Literature DB >> 11863560

Percolation and epidemics in a two-dimensional small world.

M E J Newman1, I Jensen, R M Ziff.   

Abstract

Percolation on two-dimensional small-world networks has been proposed as a model for the spread of plant diseases. In this paper we give an analytic solution of this model using a combination of generating function methods and high-order series expansion. Our solution gives accurate predictions for quantities such as the position of the percolation threshold and the typical size of disease outbreaks as a function of the density of "shortcuts" in the small-world network. Our results agree with scaling hypotheses and numerical simulations for the same model.

Mesh:

Year:  2002        PMID: 11863560     DOI: 10.1103/PhysRevE.65.021904

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


  17 in total

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2.  Consciousness related neural events viewed as brain state space transitions.

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3.  Indemics: An Interactive High-Performance Computing Framework for Data Intensive Epidemic Modeling.

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4.  An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

Authors:  Suruchi Deodhar; Keith R Bisset; Jiangzhuo Chen; Yifei Ma; Madhav V Marathe
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6.  Modeling the adoption of innovations in the presence of geographic and media influences.

Authors:  Jameson L Toole; Meeyoung Cha; Marta C González
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7.  How Inhomogeneous Site Percolation Works on Bethe Lattices: Theory and Application.

Authors:  Jingli Ren; Liying Zhang; Stefan Siegmund
Journal:  Sci Rep       Date:  2016-03-01       Impact factor: 4.379

8.  Epidemics scenarios in the "Romantic network".

Authors:  Alexsandro M Carvalho; Sebastián Gonçalves
Journal:  PLoS One       Date:  2012-11-27       Impact factor: 3.240

9.  Malaria transmission modelling: a network perspective.

Authors:  Jiming Liu; Bo Yang; William K Cheung; Guojing Yang
Journal:  Infect Dis Poverty       Date:  2012-11-01       Impact factor: 4.520

10.  Inferring epidemic network topology from surveillance data.

Authors:  Xiang Wan; Jiming Liu; William K Cheung; Tiejun Tong
Journal:  PLoS One       Date:  2014-06-30       Impact factor: 3.240

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