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

Lead Research Organisation: Imperial College London
Department Name: Dept of Medicine


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.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
ES/P000703/1 01/10/2017 30/09/2027
2110267 Studentship ES/P000703/1 01/10/2018 31/12/2022 Emanuela Estera Boncea
Description In the first year of my doctoral funding, I focused on building the evidence base that the patient journey through a hospital network influences the odds of an individual developing a hospital acquired infection. This led to a publication in the BMJ Quality and Safety and a conference presentation at the World Congress on Public Health 2020, which demonstrated that an association between patient movement and infection does exist in elderly patients, with each additional ward transfer increasing the odds of infection by 9%. The article was well received, being cited in a new editorial in the same journal on the topic of healthcare-associate infections and achieving a high altmetrics score (a social media engagement and online attention measure), which placed it in the top 10% of articles ever published, as well as above average for articles published solely in the BMJ Quality and Safety within a similar time frame. Feedback on the publication has highlighted the importance of accounting for different types of patient movement within the hospital, helping to refine a new research question focussing on characterising the complexity of patient movement trajectories and understanding how different patterns of transfers may be linked to adverse events including and beyond the risk of infection. I am therefore using network analysis, a novel tool within the public health discipline, to explore 'communities' of patients who move in similar patterns. A good opportunity to further discuss the findings and their potential impact will be the Imperial College Global Fellows Programme, for which I was accepted in 2020. The programme, which has been postponed due to Covid-19, intends to bring together doctoral students from Imperial College, Technical University of Munich, and the Nanyang Technological University in Singapore to discuss how research networks and collaborations can address topics under the theme "Health data and technology for society", and opens the opportunity to spend 3 weeks undertaking a research visit at a partnering institution.
Exploitation Route Identifying and characterising the mechanisms behind differing pathways of patient movement, and their impact on patient outcomes will be relevant to hospital managers and healthcare staff responsible for optimising the organisation of hospital services. The work is also relevant for informing model parameters for future modelling of patient movement. The knowledge generated will help to create new interventions for patient flow management and in the longer term can be applied to informing hospital design.
Sectors Communities and Social Services/Policy,Healthcare,Government, Democracy and Justice

Description NIHR Research Day 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Undergraduate students
Results and Impact Research open day showcasing the Global Digital health unit's work, including my research surrounding the impact of intrahospital transfers on odds of developing an infection
Year(s) Of Engagement Activity 2019
Description Public event - Imperial 'Lates' Beautiful Data 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact I took a lead in creating and hosting an interactive stand showcasing visualisation of infection data and patient movement with other members of my research unit (Global Digital Health Unit)
Year(s) Of Engagement Activity 2020