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Complex relationships: modelling epidemics on human social networks

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The speed and extent of spread of an epidemic are determined by the behaviour of the population through which it passes; however, understanding, measuring, and accouting for the complexities of population behaviour are challenging problems. Here, we look at contact networks as tools to represent human mixing patterns, using an unusually detailed dataset to explore some of the social factors that influence disease spread. Considering the example of Cassanova, Henry VIII , and the Mormons, we identify gaps in our models.

This talk is part of the Computational and Systems Biology series.

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