Lee Xing J, Pettitt Anthony N, Dancer Stephanie J
Centre of Research Excellence in Reducing Healthcare Associated Infections (CRE-RHAI), Queensland University of Technology, Brisbane, Queensland, Australia; ARC Centre of Excellence In Mathematical and Statistical Frontiers (ACEMS), Queensland University of Technology, Brisbane, Queensland, Australia; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
ARC Centre of Excellence In Mathematical and Statistical Frontiers (ACEMS), Queensland University of Technology, Brisbane, Queensland, Australia; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Infect Dis Health. 2018 Sep;23(3):127-136. doi: 10.1016/j.idh.2018.02.005. Epub 2018 Mar 31.
To investigate and quantify the contribution of environmental contamination towards methicillin-resistant Staphylococcus aureus (MRSA) incidence observed in a hospital ward using stochastic modelling.
A non-homogeneous Poisson process model was developed to investigate the relationship between environmental contamination and MRSA incidence in a UK surgical ward during a cleaning intervention study. The model quantified the fractional risks (FRs) from colonised patients, environmental contamination and a generic background source as a measure of their relative importance in describing the observed MRSA incidence.
While the background source remained the most likely MRSA acquisition source for this ward (as measured by the FRs), environmental contamination was the second most likely source, ahead of colonised patients in the ward. The relative importance of environmental contamination was smaller in the enhanced cleaning period compared with the normal cleaning period, albeit with notable variability in the estimates.
Accounting for environmental contamination in stochastic modelling of MRSA transmission within a hospital ward provides a richer interpretation of the FRs, and is particularly pertinent in quantitative investigations of hospital cleaning interventions to reduce MRSA acquisition.
采用随机模型研究并量化医院病房环境污染对耐甲氧西林金黄色葡萄球菌（MRSA）感染发生率的影响。
在一项清洁干预研究中，建立了一个非齐次泊松过程模型，以研究英国一个外科病房环境污染与MRSA感染发生率之间的关系。该模型量化了来自定植患者、环境污染和一般背景源的分数风险（FRs），以此衡量它们在描述观察到的MRSA感染发生率方面的相对重要性。
虽然背景源仍然是该病房最有可能的MRSA感染源（以FRs衡量），但环境污染是第二大可能的来源，排在病房内定植患者之前。与正常清洁期相比，强化清洁期环境污染的相对重要性较小，尽管估计值存在显著差异。
在医院病房MRSA传播的随机模型中考虑环境污染，能对FRs作出更丰富的解释，在减少MRSA感染的医院清洁干预定量研究中尤为重要。
