论文标题
网络分类对流行和疫苗接种行为的影响
Impact of network assortativity on epidemic and vaccination behaviour
论文作者
论文摘要
麻疹的复兴在很大程度上归因于采用疫苗的下降和活动性的增加。尽管麻疹疫苗很容易获得并且非常成功,但目前的采用不足以防止流行病。采用疫苗的采用率直接受个人疫苗接种决策的影响,并且与基本迁移率(行进)网络形成的疾病的空间传播具有复杂的相互作用。在本文中,我们将旅行连通性建模为无标度网络,并研究网络的分类性与结果流行病和疫苗接种动态之间的依赖性。在此过程中,我们扩展了具有游戏理论组件的Sir-Network模型,并在自愿疫苗接种方案下捕获了模仿动态。我们的结果表明,流行性动力学与网络的分类性之间存在相关性,强调了具有高分类性的网络倾向于在某些条件下抑制流行病。在高度分类的网络中,抑制作用持续产生早期融合到平衡。然而,在高度分离的网络中,由于非疫苗接种节点的散射以及在动力学的主要疫苗接种和非疫苗接种阶段之间的频繁切换,抑制作用会随着时间的推移而降低。
The resurgence of measles is largely attributed to the decline in vaccine adoption and the increase in mobility. Although the vaccine for measles is readily available and highly successful, its current adoption is not adequate to prevent epidemics. Vaccine adoption is directly affected by individual vaccination decisions, and has a complex interplay with the spatial spread of disease shaped by an underlying mobility (travelling) network. In this paper, we model the travelling connectivity as a scale-free network, and investigate dependencies between the network's assortativity and the resultant epidemic and vaccination dynamics. In doing so we extend an SIR-network model with game-theoretic components, capturing the imitation dynamics under a voluntary vaccination scheme. Our results show a correlation between the epidemic dynamics and the network's assortativity, highlighting that networks with high assortativity tend to suppress epidemics under certain conditions. In highly assortative networks, the suppression is sustained producing an early convergence to equilibrium. In highly disassortative networks, however, the suppression effect diminishes over time due to scattering of non-vaccinating nodes, and frequent switching between the predominantly vaccinating and non-vaccinating phases of the dynamics.