This topic concerns the development and application of mathematical, numerical, and data-driven methods for modelling the spread of infectious diseases, simulating epidemic scenarios, and supporting surveillance systems. It combines compartmental models, agent-based simulations, numerical methods for differential equations, statistical inference, machine learning, and real-time epidemiological data analysis to improve outbreak detection, forecasting, and public-health decision-making.
SCHEDULE:
25/05 Aula H 12:30-14:30
26/05 Aula T.03 11:30 - 13:30
27/05 (2 hours) TBA
