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Computer Sciences, Epidemiology
Agent-based models can be used to help study the spread of infectious diseases within a population. As no individual town is in isolation, commuting patterns into and out of a town or city are a vital part of understanding the course of an outbreak within a town. Thus the centrality of a town in a network of towns, such as a county or an entire country, should be an important influence on an outbreak. We propose looking at the probability that an outbreak enters a given town in a region and comparing that probability to the centrality of the town. Our results show that as expected there is a relationship between centrality and outbreaks. Specifically, we found that the degree of centrality of a town affected the likelihood of an outbreak within the network spreading to the town. We also found that for towns where an outbreak begins the degree of centrality of the town affects how the outbreak spreads in the network.
Hunter, E., Mac Namee, B. & Kelleher, J.D. (2019) Degree Centrality and the Probability of an Infectious Disease Outbreak in Towns within a Region, The 33rd annual European Simulation and Modelling Conference 2019,