Reverse-feeding effect of epidemic by propagators in two-layered networks

Abstract

Epidemic spreading has been studied for a long time and is currently focused on the spreading of multiple pathogens, especially in multiplex networks. However, little attention has been paid to the case where the mutual influence between different pathogens comes from a fraction of epidemic propagators, such as bisexual people in two separated groups of heterosexual and homosexual people. We here study this topic by presenting a network model of two layers connected by impulsive links, in contrast to the persistent links in each layer. We let each layer have a distinct pathogen and their interactive infection is implemented by a fraction of propagators jumping between the corresponding pairs of nodes in the two layers. By this model we show that (i) the propagators take the key role to transmit pathogens from one layer to the other, which significantly influences the stabilized epidemics; (ii) the epidemic thresholds will be changed by the propagators; and (iii) a reverse-feeding effect can be expected when the infective rate is smaller than its threshold of isolated spreading. A theoretical analysis is presented to explain the numerical results.

Hysteresis loop of nonperiodic outbreaks of recurrent epidemics

“…The spreading of epidemics is currently one of the hottest topics in the field of complex networks, and a great deal of significant progress has been achieved so far, including the infinitesimal threshold [1][2][3][4][5][6], the reactiondiffusion model [7][8][9][10], flow-driven epidemics [11][12][13][14][15], objective spreading [16,17], temporal and/or multilayered networks [18][19][20][21][22][23][24][25][26][27], and other aspects [28][29][30][31][32][33][34][35][36]; see Refs. [37][38][39] for details.…”

New results for exponential synchronization of linearly coupled ordinary differential systems

“…. , n, and min 1≤i≤n D i ≥ α 𝑇 , then system (7) is locally exponentially synchronized. In this case, we can see that system (7) is also globally exponentially synchronized because of the particularity of the map g.…”

“…Synchronization of linearly coupled ordinary differential equations (LCODEs) has been widely applied for decades to different fields, such as neuroscience, [1][2][3][4] economics, [5] biology, [6,7] ecology, [8] computer science, [9,10] and so on. Meanwhile, the synchronization technique for LCODEs has been favored by several researchers.…”

Epidemic spreading on random surfer networks with infected avoidance strategy

“…In most of the literature dealing with the epidemic spreading behavior, the topology structure of the underlying network is assumed to be static. [1][2][3][4][5][6][7][8][9][10] However, in practice, the relations between individuals are unlikely to keep unchanged all the time, the movements of individuals cause a dynamic topology structure. In fact, some recent study results indicate that the mobility of individuals can play a significant role in the epidemic spreading process.…”