NIHR Health Protection Research Unit (HPRU) - Oxford
The NIHR Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance (AMR) is a partnership between UK Health Security Agency (UKHSA) and the University of Oxford in collaboration with University of Leeds, Animal and Plant Health Agency and European Bioinformatics Institute.
National Institute for Health Research (NIHR) has provided funding to establish 14 Health Protection Research Units (HPRU) to address key public health threats. The HPRUs are partnerships between Universities and UKHSA forming multi-disciplinary centres of excellence with a focus on collaborations and knowledge sharing.
HPRU in Healthcare Associated Infections and Antimicrobial Resistance at Oxford University is led by Professor Sarah Walker and our UKHSA lead is Professor Susan Hopkins.
The HPRU in Healthcare Associated Infections and AMR vision is to find better ways to manage and prevent threats from antimicrobial resistance and healthcare-associated infections, by detecting them faster, working out who needs protecting most and how this can be done.
It consists of 4 broad Research Themes:
- Populations
- Interventions
- Context
- Sequencing
THEMES
NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance
PPIEP Activities
We want to create opportunities for individuals to interact, engage and contribute to our research to: Improve its quality and relevance: Ensure our research questions align with the wider public’s priorities: Disseminate findings to everyone who may find them relevant, useful or interesting: Inspire adults and children and promote careers in research and Science, Technology, Engineering, and Mathematics
Knowledge Mobilisation
Our strategy for knowledge mobilisation/policy-maker engagement is based on UKSHA leaders being best-placed to ensure HPRU studies directly inform UKHSA needs and results are disseminated beyond academia, including into UKHSA guidance/outputs
Latest publications
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A robust deep learning workflow to predict CD8 + T-cell epitopes
Journal article
Lee CH. et al, (2023), Genome Medicine, 15
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Evaluation of sequence hybridization for respiratory viruses using the Twist Bioscience Respiratory Virus Research panel and the OneCodex Respiratory Virus sequence analysis workflow.
Journal article
Kapel N. et al, (2023), Microbial genomics, 9
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The transcriptional landscape of endogenous retroelements delineates esophageal adenocarcinoma subtypes.
Journal article
Kazachenka A. et al, (2023), NAR cancer, 5
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CD4+ and CD8+ T cells and antibodies are associated with protection against Delta vaccine breakthrough infection: a nested case-control study within the PITCH study.
Journal article
Neale I. et al, (2023), mBio