Completed Infection & Immunity Food & Agriculture

Antimicrobial Resistance, Prescribing, and Consumption Data to Inform Country Antibiotic Guidance and Local Action – the ADILA project.

In plain English

AI plain-English summary

Doctors in low- and middle-income countries often prescribe antibiotics without knowing which ones will actually work against local infections. The ADILA project will build simple computer models that help countries turn their own surveillance data on antibiotic resistance into clear, actionable guidance for everyday prescribing. The problem is stark: antibiotic resistance data exists in many countries, but it is scattered, inconsistent, and rarely translated into practical rules for clinicians. Without local guidance, doctors rely on outdated international recommendations or guesswork, which fuels further resistance and harms patients. Current surveillance systems were designed for global reporting, not for informing a doctor’s decision at the bedside. If this project succeeds, countries will gain a straightforward framework to analyse their own resistance patterns and produce treatment guidelines tailored to local conditions. The models will be tested with partner countries during an early pilot phase, and the work links directly with WHO initiatives. The result could be a shift from passive data collection to active, patient-centred surveillance that supports real-time policy decisions on which antibiotics to use and which to reserve.

View original technical description
The overall goal of this project is to develop simple tools to help individual countries make the best use of their own AMR surveillance data to inform local action. The project will use a range of modelling methods of existing global data sets that include information on clinical infection management and outcomes, antibiotic resistance, consumption and use. The proposal aims to learn from the development of clinical surveillance networks in other disease areas such as tuberculosis (TB) and will use a public health approach to provide a conceptual framework for future surveillance implementation and policy goals. This project combines research expertise on antimicrobial resistance, usage modelling and policy development. It aims to model the existing data sets to provide a framework for future clinical patient centred AMR surveillance that can inform empiric prescribing guidance and support local individual country policy decisions on future targets and ambitions. The proposal has been developed to link closely with current and planned WHO initiatives and the work of other key stakeholders. The project includes an early pilot phase, developing and testing the models in collaboration with multiple partner countries.

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Researchers

Ben Cooper (EPMC Awardee)Catrin Moore (EPMC Awardee)Direk Limmathurotsakul (EPMC Awardee)Herman Goossens (EPMC Awardee)James Berkley (EPMC Awardee)Julia Bielicki (EPMC Awardee)Koen Pouwels (EPMC Awardee)Li Yang Hsu (EPMC Awardee)Mike Sharland (EPMC Awardee)Nicholas Feasey (EPMC Awardee)Paul Turner (EPMC Awardee)

Related Research

Grants with similar aims, by meaning.

Antimicrobial resistance as a social dilemma: Approaches to reducing broad-spectrum antibiotic use in acute medical patients internationally
The Global Governance of Antimicrobial Resistance: An Empirical Analysis of Participation and Effectiveness
Anti-Microbials In Society (AMIS): a Global Interdisciplinary Research Hub
Working Group and Research Project on Antimicrobial Resistance
NIHR Global Health Research Group Opt-AMR: Optimising Antibiotic Usage to Mitigate AMR

Original classification

Discretionary award - DRI

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