Model-based evaluation of policy impacts and the continued COVID-19 risk at long term care facilities

Bailey K Fosdick; Jude Bayham; Jake Dilliott; Gregory D Ebel; Nicole Ehrhart

doi:10.1016/j.idm.2022.07.003

Model-based evaluation of policy impacts and the continued COVID-19 risk at long term care facilities

Infect Dis Model. 2022 Sep;7(3):463-472. doi: 10.1016/j.idm.2022.07.003. Epub 2022 Jul 15.

Authors

Bailey K Fosdick¹, Jude Bayham², Jake Dilliott², Gregory D Ebel³, Nicole Ehrhart⁴

Affiliations

¹ Department of Statistics, Colorado State University, Ft. Collins, CO, 80523, USA.
² Department of Agricultural and Resource Economics, Colorado State University, Ft. Collins, CO, 80523, USA.
³ Arthropod-Borne and Infectious Diseases Laboratory, Department of Microbiology, Immunology and Pathology, Colorado State University, Ft. Collins, CO, 80526, USA.
⁴ Columbine Health Systems Center for Healthy Aging and Department of Clinical Sciences, Colorado State University, Ft. Collins, CO, 80523, USA.

Abstract

The COVID-19 pandemic severely impacted long-term care facilities resulting in the death of approximately 8% of residents nationwide as of March 2021. As COVID-19 case rates declined and state and county restrictions were lifted in spring 2021, facility managers, local and state health agencies were challenged with defining their own policies moving forward to appropriately mitigate disease transmission. The continued emergence of variants of concern and variable vaccine uptake across facilities highlighted the need for a readily available tool that can be employed at the facility-level to determine best practices for mitigation and ensure resident and staff safety. To assist leadership in determining the impact of various infection surveillance and response strategies, we developed an agent-based model and an online dashboard interface that simulates COVID-19 infection within congregate care settings under various mitigation measures. This dashboard quantifies the continued risk for COVID-19 infections within a facility given a designated testing schedule and vaccine requirements. Key findings were that choice of COVID-19 diagnostic (ex. nasal swab qRT-PCR vs rapid antigen) and testing cadence has less impact on attack rate and staff workdays missed than does vaccination rates among staff and residents. Specifically, low vaccine uptake among staff at long-term care facilities puts staff and residents at risk of ongoing COVID-19 outbreaks. Here we present our model and dashboard as an exemplar of a tool for state public health officials and facility directors to gain insights from an infectious disease model that can directly inform policy decisions in the midst of a pandemic.

Keywords: ABM, agent-based model; Agent-based model; CDC, Centers for Disease Control; CMS, Centers for Medicare and Medicaid Services; COVID-19; LTCF, long term care facility; Nonpharmaceutical interventions; Vaccine uptake.