Abstract Sickle cell disease (SCD) is one of the most prevalent monogenic disorders worldwide, with the highest burden in Africa, where ~75% of the 7.74 million global cases occur. Scientific progress in understanding its epidemiology, clinical heterogeneity, and treatment outcomes has been constrained by heterogeneous, non-standardized, and non-interoperable datasets that limit data integration and cross-country analyses. To address this, the Sickle Africa Data Coordinating Centre (SADaCC) was established as the data science hub of the SickleInAfrica consortium to support the development and expansion of Pan-African SCD registry. SADaCC now coordinates one of the largest patient-consented SCD datasets globally, with data from over 40 000 persons living with SCD in seven countries (Ghana, Mali, Nigeria, Tanzania, Uganda, Zambia, and Zimbabwe) within the Sickle Pan-African Research Consortium (SPARCo), as well as genomic data from SADaCC satellite sites in Cameroon, South Africa, and Malawi. The registry is built on FAIR-compliant architecture, the Sickle Cell Disease Ontology, and powered by a suite of digital platforms such as REDCap, NextCloud, RStudio, GitHub, Docker, and Jupyter. In partnership with SPARCo, SADaCC is also piloting a biobank that will link biospecimens with data in the registry to advance multi-omics research. Beyond infrastructure, SADaCC leads training and/or research in big data analytics, genomics, bioethics, implementation science, qualitative research, and psychosocial studies. Ethical, legal, and social considerations are embedded across all operations with emphasis on equitable intra-African collaboration and patient involvement in research. Looking ahead, SADaCC will integrate real-time data streams, AI-driven analytics, and multi-omics data to drive big data and genetic medicine research for SCD in Africa.
Wonkam et al. (2026) studied this question.