Literature DB >> 17025711

Dynamical network model of infective mobile agents.

Mattia Frasca1, Arturo Buscarino, Alessandro Rizzo, Luigi Fortuna, Stefano Boccaletti.   

Abstract

A dynamical network (consisting of a time-evolving wiring of interactions among a group of random walkers) is introduced to model the spread of an infectious disease in a population of mobile individuals. We investigate the main properties of this model, and show that peculiar features arise when individuals are allowed to perform long-distance jumps. Such peculiarities are captured and conveniently quantified by a series of appropriate parameters able to highlight the structural differences emerging in the networks when long-distance jumps are combined with local random walk processes.

Entities:  

Year:  2006        PMID: 17025711     DOI: 10.1103/PhysRevE.74.036110

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  8 in total

1.  Epidemic spreading in complex networks.

Authors:  Jie Zhou; Zong-Hua Liu
Journal:  Front Phys China       Date:  2008-07-08

Review 2.  Mechanistic movement models to understand epidemic spread.

Authors:  Abdou Moutalab Fofana; Amy Hurford
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-05-05       Impact factor: 6.237

3.  Using active matter to introduce spatial heterogeneity to the susceptible infected recovered model of epidemic spreading.

Authors:  P Forgács; A Libál; C Reichhardt; N Hengartner; C J O Reichhardt
Journal:  Sci Rep       Date:  2022-07-04       Impact factor: 4.996

4.  Epidemic spreading in modular time-varying networks.

Authors:  Matthieu Nadini; Kaiyuan Sun; Enrico Ubaldi; Michele Starnini; Alessandro Rizzo; Nicola Perra
Journal:  Sci Rep       Date:  2018-02-05       Impact factor: 4.379

5.  Inhomogeneity of epidemic spreading with entropy-based infected clusters.

Authors:  Zhou Wen-Jie; Wang Xing-Yuan
Journal:  Chaos       Date:  2013-12       Impact factor: 3.642

6.  Inhomogeneity of epidemic spreading.

Authors:  Zhenzhen Liu; Xingyuan Wang; Mogei Wang
Journal:  Chaos       Date:  2010-06       Impact factor: 3.642

7.  Towards predicting COVID-19 infection waves: A random-walk Monte Carlo simulation approach.

Authors:  D P Mahapatra; S Triambak
Journal:  Chaos Solitons Fractals       Date:  2022-01-10       Impact factor: 5.944

8.  Epidemic spreading in metapopulation networks with heterogeneous infection rates.

Authors:  Yong-Wang Gong; Yu-Rong Song; Guo-Ping Jiang
Journal:  Physica A       Date:  2014-09-01       Impact factor: 3.263

  8 in total

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