Advancing Data Sovereignty in Africa: Deploying DataSHIELD to Federate Cross-Border Data Silos within the Data Science Without Borders Initiative

Collaborative health research across Africa is constrained by data sovereignty concerns, heterogeneous regulatory frameworks, limited infrastructure, and persistent capacity gaps, which hinder equitable cross-border data sharing. These challenges limit the availability of large, harmonized datasets needed to address the continent’s burden of infectious and non-communicable diseases while maintaining control over sensitive health data. Within this context, the Data Science Without Borders in Africa (DSWB) project implemented a privacy-preserving federated analysis framework using DataSHIELD across four institutions in Senegal, Cameroon, Ethiopia, and Kenya. This study documents the design, deployment, and early outcomes of this implementation. The approach combined consortium-wide data governance harmonization, a structured capacity-building programme, and a standardized technical architecture integrating DataSHIELD with the OMOP Common Data Model via dsOMOP. The deployment resulted in a functional federated network that enabled secure, in-situ analyses of harmonized clinical data. Multidisciplinary teams successfully executed federated descriptive and modelling analyses, managed Opal-based servers and implemented OMOP-based data harmonization workflows. Challenges related to connectivity, software heterogeneity, and institutional security were mitigated through server-side computation, standardized environments, and collaboration with institutional IT teams. Overall, this work demonstrates the feasibility of scalable, ethically robust federated health data analysis in diverse African research settings while preserving data sovereignty.