Control Intervention Strategies for Within-Host, Between-Host and their Efficacy in the Treatment, Spread of COVID-19 : A Multi Scale Modeling Approach

Q2 Mathematics
Bhanu Prakash, D. Vamsi, D. Rajesh, C. Sanjeevi
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引用次数: 5

Abstract

Abstract The COVID-19 pandemic has resulted in more than 65.5 million infections and 15,14,695 deaths in 212 countries over the last few months. Different drug intervention acting at multiple stages of pathogenesis of COVID-19 can substantially reduce the infection induced, thereby decreasing the mortality. Also population level control strategies can reduce the spread of the COVID-19 substantially. Motivated by these observations, in this work we propose and study a multi scale model linking both within-host and between-host dynamics of COVID-19. Initially the natural history dealing with the disease dynamics is studied. Later comparative effectiveness is performed to understand the efficacy of both the within-host and population level interventions. Findings of this study suggest that a combined strategy involving treatment with drugs such as Arbidol, remdesivir, Lopinavir/Ritonavir that inhibits viral replication and immunotherapies like monoclonal antibodies, along with environmental hygiene and generalized social distancing proved to be the best and optimal in reducing the basic reproduction number and environmental spread of the virus at the population level.
宿主与宿主之间的控制干预策略及其在治疗和传播新冠肺炎中的疗效:一种多尺度建模方法
过去几个月,COVID-19大流行在212个国家造成6550多万人感染,1514695人死亡。在COVID-19发病的多个阶段进行不同的药物干预,可大大减少感染,从而降低死亡率。人群层面的控制策略也可以大大减少COVID-19的传播。在这些观察结果的推动下,在这项工作中,我们提出并研究了一个连接COVID-19宿主内和宿主间动态的多尺度模型。首先研究了疾病动力学的自然史。随后进行比较有效性,以了解宿主内和人群水平干预的有效性。本研究结果表明,结合使用阿比多尔、瑞德西韦、洛匹那韦/利托那韦等抑制病毒复制的药物和单克隆抗体等免疫疗法,再加上环境卫生和广泛的社会距离,是减少病毒在人群水平上的基本繁殖数量和环境传播的最佳策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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