Recipient organisationImperial College LondonSource-published name: Imperial College of Science, Technology and Medicine
Funding£5.6M
PeriodMar 2021 — Dec 2025
In plain English
AI plain-English summary
More than a million people in the UK have documented SARS-CoV-2 status through repeated random community surveys, and this programme will follow thousands of them to uncover why some develop Long COVID while others do not. Long COVID remains poorly understood. Doctors cannot predict who will get it, why symptoms persist, or how to treat it. The condition affects people who were never hospitalised, making it hard to study through conventional clinic-based approaches. This programme fills that gap by starting with a large, population-representative sample—people tested in the community, not just those sick enough to seek hospital care. If the research succeeds, it will identify biological markers and pathways that drive Long COVID, potentially pointing to drug targets. It will also reveal social and environmental factors—such as housing, work, or access to care—that shape who suffers most. That could lead to better diagnostics, targeted treatments, and policies to reduce inequalities in outcomes. The work is applied: it aims directly at improving diagnosis and care for a condition that currently has no proven treatment or clear clinical pathway.
View original technical description
The REACT-Long COVID (REACT-LC) programme aims to characterise the genetic, biological, social and environmental signatures and pathways, and their inter-relationships, that underpin progression to Long COVID, and to understand the natural history and long-term sequelae post-SARS-CoV-2 infection. To identify people with persistent symptoms who have not been hospitalised, we will use a sampling frame generated through repeated random population surveys of SARS-CoV-2 prevalence in the community, the REACT programme, which includes >1.5 million individuals with documented SARS-CoV-2 status (RT-PCR or lateral flow test), including >30,000 with positive tests, 90% of whom have consented to be re-contacted and 85% to data linkage. The research is to be delivered through five integrated work packages (WPs). WP1 will describe variations in experience of Long COVID and develop patient reported outcomes (PROMS) in consultation with expert collaborators and through our patient and public partners. We will use online focus groups, discussion forums, individual interviews, and surveys on the VOICE-Global platform, and recruit a panel of people with Long COVID to provide input on their symptoms and experience. In WP2 we will carry out detailed clinical phenotyping on 8,000 people (4,000 with Long COVID); 2,000 will have repeat measures at 4-6 months including 400 for T-cell function. The WP2 samples will be used in WP3 which includes multi-omic analysis, brain and inflammatory biomarkers. WP4 will use data from surveys sent to 30,000 test-positive and 90,000 test-negative on RT-PCR/lateral flow in REACT, plus linked health data, to explore the social and environmental determinants of Long COVID and its long-term sequelae. WP5 is the data analysis and integration to identify genetic, biological, social and environmental determinants of Long COVID. We aim to identify key biomarkers and biological pathways underlying Long COVID and possible drug targets, as well as inequalities and social determinants of variations in outcome.
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