Bayesian methods offer several advantages in epidemiology: 1. Incorporation of Prior Knowledge: It allows the incorporation of existing knowledge or expert opinion, which is particularly useful in emerging infectious diseases where data may be sparse. 2. Flexibility: Bayesian models can handle complex data structures and are adaptable to various epidemiological study designs. 3. Uncertainty Quantification: It provides a natural way to quantify uncertainty in parameter estimates and predictions. 4. Sequential Updating: Bayesian methods are well-suited for real-time data analysis, as they allow for sequential updating of predictions as new data becomes available.
