Epidemic Spreading Combined with Age and Region in Complex Networks

Xu Zhang; Yurong Song; Haiyan Wang; Guo Ping Jiang

doi:10.1155/2020/6753798

Epidemic Spreading Combined with Age and Region in Complex Networks

Xu Zhang, Yurong Song, Haiyan Wang, Guo Ping Jiang

Mathematical and Natural Sciences, School of (SMNS)

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

In social networks, the age and the region of individuals are the two most important factors in modeling infectious diseases. In this paper, a spatial susceptible-infected-susceptible (SIS) model is proposed to describe epidemic spreading over a network with region and age by establishing several partial differential equations. Numerical simulations are performed, and the simulation of the proposed model agrees well with real influenza-like illness (ILI) in the USA reported by the Centers for Disease Control (CDC). Moreover, the proposed model can be used to predict the infected density of individuals. The results show that our model can be used as a tool to analyze influenza cases in the real world.

Original language	English (US)
Article number	6753798
Journal	Mathematical Problems in Engineering
Volume	2020
DOIs	https://doi.org/10.1155/2020/6753798
State	Published - 2020

ASJC Scopus subject areas

Mathematics(all)
Engineering(all)

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title = "Epidemic Spreading Combined with Age and Region in Complex Networks",

abstract = "In social networks, the age and the region of individuals are the two most important factors in modeling infectious diseases. In this paper, a spatial susceptible-infected-susceptible (SIS) model is proposed to describe epidemic spreading over a network with region and age by establishing several partial differential equations. Numerical simulations are performed, and the simulation of the proposed model agrees well with real influenza-like illness (ILI) in the USA reported by the Centers for Disease Control (CDC). Moreover, the proposed model can be used to predict the infected density of individuals. The results show that our model can be used as a tool to analyze influenza cases in the real world.",

author = "Xu Zhang and Yurong Song and Haiyan Wang and Jiang, {Guo Ping}",

note = "Funding Information: Xu Zhang, Yurong Song, and Guo-Ping Jiang were supported by the National Natural Science Foundation of China (Grant nos. 61672298, 61873326, 61802155, and 61802201) and the Philosophy Social Science Research Key Project Fund of Jiangsu University (Grant no. 2018SJZDI142). Publisher Copyright: {\textcopyright} 2020 Xu Zhang et al.",

year = "2020",

doi = "10.1155/2020/6753798",

language = "English (US)",

volume = "2020",

journal = "Mathematical Problems in Engineering",

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TY - JOUR

T1 - Epidemic Spreading Combined with Age and Region in Complex Networks

AU - Zhang, Xu

AU - Song, Yurong

AU - Wang, Haiyan

AU - Jiang, Guo Ping

N1 - Funding Information: Xu Zhang, Yurong Song, and Guo-Ping Jiang were supported by the National Natural Science Foundation of China (Grant nos. 61672298, 61873326, 61802155, and 61802201) and the Philosophy Social Science Research Key Project Fund of Jiangsu University (Grant no. 2018SJZDI142). Publisher Copyright: © 2020 Xu Zhang et al.

PY - 2020

Y1 - 2020

N2 - In social networks, the age and the region of individuals are the two most important factors in modeling infectious diseases. In this paper, a spatial susceptible-infected-susceptible (SIS) model is proposed to describe epidemic spreading over a network with region and age by establishing several partial differential equations. Numerical simulations are performed, and the simulation of the proposed model agrees well with real influenza-like illness (ILI) in the USA reported by the Centers for Disease Control (CDC). Moreover, the proposed model can be used to predict the infected density of individuals. The results show that our model can be used as a tool to analyze influenza cases in the real world.

AB - In social networks, the age and the region of individuals are the two most important factors in modeling infectious diseases. In this paper, a spatial susceptible-infected-susceptible (SIS) model is proposed to describe epidemic spreading over a network with region and age by establishing several partial differential equations. Numerical simulations are performed, and the simulation of the proposed model agrees well with real influenza-like illness (ILI) in the USA reported by the Centers for Disease Control (CDC). Moreover, the proposed model can be used to predict the infected density of individuals. The results show that our model can be used as a tool to analyze influenza cases in the real world.

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JF - Mathematical Problems in Engineering

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Epidemic Spreading Combined with Age and Region in Complex Networks

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