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Dynamic linkage of COVID-19 test results between Public Health England’s Second Generation Surveillance System and UK Biobank

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posted on 19.04.2020, 20:24 by Jacob Armstrong, Justine Rudkin, Naomi Allen, Derrick Crook, Daniel WilsonDaniel Wilson, David Wyllie, Anne-Marie O'Connell

UK Biobank is an international health resource enabling research into the genetic and lifestyle determinants of common diseases of middle and older age. It comprises 500,000 participants. Public Health England’s Second Generation Surveillance System is a centralized microbiology database covering English clinical diagnostics laboratories that provides national surveillance of legally notifiable infections, bacterial isolations and antimicrobial resistance. We previously developed secure, anonymized, individual-level linkage of these systems. In this study, we implemented rapid dynamic linkage, which allows us to provide a regular feed of new COVID-19 (SARS-CoV-2) test results to UK Biobank to facilitate rapid and urgent research into the epidemiological and human genetic risk factors for severe infection in the cohort. Here, we have characterized the first 678 cases of COVID-19 in UKB participants, of whom 552 met our working definition of severe COVID-19 as inpatients hospitalized on or after 16 March 2020. We found that the incidence of severe COVID-19 among UKB cases was 27.1% lower than the general population in England, although this difference varied significantly by age and sex. The total number of UKB cases comprised could be estimated as 0.9% of the publicly announced number of cases in England. We considered how increasing case numbers will affect the power of genome-wide association studies. This new dynamic linkage system has further potential to facilitate the investigation of other infections and the prospective collection of microbiological cultures to create a microbiological biobank (‘bugbank’) for studying the interaction of environment, human and microbial genetics on infection in the UK Biobank cohort.

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Statistical Methods for Human-Pathogen Genome-Wide Association Studies

Wellcome Trust

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Big Data Institute Robertson Fellowship

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