Oxford-led technology to help those at high risk from COVID-19


More people in England at high risk from COVID-19 are to get priority access to vaccines thanks to new technology developed by a University of Oxford-led team of researchers that can identify those who may be most vulnerable to the virus.

Research led by Professor Julia Hippisley-Cox in the University of Oxford’s Nuffield Department of Primary Care Health Sciences, with collaborators across the UK, found that there are several health and personal factors which, when combined, could mean someone is at a higher risk from COVID-19. These include characteristics like age, ethnicity and BMI, as well as certain medical conditions and treatments.

The team turned their research into a risk prediction model called QCovid®, which has been independently validated by the Office for National Statistics. It is thought to be the only COVID-19 risk prediction model in the world to meet the highest standards of evidence.

The work was commissioned by England’s Chief Medical Officer Chris Whitty and funded by the National Institute of Health Research. Details of the development and validation of the tool were published in the BMJ, and the model has been fully published for transparency at www.qcovid.org.

NHS Digital have now used this model to develop a population risk assessment. Up to 1.5 million patients have been identified to date. Approximately 700,000 will have already been vaccinated as part of the over-70s cohort, and an additional 800,000 adults between 19 and 69 years will now be prioritised for a vaccination.

Professor Julia Hippisley-Cox, Professor of Clinical Epidemiology and General Practice in the University of Oxford’s Nuffield Department of Primary Care Health Sciences said: ‘The QCovid® model, which has been developed using anonymised data from more than 8 million adults, provides nuanced assessment of risk by taking into account a number of different factors that are cumulatively used to estimate risk including ethnicity. I’m delighted that less than a year after being funded by the NIHR, the model is now being used to help protect people at most risk from COVID-19.’

Fred Kemp, Deputy Head of Life Sciences at Oxford University Innovation, said, ‘As a further example of how the University of Oxford is at the forefront of combatting the pandemic, OUI is proud to have supported the development and implementation of QCovid as a highly validated, evidence-based risk prediction tool that will enable prioritised delivery of vaccines to those most in need.’

Deputy Chief Medical Officer for England Dr Jenny Harries said, ‘For the first time, we are able to go even further in protecting the most vulnerable in our communities. This new model is a tribute to our health and technology researchers. The model’s data-driven approach to medical risk assessment will help the NHS identify further individuals who may be at high risk from COVID-19 due to a combination of personal and health factors. This action ensures those most vulnerable to COVID-19 can benefit from both the protection that vaccines provide, and from enhanced advice, including shielding and support, if they choose it.’

QCovid® was developed using the QResearch database of anonymised electronic health records, a collaboration between Professor Julia Hippisley-Cox’s team in Oxford and primary are computer systems provider EMIS Health.