4.5 Article

A Bayesian spatiotemporal model for prevalence estimation of a VRE outbreak in a tertiary care hospital

期刊

JOURNAL OF HOSPITAL INFECTION
卷 122, 期 -, 页码 108-114

出版社

W B SAUNDERS CO LTD
DOI: 10.1016/j.jhin.2021.12.024

关键词

VRE; Outbreak; Screening; Prevalence; Bayesian modelling

资金

  1. Swiss National Science Foundation [CRSK-3_190977/1]
  2. Swiss National Science Foundation (SNF) [CRSK-3_190977] Funding Source: Swiss National Science Foundation (SNF)

向作者/读者索取更多资源

This study aimed to analyze the transmission of vancomycin-resistant enterococci (VRE) in a hospital and the effectiveness of infection control measures. The results showed significant variations in prevalence between departments and floors, with sporadic spatial and temporal clustering during the outbreak. The introduction of new infection control measures led to a decrease in prevalence.
Background: There was a nosocomial outbreak of vancomycin-resistant enterococci (VRE) at the hospital between 1st January 2018 and 31 st July 2020. The goals of this study were to describe weekly prevalence, and to identify possible effects of the introduction of selected infection control measures. Methods: A room-centric analysis of 12 floors (243 rooms) of the main hospital building was undertaken, including data on 37,558 patients over 22,072 person-weeks for the first 2 years of the outbreak (2018-2019). Poisson Bayesian hierarchical models were fitted to estimate prevalence per room and per week, including both spatial and temporal random effects terms. Results: Exploratory data analysis revealed significant variability in prevalence between departments and floors, along with sporadic spatial and temporal clustering during colonization 'flare-ups'. The oncology department experienced slightly higher prevalence over the 104-week study period [adjusted prevalence ratio (aPR) 4.8, 95% confidence interval (CI) 2.6-8.9; P<0.001; compared with general medicine], as did both the cardiac surgery (aPR 3.8, 95% CI 2.0-7.3; P<0.001) and abdominal surgery (aPR 3.7, 95% CI 1.8-7.6; P<0.001) departments. Estimated peak prevalence was reached in July 2018, at which point a number of new infection control measures (including the daily disinfection of rooms and room cleaning with ultraviolet light upon patient discharge) were introduced that resulted in decreasing prevalence (aPR 0.89 per week, 95% CI 0.87-0.91; P<0.001). Conclusion: Relatively straightforward but personnel-intensive cleaning with disinfectants and ultraviolet light provided tangible benefits in getting the outbreak under control. Despite additional complexity, Bayesian hierarchical models provide a more flexible platform to study transmission dynamics. (C) 2022 The Author(s). Published by Elsevier Ltd on behalf of The Healthcare Infection Society.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据