In risk assessment, Bayesian models provide a method to quantify the uncertainty and variability of the estimated risks. By incorporating prior information, such as historical data or expert opinion, these models can improve the estimation of risk probabilities. This leads to more adaptive and dynamic risk assessments, which are crucial for regulatory decision-making in public health.
