Discover the concepts, methods, and tools for carrying out infectious disease modelling, as well as for developing models further by leveraging the power of genomics. Modelling infectious diseases can help to understand the mechanisms of pathogen evolution and predict the development of epidemics. This had an immense impact on the COVID-19 pandemic and is crucial for the general surveillance of pathogens. During the course, you will learn about compartmental models, such as Susceptible-Infectious-Recovered (SIR) models, how to adapt them to a pathogen of your interest, and the differences between stochastic and deterministic models. You'll then apply these models to epidemic settings to predict changes in case numbers and disease severity. Additionally, you'll implement and adapt genomics-informed models for pathogen evolution, including multi-strain and Wright-Fisher models, and learn how to combine population genetics with epidemic models. You'll also make use of genomics to create timed phylogenies and reconstruct ancestral states. Finally, bringing together transmission modelling and genomic data, we'll study phylodynamic models and how this can help to detect changes in case numbers and pathogenicity earlier and more reliably than with transmission models alone.