Course Summary:

The "Data For Action" course is designed to equip participants with the essential skills needed to conduct effective data analysis using Epi-Info, a powerful software tool widely used in epidemiology and public health.

The course will focus on hands-on training, providing participants with practical knowledge and techniques to transform raw data into actionable insights. Whether you are a public health professional, researcher, or anyone dealing with data in the context of health studies, this course will enhance your data analysis capabilities and empower you to make informed decisions based on evidence.

Course Objectives:

1. Introduction to Epi-Info: Familiarize participants with the Epi-Info software, its features, and its applications in epidemiological studies and public health research.

2. Data Entry and Management: Develop proficiency in entering, cleaning, and managing data efficiently within the Epi-Info environment.

3. Exploratory Data Analysis (EDA): Learn the fundamentals of exploratory data analysis, including summary statistics, data visualization, and identifying patterns in the data.

4. Descriptive Epidemiology: Understand the principles of descriptive epidemiology and apply Epi-Info tools to analyze and interpret disease patterns, demographic characteristics, and other relevant factors.

5. Analytical Epidemiology: Gain hands-on experience in conducting analytical studies using Epi-Info, including case-control studies, cohort studies, and cross-sectional studies.

6. Statistical Analysis: Develop skills in basic statistical analysis using Epi-Info, covering measures of association, hypothesis testing, and interpreting results.

7. Data Visualization: Learn techniques for creating compelling and informative visualizations to communicate data findings effectively to different audiences.

8. Data Export and Reporting: Explore methods for exporting data from Epi-Info and creating reports suitable for publication and presentation.

9. Quality Assurance and Validation: Understand the importance of data quality assurance and validation processes to ensure the reliability and accuracy of findings.

10. Real-world Applications: Apply the acquired knowledge and skills to real-world public health scenarios, fostering a practical understanding of how data analysis contributes to informed decision-making.

Course Outline

Module 1: Introduction to Epi-Info

• Overview of Epi-Info
• Installation and setup
• Interface and basic functionalities

Module 2: Data Entry and Management

• Creating databases
• Data entry forms
• Data cleaning and validation

Module 3: Exploratory Data Analysis (EDA)

• Descriptive statistics
• Data visualization techniques
• Identifying outliers and trends

Module 4: Descriptive Epidemiology

• Disease mapping
• Demographic analysis
• Time-trend analysis

Module 5: Analytical Epidemiology

• Case-control studies
• Cohort studies
• Cross-sectional studies

Module 6: Statistical Analysis

• Measures of association
• Hypothesis testing
• Interpreting statistical results

Module 7: Data Visualization

• Creating graphs and charts
• Customizing visualizations
• Effective communication of results

Module 8: Data Export and Reporting

• Exporting data from Epi-Info
• Generating reports
• Data interpretation and presentation

Module 9: Quality Assurance and Validation

• Ensuring data accuracy
• Quality control measures
• Validation techniques

Module 10: Real-world Applications

• Practical exercises and case studies
• Applying Epi-Info skills to real-world scenarios
• Q&A and discussion on participants' projects