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

可视化感染传播途径，以识别、监测和预防抗菌药物耐药性感染

• 批准号: 2110267
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2110267
• 关键词: Visualising; infection; transmission; routes; order

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.

医疗相关感染（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。AMR在全球范围内的迅速出现可能会使抗生素这一医学上最伟大的进步之一过时。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1 000万。同时，HCAIs是最常见的威胁患者安全的不良事件，每年影响欧盟400万患者，并导致估计1600万个额外的床日。HCAIs的减少将有助于节省抗生素的使用，从而遏制AMR在医疗机构中的传播。Estera提出的研究旨在开发一种在整个医疗系统中跟踪和可视化感染的工具。获取和分析及时的数据，从而可以绘制感染源和可视化传播途径，是有效应对AMR的关键组成部分。这些信息可用于在个体与个体层面上剖析疾病传播，并为决策制定定量证据基础。这一点可以很容易地应用的一个特定领域是通过医院网络的患者旅程。在住院期间，患者访问许多程序和诊断公共区域，这为感染传播提供了机会。然而，在评估疾病传播的分析中通常不会捕获这些潜在的暴露。建议的研究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传播的定量模型提供信息，这将有助于制定干预措施和针对感染控制措施。最终，这将使医院内的监测、反馈和决策成为可能。

项目成果

Association between intrahospital transfer and hospital-acquired infection in the elderly: a retrospective case-control study in a UK hospital network.

• DOI: 10.1136/bmjqs-2020-012124
• 发表时间: 2021-06
• 期刊: BMJ quality & safety
• 影响因子: 5.4
• 作者: Boncea EE;Expert P;Honeyford K;Kinderlerer A;Mitchell C;Cooke GS;Mercuri L;Costelloe CE
• 通讯作者: Costelloe CE

Abstracts for NERCCS 2021: Fourth Northeast Regional Conference on Complex Systems

• 发表时间: 2021
• 作者: Alexandra Paxton;Ülgen Kilic;S. Muldoon;Andrea Allen;Mariah C. Boudreau;Nicholas W. Roberts;Dylan Morris;D. Cooney;S. Levin;D. Rubenstein;P. Romanczuk

The impact of atypical intrahospital transfers on patient outcomes: a mixed methods study.

• DOI: 10.1038/s41598-023-41966-w
• 发表时间: 2023-09-18
• 期刊: Scientific reports
• 影响因子: 4.6

Challenges and recommendations for high quality research using electronic health records.

• DOI: 10.3389/fdgth.2022.940330
• 发表时间: 2022
• 期刊: FRONTIERS IN DIGITAL HEALTH
• 作者: Honeyford, K.;Expert, P.;Mendelsohn, E. E.;Post, B.;Faisal, A. A.;Glampson, B.;Mayer, E. K.;Costelloe, C. E.
• 通讯作者: Costelloe, C. E.

Association between ward-transfers and hospital-acquired infection: a study using routine data

病房转移与医院获得性感染之间的关联：使用常规数据的研究

• 发表时间: 2020
• 作者: Boncea E