狂犬病在人类和狗中传播动态的参数估计和不确定性评估

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Mfano Charles , Sayoki G. Mfinanga , G.A. Lyakurwa , Delfim F.M. Torres , Verdiana G. Masanja
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引用次数: 0

摘要

狂犬病仍然是一个紧迫的全球公共卫生问题,需要有效的建模和控制策略。这项研究的重点是利用常微分方程 (ODE) 建立一个数学模型,以估计参数并评估与狂犬病在人类和狗中的传播动态有关的不确定性。为确定模型参数并解决不确定性问题,利用新一代矩阵计算基本繁殖数 R0。此外,还使用了部分等级相关系数(Partial Rank Correlation Coefficient)来确定对模型输出结果有重大影响的参数。对平衡状态的分析表明,当 R0<1 时,无狂犬病平衡状态在全局上渐近稳定,而当 R0≥1 时,地方病平衡状态在全局上渐近稳定。 为降低狂犬病的严重程度,并与 2030 年全球狂犬病控制(GRC)倡议保持一致,该研究建议实施针对室内家犬的控制策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameters estimation and uncertainty assessment in the transmission dynamics of rabies in humans and dogs
Rabies remains a pressing global public health issue, demanding effective modeling and control strategies. This study focused on developing a mathematical model using ordinary differential equations (ODEs) to estimate parameters and assess uncertainties related to the transmission dynamics of rabies in humans and dogs. To determine model parameters and address uncertainties, next-generation matrices were utilized to calculate the basic reproduction number R0. Furthermore, the Partial Rank Correlation Coefficient was used to identify parameters that significantly influence model outputs. The analysis of equilibrium states revealed that the rabies-free equilibrium is globally asymptotically stable when R0<1, whereas the endemic equilibrium is globally asymptotically stable when R01. To reduce the severity of rabies and align with the Global Rabies Control (GRC) initiative by 2030, the study recommends implementing control strategies targeting indoor domestic dogs.
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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