There are several methods used in disease forecasting:
Time-Series Analysis: Uses historical data to predict future trends. Mathematical Modeling: Includes compartmental models like SIR (Susceptible, Infected, Recovered) to simulate disease transmission dynamics. Machine Learning: Employs algorithms to analyze large datasets and make predictions. Geospatial Analysis: Utilizes geographic information systems (GIS) to map disease spread. Sentinel Surveillance: Involves monitoring specific sites or populations for early signs of disease.
