CO-CONNECT: COVID - Curated and Open aNalysis aNd rEsearCh plaTform

Lead Research Organisation: University of Nottingham
Department Name: School of Computer Science

Abstract

CO-CONNECT is a collaborative project and it has four CO-PIs: Jefferson (Dundee), Sheikh (Edinburgh), Hopkins (PHE) and Quinlan (Nottingham).

The current COVID-19 pandemic has caused hundreds of thousands of deaths, severely strained health systems and damaged economies across the world. At this time there is limited evidence that people who have recovered from COVID-19 and have antibodies are protected from a second infection and if so, how long that lasts. Understanding who is immune is vital to protect vulnerable individuals, to safely scale back population-based interventions and for managing disease transmission.
The data which can help us to answer these key questions have been collected across the UK by a range of research groups and within clinical primary and secondary care settings. As this is a new disease, the standards for antibody data capture are in their infancy so some of the details need to answer the key questions are not being captured systematically. The fragmented landscape of data means that it can be challenging for public health groups and researchers to find and access the high-quality data they need at pace.
We will:
- Standardise antibody data collection across the UK
- Configure an infrastructure which enables trustworthy, fast, de-identified, secure analysis of data sets from across multiple sources
- Answer key questions about immunity to COVID-19 and the implications for patient outcomes.

Technical Summary

CO-CONNECT is a collaborative project and it has four CO-PIs: Jefferson (Dundee), Sheikh (Edinburgh), Hopkins (PHE) and Quinlan (Nottingham).

The UK has rich, globally important COVID-19 datasets, including large serology cohort studies funded by UKRI, Wellcome, DHSC/NHS, NIHR and the devolved administrations. However, this breadth of data creates a risk of fragmentation, inconsistent structure and access processes, severely limiting utility, timeliness and impact.

Our vision is to transform UK COVID-19 diagnostic datasets to be Findable, Accessible, Interoperable and Reusable (FAIR) and couple this with expert data engineering, enabled by Health Data Research (HDR) UK, to catalyse responsible and trustworthy use of the data for research and innovation.

We propose to support PIs and data custodians to link COVID-19 cohort, serology and other health and non-health datasets. This longitudinal linkage is vital to derive new scientific insights and deliver informed decisions about how best to control the spread of SARS-CoV-2. At present there are >30 independent studies with no streamlined approach to linkage to other health and non-health related datasets, lack of data standardisation, and no strategic approach to synthesise analyses across studies.

SAGE (9th June) requested HDR to work with partners to develop the UK-wide serology and testing data research asset that is linkable to other data sources.

This proposal has been prepared in response to this request. We have bought together 41 leaders from 29 different organisations and 44 data sources to address a major data engineering challenge by building upon existing UKRI investments, including the HDR BREATHE Hub, to create a 'one-stop' service for trustworthy, multi-stakeholder utilisation of curated COVID-19 data for public, private and third sector benefit.

People

ORCID iD

Philip Quinlan (Principal Investigator)
Ian Hall (Co-Investigator)
Susan Hopkins (Co-Investigator) orcid http://orcid.org/0000-0001-5179-5702
Ana Valdes (Co-Investigator) orcid http://orcid.org/0000-0003-1141-4471
Amir Gander (Co-Investigator)
David Vincent Ford (Co-Investigator)
Gerry Reilly (Co-Investigator) orcid http://orcid.org/0000-0003-1427-3598
Tim Gentry (Co-Investigator) orcid http://orcid.org/0000-0001-8486-5797
Charlotte Manisty (Co-Investigator) orcid http://orcid.org/0000-0003-0245-7090
Malcolm Gracie Semple (Co-Investigator) orcid http://orcid.org/0000-0001-9700-0418
Shamez Ladhani (Co-Investigator)
Emma Lawrence (Co-Investigator) orcid http://orcid.org/0000-0001-9018-6010
Susheel Varma (Co-Investigator)
Emily Jefferson (Co-Investigator) orcid http://orcid.org/0000-0003-2992-7582
John Danesh (Co-Investigator)
Laura Shallcross (Co-Investigator) orcid http://orcid.org/0000-0003-1713-2555
Aziz Sheikh (Co-Investigator)
Declan Terence Bradley (Co-Investigator) orcid http://orcid.org/0000-0003-1468-1823
Andrew David Morris (Co-Investigator)
Jessica Mai Sims (Co-Investigator)
Katie Jeffery (Co-Investigator) orcid http://orcid.org/0000-0002-6506-2689
Paul Moss (Co-Investigator)
Victoria Chico (Co-Investigator)
Louis Grandjean (Co-Investigator)
Emanuele Di Angelantonio (Co-Investigator)
Simon Thompson (Co-Investigator)
Nicholas John Timpson (Co-Investigator)
James D Chalmers (Co-Investigator)
Joanne Martin (Co-Investigator)
Neil Sebire (Co-Investigator)
Jim McMenamin (Co-Investigator)
David Robert Seymour (Co-Investigator) orcid http://orcid.org/0000-0003-4194-2056
Kenny Baillie (Co-Investigator)
David Wells (Co-Investigator)
Ming Tang (Co-Investigator)
Benjamin Ollivere (Co-Investigator) orcid http://orcid.org/0000-0002-1410-1756
Daniel Morales (Co-Investigator)
Paul Elliott (Co-Investigator) orcid http://orcid.org/0000-0002-7511-5684
Tom Charles Giles (Researcher)
Roberto Santos (Researcher) orcid http://orcid.org/0000-0003-1333-2605

Publications

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