Epidemic modelling has grown in prominence as a tool to assist public health professionals and policy-makers to plan for and respond to outbreaks of human and animal diseases. Recent examples include Foot and Mouth Disease in livestock, SARS in humans, planning for a severe H5N1 'bird flu' pandemic, and responding to the H1N1 'swine flu' pandemic last year. This series of lectures will review recent progress in the field of epidemic modelling. I will discuss how increasing computer power and expectations of public health 'consumers' of modelling have led to a trend towards dramatically increased model complexity in the last 5 years, posing challenges for model assessment and validation. Fortunately, methodological progress in inference for complex models, plus vastly increased availability of population and epidemiological data offers some potential to meet those challenges. After reviewing developments in model design and parameterisation (Lecture 1), I will discuss how models have been used to inform public health policy making during a range of outbreaks (Lecture 2), before focussing on how modelling can be used to evaluate the risk posed by the evolution of resistance to antiviral drugs during an influenza pandemic (Lecture 3).