Introduction

Chronic diseases such as cardiovascular diseases, cancer, diabetes, chronic respiratory diseases, and metabolic syndromes are the leading causes of morbidity and mortality globally. Chronic Disease Epidemiology Training Course is designed to build advanced competencies in non-communicable disease (NCD) surveillance, epidemiological methods, risk factor analysis, population health intelligence, and evidence-based public health interventions. The course integrates modern biostatistics, data science in epidemiology, digital health surveillance systems, and global burden of disease frameworks to equip learners with practical and analytical skills for real-world application.

With the rising global burden of NCDs driven by lifestyle changes, urbanization, aging populations, and environmental exposures, there is a growing demand for professionals skilled in disease modeling, cohort studies, case-control analysis, health informatics, and preventive epidemiology strategies. This training emphasizes data-driven decision-making, predictive analytics, health policy development, and community-based intervention design, preparing participants to contribute effectively to national and global chronic disease control programs.

Programme Curriculum

Chronic Disease Epidemiology Training Course

Introduction

Course Duration

10 days

Course Objectives

Master principles of chronic disease epidemiology and surveillance systems
Apply biostatistical methods in NCD research and analysis
Conduct cohort, case-control, and cross-sectional studies
Analyze risk factors for cardiovascular and metabolic diseases
Utilize global burden of disease (GBD) methodologies
Interpret population health data using R, SPSS, and Python tools
Develop chronic disease prevention and control strategies
Evaluate screening programs and early detection models
Integrate digital epidemiology and health informatics systems
Assess environmental and occupational health impacts on NCDs
Design community-based intervention programs
Strengthen policy formulation and health systems research
Apply predictive modeling and AI in disease forecasting

Target Audience

Public health professionals
Epidemiologists and biostatisticians
Medical doctors and clinicians
Health policy analysts
Research scientists and academics
NGO and humanitarian health workers
Data analysts in health sectors
Graduate students in public health and medicine

Course Modules

Module 1: Foundations of Chronic Disease Epidemiology

Overview of NCD burden and global trends
Key concepts: incidence, prevalence, mortality
Epidemiological transition theory
Case study: Global rise of diabetes in urban populations
Introduction to surveillance systems

Module 2: Biostatistics for Epidemiology

Descriptive and inferential statistics
Measures of association (RR, OR)
Hypothesis testing techniques
Case study: Hypertension prevalence analysis
Statistical software introduction

Module 3: Study Designs in Epidemiology

Cohort study design principles
Case-control study applications
Cross-sectional survey methods
Case study: Smoking and lung cancer association
Bias and confounding control

Module 4: Cardiovascular Disease Epidemiology

Risk factors and population trends
Hypertension and stroke epidemiology
Lifestyle determinants
Case study: Heart disease in aging populations
Prevention strategies

Module 5: Diabetes and Metabolic Disorders

Type 1 vs Type 2 diabetes epidemiology
Obesity and insulin resistance
Nutritional epidemiology
Case study: Urban obesity epidemic
Prevention interventions

Module 6: Cancer Epidemiology

Cancer registry systems
Carcinogens and risk factors
Screening effectiveness
Case study: Breast cancer screening programs
Survival analysis basics

Module 7: Chronic Respiratory Diseases

COPD and asthma epidemiology
Air pollution impact
Occupational exposures
Case study: Urban air quality and asthma spikes
Intervention models

Module 8: Infectious vs Chronic Disease Interaction

Dual burden of disease
HIV and NCD comorbidities
Health system challenges
Case study: TB-diabetes co-infection
Integrated care models

Module 9: Risk Factor Epidemiology

Behavioral risk factors (tobacco, alcohol)
Dietary and physical inactivity analysis
Genetic predispositions
Case study: Tobacco control success stories
Risk attribution methods

Module 10: Environmental Epidemiology

Climate change and NCDs
Pollution exposure pathways
Urbanization effects
Case study: Industrial pollution and cancer clusters
Exposure assessment tools

Module 11: Health Informatics & Digital Epidemiology

Electronic health records (EHRs)
Big data in epidemiology
Mobile health surveillance
Case study: COVID-era chronic disease tracking
Data integration systems

Module 12: Global Burden of Disease Analysis

DALYs and QALYs concepts
WHO burden estimation methods
Regional health comparisons
Case study: Global NCD mortality ranking
Policy implications

Module 13: Screening and Early Detection Programs

Screening test validity
Sensitivity and specificity
Population screening strategies
Case study: Cervical cancer screening success
Cost-effectiveness analysis

Module 14: Public Health Intervention Design

Behavior change models
Community engagement strategies
Health promotion frameworks
Case study: National anti-obesity campaigns
Program evaluation methods

Module 15: Predictive Modeling & AI in Epidemiology

Machine learning in disease prediction
Time-series forecasting
Risk stratification models
Case study: AI-based heart disease prediction
Ethical considerations in AI health use

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

Interactive lectures and presentations.
Group discussions and brainstorming sessions.
Hands-on exercises using real-world datasets.
Role-playing and scenario-based simulations.
Analysis of case studies to bridge theory and practice.
Peer-to-peer learning and networking.
Expert-led Q&A sessions.
Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Disease surveillance Risk factor analysis Long-term cohort studies Statistical modeling

Programme Fee

Duration: 10 Days

Method: Online or Physical

Online Price: $2,000

Physical Price: $3,000

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 30 Oct 2026

💻 Online / Virtual session

Online $2,000