Evidence-Driven Response
Transform epidemic response from reactive to proactive through real-time analytics, forecasting, and scenario planning.
A trusted regional reference for epidemic analytics
Transform epidemic response from reactive to proactive through real-time analytics, forecasting, and scenario planning.
Build sustainable analytical expertise within Central Africa to reduce dependence on external support during outbreaks.
Position Central Africa at the forefront of epidemic science with internationally recognized standards and innovations.
What we do to achieve our vision
To produce integrated analytics (modelling, geospatial, epidemiological and genomic data) co-developed with public health actors, and to strengthen national capacity through courses, internships, and standardization.
CEpiNet transforms epidemiological, genomic, and geospatial data into actionable products—forecasts, scenarios, and risk maps—to support timely public health decisions in Central Africa.
Produce rapid outbreak analytics (48-72h), scenario briefs, geospatial intelligence, and integrated epidemiological-genomic insights that directly inform response strategies.
Strengthen analytical expertise through structured training, modelling clinics, fellowships, internships, and hands-on practicums for sustainable epidemic response capabilities.
Maintain model registries, data dictionaries, SOPs, and transparent assumptions to ensure reproducibility, reliability, and credibility of epidemic analytics.
Co-design analytical questions with public health stakeholders and coordinate across institutions to ensure products meet real-world decision needs.
Build robust data pipelines with quality assurance, harmonization, security protocols, and integration of surveillance, laboratory, and geospatial data.
Develop and adapt cutting-edge methods in epidemic modeling, geospatial analysis, and genomic integration to address unique Central African contexts.
Principles that guide everything we do
Scientific excellence and methodological soundness in all analytics and modeling work.
Open methods, explicit assumptions, and clear communication of uncertainty in all outputs.
Partnership-driven approach with stakeholders, institutions, and communities across Central Africa.
Building sustainable local capacity and reducing dependence on external expertise.
Every forecast, map, and scenario we produce serves one ultimate purpose: to help decision-makers save lives and protect communities during epidemic threats. We measure our success not by publications or models, but by the quality and timeliness of decisions our work enables.