Relationship between nursing home COVID-19 outbreaks and staff neighborhood characteristics

Author:

Shen Karen

Abstract

AbstractThe COVID-19 pandemic has taken a significant toll on nursing homes in the US, with upwards of a third of deaths occurring in nursing homes, and more in long-term care facilities. By combining data on facility-level COVID-19 deaths with facility-level data on the neighborhoods where nursing home staff reside for a sample of eighteen states, this paper finds that staff neighborhood characteristics are a large and significant predictor of COVID-19 outbreaks. One standard deviation increases in average staff tract population density, public transportation use, and non-white share were associated with 1.3 (SE .33), 1.4 (SE .35), and 0.9 (SE .24) additional deaths per 100 beds, respectively. These effects are larger than all facility management or quality variables, and larger than the effect of the nursing home’s own neighborhood characteristics. These results suggest that staff communities are likely to be an important source of infection, and that disparities in nursing home outbreaks may be related to differences in the types of neighborhoods nursing home staff live in.

Publisher

Cold Spring Harbor Laboratory

Reference18 articles.

1. Lau-Ng R , Caruso LB , Perls TT. COVID-19 deaths in long term care facilities—a critical piece of the pandemic puzzle. Journal of the American Geriatrics Society. 2020.

2. Khimm S , Strickler L. The government counts 26,000 COVID-19 deaths in nursing homes. That’s at least 14,000 deaths too low. NBC News. 2020.

3. Rau J , Almendraia A. COVID-plagued California nursing homes often had problems in past. Kaiser Health News. 2020.

4. Alonso-Zaldivar R. Harrowing blame game over COVID-19 toll in nursing homes. Associated Press. 2020.

5. Abrams, HR , Loomer L , Gandhi A , Grabowski DC. Characteristics of US nursing homes with COVID-19. Journal of the American Geriatrics Society. 2020.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3