SIQR dynamics in a random network with heterogeneous connections with infection age

Journal of Nonlinear Sciences and Applications Pub Date : 2020-12-27 DOI:10.22436/jnsa.014.04.02

Hairong Yan, Jinxian Li

引用次数: 3

Abstract

In this paper, an SIQR-Epidemic transmission model of the non-Markovian infection process and quarantine process in a heterogeneous complex network is established, in which the infection rate and quarantine rate are related to infection age. Next, we use the method of characteristics to transform the model into an integro-differential equation and derive the epidemic threshold of the model. Finally, we focus on the impact of three different infection or quarantine time distributions on the disease transmission and show that infection or quarantine time distribution has a significant effect on the disease dynamics.

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具有异质连接的随机网络中的SIQR动态与感染年龄

本文建立了异质复杂网络中非马尔可夫感染过程和隔离过程的SIQR-Epidemic传播模型，其中感染率和隔离率与感染年龄相关。其次，利用特征法将模型转化为积分-微分方程，推导出模型的流行阈值。最后，我们重点研究了三种不同的感染或隔离时间分布对疾病传播的影响，并表明感染或隔离时间分布对疾病动态有显著影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Nonlinear Sciences and Applications MATHEMATICS, APPLIED-MATHEMATICS

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期刊介绍： The Journal of Nonlinear Science and Applications (JNSA) (print: ISSN 2008-1898 online: ISSN 2008-1901) is an international journal which provides very fast publication of original research papers in the fields of nonlinear analysis. Journal of Nonlinear Science and Applications is a journal that aims to unite and stimulate mathematical research community. It publishes original research papers and survey articles on all areas of nonlinear analysis and theoretical applied nonlinear analysis. All articles are fully refereed and are judged by their contribution to advancing the state of the science of mathematics. Manuscripts are invited from academicians, research students, and scientists for publication consideration. Papers are accepted for editorial consideration through online submission with the understanding that they have not been published, submitted or accepted for publication elsewhere.