David Eyre
Professor of Infectious Diseases
- Robertson Fellow
- Infectious Diseases Clinician
My research aims to understand who gets different infections and why, and how best to prevent, treat and monitor these infections. I also work on developing artificial intelligence tools to help diagnose and treat hospital patients, and to help hospitals run better.
I use a range of approaches spanning epidemiology, statistics, causal inference, and machine learning. I work with detailed deidentified healthcare record data at both regional and national scales. I also have extensive programming and database expertise.
My other research interests include the use of whole-genome sequencing as a tool for understanding the epidemiology and transmission of bacteria, viruses and fungi, and mathematical modelling of infectious disease transmission. I am also interested in using sequencing technologies as a novel tool for culture-independent microbiology diagnostics. These technologies offer the prospect of same-day diagnosis of infection, rather than having to wait several days for bacteria to grow in the lab as is common now.
I work closely with the Modernising Medical Microbiology consortium on several of these projects, contributing to the Oxford NIHR Biomedical Research Centre and an NIHR Health Protection Research Unit.
Recent publications
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Leveraging transformers and large language models with antimicrobial prescribing data to predict sources of infection for electronic health record studies
Preprint
Yuan K. et al, (2024)
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No evidence of difference in mortality with amoxicillin versus co-amoxiclav for hospital treatment of community-acquired pneumonia
Journal article
Wei J. et al, (2024), Journal of Infection
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Distinct patterns of vital sign and inflammatory marker responses in adults with suspected bloodstream infection.
Journal article
Gu Q. et al, (2024), The Journal of infection
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SARS-CoV-2, influenza A/B and respiratory syncytial virus positivity and association with influenza-like illness and self-reported symptoms, over the 2022/23 winter season in the UK: a longitudinal surveillance cohort.
Journal article
Dietz E. et al, (2024), BMC Med, 22
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Target enrichment improves culture-independent detection of Neisseria gonorrhoeae and antimicrobial resistance determinants direct from clinical samples with Nanopore sequencing.
Journal article
Street TL. et al, (2024), Microb Genom, 10