d-cliqued图流行病建模

Q3 Mathematics
L. Schaposnik, Anlin Zhang
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引用次数: 1

摘要

摘要由于社会互动已被证明会导致对称集群,我们在这里提出对称性在流行病建模中起着关键作用。最近,d元树图上的数学模型被证明在简单网络中对流行病建模特别有效。为了说明对称关系,我们将其推广到一种新的基于d群树图的网络,该网络是通过向正则d树添加边来形成d群而获得的。这种设置为源自家庭或教室的流行病疫情提供了一个更现实的模型,这些疫情可能通过学校的儿童传播给人群。具体来说,我们量化了从一个群体(如家庭)开始的感染如何通过图体(如公共场所)传播到其他群体。此外,我们提出并研究了安全区的概念,即感染概率可忽略不计的子集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling epidemics on d-cliqued graphs
Abstract Since social interactions have been shown to lead to symmetric clusters, we propose here that symmetries play a key role in epidemic modelling. Mathematical models on d-ary tree graphs were recently shown to be particularly effective for modelling epidemics in simple networks. To account for symmetric relations, we generalize this to a new type of networks modelled on d-cliqued tree graphs, which are obtained by adding edges to regular d-trees to form d-cliques. This setting gives a more realistic model for epidemic outbreaks originating within a family or classroom and which could reach a population by transmission via children in schools. Specifically, we quantify how an infection starting in a clique (e.g. family) can reach other cliques through the body of the graph (e.g. public places). Moreover, we propose and study the notion of a safe zone, a subset that has a negligible probability of infection.
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来源期刊
Letters in Biomathematics
Letters in Biomathematics Mathematics-Statistics and Probability
CiteScore
2.00
自引率
0.00%
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0
审稿时长
14 weeks
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