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The Susceptible-Infectious-Recovered (SIR) equations and their extensions comprise a commonly utilized set of models for understanding and predicting the course of an epidemic. In practice, it is of substantial interest to estimate the…

应用统计 · 统计学 2025-05-07 Omar Melikechi , Alexander L. Young , Tao Tang , Trevor Bowman , David Dunson , James Johndrow

The susceptible-infectious-recovered (SIR) model describes the evolution of three species of individuals which are subject to an infection and recovery mechanism. A susceptible $S$ can become infectious with an infection rate $\beta$ by an…

统计力学 · 物理学 2008-06-30 Gunter M. Schütz , Marian Brandau , Steffen Trimper

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

We study the problem of optimal control of the stochastic SIR model. Models of this type are used in mathematical epidemiology to capture the time evolution of highly infectious diseases such as COVID-19. Our approach relies on…

种群与进化 · 定量生物学 2020-05-04 Andrew Lesniewski

We present an exact analytical solution to a one-dimensional model of the Susceptible-Infected-Recovered (SIR) epidemic type, with infection rates dependent on nearest-neighbor occupations. We use a quantum mechanical approach, transforming…

统计力学 · 物理学 2015-05-30 H. Thomas Williams , Irina Mazilu , Dan Mazilu

Susceptible-Infected-Recovered (SIR) models have been used for decades to understand epidemic outbreak dynamics. We develop an SIR model specifically designed to study the effects of population behavior with respect to health and…

种群与进化 · 定量生物学 2023-08-03 Jasmin Nunuvero , Angelique Santiago , Moshe Cohen , Anca Radulescu

The SIR model is the cornerstone model for mathematical epidemiology, explaining key epidemic features such as the second-order transition between disease-free and epidemic states, the initial exponential growth of outbreaks or the…

种群与进化 · 定量生物学 2026-03-20 Santiago Lamata-Otín , Alex Arenas , Jesús Gómez-Gardeñes , David Soriano-Paños

Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in…

种群与进化 · 定量生物学 2016-03-29 Chantal Nguyen , Jean M. Carlson

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

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…

This paper presents a simple continuous-time linear vaccination-based control strategy for a SEIR (susceptible plus infected plus infectious plus removed populations) propagation disease model. The model takes into account the total…

动力系统 · 数学 2011-03-28 M. De la Sen , A. Ibeas , S. Alonso-Quesada

In this work, we study the evolution of the susceptible individuals during the spread of an epidemic modeled by the susceptible-infected-recovered (SIR) process spreading on the top of complex networks. Using an edge-based compartmental…

物理与社会 · 物理学 2012-09-25 L. D. Valdez , P. A. Macri , L. A. Braunstein

In the recent COVID-19 pandemic we assisted at a sequence of epidemic waves intertwined by anomalous fade-outs with periods of low but persistent epidemic prevalence. These long-living epidemic states complicate epidemic control and…

物理与社会 · 物理学 2025-08-27 Javier Aguilar , Beatriz Arregui García , Raúl Toral , Sandro Meloni , Jose J. Ramasco

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…

We consider the SIR epidemiological model applied to the evolution of COVID-19 with two approaches. In the first place we fit a global SIR model, with time delay, and constant parameters throughout the outbreak, including the contagion…

种群与进化 · 定量生物学 2020-06-23 Nana Geraldine Cabo Bizet , Damián Kaloni Mayorga Peña

We study the susceptible-infective-recovered (SIR) epidemic on a random graph chosen uniformly subject to having given vertex degrees. In this model infective vertices infect each of their susceptible neighbours, and recover, at a constant…

概率论 · 数学 2014-09-24 Svante Janson , Malwina Luczak , Peter Windridge

To better describe the spread of a disease, we extend a discrete time stochastic SIR-type epidemic model of Tuckwell and Williams. We assume the dependence on time of the number of daily encounters and include a parameter to represent a…

种群与进化 · 定量生物学 2022-09-30 Mireia Besalú , Giulia Binotto

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

In this paper we generalise a simple discrete time stochastic SIR type model defined by Tuckwell and Williams. The SIR model by Tuckwell and Williams assumes a homogeneous population, a fixed infectious period, and a strict transition from…

种群与进化 · 定量生物学 2025-04-21 Carles Rovira

We consider a susceptible, infected, removed (SIR) system where the transmission rate may be temporarily reduced for a fixed amount of time. We show that in order to minimize the total number of fatalities, the transmission rate should be…

动力系统 · 数学 2021-07-20 Yuanyuan Feng , Gautam Iyer , Lei Li