While disease simulation is a powerful tool, it has limitations:
1. Data Quality: The accuracy of the simulation depends on the quality and completeness of the input data. 2. Assumptions: Models often rely on assumptions that may not hold in real-world scenarios, potentially affecting the results. 3. Complexity: Simulating complex interactions within a population can be computationally intensive and challenging. 4. Uncertainty: Predictions are inherently uncertain, and unexpected factors can influence the outcomes.
