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Data sharing: A Long COVID perspective, challenges, and road map for the future

  • Sunday O. Oladejo*
  • , Liam R. Watson
  • , Bruce W. Watson
  • , Kanshukan Rajaratnam
  • , Maritha J. Kotze
  • , Douglas B. Kell
  • , Etheresia Pretorius
  • *Corresponding author for this work
    • University of Liverpool
    • Stellenbosch University

    Research output: Contribution to journalJournal articleResearchpeer-review

    65 Downloads (Orbit)

    Abstract

    ‘Long COVID’ is the term used to describe the phenomenon in which patients who have survived a COVID-19 infection continue to experience prolonged SARS-CoV-2 symptoms. Millions of people across the globe are affected by Long COVID. Solving the Long COVID conundrum will require drawing upon the lessons of the COVID-19 pandemic, during which thousands of experts across diverse disciplines such as epidemiology, genomics, medicine, data science, and computer science collaborated, sharing data and pooling resources to attack the problem from multiple angles. Thus far, there has been no global consensus on the definition, diagnosis, and most effective treatment of Long COVID. In this work, we examine the possible applications of data sharing and data science in general with a view to, ultimately, understand Long COVID in greater detail and hasten relief for the millions of people experiencing it. We examine the literature and investigate the current state, challenges, and opportunities of data sharing in Long COVID research.
    Original languageEnglish
    Article number14719
    JournalSouth African Journal of Science
    Volume119
    Issue number5/6
    Number of pages8
    ISSN0038-2353
    DOIs
    Publication statusPublished - 2023

    Keywords

    • Long COVID
    • Data sharing
    • Data science

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