Abstract
We discuss the uses of networks as epidemiological tools to describe the interactions taking place within populations. The difficulties of accurate measurement of real-world social networks are discussed, along with modelling approaches designed to require only incomplete data. Properties of human contact networks such as clustering and variable strengths of interactions are seen to be important factors in the spread of an epidemic. We consider the evolution of a pathogen spreading through a dynamic network and show that the pattern of contacts within a host population determines the evolutionary pressures that a pathogen experiences.
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Eames, K.T.D., Read, J.M. (2008). Networks in Epidemiology. In: Liò, P., Yoneki, E., Crowcroft, J., Verma, D.C. (eds) Bio-Inspired Computing and Communication. BIOWIRE 2007. Lecture Notes in Computer Science, vol 5151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92191-2_8
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DOI: https://doi.org/10.1007/978-3-540-92191-2_8
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