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Social inequalities and long-term health impact of COVID-19 in Belgium: protocol of the HELICON population data linkage

  • Robbie De Pauw
  • , Laura Van den Borre
  • , Bayens Yoeri
  • , Lisa Cavillot
  • , Sylvie Gadeyne
  • , Jinane Ghattas
  • , Delphine De Smedt
  • , David Jaminé
  • , Yasmine Patricia Khan
  • , Patrick Lusyne
  • , Niko Speybroeck
  • , Judith Racapé
  • , Andrea Rea
  • , Dieter van Cauteren
  • , Sophie Vandepitte
  • , Katrien Vanthomme
  • , Brecht Devleeschauwer

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
24 Downloads (Pure)

Abstract

Introduction Data linkage systems have proven to be a powerful tool in support of combating and managing the COVID-19 pandemic. However, the interoperability and the reuse of different data sources may pose a number of technical, administrative and data security challenges.

Methods and analysis This protocol aims to provide a case study for linking highly sensitive individual-level information. We describe the data linkages between health surveillance records and administrative data sources necessary to investigate social health inequalities and the long-term health impact of COVID-19 in Belgium. Data at the national institute for public health, Statistics Belgium and InterMutualistic Agency are used to develop a representative case-cohort study of 1.2 million randomly selected Belgians and 4.5 million Belgians with a confirmed COVID-19 diagnosis (PCR or antigen test), of which 108 211 are COVID-19 hospitalised patients (PCR or antigen test). Yearly updates are scheduled over a period of 4 years. The data set covers inpandemic and postpandemic health information between July 2020 and January 2026, as well as sociodemographic characteristics, socioeconomic indicators, healthcare use and related costs. Two main research questions will be addressed. First, can we identify socioeconomic and sociodemographic risk factors in COVID-19 testing, infection, hospitalisations and mortality? Second, what is the medium-term and long-term health impact of COVID-19 infections and hospitalisations? More specific objectives are (2a) To compare healthcare expenditure during and after a COVID-19 infection or hospitalisation; (2b) To investigate long-term health complications or premature mortality after a COVID-19 infection or hospitalisation; and (2c) To validate the administrative COVID-19 reimbursement nomenclature. The analysis plan includes the calculation of absolute and relative risks using survival analysis methods.

Original languageEnglish
Article numbere069355
Pages (from-to)1-9
Number of pages9
JournalBMJ Open
Volume13
Issue number5
DOIs
Publication statusPublished - May 2023

Bibliographical note

Publisher Copyright:
© 2023 BMJ Publishing Group. All rights reserved.

Keywords

  • Social inequalities, health impact COVID-19, data linkage protocol HELICON

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