Model updating can be performed through several methods:
Parameter Estimation: Adjusting parameters to reflect new data, such as transmission rates or recovery rates. Data Assimilation: Integrating real-time data into models to update predictions. Model Calibration: Fine-tuning the model to fit observed data more accurately. Bayesian Updating: Using Bayesian methods to update model probabilities as new data is acquired.
