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We consider an SEIR epidemic model on a network also allowing random contacts, where recovered individuals could either recover naturally or be diagnosed. Upon diagnosis, manual contact tracing is triggered such that each infected network…

物理与社会 · 物理学 2024-06-06 Dongni Zhang , Tom Britton

Consider a Markovian SIR epidemic model in a homogeneous community. To this model we add a rate at which individuals are tested, and once an infectious individual tests positive it is isolated and each of their contacts are traced and…

种群与进化 · 定量生物学 2022-08-08 Dongni Zhang , Tom Britton

Contacts between people are the absolute drivers of contagious respiratory infections. For this reason, limiting and tracking contacts is a key strategy for the control of the COVID-19 epidemic. Digital contact tracing has been proposed as…

计算机与社会 · 计算机科学 2022-12-01 Chiara Boldrini , Andrea Passarella , Marco Conti

A stochastic epidemic model accounting for the effect of contact-tracing on the spread of an infectious disease is studied. Precisely, individuals identified as infected may contribute to detecting other infectious individuals by providing…

概率论 · 数学 2009-03-28 Stéphan Clémençon , Viet Chi Tran , Hector De Arazoza

In this paper we consider a model for the spread of a stochastic SIR (Susceptible $\to$ Infectious $\to$ Recovered) epidemic on a network of individuals described by a random intersection graph. Individuals belong to a random number of…

概率论 · 数学 2014-04-29 Frank G. Ball , David J. Sirl , Pieter Trapman

We study a class of individual-based, fixed-population size epidemic models under general assumptions, e.g., heterogeneous contact rates encapsulating changes in behavior and/or enforcement of control measures. We show that the…

概率论 · 数学 2023-07-04 Jean-Jil Duchamps , Félix Foutel-Rodier , Emmanuel Schertzer

A stochastic SIR (susceptible $\to$ infective $\to$ recovered) epidemic model defined on a social network is analysed. The underlying social network is described by an Erd\H{o}s-R\'{e}nyi random graph but, during the course of the epidemic,…

概率论 · 数学 2020-08-17 Frank Ball , Tom Britton

We consider a stochastic epidemic model with sideward contact tracing. We assume that infection is driven by interactions within mixing events (gatherings of two or more individuals). Once an infective is diagnosed, each individual who was…

种群与进化 · 定量生物学 2025-03-28 Dongni Zhang , Martina Favero

We study extensions of the classical SIR model of epidemic spread. First, we consider a single population modified SIR epidemics model in which the contact rate is allowed to be an arbitrary function of the fraction of susceptible and…

动力系统 · 数学 2021-12-17 Martina Alutto , Giacomo Como , Fabio Fagnani

A generalization of the standard susceptible-infectious-removed (SIR) stochastic model for epidemics in sparse random networks is introduced which incorporates contact tracing in addition to random screening. We propose a deterministic…

适应与自组织系统 · 物理学 2009-11-07 Ramon Huerta , Lev S. Tsimring

In this paper we study a susceptible infectious recovered (SIR) model with asymptomatic patients, contact tracing and isolation on a configuration network. Using degree based approximation, we derive a system of differential equations for…

社会与信息网络 · 计算机科学 2022-12-20 Duan-Shin Lee , Ting-Zhe Liu , Ruhui Zhang , Cheng-Shang Chang

We investigate final outcome properties of an SIR (susceptible $\to$ infective $\to$ recovered) epidemic model defined on a population of large sub-communities in which there is stronger disease transmission within the communities than…

概率论 · 数学 2024-04-08 Frank Ball , David Sirl , Pieter Trapman

Infection spread among individuals is modelled with a continuous time Markov chain, in which subject interactions depend on their distance in space. The well known SIR model and non local variants of the latter are then obtained as large…

概率论 · 数学 2023-09-27 Franco Flandoli , Francesco Grotto , Andrea Papini , Cristiano Ricci

We present a modelling framework for the spreading of epidemics on temporal networks from which both the individual-based and pair-based models can be recovered. The proposed temporal pair-based model that is systematically derived from…

物理与社会 · 物理学 2020-11-17 Rory Humphries , Kieran Mulchrone , Jamie Tratalos , Simon More , Philipp Hövel

We propose a generative model and an inference scheme for epidemic processes on dynamic, adaptive contact networks. Network evolution is formulated as a link-Markovian process, which is then coupled to an individual-level stochastic SIR…

统计方法学 · 统计学 2020-04-07 Fan Bu , Allison E. Aiello , Jason Xu , Alexander Volfovsky

Consider a large uniformly mixing dynamic population, which has constant birth rate and exponentially distributed lifetimes, with mean population size $n$. A Markovian SIR (susceptible $\to$ infective $\to$ recovered) infectious disease,…

概率论 · 数学 2015-06-09 Frank Ball , Tom Britton , Pieter Trapman

In most models of the spread of disease over contact networks it is assumed that the probabilities per unit time of disease transmission and recovery from disease are constant, implying exponential distributions of the time intervals for…

物理与社会 · 物理学 2010-07-23 Brian Karrer , M. E. J. Newman

We study an individual-based stochastic SIR epidemic model with infection-age dependent infectivity on a large random graph, capturing individual heterogeneity and non-homogeneous connectivity. Each individual is associated with particular…

概率论 · 数学 2026-02-11 Guodong Pang , Étienne Pardoux , Aurélien Velleret

Epidemic modelling on complex networks has been studied intensively all the time. The majority of relative research assumes that the time scale of the underlying network evolution is much larger compared to the propagation dynamics on it,…

物理与社会 · 物理学 2026-04-14 Minyu Feng , Yuhan Li , Jürgen Kurths

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
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