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相关论文: Large-deviations of the SIR model around the epide…

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We study the spread of susceptible-infected-recovered (SIR) infectious diseases where an individual's infectiousness and probability of recovery depend on his/her "age" of infection. We focus first on early outbreak stages when stochastic…

种群与进化 · 定量生物学 2009-05-14 Joel Miller , Bahman Davoudi , Rafael Meza , Anja Slim , Babak Pourbohloul

Mathematical models of infectious diseases exhibit robust dynamics such as stable endemic or a disease-free equilibrium, or convergence of the solutions to periodic epidemic waves. The present work shows that the accuracy of such dynamics…

应用统计 · 统计学 2022-05-04 Hadeel AlQadi , Majid Bani-Yaghoub

We study two simple mathematical models of the epidemic. At first, we study the repetitive infection spreading in a simplified SIRS model including the effect of the decay of the acquired immune. The model is an intermediate model of the…

种群与进化 · 定量生物学 2024-03-13 Hidetsugu Sakaguchi , Keito Yamasaki

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

We introduce a modified SIR model with memory for the dynamics of epidemic spreading in a constant population of individuals. Each individual is in one of the states susceptible (${\bf S}$), infected (${\bf I}$) or recovered (${\bf R}$). In…

Disease awareness in infection dynamics can be modeled with adaptive contact networks whose rewiring rules reflect the attempt by susceptibles to avoid infectious contacts. Simulations of this type of models show an active phase with…

适应与自组织系统 · 物理学 2012-12-06 Stefan Wieland , Tomas Aquino , Ana Nunes

We performed a thorough sensitivity analysis of the herd immunity threshold for discrete-time SIR compartmental models with a static network structure. We find unexpectedly that these models violate classical intuition which holds that the…

种群与进化 · 定量生物学 2023-02-27 Sinan A. Ozbay , Bjarke F. Nielsen , Maximilian M. Nguyen

We consider a SIR model with vaccination strategy on a sparse configuration model random graph. We show the convergence of the system when the number of nodes grows and characterize the scaling limits. Then, we prove the existence of…

We consider in this paper a general SEIRS model describing the dynamics of an infectious disease including latency, waning immunity and infection-induced mortality. We derive an infinite system of differential equations that provides an…

最优化与控制 · 数学 2022-01-26 Marcel Fang , Pierre-Alexandre Bliman

In this paper, we analyze dynamic switching networks, wherein the networks switch arbitrarily among a set of topologies. For this class of dynamic networks, we derive an epidemic threshold, considering the SIS epidemic model. First, an…

社会与信息网络 · 计算机科学 2015-08-03 Mohammad Reza Sanatkar , Warren N. White , Balasubramaniam Natarajan , Caterina Scoglio , Karren A. Garrett

Contact patterns in populations fundamentally influence the spread of infectious diseases. Current mathematical methods for epidemiological forecasting on networks largely assume that contacts between individuals are fixed, at least for the…

种群与进化 · 定量生物学 2007-05-23 Erik Volz , Lauren Ancel Meyers

This paper presents a discrete time probabilistic dynamic for simulating a contact-based epidemic spreading based on discrete time Markov chain process, in particular the attention is addressed to the susceptible-infectious-removed (SIR)…

物理与社会 · 物理学 2017-12-22 Fabrizio Angaroni

We propose a novel multi-scale modeling framework for infectious disease spreading, borrowing ideas and modeling tools from the so-called Refractory Density (RD) approach. We introduce a microscopic model that describes the probability of…

种群与进化 · 定量生物学 2025-03-24 Anton Chizhov , Laurent Pujo-Menjouet , Tilo Schwalger , Mattia Sensi

Understanding the dynamics of the spread of diseases within populations is critical for effective public health interventions. We extend the classical SIR model by incorporating additional complexities such as the introduction of a cure and…

种群与进化 · 定量生物学 2025-10-30 Daniel Perkins , Davis Hunter , Drake Brown , Trevor Garrity , Wyatt Pochman

Most infectious diseases spread on a dynamic network of human interactions. Recent studies of social dynamics have provided evidence that spreading patterns may depend strongly on detailed micro-dynamics of the social system. We have…

物理与社会 · 物理学 2015-09-23 Arkadiusz Stopczynski , Alex Sandy Pentland , Sune Lehmann

A network epidemic model is studied. The underlying social network has two different types of group structures, households and workplaces, such that each individual belongs to exactly one household and one workplace. The random network is…

概率论 · 数学 2024-10-10 Frank Ball , Tom Britton , Peter Neal

Network science has increasingly become central to the field of epidemiology and our ability to respond to infectious disease threats. However, many networks derived from modern datasets are not just large, but dense, with a high ratio of…

种群与进化 · 定量生物学 2023-01-11 Alexander M. Mercier , Samuel V. Scarpino , Cristopher Moore

In this paper, we are concerned with stochastic susceptible-exposed-infected-removed epidemics on complete graphs with vertex-dependent transition rates. Large and moderate deviations of empirical density fields of our models are given.…

概率论 · 数学 2023-05-02 Xiaofeng Xue , Xueting Yin

We study the phase transition from the persistence phase to the extinction phase for the SIRS (susceptible/ infected/ refractory/ susceptible) model of diseases spreading on the networks. We derive an analytical expression of the…

种群与进化 · 定量生物学 2019-11-18 M. Ali Saif

In the standard SIR model, infected vertices infect their neighbors at rate $\lambda$ independently across each edge. They also recover at rate $\gamma$. In this work we consider the SIR-$\omega$ model where the graph structure itself…

概率论 · 数学 2025-05-16 Wenze Chen , Yuewen Hou , Dong Yao