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A general stochastic model for susceptible -> infective -> recovered (SIR) epidemics in non homogeneous populations is considered. The heterogeneity is a very important aspect here since it allows more realistic but also more complex…

种群与进化 · 定量生物学 2020-08-13 Zeynep Gökçe İşlier , Wolfgang Hörmann , Refik Güllü

An important issue in theoretical epidemiology is the epidemic threshold phenomenon, which specify the conditions for an epidemic to grow or die out. In standard (mean-field-like) compartmental models the concept of the basic reproductive…

生物物理 · 物理学 2007-05-23 D. Alves , V. J. Haas , A. Caliri

In this paper, we provide a straightforward approach to defining and deriving the key epidemiological quantity, the basic reproduction number, $R_0$, for Markovian epidemics in structured populations. The methodology derived is applicable…

种群与进化 · 定量生物学 2019-03-26 Peter Neal , Thitiya Theparod

Threshold theorem is probably the most important development of mathematical epidemic modelling. Unfortunately, some models may not behave according to the threshold. In this paper, we will focus on the final outcome of SIR model with…

种群与进化 · 定量生物学 2018-03-06 Kurnia Susvitasari

Accurate epidemic forecasting requires models that account for the layered and heterogeneous nature of real social interactions. The basic reproduction number $\mathcal R_0$ calculated from models that assume homogeneous mixing or…

Studies about epidemic modelling have been conducted since before 19th century. Both deterministic and stochastiic model were used to capture the dynamic of infection in the population. The purpose of this project is to investigate the…

种群与进化 · 定量生物学 2018-03-06 Kurnia Susvitasari

In this paper we consider epidemic models of directly transmissible SIR (susceptible $\to$ infective $\to$ recovered) and SEIR (with an additional latent class) infections in fully-susceptible populations with a social structure, consisting…

种群与进化 · 定量生物学 2015-12-11 Frank Ball , Lorenzo Pellis , Pieter Trapman

In this paper, we consider a compartmental SIRS epidemic model with asymptomatic infection and seasonal succession, which is a periodic discontinuous differential system. The basic reproduction number $\mathcal{R}_0$ is defined and valuated…

动力系统 · 数学 2017-08-15 Yilei Tang , Dongmei Xiao , Weinian Zhang , Di Zhu

The basic reproduction number, $R_0$, is a well-known quantifier of epidemic spread. However, a class of existing methods for estimating $R_0$ from incidence data early in the epidemic can lead to an over-estimation of this quantity. In…

种群与进化 · 定量生物学 2024-03-27 Wajid Ali , Christopher E. Overton , Robert R. Wilkinson , Kieran J. Sharkey

We discuss the criticality in the stochastic SIR model for infectious diseases. We adopt the path-integral formalism for the propagation of infections among susceptible, infectious, and removed individuals, and perform the perturbative and…

种群与进化 · 定量生物学 2022-02-14 Shigehiro Yasui , Yutaka Hatakeyama , Yoshiyasu Okuhara

The SIR model is a three-compartment model of the time development of an epidemic. After normalizing the dependent variables, the model is a system of two non-linear differential equations for the susceptible proportion $S$ and the infected…

动力系统 · 数学 2021-04-27 William G. Faris

In this paper, we study a reaction-diffusion vector-host epidemic model. We define the basic reproduction number $R_0$ and show that $R_0$ is a threshold parameter: if $R_0\le 1$ the disease free steady state is globally stable; if $R_0>1$…

偏微分方程分析 · 数学 2018-12-05 Pierre Magal , G. F. Webb , Yixiang Wu

Stochastic discrete-time SIS and SIR models of endemic diseases are introduced and analyzed. For the deterministic, mean-field model, the basic reproductive number $R_0$ determines their global dynamics. If $R_0\le 1$, then the frequency of…

种群与进化 · 定量生物学 2020-05-19 Sebastian J. Schreiber , Shuo Huang , Jifa Jiang , Hao Wang

The main aim of the work is to present a general class of two time scales discrete-time epidemic models. In the proposed framework the disease dynamics is considered to act on a slower time scale than a second different process that could…

动力系统 · 数学 2024-02-07 Luis Sanz-Lorenzo , Rafael Bravo de la Parra

The present article studies the extension of two deterministic models for describing the novel coronavirus pandemic crisis, the SIR model and the SEIR model. The models were studied and compared to real data in order to support the validity…

物理与社会 · 物理学 2020-06-05 P. H. P. Cintra , M. F. Citeli , F. N. Fontinele

The Susceptible-Infected-Recovered (SIR) model is the cornerstone of epidemiological models. However, this specification depends on two parameters only, which implies a lack of flexibility and the difficulty to replicate the volatile…

种群与进化 · 定量生物学 2020-11-17 Christian Gourieroux , Yang Lu

When an infectious disease strikes a population, the number of newly reported cases is often the only available information that one can obtain during early stages of the outbreak. An important goal of early outbreak analysis is to obtain a…

定量方法 · 定量生物学 2013-05-30 Bahman Davoudi , Babak Pourbohloul , Joel Miller , Rafael Meza , Lauren Ancel Meyers , David J. D. Earn

Our paper presents three new classes of models: SIR-PH, SIR-PH-FA, and SIR-PH-IA, and states two problems we would like to solve about them. Recall that deterministic mathematical epidemiology has one basic general law, the R0 alternative"…

种群与进化 · 定量生物学 2022-05-10 Florin Avram , Rim Adenane , Andrei Halanay

We study the spread of susceptible-infected-recovered (SIR) infectious diseases where an individual's infectiousness and probability of recovery depend on his/her "age" of infection. We focus first on early outbreak stages when stochastic…

种群与进化 · 定量生物学 2009-05-14 Joel Miller , Bahman Davoudi , Rafael Meza , Anja Slim , Babak Pourbohloul

This paper is concerned with stochastic SIR and SEIR epidemic models on random networks in which individuals may rewire away from infected neighbors at some rate $\omega$ (and reconnect to non-infectious individuals with probability…

种群与进化 · 定量生物学 2016-11-15 Tom Britton , David Juher , Joan Saldana
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