Professor Amitava Banerjee has a major research portfolio (9 grants as principal investigator: total £8.8 million, and 9 grants as co-investigator (responsible for £1.4 million of a total £26 million) for cardiovascular diseases individually and overall, from risk prediction to personalised management. Professor Banerjee’s research interests span health informatics, learning health systems, cardiovascular epidemiology, global health, training and evidence-based healthcare. Banerjee Lab applies data science to improve knowledge and care of cardiovascular disease (CVD) through epidemiology, informatics and global health approaches to aid clinical practice, address public health needs and answer policy questions.

The work he has been leading throughout the pandemic encompasses epidemiology, clinical medicine and data science to tackle the pressing clinical and public health issues, whether how best to predict and communicate mortality risk, or how best to define and prevent organ-specific complications of long Covid. Notable publications include:

Identifying subtypes of heart failure from three electronic health record sources with machine learning: an external, prognostic, and genetic validation study (Lancet Digital Health)

A population-based study of 92 clinically recognized risk factors for heart failure: co-occurrence, prognosis and preventive potential. (European Journal of Heart Failure)

Prevalence, incidence, and outcomes across cardiovascular diseases in homeless individuals using national linked electronic health records. (European Heart Journal)

Risk of death following COVID-19 vaccination or positive SARS-CoV-2 test in young people in England. (Nature Communications)

Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic. (European Journal of Preventive Cardiology)

Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study. (Lancet)

Awards received

UCL Faculty Education Award for outstanding contribution to student education, 2021

RCP Excellence in Patient Care Awards for DATA-CAN, 2021

Impact of the Year, HDR UK, 2020

Team of the Year, HDR UK, 2020