Literature DB >> 25580063

Epidemic spread in networks: Existing methods and current challenges.

Joel C Miller1, Istvan Z Kiss2.   

Abstract

We consider the spread of infectious disease through contact networks of Configuration Model type. We assume that the disease spreads through contacts and infected individuals recover into an immune state. We discuss a number of existing mathematical models used to investigate this system, and show relations between the underlying assumptions of the models. In the process we offer simplifications of some of the existing models. The distinctions between the underlying assumptions are subtle, and in many if not most cases this subtlety is irrelevant. Indeed, under appropriate conditions the models are equivalent. We compare the benefits and disadvantages of the different models, and discuss their application to other populations (e.g., clustered networks). Finally we discuss ongoing challenges for network-based epidemic modeling.

Entities:  

Keywords:  Configuration Model Networks; Edge-based Compartmental Models; Effective Degree; Epidemic; Network; Pairwise; SIR disease

Year:  2014        PMID: 25580063      PMCID: PMC4287241          DOI: 10.1051/mmnp/20149202

Source DB:  PubMed          Journal:  Math Model Nat Phenom        ISSN: 0973-5348            Impact factor:   4.157


  33 in total

1.  A note on a paper by Erik Volz: SIR dynamics in random networks.

Authors:  Joel C Miller
Journal:  J Math Biol       Date:  2010-03-23       Impact factor: 2.259

2.  Percolation and epidemic thresholds in clustered networks.

Authors:  M Angeles Serrano; Marián Boguñá
Journal:  Phys Rev Lett       Date:  2006-08-23       Impact factor: 9.161

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.  Network epidemic models with two levels of mixing.

Authors:  Frank Ball; Peter Neal
Journal:  Math Biosci       Date:  2008-01-11       Impact factor: 2.144

5.  A motif-based approach to network epidemics.

Authors:  Thomas House; Geoffrey Davies; Leon Danon; Matt J Keeling
Journal:  Bull Math Biol       Date:  2009-04-25       Impact factor: 1.758

6.  Random graphs with clustering.

Authors:  M E J Newman
Journal:  Phys Rev Lett       Date:  2009-07-27       Impact factor: 9.161

7.  Percolation and epidemics in random clustered networks.

Authors:  Joel C Miller
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2009-08-04

8.  Random graphs containing arbitrary distributions of subgraphs.

Authors:  Brian Karrer; M E J Newman
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2010-12-30

9.  Insights from unifying modern approximations to infections on networks.

Authors:  Thomas House; Matt J Keeling
Journal:  J R Soc Interface       Date:  2010-06-10       Impact factor: 4.118

10.  Model hierarchies in edge-based compartmental modeling for infectious disease spread.

Authors:  Joel C Miller; Erik M Volz
Journal:  J Math Biol       Date:  2012-08-22       Impact factor: 2.259

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  16 in total

1.  Host contact structure is important for the recurrence of Influenza A.

Authors:  J M Jaramillo; Junling Ma; P van den Driessche; Sanling Yuan
Journal:  J Math Biol       Date:  2018-07-04       Impact factor: 2.259

2.  Heterogeneous network epidemics: real-time growth, variance and extinction of infection.

Authors:  Frank Ball; Thomas House
Journal:  J Math Biol       Date:  2017-01-17       Impact factor: 2.259

3.  Phase Transitions in Spatial Connectivity during Influenza Pandemics.

Authors:  Nathan Harding; Richard Spinney; Mikhail Prokopenko
Journal:  Entropy (Basel)       Date:  2020-01-22       Impact factor: 2.524

4.  Pairwise approximation for SIR-type network epidemics with non-Markovian recovery.

Authors:  G Röst; Z Vizi; I Z Kiss
Journal:  Proc Math Phys Eng Sci       Date:  2018-02-21       Impact factor: 2.704

5.  Mean-field models for non-Markovian epidemics on networks.

Authors:  Neil Sherborne; Joel C Miller; Konstantin B Blyuss; Istvan Z Kiss
Journal:  J Math Biol       Date:  2017-07-06       Impact factor: 2.259

6.  Incorporating disease and population structure into models of SIR disease in contact networks.

Authors:  Joel C Miller; Erik M Volz
Journal:  PLoS One       Date:  2013-08-19       Impact factor: 3.240

7.  Systematic Approximations to Susceptible-Infectious-Susceptible Dynamics on Networks.

Authors:  Matt J Keeling; Thomas House; Alison J Cooper; Lorenzo Pellis
Journal:  PLoS Comput Biol       Date:  2016-12-20       Impact factor: 4.475

8.  Mathematical models of SIR disease spread with combined non-sexual and sexual transmission routes.

Authors:  Joel C Miller
Journal:  Infect Dis Model       Date:  2017-01-11

9.  Epidemics on networks with large initial conditions or changing structure.

Authors:  Joel C Miller
Journal:  PLoS One       Date:  2014-07-08       Impact factor: 3.240

10.  Development of structural correlations and synchronization from adaptive rewiring in networks of Kuramoto oscillators.

Authors:  Lia Papadopoulos; Jason Z Kim; Jürgen Kurths; Danielle S Bassett
Journal:  Chaos       Date:  2017-07       Impact factor: 3.642

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