Epidemiological data and processes are inherently complex, involving numerous variables such as human behavior, environmental factors, and biological mechanisms. Simplifying assumptions allow researchers to focus on the most critical elements of a problem. They help in:
- Reducing Complexity: Simplifying assumptions can strip away less critical elements, allowing researchers to focus on core dynamics. - Feasibility: Some models would be computationally impossible or impractical without certain assumptions. - Understanding: Simplified models can help in better understanding the fundamental mechanisms of disease spread.
