The primary importance of stacking in epidemiological studies lies in its ability to enhance prediction accuracy. By integrating multiple models, researchers can mitigate the limitations and biases inherent in individual models. This leads to more reliable forecasts, which are crucial for timely interventions and policy-making in public health.
