Modified diffusive epidemic process on Apollonian networks

IF 1.8 4区 生物学 Q3 BIOPHYSICS
David Alencar, Antonio Filho, Tayroni Alves, Gladstone Alves, Ronan Ferreira, Francisco Lima
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Abstract

We present an analysis of an epidemic spreading process on an Apollonian network that can describe an epidemic spreading in a non-sedentary population. We studied the modified diffusive epidemic process using the Monte Carlo method by computational analysis. Our model may be helpful for modeling systems closer to reality consisting of two classes of individuals: susceptible (A) and infected (B). The individuals can diffuse in a network according to constant diffusion rates \(D_{A}\) and \(D_{B}\), for the classes A and B, respectively, and obeying three diffusive regimes, i.e., \(D_{A}<D_{B}\), \(D_{A}=D_{B}\), and \(D_{A}>D_{B}\). Into the same site i, the reaction occurs according to the dynamical rule based on Gillespie’s algorithm. Finite-size scaling analysis has shown that our model exhibits continuous phase transition to an absorbing state with a set of critical exponents given by \(\beta /\nu =0.66(1)\), \(1/\nu =0.46(2)\), and \(\gamma '/\nu =-0.24(2)\) familiar to every investigated regime. In summary, the continuous phase transition, characterized by this set of critical exponents, does not have the same exponents of the mean-field universality class in both regular lattices and complex networks.

Abstract Image

阿波罗网络上改进的扩散流行病过程
我们提出了一个流行病传播过程的分析阿波罗网络,可以描述流行病在非久坐人群中的传播。通过计算分析,采用蒙特卡罗方法研究了改进的扩散流行病过程。我们的模型可能有助于建模更接近现实的系统,该系统由两类个体组成:易感个体(A)和受感染个体(B)。对于A类和B类,个体可以分别按照恒定的扩散速率\(D_{A}\)和\(D_{B}\)在网络中扩散,并且服从三种扩散机制,即\(D_{A}<D_{B}\), \(D_{A}=D_{B}\)和\(D_{A}>D_{B}\)。进入同一位点i,反应按照基于Gillespie算法的动力学规律发生。有限尺寸的缩放分析表明,我们的模型显示出连续的相变到一个吸收状态,其临界指数由\(\beta /\nu =0.66(1)\), \(1/\nu =0.46(2)\)和\(\gamma '/\nu =-0.24(2)\)给出,每个研究体系都很熟悉。综上所述,以这组临界指数为特征的连续相变,在正则格和复杂网络中都不具有相同的平均场普适性类指数。
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来源期刊
Journal of Biological Physics
Journal of Biological Physics 生物-生物物理
CiteScore
3.00
自引率
5.60%
发文量
20
审稿时长
>12 weeks
期刊介绍: Many physicists are turning their attention to domains that were not traditionally part of physics and are applying the sophisticated tools of theoretical, computational and experimental physics to investigate biological processes, systems and materials. The Journal of Biological Physics provides a medium where this growing community of scientists can publish its results and discuss its aims and methods. It welcomes papers which use the tools of physics in an innovative way to study biological problems, as well as research aimed at providing a better understanding of the physical principles underlying biological processes.
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