Department of Physics and Astronomy, University of Bologna, Bologna, Italy.
Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, Verona, Italy.
Sci Rep. 2023 Sep 22;13(1):15803. doi: 10.1038/s41598-023-42511-5.
Infection control programs and antimicrobial stewardship have been proven effective in reducing the burden of diseases due to multidrug-resistant organisms, but quantifying the effect of each intervention is an open issue. For this aim, we propose a model to characterize the effect of interventions at single ward level. We adapted the Ross-Macdonald model to describe hospital cross-transmission dynamics of carbapenem resistant Klebsiella pneumoniae (CRKP), considering healthcare workers as the vectors transmitting susceptible and resistant pathogens among admitted patients. The model parameters were estimated from a literature review, further adjusted to reproduce observed clinical outcomes, and validated using real life data from a 2-year study in a university hospital. The model has been further explored through extensive sensitivity analysis, in order to assess the relevance of single interventions as well as their synergistic effects. Our model has been shown to be an effective tool to describe and predict the impact of interventions in reducing the prevalence of CRKP colonisation and infection, and can be extended to other specific hospital and pathological scenarios to produce tailored estimates of the most effective strategies.
感染控制项目和抗菌药物管理已被证明可有效降低多药耐药菌引起的疾病负担，但量化每项干预措施的效果仍是一个悬而未决的问题。为此，我们提出了一种在单个病房层面上描述干预措施效果的模型。我们对 Ross-Macdonald 模型进行了改编，以描述耐碳青霉烯类肺炎克雷伯菌（CRKP）在医院内的交叉传播动态，将医护人员视为在住院患者中传播易感和耐药病原体的媒介。通过文献回顾估计模型参数，进一步调整以再现观察到的临床结果，并使用一所大学医院为期 2 年的研究中的真实数据进行验证。通过广泛的敏感性分析进一步探讨了该模型，以评估单一干预措施及其协同作用的相关性。我们的模型已被证明是一种有效的工具，可用于描述和预测干预措施在降低 CRKP 定植和感染流行率方面的影响，并且可以扩展到其他特定的医院和病理情况，以产生最有效策略的定制估计。
