There are several challenges in making accurate epidemiological predictions, such as:
Data Quality: Incomplete, inaccurate, or biased data can lead to unreliable predictions. Model Assumptions: Models are based on assumptions that may not always hold true in real-world scenarios. Emerging Diseases: New pathogens can introduce unpredictability, as there may be limited data and understanding of their behavior. Human Behavior: Changes in public behavior, compliance with health measures, and other social factors can significantly impact disease spread and are often difficult to predict.
