Literature DB >> 15649519

The implications of network structure for epidemic dynamics.

Matt Keeling1.   

Abstract

It has long been realised that the standard assumptions of mass-action mixing are a crude approximation of the true mechanistic processes that govern the transmission of infection. In particular, many infections can be considered to be spread through a limited network of contacts. Yet, despite the underlying discrepancies, mass-action models continue to be used and provide a remarkably accurate description of epidemic behaviour. Here, the differences between mass-action and network-based models are investigated. This allows us to determine when mass-action models are a reliable tool, and suggest ways in which their behaviour should be refined.

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Year:  2005        PMID: 15649519     DOI: 10.1016/j.tpb.2004.08.002

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  92 in total

1.  Prioritizing healthcare worker vaccinations on the basis of social network analysis.

Authors:  Philip M Polgreen; Troy Leo Tassier; Sriram Venkata Pemmaraju; Alberto Maria Segre
Journal:  Infect Control Hosp Epidemiol       Date:  2010-09       Impact factor: 3.254

2.  Brown spider monkeys (Ateles hybridus): a model for differentiating the role of social networks and physical contact on parasite transmission dynamics.

Authors:  Rebecca Rimbach; Donal Bisanzio; Nelson Galvis; Andrés Link; Anthony Di Fiore; Thomas R Gillespie
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2015-05-26       Impact factor: 6.237

3.  Disease transmission in territorial populations: the small-world network of Serengeti lions.

Authors:  Meggan E Craft; Erik Volz; Craig Packer; Lauren Ancel Meyers
Journal:  J R Soc Interface       Date:  2010-10-28       Impact factor: 4.118

Review 4.  Networks and epidemic models.

Authors:  Matt J Keeling; Ken T D Eames
Journal:  J R Soc Interface       Date:  2005-09-22       Impact factor: 4.118

5.  Network frailty and the geometry of herd immunity.

Authors:  Matthew J Ferrari; Shweta Bansal; Lauren A Meyers; Ottar N Bjørnstad
Journal:  Proc Biol Sci       Date:  2006-11-07       Impact factor: 5.349

6.  Free-living pathogens: life-history constraints and strain competition.

Authors:  Thomas Caraco; Ing-Nang Wang
Journal:  J Theor Biol       Date:  2007-10-30       Impact factor: 2.691

7.  Stochastic fluctuations in epidemics on networks.

Authors:  M Simões; M M Telo da Gama; A Nunes
Journal:  J R Soc Interface       Date:  2008-05-06       Impact factor: 4.118

8.  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

9.  Increased frequency of travel in the presence of cross-immunity may act to decrease the chance of a global pandemic.

Authors:  R N Thompson; C P Thompson; O Pelerman; S Gupta; U Obolski
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-06-24       Impact factor: 6.237

10.  The influence of the phonological neighborhood clustering coefficient on spoken word recognition.

Authors:  Kit Ying Chan; Michael S Vitevitch
Journal:  J Exp Psychol Hum Percept Perform       Date:  2009-12       Impact factor: 3.332

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