Wellcome Open Research (Dec 2021)

Extended Cohort for E-health, Environment and DNA (EXCEED) COVID-19 focus [version 1; peer review: 2 approved]

  • Paul H. Lee,
  • Altaf Ali,
  • Anna L. Guyatt,
  • Manish Pareek,
  • Alexander T. Williams,
  • Xueyang Wang,
  • Chiara Batini,
  • Bo Zhao,
  • Emma Adams,
  • Catherine Bee,
  • Ron Hsu,
  • Christopher E. Brightling,
  • Nicola Reeve,
  • Jane Bethea,
  • Sarah Terry,
  • Ioanna Ntalla,
  • Julian Barwell,
  • Nigel J. Brunskill,
  • Jose Miola,
  • Edward J. Hollox,
  • David J. Shepherd,
  • Susan E. Wallace,
  • Louise V. Wain,
  • Laura Venn,
  • Richard Packer,
  • Martin D. Tobin,
  • Robert C. Free,
  • Carl A. Melbourne,
  • Catherine John

Journal volume & issue
Vol. 6

Abstract

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Background: New data collection in established longitudinal population studies provides an opportunity for studying the risk factors and sequelae of the novel coronavirus disease 2019 (COVID-19), plus the indirect impacts of the COVID-19 pandemic on wellbeing. The Extended Cohort for E-health, Environment and DNA (EXCEED) cohort is a population-based cohort (N>11,000), recruited from 2013 in Leicester, Leicestershire and Rutland. EXCEED includes consent for electronic healthcare record (EHR) linkage, spirometry, genomic data, and questionnaire data. Methods: Between May 2020 and July 2021, a new questionnaire was deployed in EXCEED, which captured COVID-19 symptoms, general physical and mental health, plus socioeconomic and environmental factors during the pandemic. An online system was developed to invite new participants to join EXCEED, with informed consent being provided online. New and existing participants then completed the COVID-19 questionnaire online. A subset of the new questionnaire respondents were invited to participate in COVID-19 serology substudies, using home antibody testing kits. Results: In total, 3,693 participants provided COVID-19 infection status (median age 62.9 (IQR 54.7-69.2), 58.9% female). Trends of monthly incidence proportions of COVID-19 in EXCEED (self-report or symptom-predicted) approximated local and national figures. Regression analysis of 2,768 participants with linked EHR data showed no obvious monotonic relationship between number of chronic diseases (of 16 pre-specified diseases) and COVID-19 infection. There were 2,144 participants with valid results from a kit allowing differentiation between antibodies due to vaccination or infection. Of these, 8.5% had results consistent with previous COVID-19 infection, and 85.9% had evidence of COVID-19 vaccination, but without evidence of infection. Conclusions: Enriching EXCEED with a new COVID-19 questionnaire and serology data may improve understanding of the risk factors, clinical sequelae and broader impacts of the COVID-19 pandemic in the general population. Controlled access to these data for bona fide researchers is via application to the EXCEED study.

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