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We introduce a kinetic framework for modeling the time evolution of the statistical distributions of the population densities in the three compartments of susceptible, infectious, and recovered individuals, under epidemic spreading driven…

偏微分方程分析 · 数学 2025-12-16 Giorgio Martalò , Giuseppe Toscani , Mattia Zanella

This paper proposes a novel discrete-time multi-virus SIR (susceptible-infected-recovered) model that captures the spread of competing SIR epidemics over a population network. First, we provide a sufficient condition for the infection level…

系统与控制 · 电气工程与系统科学 2022-04-05 Ciyuan Zhang , Sebin Gracy , Tamer Basar , Philip E. Pare

A network epidemic model is studied. The underlying social network has two different types of group structures, households and workplaces, such that each individual belongs to exactly one household and one workplace. The random network is…

概率论 · 数学 2024-10-10 Frank Ball , Tom Britton , Peter Neal

The paradigm for compartment models in epidemiology assumes exponentially distributed incubation and removal times, which is not realistic in actual populations. Commonly used variations with multiple exponentially distributed variables are…

种群与进化 · 定量生物学 2021-02-10 P. Hernández , C. Pena , A. Ramos , J. J. Gómez-Cadenas

The SIR pandemic model suffers from an unrealistic assumption: The rate of removal from the infectious class of individuals is assumed to be proportional to the number of infectious individuals. This means that a change in the rate of…

种群与进化 · 定量生物学 2021-02-23 Paul A. Reiser

It is generally accepted that scale-free networks is prone to epidemic spreading allowing the onset of large epidemics whatever the spreading rate of the infection. In the paper, we show that disease propagation may be suppressed in…

其他凝聚态物理 · 物理学 2008-03-05 Zhongzhi Zhang , Shuigeng Zhou , Tao Zou , Jihong Guan

We study a discrete Susceptible-Infected-Recovered (SIR) model for the spread of infectious disease on a homogeneous tree and the limit behavior of the model in the case when the tree vertex degree tends to infinity. We obtain the…

概率论 · 数学 2022-07-08 Alexander Gairat , Vadim Shcherbakov

To simplify mathematical models of disease spread, we often assume equal contact rates among hosts, but real-world scenarios differ. Network-based frameworks help capture these complexities and structural variations in actual systems. We…

动力系统 · 数学 2024-07-03 Saswata Das , Mohammad Hossein Samaei , Caterina Scoglio

We use the pair heterogeneous mean-field (PHMF) approximation for an asynchronous version of the susceptible-infected-removed (SIR) model to estimate the epidemic thresholds on complex quenched networks. Our results indicate an improvement…

物理与社会 · 物理学 2024-02-19 D. S. M. Alencar , T. F. A. Alves , F. W. S. Lima , R. S. Ferreira , G. A. Alves , A. Macedo-Filho

It is a longstanding debate on the absence of threshold for susceptible-infected-susceptible (SIS) model on networks with finite second order moment of degree distribution. The eigenvector localization of the adjacency matrix for a network…

物理与社会 · 物理学 2020-05-20 Zong-Wen Wei , Bing-Hong Wang

This brief note highlights a largely overlooked similarity between the SIR ordinary differential equations used for epidemics on the configuration model of a Poisson network and the classical mass-action SIR equations introduced nearly a…

种群与进化 · 定量生物学 2023-10-24 Grzegorz A. Rempala

This paper considers a stochastic SIR (susceptible$\to$infective$\to$removed) epidemic model in which individuals may make infectious contacts in two ways, both within `households' (which for ease of exposition are assumed to have equal…

概率论 · 数学 2015-03-13 Frank Ball , David Sirl , Pieter Trapman

We propose an approach to model spatial heterogeneity in SIR-type models for the spread of epidemics via \emph{nonlocal aggregation terms}. More precisely, we first consider an SIR model with spatial movements driven by nonlocal aggregation…

偏微分方程分析 · 数学 2025-04-03 Marco Di Francesco , Fatemeh Ghaderi Zefreh

This paper examines a susceptible-infected-susceptible (SIS) epidemic reaction-diffusion model with no-flux boundary conditions and constant total population. The infection mechanism in the model is described by a nonlinear term of the form…

偏微分方程分析 · 数学 2024-12-20 Rui Peng , Rachidi B Salako , Yixiang Wu

We study the susceptible-infected-recovered (SIR) epidemic on a random graph chosen uniformly over all graphs with certain critical, heavy-tailed degree distributions. For this model, each vertex infects all its susceptible neighbors and…

概率论 · 数学 2021-05-14 David Clancy

An epidemic model where disease transmission can occur either through global contacts or through local, nearest neighbor interactions is considered. The classical SIR--model describing the global interactions is extended by adding…

种群与进化 · 定量生物学 2022-02-02 Thomas Götz

Compartmental models, especially the Susceptible-Infected-Removed (SIR) model, have long been used to understand the behaviour of various diseases. Allowing parameters, such as the transmission rate, to be time-dependent functions makes it…

统计方法学 · 统计学 2024-09-27 Son Luu , Edward Susko , Lam Si Tung Ho

Modeling epidemic dynamics plays an important role in studying how diseases spread, predicting their future course, and designing strategies to control them. In this letter, we introduce a model of SIR (susceptible-infected-removed) type…

种群与进化 · 定量生物学 2013-12-17 Li Chen , Fakhteh Ghanbarnejad , Weiran Cai , Peter Grassberger

The study of the Ising model from a percolation perspective has played a significant role in the modern theory of critical phenomena. We consider the celebrated square-lattice Ising model and construct percolation clusters by placing bonds,…

统计力学 · 物理学 2025-09-30 Tao Chen , Jinhong Zhu , Wei Zhong , Sheng Fang , Youjin Deng

Here we propose and implement a generalized mathematical model to find the time evolution of population in infectious diseases and apply the model to study the recent COVID-19 pandemic. Our model at the core is a non-local generalization of…

种群与进化 · 定量生物学 2020-05-01 Saumyak Mukherjee , Sayantan Mondal , Biman Bagchi