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An SIS epidemic model with vaccination in a dynamical contact network of mobile individuals with heterogeneous spatial constraints

机译:具有异质空间限制的移动人体动态接触网络中的SIS流行病模型

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Network-based epidemic models have been extensively employed to understand the spread of infectious diseases, but have generally overlooked the fact that most realistic networks are dynamical rather than static. In this paper, we study a susceptible-infected-susceptible epidemic model with vaccination in a dynamical contact network of moving individuals, where we regard mobile individuals as random walkers that are allowed to perform long-range jumps. Different from previous studies of epidemics in a random walk network with a constant interaction radius, we consider the scenario where the individuals have a heterogeneous distribution of interaction radius r and infected individuals are vaccinated with a probability depending on the interaction radius distribution. We derive the basic reproduction number R-0, which is strongly related to the interaction radius distribution and is proportional to the second order moment of interaction radius r(2) in the special case of a constant vaccination rate. We argue that if R-0 1 then the disease-free equilibrium is locally asymptotically stable, whereas if R-0 1 then there is a unique endemic equilibrium which is locally asymptotically stable and uniformly persistent. In addition, we provide a sufficient condition for the global stability of the disease-free equilibrium. Both theoretical and simulation results reveal that the distribution of individual interaction radius has significant effects on the basic reproduction number and the final epidemic prevalence. In general, the disease will break out more readily in the population with a more heterogeneous radius distribution, while it will end in a lower epidemic prevalence. Interestingly, the results suggest that an optimal vaccination intervention for disease prevention and control is achievable regardless of the radius distribution. Furthermore, some interesting results on the structure of the underlying contact network are shown to have strong correlation with the epidemic dynamics. This study provides potential implications for developing efficient containment measures against infectious disease while considering the spatial constraints of moving individuals. (C) 2019 Elsevier B.V. All rights reserved.
机译:基于网络的流行模式已经广泛用于了解传染病的传播,但通常忽略了大多数现实网络是动态而不是静态的事实。在本文中,我们研究了一种敏感感染的易感敏感性模型,其动态接触网络中的动态接触网络,在那里我们将移动人员视为随机步行者,允许执行远程跳跃。与以往的随机步行网络中的流行病学研究不同,我们考虑个体具有相互作用半径R和感染的个体的异构分布的场景,这取决于相互作用半径分布。我们得出了与交互半径分布强烈相关的基本再现数R-0,并且在恒定接种率的特殊情况下与相互作用半径的二阶变矩进行成比例。我们争辩说,如果r-0 <1那么无疾病平衡是局部渐近稳定的,则如果R-0> 1,则存在独特的流动性平衡,局部渐近稳定且均匀持久。此外,我们为无疾病平衡的全球稳定性提供了足够的条件。理论和模拟结果均表明,个体相互作用半径的分布对基本生殖数量和最终疫情的巨大影响。通常,这种疾病将更容易地在具有更异质的半径分布的人群中爆发,而它将以较低的疫情结束。有趣的是,结果表明,无论半径分布如何,都可以实现疾病预防和控制的最佳疫苗接种干预。此外,关于底层接触网络的结构的一些有趣结果被证明与流行性动力学具有很强的相关性。该研究提供了在考虑移动个体的空间限制的同时对传染病产生有效遏制措施的潜在影响。 (c)2019 Elsevier B.v.保留所有权利。

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    Shanxi Univ Complex Syst Res Ctr Taiyuan 030006 Shanxi Peoples R China|Shanxi Univ Shanxi Key Lab Math Tech & Big Data Anal Dis Cont Taiyuan 030006 Shanxi Peoples R China;

    Shanxi Univ Complex Syst Res Ctr Taiyuan 030006 Shanxi Peoples R China|Shanxi Univ Shanxi Key Lab Math Tech & Big Data Anal Dis Cont Taiyuan 030006 Shanxi Peoples R China|Shanxi Univ Sch Math Sci Taiyuan 030006 Shanxi Peoples R China;

    Shanxi Univ Complex Syst Res Ctr Taiyuan 030006 Shanxi Peoples R China|Shanxi Univ Shanxi Key Lab Math Tech & Big Data Anal Dis Cont Taiyuan 030006 Shanxi Peoples R China;

    Shanxi Univ Complex Syst Res Ctr Taiyuan 030006 Shanxi Peoples R China|Shanxi Univ Shanxi Key Lab Math Tech & Big Data Anal Dis Cont Taiyuan 030006 Shanxi Peoples R China;

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  • 正文语种 eng
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  • 关键词

    Dynamical network; Epidemic spreading; Vaccination; Spatial constraint;

    机译:动态网络;流行蔓延;疫苗接种;空间约束;

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