Your browser doesn't support javascript.
Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions.
Lyons, Jane; Akbari, Ashley; Torabi, Fatemeh; Davies, Gareth I; North, Laura; Griffiths, Rowena; Bailey, Rowena; Hollinghurst, Joseph; Fry, Richard; Turner, Samantha L; Thompson, Daniel; Rafferty, James; Mizen, Amy; Orton, Chris; Thompson, Simon; Au-Yeung, Lee; Cross, Lynsey; Gravenor, Mike B; Brophy, Sinead; Lucini, Biagio; John, Ann; Szakmany, Tamas; Davies, Jan; Davies, Chris; Thomas, Daniel Rh; Williams, Christopher; Emmerson, Chris; Cottrell, Simon; Connor, Thomas R; Taylor, Chris; Pugh, Richard J; Diggle, Peter; John, Gareth; Scourfield, Simon; Hunt, Joe; Cunningham, Anne M; Helliwell, Kathryn; Lyons, Ronan.
  • Lyons J; Population Data Science, Swansea University Medical School, Swansea, UK j.lyons@swansea.ac.uk.
  • Akbari A; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Torabi F; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Davies GI; Population Data Science, Swansea University Medical School, Swansea, UK.
  • North L; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Griffiths R; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Bailey R; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Hollinghurst J; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Fry R; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Turner SL; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Thompson D; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Rafferty J; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Mizen A; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Orton C; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Thompson S; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Au-Yeung L; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Cross L; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Gravenor MB; Institute of Life Sciences, Swansea University Medical School, Swansea, UK.
  • Brophy S; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Lucini B; Population Data Science, Swansea University Medical School, Swansea, UK.
  • John A; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Szakmany T; Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff, UK.
  • Davies J; Aneurin Bevan University Health Board, Newport, UK.
  • Davies C; Members of the public, Swansea, UK.
  • Thomas DR; Members of the public, Swansea, UK.
  • Williams C; Public Health Wales NHS Trust, Cardiff, Cardiff, UK.
  • Emmerson C; Public Health Wales NHS Trust, Cardiff, Cardiff, UK.
  • Cottrell S; Public Health Wales NHS Trust, Cardiff, Cardiff, UK.
  • Connor TR; Public Health Wales NHS Trust, Cardiff, Cardiff, UK.
  • Taylor C; School of Biosciences, Cardiff University, Cardiff, South Glamorgan, UK.
  • Pugh RJ; School of Social Sciences, Cardiff University, Cardiff, South Glamorgan, UK.
  • Diggle P; Glan Clwyd Hospital, Betsi Cadwaladr University Health Board, Rhyl, UK.
  • John G; Faculty of Health and Medicine, Lancaster University, Lancaster, Lancashire, UK.
  • Scourfield S; Epidemiology and Population Health, University of Liverpool, Liverpool, Merseyside, UK.
  • Hunt J; NHS Wales Informatics Service, Cardiff, Wales, UK.
  • Cunningham AM; NHS Wales Informatics Service, Cardiff, Wales, UK.
  • Helliwell K; NHS Wales Informatics Service, Cardiff, Wales, UK.
  • Lyons R; NHS Wales Informatics Service, Cardiff, Wales, UK.
BMJ Open ; 10(10): e043010, 2020 10 21.
Article in English | MEDLINE | ID: covidwho-889902
ABSTRACT

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.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Delivery of Health Care / Pandemics / Betacoronavirus Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: Europa Language: English Journal: BMJ Open Year: 2020 Document Type: Article Affiliation country: Bmjopen-2020-043010

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Delivery of Health Care / Pandemics / Betacoronavirus Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: Europa Language: English Journal: BMJ Open Year: 2020 Document Type: Article Affiliation country: Bmjopen-2020-043010