Training on AI-Driven Outbreak Early Warning Systems for Waterborne Diseases
Professional training on AI-driven early warning systems for predicting and responding to waterborne disease outbreaks.
Next intake
20 Jul 2026 · Nakuru
Duration
5 days
Live instruction
Delivery
Physical + Virtual
Cohort based
Level
Intermediate
Working professionals
Certification
NITA reimbursable
For Kenyan cohorts
Language
English
All materials
About this programme
This specialized programme is designed to equip public health and WASH professionals with the knowledge and practical skills to leverage Artificial Intelligence (AI), predictive analytics, and digital surveillance systems for the early detection and prediction of waterborne disease outbreaks. The programme explores how AI can integrate epidemiological, environmental, climate, and water quality data to identify emerging health risks, strengthen early warning systems, and support timely public health interventions. Through practical exercises, case studies, and real-world applications, participants will develop the capacity to implement data-driven disease surveillance strategies that enhance outbreak preparedness, protect public health, and strengthen WASH programme effectiveness.
Duration
5 Days
Who Should Attend
- Public health professionals
- WASH programme managers and specialists
- Epidemiologists and disease surveillance officers
- Environmental health officers
- Water quality and laboratory professionals
- Disaster risk management practitioners
- Data analysts and GIS specialists
- Government health and water sector officials
- NGOs, humanitarian agencies, and development partners
What you'll walk away with
By the end of the training, participants will be able to:
- Understand the role of AI in waterborne disease surveillance and early warning
- Analyze epidemiological, climate, and water quality data to identify outbreak risks
- Apply predictive analytics to forecast disease outbreaks
- Design AI-enabled early warning and response systems
- Strengthen evidence-based public health decision-making and emergency preparedness
- Develop implementation strategies for AI-driven disease surveillance systems
What we cover, module by module
Module 1: Foundations of AI and Waterborne Disease Surveillance
- Introduction to AI, predictive analytics, and digital epidemiology
- Waterborne diseases and public health surveillance systems
- Data sources for outbreak monitoring
- Case Study: AI applications in disease surveillance
Module 2: Data Integration and Risk Assessment
- Integrating health, climate, environmental, and water quality data
- GIS and spatial analysis for disease surveillance
- Data quality, governance, and visualization
- Practical: Analyzing multi-source outbreak datasets
Module 3: AI-Powered Outbreak Prediction
- Machine Learning models for outbreak forecasting
- Risk modeling and hotspot identification
- Early detection of disease transmission patterns
- Practical: Developing predictive outbreak models
Module 4: Early Warning Systems and Emergency Response
- Designing AI-enabled early warning systems
- Decision support dashboards and automated alerts
- Risk communication and emergency response planning
- Case Study: AI-supported outbreak response strategies
Module 5: Implementation, Governance and Strategic Planning
- Integrating AI into disease surveillance programmes
- Ethical AI, data privacy, and regulatory considerations
- Monitoring system performance and continuous improvement
- Practical: Developing an AI-driven outbreak early warning framework
Where the change lands
Individual Impact
- Enhanced expertise in AI-driven disease surveillance and predictive analytics
- Improved skills in outbreak forecasting and risk assessment
- Strengthened capacity to support data-driven public health interventions
Organizational Impact
- Improved outbreak preparedness and response capabilities
- Enhanced disease surveillance and early warning systems
- Better coordination between WASH and public health programmes
- Strengthened evidence-based planning and decision-making
Dates and locations
Upcoming intakes
Every intake is limited to a small cohort. Booking closes when a date fills or three weeks before the start, whichever comes first.
| City | Starts | Ends | Delivery | Book |
|---|---|---|---|---|
NakuruNext | 20 Jul 2026 | 24 Jul 2026 | In-Person | Book |
Kigali | 20 Jul 2026 | 24 Jul 2026 | In-Person | Book |
Accra | 20 Jul 2026 | 24 Jul 2026 | In-Person | Book |
Kisumu | 27 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Johannesburg | 27 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Dakar | 27 Jul 2026 | 31 Jul 2026 | In-Person | Book |
- NakuruNext
20 Jul → 24 Jul·In-Person
Book this intake - Kigali
20 Jul → 24 Jul·In-Person
Book this intake - Accra
20 Jul → 24 Jul·In-Person
Book this intake - Kisumu
27 Jul → 31 Jul·In-Person
Book this intake - Johannesburg
27 Jul → 31 Jul·In-Person
Book this intake - Dakar
27 Jul → 31 Jul·In-Person
Book this intake
Common questions.
Still not sure? Send us a note and a facilitator will get back to you within a business day.
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Course finder
Find the right course for you
Prefer to talk it through? Send us an enquiry and a facilitator will scope a fit within a business day.
For corporate teams
Training 10+ professionals?
We deliver Training on AI-Driven Outbreak Early Warning Systems for Waterborne Diseases in-house at your offices, at a venue we arrange, or fully virtual. Customise the curriculum against your KPIs, and get a bespoke price for the cohort size you need.