Visualising infection transmission routes in order to identify, monitor and prevent antimicrobial resistant infection

卫生保健相关感染（HCAI），特别是抗菌素耐药性（AMR）是全球公共卫生面临的最紧迫威胁之一。抗生素耐药性在世界范围内的迅速出现可能会使抗生素——医学上最伟大的进步之一——变得过时。每年约有70万人死于耐多药细菌感染；据估计，到2050年，这一数字将上升到1000万。同时，hcai是最常遇到的威胁患者安全的不良事件，每年在欧盟影响400万患者，估计造成1600万额外的住院日。减少hcai将有助于保留抗生素的使用，从而遏制抗菌素耐药性在卫生保健环境中的传播。埃斯特拉提出的研究旨在开发一种工具，用于跟踪和可视化整个医疗系统的感染情况。获取和分析及时的数据，以便绘制感染源地图和可视化传播途径，是有效应对抗菌素耐药性的关键组成部分。这些信息可用于分析个体间的疾病传播，并为决策建立定量证据基础。这可以很容易地应用的一个特定领域是病人通过医院网络的旅程。在住院期间，患者访问了许多程序和诊断共用区域，提供了传播感染的机会。然而，在评估疾病传播的分析中通常没有捕捉到这些潜在的暴露。拟议的研究将旨在使用电子健康记录数据和计算机模拟，以研究传染病爆发和医院在关键医疗保健质量指标方面的表现。这些途径的可视化将为HCAI传播的定量建模提供信息，这将促进干预措施的制定和感染控制措施的目标。最终，这将实现医院内部的监测、反馈和决策。

Healthcare-associated infection (HCAI), and specifically antimicrobial resistance (AMR) is one of the most pressing threats to global public health. The rapid worldwide emergence of AMR may render antibiotics, one of the greatest advances in medicine, obsolete. Approximately 700,000 people die annually as a result of multi-drug resistant bacterial infections; a figure which is estimated to rise to 10 million by 2050. Concurrently HCAIs are the most frequently encountered adverse event to threaten patient safety, affecting 4 million patients in the EU annually and causing an estimated 16 million additional bed-days. A reduction in HCAIs would aid in conserving the use of antibiotics, and therefore curb the spread of AMR in healthcare settings.Estera's proposed research aims to to develop a tool for tracking and visualising infections throughout a healthcare system. Acquiring and analysing timely data which allows the mapping of infection sources and visualisation of transmission routes is a key component of effective responses against AMR. This information can be used to dissect disease spread at an individual-to-individual level, and develop a quantitative evidence base for decision making. A specific area where this can be readily applied is the patient journey through a hospital network. During hospitalisation, patients visit many procedural and diagnostic common areas, presenting opportunities for transmission of infection. However, these potential exposures are not typically captured in analyses evaluating disease transmission. The proposed study will aim to use electronic health record data and in-silico simulations in order to study infectious disease outbreaks and hospital performance on key healthcare quality metrics.Visualisation of these pathways will inform quantitative modelling of HCAI transmission, which will facilitate intervention development and targeting of infection control measures. Ultimately this will enable monitoring, feedback and decision making within hospitals.