Advanced Genetics (Jun 2021)

Design of a FAIR digital data health infrastructure in Africa for COVID‐19 reporting and research

  • Mirjam vanReisen,
  • Francisca Oladipo,
  • Mia Stokmans,
  • Mouhamed Mpezamihgo,
  • Sakinat Folorunso,
  • Erik Schultes,
  • Mariam Basajja,
  • Aliya Aktau,
  • Samson Yohannes Amare,
  • Getu Tadele Taye,
  • Putu Hadi Purnama Jati,
  • Kudakwashe Chindoza,
  • Morgane Wirtz,
  • Meriem Ghardallou,
  • Gertjan vanStam,
  • Wondimu Ayele,
  • Reginald Nalugala,
  • Ibrahim Abdullahi,
  • Obinna Osigwe,
  • John Graybeal,
  • Araya Abrha Medhanyie,
  • Abdullahi Abubakar Kawu,
  • Fenghong Liu,
  • Katy Wolstencroft,
  • Erik Flikkenschild,
  • Yi Lin,
  • Joëlle Stocker,
  • Mark A. Musen

DOI
https://doi.org/10.1002/ggn2.10050
Journal volume & issue
Vol. 2, no. 2
pp. n/a – n/a

Abstract

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Abstract The limited volume of COVID‐19 data from Africa raises concerns for global genome research, which requires a diversity of genotypes for accurate disease prediction, including on the provenance of the new SARS‐CoV‐2 mutations. The Virus Outbreak Data Network (VODAN)‐Africa studied the possibility of increasing the production of clinical data, finding concerns about data ownership, and the limited use of health data for quality treatment at point of care. To address this, VODAN Africa developed an architecture to record clinical health data and research data collected on the incidence of COVID‐19, producing these as human‐ and machine‐readable data objects in a distributed architecture of locally governed, linked, human‐ and machine‐readable data. This architecture supports analytics at the point of care and—through data visiting, across facilities—for generic analytics. An algorithm was run across FAIR Data Points to visit the distributed data and produce aggregate findings. The FAIR data architecture is deployed in Uganda, Ethiopia, Liberia, Nigeria, Kenya, Somalia, Tanzania, Zimbabwe, and Tunisia.

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