Expanding on the incredible work of the UK health research community in supporting policy makers to understand and respond to COVID-19, Health Data Research UK (HDR UK) and The Alan Turing Institute are working in partnership with research teams across the UK to support nine new research projects that tackle ongoing, urgent questions about the virus and support future pandemic preparedness.
The nine projects will be delivered by 16 collaborating universities across Scotland, England, Northern Ireland, and Wales.
The Oxford project is led by Sara Khalid, University Research Lecturer and Senior Research Associate in Biomedical Data Science at NDORMS.
Funded by UK Research and Innovation (UKRI), the project will ask:
- What are the biases in ethnicity data and how can they be avoided?
- What are the differences in risk factors for severe disease between ethnic groups?
- Can we use data science and machine learning to predict which patients are at increased risk of hospitalisation following COVID-19 infection?
Sara Khalid said: "We know there are inequalities in healthcare and patient outcomes between ethnic groups and the COVID-19 pandemic has highlighted the problem. Health technology can predict a person's future health risk but any biases in the data and models could lead to patients ultimately getting the wrong care or no care. Working with routinely collected data from around the UK and by building ethnicity-specific models, we hope to tackle some of these underlying biases. By doing so we hope to move towards realistic, reproducible and representative models that are suitable and fair for all ethnicities to guide better care for COVID-19 patients."
The other funded projects include:
- What impact will disruption to healthcare services have on health outcomes, and what will be the patterns of healthcare use in children and young people following COVID-19 infection?
- What is the impact of the COVID-19 pandemic on outcomes in patients with Long Term Conditions?
- What are the effects of COVID-19, vaccinations and "booster doses" in pregnancy, among children and young people, and on disease caused by different variants?
The projects will use advanced analytics, modelling, statistical and machine learning techniques; utilising and developing the data infrastructure that has been rapidly enabled for research into COVID-19. In partnership with the network of Trusted Research Environments (TREs) in England, Northern Ireland, Scotland and Wales, researchers will be able to access large-scale, national and linked datasets in secure environments, including viral variant and genomic sequencing data, outbreak-relevant data from clinical records, vaccination data including vaccine status and adverse events across the UK.
Successful projects had to demonstrate the proposed benefits to patients and the public in their application. Dr Laura Coates, NIHR clinician scientist, senior clinical research fellow, and co-investigator on the study said: “Patients and their health outcomes are at the heart of this project, so patient and public involvement (PPI) is an integral and exciting element of this study. Through our PPI group, OPEN ARMS, and through our collaboration with the Centre for Ethnic Health Research in Leicester, patient representatives will help us interpret our results moving towards minimising bias in ethnicity data.”
Sir Patrick Vallance, Government Chief Scientific Adviser said: "The ability to link large scale health datasets across the four nations is crucial and has enabled vital insights into COVID-19 since the National Core Studies were established. This programme will take the use of this data to the next level as we continue to improve our understanding of this virus".
The research is part of the COVID-19 Data and Connectivity programme, one of the National Core Studies, co-sponsored by UK Research and Innovation (UKRI), National Institute for Health Research (NIHR) and the Government Office for Science.
Other co-investigators from NDORMS, Antonella Delmestri, Daniel Prieto-Alhambra, and Gary Collins, will be working alongside Professor Kamlesh Kunti from the University of Leicester and Professor Irene Petersen from UCL.