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传染病传播最优控制的动力学:敏感性分析。

Dynamics of the optimality control of transmission of infectious disease: a sensitivity analysis.

机构信息

Department of Applied Sciences, National Textile University, Faisalabad, 37610, Pakistan.

Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, 602105, India.

出版信息

Sci Rep. 2024 Jan 10;14(1):1041. doi: 10.1038/s41598-024-51540-7.

Abstract

Over the course of history global population has witnessed deterioration of unprecedented scale caused by infectious transmission. The necessity to mitigate the infectious flow requires the launch of a well-directed and inclusive set of efforts. Motivated by the urge for continuous improvement in existing schemes, this article aims at the encapsulation of the dynamics of the spread of infectious diseases. The objectives are served by the launch of the infectious disease model. Moreover, an optimal control strategy is introduced to ensure the incorporation of the most feasible health interventions to reduce the number of infected individuals. The outcomes of the research are facilitated by stratifying the population into five compartments that are susceptible class, acute infected class, chronic infected class, recovered class, and vaccinated class. The optimal control strategy is formulated by incorporating specific control variables namely, awareness about medication, isolation, ventilation, vaccination rates, and quarantine level. The developed model is validated by proving the pivotal delicacies such as positivity, invariant region, reproduction number, stability, and sensitivity analysis. The legitimacy of the proposed model is delineated through the detailed sensitivity analysis along with the documentation of local and global features in a comprehensive manner. The maximum sensitivity index parameters are disease transmission and people moved from acute stages into chronic stages whose value is (0.439, 1) increase in parameter by 10 percent would increase the threshold quantity by (4.39, 1). Under the condition of a stable system, we witnessed an inverse relationship between susceptible class and time. Moreover, to assist the gain of the fundamental aim of this research, we take the control variables as time-dependent and obtain the optimal control strategy to minimize infected populations and to maximize the recovered population, simultaneously. The objectives are attained by the employment of the Pontryagin maximum principle. Furthermore, the efficacy of the usual health interventions such as quarantine, face mask usage, and hand sanitation are also noticed. The effectiveness of the suggested control plan is explained by using numerical evaluation. The advantages of the new strategy are highlighted in the article.

摘要

纵观历史,全球人口见证了由传染病传播引起的前所未有的恶化。减轻传染病流量的必要性需要发起一系列有针对性和包容性的努力。受不断改进现有方案的紧迫性的推动,本文旨在封装传染病传播的动态。目标是通过启动传染病模型来实现。此外,引入了最优控制策略,以确保纳入最可行的卫生干预措施,以减少感染人数。通过将人口分为五个隔室来促进研究结果,这五个隔室分别是易感人群、急性感染人群、慢性感染人群、康复人群和接种疫苗人群。最优控制策略通过合并特定的控制变量来制定,这些变量包括对药物的认识、隔离、通风、接种率和隔离水平。通过证明正定性、不变区域、繁殖数、稳定性和敏感性分析等关键细节,验证了所开发模型的有效性。通过详细的敏感性分析以及全面记录局部和全局特征,来描述所提出模型的合法性。最大敏感性指数参数是疾病传播和从急性阶段转移到慢性阶段的人数,其值为(0.439,1),参数增加 10%将使阈值数量增加(4.39,1)。在系统稳定的情况下,我们观察到易感人群与时间呈反比关系。此外,为了帮助实现本研究的基本目标,我们将控制变量视为时间相关,并获得最优控制策略,以最大限度地减少感染人群并同时最大限度地增加康复人群。目标是通过使用庞特里亚金极大值原理来实现。此外,还注意到了隔离、戴口罩和手部卫生等常用卫生干预措施的效果。通过数值评估解释了建议控制计划的有效性。文章强调了新策略的优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac5a/10781764/b2d3a23f7be0/41598_2024_51540_Fig1_HTML.jpg

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