In Epidemiology, understanding the spread and control of diseases often relies on historical data. AR models help in forecasting future disease incidence based on past trends, which can be invaluable for public health planning and intervention. They are effective in capturing the temporal dependencies inherent in epidemiological data, making them a robust tool for disease prediction and control measures.