Cooperative epidemics on multiplex networks

Azimi-Tafreshi, N.

doi:10.1103/physreve.93.042303

Cited by 55 publications

(43 citation statements)

References 40 publications

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“…Only recently, cooperative contagion in which infection with one transmissible agent facilitates infection with another was investigated [36][37][38][39][40][41][42][43][44][45][46][47]. These studies mainly focused on transient dynamics of the generic susceptible-infected-recovery (SIR) model in which individuals acquire immunity after infection.…”

Section: Introductionmentioning

confidence: 99%

“…This model exhibits avalanche-like outbreak scenarios, depending on the level of cooperation and the structure of the underlying transmission network. Analytical insights [44] have been obtained that explain the role of network topology in cooperative bond percolation systems, in multiplex systems [45], power-law networks [43], as well as sequential coinfection on Poisson networks [37]. Furthermore, it has been found that highly clustered structures in population aid the proliferation of coinfections, contrary to the effect observed in single disease dynamics [41].…”

Section: Introductionmentioning

confidence: 99%

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Fundamental properties of cooperative contagion processes

2017

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We investigate the effects of cooperativity between contagion processes that spread and persist in a host population. We propose and analyze a dynamical model in which individuals that are affected by one transmissible agent A exhibit a higher than baseline propensity of being affected by a second agent B and vice versa. The model is a natural extension of the traditional susceptible-infected-susceptible model used for modeling single contagion processes. We show that cooperativity changes the dynamics of the system considerably when cooperativity is strong. The system exhibits discontinuous phase transitions not observed in single agent contagion, multi-stability, a separation of the traditional epidemic threshold into different thresholds for inception and extinction as well as hysteresis. These properties are robust and are corroborated by stochastic simulations on lattices and generic network topologies. Finally, we investigate wave propagation and transients in a spatially extended version of the model and show that especially for intermediate values of baseline reproduction ratios the system is characterized by various types of wave-front speeds. The system can exhibit spatially heterogeneous stationary states for some parameters and negative front speeds (receding wave fronts). The two agent model can be employed as a starting point for more complex contagion processes, involving several interacting agents, a model framework particularly suitable for modeling the spread and dynamics of microbiological ecosystems in host populations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fundamental properties of cooperative contagion processes

2017

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“…Here we call this dynamical process directed percolation and its order parameter directed mutually connected giant component (DMCGC) to distinguish it from the MCGC. The choice of this terminology is due to the fact that we want to highlight the directed nature of the underlying process, and the connection to epidemic spreading [45] processes; nevertheless, we want to clarify that the links of the underlying multiplex network do not have an intrinsic directionality.…”

Section: Introductionmentioning

confidence: 99%

Message passing theory for percolation models on multiplex networks with link overlap

2016

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Multiplex networks describe a large variety of complex systems, including infrastructures, transportation networks, and biological systems. Most of these networks feature a significant link overlap. It is therefore of particular importance to characterize the mutually connected giant component in these networks. Here we provide a message passing theory for characterizing the percolation transition in multiplex networks with link overlap and an arbitrary number of layers M. Specifically we propose and compare two message passing algorithms that generalize the algorithm widely used to study the percolation transition in multiplex networks without link overlap. The first algorithm describes a directed percolation transition and admits an epidemic spreading interpretation. The second algorithm describes the emergence of the mutually connected giant component, that is the percolation transition, but does not preserve the epidemic spreading interpretation. We obtain the phase diagrams for the percolation and directed percolation transition in simple representative cases. We demonstrate that for the same multiplex network structure, in which the directed percolation transition has nontrivial tricritical points, the percolation transition has a discontinuous phase transition, with the exception of the trivial case in which all the layers completely overlap.

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“…For Erdős-Rényi (ER) networks with average degree k = z, Eqs. (20) and (22) yield In Fig. 1, we display, for fixed z = 4, the phase-diagram of the model.…”

Section: A Erdős-rényi Networkmentioning

confidence: 99%

Message-passing theory for cooperative epidemics

Min

Castellano

2020

Chaos: An Interdisciplinary Journal of Nonlinear Science

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The interaction among spreading processes on a complex network is a nontrivial phenomenon of great importance. It has recently been realized that cooperative effects among infective diseases can give rise to qualitative changes in the phenomenology of epidemic spreading, leading for instance to abrupt transitions and hysteresis. Here we consider a simple model for two interacting pathogens on a network and we study it by using the message-passing approach. In this way we are able to provide detailed predictions for the behavior of the model in the whole phase-diagram for any given network structure. Numerical simulations on synthetic networks (both homogeneous and heterogeneous) confirm the great accuracy of the theoretical results. We finally consider the issue of identifying the nodes where it is better to seed the infection in order to maximize the probability of observing an extensive outbreak. The message-passing approach provides an accurate solution also for this problem.How to predict and control mutually cooperative epidemics on a networked system is an outstanding problem of much interest. Previous attempts in this problem have assumed well-mixed populations and focused on the meanfield analysis. A full analysis of the cooperativity in epidemics at the level of single node is still lacking. In this work, we provide a message-passing approach in order to fully analyze cooperative epidemics on complex networks. We confirm the great accuracy of our theory with numerical simulations for both homogeneous and heterogeneous network structures. In addition, we reveal how to identify precisely influential spreaders in cooperative epidemics by using the message-passing equations.

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Cooperative epidemics on multiplex networks

Cited by 55 publications

References 40 publications

Fundamental properties of cooperative contagion processes

Fundamental properties of cooperative contagion processes

Message passing theory for percolation models on multiplex networks with link overlap

Message-passing theory for cooperative epidemics

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