Target reproduction numbers for time-delayed population systems

IF 1.9 4区 数学 Q2 BIOLOGY
Xueying Wang , Xiao-Qiang Zhao
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引用次数: 0

Abstract

In the field of population dynamics, target reproduction number is a crucial metric that dictates the necessary control efforts for achieving specific prevention, intervention, or control goals. Recently, the concept of the target reproduction number has undergone significant extensions. Lewis et al. [1] presented a general framework of the target reproduction number for nonnegative matrices, and Wang and Zhao [2] further developed it to positive operators on an ordered Banach space. These extensions encompass fundamental metrics like basic reproduction number and type reproduction number, along with other threshold parameters from existing literature, elucidating their roles in population control. In the current paper, we establish the theory of target reproduction number for a large class of compartmental population models with time delay in the case where control is targeted toward either new infection/production or internal evolution/transition. It turns out that the target reproduction number of the original time-delayed population model can be viewed as a basic reproduction number of some modified system. At the end, we apply these analytic results to three epidemic models, which enhances our theoretical understanding and provides valuable insights for effective strategies in population-based interventions and control measures.
时滞种群系统的目标繁殖数
在种群动力学领域,目标繁殖数是决定实现特定预防、干预或控制目标所需的控制努力的关键指标。近年来,目标再生产数的概念有了显著的扩展。Lewis et al.[1]提出了非负矩阵目标再现数的一般框架,Wang and Zhao[2]进一步将其发展为有序Banach空间上的正算子。这些扩展包括基本繁殖数和类型繁殖数等基本指标,以及现有文献中的其他阈值参数,阐明了它们在人口控制中的作用。本文建立了一类具有时滞的区隔种群模型的目标繁殖数理论,其中控制目标是新感染/生产或内部进化/过渡。结果表明,原时滞种群模型的目标繁殖数可以看作是某一修正系统的基本繁殖数。最后,我们将这些分析结果应用于三种流行病模型,增强了我们的理论认识,并为基于人群的干预和控制措施的有效策略提供了有价值的见解。
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
Mathematical Biosciences 生物-生物学
CiteScore
7.50
自引率
2.30%
发文量
67
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.
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