Evidence-Based Public Health Training Course

Evidence-Based Public Health Training Course

Introduction

Evidence-Based Public Health (EBPH) is a modern, data-driven approach that integrates the best available research evidence with public health expertise and population needs to improve health outcomes, strengthen health systems, and support policy innovation. In an era defined by global pandemics, climate-related health risks, emerging infectious diseases, and digital health transformation, EBPH has become a critical competency for public health professionals, policymakers, epidemiologists, and healthcare leaders. Evidence-Based Public Health Training Course is designed to equip learners with advanced skills in data analytics, health surveillance, program evaluation, systematic reviews, and policy translation, ensuring that public health interventions are both scientifically grounded and impact-oriented.

The course emphasizes practical application of real-world evidence (RWE), big data in health, AI-driven epidemiology, health informatics, and implementation science. Participants will learn how to transform raw data into actionable insights, design effective interventions, and evaluate public health programs using globally recognized frameworks. Through interactive modules, case-based learning, and applied research methodologies, learners will develop the capacity to address complex health challenges such as non-communicable diseases (NCDs), infectious disease outbreaks, maternal and child health disparities, and environmental health threats using evidence-based strategies.

Course Duration

5 days

Course Objectives

1. Apply evidence-based public health (EBPH) principles in real-world settings 
2. Analyze epidemiological data using advanced biostatistical tools
3. Conduct systematic reviews and meta-analysis for health decision-making
4. Integrate health informatics and digital surveillance systems
5. Evaluate public health interventions using impact assessment frameworks
6. Strengthen data-driven policy formulation and health governance
7. Apply implementation science in public health program delivery
8. Utilize AI and machine learning in disease prediction and prevention
9. Improve health systems strengthening through evidence translation
10. Design community-based participatory research (CBPR) interventions
11. Address global health challenges including pandemics and climate health risks
12. Enhance monitoring and evaluation (M&E) of health programs
13. Develop skills in health equity, social determinants of health, and SDG alignment

Target Audience

1. Public health professionals and officers 
2. Epidemiologists and biostatisticians 
3. Healthcare policymakers and government officials 
4. NGO and humanitarian health workers 
5. Medical doctors and clinical researchers 
6. Health data analysts and informatics specialists 
7. Graduate students in public health and medicine 
8. International development and global health consultants 

Course Modules

Module 1: Foundations of Evidence-Based Public Health

• Principles of EBPH and global frameworks 
• Hierarchy of scientific evidence 
• Translating research into policy 
• Introduction to public health decision-making models 
• Ethics in evidence-based practice 
• Case Study: COVID-19 response strategies and evidence-driven lockdown policies 

Module 2: Epidemiology and Biostatistics in Public Health

• Descriptive and analytical epidemiology 
• Measures of disease burden 
• Regression and statistical modeling 
• Outbreak investigation techniques 
• Data interpretation for policy 
• Case Study: Cholera outbreak tracking and containment in East Africa 

Module 3: Health Informatics and Digital Surveillance

• Electronic Health Records (EHR) systems 
• Disease surveillance platforms 
• GIS mapping in public health 
• Big data analytics in healthcare 
• Real-time outbreak monitoring systems 
• Case Study: Mobile-based malaria surveillance systems in Sub-Saharan Africa 

Module 4: Systematic Reviews and Meta-Analysis

• Literature search strategies 
• PRISMA guidelines 
• Data extraction techniques 
• Meta-analysis interpretation 
• Evidence synthesis for policy briefs 
• Case Study: Global vaccine effectiveness meta-analysis studies 

Module 5: Implementation Science in Public Health

• Translating research into practice 
• Adoption and diffusion of innovations 
• Barriers to implementation 
• Scaling up interventions 
• Real-world effectiveness studies 
• Case Study: Scaling HIV prevention programs in resource-limited settings 

Module 6: Health Policy and Systems Strengthening

• Policy formulation process 
• Health governance structures 
• Financing and resource allocation 
• Stakeholder engagement strategies 
• Policy evaluation frameworks 
• Case Study: Universal Health Coverage (UHC) implementation models 

Module 7: Monitoring, Evaluation, and Impact Assessment

• M&E frameworks and indicators 
• Logical framework approach (LogFrame) 
• Performance measurement systems 
• Outcome vs impact evaluation 
• Data visualization for reporting 
• Case Study: Maternal mortality reduction program evaluation 

Module 8: Global Health Challenges and Innovation

• Emerging infectious diseases 
• Climate change and health risks 
• Digital health innovations 
• Non-communicable diseases (NCDs) burden 
• Health equity and SDGs 
• Case Study: AI-based early warning systems for epidemic prediction 

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@datastatresearch.org or call +254724527104 

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 DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.