Our Training Programs
World-class professional certification courses in Food Safety, Quality, Science, Technology & Agriculture
About This Course
The Applied Epidemiology, Disease Surveillance, Public Health Analytics & Outbreak Intelligence Training Course is a premium, competency-based programme designed to equip public health professionals, epidemiologists, researchers, clinicians, veterinarians, food safety specialists, and development practitioners with advanced competencies in applied epidemiology, disease surveillance, outbreak intelligence, public health analytics, One Health, digital epidemiology, health informatics, predictive analytics, and evidence-based public health decision-making. Participants develop practical expertise in surveillance systems, outbreak investigation, epidemiological study design, statistical analysis, GIS, R, Stata, DHIS2, KoboToolbox, dashboard development, artificial intelligence (AI), machine learning, genomic epidemiology, and early warning systems. Through hands-on analytical laboratories, real-world outbreak investigations, multidisciplinary case studies, simulation exercises, and executive capstone projects, participants gain the capability to detect, analyse, predict, prevent, and respond to public health threats while strengthening resilient health systems, food safety, global health security, and One Health programmes.
What You’ll Learn
- Apply modern epidemiological principles, surveillance methodologies, and public health analytics to detect, investigate, and control infectious diseases, non-communicable diseases, foodborne illnesses, zoonoses, and emerging health threats.
- Design and strengthen integrated disease surveillance and outbreak intelligence systems using digital technologies, early warning systems, health informatics, and One Health approaches.
- Perform advanced epidemiological analyses using R, Stata, GIS, DHIS2, KoboToolbox, statistical modelling, predictive analytics, and spatial epidemiology to generate actionable public health intelligence.
- Integrate artificial intelligence (AI), machine learning, genomic epidemiology, and digital surveillance technologies into public health monitoring, forecasting, and outbreak response.
- Lead multidisciplinary outbreak investigations and evidence-based public health interventions that strengthen health security, policy development, emergency preparedness, and resilient health systems.
Course Curriculum
- Principles of Applied Epidemiology and Population Health
- Epidemiological Concepts, Measures and Indicators
- Disease Transmission Dynamics and Determinants of Health
- Public Health Surveillance Systems and Health Intelligence
- One Health and Global Health Security Frameworks
- Descriptive, Analytical and Experimental Study Designs
- Cross-Sectional, Cohort and Case-Control Studies
- Sampling Methods and Field Epidemiology
- Outbreak Investigation Methodologies
- Bias, Confounding and Causal Inference
- Integrated Disease Surveillance and Response (IDSR)
- Event-Based and Indicator-Based Surveillance
- Digital Epidemiology and Digital Disease Detection
- Early Warning Systems and Public Health Intelligence
- Surveillance Data Quality and Performance Evaluation
- Epidemiological Data Management
- Statistical Analysis Using R and Stata
- Epidemiological Measures and Risk Estimation
- Time Series Analysis and Disease Trend Monitoring
- Data Visualization, Dashboards and Executive Reporting
- Geographic Information Systems (GIS) for Public Health
- Spatial Epidemiology and Disease Mapping
- Hotspot Analysis and Cluster Detection
- Environmental Exposure Assessment
- Spatial Decision Support for Public Health
- Outbreak Detection and Verification
- Epidemic Intelligence and Rapid Risk Assessment
- Incident Management Systems and Emergency Operations
- Crisis Communication and Risk Communication
- Public Health Emergency Preparedness and Response
- Integrated Human-Animal-Environmental Surveillance
- Zoonotic Disease Epidemiology
- Foodborne Disease Surveillance and Food Safety Intelligence
- Antimicrobial Resistance (AMR) Surveillance
- Climate Change and Emerging Disease Risks
- Genomic Epidemiology and Pathogen Genomics
- Artificial Intelligence in Public Health
- Machine Learning for Disease Prediction
- Predictive Modelling and Forecasting
- Explainable AI and Public Health Decision Support
- Health Information Systems and Digital Transformation
- DHIS2, KoboToolbox, ODK, and Mobile Surveillance
- Interoperability and Data Integration
- Electronic Surveillance Platforms and Dashboards
- Data Governance, Ethics and Privacy
- Monitoring and Evaluation of Surveillance Systems
- Health Programme Evaluation and Performance Measurement
- Evidence-Based Policy Development
- Health Systems Resilience and Universal Health Coverage
- Leadership in Public Health Decision-Making
- Digital Public Health and Smart Surveillance
- Wastewater Surveillance and Environmental Monitoring
- Precision Public Health and Population Health Analytics
- Climate Intelligence and Emerging Disease Forecasting
- Future Technologies in Epidemiology and Global Health Security
- Designing an Integrated Disease Surveillance and Early Warning System
- Conducting a Comprehensive Outbreak Investigation and Epidemiological Analysis
- Developing an AI-Enabled Public Health Analytics and Decision Support Platform
- Building GIS Dashboards and Executive Public Health Intelligence Reports
- Executive Capstone Presentation: Epidemiology, Outbreak Intelligence and Public Health Surveillance Strategy
Who Should Attend
- Epidemiologists, public health professionals, clinicians, veterinarians, laboratory scientists, and disease surveillance officers.
- Researchers, academics, postgraduate students, and health data analysts working in health and life sciences.
- Food safety, One Health, environmental health, agriculture, and veterinary professionals involved in integrated disease surveillance.
- Government ministries, public health institutes, WHO, Africa CDC, NGOs, humanitarian agencies, and international development organizations.
- Monitoring, evaluation, health informatics, GIS, and emergency preparedness professionals supporting public health programmes.
Prerequisites
- Previous experience with data analysis or surveillance systems is beneficial but not essential.
- The programme is designed for both emerging and experienced professionals seeking advanced competencies in epidemiology, surveillance, outbreak intelligence, and public health analytics.
Key Benefits
- Master applied epidemiology, disease surveillance, outbreak intelligence, and public health analytics using internationally recognized methods and digital surveillance technologies.
- Develop expertise in outbreak investigation, epidemiological modelling, GIS, R, Stata, DHIS2, KoboToolbox, and dashboard development for evidence-based public health decision-making.
- Apply artificial intelligence (AI), machine learning, genomic epidemiology, and predictive analytics to improve disease forecasting, early warning, and public health preparedness.
- Strengthen One Health surveillance systems by integrating human, animal, environmental, and food safety data to address emerging health threats.
- Enhance leadership capacity in public health emergency preparedness, health security, policy development, and resilient health systems through modern analytical and decision-support approaches.
Delivery Technique
- Expert-led epidemiology and outbreak intelligence masterclasses integrating theory with practical public health applications.
- Hands-on analytical laboratories using R, Stata, DHIS2, KoboToolbox, GIS, and interactive dashboards.
- Real-world outbreak investigation simulations based on infectious diseases, foodborne outbreaks, zoonoses, and humanitarian emergencies.
- Collaborative case studies and multidisciplinary surveillance workshops using authentic datasets.
- Executive capstone project focused on designing an integrated disease surveillance and outbreak intelligence system.