Unraveling Social Health Inequalities during COVID-19 in Belgium: The Vital Role of Data Linkages

Abstract Background During the COVID-19 crisis, data linkages were set up to efficiently monitor the outbreak and identify vulnerable population groups. Yet, considerable technical, administrative and data security issues have hindered the effectiveness of data linkages as a critical instrument during public health emergencies. This workshop aims to provide a practical demonstration of the challenges encountered in a Belgian data linkage during the COVID-19 crisis, along with the strategies implemented to overcome these challenges. This case study offers insights into the development of a highly sensitive linkage between COVID-19 hospital data and information related to social and health use in Belgium. Methods The HELICON data linkage is developed at the individual level to investigate the risk of COVID-19 hospitalization and the influence of various social and biomedical factors during and after the crisis. Data are drawn from data collections on hospitalization from the COVID-19 health surveillance (Sciensano), on the socioeconomic and sociodemographic context (Statistics Belgium), and on healthcare use and reimbursement (InterMutualistic Agency). Results A representative case-cohort study is established comprising 1,149,264 million randomly selected Belgians and 44,508 hospitalized patients. Annual follow-up is scheduled over a four-year span, allowing the investigation of pre- and post-pandemic health data from July 2020 to January 2026. Conclusions The HELICON data linkage took 3.5 years to complete. Among the many challenges, we were faced with complicated approval procedures, ambiguous data security guidelines, unclear cost estimates, and technical issues related to the analysis environment. Building on these experiences, we explore the strengths and weaknesses of data linkages as a research instrument during the COVID-19 pandemic and discuss which lessons should be drawn to for the post-pandemic era.