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相关论文: Non-Markovian SIR epidemic spreading model

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In this paper, we present a model to predict the spread of the Covid-19 epidemic and apply it to the specific case of Italy. We started from a simple Susceptible, Infected, Recovered (SIR) model and we added the condition that, after a…

The purpose of this work is to give a contribution to the understanding of the COVID-19 contagion in Italy. To this end, we developed a modified Susceptible-Infected-Recovered (SIR) model for the contagion, and we used official data of the…

物理与社会 · 物理学 2020-04-01 Giuseppe C. Calafiore , Carlo Novara , Corrado Possieri

The growing literature on the propagation of COVID-19 relies on various dynamic SIR-type models (Susceptible-Infected-Recovered) which yield model-dependent results. For transparency and ease of comparing the results, we introduce a common…

种群与进化 · 定量生物学 2020-06-19 Christian Gourieroux , Joann Jasiak

We study a simple realistic model for describing the diffusion of an infectious disease on a population of individuals. The dynamics is governed by a single functional delay differential equation, which, in the case of a large population,…

种群与进化 · 定量生物学 2020-09-28 Luca Dell'Anna

Waiting times between two consecutive infection and recovery events in spreading processes are often assumed to be exponentially distributed, which results in Markovian (i.e., memoryless) continuous spreading dynamics. However, this is not…

物理与社会 · 物理学 2020-07-27 Lucas Böttcher , Nino Antulov-Fantulin

We propose a stochastic SIR model, specified as a system of stochastic differential equations, to analyse the data of the Italian COVID-19 epidemic, taking also into account the under-detection of infected and recovered individuals in the…

种群与进化 · 定量生物学 2021-02-22 Sara Pasquali , Antonio Pievatolo , Antonella Bodini , Fabrizio Ruggeri

We examine the age-structured SIR model, a variant of the classical Susceptible-Infected-Recovered (SIR) model of epidemic propagation, in the context of COVID-19. In doing so, we provide a theoretical basis for the model, perform an…

最优化与控制 · 数学 2022-03-11 Rohit Parasnis , Ryosuke Kato , Amol Sakhale , Massimo Franceschetti , Behrouz Touri

We present the generalised mean-field and pairwise models for non-Markovian epidemics on networks with arbitrary recovery time distributions. First we consider a hyperbolic system, where the population of infective nodes and links are…

动力系统 · 数学 2016-05-11 G. Röst , Z. Vizi , I. Z. Kiss

In this paper, a susceptible-infected-removed (SIR) model has been used to track the evolution of the spread of the COVID-19 virus in four countries of interest. In particular, the epidemic model, that depends on some basic characteristics,…

种群与进化 · 定量生物学 2020-10-28 Ian Cooper , Argha Mondal , Chris G. Antonopoulos

Although viral spreading processes taking place in networks are often analyzed using Markovian models in which both the transmission and the recovery times follow exponential distributions, empirical studies show that, in many real…

社会与信息网络 · 计算机科学 2019-03-19 Masaki Ogura , Victor M. Preciado

There is increasing evidence that one of the most difficult problems in trying to control the ongoing COVID-19 epidemic is the presence of a large cohort of asymptomatic infectives. We develop a SIR-type model taking into account the…

种群与进化 · 定量生物学 2020-06-29 Giuseppe Gaeta

In this work, the SIR epidemiological model is reformulated so to highlight the important {\em effective reproduction number}, as well as to account for the {\em generation time}, inverse of the {\em incidence rate}, and the {\em infectious…

种群与进化 · 定量生物学 2021-07-27 Ignazio Lazzizzera

In this paper, we study the effectiveness of the modelling approach on the pandemic due to the spreading of the novel COVID-19 disease and develop a susceptible-infected-removed (SIR) model that provides a theoretical framework to…

种群与进化 · 定量生物学 2020-08-26 Ian Cooper , Argha Mondal , Chris G. Antonopoulos

The Markovian approach, which assumes exponentially distributed interinfection times, is dominant in epidemic modeling. However, this assumption is unrealistic as an individual's infectiousness depends on its viral load and varies over…

种群与进化 · 定量生物学 2023-08-02 Qihui Yang , Joan Saldaña , Caterina Scoglio

Initially emerged in the Chinese city Wuhan and subsequently spread almost worldwide causing a pandemic, the SARS-CoV-2 virus follows reasonably well the SIR (Susceptible-Infectious-Recovered) epidemic model on contact networks in the…

物理与社会 · 物理学 2020-10-28 Clara Pizzuti , Annalisa Socievole , Bastian Prasse , Piet Van Mieghem

In the light of several major epidemic events that emerged in the past two decades, and emphasized by the COVID-19 pandemics, the non-Markovian spreading models occurring on complex networks gained significant attention from the scientific…

物理与社会 · 物理学 2021-11-30 Igor Tomovski , Lasko Basnarkov , Alajdin Abazi

An epidemic disease caused by a new coronavirus has spread in Northern Italy with a strong contagion rate. We implement an SEIR model to compute the infected population and number of casualties of this epidemic. The example may ideally…

种群与进化 · 定量生物学 2020-05-12 Jose' M. Carcione , Juan E. Santos , Claudio Bagaini , Jing Ba

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

In this note, we describe simple generalizations of the basic SIR model for epidemic, in case of a multi-region scenario, to be used for predicting the COVID-19 epidemic spread in Italy.

种群与进化 · 定量生物学 2020-05-14 Luigi Brugnano , Felice Iavernaro

The rapidly spreading Covid-19 that affected almost all countries, was first reported at the end of 2019. As a consequence of its highly infectious nature, countries all over the world have imposed extremely strict measures to control its…

种群与进化 · 定量生物学 2020-07-13 Semra Ahmetolan , Ayse Humeyra Bilge , Ali Demirci , Ayse Peker-Dobie , Onder Ergonul
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