

• Large numbers of people in the household

• No access to a vehicle

• Living in an apartment building

• Living in an urban area

• Presence of children or unavailability of daycare

Racial disparities in each of these factors favor increased transmission among people of color. For example, at 42 percent, a higher proportion of Black people live in urban areas, compared with just 20 percent of white people. And the number of persons per household for Latinos is 3.22, compared to 2.52 for all populations.

2. Exposure Related to Employment. Factors that make it harder to stay home—and therefore raise workplace exposure—include jobs that:

• Offer no option to work from home

• Involve public exposure

• Provide no paid sick leave

• Allow little ability to take time off

• Require a long commute on public transit

For example, consider some of the industries hardest hit by coronavirus outbreaks. Frontline workers—including grocery store clerks, nurses, cleaners, warehouse workers, and bus drivers—are over-represented by people of color and women.⁵ Of health care workers who have contracted coronavirus, 21 percent were Black and 73 percent were women.⁶ In the direct care industry, Black Americans make up nearly 30 percent of personal care aides, home health aides, and nursing assistants.⁷ In meat processing, 27 percent of workers are Black and 47 percent are Latino.⁸

3. Susceptibility: Socioeconomic Status. Income, employment, education level, and poverty are also predictors of lower health status. The federal government uses the Social Vulnerability Index (SVI)⁹ to assess which populations will be most vulnerable in times of disaster and disease outbreaks. The index comprises 15 metrics grouped into housing and transportation (including access to a vehicle); minority status and language; household composition, including elderly and disabled populations; and socioeconomic status, including the percent below poverty, employment, and income. Many of these metrics are also correlated with race.

Poverty Rate by Race and Ethnicity.¹⁰ Black Americans, Latinos, and American Indian/Alaska Natives have higher shares of people below the poverty level.

Evidence suggests that social distancing is more difficult for lower-income workers: cell phone data show that users from higher-income areas consistently decreased movement more than those from lower-income zip codes.¹¹

4. Susceptibility: Underlying Conditions. COVID-19 infection and death are clearly aggravated by underlying health conditions. Among people hospitalized, over 57 percent also had hypertension, 50 percent were obese, 41 percent had metabolic disease, and 31 percent had cardiovascular disease. Over 90 percent had at least one of these conditions. Looking at hypertension alone, men more than women, older people more than younger, Black people more than white, and poorer populations more than richer are all more susceptible to COVID-19.¹²

Prevalence of Hypertension by Demographic Characteristic.¹³

5. Susceptibility and Severity: Access to Health Care. The same vulnerable groups tend to have lower average rates of insurance coverage. Compared to about 11 percent of the U.S. population overall,¹⁴ the uninsured rate is 12.2 percent for men and 9.9 percent for women. Low-income groups have even less coverage, with 20.2 percent of those in households earning less than $35,000 reporting no insurance. Black Americans have an uninsured rate of 12.2 percent, compared to 10.9 percent for white Americans.

Another factor that affects access to care—even for the insured—is cost. When asked whether they had ever foregone or delayed health care due to cost, 4.7 percent said they had foregone care, and 7.2 percent had delayed a provider visit. These disparities are relevant to the COVID-19 outbreak because they may influence the outcome of the disease. Some researchers have raised concerns about patterns of testing, and how Black and brown people may not be receiving testing at the same rates as white people.¹⁵

6. What Else May Be Causing the Disparities? Despite the many variables that illuminate the root causes, much research shows we still don't fully understand these disparities. Numerous studies find that they persist across racial lines even after correcting for income, education, gender, age, and health behavior such as smoking, diet, physical activity, and access to health care.¹⁶ It may come down to cumulative risk factors not yet explained by anything better than race. Recent research has called for a better approach to understanding cumulative risk, especially with respect to respiratory ailments and susceptibility to air pollutants.¹⁷

No discussion of health inequity in the U.S. would be complete without reference to Dr. Robert Bullard, thought of as the father of the environmental justice movement. His seminal 1987 research¹⁸ addressed health risks and exposure to hazardous waste in the South. In 2007, Bullard and others revisited the work and found that even after 20 years, the neighborhoods within three kilometers of the nation's 413 commercial hazardous waste facilities were 56 percent people of color, whereas the rest of the country was just 30 percent.¹⁹

7. International Implications. The concerns above show how COVID-19 may disproportionately affect populations based on income, housing, employment, age, race, and access to health care in the U.S. Translating this to the broader international situation is not encouraging, since many countries have lower incomes, inadequate health care facilities, less capacity to shelter in place, and worse underlying health conditions. In addition, the current disruption to global food supplies presents the risk of severe hunger on top of the pandemic.

8. Poor Health Outcomes for Some Mean Greater Risk for All. The CDC's Global Health Security Agenda recognizes the need to support an interconnected global network to "limit the spread of infectious disease outbreaks in humans and animals, mitigate human suffering and the loss of human life, and reduce economic impact."²⁰ This pandemic underscores the need for a more targeted response to the populations where the disease is most likely to flourish. The point is summarized well in a 2014 article from Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science:

"Historical accounts of influenza pandemics and contemporary reports on infectious diseases clearly demonstrate that poverty, inequality, and social determinants of health create conditions for the transmission of infectious diseases, and existing health disparities or inequalities can further contribute to unequal burdens of morbidity and mortality." ²¹

Despite all of this evidence, the virus (a biochemical phenomenon) may be color-blind, age-blind, and sex-blind—an equal opportunity disease. But in economics, the risk of an event is made up of two factors: the probability of the event and its consequences. Different demographic groups have greater exposure to the virus, which increases the probability that they contract it. The consequences also vary depending on access to health care and underlying conditions. So while the virus may blindly seek its human hosts, different people face different levels of risk. Ultimately, understanding the complex, overlapping demographics of COVID-19 risk is essential to mitigating human suffering, loss of life, and economic damage.

Acknowledgments Greene Economics thanks Dr. Deborah McGrath, of the University of the South; Max Kunetz, of the University of Washington; and Beth Umland, of Mercer, Inc., for their thoughtful reviews and comments.

[References]

1. New York City Department of Health, COVID-19 Data. https://www1.nyc.gov/site/doh/covid/covid-19-data.page — data downloaded May 2, 2020.

2. National Center for Health Statistics, 2020. Provisional Death Counts for Coronavirus Disease (COVID-19): Weekly State-Specific Data Updates, updated April 28, 2020. https://data.cdc.gov/NCHS/Provisional-Death-Counts-for-Coronavirus-Disease-C/pj7m-y5uh

3. CDC, Demographic Characteristics of COVID-19 Patients in the U.S. https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html — last accessed May 2, 2020.

4. U.S. Census Bureau, QuickFacts. https://www.census.gov/quickfacts/fact/table/US/IPE120218 — last accessed May 2, 2020.

5. Rho, Hye Jin, Hayley Brown, and Shawn Fremstad, 2020. A Basic Demographic Profile of Workers in Frontline Industries, Center for Economic and Policy Research, April. https://cepr.net/wp-content/uploads/2020/04/2020-04-Frontline-Workers.pdf

6. Morbidity and Mortality Weekly Report, Vol. 69(15), April 17, 2020. "Characteristics of Health Care Personnel with COVID-19—United States, February 12–April 9, 2020."

7. Campbell, Stephen, 2018. Racial Disparities in the Direct Care Workforce: Spotlight on Black/African American Workers, PHI, February. https://phinational.org/wp-content/uploads/2018/02/Black-Direct-Care-Workers-PHI-2018.pdf

8. Rural Migration News, 2012, Vol. 18(2). "Race/Ethnicity of Food and Meat Workers, Percent Shares, 2000–2010." https://migration.ucdavis.edu/rmn/more.php?id=1691

9. CDC/ATSDR Social Vulnerability Index. https://healthdata.gov/dataset/cdc-social-vulnerability-index-svi

10. Kaiser Family Foundation, Poverty Rate by Race/Ethnicity, based on the Census Bureau's American Community Survey, 2008–2018. https://www.kff.org/other/state-indicator/poverty-rate-by-raceethnicity/

11. New York Times, 2020. "Location Data Says It All: Staying at Home During Coronavirus Is a Luxury," by Jennifer Valentino-DeVries, Denise Lu, and Gabriel J.X. Dance, April 3. https://www.nytimes.com/interactive/2020/04/03/us/coronavirus-stay-home-rich-poor.html

12. Summary Health Statistics, National Health Interview Survey, 2018, Table A-1a. https://www.cdc.gov/nchs/nhis/shs/tables.htm

13. Summary Health Statistics, National Health Interview Survey, 2018, Table A-1a. https://www.cdc.gov/nchs/nhis/shs/tables.htm

14. Summary Health Statistics, National Health Interview Survey, 2018, Table P-11a. https://www.cdc.gov/nchs/nhis/shs/tables.htm

15. Curtis, Alyssa, 2020. "Black Communities Are Being Tested for Coronavirus at a Disproportionate Rate," April 1. https://blavity.com/black-communities-are-being-tested-for-coronavirus-at-a-disproportionate-rate

16. Williams, David R., Selina Mohammed, Jacinta Leavell, and Chiquita Collins, 2010. "Race, Socioeconomic Status and Health: Complexities, Ongoing Challenges and Research Opportunities," Annals of the New York Academy of Sciences, February; 1186: 69–101.

17. Lewis, Ari S., Sonja N. Sax, Susan C. Wason, and Sharan L. Campleman, 2011. "Non-Chemical Stressors and Cumulative Risk Assessment: An Overview of Current Initiatives and Potential Air Pollutant Interactions," International Journal of Environmental Research and Public Health, 8, 2020–2073.

18. Bullard, R.D., and B.H. Wright, 1987. "Environmentalism and the Politics of Equity: Emergent Trends in the Black Community," Mid-America Review of Sociology, Vol. 12, No. 2 (Winter): 21–38. http://kuscholarworks.ku.edu/dspace/bitstream/1808/5017/1/MARSV12N2A2.pdf

19. Bullard, Robert D., Paul Mohai, Robin Saha, and Beverly Wright, 2008. "Toxic Wastes and Race at Twenty: Why Race Still Matters After All of These Years," Lewis & Clark Environmental Law Journal 38(2).

20. U.S. Department of Health and Human Services, Global Health Security: Vision and Overarching Target. Accessed May 2, 2020.

21. Quinn, Sandra Crouse, and Supriya Kumar, 2014. "Health Inequalities and Infectious Disease Epidemics: A Challenge for Global Health Security," Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science, Vol. 12, No. 5.