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

Research output: Contribution to journalJournal articleResearchpeer-review

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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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