Abstract

This two-hour talk, explores how real-world epidemiological data can be used to calibrate and validate mathematical models of infectious disease spread. Participants will gain hands-on insight into parameter estimation techniques, with a particular focus on the Least Squares method for fitting compartmental models such as SIR and SEIR. The session also introduces model validation strategies, helping participants assess how well a model captures observed dynamics. The talk also covers sensitivity analysis, which looks at how changes in key factors affect the spread of disease. It emphasizes the importance of identifying and focusing on the most important factors when planning public health interventions. By combining theoretical understanding with practical examples, this session equips public health professionals, researchers, and students with essential tools for connecting models to real-world data and enhancing the predictive power of epidemiological models.