Rationale: Black race and Hispanic ethnicity are associated with increased risks for coronavirus disease (COVID-19) infection and severity. It is purported that socioeconomic factors may drive this association, but data supporting this assertion are sparse. Objectives: To evaluate whether socioeconomic factors mediate the association of race/ethnicity with COVID-19 incidence and outcomes. Methods: We conducted a retrospective cohort study of adults tested for (cohort 1) or hospitalized with (cohort 2) COVID-19 between March 1, 2020, and July 23, 2020, at the University of Miami Hospital and Clinics. Our primary exposure was race/ethnicity. We considered socioeconomic factors as potential mediators of our exposure’s association with outcomes. We used standard statistics to describe our cohorts and multivariable regression modeling to identify associations of race/ethnicity with our primary outcomes, one for each cohort, of test positivity (cohort 1) and hospital mortality (cohort 2). We performed a mediation analysis to see whether household income, population density, and household size mediated the association of race/ethnicity with outcomes. Results: Our cohorts included 15,473 patients tested (29.0% non-Hispanic White, 48.1% Hispanic White, 15.0% non-Hispanic Black, 1.7% Hispanic Black, and 1.6% other) and 295 patients hospitalized (9.2% non-Hispanic White, 56.9% Hispanic White, 21.4% non-Hispanic Black, 2.4% Hispanic Black, and 10.2% other). Among those tested, 1,256 patients (8.1%) tested positive, and, of the hospitalized patients, 47 (15.9%) died. After adjustment for demographics, race/ethnicity was associated with test positivity—odds-ratio (95% confidence interval [CI]) versus non-Hispanic White for Non-Hispanic Black: 3.21 (2.60–3.96), Hispanic White: 2.72 (2.28–3.26), and Hispanic Black: 3.55 (2.33–5.28). Population density mediated this association (percentage mediated, 17%; 95% CI, 11–31%), as did median income (27%; 95% CI, 18–52%) and household size (20%; 95% CI, 12–45%). There was no association between race/ethnicity and mortality, although this analysis was underpowered. Conclusions: Black race and Hispanic ethnicity are associated with an increased odds of COVID-19 positivity. This association is substantially mediated by socioeconomic factors.

Hospital-acquired infections are emerging major concurrent conditions during the coronavirus disease (COVID-19) pandemic. We conducted a retrospective review of hospitalizations during March‒October 2020 of adults tested by reverse transcription PCR for severe acute respiratory syndrome coronavirus 2. We evaluated associations of COVID-19 diagnosis with risk for laboratory-confirmed bloodstream infections (LCBIs, primary outcome), time to LCBI, and risk for death by using logistic and competing risks regression with adjustment for relevant covariates. A total of 10,848 patients were included in the analysis: 918 (8.5%) were given a diagnosis of COVID-19, and 232 (2.1%) had LCBIs during their hospitalization. Of these patients, 58 (25%) were classified as having central line‒associated bloodstream infections. After adjusting for covariates, COVID-19‒positive status was associated with higher risk for LCBI and death. Reinforcement of infection control practices should be implemented in COVID-19 wards, and review of superiority and inferiority ranking methods by National Healthcare Safety Network criteria might be needed.

Background To assess the effectiveness of messenger RNA vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) in preventing emergency department (ED) presentations for acute respiratory illness. Basic procedures We conducted a retrospective study assessing adult presentations (age ≥ 18) to the University of Miami Hospital's ED from January 1st through August 25th, 2021, with a SARS-COV-2 PCR test and acute respiratory infection symptoms. Vaccine effectiveness was calculated using a test-negative design. Both univariable and multivariable (adjusted for age, gender, race, insurance status, imputed body mass index [BMI], vaccine type, week of presentation) regression analyses were conducted for the full cohort and subgroups. Main findings The cohort consisted of 13,203 ED presentations—3134 (23.7%) fully vaccinated and SARS-COV-2 negative, 108 (0.8%) fully vaccinated and SARS-COV-2 positive, 8817 (66.8%) unvaccinated and SARS-COV-2 negative, and 1144 (8.7%) unvaccinated and SARS-COV-2 positive. Unadjusted vaccination effectiveness was 73.4% (95% confidence interval: 67.5%,78.3%) and, after adjustment, 73.8% (66.2%,79.7%). The Moderna vaccine's effectiveness was numerically higher (unadjusted: 78.2% [68.8%, 84.7%]; adjusted: 78.0% [68.1%, 84.9%]) than the Pfizer vaccine's (unadjusted: 70.8% [62.9%, 76.9%]; adjusted: 73.9% [66.3%,79.8%]). We found a significant difference in adjusted vaccine effectiveness across categories was BMI ( p < 0.001)—BMI <25: 66.3% (45.3%,79.2%); BMI 25–29: 71.3% (56.1%, 81.2%); BMI 30–34: 84.5% (71.7%, 91.5%); and BMI ≥35: 72.7% (50.5%, 84.9%). Principal conclusions We demonstrated excellent real-world effectiveness of mRNA vaccines in preventing ED presentation for SARS-COV-2 in a diverse U.S. cohort. Notably, vaccine effectiveness improved with increasing BMI (until class 2 obesity).

Many US states published crisis standards of care (CSC) guidelines for allocating scarce critical care resources during the COVID-19 pandemic. However, the performance of these guidelines in maximizing population benefit has not been well tested. In 2,272 adults with COVID-19 requiring ICU admission drawn from the STOP-COVID multicenter cohort, we tested three approaches to CSC algorithms: SOFA scores grouped into ranges, SOFA score ranges plus comorbidities, and a hypothetical approach using raw SOFA scores not grouped into ranges. We found that area under receiver operating characteristic (AUROC) curves for all three algorithms demonstrate only modest discrimination for 28-day mortality. Adding comorbidity scoring modestly improves algorithm performance over SOFA scores alone. The algorithm incorporating comorbidities has modestly worse predictive performance for Black compared to White patients. CSC algorithms should be empirically examined to refine approaches to the allocation of scarce resources during pandemics and to avoid potential exacerbation of racial inequities.