(Antibiotic Data to Inform Local Action)

The ADILA project is led by Prof. Mike Sharland, with co-investigators including Prof. Ben Cooper and Dr. Koen Pouwels from the University of Oxford and Dr. Catrin Moore and Dr. Julia Bielicki at St George’s University of London.


Wellcome Trust


St George’s University of London

Type of Study

Data Reuse Study


3.5 years


In 2015, the World Assembly endorsed the Global Action Plan (GAP) on antimicrobial resistance (AMR) encouraging countries to develop of National Action Plans (NAP) to tackle AMR. As of 2022, 148 countries had a NAP with an additional 38 countries in the process of developing their NAP. While improvements in collection of microbiology and antibiotic consumption data have been helpful to inform countries of the scale of the issue, guidance on how best to use these data at a country level to inform prescribing practices and improve clinical outcomes based on local priorities is urgently needed.

The goal of the ‘Antimicrobial resistance, prescribing, and consumption Data to Inform country antibiotic guidance and Local Action’ (ADILA) project, funded by the Wellcome Trust, is to optimise the use of AMR surveillance data by developing tools that can be implemented nationally to inform and support individual country’s policies on improving the quality of antibiotic use. The proposal aims to learn from the development of clinical surveillance in other disease areas and provide a conceptual framework for future implementation.

This project combines expertise on antimicrobial resistance, usage modelling, and policy development. It aims to model existing datasets to provide a framework for future clinical patient-centred AMR surveillance, that can inform empiric prescribing guidance and support local policy decisions. The proposal has been developed to link closely with current and planned WHO AMR initiatives, including the AWaRe handbook, and the work of other key stakeholders.

We invite you to become a part of this network of international collaborators comprised of clinicians, epidemiologists, microbiologists, and other professionals around the world, working together towards the common goal of tackling antimicrobial resistance and refining antimicrobial usage.

Data Collaboration

We are interested in any antibiotic use and resistance datasets from any available source. We aim to work with global collaborators to include as many existing de-identified patient-level datasets linking AMU and AMR with clinical indication and outcome available as possible. We also seek any available antibiotic use/consumption datasets, clinical infection burden, and antimicrobial resistance datasets, even if they are not linked. These can include patient-level datasets, prescribing datasets, aggregate antibiotic consumption at health facility level or any higher geographic level (e.g. district, country), and wholesale and imports pharmacy data.

We would be interested in discussing any datasets you have access to that you think may be useful to contribute to these objectives. Please get in touch for more information or to discuss any datasets. 

Get in touch


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