Time-series analysis is crucial for monitoring and predicting trends over time. Techniques like autoregressive integrated moving average (ARIMA) models can forecast future incidences of disease by analyzing past trends. This is particularly useful in infectious disease epidemiology for anticipating outbreaks.
