QCovid algorithm to help identify those at high risk from COVID-19
More people in England at high risk from COVID-19 will get priority access to vaccines thanks to new technology 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 (including Usher Institute Director, Professor Aziz Sheikh and Head of the Usher Institute's Centre for Medical Informatics, Professor Ewen Harrison), 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 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. The research to develop and validate the model is published in the British Medical Journal along with the underlying model for transparency. This will be updated to take account of new information as the pandemic progresses. 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.
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, which was supported by the NIHR Oxford Biomedical Research Centre, was commissioned by England’s Chief Medical Officer, Prof Chris Whitty. 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.
More people added to the shielding list
NHS Digital has now used this model to develop a population risk assessment. The risk assessment predicts on a population basis whether registered patients with a combination of risk factors may be at more serious risk from COVID-19, enabling the government to prioritise them for vaccination, and provide appropriate advice and support.
These individuals will be added to the shielded patient list on a precautionary basis and to enable rapid vaccination.
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.
Oxford-led technology to help those at high risk from Covid-19 - NIHR Oxford Biomedical Research Centre News
QCovid: how improved algorithm can identify more higher-risk adults in The Guardian
External validation by ONS pre-print