Xu Huiwen, Bowblis John R, Li Shuang, Kuo Yong-Fang, Goodwin James S
Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA.
Department of Economics, Farmer School of Business, Miami University, Oxford, OH; Scripps Gerontology Center, Miami University, Oxford, OH.
Am J Infect Control. 2025 Jul 16. doi: 10.1016/j.ajic.2025.07.003.
During the Coronavirus disease 2019 (COVID-19) pandemic, Ohio was the only state that collected facility-level visitation data after rescinding its ban on visitors. This study examines the association of allowing outside visitors with COVID-19 infection rates among nursing home residents.
We assembled a cohort of Ohio nursing homes over 9 weeks (November 1, 2020-January 3, 2021). For each week, we obtained whether a facility allowed visitors, any COVID-19 infections among residents, community infection rates, and other facility characteristics. Marginal structural models examined the association of allowing visitors with resident infections, weighted by the inverse of the probability of allowing visitors.
Of the 677 nursing homes with visitation data, the number of facilities allowing visitors during any week from October 29, 2020 to January 3, 2021 ranged from 226 to 327. Marginal models substantially improved the balance in covariates. In the marginal models, allowing visitors was not associated with the unadjusted rates or adjusted odds of new infection among residents (odds ratio = 0.92, 95% confidence interval: 0.78, 1.08). The result was similar in sensitivity analyses on the lagged effect of allowing visitors.
Allowing visitors in the context of adequate preventive measures was safe, even during a period of high community transmission and before vaccine rollouts.
在2019冠状病毒病（COVID-19）大流行期间，俄亥俄州是唯一在取消访客禁令后收集机构层面访客数据的州。本研究探讨了允许外部访客与疗养院居民中COVID-19感染率之间的关联。
我们在9周内（2020年11月1日至2021年1月3日）组建了一个俄亥俄州疗养院队列。每周，我们获取了一个机构是否允许访客、居民中是否有任何COVID-19感染、社区感染率以及其他机构特征。边际结构模型研究了允许访客与居民感染之间的关联，并以允许访客概率的倒数为权重。
在有访客数据的677家疗养院中，2020年10月29日至2021年1月3日期间任何一周允许访客的机构数量从226家到327家不等。边际模型显著改善了协变量的平衡。在边际模型中，允许访客与居民中未调整的新感染率或调整后的感染几率无关（优势比 = 0.92，95%置信区间：0.78，1.08）。在对允许访客的滞后效应进行的敏感性分析中，结果相似。
即使在社区传播率高且疫苗推出之前的时期，在采取充分预防措施的情况下允许访客是安全的。
