Demand forecasting in epidemiology typically involves the following steps: 1. Data Collection: Gathering historical data on disease incidence, healthcare utilization, and population demographics. 2. Model Selection: Choosing appropriate predictive models, such as time-series analysis, machine learning models, or compartmental models like SIR (Susceptible-Infectious-Recovered). 3. Validation: Validating models using a subset of the data to ensure accuracy. 4. Prediction: Using the models to make forecasts and predict future demand for healthcare resources.
