Improving characterisation, prediction and intervention for COVID- and influenza- related morbidity and mortality
Project led by Professor Amitava Banerjee at University College London, coordinated and supported by Health Data Research UK with funding from the National Institute for Health and Care Research (NIHR).
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This winter, COVID-19, influenza and their indirect effects on chronic disease care for conditions such as cardiovascular disease (CVD) represent the greatest challenges for the NHS. Both COVID-19 and influenza can have direct (e.g. hospitalisation and death), indirect (e.g. reduced number of procedures for CVD care) and longer-term (e.g. Long Covid) health effects. However, we don’t really know what happens when patients have both COVID and influenza together because there has been very little research looking into this.
In this study, researchers will use national electronic health records to explore how COVID-19 and influenza (either or both) affect hospitalisations, new CVD cases, death and Long Covid. The team will first identify the groups with highest risk (e.g. by age, gender, ethnicity, underlying conditions), then seek to understand whether these outcomes can be predicted using underlying risk of CVD and other conditions.
The results will help policy makers understand who should be prioritised for COVID-19 and influenza vaccinations, and whether focused prevention strategies for CVD – such as better treatment for hypertension and following heart attacks or strokes – reduce severe illness and death.