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In this paper we present a model describing Susceptible-Infected-Susceptible (SIS) type epidemics spreading on a dynamic contact network with random link activation and deletion where link ac- tivation can be locally constrained. We use and…

动力系统 · 数学 2015-05-30 Michael Taylor , Timothy J. Taylor , Istvan Z. Kiss

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 develop an analytical approach to the susceptible-infected-susceptible (SIS) epidemic model that allows us to unravel the true origin of the absence of an epidemic threshold in heterogeneous networks. We find that a delicate balance…

物理与社会 · 物理学 2013-09-13 Marian Boguna , Claudio Castellano , Romualdo Pastor-Satorras

The epidemic threshold of the susceptible-infected-susceptible (SIS) dynamics on random networks having a power law degree distribution with exponent $\gamma>3$ has been investigated using different mean-field approaches, which predict…

物理与社会 · 物理学 2015-06-19 Angélica S. Mata , Silvio C. Ferreira

In the study of infectious diseases on networks, researchers calculate epidemic thresholds to help forecast whether a disease will eventually infect a large fraction of a population. Because network structure typically changes in time,…

社会与信息网络 · 计算机科学 2021-08-11 Qinyi Chen , Mason A. Porter

In this paper, we study the dynamics of epidemic processes taking place in adaptive networks of arbitrary topology. We focus our study on the adaptive susceptible-infected-susceptible (ASIS) model, where healthy individuals are allowed to…

社会与信息网络 · 计算机科学 2016-06-29 Masaki Ogura , Victor M. Preciado

The SIS (susceptible-infected-susceptible) epidemic model on an arbitrary network, without making approximations, is a $2^n$-state Markov chain with a unique absorbing state (the all-healthy state). This makes analysis of the SIS model and,…

社会与信息网络 · 计算机科学 2019-01-21 Navid Azizan Ruhi , Christos Thrampoulidis , Babak Hassibi

To simplify mathematical models of disease spread, we often assume equal contact rates among hosts, but real-world scenarios differ. Network-based frameworks help capture these complexities and structural variations in actual systems. We…

动力系统 · 数学 2024-07-03 Saswata Das , Mohammad Hossein Samaei , Caterina Scoglio

Network-based models of epidemic spread have become increasingly popular in recent decades. Despite a rich foundation of such models, few low-dimensional systems for modeling SIS-type diseases have been proposed that manage to capture the…

动力系统 · 数学 2021-01-01 Carl Corcoran , Alan Hastings

We study the susceptible-infected-susceptible (SIS) model on directed complex networks within the quenched mean-field approximation. Combining results from random matrix theory with an analytic approach to the distribution of fixed-point…

物理与社会 · 物理学 2025-12-12 Vinícius B. Müller , Fernando L. Metz

Recent work has shown that different theoretical approaches to the dynamics of the Susceptible-Infected-Susceptible (SIS) model for epidemics lead to qualitatively different estimates for the position of the epidemic threshold in networks.…

统计力学 · 物理学 2012-10-17 Silvio C. Ferreira , Claudio Castellano , Romualdo Pastor-Satorras

We analyze two alterations of the standard susceptible-infected-susceptible (SIS) dynamics that preserve the central properties of spontaneous healing and infection capacity of a vertex increasing unlimitedly with its degree. All models…

物理与社会 · 物理学 2018-07-19 Wesley Cota , Angélica S. Mata , Silvio C. Ferreira

We demonstrate that the susceptible-infected-susceptible (SIS) model on complex networks can have an inactive Griffiths phase characterized by a slow relaxation dynamics. It contrasts with the mean field theoretical prediction that the SIS…

物理与社会 · 物理学 2015-06-12 Hyun Keun Lee , Pyoung-Seop Shim , Jae Dong Noh

We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold…

统计力学 · 物理学 2009-11-07 Romualdo Pastor-Satorras , Alessandro Vespignani

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

Epidemic threshold is one of the most important features of the epidemic dynamics. Through a lot of numerical simulations in classic Susceptible-Infected-Recovered (SIR) and Susceptible-Infected-Susceptible (SIS) models on various types of…

物理与社会 · 物理学 2014-10-16 Panpan Shu , Wei Wang , Ming Tang , Younghae Do

We calculate epidemic thresholds and investigate the dynamics of a disease in a networked metapopulation model. To study the specific role of mobility levels and network geometry, we utilize the SIR-Network model and consider a range of…

物理与社会 · 物理学 2023-08-07 Haridas K. Das , Lucas M. Stolerman

Pairwise models are used widely to model epidemic spread on networks. These include the modelling of susceptible-infected-removed (SIR) epidemics on regular networks and extensions to SIS dynamics and contact tracing on more exotic networks…

种群与进化 · 定量生物学 2018-09-24 István Z. Kiss , Joel C. Miller , Péter L. Simon

We study the Susceptible-Infectious-Susceptible (SIS) model on arbitrary networks. The well-established pair approximation treats neighboring pairs of nodes exactly while making a mean field approximation for the rest of the network. We…

社会与信息网络 · 计算机科学 2026-05-05 George Cantwell , Cristopher Moore

We study the standard SIS model of epidemic spreading on networks where individuals have a fluctuating number of connections around a preferred degree $\kappa $. Using very simple rules for forming such preferred degree networks, we find…

统计力学 · 物理学 2012-12-05 Shivakumar Jolad , Wenjia Liu , B. Schmittmann , R. K. P. Zia
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