COVID-19-related state-wise racial and ethnic disparities across the USA: an observational study based on publicly available data from The COVID Tracking Project

Examining COVID-19 testing and vaccination behaviors by heritage and linguistic preferences among Hispanic, Latino, or Spanish RADx-UP participants

The Hispanic, Latino, or Spanish (hereafter, "Hispanic") populations in the U.S. bear a disproportionate burden of COVID-19-related outcomes, including disease incidence and mortality. Developing culturally appropriate national public health services for Hispanic persons remains a challenge. This study examined the association of heritage and language preference with COVID-19 testing (tested vs. not tested) and vaccination (vaccinated vs. not vaccinated) outcomes among Hispanic participants from 18 Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) projects (n = 3308; mean age = 44.1 years [SD = 14.9], 60% women; 83% spoke other than English at home). Generalized estimating equation models adjusted for age, gender, education level, income, insurance coverage, geographic region, comorbidities, and prior infection. Relative to Mexican heritage, individuals identifying as Puerto Rican or Dominican were more likely to test for COVID-19, and South American heritage was associated with higher testing and vaccination rates. Speaking Spanish or another language at home was associated with increased testing compared with speaking English at home for individuals who preferred not to report their heritage, and increased vaccination for those with Mexican, Cuban, or Central American heritage. This study highlights heterogeneity in testing and vaccination behaviors among Hispanic populations based on heritage and language preference, underscoring the diversity within the U.S. Hispanic community. In contrast to other studies on linguistic acculturation and health care utilization, our study found that a language other than English spoken at home was associated with greater vaccine uptake. That is, enculturation - the retention of Spanish language and presumably of Hispanic cultural norms - was linked with being vaccinated.

Clinically stable covid-19 patients presenting to acute unscheduled episodic care venues have increased risk of hospitalization: secondary analysis of a randomized control trial

BACKGROUND

Assessment for risks associated with acute stable COVID-19 is important to optimize clinical trial enrollment and target patients for scarce therapeutics. To assess whether healthcare system engagement location is an independent predictor of outcomes we performed a secondary analysis of the ACTIV-4B Outpatient Thrombosis Prevention trial.

METHODS

A secondary analysis of the ACTIV-4B trial that was conducted at 52 US sites between September 2020 and August 2021. Participants were enrolled through acute unscheduled episodic care (AUEC) enrollment location (emergency department, or urgent care clinic visit) compared to minimal contact (MC) enrollment (electronic contact from test center lists of positive patients).We report the primary composite outcome of cardiopulmonary hospitalizations, symptomatic venous thromboembolism, myocardial infarction, stroke, transient ischemic attack, systemic arterial thromboembolism, or death among stable outpatients stratified by enrollment setting, AUEC versus MC. A propensity score for AUEC enrollment was created, and Cox proportional hazards regression with inverse probability weighting (IPW) was used to compare the primary outcome by enrollment location.

RESULTS

Among the 657 ACTIV-4B patients randomized, 533 (81.1%) with known enrollment setting data were included in this analysis, 227 from AUEC settings and 306 from MC settings. In a multivariate logistic regression model, time from COVID test, age, Black race, Hispanic ethnicity, and body mass index were associated with AUEC enrollment. Irrespective of trial treatment allocation, patients enrolled at an AUEC setting were 10-times more likely to suffer from the adjudicated primary outcome, 7.9% vs. 0.7%; p < 0.001, compared with patients enrolled at a MC setting. Upon Cox regression analysis adjustment patients enrolled at an AUEC setting remained at significant risk of the primary composite outcome, HR 3.40 (95% CI 1.46, 7.94).

CONCLUSIONS

Patients with clinically stable COVID-19 presenting to an AUEC enrollment setting represent a population at increased risk of arterial and venous thrombosis complications, hospitalization for cardiopulmonary events, or death, when adjusted for other risk factors, compared with patients enrolled at a MC setting. Future outpatient therapeutic trials and clinical therapeutic delivery programs of clinically stable COVID-19 patients may focus on inclusion of higher-risk patient populations from AUEC engagement locations.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04498273.

Diverging maternal and infant cord antibody functions from SARS-CoV-2 infection and vaccination in pregnancy

Immunization in pregnancy is a critical tool that can be leveraged to protect the infant with an immature immune system but how vaccine-induced antibodies transfer to the placenta and protect the maternal-fetal dyad remains unclear. Here, we compare matched maternal-infant cord blood from individuals who in pregnancy received mRNA COVID-19 vaccine, were infected by SARS-CoV-2, or had the combination of these two immune exposures. We find that some but not all antibody neutralizing activities and Fc effector functions are enriched with vaccination compared to infection. Preferential transport to the fetus of Fc functions and not neutralization is observed. Immunization compared to infection enriches IgG1-mediated antibody functions with changes in antibody post-translational sialylation and fucosylation that impact fetal more than maternal antibody functional potency. Thus, vaccine enhanced antibody functional magnitude, potency and breadth in the fetus are driven more by antibody glycosylation and Fc effector functions compared to maternal responses, highlighting prenatal opportunities to safeguard newborns as SARS-CoV-2 becomes endemic.

Race and ethnicity: Risk factors for fungal infections?

Racial and ethnic identities, largely understood as social rather than biologic constructs, may impact risk for acquiring infectious diseases, including fungal infections. Risk factors may include genetic and immunologic differences such as aberrations in host immune response, host polymorphisms, and epigenomic factors stemming from environmental exposures and underlying social determinants of health. In addition, certain racial and ethnic groups may be predisposed to diseases that increase risk for fungal infections, as well as disparities in healthcare access and health insurance. In this review, we analyzed racial and ethnic identities as risk factors for acquiring fungal infections, as well as race and ethnicity as they relate to risk for severe disease from fungal infections. Risk factors for invasive mold infections such as aspergillosis largely appear related to environmental differences and underlying social determinants of health, although immunologic aberrations and genetic polymorphisms may contribute in some circumstances. Although black and African American individuals appear to be at high risk for superficial and invasive Candida infections and cryptococcosis, the reasons for this are unclear and may be related to underling social determinants of health, disparities in access to healthcare, and other socioeconomic disparities. Risk factors for all the endemic fungi are likely largely related to underlying social determinants of health, socioeconomic, and health disparities, although immunologic mechanisms likely play a role as well, particularly in disseminated coccidioidomycosis.

Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts

Infectious disease surveillance frequently lacks complete information on race and ethnicity, making it difficult to identify health inequities. Greater awareness of this issue has occurred due to the COVID-19 pandemic, during which inequities in cases, hospitalizations, and deaths were reported but with evidence of substantial missing demographic details. Although the problem of missing race and ethnicity data in COVID-19 cases has been well documented, neither its spatiotemporal variation nor its particular drivers have been characterized. Using individual-level data on confirmed COVID-19 cases in Massachusetts from March 2020 to February 2021, we show how missing race and ethnicity data: (1) varied over time, appearing to increase sharply during two different periods of rapid case growth; (2) differed substantially between towns, indicating a nonrandom distribution; and (3) was associated significantly with several individual- and town-level characteristics in a mixed-effects regression model, suggesting a combination of personal and infrastructural drivers of missing data that persisted despite state and federal data-collection mandates. We discuss how a variety of factors may contribute to persistent missing data but could potentially be mitigated in future contexts.

The Missing COVID-19 Demographic Data: A Statewide Analysis of COVID-19-Related Demographic Data From Local Government Sources and a Comparison With Federal Public Surveillance Data

Objectives. To collect and standardize COVID-19 demographic data published by local public-facing Web sites and analyze how this information differs from Centers for Disease Control and Prevention (CDC) public surveillance data. Methods. We aggregated and standardized COVID-19 data on cases and deaths by age, gender, race, and ethnicity from US state and territorial governmental sources between May 24 and June 4, 2021. We describe the standardization process and compare it with the CDC's process for public surveillance data. Results. As of June 2021, the CDC's public demographic data set included 80.9% of total cases and 46.7% of total deaths reported by states, with significant variation across jurisdictions. Relative to state and territorial data sources, the CDC consistently underreports cases and deaths among African American and Hispanic or Latino individuals and overreports deaths among people older than 65 years and White individuals. Conclusions. Differences exist in amounts of data included and demographic composition between the CDC's public surveillance data and state and territory reporting, with large heterogeneity across jurisdictions. A lack of standardization and reporting mechanisms limits the production of complete real-time demographic data.