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Effect of Vaccination Strategies on the Herd Immunity of Growing Networks

机译:疫苗接种策略对生长网络畜牧业的影响

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It is well known that non-vaccinated individuals may be protected from contacting a disease by vaccinated individuals in a social network through community protection (herd immunity). Such protection greatly depends on the underlying topology of the social network, and the strategy used in selecting individuals for vaccination. Social networks however undergo constant growth, and it may be argued that network growth may change the level of herd immunity present in social networks. In this paper, we analyse the effect of growth and immunization strategies on herd immunity of social networks. Considering three classical topologies - Random, scale-free and small-world, we compare the influence of immunization strategies on each of them and then discuss how network growth can nullify or amplify these differences. We show that betweenness based vaccination is best strategy of immunization, regardless of topology, in static networks, but its prominence over other strategies diminishes in dynamically growing topologies. We demonstrate that herd immunity of random networks actually increases with growth, if the proportion of survivors to a secondary infection is considered, while the community protection in scale-free and small world networks decreases with growth. We compare the relative influence of growth on each class of networks vaccinated under different strategies.
机译:众所周知,可以通过社区保护(畜群免疫)保护非接种疫苗的个体通过社区网络中的疫苗接种的个体来保护疾病。这种保护大大取决于社交网络的基础拓扑,以及选择个人接种疫苗的策略。然而,社交网络经历了不断的增长,并且可能认为网络增长可能会改变社交网络中存在的畜群免疫水平。在本文中,我们分析了增长和免疫策略对社会网络畜牧业的影响。考虑到三种古典拓扑 - 随机,无规模和小世界,我们比较免疫策略对每个拓扑策略的影响,然后讨论网络增长如何无效或放大这些差异。我们表明基于性的疫苗接种是最佳免疫策略,无论静态网络,拓扑,但它在动态增长的拓扑中突出了其他策略。我们证明随机网络的畜群免疫力实际上随着幸存者的比例考虑到次要感染的比例,而无规模的和小型世界网络的社区保护随着增长而降低。我们比较在不同策略下接种疫苗的每类网络上的相对影响。

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