论文标题
通过人口异质性在多层网络上传播过程
Spreading processes with population heterogeneity over multi-layer networks
论文作者
论文摘要
重新开放的学校是否会通过缓解措施(例如戴口罩的策略)在家庭社区之间促进病毒传播一直存在争议。在这项工作中,我们提出了一个流行病学模型,该模型探讨了由学校层和社区层组成的多层接触网络的病毒传播,并具有戴面具行为的种群异质性。我们得出了三个关键流行病学量的分析表达:出现的可能性,流行阈值和预期的流行大小。特别是,我们展示了上述量如何取决于多层接触网络的结构,病毒传递动力学以及人群中不同类型的掩码的分布。通过大量的模拟,我们的分析结果表明与仿真结果的一致性近乎完美,节点数量有限。利用该模型,我们研究了学校层开放/关闭对病毒传播动力学的影响,并使用各种戴面膜的场景。有趣的是,我们发现,在人口中,可以使用适当的优质面具比例开放学校层。此外,我们验证了Tian等人在我们的多层设置上对源控制与自我保护之间的权衡理论。我们得出的结论是,即使在多层网络上,在考虑缓解策略时,将扩散过程视为两个不同的阶段也很重要。此外,我们想指出,我们在具有人口异质性的多层网络上传播过程的模型也可以应用于其他各种领域,例如错误信息控制。
It's been controversial whether re-opening school will facilitate viral spread among household communities with mitigation strategies such as mask-wearing in place. In this work, we propose an epidemiological model that explores the viral transmission over the multi-layer contact network composed of the school layer and community layer with population heterogeneity on mask-wearing behavior. We derive analytical expressions for three key epidemiological quantities: the probability of emergence, the epidemic threshold, and the expected epidemic size. In particular, we show how the aforementioned quantities depend on the structure of the multi-layer contact network, viral transmission dynamics, and the distribution of the different types of masks within the population. Through extensive simulations, our analytical results show near-perfect agreement with the simulation results with a limited number of nodes. Utilizing the model, we study the impact of the opening/closure of the school layer on the viral transmission dynamics with various mask-wearing scenarios. Interestingly, we found that it's safe to open the school layer with the proper proportion of good-quality masks in the population. Moreover, we validate the theory of the trade-off between source-control and self-protection over a single layer by Tian et al on our multi-layer setting. We conclude that even on a multi-layer network, it's of great significance to treat the spreading process as two distinct phases in mind when considering mitigation strategies. Besides, we would like to remark that our model of spreading process over multi-layer networks with population heterogeneity can also be applied to various other domains, such as misinformation control.