Durability of SARS-CoV-2 mRNA Booster Vaccine Protection Against Omicron Among Health Care Workers with a Vaccine Mandate.

BACKGROUND: The SARS-CoV-2 Omicron Variant has spread rapidly throughout the world since being identified in South Africa in November 2021. Few studies have assessed primary series and booster vaccine effectiveness against Omicron among US health care workers. METHODS: We conducted a test-negative case-control design to estimate BNT162b2 and mRNA1273 primary vaccination and booster effectiveness against SARS-CoV-2 infection and symptomatic Covid-19 during an Omicron surge among employees of the University of Pennsylvania Health System. The study period was between 7/1/21-4/5/22. We defined the Delta period as 7/1/21-12/12/21 and the Omicron period as beginning 12/20/21. RESULTS: Our sample included 14,520 tests (2,776 [19%] positive)-7,422 (506 [7%] positive) during Delta, and 7,098 (2270 [32%] positive) during Omicron. Benchmarked against Delta, vaccine effectiveness of two vaccine doses was lower during Omicron, with no significant protection against infection. Booster doses added significant protection, although they also showed reduced effectiveness during Omicron. Compared to employees who had received two vaccine doses, three BNT162b2 doses had a relative effectiveness of 50% (95% CI 42-56%) during Omicron, relative to 78% (95% CI 63-87%) during Delta; three mRNA1273 doses had a relative effectiveness of 56% (95% CI 45-65%) during Omicron, relative to 96% (95% CI 82-99%) during Delta. Restricting the sample to symptomatic tests yielded similar results to our primary analysis. After initial waning in BNT162b2 booster protection against infection, it remained largely stable for at least 16 weeks after vaccination. DISCUSSION: Our findings provide a strong rationale for boosters among healthcare workers in the Omicron era.

Community-Based COVID-19 Vaccine Clinics in Medically Underserved Neighborhoods to Improve Access and Equity, Philadelphia, 2021-2022.

Vaccination remains key to reducing the risk of COVID-19-related severe illness and death. Because of historic medical exclusion and barriers to access, Black communities have had lower rates of COVID-19 vaccination than White communities. We describe the efforts of an academic medical institution to implement community-based COVID-19 vaccine clinics in medically underserved neighborhoods in Philadelphia, Pennsylvania. Over a 13-month period (April 2021-April 2022), the initiative delivered 9038 vaccine doses to community members, a majority of whom (57%) identified as Black. (Am J Public Health. 2022;112(12):1721-1725. https://doi.org/10.2105/AJPH.2022.307030).

Factors Associated With COVID-19 Vaccine Receipt by Health Care Personnel at a Major Academic Hospital During the First Months of Vaccine Availability.

Importance: Several COVID-19 vaccines have been authorized in the US, yet preliminary evidence suggests high levels of vaccine hesitancy and wide racial, ethnic, and socioeconomic disparities in uptake. Objective: To assess COVID-19 vaccine acceptance among health care personnel (HCP) during the first 4 months of availability in a large academic hospital, compare acceptance with previously measured vaccine hesitancy, and describe racial, ethnic, and socioeconomic disparities in vaccine uptake. Design, Setting, and Participants: This cross-sectional study included 12 610 HCP who were offered COVID-19 vaccination at a major academic hospital in Philadelphia between December 16, 2020, and April 16, 2021. Exposures: For each HCP, data were collected on occupational category, age, sex, race and ethnicity (Asian or Pacific Islander, Black or African American [Black], Hispanic, White, and multiracial), and social vulnerability index (SVI) at the zip code of residence. Main Outcomes and Measures: Vaccine uptake by HCP at the employee vaccination clinic. Results: The study population included 4173 men (34.8%) and 7814 women (65.2%) (623 without data). A total of 1480 were Asian or Pacific Islander (12.4%); 2563 (21.6%), Black; 452 (3.8%), Hispanic; 7086 (59.6%), White; and 192 (1.6%), multiracial; 717 had no data for race and ethnicity. The mean (SD) age was 40.9 (12.4) years, and 9573 (76.0%) received at least 1 vaccine dose during the first 4 months of vaccine availability. Adjusted for age, sex, job position, and SVI, Black (relative risk [RR], 0.69; 95% CI, 0.66-0.72) and multiracial (RR, 0.80; 95% CI, 0.73-0.89) HCP were less likely to receive vaccine compared with White HCP. When stratified by job position, Black nurses (n = 189; 62.8%), Black HCP with some patient contact (n = 466; 49.9%), and Black HCP with no patient contact (n = 636; 56.3%) all had lower vaccine uptake compared with their White and Asian or Pacific Islander counterparts. Similarly, multiracial HCP with some (n = 26; 52.0%) or no (n = 48; 58.5%) patient contact had lower vaccine uptake. In contrast, Black physicians were just as likely to receive the vaccine as physicians of other racial and ethnic groups. Conclusions and Relevance: In this cross-sectional study, more than two-thirds of HCP at a large academic hospital in Philadelphia received a COVID-19 vaccine within 4 months of vaccine availability. Although racial, ethnic, and socioeconomic disparities were seen in vaccine uptake, no such disparities were found among physicians. Better understanding of factors driving these disparities may help improve uptake.

Characteristics, Outcomes, and Trends of Patients With COVID-19-Related Critical Illness at a Learning Health System in the United States.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic continues to surge in the United States and globally. OBJECTIVE: To describe the epidemiology of COVID-19-related critical illness, including trends in outcomes and care delivery. DESIGN: Single-health system, multihospital retrospective cohort study. SETTING: 5 hospitals within the University of Pennsylvania Health System. PATIENTS: Adults with COVID-19-related critical illness who were admitted to an intensive care unit (ICU) with acute respiratory failure or shock during the initial surge of the pandemic. MEASUREMENTS: The primary exposure for outcomes and care delivery trend analyses was longitudinal time during the pandemic. The primary outcome was all-cause 28-day in-hospital mortality. Secondary outcomes were all-cause death at any time, receipt of mechanical ventilation (MV), and readmissions. RESULTS: Among 468 patients with COVID-19-related critical illness, 319 (68.2%) were treated with MV and 121 (25.9%) with vasopressors. Outcomes were notable for an all-cause 28-day in-hospital mortality rate of 29.9%, a median ICU stay of 8 days (interquartile range [IQR], 3 to 17 days), a median hospital stay of 13 days (IQR, 7 to 25 days), and an all-cause 30-day readmission rate (among nonhospice survivors) of 10.8%. Mortality decreased over time, from 43.5% (95% CI, 31.3% to 53.8%) to 19.2% (CI, 11.6% to 26.7%) between the first and last 15-day periods in the core adjusted model, whereas patient acuity and other factors did not change. LIMITATIONS: Single-health system study; use of, or highly dynamic trends in, other clinical interventions were not evaluated, nor were complications. CONCLUSION: Among patients with COVID-19-related critical illness admitted to ICUs of a learning health system in the United States, mortality seemed to decrease over time despite stable patient characteristics. Further studies are necessary to confirm this result and to investigate causal mechanisms. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.

Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic challenges hospital leaders to make time-sensitive, critical decisions about clinical operations and resource allocations. OBJECTIVE: To estimate the timing of surges in clinical demand and the best- and worst-case scenarios of local COVID-19-induced strain on hospital capacity, and thus inform clinical operations and staffing demands and identify when hospital capacity would be saturated. DESIGN: Monte Carlo simulation instantiation of a susceptible, infected, removed (SIR) model with a 1-day cycle. SETTING: 3 hospitals in an academic health system. PATIENTS: All people living in the greater Philadelphia region. MEASUREMENTS: The COVID-19 Hospital Impact Model (CHIME) (http://penn-chime.phl.io) SIR model was used to estimate the time from 23 March 2020 until hospital capacity would probably be exceeded, and the intensity of the surge, including for intensive care unit (ICU) beds and ventilators. RESULTS: Using patients with COVID-19 alone, CHIME estimated that it would be 31 to 53 days before demand exceeds existing hospital capacity. In best- and worst-case scenarios of surges in the number of patients with COVID-19, the needed total capacity for hospital beds would reach 3131 to 12 650 across the 3 hospitals, including 338 to 1608 ICU beds and 118 to 599 ventilators. LIMITATIONS: Model parameters were taken directly or derived from published data across heterogeneous populations and practice environments and from the health system's historical data. CHIME does not incorporate more transition states to model infection severity, social networks to model transmission dynamics, or geographic information to account for spatial patterns of human interaction. CONCLUSION: Publicly available and designed for hospital operations leaders, this modeling tool can inform preparations for capacity strain during the early days of a pandemic. PRIMARY FUNDING SOURCE: University of Pennsylvania Health System and the Palliative and Advanced Illness Research Center.