Professor Eva Morris
Contact information
Research groups
Eva Morris
PhD
Professor of Health Data Epidemiology
- Deputy Director, Big Data Institute
- BDI Associate Head (Translation and Culture)
Eva Morris studied Neuroscience at the University of Edinburgh (1993-1998) before undertaking a PhD in Cancer Epidemiology and Health Services Research at the University of Leeds (2001-2004). After a short period working in Public Health at the University of Newcastle, she then returned to Leeds to work with the regional cancer registry and, subsequently, the National Cancer Intelligence Network to undertake large-scale population-based studies based on linked administrative health datasets. In 2008 she was awarded a Cancer Research UK Career Development Fellowship and made a Professor of Cancer Epidemiology in 2015. She has a portfolio of research based around the use of linked datasets to investigate the management of colorectal cancer and so generate evidence that will drive improvements in care and outcome.
In 2019, Eva moved to Oxford as a Professor of Health Data Epidemiology within the Big Data Institute and the Nuffield Department of Population Health. Here she continues to work in the field of health data research with a continued interest in national cancer datasets.
Recent publications
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Socioeconomic inequalities of Long COVID: a retrospective population-based cohort study in the United Kingdom
Journal article
Shabnam S. et al, (2023), Journal of the Royal Society of Medicine, 014107682311683 - 014107682311683
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Immortal-time bias in older vs younger age groups: a simulation study with application to a population-based cohort of patients with colon cancer.
Journal article
Pilleron S. et al, (2023), Br J Cancer
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Germline mismatch repair (MMR) gene analyses from English NHS regional molecular genomics laboratories 1996-2020: development of a national resource of patient-level genomics laboratory records.
Journal article
Loong L. et al, (2022), J Med Genet
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BLOod Test Trend for cancEr Detection (BLOTTED): protocol for an observational and prediction model development study using English primary care electronic health records data
Journal article
Virdee PS. et al, (2022), Diagnostic and Prognostic Research
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Age-related differences in cancer relative survival in the US: a SEER-18 analysis
Preprint
Withrow D. et al, (2022)