A NEW model has been shown to accurately predict a person’s risk of becoming infected and then seriously ill due to Covid-19.
The algorithm, developed using routine anonymised data from more than eight million adults in 1,205 general practices across England, calculates risk based on factors such as age, ethnicity and existing medical conditions.
The model, developed with input from researchers at Edinburgh University, has the potential to provide doctors and the public with more nuanced information about risk of serious illness due to Covid-19, and the sorts of preventative measures people can take in their daily lives.
Researchers at Oxford University with collaborators across the UK used anonymous data from primary care, hospitals, Covid-19 test results, and death registries to determine which factors were associated with poor outcomes during the first wave of the pandemic.
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This data was used to create the 'QCovid' tool which provides a weighted, cumulative calculation of risk based on factors including age, sex, ethnicity, level of deprivation, obesity, whether someone lived in residential care or was homeless, and a range of existing medical conditions, such as cardiovascular disease, diabetes, respiratory disease and cancer.
The QCovid algorithm was then tested in two independent sets of anonymised data, from January to April 2020 and 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 research results, published today in the British Medical Journal, showed that those in the top 20 per cent for predicted risk of death accounted for 94% of Covid mortality.
Lead researcher Professor Julia Hippisley-Cox, a GP and professor of clinical epidemiology, said: “Risk assessments to date have been based on the best evidence and clinical expertise, but have focused largely on single factors.
"The QCovid risk model provides a much more nuanced assessment of risk by taking into account a number of different factors that are cumulatively used to estimate risk.
“This model will help inform clinical advice so that people can take proportionate precautions to protect themselves from Covid-19.”
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The researchers plan to regularly update their model as levels of immunity change and more data on the disease becomes available.
The research was funded by the National Institute for Health Research (NIHR) and commissioned by the Chief Medical Officer for England.
Deputy CMO for England Dr Jenny Harries said: “Continuing to improve our understanding of the virus and how it affects different members of the population is vital as prevalence continues to rise.
“This is why we commissioned and funded this research, and I’m pleased it is providing useful.”
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