Hybrid AI Model Improves Pandemic Forecast Accuracy and Interpretability

Researchers have introduced a hybrid forecasting framework combining an SEIR epidemiological model with a Temporal Fusion Transformer. This new AI approach aims to provide more stable and accurate multi-horizon infection forecasts, particularly during changing intervention regimes, using region-wise COVID-19 data. The preliminary work offers a practical decision-support system for policy-sensitive pandemic forecasting by integrating mechanistic modeling, deep learning, and explainable AI.