A framework for the modelling and the analysis of epidemiological spread in commuting populations

IF 1.9 4区数学 Q2 BIOLOGY

Mathematical Biosciences Pub Date : 2025-02-25 DOI:10.1016/j.mbs.2025.109403

Pierre-Alexandre Bliman , Boureima Sangaré , Assane Savadogo

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引用次数: 0

Abstract

In the present paper, our goal is to establish a framework for the mathematical modelling and the analysis of the spread of an epidemic in a large population commuting regularly, typically along a time-periodic pattern, as is roughly speaking the case in populous urban centre. Our modelling contribution develops along two axes. To model the commuting, we consider a large number of distinct homogeneous groups of individuals of various sizes, called subpopulations, and focus on the modelling of the changing conditions of their mixing along time and of the induced disease transmission. Also, for the purposes of the study, we propose a general class of epidemiological models in which the ‘force of infection’ plays a central role, which extends and unifies several classes previously developed. We take special care in explaining the modelling approach in details, and provide first analytic results that allow to compute or estimate the value of the basic reproduction number for such general periodic epidemic systems.

查看原文本刊更多论文

通勤人群中流行病学传播的建模和分析框架。

在本文中，我们的目标是建立一个数学建模框架，并分析流行病在定期上下班的大量人口中传播的情况，通常是沿着时间周期模式，就像在人口稠密的城市中心一样。我们的建模贡献沿着两个轴发展。为了模拟通勤，我们考虑了大量不同大小的个体同质群体，称为亚种群，并重点模拟了它们随时间混合和诱导疾病传播的变化条件。此外，为了本研究的目的，我们提出了一类流行病学模型，其中“感染力”起着中心作用，它扩展和统一了以前开发的几个类别。我们特别注意详细解释建模方法，并提供分析结果，以便计算或估计这种一般周期性流行病系统的基本再现数的值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mathematical Biosciences 生物-生物学

CiteScore

7.50

自引率

2.30%

发文量

审稿时长

18 days

期刊介绍： Mathematical Biosciences publishes work providing new concepts or new understanding of biological systems using mathematical models, or methodological articles likely to find application to multiple biological systems. Papers are expected to present a major research finding of broad significance for the biological sciences, or mathematical biology. Mathematical Biosciences welcomes original research articles, letters, reviews and perspectives.