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Advancing epidemic intelligence: evaluating Senegal's mpox surveillance system and readiness for AI-driven predictive
Sylvain L B Faye1, Fatoumata B Diongue2, Abdourakhmane Ndao3
1Laboratory of Sociology, Anthropology, and Psychology (LASAP-ETHOS) FLSH, Cheikh Anta DIOP University - DAKAR, Dakar, Senegal.
Frontiers in Public Health
|February 19, 2026
Summary
Senegal
Area of Science:
- Epidemiology
- Public Health Surveillance
- Artificial Intelligence in Health
Background:
- Mpox re-emergence in West Africa necessitates improved surveillance.
- Senegal's mpox surveillance system requires evaluation for enhanced response.
- The study explores AI's potential for predictive epidemic intelligence.
Purpose of the Study:
- Evaluate Senegal's mpox surveillance system performance, data quality, and governance.
- Assess the potential of AI-powered predictive epidemic intelligence for mpox.
- Identify areas for improvement in early warning systems.
Main Methods:
- Descriptive, exploratory approach using quantitative and qualitative data.
- Retrospective review of mpox cases (Jan 2024-Oct 2025) via DHIS2 Tracker.
- Data quality checks and stakeholder interviews for system insights.
Main Results:
- Seven mpox cases reported by Oct 2025, concentrated in Dakar among young, mobile populations.
- Transmission linked to mobility corridors; surveillance system showed improvements.
- Challenges include underreporting, uneven coverage, and limited AI regulation.
Conclusions:
- Developing predictive epidemic intelligence requires stakeholder involvement, transparency, and ethical AI safeguards.
- Integrating technology and governance can shift Senegal towards proactive mpox surveillance.
- Strengthening health security positions Senegal as a regional leader.
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