Kah Loon Ng

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In the modeling of infectious disease spread within explicit social contact networks, previous studies have predominantly assumed that the effects of shifting social associations within groups are small. These models have utilized static approximations of contact networks. We examine this assumption by modeling disease spread within dynamic networks where(More)
Social networks can be used to represent group structure as a network of interacting components, and also to quantify both the position of each individual and the global properties of a group. In a series of simulation experiments based on dynamic social networks, we test the prediction that social behaviors that help individuals reach prominence within(More)
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