Multiple peaks patterns of epidemic spreading in multi-layer networks

Abstract

The study of epidemic spreading on populations of networked individuals has seen recently a great deal of significant progresses. A common point of all past studies is, however, that there is only one peak of infected density in each single epidemic spreading episode. At variance, real data from different cities over the world suggest that, besides a major single peak trait of infected density, a finite probability exists for a pattern made of two (or multiple) peaks. We show that such a latter feature is fully distinctive of a multilayered network of interactions, and reveal that actually a two peaks pattern emerges from different time delays at which the epidemic spreads in between the two layers. Further, we show that essential ingredients 1

Prevalence of SARS-CoV-2 among workers returning to Bihar gives snapshot of COVID across India

“…An alternative explanation for the discrepancy is that data on returning workers may be more representative than state data of the non-monotonic patterns in prevalence common in epidemics. A national epidemic is a sum of local epidemics (20). The data on workers is compatible with this view.…”

A dynamic vaccination strategy to suppress the recurrent epidemic outbreaks

“…Thus to study the vaccination strategy in community networks and investigate whether selecting individuals with large connections or in high connected communities to vaccinate is better is needed. In addition, in the disease spread process, both time and space play an important role [39][40][41][42][43] , and many significant results have been achieved to understand the traveling wave and pattern formation [2,44] . Therefore, to incorporate the spatial details or realistic population mixing structures to epidemic spreading process and assess the potential impact of different intervention strategies are our future works.…”

Double transition of information spreading in a two-layered network

“…The edge-based compartmental theory on a two-layered network Now, we develop an analogous theoretical framework from the single network to the case of two uncorrelated interconnected networks based on the approach in Refs. 22 , which is suited to the problems studied in our work. In particular, when one assumes that the population is made up of two layers, then P j (k 1 , k 2 ) denote the probability that a node of layer j has k 1 degree in layer 1 and k 2 in layer 2.…”

“…The spreading process is currently one of the hottest topics in the field of complex networks, such as the spreading of epidemic, opinion, rumor, new technologies and behaviors and so on. So far, a great deal of significant progresses have been achieved including the infinitesimal threshold [1][2][3][4][5][6] , reaction-diffusion model [7][8][9][10] , temporal and/or multilayer networks [11][12][13][14][15][16][17][18][19][20][21][22][23][24] etc (see the review Refs. [25][26][27][28] for details).…”

“…The effects of multiple channels on the spreading process have been widely investigated based on a powerful analytical framework: multilayer or multiplex networks [11][12][13][14][15][16][17][18][19][20][21][22] , where the intra-links and inter-links represent the multiple social relations (channels) among individuals. So far, the majority of researches about multilayer networks are mainly focused on how the one-to-one interconnections influence the dynamic processes taking place on them [41][42][43][44][45][46][47][48] .…”