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

• Published in: The Journal of hospital infection 2022-04, Vol.122, p.108-114
• Main Authors: Atkinson, A., Ellenberger, B., Piezzi, V., Kaspar, T., Endrich, O., Leichtle, A.B., Zwahlen, M., Marschall, J.
• Format: Article
• Language: English
• Subjects: Bayes Theorem; Bayesian modelling; Cross Infection - epidemiology; Cross Infection - prevention & control; Disease Outbreaks; Gram-Positive Bacterial Infections - epidemiology; Gram-Positive Bacterial Infections - prevention & control; Humans; Outbreak; Prevalence; Screening; Tertiary Care Centers; Vancomycin-Resistant Enterococci; VRE
• ISSN: 0195-6701; 1532-2939
• DOI: 10.1016/j.jhin.2021.12.024

There was a nosocomial outbreak of vancomycin-resistant enterococci (VRE) at the hospital between 1st January 2018 and 31st 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. 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. 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