A Typology of COVID-19 Data Gaps and Noise From Long-Term Care Facilities: Approximating the True Numbers

Nursing Home Residents' COVID-19 Infections in the United States: A Systematic Review of Personal and Contextual Factors

Background: This mixed methods systemic review synthesizes the evidence about nursing home risks for COVID-19 infections. Methods: Four electronic databases (PubMed, Web of Science, Scopus, and Sage Journals Online) were searched between January 2020 and October 2022. Inclusion criteria were studies reported on nursing home COVID-19 infection risks by geography, demography, type of nursing home, staffing and resident's health, and COVID-19 vaccination status. The Mixed Methods Appraisal Tool (MMAT) was used to assess the levels of evidence for quality, and a narrative synthesis for reporting the findings by theme. Results: Of 579 initial articles, 48 were included in the review. Findings suggest that highly populated counties and urban locations had a higher likelihood of COVID-19 infections. Larger nursing homes with a low percentage of fully vaccinated residents also had increased risks for COVID-19 infections than smaller nursing homes. Residents with advanced age, of racial minority, and those with chronic illnesses were at higher risk for COVID-19 infections. Discussion and implications: Findings suggest that along with known risk factors for COVID-19 infections, geographic and resident demographics are also important preventive care considerations. Access to COVID-19 vaccinations for vulnerable residents should be a priority.

COVID-19 Across the Landscape of Long-Term Care in Alameda County: Heterogeneity and Disparities

Throughout the pandemic, public health and long-term care professionals in our urban California county have linked local and state COVID-19 data and performed observational exploratory analyses of the impacts among our diverse long-term care facilities (LTCFs). Case counts from LTCFs through March 2021 included 4309 (65%) in skilled nursing facilities (SNFs), 1667 (25%) in residential care facilities for the elderly (RCFEs), and 273 (4%) in continuing care retirement communities (CCRCs). These cases led to 582 COVID-19 resident deaths and 12 staff deaths based on death certificates. Data on decedents' age, race, education, and country of birth reflected a hierarchy of wealth and socioeconomic status from CCRCs to RCFEs to SNFs. Mortality rates within SNFs were higher for non-Whites than Whites. Staff accounted for 42% of LTCF-associated COVID-19 cases, and over 75% of these staff were unlicensed. For all COVID-19 deaths in our jurisdiction, both LTCF and community, 82% of decedents were age 65 or over. Taking a comprehensive, population-based approach across our heterogenous LTCF landscape, we found socioeconomic disparities within COVID-19 cases and deaths of residents and staff. An improved data infrastructure linking public health and delivery systems would advance our understanding and potentiate life-saving interventions within this vulnerable ecosystem.