Computational modeling is increasingly important in epidemiology. Models can simulate the spread of diseases, predict the impact of interventions, and optimize resource allocation. However, these models require detailed input data and assumptions about disease transmission, which can introduce uncertainty. Building and validating these models often involves interdisciplinary collaboration between epidemiologists, mathematicians, and computer scientists.
