Recalibration typically involves the following steps:
Data Collection: Gathering new data from recent studies, surveillance systems, or clinical observations. Model Assessment: Evaluating the current model's performance by comparing its predictions with actual outcomes. Model Adjustment: Modifying the model parameters to better fit the new data. Validation: Testing the recalibrated model to ensure its accuracy and reliability before applying it to real-world scenarios.
