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

Mirjam van Reisen, Fransisca Oladipo, Mia Stokmans, Mouhamed Mpezamihigo, Sakinat Folorunso, Erik Schultes, Mariam Basajja, Aliya Aktau, Samson Yohannes Amare, Getu Taye, Putu Hadi Purnama Jati, Kudakwashe Chindoza, Morgane Wirtz, Mariem Ghardallou, Gertjan van Stam, Wondimu Ayele, Reginald Nalugala, Ibrahim Abdullahi, Obinna Osigwe, John GraybealAraya Abrha Medhanyie, Abdulahi Kawu, Fenghong Liu, Katy Wolstencroft, Erik Flikkenschild, Yi Lin, Joëlle Stocker, Mark Musen

Research output: Contribution to journalArticleScientificpeer-review

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.
Original languageEnglish
Pages (from-to)1-17
Number of pages17
JournalAdvanced Genetics
Volume2
Issue number2
DOIs
Publication statusPublished - 11 Jun 2021

Keywords

  • Data Science
  • Ethical
  • Health Information
  • Knowledge Capture
  • Legal and Social Implications

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