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Our HPRU brings together world-leading expertise to deliver a step-change in how we exploit increasingly rich data sources, technologies and theory to improve our response to AMR&HAI and deliver cost-effective, evidence-based, high-quality public health impact. We aim to:

  • Understanding better who is most at-risk from AMR&HAI, particularly in terms of inequalities.
  • Developing and testing interventions to reduce their risks, and assessing how these can be targeted to at-risk populations (personalised approaches)
  • Identifying the contexts in which AMR&HAI proliferate, in order to manage and reduce their influence.
  • Improving software to exploit genetic data from millions of microorganisms, to predict resistance to antibiotics, and to identify transmission.

We will use:

(1)   Traditional and new ways of investigating diseases, e.g. using genetic data and looking for patterns in linked ‘big data’ from microbes and electronic records about patients’ health, regionally and nationally.

(2)   Robust statistical and economic methods

(3)   Detailed modelling, and

(4)   Models of behaviours around health choices.



We will:

(1)   Bring world-class Oxford researchers with experience in many different areas, including the Big Data Institute and Social Sciences, together with patient representatives and highly-experienced scientists from Public Health England, Leeds University, the Animal and Plant Health Agency and the European Bioinformatics Institute.

(2)   Train junior researchers in the new methods needed to answer these questions and support them to become research leaders


Our outcomes include

(1)   Better use of routinely-collected electronic health records to monitor and manage infections, reducing data collection burden for the NHS.

(2)   Better estimates of future trends in antibiotic use, AMR and HAIs, and when we need to change commonly-used antibiotics

(3)   Recognition of important at-risk populations to target with future actions to prevent HAIs, and approaches to use antibiotics better

Comparisons of the potential for AMR to spread through different routes, and strategies to reduce this. 

(4)   New software solutions for managing and analysing large amounts of microorganism sequence data that can be used by public health agencies across England, Wales, Scotland and Northern Ireland and even in other countries