Domination-time dynamics in susceptible-infected-susceptible virus competition on networks

Bovenkamp, Ruud van de; Kuipers, Fernando A.; Mieghem, Piet Van

doi:10.1103/physreve.89.042818

Cited by 13 publications

(7 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Super-infection was then shown to be a limit of co-infection. Similar to technology diffusion models, competition is modeled as cross-immunity in networks [30].…”

Section: Literature Reviewmentioning

confidence: 99%

Co-diffusion of social contagions

Chang

2018

New J. Phys.

View full text Add to dashboard Cite

Prior social contagion models consider the spread of either one contagion on interdependent networks or multiple contagions on single layer networks, usually under assumptions of competition. We propose a new threshold model for the diffusion of multiple contagions. Individuals are placed on a multiplex network with a periodic lattice layer and a random-regular-graph layer. On these population structures, we study the interface between two key aspects of the diffusion process: the level of synergy between two contagions, and the rate at which individuals become dormant after adoption. Dormancy is defined as a looser form of immunity that limits active spreading but without conferring resistance. Monte Carlo simulations reveal lower synergy makes contagions more susceptible to percolation, especially those that diffuse on lattices. Faster diffusion of one contagion with dormancy probabilistically blocks the diffusion of the other, in a way similar to ring vaccination. We show that within a band of synergy, bimodal or trimodal branchings occur on the slower contagion on the lattice. We also show complimentary contagions can provide a synergistic boost to help spread contagions that have almost gone dormant.

show abstract

“…Super-infection was then shown to be a limit of co-infection. Similar to technology diffusion models, competition is modeled as cross-immunity in networks [30].…”

Section: Literature Reviewmentioning

confidence: 99%

Co-diffusion of social contagions

Chang

2018

New J. Phys.

View full text Add to dashboard Cite

show abstract

“…Once the two competing SIS epidemics have partial immunizing functions, there is a coexistence region of the two epidemics [109]. Bovenkamp et al studied two competing SIS epidemics on a complete network [110], and revealed that only one epidemic exists when the transmission probability is above the epidemic threshold, which is markedly different from the observations of competing SIR epidemics. Disallowing epidemic extension by allowing one node to become infected automatically when there are no infected nodes, the dominant and dominated epidemics alternate when the two epidemics are identical.…”

Section: Competing or Cross-immunity Contagionsmentioning

confidence: 99%

Coevolution spreading in complex networks

et al. 2019

View full text Add to dashboard Cite

a b s t r a c tThe propagations of diseases, behaviors and information in real systems are rarely independent of each other, but they are coevolving with strong interactions. To uncover the dynamical mechanisms, the evolving spatiotemporal patterns and critical phenomena of networked coevolution spreading are extremely important, which provide theoretical foundations for us to control epidemic spreading, predict collective behaviors in social systems, and so on. The coevolution spreading dynamics in complex networks has thus attracted much attention in many disciplines. In this review, we introduce recent progress in the study of coevolution spreading dynamics, emphasizing the contributions from the perspectives of statistical mechanics and network science. The theoretical methods, critical phenomena, phase transitions, interacting mechanisms, and effects of network topology for four representative types of coevolution spreading mechanisms, including the coevolution of biological contagions, social contagions, epidemic-awareness, and epidemic-resources, are presented in detail, and the challenges in this field as well as open issues for future studies are also discussed.

show abstract

“…A common assumption is that spreading processes can become extinct; in this case, one process will dominate the other one even when the diffusion rates of both of them are above the epidemic threshold [129]. Recently, in [130] the authors relax this assumption and address the domination time. They find that it depends on the number of infected nodes at the beginning of the domination period.…”

Section: Interacting Spreading Processesmentioning

confidence: 99%

Spreading Processes in Multilayer Networks

Salehi

Sharma

Marzolla

et al. 2015

IEEE Trans. Netw. Sci. Eng.

216

150

View full text Add to dashboard Cite

Abstract-Several systems can be modeled as sets of interconnected networks or networks with multiple types of connections, here generally called multilayer networks. Spreading processes such as information propagation among users of an online social networks, or the diffusion of pathogens among individuals through their contact network, are fundamental phenomena occurring in these networks. However, while information diffusion in single networks has received considerable attention from various disciplines for over a decade, spreading processes in multilayer networks is still a young research area presenting many challenging research issues. In this paper we review the main models, results and applications of multilayer spreading processes and discuss some promising research directions.

show abstract

Domination-time dynamics in susceptible-infected-susceptible virus competition on networks

Cited by 13 publications

References 27 publications

Co-diffusion of social contagions

Co-diffusion of social contagions

Coevolution spreading in complex networks

Spreading Processes in Multilayer Networks

Contact Info

Product

Resources

About