Improvement of population health is underpinned by quantification of disease burden, understanding what causes disease and evaluating interventions to reduce or prevent morbidity. Modern technology has enabled the collection and storage of ever increasing amounts of information, including electronic health records, new types of surveillance data, and data from genetic studies. Availability of these rich data offers unprecedented opportunities to tackle questions of key biomedical and public health importance. However, these conveniently available resources have been collected for other purposes and, therefore, are most likely affected by selection and informative observation biases; and are heterogeneous in type, relevance and granularity. The goal of the SURPH research theme is to capitalise on this wealth of data to contribute to the improvement of population health. We achieve this goal by developing and applying methods to address pressing needs for: principled assessment of disease aetiology in the presence of confounding; robust quantification of disease burden; improvement in healthrelated policy-making.
(Previous theme name: Evidence Synthesis to inform Health – ESH)
Other Research Themes:
- DART: Design and Analysis of Randomised Trials
- SOMX: Statistical Omics
- PREM: Precision Medicine and Inference for Complex Outcomes