Self-Awareness-Based Resource Allocation Strategy for Containment of Epidemic Spreading

Resource support between individuals is of particular importance in controlling or mitigating epidemic spreading, especially during pandemics. However, there remains the question of how we can protect ourselves from being infected while helping others by donating resources in fighting against the ep...

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Main Authors: Xiaolong Chen, Quanhui Liu, Ruijie Wang, Qing Li, Wei Wang
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/3256415
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author Xiaolong Chen
Quanhui Liu
Ruijie Wang
Qing Li
Wei Wang
author_facet Xiaolong Chen
Quanhui Liu
Ruijie Wang
Qing Li
Wei Wang
author_sort Xiaolong Chen
collection DOAJ
description Resource support between individuals is of particular importance in controlling or mitigating epidemic spreading, especially during pandemics. However, there remains the question of how we can protect ourselves from being infected while helping others by donating resources in fighting against the epidemic. To answer the question, we propose a novel resource allocation model by considering the awareness of self-protection of individuals. In the model, a tuning parameter is introduced to quantify the reaction strength of individuals when they are aware of the disease. And then, a coupled model of resource allocation and disease spreading is proposed to study the impact of self-awareness on resource allocation and its impact on the dynamics of epidemic spreading. Through theoretical analysis and extensive Monte Carlo simulations, we find that in the stationary state, the system converges to two states: the whole healthy or the completely infected, which indicates an abrupt increase in the prevalence when there is a shortage of resources. More importantly, we find that too cautious and too selfless for the people during the outbreak of an epidemic are both not suitable for disease control. Through extensive simulations, we locate the optimal point, at which there is a maximum value of the epidemic threshold, and an outbreak can be delayed to the greatest extent. At last, we study further the effects of the network structure on the coupled dynamics. We find that the degree heterogeneity promotes the outbreak of disease, and the network structure does not alter the optimal phenomenon in behavior response. Based on the results of this study, a constructive suggestion is that in the face of a global pandemic, individuals or countries should strengthen mutual support and cooperation while doing their own prevention to suppress the epidemic optimally.
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spelling doaj-art-649fe69f1dcb43a4a0687fe83bae44ad2025-08-20T02:23:51ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/32564153256415Self-Awareness-Based Resource Allocation Strategy for Containment of Epidemic SpreadingXiaolong Chen0Quanhui Liu1Ruijie Wang2Qing Li3Wei Wang4Financial Intelligence and Financial Engineering Key Laboratory of Sichuan Province, School of Economic Information Engineering, Southwestern University of Finance and Economics, Chengdu 611130, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaAba Teachers University, Aba 623002, ChinaFinancial Intelligence and Financial Engineering Key Laboratory of Sichuan Province, School of Economic Information Engineering, Southwestern University of Finance and Economics, Chengdu 611130, ChinaCybersecurity Research Institute, Sichuan University, Chengdu 610065, ChinaResource support between individuals is of particular importance in controlling or mitigating epidemic spreading, especially during pandemics. However, there remains the question of how we can protect ourselves from being infected while helping others by donating resources in fighting against the epidemic. To answer the question, we propose a novel resource allocation model by considering the awareness of self-protection of individuals. In the model, a tuning parameter is introduced to quantify the reaction strength of individuals when they are aware of the disease. And then, a coupled model of resource allocation and disease spreading is proposed to study the impact of self-awareness on resource allocation and its impact on the dynamics of epidemic spreading. Through theoretical analysis and extensive Monte Carlo simulations, we find that in the stationary state, the system converges to two states: the whole healthy or the completely infected, which indicates an abrupt increase in the prevalence when there is a shortage of resources. More importantly, we find that too cautious and too selfless for the people during the outbreak of an epidemic are both not suitable for disease control. Through extensive simulations, we locate the optimal point, at which there is a maximum value of the epidemic threshold, and an outbreak can be delayed to the greatest extent. At last, we study further the effects of the network structure on the coupled dynamics. We find that the degree heterogeneity promotes the outbreak of disease, and the network structure does not alter the optimal phenomenon in behavior response. Based on the results of this study, a constructive suggestion is that in the face of a global pandemic, individuals or countries should strengthen mutual support and cooperation while doing their own prevention to suppress the epidemic optimally.http://dx.doi.org/10.1155/2020/3256415
spellingShingle Xiaolong Chen
Quanhui Liu
Ruijie Wang
Qing Li
Wei Wang
Self-Awareness-Based Resource Allocation Strategy for Containment of Epidemic Spreading
Complexity
title Self-Awareness-Based Resource Allocation Strategy for Containment of Epidemic Spreading
title_full Self-Awareness-Based Resource Allocation Strategy for Containment of Epidemic Spreading
title_fullStr Self-Awareness-Based Resource Allocation Strategy for Containment of Epidemic Spreading
title_full_unstemmed Self-Awareness-Based Resource Allocation Strategy for Containment of Epidemic Spreading
title_short Self-Awareness-Based Resource Allocation Strategy for Containment of Epidemic Spreading
title_sort self awareness based resource allocation strategy for containment of epidemic spreading
url http://dx.doi.org/10.1155/2020/3256415
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