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Dynamic properties of spreading infection through a heterogeneous population are studied numerically and analytically using a dynamic variant of Watts and Strogatz Small World Network-based stochastic Susceptible-Exposed-Infectious-Removed…

种群与进化 · 定量生物学 2019-06-28 O. Mosbah , N. Zekri , M. Mokhtari , S. Sahraoui

Containment measures implemented by some countries to suppress the spread of COVID-19 have resulted in a slowdown of the epidemic characterized by time series of daily infections plateauing over extended periods of time. We prove that such…

物理与社会 · 物理学 2020-11-17 Filippo Radicchi , Ginestra Bianconi

Since 1927, until recently, models describing the spread of disease have mostly been of the SIR-compartmental type, based on the assumption that populations are homogeneous and well-mixed. The focus of these models have typically been on…

物理与社会 · 物理学 2014-07-23 Lara Goscé , David A W Barton , Anders Johansson

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

In general, the rates of infection and removal (whether through recovery or death) are nonlinear functions of the number of infected and susceptible individuals. One of the simplest models for the spread of infectious diseases is the SIR…

种群与进化 · 定量生物学 2026-05-11 Seong Jun Park , M. Y. Choi

In this study, a new and natural way of constructing a stochastic Susceptible-Infected-Susceptible (SIS) model is proposed. This approach is natural in the sense that the disease transmission rate, $\beta$, is substituted with a generic,…

概率论 · 数学 2025-11-07 Berk Tan Perçin

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

Transmission rates in epidemic outbreaks may vary over time depending on the societal response. Non-pharmacological mitigation strategies such as social distancing and the adoption of protective equipment aim precisely at reducing…

种群与进化 · 定量生物学 2020-12-24 Elisa Franco

Throughout human history, epidemics have been a constant presence. Understanding their dynamics is essential to predict scenarios and make substantiated decisions. Mathematical models are powerful tools to describe an epidemic behavior.…

系统与控制 · 电气工程与系统科学 2024-07-26 Walter HMendes aselein , Diego Eckhard

We study a multilayer SIR model with two levels of mixing, namely a global level which is uniformly mixing, and a local level with two layers distinguishing household and workplace contacts, respectively. We establish the large population…

概率论 · 数学 2023-10-27 Madeleine Kubasch

We propose a simple SIR model in order to investigate the impact of various confinement strategies on a most virulent epidemic. Our approach is motivated by the current COVID-19 pandemic. The main hypothesis is the existence of two…

种群与进化 · 定量生物学 2020-12-30 G. Nakamura , B. Grammaticos , M. Badoual

We study the SIR epidemiological model, with a variable contagion rate, applied to the evolution of COVID19 in Cuba. It is highlighted that an increase in the predictive character depends on understanding the dynamics for the temporal…

种群与进化 · 定量生物学 2020-04-24 Nana Cabo Bizet , Alejandro Cabo Montes de Oca

Covid-19 is one of the most dreaded pandemics/epidemics in the world threatening the human population. The dynamics of this pandemic is quite complicated and prediction of pandemic states often fails. In this work, we study and correlate…

种群与进化 · 定量生物学 2021-10-06 Jyoti Bhadana , R. K. Brojen Singh

This paper seeks to study the evolution of the COVID-19 pandemic based on daily published data from Worldometer website, using a time-dependent SIR model. Our findings indicate that this model fits well such data, for different chosen…

种群与进化 · 定量生物学 2023-11-28 Rawan H. Madi , Sophie M. Moufawad , Nabil R. Nassif

Susceptibility governs the dynamics of contagion. The classical SIR model is one of the simplest compartmental models of contagion spread, assuming a single shared susceptibility level. However, variation in susceptibility over a population…

种群与进化 · 定量生物学 2020-09-22 Christopher Rose , Andrew J. Medford , C. Franklin Goldsmith , Tejs Vegge , Joshua Weitz , Andrew A. Peterson

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

Case isolation, that is, detection and isolation of infected individuals in order to prevent spread, is a strategy to curb infectious disease epidemics. Here, we study the efficiency of a case isolation strategy subject to time delays in…

最优化与控制 · 数学 2022-09-20 Jonas Hansson , Alain Govaert , Richard Pates , Emma Tegling , Kristian Soltesz

Attempts to curb the spread of coronavirus by introducing strict quarantine measures apparently have different effect in different countries: while the number of new cases has reportedly decreased in China and South Korea, it still exhibit…

种群与进化 · 定量生物学 2020-03-24 Vitaly Volpert , Malay Banerjee , Sergei Petrovskii

This paper focuses on and analyzes realistic SIR models that take stochasticity into account. The proposed systems are applicable to most incidence rates that are used in the literature including the bilinear incidence rate, the…

概率论 · 数学 2024-07-10 Nguyen Du , Alexandru Hening , Nhu Nguyen , George Yin

The SIR model with spatially inhomogeneous infection rate is studied with numerical simulations in one, two, and three dimensions, considering the case that the infection spreads inhomogeneously in densely populated regions or hot spots. We…

医学物理 · 物理学 2020-12-25 Hidetsugu Sakaguchi , Yuta Nakao
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