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SARS-CoV-2与寨卡病毒共感染模型中的反向分岔与最优控制

Backward bifurcation and optimal control in a co-infection model for SARS-CoV-2 and ZIKV.

作者信息

Omame Andrew, Abbas Mujahid, Onyenegecha Chibueze P

机构信息

Department of Mathematics, Federal University of Technology, Owerri, Nigeria.

Abdus Salam School of Mathematical Sciences, Government College University Katchery Road, Lahore 54000, Pakistan.

出版信息

Results Phys. 2022 Jun;37:105481. doi: 10.1016/j.rinp.2022.105481. Epub 2022 Apr 9.

Abstract

In co-infection models for two diseases, it is mostly claimed that, the dynamical behavior of the sub-models usually predict or drive the behavior of the complete models. However, under a certain assumption such as, allowing incident co-infection with both diseases, we have a different observation. In this paper, a new mathematical model for SARS-CoV-2 and Zika co-dynamics is presented which incorporates incident co-infection by susceptible individuals. It is worth mentioning that the assumption is missing in many existing co-infection models. We shall discuss the impact of this assumption on the dynamics of a co-infection model. The model also captures sexual transmission of Zika virus. The positivity and boundedness of solution of the proposed model are studied, in addition to the local asymptotic stability analysis. The model is shown to exhibit backward bifurcation caused by the disease-induced death rates and parameters associated with susceptibility to a second infection by those singly infected. Using Lyapunov functions, the disease free and endemic equilibria are shown to be globally asymptotically stable for , respectively. To manage the co-circulation of both infections effectively, under an endemic setting, time dependent controls in the form of SARS-CoV-2, Zika and co-infection prevention strategies are incorporated into the model. The simulations show that SARS-CoV-2 prevention could greatly reduce the burden of co-infections with Zika. Furthermore, it is also shown that prevention controls for Zika can significantly decrease the burden of co-infections with SARS-CoV-2.

摘要

在两种疾病的合并感染模型中,大多观点认为,子模型的动力学行为通常能预测或驱动完整模型的行为。然而,在诸如允许个体同时感染两种疾病的特定假设下,我们有了不同的观察结果。本文提出了一种新的SARS-CoV-2与寨卡病毒共同动力学数学模型,该模型纳入了易感个体的同时感染情况。值得一提的是,许多现有的合并感染模型中缺少这一假设。我们将讨论这一假设对合并感染模型动力学的影响。该模型还考虑了寨卡病毒的性传播。除了进行局部渐近稳定性分析外,还研究了所提模型解的正性和有界性。结果表明,该模型会因疾病诱导死亡率以及与单次感染者二次感染易感性相关的参数而出现向后分岔。利用李雅普诺夫函数,分别证明了无病平衡点和地方病平衡点在 时是全局渐近稳定的。为了在地方病流行情况下有效管理两种感染的共同传播,将以SARS-CoV-2、寨卡病毒及合并感染预防策略形式呈现的与时间相关的控制措施纳入模型。模拟结果表明,预防SARS-CoV-2可大幅减轻与寨卡病毒合并感染的负担。此外,研究还表明,预防寨卡病毒的控制措施可显著降低与SARS-CoV-2合并感染的负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e62d/8994284/4d65d600b88a/gr1_lrg.jpg

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