QCovid® risk calculator

An evidence-based model that uses a range of factors such as age, sex, ethnicity and existing medical conditions to predict risk of death or hospitalisation from COVID-19.

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University of Oxford
Warning:

PLEASE NOTE: This implementation of the QCovid risk calculator is NOT intended for use supporting or informing clinical decision-making. It is ONLY to be used for academic research, peer review and validation purposes, and it must NOT be used with data or information relating to any individual. For full terms and conditions please see the Academic Licence. For any other use cases, please contact enquiries@innovation.ox.ac.uk quoting reference 17939.

QCovid® has been produced to provide doctors and the public with more nuanced information about risk of serious illness due to COVID-19, and to help patients and doctors reach a shared understanding of risk, within the context of individual circumstances, risk attitude and the sorts of preventative measures people can take in their daily lives.

QCovid® was used by NHS Digital in England to identify patients at high risk of severe COVID-19 outcomes, adding an additional 1.5 million people to the national shielded patient list in February 2021 and prioritising them for vaccination.

About the model

QCovid® was commissioned in 2020 by the Chief Medical Officer for England. The first QCovid® tool was developed using the QResearch database hosted at Oxford. This database has anonymised data from primary care, hospitals, COVID-19 test results and death registries which was used to determine factors that were associated with poor outcomes during the first wave of COVID-19 and create a risk prediction model. QCovid® provides a weighted, cumulative calculation of absolute risk using the variables associated with poor COVID-19 outcomes.

The tool has now been updated to include factors such as vaccination status.There is a need to identify those at highest risk of severe outcomes if infected with COVID-19, even if individuals are vaccinated. QCovid® could be used to prioritise individuals for early interventions or booster vaccinations where appropriate.

The first model was tested in two independent sets of data, one from January to April 2020 and one from May 2020 to June 2020, to find out whether it accurately predicted severe outcomes due to COVID-19 during the first wave of the pandemic in England.

The newer model was tested on vaccinated individuals with one or two doses between December 2020 and June 2021.

The research, published in the BMJ, showed that the model performed well in predicting severe outcomes due to COVID-19 (death and hospitalisation) in both models.

Photo of Professor Julia Hippisley-Cox

The Team

The research team is led by Professor Julia Hippisley-Cox at the University of Oxford and includes researchers from the universities of Edinburgh, Swansea, Leicester, Nottingham and Liverpool with the London School of Hygiene & Tropical Medicine, Queen's University Belfast, Queen Mary University of London, University College London, the Department of Health and Social Care, NHS Digital, NHSx and NHS England.

Request a licence

QCovid.org is available for free to be used for academic and peer review purposes. To request a licence for any other use please contact us via email with details of your requirements.

The contribution of QCovid® to healthcare in the UK has been recognised by the Royal Statistical Society . The Covid-19 Population Risk Assessment, powered by QCovid® was awarded the Florence Nightingale Award for Excellence in Healthcare Data Analytics by the RSS in July 2021.