Interventions

We built model-based simulations of hospitals, with CPE prevalence covering the range of levels observed in England, and used these to evaluate the existing national CPE admission screening guidelines and alternatives to. Two beneficial guideline changes were identified: 1) broadening screening selection criteria to include all admissions who had been hospital inpatients anywhere in the last year, 2) shortening the screening test pathway to a single, rather than three consecutive, swabs.  

We found these changes to be both clinically and operationally desirable: more previously unidentified CPE-carriers entering hospital would be selected for testing, and the shorter optimised testing pathway means status would be known more rapidly, importantly increasing the chance this would be prior to hospital discharge, without unduly compromising overall sensitivity/specificity. 

Conduct trial and qualitative work investigating the provision of new point-of-care tests for RTIs in community care  

We are contributing our qualitative expertise to develop and conduct a study investigating views on POCT as part of the EU VALUE-Dx project (https://www.value-dx.eu/) which aims to build the medical and economic case for rapid diagnostics as a public good in the fight against antibiotic resistance, focussing on the management of community-acquired respiratory tract infections in European community care.   

Investigating impact of plasmid dynamics on CPE surveillance and control  

Theoretical and data-driven approaches are currently being used to understand plasmid evolution and plasmid-mediated AMR spread in Enterobacteriales. A PhD student is looking at Plasmid-mediated Carbapenemase-Producing Enterobacterales (CPE) outbreaks to understand outbreak characteristics and predicting public health risk.

Network modelling for nowcasting, forecasting and intervention evaluation at an individual level  

We have developed a protocol and initiated a phased approach to this project, with the short-term objective to: (1) Develop and calibrate an individual-based spatially explicit dynamic network model (building on work from the last HPRU) to allow simulation of CPE spread across the NHS referral network that supports nowcasting, forecasting and scenario analysis. Longer-term objectives are to: (2) Establish real-time trust-level data feeds for key model inputs including: patient movements, microbiological test results, antibiotic use, infection control measures in operation, and aspects of building design that potentially impact on transmission (3) Develop a Dashboard interface to enable healthcare professionals to interact with model output (4) Develop innovative approaches to ensure the model and control policies address health inequalities (5).Using the modelling framework, evaluate the potential benefit of different intervention measures (including screening and isolation strategies), considering both effectiveness and cost-effectiveness (6) Perform in silico evaluations of the potential benefits from incorporating additional types of surveillance data including genomic data into the proposed analysis.  

Exploring antibiotic choice and associated implications  

We have designed a stated preference study (determining what people say they will do) to investigate which clinical factors drive prescribing decision-making post-COVID-19. Through literature review and a ranking exercise with GPs we have identified key attributes to be included in a discrete choice experiment.   

Alongside this, we are conducting a revealed preference study (to determine what people actually do) exploring predictors of actual infection-related primary care prescribing using CPRD data. Combining stated and revealed preference data, we plan to enhance predictions of behavioural change from introducing interventions influencing drivers of antibiotic choice, inform intervention design and implementation.   

Qualitative and quantitative investigation “Stopping antibiotics when patients feel better” as a mechanism to reduce overall antibiotic exposure  

The research has involved both a qualitative study with clinicians and patients to explore their views on the advice to stop antibiotics when patients feel better and a quantitative mathematical modelling study investigating the impact of stopping antibiotics when better on treatment success as well as resistance development. We are also currently combing the results of these two studies in the context of current evidence and outlining future research directions.  

Qualitative evaluation of Acute Respiratory Infection Hubs Implementation (ARIHI) as a mechanism to reduce antibiotic prescribing  

This is on ongoing qualitative study to explore the implementation of Acute Respiratory Infection (ARI) hubs in England; it involves interviews with professionals involved in setting up, managing and providing care in ARI hubs to understand the role of ARI hubs in managing ARIs and barriers and facilitators to implementation.