Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

external supervisor

Professor Mike Sharland, St George’s University of London
Professor Ben Cooper, Nuffield Department of Medicine, University of Oxford


Antimicrobial resistance (AMR) is responsible for significant mortality and economic harm and will inevitably worsen without substantial changes to global patterns of antibiotic use. Total and broad-spectrum antibiotic use in humans are important drivers of AMR. In an effort to optimize antibiotic use, the World Health Organization (WHO) created a classification in which antibiotics were stratified into Access, Watch, and Reserve (AWaRe) groups based on their clinical efficacy, risk of toxicity, cost and anticipated risk of resistance development. The AWaRe classification was developed using expert consensus of the literature but has not been empirically evaluated. The DPhil student is expected to obtain empirical estimates on the effectiveness and adverse effects of different antibiotics by applying different statistical and econometric methods to large electronic healthcare databases. Importantly, the student will also evaluate how these different effects could be combined into novel metrics to evaluate the preferred selection of antibiotics for common infections, considering not only costs and benefits for individual patients, but also their public health utility. The overall aim of the project is to inform the development of global targets of optimal antibiotic use. The DPhil candidate will work as part of the Wellcome funded ADILA project team, using multiple data sources to inform country level action to combat AMR. 


Candidates will acquire research skills through regular supervisory meetings, and by attending relevant seminars, courses, workshops. By the end of the DPhil, it is expected that the candidate will be able to plan, undertake and interpret statistical/econometric analysis of large-scale data, and to report their findings through presentation at conferences and peer-reviewed papers. 


There will be opportunities to work with external partners and/or datasets from other countries, including low and middle income countries.  


The ideal candidate will have a Masters degree in (health)-economics, statistics, mathematics, epidemiology, or a related quantitative area. Prior knowledge and an interest in antimicrobial resistance or infections is desirable. Candidates are encouraged to contact Dr Koen Pouwels to work out a specific project proposal.