Model-based evaluation of policy impacts and the continued COVID-19 risk at long term care facilities
作者机构：Department of StatisticsColorado State UniversityFt.CollinsCO80523USA Department of Agricultural and Resource EconomicsColorado State UniversityFt.CollinsCO80523USA Arthropod-Borne and Infectious Diseases LaboratoryDepartment of MicrobiologyImmunology and PathologyColorado State UniversityFt.CollinsCO80526USA Columbine Health Systems Center for Healthy Aging and Department of Clinical SciencesColorado State UniversityFt.CollinsCO80523USA
出 版 物：《Infectious Disease Modelling》 (传染病建模（英文）)
年 卷 期：2022年第7卷第3期
页 面：463-472页
学科分类：0710[理学-生物学] 1004[医学-公共卫生与预防医学(可授医学、理学学位)] 1002[医学-临床医学] 10[医学]
基 金：This work was supported by Colorado State University's Center for Healthy Aging the Office of the Vice President for Research the College of Health and Human Sciences the College of Natural Sciences the College of Veterinary Medicine and Biomedical Sciences and the Walter Scott Jr College of Engineering.It was also supported by Colorado Department of Public Health and the Environment COVID-19 Epidemic Modeling Services(RFAA 202000011320).
主 题：Agent-based model Nonpharmaceutical interventions Vaccine uptake COVID-19
摘 要：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 vaccineuptake across facilitieshighlighted the need for a readily available tool that can beemployed 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.
维普期刊数据库