Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions
Ashley Akbari,
Chris Davies,
Ann John,
Simon Thompson,
Ronan Lyons,
Sinead Brophy,
Tamas Szakmany,
Amy Mizen,
Richard Fry,
Rowena Griffiths,
Jan Davies,
Gareth John,
Peter Diggle,
Chris Orton,
James Rafferty,
Christopher Williams,
Jane Lyons,
Fatemeh Torabi,
Gareth I Davies,
Laura North,
Rowena Bailey,
Joseph Hollinghurst,
Samantha L Turner,
Daniel Thompson,
Lee Au-Yeung,
Lynsey Cross,
Mike B Gravenor,
Biagio Lucini,
Daniel Rh Thomas,
Chris Emmerson,
Simon Cottrell,
Thomas R Connor,
Chris Taylor,
Richard J Pugh,
Simon Scourfield,
Joe Hunt,
Anne M Cunningham,
Kathryn Helliwell
Affiliations
Ashley Akbari
Population Data Science, Swansea University Medical School, Swansea, UK
Chris Davies
3 Institute for Clinical Science and Technology, Cardiff, UK
Ann John
Population Data Science, Swansea University Medical School, Swansea, UK
Simon Thompson
Population Data Science, Swansea University Medical School, Swansea, UK
Ronan Lyons
School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
Sinead Brophy
National Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, UK
Tamas Szakmany
9 Critical Care Directorate, Aneurin Bevan University Health Board, Newport, UK
Amy Mizen
Population Data Science, Swansea University Medical School, Swansea, UK
Richard Fry
Population Data Science, Swansea University Medical School, Swansea, UK
Rowena Griffiths
Population Data Science, Swansea University Medical School, Swansea, UK
Jan Davies
Patient and public representatives, UK
Gareth John
7 NHS Wales Informatics Service, Cardiff, UK
Peter Diggle
Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, UK
Chris Orton
Population Data Science, Swansea University Medical School, Swansea, UK
James Rafferty
2 Population Data Science, Swansea University Medical School, Swansea, UK
Christopher Williams
Public Health Wales, Communicable Disease Surveillance Centre, Cardiff, UK
Jane Lyons
School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
Fatemeh Torabi
Population Data Science, Swansea University Medical School, Swansea, UK
Gareth I Davies
Population Data Science, Swansea University Medical School, Swansea, UK
Laura North
Population Data Science, Swansea University Medical School, Swansea, UK
Rowena Bailey
2 Population Data Science, Swansea University Medical School, Swansea, UK
Joseph Hollinghurst
Population Data Science, Swansea University Medical School, Swansea, UK
Samantha L Turner
Population Data Science, Swansea University Medical School, Swansea, UK
Daniel Thompson
Independent Statistical Consultant, Tallahassee, Florida, USA
Lee Au-Yeung
Population Data Science, Swansea University Medical School, Swansea, UK
Lynsey Cross
Population Data Science, Swansea University Medical School, Swansea, UK
Mike B Gravenor
Swansea University Medical School, Swansea University, Swansea, UK
Biagio Lucini
Population Data Science, Swansea University Medical School, Swansea, UK
Daniel Rh Thomas
Communicable Disease Surveillance Centre, Public Health Wales, Cardiff, UK
Chris Emmerson
Public Health Wales NHS Trust, Cardiff, Cardiff, UK
Simon Cottrell
consultant medical epidemiologist
Thomas R Connor
School of Biosciences, Cardiff University, Cardiff, South Glamorgan, UK
Chris Taylor
School of Social Sciences, Cardiff University, Cardiff, South Glamorgan, UK
Richard J Pugh
Glan Clwyd Hospital, Betsi Cadwaladr University Health Board, Rhyl, UK
Introduction The emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions.Methods and analysis Two privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection.Ethics and dissemination The Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.
