评估遏制疾病传播的年龄结构疫苗接种策略

IF 2.2 4区 数学 Q2 BIOLOGY Journal of Mathematical Biology Pub Date : 2024-04-15 DOI:10.1007/s00285-024-02085-w
Junyuan Yang, Miao Zhou, Zhaosheng Feng
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摘要

年龄结构是描述异质性流行病传播特征的关键因素之一。疫苗接种被认为是预防和控制流行病的有效控制措施。由于流行病爆发时疫苗接种能力不足,如何设计疫苗接种政策已成为抑制疾病传播的迫切问题。为了更好地理解疾病传播和控制,我们在本文中尝试提出了一个年龄结构的 SVEIHR 模型,该模型考虑了与年龄相关的疫苗接种政策的动态变化,并将疾病引起的死亡纳入其中。我们提出了决定疾病是否持续的基本繁殖数 \(\mathscr {R}_0\)的明确表达式,并在一定条件下建立了流行均衡的存在性和稳定性。通过数值模拟说明了与年龄相关的疫苗接种政策对遏制疾病传播的巨大影响。特别是,在意大利,为 65 岁以上人群接种疫苗比为 21-65 岁人群接种疫苗更有利于快速根除该疾病。
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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Evaluation of age-structured vaccination strategies for curbing the disease spread

Age structure is one of the crucial factors in characterizing the heterogeneous epidemic transmission. Vaccination is regarded as an effective control measure for prevention and control epidemics. Due to the shortage of vaccine capacity during the outbreak of epidemics, how to design vaccination policy has become an urgent issue in suppressing the disease transmission. In this paper, we make an effort to propose an age-structured SVEIHR model with the disease-caused death to take account of dynamics of age-related vaccination policy for better understanding disease spread and control. We present an explicit expression of the basic reproduction number \(\mathscr {R}_0\), which determines whether or not the disease persists, and then establish the existence and stability of endemic equilibria under certain conditions. Numerical simulations are illustrated to show that the age-related vaccination policy has a tremendous influence on curbing the disease transmission. Especially, vaccination of people over 65 is better than for people aged 21–65 in terms of rapid eradication of the disease in Italy.

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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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