Introduction

Health Survey Design is a cornerstone of modern public health intelligence, epidemiological research, and data-driven healthcare planning. In an era defined by digital health transformation, real-time surveillance systems, and evidence-based policy making, the ability to design accurate, reliable, and scalable health surveys is critical for governments, NGOs, research institutions, and global health agencies. Health Survey Design Training Course equips participants with advanced competencies in survey methodology, sampling techniques, questionnaire design, field data collection, and health data analytics, ensuring high-quality insights for decision-making in both routine and emergency health contexts.

With the rapid rise of AI-driven health analytics, mobile data collection tools, DHIS2 integration, and population health monitoring systems, professionals must master structured approaches to collecting and interpreting health data. This course bridges theoretical foundations with practical applications, enabling participants to design robust health surveys that align with WHO standards, Sustainable Development Goals (SDGs), and global disease surveillance frameworks. Learners will gain hands-on experience in building scalable survey instruments, minimizing bias, and ensuring data validity in complex health environments.

Programme Curriculum

Health Survey Design Training Course

Introduction

Course Duration

5 days

Course Objectives

By the end of this training, participants will be able to:

Apply epidemiological survey design principles for public health research
Develop structured health data collection frameworks aligned with SDGs
Design AI-assisted digital health surveys using modern platforms
Implement robust sampling techniques (random, stratified, cluster sampling)
Construct validated questionnaires for population health studies
Apply biostatistics fundamentals in health data interpretation
Use mobile-based data collection tools (ODK, KoboToolbox, DHIS2)
Ensure data quality assurance and validation in field surveys
Reduce sampling bias and non-response errors in health research
Integrate real-time health surveillance and reporting systems
Conduct community-based health needs assessments
Analyze health indicators for policy and decision making
Strengthen data-driven healthcare planning and predictive analytics

Target Audience

Public Health Officers
Epidemiologists and Biostatisticians
NGO and Humanitarian Health Workers
Government Health Planners and Policymakers
Medical Researchers and Academics
Data Analysts in Health Informatics
WHO/UNICEF/Global Health Program Staff
Graduate Students in Public Health and Medicine

Course Modules

Module 1: Fundamentals of Health Survey Design

Principles of public health surveys
Types of health surveys (cross-sectional, cohort, longitudinal)
Role in epidemiology and surveillance systems
Ethical considerations in human data collection
Introduction to WHO survey frameworks
Case Study: COVID-19 rapid assessment survey design in urban populations

Module 2: Sampling Techniques in Health Research

Probability vs non-probability sampling
Cluster and stratified sampling methods
Sample size calculation techniques
Reducing sampling bias in field studies
Household and population sampling strategies
Case Study: National malaria prevalence sampling survey

Module 3: Questionnaire Design & Instrument Development

Structuring health questionnaires
Closed vs open-ended question design
Scaling methods (Likert, ordinal, categorical)
Translation and cultural adaptation
Pilot testing and validation
Case Study: Maternal health survey instrument in rural clinics

Module 4: Digital Health Data Collection Tools

Introduction to ODK and KoboToolbox
Mobile-based data entry systems
Offline data collection strategies
Integration with DHIS2 systems
Real-time data synchronization
Case Study: Immunization tracking using mobile survey tools

Module 5: Biostatistics for Survey Analysis

Descriptive and inferential statistics
Data cleaning and preprocessing
Regression and correlation analysis
Confidence intervals and hypothesis testing
Visualization of health data
Case Study: HIV prevalence trend analysis in adolescent populations

Module 6: Data Quality Assurance & Validation

Data reliability and validity checks
Error detection techniques
Field supervision and monitoring
Data consistency frameworks
Audit trails in health datasets
Case Study: Eliminating duplicate entries in national health surveys

Module 7: Health Surveillance Systems & Reporting

Real-time disease surveillance systems
Integration with national reporting frameworks
Early warning health systems
Dashboard creation and reporting tools
Outbreak detection mechanisms
Case Study: Ebola outbreak surveillance system in West Africa

Module 8: Advanced Health Analytics & Policy Application

Predictive analytics in healthcare
AI and machine learning in survey data
Health policy formulation from data insights
Population health trend forecasting
Decision-support systems in healthcare
Case Study: Predicting diabetes prevalence using national survey datasets

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

Questionnaire design Sampling techniques Data collection methods Survey data analysis

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 23 Oct 2026

💻 Online / Virtual session

Online $1,000