Recalibration refers to the systematic adjustment of a predictive model to align its outputs more closely with observed outcomes. It is particularly important in epidemiology, where models predict the spread, impact, and control of diseases. Recalibration ensures that these models remain accurate in the face of changing disease dynamics, environmental factors, and population behaviors.
