Literature DB >> 26317749

Generalization of Pairwise Models to non-Markovian Epidemics on Networks.

Istvan Z Kiss1, Gergely Röst2, Zsolt Vizi2.   

Abstract

In this Letter, a generalization of pairwise models to non-Markovian epidemics on networks is presented. For the case of infectious periods of fixed length, the resulting pairwise model is a system of delay differential equations, which shows excellent agreement with results based on stochastic simulations. Furthermore, we analytically compute a new R_{0}-like threshold quantity and an analytical relation between this and the final epidemic size. Additionally, we show that the pairwise model and the analytic results can be generalized to an arbitrary distribution of the infectious times, using integro-differential equations, and this leads to a general expression for the final epidemic size. By showing the rigorous link between non-Markovian dynamics and pairwise delay differential equations, we provide the framework for a more systematic understanding of non-Markovian dynamics.

Year:  2015        PMID: 26317749     DOI: 10.1103/PhysRevLett.115.078701

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  14 in total

1.  The relationships between message passing, pairwise, Kermack-McKendrick and stochastic SIR epidemic models.

Authors:  Robert R Wilkinson; Frank G Ball; Kieran J Sharkey
Journal:  J Math Biol       Date:  2017-04-13       Impact factor: 2.259

2.  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

3.  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

4.  Reconstruction of stochastic temporal networks through diffusive arrival times.

Authors:  Xun Li; Xiang Li
Journal:  Nat Commun       Date:  2017-06-12       Impact factor: 14.919

5.  Non-Markovian recovery makes complex networks more resilient against large-scale failures.

Authors:  Zhao-Hua Lin; Mi Feng; Ming Tang; Zonghua Liu; Chen Xu; Pak Ming Hui; Ying-Cheng Lai
Journal:  Nat Commun       Date:  2020-05-19       Impact factor: 14.919

6.  Markovian approaches to modeling intracellular reaction processes with molecular memory.

Authors:  Jiajun Zhang; Tianshou Zhou
Journal:  Proc Natl Acad Sci U S A       Date:  2019-11-04       Impact factor: 11.205

7.  Hysteresis loop of nonperiodic outbreaks of recurrent epidemics.

Authors:  Hengcong Liu; Muhua Zheng; Dayu Wu; Zhenhua Wang; Jinming Liu; Zonghua Liu
Journal:  Phys Rev E       Date:  2016-12-29       Impact factor: 2.529

8.  A paradox of epidemics between the state and parameter spaces.

Authors:  Hengcong Liu; Muhua Zheng; Zonghua Liu
Journal:  Sci Rep       Date:  2018-05-14       Impact factor: 4.379

9.  Bursting endemic bubbles in an adaptive network.

Authors:  N Sherborne; K B Blyuss; I Z Kiss
Journal:  Phys Rev E       Date:  2018-04       Impact factor: 2.529

10.  Efficient simulation of non-Markovian dynamics on complex networks.

Authors:  Gerrit Großmann; Luca Bortolussi; Verena Wolf
Journal:  PLoS One       Date:  2020-10-30       Impact factor: 3.240

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