Operationalizing One Digital Health and FAIR Data Principles for Disease Surveillance in a Low-Medium Income Country in Africa: Qualitative Study in the Democratic Republic of the Congo.
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2026-08
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Abstract
Background
Recent crises involving zoonotic diseases (Ebola, COVID-19, and Mpox) have highlighted the limitations of fragmented public health systems for the prevention and response to health emergencies at the international and continental level, and particularly in Africa, more specifically in the Democratic Republic of the Congo (DRC). In this context, the One Health (OH) approach and its extension, One Digital Health (ODH), articulated with the findable, accessible, interoperable, reusable (FAIR) principles, offer a framework for rethinking the digital transition in health in the DRC. This study analyzes the reality of this transition in Kinshasa, DRC, and questions the feasibility of ODH in this context.Objective
This study aimed to (1) explore how stakeholders across human, animal, and environmental health sectors perceive and experience digital tool integration and data interoperability in Kinshasa; (2) identify structural, institutional, and technical constraints affecting cross-sectoral data sharing; and (3) analyze the sociotechnical conditions required for the operationalization of ODH in a fragmented digital health (DH) context.Methods
A qualitative study was conducted in Kinshasa, DRC, between November 10, 2025, and November 25, 2025, combining semistructured interviews with key actors (health professionals, administrative officials, digital experts, and engaged citizens) and a document review of strategic and regulatory texts related to DH in the DRC. The data were analyzed using a thematic approach to identify the representations, uses, and constraints related to DH and the operationalization of ODH.Results
Overall, 22 stakeholders participated (n=9, 40.9% human health; n=8, 36.4% animal health; n=4, 18.2% environmental health; n=1, 4.50% digital sector), predominantly male (n=15, 68.2%) and mainly in operational roles (n=12, 54.5%). Three interrelated topics emerged. First, a dual-track digital ecosystem characterized by the coexistence of formal platforms (eg, District Health Information Software 2 and electronic records) and informal tools (eg, WhatsApp [Meta]), with persistent paper-digital double-entry generating inefficiencies. Second, structural and governance bottlenecks, including electricity instability, limited connectivity, software incompatibility, external data-hosting concerns that affect sovereignty, and institutional silos that privilege human health over animal and environmental sectors. Third, prerequisites for operationalizing ODH emphasize foundational infrastructure (energy and internet), sustainable capacity building beyond one-off training, interoperable "bridges" between fragmented systems, and high-level political leadership. These elements were synthesized into an ODH-FAIR DRC conceptual model structured around three enabling pillars linking sectors for integrated zoonotic surveillance.Conclusions
Operationalizing ODH in DRC requires addressing foundational enablers beyond tools: synchronized energy-digital policies, decompartmentalized governance, and context-adapted capacity building. These insights inform low- and middle-income countries' DH strategies, urging donors and ministries to prioritize interoperability over isolated pilots to achieve sustainable zoonotic surveillance.Type
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Basivikidi, Harvey, Lefilso'o Lambuku, Delphin Kayembe, Arriel Benis and Didier Bompangue (2026). Operationalizing One Digital Health and FAIR Data Principles for Disease Surveillance in a Low-Medium Income Country in Africa: Qualitative Study in the Democratic Republic of the Congo. JMIR medical informatics, 14. p. e93321. 10.2196/93321 Retrieved from https://hdl.handle.net/10161/35476.
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Arriel Benis
Dr. Arriel Benis is a researcher and educator working at the intersection of medical informatics, digital health, epidemiology, and artificial intelligence, advancing health systems and biomedical engineering innovation. His work leverages AI, data science, and knowledge management to improve health-related decision-making at the individual, population, and public health levels.
His research focuses on developing data-driven healthcare solutions that enhance patient care, optimize clinical processes, and promote sustainable systems. Dr. Benis has engineered (a) clinical decision support systems with direct patient and healthcare partitioners impact such as ADHD, PTSD, and diabetes patient management and health communication, (b) MIMO -the Medical Informatics and Digital Health Multilingual Ontology- integrating more than 3500 terms and concepts across 30+ languages, actively deployed in healthcare organizations for AI-powered training and international projects support, (c) smart home and smart city health monitoring approach from a One Health viewpoint. Dr. Benis is a pioneer of the One Digital Health framework, which strategically links digital health innovation with environmental monitoring and digital epidemiology.
His past academic positions include serving as a department head and track director in biomedical and health informatics. He holds various leadership roles in the international medical informatics community, is a fellow of the International Academy for Health Sciences Informatics (FIAHSI), a Senior Member of the Institute of Electrical and Electronics Engineers (SMIEEE), and a Member of the American College of Epidemiology (MACE). Arriel Benis is the Editor-in-Chief of JMIR Medical Informatics. Dr. Benis is committed to training the next generation of innovators in digital health, medical informatics, and public health.
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