Assessing missing data

⚠️ Section Under Development

Objectives

• Learn systematic approaches to detect and visualize missing data patterns in surveillance systems
• Examine missingness across temporal, spatial, and demographic dimensions
• Identify structural zeros, legitimate zeros, and logical inconsistencies in related indicators
• Distinguish between MCAR, MAR, and MNAR missing data mechanisms
• Apply diagnostic visualizations to assess data quality and reporting completeness
• Generate comprehensive missing data assessments to inform analytical decisions