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相关论文: Modeling the Spread of Multiple Contagions on Mult…

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We develop a theory for the susceptible-infected-susceptible (SIS) epidemic model on networks that incorporate both network structure and dynamic correlations. This theory can account for the multistage onset of the epidemic phase in…

物理与社会 · 物理学 2021-04-07 Chao-Ran Cai , Zhi-Xi Wu , Petter Holme

The Susceptible-Infected-Recovered (SIR) model is studied in multilayer networks with arbitrary number of links across the layers. By following the mapping to bond percolation we give the analytical expression for the epidemic threshold and…

种群与进化 · 定量生物学 2017-03-09 Ginestra Bianconi

Social interactions are stratified in multiple contexts and are subject to complex temporal dynamics. The systematic study of these two features of social systems has started only very recently mainly thanks to the development of multiplex…

物理与社会 · 物理学 2018-12-12 Quan-Hui Liu , Xinyue Xiong , Qian Zhang , Nicola Perra

One of the popular dynamics on complex networks is the epidemic spreading. An epidemic model describes how infections spread throughout a network. Among the compartmental models used to describe epidemics, the…

物理与社会 · 物理学 2011-07-14 Faryad Darabi Sahneh , Caterina Scoglio

We present a modified \emph{susceptible-infected-susceptible} (SIS) model on complex networks, small-world and scale-free, to study epidemic spreading with the effect of time delay which is introduced to the infected phase. Considering the…

物理与社会 · 物理学 2009-11-11 Xin-Jian Xu , Hai-Ou Peng , Xiao-Mei Wang , Ying-Hai Wang

Infectious diseases are practically represented by models with multiple states and complex transition rules corresponding to, for example, birth, death, infection, recovery, disease progression, and quarantine. In addition, networks…

无序系统与神经网络 · 物理学 2007-05-23 Naoki Masuda , Norio Konno

A key scientific challenge during the outbreak of novel infectious diseases is to predict how the course of the epidemic changes under different countermeasures that limit interaction in the population. Most epidemiological models do not…

The compartmental models used to study epidemic spreading often assume the same susceptibility for all individuals, and are therefore, agnostic about the effects that differences in susceptibility can have on epidemic spreading. Here we…

物理与社会 · 物理学 2014-03-12 Daniel Smilkov , Cesar A. Hidalgo , Ljupco Kocarev

There is a rich history of models for the interaction of a biological contagion like influenza with the spread of related information such as an influenza vaccination campaign. Recent work on the spread of interacting contagions on networks…

物理与社会 · 物理学 2020-09-02 Laurent Hébert-Dufresne , Dina Mistry , Benjamin M. Althouse

To improve the accuracy of network-based SIS models we introduce and study a multilayer representation of a time-dependent network. In particular, we assume that individuals have their long-term (permanent) contacts that are always present,…

物理与社会 · 物理学 2018-12-13 Aram Vajdi , David Juher , Joan Saldana , Caterina Scoglio

In this paper we study the household-structure SIS epidemic spreading on general complex networks. The household structure gives us the way to distinguish inner and the outer infection rate. Unlike household-structure models on homogenous…

种群与进化 · 定量生物学 2013-02-14 Jingzhou Liu , Jinshan Wu , Z. R. Yang

We study the spreading of a disease on top of structured scale-free networks recently introduced. By means of numerical simulations we analyze the SIS and the SIR models. Our results show that when the connectivity fluctuations of the…

统计力学 · 物理学 2009-11-07 Yamir Moreno , Alexei Vazquez

This paper deals with the statistical signal pro- cessing over graphs for tracking infection diffusion in social networks. Infection (or Information) diffusion is modeled using the Susceptible-Infected-Susceptible (SIS) model. Mean field…

社会与信息网络 · 计算机科学 2016-11-01 Vikram Krishnamurthy , Sujay Bhatt , Tavis Pedersen

Recent studies on network geometry, a way of describing network structures as geometrical objects, are revolutionizing our way to understand dynamical processes on networked systems. Here, we cope with the problem of epidemic spreading,…

物理与社会 · 物理学 2020-03-04 Joan T. Matamalas , Sergio Gómez , Alex Arenas

We study the spreading of an infection within an SIS epidemiological model on a network. Susceptible agents are given the opportunity of breaking their links with infected agents. Broken links are either permanently removed or reconnected…

种群与进化 · 定量生物学 2007-11-07 Damian H. Zanette , Sebastian Risau Gusman

The duration, type and structure of connections between individuals in real-world populations play a crucial role in how diseases invade and spread. Here, we incorporate the aforementioned heterogeneities into a model by considering a…

物理与社会 · 物理学 2018-04-05 Rosanna C Barnard , Istvan Z Kiss , Luc Berthouze , Joel C Miller

This study extends the SIS epidemic model for single virus propagation over an arbitrary graph to an SI1SI2S epidemic model of two exclusive, competitive viruses over a two-layer network with generic structure, where network layers…

物理与社会 · 物理学 2013-09-02 Faryad Darabi Sahneh , Caterina Scoglio

Prior social contagion models consider the spread of either one contagion at a time on interdependent networks or multiple contagions on single layer networks or under assumptions of competition. We propose a new threshold model for the…

社会与信息网络 · 计算机科学 2018-09-13 Ho-Chun Herbert Chang , Feng Fu

This paper deals with the spread of diseases over both a population network and an infrastructure network. We develop a layered networked spread model for a susceptible-infected-susceptible (SIS) pathogen-borne disease spreading over a…

系统与控制 · 电气工程与系统科学 2021-09-21 Philip E. Pare , Axel Janson , Sebin Gracy , Ji Liu , Henrik Sandberg , Karl H. Johansson

Over the years numerous models of SIS (susceptible - infected - susceptible) disease dynamics unfolding on networks have been proposed. Here, we discuss the links between many of these models and how they can be viewed as more general…

种群与进化 · 定量生物学 2013-04-10 Timothy J Taylor , Istvan Z Kiss
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