Multiple Imputation of Missing Race and Ethnicity in CDC COVID-19 Case-Level Surveillance Data.

The COVID-19 pandemic has resulted in a disproportionate burden on racial and ethnic minority groups, but incompleteness in surveillance data limits understanding of disparities. CDC's case-based surveillance system contains case-level information on most COVID-19 cases in the United States. Data analyzed in this paper contain COVID-19 cases with case-level information through September 25, 2020, which represent 70.9% of all COVID-19 cases reported to CDC during the period. Case-level surveillance data are used to investigate COVID-19 disparities by race/ethnicity, sex, and age. However, demographic information on race and ethnicity is missing for a substantial percentage of COVID-19 cases (e.g., 35.8% and 47.2% of cases analyzed were missing race and ethnicity information, respectively). Our goal in this study was to impute missing race and ethnicity to derive more accurate incidence and incidence rate ratio (IRR) estimates for different racial and ethnic groups, and evaluate the results from imputation compared to complete case analysis, which involves removing cases with missing race/ethnicity information from the analysis. Two multiple imputation (MI) models were developed. Model 1 imputes race using six binary race variables, and Model 2 imputes race as a composite multinomial variable. Our evaluation found that compared with complete case analysis, MI reduced biases and improved coverage on incidence and IRR estimates for all race/ethnicity groups, except for the Non-Hispanic Multiple/other group. Our research highlights the importance of supplementing complete case analysis with additional methods of analysis to better describe racial and ethnic disparities. When race and ethnicity data are missing, multiple imputation may provide more accurate incidence and IRR estimates to monitor these disparities in tandem with efforts to improve the collection of race and ethnicity information for pandemic surveillance.

Counties with High COVID-19 Incidence and Relatively Large Racial and Ethnic Minority Populations - United States, April 1-December 22, 2020.

Long-standing systemic social, economic, and environmental inequities in the United States have put many communities of color (racial and ethnic minority groups) at increased risk for exposure to and infection with SARS-CoV-2, the virus that causes COVID-19, as well as more severe COVID-19-related outcomes (1-3). Because race and ethnicity are missing for a proportion of reported COVID-19 cases, counties with substantial missing information often are excluded from analyses of disparities (4). Thus, as a complement to these case-based analyses, population-based studies can help direct public health interventions. Using data from the 50 states and the District of Columbia (DC), CDC identified counties where five racial and ethnic minority groups (Hispanic or Latino [Hispanic], non-Hispanic Black or African American [Black], non-Hispanic Asian [Asian], non-Hispanic American Indian or Alaska Native [AI/AN], and non-Hispanic Native Hawaiian or other Pacific Islander [NH/PI]) might have experienced high COVID-19 impact during April 1-December 22, 2020. These counties had high 2-week COVID-19 incidences (>100 new cases per 100,000 persons in the total population) and percentages of persons in five racial and ethnic groups that were larger than the national percentages (denoted as "large"). During April 1-14, a total of 359 (11.4%) of 3,142 U.S. counties reported high COVID-19 incidence, including 28.7% of counties with large percentages of Asian persons and 27.9% of counties with large percentages of Black persons. During August 5-18, high COVID-19 incidence was reported by 2,034 (64.7%) counties, including 92.4% of counties with large percentages of Black persons and 74.5% of counties with large percentages of Hispanic persons. During December 9-22, high COVID-19 incidence was reported by 3,114 (99.1%) counties, including >95% of those with large percentages of persons in each of the five racial and ethnic minority groups. The findings of this population-based analysis complement those of case-based analyses. In jurisdictions with substantial missing race and ethnicity information, this method could be applied to smaller geographic areas, to identify communities of color that might be experiencing high potential COVID-19 impact. As areas with high rates of new infection change over time, public health efforts can be tailored to the needs of communities of color as the pandemic evolves and integrated with longer-term plans to improve health equity.

Association of State-Issued Mask Mandates and Allowing On-Premises Restaurant Dining with County-Level COVID-19 Case and Death Growth Rates - United States, March 1-December 31, 2020.

CDC recommends a combination of evidence-based strategies to reduce transmission of SARS-CoV-2, the virus that causes COVID-19 (1). Because the virus is transmitted predominantly by inhaling respiratory droplets from infected persons, universal mask use can help reduce transmission (1). Starting in April, 39 states and the District of Columbia (DC) issued mask mandates in 2020. Reducing person-to-person interactions by avoiding nonessential shared spaces, such as restaurants, where interactions are typically unmasked and physical distancing (≥6 ft) is difficult to maintain, can also decrease transmission (2). In March and April 2020, 49 states and DC prohibited any on-premises dining at restaurants, but by mid-June, all states and DC had lifted these restrictions. To examine the association of state-issued mask mandates and allowing on-premises restaurant dining with COVID-19 cases and deaths during March 1-December 31, 2020, county-level data on mask mandates and restaurant reopenings were compared with county-level changes in COVID-19 case and death growth rates relative to the mandate implementation and reopening dates. Mask mandates were associated with decreases in daily COVID-19 case and death growth rates 1-20, 21-40, 41-60, 61-80, and 81-100 days after implementation. Allowing any on-premises dining at restaurants was associated with increases in daily COVID-19 case growth rates 41-60, 61-80, and 81-100 days after reopening, and increases in daily COVID-19 death growth rates 61-80 and 81-100 days after reopening. Implementing mask mandates was associated with reduced SARS-CoV-2 transmission, whereas reopening restaurants for on-premises dining was associated with increased transmission. Policies that require universal mask use and restrict any on-premises restaurant dining are important components of a comprehensive strategy to reduce exposure to and transmission of SARS-CoV-2 (1). Such efforts are increasingly important given the emergence of highly transmissible SARS-CoV-2 variants in the United States (3,4).