CEpiNet transforms epidemiological, genomic, and geospatial data into actionable products—forecasts, scenarios, and risk maps—to support timely public health decisions in Central Africa.
Transforming data into decision-ready products for outbreak response
A structured approach to epidemic analytics and decision support
Collaborate with public health stakeholders to define decision-relevant questions and analytical priorities for outbreak response.
Establish data quality, harmonization, and security protocols to ensure reliable and reproducible analytics workflows.
Execute documented methods with explicit uncertainty quantification and transparent assumptions for decision support.
Produce actionable outputs and iterate based on stakeholder feedback for continuous improvement.
Human resource capacity building to strengthen local expertise in epidemic analytics and public health decision support.
Design and conduct biomedical and epidemiological studies such as clinical trials, intervention studies, etc., at the Interdisciplinary Research Program in Public Health of the Doctoral School of the University of Burundi.
Three complementary institutions driving CEpiNet's mission
Administrative and financial management, epidemiological and genomic data pipelines, quality assurance and interpretation for outbreak response.
Structured training modules, modelling clinics, and a community of practice for epidemic analytics capacity building.
Hands-on modelling placements, production-focused mentoring, and model development at the Interdisciplinary Research Program in Public Health of the Doctoral School of the University of Burundi.
CEpiNet is supported by a portfolio of collaborative initiatives
Supported by Gates Foundation - Mpox modelling and decision briefs for outbreak control in DRC.
Supported by EDCTP - Standards, training, and network strengthening in epidemic analytics and modelling in Central Africa.
Supported by MRC/Imperial College London - Control strategy analytics translation for Central Africa.
Supported by IDRC/University of Toronto - Validated AI-enhanced analytics and response network.
Contact CEpiNet to co-develop analytics, modelling products, training, or data pipelines for epidemic preparedness and response
Whether you need outbreak analytics, training programs, or data support, we're here to help strengthen epidemic response in Central Africa.
