Literature DB >> 12387929

Percolation on heterogeneous networks as a model for epidemics.

L M Sander1, C P Warren, I M Sokolov, C Simon, J Koopman.   

Abstract

We consider a spatial model related to bond percolation for the spread of a disease that includes variation in the susceptibility to infection. We work on a lattice with random bond strengths and show that with strong heterogeneity, i.e. a wide range of variation of susceptibility, patchiness in the spread of the epidemic is very likely, and the criterion for epidemic outbreak depends strongly on the heterogeneity. These results are qualitatively different from those of standard models in epidemiology, but correspond to real effects. We suggest that heterogeneity in the epidemic will affect the phylogenetic distance distribution of the disease-causing organisms. We also investigate small world lattices, and show that the effects mentioned above are even stronger.

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Year:  2002        PMID: 12387929     DOI: 10.1016/s0025-5564(02)00117-7

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  32 in total

1.  Epidemics in networks of spatially correlated three-dimensional root-branching structures.

Authors:  T P Handford; F J Pérez-Reche; S N Taraskin; L da F Costa; M Miazaki; F M Neri; C A Gilligan
Journal:  J R Soc Interface       Date:  2010-07-28       Impact factor: 4.118

2.  Heterogeneity in susceptible-infected-removed (SIR) epidemics on lattices.

Authors:  Franco M Neri; Francisco J Pérez-Reche; Sergei N Taraskin; Christopher A Gilligan
Journal:  J R Soc Interface       Date:  2010-07-14       Impact factor: 4.118

3.  Network-based analysis of stochastic SIR epidemic models with random and proportionate mixing.

Authors:  Eben Kenah; James M Robins
Journal:  J Theor Biol       Date:  2007-09-15       Impact factor: 2.691

4.  Second look at the spread of epidemics on networks.

Authors:  Eben Kenah; James M Robins
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2007-09-25

5.  Complexity and anisotropy in host morphology make populations less susceptible to epidemic outbreaks.

Authors:  Francisco J Pérez-Reche; Sergei N Taraskin; Luciano da F Costa; Franco M Neri; Christopher A Gilligan
Journal:  J R Soc Interface       Date:  2010-01-14       Impact factor: 4.118

6.  Preventable H5N1 avian influenza epidemics in the British poultry industry network exhibit characteristic scales.

Authors:  A R T Jonkers; K J Sharkey; R M Christley
Journal:  J R Soc Interface       Date:  2009-10-14       Impact factor: 4.118

7.  Empirical evidence of spatial thresholds to control invasion of fungal parasites and saprotrophs.

Authors:  Wilfred Otten; Douglas J Bailey; Christopher A Gilligan
Journal:  New Phytol       Date:  2004-07       Impact factor: 10.151

8.  Thermodynamic efficiency of contagions: a statistical mechanical analysis of the SIS epidemic model.

Authors:  Nathan Harding; Ramil Nigmatullin; Mikhail Prokopenko
Journal:  Interface Focus       Date:  2018-10-19       Impact factor: 3.906

9.  The Ratio of Free to Bound Desmosine and Isodesmosine May Reflect Emphysematous Changes in COPD.

Authors:  Xingjian Liu; Shuren Ma; Sophie Liu; Ming Liu; Gerard Turino; Jerome Cantor
Journal:  Lung       Date:  2015-03-12       Impact factor: 2.584

10.  Contact heterogeneity and phylodynamics: how contact networks shape parasite evolutionary trees.

Authors:  Eamon B O'Dea; Claus O Wilke
Journal:  Interdiscip Perspect Infect Dis       Date:  2010-12-01
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