Analysis of stochastic epidemic model with awareness decay and heterogeneous individuals on multi-weighted networks

In the current study, we present a stochastic SAIS (unaware susceptible-aware susceptible-infectious-unaware susceptible) epidemic dynamic model on complex networks with multi-weights. The disease dynamic is influenced by random perturbations to the force of the infection rates, as well as awareness rates. To analyze the problem of extinction, we discuss both the stochastic asymptotic stability in the large and almost surely exponential stability of the trivial solution. Then, we get some sufficient conditions, which guarantee the stochastic persistence of infectious disease. Based on the Erdös-Réyni random graph, the numerical simulations are given. These not only validate our conclusions but also obtain else significative results. Both theoretical results and numerical simulations further reflect that improvement of risk awareness and reduction of decay in awareness are highly effective in preventing disease spread. And then, environmental noises play a significant role in disease transmission.

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Publication Details

Journal
Scientific Reports
Published
2024-11-05
DOI
https://doi.org/10.1038/s41598-024-78218-4
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Analysis of stochastic epidemic model with awareness decay and heterogeneous individuals on multi-weighted networks

Guirong Liu, Xin Yi
Scientific Reports
Complex Network Analysis Techniques
article

Analysis of stochastic epidemic model with awareness decay and heterogeneous individuals on multi-weighted networks

Guirong Liu, Xin Yi
article en

Abstract

In the current study, we present a stochastic SAIS (unaware susceptible-aware susceptible-infectious-unaware susceptible) epidemic dynamic model on complex networks with multi-weights. The disease dynamic is influenced by random perturbations to the force of the infection rates, as well as awareness rates. To analyze the problem of extinction, we discuss both the stochastic asymptotic stability in the large and almost surely exponential stability of the trivial solution. Then, we get some sufficient conditions, which guarantee the stochastic persistence of infectious disease. Based on the Erdös-Réyni random graph, the numerical simulations are given. These not only validate our conclusions but also obtain else significative results. Both theoretical results and numerical simulations further reflect that improvement of risk awareness and reduction of decay in awareness are highly effective in preventing disease spread. And then, environmental noises play a significant role in disease transmission.

Scientific ReportsVol. 14(1)
Taiyuan Normal University (CN), Shanxi University (CN)
National Natural Science Foundation of China, Shanxi Provincial Key Research and Development Project
Good health and well-being
Openalex Percentile: Top 82%
Complex Network Analysis Techniques
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Analysis of stochastic epidemic model with awareness decay and heterogeneous individuals on multi-weighted networks — Guirong Liu, Xin Yi · Scientific Reports (2024) | TGRS Research Map | TGRS