There are several reasons why ARIMA models are particularly useful in epidemiology:
Flexibility: ARIMA models can handle different types of time series data, including non-stationary data. Accuracy: When properly specified, ARIMA models can provide accurate short-term forecasts. Simplicity: The models are relatively simple to implement and interpret, making them accessible for public health professionals.
