利用 SVEAIQHR 模型建立 COVID-19 动态数学模型

Q2 Mathematics
Ambalarajan Venkatesh, M. A. Rao, Murugadoss Prakash Raj, Karuppusamy Arun Kumar, D. Vamsi
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引用次数: 0

摘要

在本研究中,我们建立了一个八室数学模型,以疫苗接种为其中一室,分析 COVID-19 的传播动态。我们研究了该模型的定性特性,如解的正相关性和有界性,以及无病平衡对基本繁殖数的稳定性分析。我们估算了十个重要参数,并通过对印度每日确诊病例和累计确诊 COVID-19 病例进行拟合,计算出印度基本繁殖数的大小。我们对基本繁殖数进行了敏感性分析,并确定了影响疾病流行的主要参数。我们将四种非药物和药物干预措施作为控制函数,进一步将该模型扩展为优化控制问题。数值结果表明,四种控制策略比三种控制策略、两种控制策略和单一控制策略对降低 COVID-19 传播动态的影响更大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mathematical modelling of COVID-19 dynamics using SVEAIQHR model
In this study, we formulate an eight-compartment mathematical model with vaccination as one of the compartments to analyze the dynamics of COVID-19 transmission. We examine the model’s qualitative properties, such as positivity and boundedness of solutions, and stability analysis of the illness-free equilibrium with respect to the basic reproduction number. We estimate ten significant parameters and also compute the magnitude of the basic reproduction number for India by fitting the proposed model to daily confirmed and cumulative confirmed COVID-19 cases in India. Sensitivity analysis with respect to basic reproduction number is conducted, and the main parameters that impact the widespread of disease are determined. We further extend this model to an optimal control problem by including four non-pharmaceutical and pharmaceutical intervention measures as control functions. Our numerical results show that the four control strategy has greater impact than the three control strategies, two control strategies, and single control strategies on reducing the dynamics of COVID-19 transmission.
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来源期刊
Computational and Mathematical Biophysics
Computational and Mathematical Biophysics Mathematics-Mathematical Physics
CiteScore
2.50
自引率
0.00%
发文量
8
审稿时长
30 weeks
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