Decision-Driven
Co-designed questions with public health stakeholders to ensure our analytics directly support outbreak response decisions.
Central Africa Epidemic Modelling Network
CEpiNet is a regional network designed to institutionalize epidemic analytics and modelling in Central Africa, delivering reliable decision products and strengthening capacity through training and hands-on practice.
We are a regional network advancing epidemic analytics and modelling in Central Africa. We transform epidemiological, genomic, and geospatial data into actionable products—forecasts, scenarios, and risk maps—to support timely public health decisions.
From data to decisions for outbreak control. We work in close collaboration with public health authorities, research institutions, and international partners to deliver decision-ready products that inform outbreak response strategies across Central Africa.
Central Africa Epidemic Modelling Network approach
Central Africa, with a network approach connecting institutions, projects, and country nodes across the region to strengthen epidemic preparedness and response capacity.
Guiding values for epidemic analytics and decision support
Co-designed questions with public health stakeholders to ensure our analytics directly support outbreak response decisions.
Clear communication of assumptions and uncertainty in all outputs, ensuring stakeholders understand the basis of our analyses.
Versioned code and documented runs to ensure our methods can be verified and built upon by others.
Responsible data use aligned with national regulations and institutional ethics frameworks for all analytics.
Strengthening national capacity through courses, internships, and standardization for sustainable epidemic response.
Building lasting regional expertise and infrastructure to reduce dependence on external support during outbreaks.
Decision-ready products for outbreak response
Nowcasting, Rt estimation, short-term projections, and operational maps during alerts to support immediate response decisions.
Comparative impact of intervention options including targeting, logistics, coverage, and WASH strategies with uncertainty analysis.
Hotspot detection, accessibility analysis, micro-targeting, and atlas products for strategic resource allocation.
Link surveillance and lab/genomics data to inform transmission patterns, clusters, and outbreak interpretation.
Courses, modelling clinics, fellowships, and hands-on internships to build regional analytical expertise.
Model registry, data dictionaries, SOPs, and transparent assumptions for reliable decision support.
A structured approach to epidemic analytics and decision support
Collaborate with public health stakeholders to define decision-relevant questions and analytical priorities.
Establish data quality, harmonization, and security protocols for reliable and reproducible workflows.
Execute documented methods with explicit uncertainty quantification and transparent assumptions.
Produce actionable outputs and iterate based on stakeholder feedback for continuous improvement.
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 Niyukuri Lab.