• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

疫苗失败率对响应式网络中流行动态的影响。

The impact of vaccine failure rate on epidemic dynamics in responsive networks.

作者信息

Liang Yu-Hao, Juang Jonq

机构信息

Department of Applied Mathematics, National Chiao Tung University, Hsinchu, Taiwan.

Department of Applied Mathematics, and Center of Mathematics Modeling and Scientific Computing, National Chiao Tung University, Hsinchu, Taiwan.

出版信息

Chaos. 2015 Apr;25(4):043116. doi: 10.1063/1.4919245.

DOI:10.1063/1.4919245
PMID:25933664
Abstract

An SIS model based on the microscopic Markov-chain approximation is considered in this paper. It is assumed that the individual vaccination behavior depends on the contact awareness, local and global information of an epidemic. To better simulate the real situation, the vaccine failure rate is also taken into consideration. Our main conclusions are given in the following. First, we show that if the vaccine failure rate α is zero, then the epidemic eventually dies out regardless of what the network structure is or how large the effective spreading rate and the immunization response rates of an epidemic are. Second, we show that for any positive α, there exists a positive epidemic threshold depending on an adjusted network structure, which is only determined by the structure of the original network, the positive vaccine failure rate and the immunization response rate for contact awareness. Moreover, the epidemic threshold increases with respect to the strength of the immunization response rate for contact awareness. Finally, if the vaccine failure rate and the immunization response rate for contact awareness are positive, then there exists a critical vaccine failure rate αc > 0 so that the disease free equilibrium (DFE) is stable (resp., unstable) if α < αc (resp., α > αc). Numerical simulations to see the effectiveness of our theoretical results are also provided.

摘要

本文考虑了一种基于微观马尔可夫链近似的SIS模型。假设个体的疫苗接种行为取决于对疫情的接触意识、局部和全局信息。为了更好地模拟实际情况,还考虑了疫苗失败率。我们的主要结论如下。首先,我们表明,如果疫苗失败率α为零,那么无论网络结构如何,也无论疫情的有效传播率和免疫反应率有多大,疫情最终都会消失。其次,我们表明,对于任何正的α,存在一个取决于调整后网络结构的正的疫情阈值,它仅由原始网络的结构、正的疫苗失败率和对接触意识的免疫反应率决定。此外,疫情阈值随着对接触意识的免疫反应率的强度而增加。最后,如果疫苗失败率和对接触意识的免疫反应率为正,那么存在一个临界疫苗失败率αc > 0,使得如果α < αc(分别地,α > αc),无病平衡点(DFE)是稳定的(分别地,不稳定的)。还提供了数值模拟以验证我们理论结果的有效性。

相似文献

1
The impact of vaccine failure rate on epidemic dynamics in responsive networks.疫苗失败率对响应式网络中流行动态的影响。
Chaos. 2015 Apr;25(4):043116. doi: 10.1063/1.4919245.
2
On the impact of epidemic severity on network immunization algorithms.论疫情严重程度对网络免疫算法的影响
Theor Popul Biol. 2015 Dec;106:83-93. doi: 10.1016/j.tpb.2015.10.007. Epub 2015 Oct 23.
3
Responsive immunization and intervention for infectious diseases in social networks.社交网络中传染病的响应式免疫与干预
Chaos. 2014 Jun;24(2):023108. doi: 10.1063/1.4872177.
4
The impact of vaccine success and awareness on epidemic dynamics.疫苗成效与认知对疫情动态的影响。
Chaos. 2016 Nov;26(11):113105. doi: 10.1063/1.4966945.
5
Measuring Infection Transmission in a Stochastic SIV Model with Infection Reintroduction and Imperfect Vaccine.测量具有感染再引入和不完美疫苗的随机 SIV 模型中的感染传播。
Acta Biotheor. 2020 Dec;68(4):395-420. doi: 10.1007/s10441-019-09373-9. Epub 2020 Jan 8.
6
Epidemic dynamics on semi-directed complex networks.半有向复杂网络上的传染病动力学。
Math Biosci. 2013 Dec;246(2):242-51. doi: 10.1016/j.mbs.2013.10.001. Epub 2013 Oct 17.
7
Analysis of an epidemic model with awareness decay on regular random networks.基于规则随机网络上具有认知衰退的传染病模型分析
J Theor Biol. 2015 Jan 21;365:457-68. doi: 10.1016/j.jtbi.2014.10.013. Epub 2014 Oct 23.
8
Epidemic spreading in a hierarchical social network.流行病在分层社会网络中的传播。
Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Sep;70(3 Pt 1):031908. doi: 10.1103/PhysRevE.70.031908. Epub 2004 Sep 21.
9
Susceptible-infected-susceptible model: a comparison of N-intertwined and heterogeneous mean-field approximations.易感-感染-易感模型:N 交织与异质平均场近似的比较
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Aug;86(2 Pt 2):026116. doi: 10.1103/PhysRevE.86.026116. Epub 2012 Aug 28.
10
Human mobility and time spent at destination: impact on spatial epidemic spreading.人口流动与停留时间:对空间传染病传播的影响。
J Theor Biol. 2013 Dec 7;338:41-58. doi: 10.1016/j.jtbi.2013.08.032. Epub 2013 Sep 4.

引用本文的文献

1
Global stability for epidemic models on multiplex networks.多重网络上流行病模型的全局稳定性
J Math Biol. 2018 May;76(6):1339-1356. doi: 10.1007/s00285-017-1179-5. Epub 2017 Sep 7.
2
Behavioural change models for infectious disease transmission: a systematic review (2010-2015).传染病传播的行为改变模型:一项系统综述(2010 - 2015年)
J R Soc Interface. 2016 Dec;13(125). doi: 10.1098/rsif.2016.0820.
3
The impact of vaccine success and awareness on epidemic dynamics.疫苗成效与认知对疫情动态的影响。
Chaos. 2016 Nov;26(11):113105. doi: 10.1063/1.4966945.