QCovid® risk calculator

QCovid® was developed as a model to estimate a person’s risk of being hospitalised or dying due to catching coronavirus.

The QCovid® tool below may be used for academic research or for peer review in Great Britain only. Before using the tool, please make sure your organisation has a Data Protection Impact Assessment (DPIA) in place that covers your use of the tool.

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University of Oxford

More details about QCovid®

QCovid® was used by NHS Digital to identify patients in England at high risk of severe COVID-19 outcomes, adding an additional 1.7 million people to the national shielded patient list in February 2021 and prioritising them for vaccination.

NHS Digital

How QCovid® was developed?

QCovid® was commissioned in 2020 by the Chief Medical Officer for England on behalf of the UK government. The first QCovid® tool was developed using the QResearch database hosted at Oxford. This database has anonymised data from GP and hospital records, COVID-19 test results and death registries. Factors such as age and medical conditions which were found to increase risk relating to coronavirus were used to build a risk prediction model. The model, QCovid®, estimates someone’s combined risk of catching coronavirus and being admitted to hospital and their combined risk of catching coronavirus and dying.

The tool has now been updated to include factors such as vaccination status and prior infection. There is a need to identify those at highest risk of severe outcomes if infected with COVID-19, even if individuals are vaccinated.

The model was tested to find out whether it accurately predicted severe outcomes due to COVID-19 during the first wave of the pandemic in England. More recently, it has been updated and tested in subsequent pandemic waves with the most recent version tested on individuals with a positive COVID-19 test between December 2021 and June 2022.

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. See publication page for latest research

Photo of Professor Julia Hippisley-Cox

The Team

The research team is led by Professor Julia Hippisley-Cox at the University of Oxford

The QCovid team includes researchers from:

  • University of Nottingham
  • London School of Hygiene & Tropical Medicine,
  • University of Leicester,
  • Swansea University,
  • Queen's University Belfast,
  • University of Edinburgh,
  • Department of Health and Social Care,
  • NHS England and Improvement,
  • Queen Mary University of London,
  • University of Liverpool,
  • University College London,
  • NHSx and
  • NHS Digital.

Request a licence

QCovid.org is available for free to be used in Great Britain, for academic research and peer review purposes. To request a licence for any other use or to request use of the Calculation Engine code please contact us via email with details of with details of your requirements.


The team are proud to have been recognised for the contribution of QCovid® to healthcare in the UK.

Royal Statistical Society, Supported by The Health Foundation - Florence Nightingale Award for Excellence in Healthcare Data Analytics - Winner: COVID19 Population Risk Assessment, powered by QCOVID® - The COVID-19 Population Risk Assessment team

QCovid® won the Florence Nightingale Award in July 2021. Read more on the Royal Statistical Society website.

bcs The Chartered Institute for IT - Primary Health Care Specialist Group

QCovid® was awarded the John Perry Prize in October 2021. www.phcsg.org

PATIENT SAFETY AWARDS 2021 - WE ARE PROUD TO BE HIGHLY COMMENDED - Best use of technology in patient safety award

QCovid® received Highly Commended in the category of “Best use of technology in patient safety” by the Patient Safety Awards 2021. https://awards.patientsafetycongress.co.uk/winners-2021

RCGP - Royal College of General Practitioners

RCGP paper of the year.