David Alencar, Antonio Filho, Tayroni Alves, Gladstone Alves, Ronan Ferreira, Francisco Lima
{"title":"Modified diffusive epidemic process on Apollonian networks","authors":"David Alencar, Antonio Filho, Tayroni Alves, Gladstone Alves, Ronan Ferreira, Francisco Lima","doi":"10.1007/s10867-023-09634-2","DOIUrl":null,"url":null,"abstract":"<div><p>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 <span>\\(D_{A}\\)</span> and <span>\\(D_{B}\\)</span>, for the classes A and B, respectively, and obeying three diffusive regimes, i.e., <span>\\(D_{A}<D_{B}\\)</span>, <span>\\(D_{A}=D_{B}\\)</span>, and <span>\\(D_{A}>D_{B}\\)</span>. Into the same site <i>i</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 <span>\\(\\beta /\\nu =0.66(1)\\)</span>, <span>\\(1/\\nu =0.46(2)\\)</span>, and <span>\\(\\gamma '/\\nu =-0.24(2)\\)</span> 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.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"49 3","pages":"329 - 343"},"PeriodicalIF":1.8000,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-023-09634-2.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biological Physics","FirstCategoryId":"99","ListUrlMain":"https://link.springer.com/article/10.1007/s10867-023-09634-2","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOPHYSICS","Score":null,"Total":0}
引用次数: 0
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.
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.