Self-reported resilience of North Carolina long-term care organizations and public health agencies in the midst of the COVID-19 pandemic

The objective of this study was to determine the self-reported resilience of North Carolina long-term care (LTC) and public health organizations while in the midst of a pandemic. Further, we correlate resilience with several organizational attributes for some insight into the types of organizations that are more resilient. Through collaboration with four LTC professional associations in North Carolina, the Benchmark Resilience Tool-13 (BRT-13) survey was disseminated to LTC leaders across North Carolina, and emailed to Public Health leaders during April 2021. The 13 survey items were divided into adaptive capacity and planning factors. Analysis of variance was used to determine whether organizational factors contributed to resiliency. A total of 142 completed surveys were received, 20 from assisted living administrators, 67 nursing home administrators, 14 from continuing care retirement community leaders, and 41 from public health officials. Average resilience, adaptive capacity, and planning were measured and analyzed against type of facility, RUCA area designation, owner type, level of debt, level of profitability, and employee satisfaction. Average resilience scores were 3.96 (SD = 0.774) for public health, 4.19 (SD = 0.725) for nursing homes, 4.22 (SD = 0.509) for assisted living, and 4.46 (SD = 0.407) for continuing care retirement communities. Results show a significant trend of higher employee satisfaction related to higher adaptive capacity, planning, and overall resilience. A key to organizational resilience in the pandemic was how well an organization cared for their employees. We must prepare before a crisis by being attentive to employee satisfaction and not lose track of employee satisfaction during the crisis. Public health agencies and LTC organizations who maintain high employee satisfaction will be more resilient.

Southeastern United States Predictors of COVID-19 in Nursing Homes.

This study's aim was to determine nursing home (NH) and county-level predictors of COVID-19 outbreaks in nursing homes (NHs) in the southeastern region of the United States across three time periods. NH-level data compiled from census data and from NH compare and NH COVID-19 infection datasets provided by the Center for Medicare and Medicaid Services cover 2951 NHs located in 836 counties in nine states. A generalized linear mixed-effect model with a random effect was applied to significant factors identified in the final stepwise regression. County-level COVID-19 estimates and NHs with more certified beds were predictors of COVID-19 outbreaks in NHs across all time periods. Predictors of NH cases varied across the time periods with fewer community and NH variables predicting COVID-19 in NH during the late period. Future research should investigate predictors of COVID-19 in NH in other regions of the US from the early periods through March 2021.

Participatory COVID-19 Surveillance Tool in Rural Appalachia : Real-Time Disease Monitoring and Regional Response.

INTRODUCTION: Few US studies have examined the usefulness of participatory surveillance during the coronavirus disease 2019 (COVID-19) pandemic for enhancing local health response efforts, particularly in rural settings. We report on the development and implementation of an internet-based COVID-19 participatory surveillance tool in rural Appalachia. METHODS: A regional collaboration among public health partners culminated in the design and implementation of the COVID-19 Self-Checker, a local online symptom tracker. The tool collected data on participant demographic characteristics and health history. County residents were then invited to take part in an automated daily electronic follow-up to monitor symptom progression, assess barriers to care and testing, and collect data on COVID-19 test results and symptom resolution. RESULTS: Nearly 6500 county residents visited and 1755 residents completed the COVID-19 Self-Checker from April 30 through June 9, 2020. Of the 579 residents who reported severe or mild COVID-19 symptoms, COVID-19 symptoms were primarily reported among women (n = 408, 70.5%), adults with preexisting health conditions (n = 246, 70.5%), adults aged 18-44 (n = 301, 52.0%), and users who reported not having a health care provider (n = 131, 22.6%). Initial findings showed underrepresentation of some racial/ethnic and non-English-speaking groups. PRACTICAL IMPLICATIONS: This low-cost internet-based platform provided a flexible means to collect participatory surveillance data on local changes in COVID-19 symptoms and adapt to guidance. Data from this tool can be used to monitor the efficacy of public health response measures at the local level in rural Appalachia.