Course Overview

Public Health Data Analytics is a critical discipline that enables health professionals, researchers, policymakers, and development practitioners to transform health data into actionable insights for improving population health outcomes, disease surveillance, healthcare planning, and evidence-based decision-making. As healthcare systems increasingly generate large volumes of data through electronic health records, disease surveillance systems, health surveys, laboratory information systems, and public health programs, organizations require advanced analytical capabilities to monitor health trends, assess interventions, identify risks, and optimize resource allocation. This comprehensive training course provides participants with practical knowledge and hands-on skills in public health analytics, epidemiological analysis, health data management, statistical modeling, disease surveillance, and health intelligence systems.

The training explores modern public health data analytics methodologies used by ministries of health, hospitals, public health institutions, international health organizations, NGOs, research centers, and development agencies. Participants will learn how to collect, manage, analyze, visualize, and interpret health data to support disease prevention, health promotion, healthcare quality improvement, and policy development. The course combines theoretical concepts with practical applications using real-world health datasets and public health case studies.

Participants will gain practical experience in health data management, epidemiological analysis, disease trend monitoring, outbreak investigation, health program evaluation, predictive analytics, dashboard development, and healthcare performance measurement. The course examines how data analytics can be used to identify disease patterns, assess risk factors, monitor population health indicators, improve service delivery, evaluate interventions, and strengthen health systems. Through practical exercises and case studies, participants will develop confidence in applying analytical tools and methodologies to address complex public health challenges.

The training further addresses emerging trends in public health analytics, including artificial intelligence in healthcare, big data analytics, digital health systems, geospatial health analysis, predictive disease modeling, health informatics, real-time surveillance systems, precision public health, and data-driven healthcare innovation. Participants will develop the competencies required to generate meaningful health insights, improve public health outcomes, and support evidence-based health policy and program management.

Course Objectives

1.      Understand the principles and applications of public health data analytics.

2.      Collect, manage, and analyze public health datasets effectively.

3.      Apply epidemiological and statistical methods to health data.

4.      Monitor disease trends and population health indicators.

5.      Conduct health program evaluation and performance assessments.

6.      Utilize data visualization and dashboard tools for health reporting.

7.      Apply predictive analytics and forecasting techniques in public health.

8.      Strengthen evidence-based healthcare planning and decision-making.

9.      Improve disease surveillance and outbreak response capabilities.

10.  Utilize emerging technologies for public health intelligence and analytics.

Organizational Benefits

1.      Improved health program planning and management.

2.      Enhanced disease surveillance and outbreak detection capabilities.

3.      Better evidence-based healthcare decision-making.

4.      Improved monitoring and evaluation of health interventions.

5.      Enhanced healthcare service delivery and resource allocation.

6.      Better identification of population health risks and priorities.

7.      Increased efficiency in health reporting and performance monitoring.

8.      Improved policy development through health intelligence.

9.      Strengthened organizational research and analytical capacity.

10.  Enhanced public health outcomes and system resilience.

Target Participants

·         Public health professionals

·         Epidemiologists and biostatisticians

·         Healthcare managers and administrators

·         Health information officers and data managers

·         Monitoring and Evaluation (M&E) specialists

·         Medical researchers and clinical investigators

·         Government health officers and policymakers

·         NGO and development practitioners in health programs

·         Hospital and health facility managers

·         Data analysts and statisticians

·         Academic researchers and university lecturers

·         Graduate and postgraduate students in health sciences

Course Outline

Module 1: Foundations of Public Health Data Analytics

1.      Introduction to public health analytics and health intelligence

2.      Sources of public health and healthcare data

3.      Health information systems and data ecosystems

4.      Public health indicators and performance metrics

5.      Data-driven decision-making in healthcare

6.      Applications of analytics in public health programs

Case Study:
Using health data analytics to identify priority health challenges and guide public health interventions.

Module 2: Health Data Collection, Management, and Quality Assurance

1.      Public health data collection methodologies

2.      Health surveys, surveillance systems, and registries

3.      Data cleaning, validation, and quality assurance

4.      Managing electronic health records and health databases

5.      Data governance, privacy, and confidentiality

6.      Health data integration and interoperability

Case Study:
Improving data quality in a national disease surveillance system to enhance reporting accuracy.

Module 3: Epidemiological Analysis and Disease Surveillance

1.      Principles of epidemiology and population health analysis

2.      Disease frequency and distribution measures

3.      Outbreak investigation and surveillance techniques

4.      Risk factor analysis and health determinants

5.      Trend analysis and disease monitoring

6.      Epidemiological reporting and interpretation

Case Study:
Analyzing infectious disease surveillance data to identify emerging health threats and intervention priorities.

Module 4: Statistical Analysis and Health Program Evaluation

1.      Descriptive and inferential statistics for public health

2.      Hypothesis testing and significance analysis

3.      Regression analysis and health outcome modeling

4.      Monitoring and evaluation frameworks for health programs

5.      Impact assessment and effectiveness evaluation

6.      Interpretation of analytical findings for decision-making

Case Study:
Evaluating the effectiveness of a maternal and child health program using health outcome data.

Module 5: Data Visualization, Dashboards, and Predictive Analytics

1.      Health data visualization principles and best practices

2.      Dashboard design for healthcare performance monitoring

3.      Geographic Information Systems (GIS) in public health

4.      Predictive analytics and disease forecasting

5.      Healthcare performance and utilization analytics

6.      Communicating health insights to stakeholders

Case Study:
Developing a public health dashboard to monitor disease trends, service delivery, and population health outcomes.

Module 6: Emerging Technologies and Future Trends in Public Health Analytics

1.      Artificial intelligence and machine learning in healthcare

2.      Big data analytics and digital health innovations

3.      Real-time surveillance and early warning systems

4.      Precision public health and personalized interventions

5.      Health informatics and decision-support systems

6.      Future trends in public health analytics and healthcare transformation

Case Study:
Designing an integrated public health analytics system that combines surveillance data, electronic health records, predictive modeling, GIS mapping, and real-time dashboards to support disease prevention, healthcare planning, policy development, and improved population health outcomes.

 

 

 

Essential Information

 

1. Our courses are customizable to suit the specific needs of participants.
2. Participants are required to have proficiency in the English language.
3. Our training sessions feature comprehensive guidance through presentations, practical exercises, web-based tutorials, and collaborative group activities. Our facilitators boast extensive expertise, each with over a decade of experience.
4. Upon fulfilling the training requirements, participants will receive a prestigious Global King Project Management certificate.
5. Training sessions are conducted at various Global King Project Management Centers, including locations in Nairobi, Mombasa, Kigali, Dubai, Lagos, and others.
6. Organizations sending more than two participants from the same entity are eligible for a generous 20% discount.
7. The duration of our courses is adaptable, and the curriculum can be adjusted to accommodate any number of days.
8. To ensure seamless preparation, payment is expected before the commencement of training, facilitated through the Global King Project Management account.
9. For inquiries, reach out to us via email at training@globalkingprojectmanagement.org or by phone at +254 114 830 889.
10. Additional amenities such as tablets and laptops are available upon request for an extra fee. The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a certificate of successful completion. Participants are responsible for arranging and covering their travel expenses, including airport transfers, visa applications, dinners, health insurance, and any other personal expenses.