Validating the QCOVID risk prediction algorithm for risk of mortality from COVID-19 in the adult population in Wales, UK

Jane Lyons, Vahé Nafilyan, Ashley Akbari, Gareth Davies, Rowena Griffiths, Ewen M Harrison, Julia Hippisley-Cox, Joe Hollinghurst, Kamlesh Khunti, Laura North, Aziz Sheikh, Fatemeh Torabi, Ronan A Lyons

Research output: Contribution to journalArticlepeer-review


Introduction: COVID-19 risk prediction algorithms can be used to identify at-risk individuals from short-term serious adverse COVID-19 outcomes such as hospitalisation and death. It is important to validate these algorithms in different and diverse populations to help guide risk management decisions and target vaccination and treatment programs to the most vulnerable individuals in society.

Objectives: To validate externally the QCOVID risk prediction algorithm that predicts mortality outcomes from COVID-19 in the adult population of Wales, UK.

Methods: We conducted a retrospective cohort study using routinely collected individual-level data held in the Secure Anonymised Information Linkage (SAIL) Databank. The cohort included individuals aged between 19 and 100 years, living in Wales on 24th January 2020, registered with a SAIL-providing general practice, and followed-up to death or study end (28th July 2020). Demographic, primary and secondary healthcare, and dispensing data were used to derive all the predictor variables used to develop the published QCOVID algorithm. Mortality data were used to define time to confirmed or suspected COVID-19 death. Performance metrics, including R2 values (explained variation), Brier scores, and measures of discrimination and calibration were calculated for two periods (24th January-30th April 2020 and 1st May-28th July 2020) to assess algorithm performance.

Results: 1,956,760 individuals were included. 1,192 (0.06%) and 610 (0.03%) COVID-19 deaths occurred in the first and second time periods, respectively. The algorithms fitted the Welsh data and population well, explaining 68.8% (95% CI: 66.9-70.4) of the variation in time to death, Harrell's C statistic: 0.929 (95% CI: 0.921-0.937) and D statistic: 3.036 (95% CI: 2.913-3.159) for males in the first period. Similar results were found for females and in the second time period for both sexes.

Conclusions: The QCOVID algorithm developed in England can be used for public health risk management for the adult Welsh population.

Original languageEnglish
Article number13
Pages (from-to)1697
JournalInternational Journal of Population Data Science
Issue number4
Publication statusPublished - 16 Feb 2022


  • COVID-19 outcomes
  • Population data-linkage
  • QCOVID algorithm
  • Risk prediction models
  • SAIL Databank


Dive into the research topics of 'Validating the QCOVID risk prediction algorithm for risk of mortality from COVID-19 in the adult population in Wales, UK'. Together they form a unique fingerprint.

Cite this