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A Markovian SIR (Susceptible-Infectious-Recovered) model is considered for the spread of an epidemic on a configuration model network, in which susceptible individuals may take preventive measures by dropping edges to infectious neighbours.…

概率论 · 数学 2019-01-23 Frank Ball , Tom Britton , Ka Yin Leung , David Sirl

Containment of epidemic outbreaks entails great societal and economic costs. Cost-effective containment strategies rely on efficiently identifying infected individuals, making the best possible use of the available testing resources.…

种群与进化 · 定量生物学 2020-12-01 Laura Natali , Saga Helgadottir , Onofrio M. Marago , Giovanni Volpe

This paper presents a novel time-space SIR (Susceptible-Infected-Recovered) model for simulating infectious disease dynamics in two interconnected regions. The model is formulated as a coupled reaction-diffusion system with boundary…

偏微分方程分析 · 数学 2026-05-13 Omar Elamraoui , Jawad Salhi , Abderrahim Zafrar

The internet of things (IoT) has gained worldwide attention in recent years. It transforms the everyday objects that surround us into proactive actors of the Internet, generating and consuming information. An important issue related to the…

分布式、并行与集群计算 · 计算机科学 2016-08-29 Abdallah Makhoul , Christophe Guyeux , Mourad Hakem , Jacques M. Bahi

It is the main purpose of this paper to introduce a graph-valued stochastic process in order to model the spread of a communicable infectious disease. The major novelty of the SIR model we promote lies in the fact that the social network on…

应用统计 · 统计学 2014-02-06 Charanpal Dhanjal , Stéphan Clémençon

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

The paper deals with the setting where two viruses (say virus 1 and virus 2) coexist in a population, and they are not necessarily mutually exclusive, in the sense that infection due to one virus does not preclude the possibility of…

种群与进化 · 定量生物学 2024-07-12 Sebin Gracy , Philip E. Paré , Ji Liu , Henrik Sandberg , Carolyn L. Beck , Karl Henrik Johansson , Tamer Başar

Compartmental models like the Susceptible-Infected-Recovered (SIR)\cite{Kermack1927} and its extensions such as the Susceptible-Exposed-Infected-Recovered (SEIRS)\cite{Ottar2020,Ignazio2021,Grimm2021,Paoluzzi2021} are commonly used to model…

种群与进化 · 定量生物学 2025-07-14 Kasturi Banerjee , Subhankar Ray , Jayalakshmi Shamanna

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

How to prevent the spread of human diseases is a great challenge for the scientific community and so far there are many studies in which immunization strategies have been developed. However, these kind of strategies usually do not consider…

物理与社会 · 物理学 2018-08-22 M. A. Di Muro , L. G. Alvarez-Zuzek , S. Havlin , L. A. Braunstein

The non-population conserving SIR (SIR-NC) model to describe the spread of infections in a community is proposed and studied. Unlike the standard SIR model, SIR-NC does not assume population conservation. Although similar in form to the…

最优化与控制 · 数学 2020-11-06 Vivek S. Borkar , D. Manjunath

This paper analyses the optimal control of infectious disease propagation using a classic susceptible-infected-recovered (SIR) model characterised by permanent immunity and the absence of available vaccines. The control is performed over a…

In a metapopulation network, infectious diseases spread widely because of the travel of individuals. In the present study, we consider a modified metapopulation Susceptible-Infected-Removed (SIR) model with a latent period, which we call…

物理与社会 · 物理学 2017-08-02 Kazue Kudo , Kanako Mizuno

The simplest epidemiologic model composed by mutually exclusive compartments SIR (susceptible-infected-susceptible) is presented to describe a reality. From health concerns to situations related with marketing, informatics or even…

物理与社会 · 物理学 2016-11-09 Helena Sofia Rodrigues

We study the class of SIS epidemics on temporal networks and propose a new activity-driven and adaptive epidemic model that captures the impact of asymptomatic and infectious individuals in the network. In the proposed model, referred to as…

物理与社会 · 物理学 2020-08-04 Ashish R. Hota , Kavish Gupta

We numerically study the dynamics of the SIR disease model on small-world networks by using a large-deviation approach. This allows us to obtain the probability density function of the total fraction of infected nodes and of the maximum…

物理与社会 · 物理学 2022-09-01 Yannick Feld , Alexander K. Hartmann

In this paper, we propose a Susceptible-Infected-Removal (SIR) model with time fused coefficients. In particular, our proposed model discovers the underlying time homogeneity pattern for the SIR model's transmission rate and removal rate…

应用统计 · 统计学 2021-03-11 Hou-Cheng Yang , Yishu Xue , Yuqing Pan , Qingyang Liu , Guanyu Hu

I estimate the Susceptible-Infected-Recovered (SIR) epidemic model for Coronavirus Disease 2019 (COVID-19). The transmission rate is heterogeneous across countries and far exceeds the recovery rate, which enables a fast spread. In the…

种群与进化 · 定量生物学 2020-03-27 Alexis Akira Toda

We study a dynamic infection spread model, inspired by the discrete time SIR model, where infections are spread via non-isolated infected individuals. While infection keeps spreading over time, a limited capacity testing is performed at…

统计方法学 · 统计学 2022-01-25 Batuhan Arasli , Sennur Ulukus

This paper addresses novel consensus problems for multi-agent systems operating in an unreliable environment where adversaries are spreading. The dynamics of the adversarial spreading processes follows the susceptible-infected-recovered…

系统与控制 · 电气工程与系统科学 2022-01-12 Yuan Wang , Hideaki Ishii , François Bonnet , Xavier Défago