Literature DB >> 27176320

Connectivity disruption sparks explosive epidemic spreading.

L Böttcher1, O Woolley-Meza2, E Goles3, D Helbing4, H J Herrmann5.   

Abstract

We investigate the spread of an infection or other malfunction of cascading nature when a system component can recover only if it remains reachable from a functioning central component. We consider the susceptible-infected-susceptible model, typical of mathematical epidemiology, on a network. Infection spreads from infected to healthy nodes, with the addition that infected nodes can only recover when they remain connected to a predefined central node, through a path that contains only healthy nodes. In this system, clusters of infected nodes will absorb their noninfected interior because no path exists between the central node and encapsulated nodes. This gives rise to the simultaneous infection of multiple nodes. Interestingly, the system converges to only one of two stationary states: either the whole population is healthy or it becomes completely infected. This simultaneous cluster infection can give rise to discontinuous jumps of different sizes in the number of failed nodes. Larger jumps emerge at lower infection rates. The network topology has an important effect on the nature of the transition: we observed hysteresis for networks with dominating local interactions. Our model shows how local spread can abruptly turn uncontrollable when it disrupts connectivity at a larger spatial scale.

Entities:  

Year:  2016        PMID: 27176320     DOI: 10.1103/PhysRevE.93.042315

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  7 in total

Review 1.  Coevolution spreading in complex networks.

Authors:  Wei Wang; Quan-Hui Liu; Junhao Liang; Yanqing Hu; Tao Zhou
Journal:  Phys Rep       Date:  2019-07-29       Impact factor: 25.600

2.  Targeted Recovery as an Effective Strategy against Epidemic Spreading.

Authors:  L Böttcher; J S Andrade; H J Herrmann
Journal:  Sci Rep       Date:  2017-10-30       Impact factor: 4.379

3.  Failure and recovery in dynamical networks.

Authors:  L Böttcher; M Luković; J Nagler; S Havlin; H J Herrmann
Journal:  Sci Rep       Date:  2017-02-03       Impact factor: 4.379

4.  Critical Behaviors in Contagion Dynamics.

Authors:  L Böttcher; J Nagler; H J Herrmann
Journal:  Phys Rev Lett       Date:  2017-02-23       Impact factor: 9.161

5.  A toy model for the epidemic-driven collapse in a system with limited economic resource.

Authors:  I S Gandzha; O V Kliushnichenko; S P Lukyanets
Journal:  Eur Phys J B       Date:  2021-04-28       Impact factor: 1.500

6.  Why case fatality ratios can be misleading: individual- and population-based mortality estimates and factors influencing them.

Authors:  Lucas Böttcher; Mingtao Xia; Tom Chou
Journal:  Phys Biol       Date:  2020-09-23       Impact factor: 2.583

7.  Why estimating population-based case fatality rates during epidemics may be misleading.

Authors:  Lucas Böttcher; Mingtao Xia; Tom Chou
Journal:  medRxiv       Date:  2020-03-30
  7 in total

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