Racial and Ethnic Disparities in Incidence of SARS-CoV-2 Infection, 22 US States and DC, January 1–October 1, 2020

We examined disparities in cumulative incidence of severe acute respiratory syndrome coronavirus 2 by race/ethnicity, age, and sex in the United States during January 1–October 1, 2020. Hispanic/Latino and non-Hispanic Black, American Indian/Alaskan Native, and Native Hawaiian/other Pacific Islander persons had a substantially higher incidence of infection than non-Hispanic White persons.

accordance with applicable federal law and Centers for Disease Control and Prevention policy [45 Code of Federal Regulations part 46.102(l) (2)].
We found that most racial/ethnic minority groups had significantly higher cumulative incidence of SARS-CoV-2 than did White persons (Table). Cumulative incidence ranged from 874 (95% CI 865-884)/100,000 population in Asian persons to 2,860 (95% CI 2,850-2,869)/100,000 population in Hispanic persons. CIRs were significantly higher among Black (2.11), AIAN (2.43), NHOPI (2.88), and Hispanic persons (3.06) compared with White persons; the CIR was nominally but significantly different for multiple race (1.02) and Asian persons (0.93). Cumulative incidence for men compared with women, when adjusted for both race/ethnicity and age, was similar (p = 0.982; data not shown).
We found differences in infection rates by sex within various racial/ethnic and age groups (CIRs 0.64-1.30) (Figure 2; Appendix Table 2). Overall, cumulative incidence among men in all racial/ethnic groups was significantly lower than among women (CIRs 0.85-0.97), with an exception among Asian men (CIR 1.05). Men who were Black and >65 years of age, multiple race and 65-74 years of age, and Hispanic or White and 55-84 years of age had a higher cumulative incidence than women. Among NHOPI and AIAN persons, cumulative incidence was significantly lower than for White persons only for men 20-44 years of age.

Conclusions
Among >1.75 million persons with SARS-CoV-2 in 23 US jurisdictions during January 1-October 1, 2020, persons from most racial/ethnic minority groups had higher cumulative incidence than White persons. Hispanic persons had a 3.1-fold higher incidence and Black, AIAN, and NHOPI persons a >2-fold higher  incidence of SARS-CoV-2 than did White persons. Racial/ethnic disparities varied by age group. Sex differences in cumulative incidence within racial/ ethnic groups were less pronounced than disparities between racial/ethnic groups.
have rarely disaggregated NHOPI persons, preventing detection of disparities. Although previous studies have shown higher rates of severe COVID-19 illness among men, we observed lower infection rates among men overall (1,13).
Social determinants of health drive racial/ethnic disparities in disease incidence (3)(4)(5)(6)(7)(8). For example, members of some racial/ethnic groups are overrepresented in the essential workforce and more likely to live in multigenerational or high-density housing, increasing the risk for SARS-CoV-2 exposure (https:// www.cdc.gov/coronavirus/2019-ncov/community/ health-equity/racial-ethnic-disparities/index.html). Outbreaks in some occupational settings have had racial/ethnic disparities in infection (3,8). Employers, community organizations, healthcare systems, public health agencies, and governments can act to reduce racial/ethnic disparities in COVID-19 incidence by implementing flexible, nonpunitive leave policies (e.g., paid sick leave); equitable access to testing and screening programs, personal protective equipment, and vaccines; and policies that encourage physical distancing (14). In addition, public health officials can tailor COVID-19 prevention messaging to the languages and cultures of various racial/ethnic groups. Multisectoral partnerships could support COVID-19 mitigation strategies through initiatives that provide spaces for isolation or self-quarantine, safe transportation, free or reduced-cost broadband internet, and housing resources (14).
One limitation of this study is that underreporting to the Centers for Disease Control and Prevention database, which documented 78% of cases in selected jurisdictions, probably caused underestimates in calculated incidence. Second, selected jurisdictions comprise 31% of the US population; in these jurisdictions, NHOPI, White, AIAN, and multiple race persons are overrepresented and Asian, Hispanic, and Black persons underrepresented (Appendix Table 3). As a result, our findings are not nationally representative or generalizable. Third, we excluded persons of unknown race/ethnicity (24%) from incidence calculations. Among persons of unknown race/ethnicity, 33% specified race but not ethnicity; minority racial groups were overrepresented (Appendix Table 4). Fourth, cases among racial/ethnic minority groups might be underreported because of disparities in testing access (15). The third and fourth issues probably resulted in underestimation of racial/ethnic disparities. Finally, aggregation of NHOPI and Asian persons in >2 jurisdictions probably resulted in underestimating incidence among NHOPI persons and overestimating among Asian persons.
In summary, documenting population-based racial/ethnic disparities in SARS-CoV-2 infection rates and how disparities vary by age and sex informs the development and implementation of equitable policies and intervention strategies. Strategies should prioritize collection and analysis of data relating to health equity and focus on mitigating disproportionate risks of exposure related to social determinants of health.
Science wields many diff erent tools in the pursuit of public health. These tools can work together to capture a detailed picture of disease. However, many tools accomplish similar tasks, o� en leaving policymakers wondering, when it comes to disease surveillance, what is the best tool for the job?
Diff erent tests are currently used to diagnose Clostridioides diffi cile, a dangerous bacterium found in hospitals around the world. As rates of this infec� on surge globally, researchers need to be able to compare sta� s� cs from diff erent hospitals, regions, and countries.
In this EID podcast, Sarah Tschudin-Su� er, a professor of infec� ous disease epidemiology at the University Hospital -Basel in Switzerland, discusses using 2 tests for C. diffi cile infec� on in Europe.