Complex models for the spread of infectious diseases: linking biology, epidemiology and social network analysis

Mathematical models of infectious disease spread are playing an increasingly important role in health policy planning, for example in influenza pandemic preparedness planning. With increasing utilisation, the tension between parsimony and complexity increases. Simple models are appealing due to their ease of interpretation. Complex models are appealing due to the details they are able to capture.

Quantitative characterisations of social networks, and in particular, the social interactions that are sufficient for respiratory disease transmission will provide the next level of realism in computer simulations of pathogen spread.

With access to high-powered supercomputing facilities, researchers will be able to simultaneously capture, for the first-time, individual level effects, social- and spatial- network effects and detailed within-human-host pathogen responses. Furthermore, the power to run many thousands of simulations will bring certainty to the outputs and ensure that interpretations of the numerical simulations are valid.

In this presentation James McCaw will discuss how models of influenza spread have been used for pandemic planning. Pip Pattison will discuss the challenges for measuring and then describing social networks relevant to respiratory disease transmission. Both speakers will highlight how the VLSCI will enable them to extract more information from collected data, improving both the characterisations of social networks and the predictions from disease transmission models.

Jame's presentation3.6MB

Animation from slide 11 of James's presentation .avi 24MB

Pip's presentation5MB