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Although we have made progress in understanding disease spread in complex systems with non-Poissonian activity patterns, current models still fail to capture the full range of recovery time distributions. In this paper, we propose an…

社会与信息网络 · 计算机科学 2025-11-25 Jiexi Tang , Yichao Yao , Meiling Xie , Minyu Feng

We study a susceptible-infected-removed (SIR) model with multiple seeds on a regular random graph. Many researchers have studied the epidemic threshold of epidemic models above which a global outbreak can occur, starting from an…

物理与社会 · 物理学 2016-04-06 Takehisa Hasegawa , Koji Nemoto

Initially emerged in the Chinese city Wuhan and subsequently spread almost worldwide causing a pandemic, the SARS-CoV-2 virus follows reasonably well the SIR (Susceptible-Infectious-Recovered) epidemic model on contact networks in the…

物理与社会 · 物理学 2020-10-28 Clara Pizzuti , Annalisa Socievole , Bastian Prasse , Piet Van Mieghem

The rapidly spreading Covid-19 that affected almost all countries, was first reported at the end of 2019. As a consequence of its highly infectious nature, countries all over the world have imposed extremely strict measures to control its…

种群与进化 · 定量生物学 2020-07-13 Semra Ahmetolan , Ayse Humeyra Bilge , Ali Demirci , Ayse Peker-Dobie , Onder Ergonul

The SIRS process is a continuous-time process for how infections spread on a graph. In this model, each vertex is in one of the following three states: susceptible (to the infection; S), infected (I), or recovered (R) and thus immune to the…

概率论 · 数学 2026-05-20 Andreas Göbel , Nicolas Klodt , Martin S. Krejca

We study the diffusion of epidemics on networks that are partitioned into local communities. The gross structure of hierarchical networks of this kind can be described by a quotient graph. The rationale of this approach is that individuals…

社会与信息网络 · 计算机科学 2016-01-19 Stefano Bonaccorsi , Stefania Ottaviano , Delio Mugnolo , Francesco De Pellegrini

Much effort has been directed towards using mathematical models to understand and predict contagious disease, in particular Ebola outbreaks. Classical SIR (susceptible-infected-recovered) compartmental models capture well the dynamics of…

种群与进化 · 定量生物学 2015-12-22 Anca Radulescu , Joanna Herron

We consider the spread of a supercritical stochastic SIR (Susceptible, Infectious, Recovered) epidemic on a configuration model random graph. We mainly focus on the final stages of a large outbreak and provide limit results for the duration…

概率论 · 数学 2020-02-26 Abid Ali Lashari , Ana Serafimović , Pieter Trapman

We consider the spread of a Susceptible-Infected-Recovered (SIR) disease through finite populations and derive an expression for the final size distribution. Our derivation allows arbitrary distributions of the number of transmissions…

种群与进化 · 定量生物学 2019-07-12 Joel C Miller

Exact solution of the Susceptible-Infectious-Recovered (SIR) epidemic model is derived, and various properties of solution are obtained directly from the exact solution. It is shown that there exists an exact solution of an initial value…

种群与进化 · 定量生物学 2022-10-04 Norio Yoshida

This paper is concerned with a stochastic model for the spread of an SEIR (susceptible -> exposed (=latent) -> infective -> removed) epidemic with a contact tracing scheme, in which removed individuals may name some of their infectious…

概率论 · 数学 2015-12-08 Frank G Ball , Edward S Knock , Philip D O'Neill

This paper investigates a behavioral-feedback SIR model in which the infection rate adapts dynamically based on the fractions of susceptible and infected individuals. We introduce an invariant of motion and we characterize the peak of…

种群与进化 · 定量生物学 2025-09-17 Martina Alutto , Leonardo Cianfanelli , Giacomo Como , Fabio Fagnani , Francesca Parise

One of the most effective strategies to mitigate the global spreading of a pandemic (e.g., COVID-19) is to shut down international airports. From a network theory perspective, this is since international airports and flights, essentially…

物理与社会 · 物理学 2023-10-24 Jing Ma , Xiangyi Meng , Lidia A. Braunstein

Most real networks are characterized by connectivity patterns that evolve in time following complex, non-Markovian, dynamics. Here we investigate the impact of this ubiquitous feature by studying the Susceptible-Infected-Recovered (SIR) and…

物理与社会 · 物理学 2016-01-20 Kaiyuan Sun , Andrea Baronchelli , Nicola Perra

With the premise that social interactions are described by power-law distributions, we study a SIR stochastic dynamic on a static scale-free random network generated via configuration model. We verify our model with respect to deterministic…

物理与社会 · 物理学 2024-05-10 Sara Sottile , Ozan Kahramanoğulları , Mattia Sensi

Consider an SI process on a graph $G$ where each S--I connection becomes I--I at rate $\lambda$. Here S and I stand for ``susceptible'' and ``infected'' respectively. The evoSI model is a modification of the SI model in which S--I edges are…

概率论 · 数学 2026-03-04 Wenze Chen , Haojie Hou , Ruibo Ma , Dong Yao

Epidemic models are increasingly used in real-world networks to understand diffusion phenomena (such as the spread of diseases, emotions, innovations, failures) or the transport of information (such as news, memes in social on-line…

物理与社会 · 物理学 2016-12-06 Piet Van Mieghem

We study the Suscectible-Infected-Recovered-Susceptible (SIRS) epidemic model on deterministic networks. For connected but otherwise general interaction patterns and heterogeneous recovery and loss-of-immunity rates, we identify a…

系统与控制 · 电气工程与系统科学 2026-04-24 Giulia Gatti , Giacomo Como

An ultrametric model of epidemic spread of infections based on the classical SIR model is proposed. Ultrametrics on a set of individuals based on theire hierarchical clustering relativly to the average time of infectious contact is…

物理与社会 · 物理学 2020-07-21 V. T. Volov , A. P. Zubarev

In this manuscript, we develop a mobility-based Susceptible-Infectious-Recovered (SIR) model to elucidate the dynamics of pandemic propagation. While traditional SIR models within the field of epidemiology aptly characterize transitions…

动力系统 · 数学 2025-01-16 Ciana Applegate , Jiaxu Li , Dan Han
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