Several types of data structures are commonly used in epidemiology:
Tabular data: This is the most common form, represented in rows and columns, often using spreadsheets or databases. Each row typically represents an individual case or event, while columns capture variables such as age, sex, and exposure status. Hierarchical data: This structure involves data with a parent-child relationship, often used in family tree and lineage studies, where data points are nested within each other. Relational databases: These databases use tables to organize data and are linked through keys and indexes. They are suitable for managing large datasets with complex relationships. Time-series data: Used to analyze trends over time, this structure is crucial for tracking the progression of an outbreak or monitoring the impact of interventions.
