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关于新冠疫情后改善公共卫生:具有短时记忆效应和高效优化策略的分形分数阶数学解决方案

On improving public health after COVID-19 epidemic: A fractal-fractional mathematical solutions with short memory effect and efficient optimal strategies.

作者信息

Dhar Biplab, Sajid Mohammad

机构信息

Applied Science Cluster-Mathematics, UPES Dehradun, Uttarakhand, India.

Department of Mechanical Engineering, College of Engineering, Qassim University, Buraydah, Saudi Arabia.

出版信息

PLoS One. 2025 May 28;20(5):e0321195. doi: 10.1371/journal.pone.0321195. eCollection 2025.

Abstract

As per the report of W.H.O. about 7 million people died in India till date due to COVID-19 infection. The transmission of COVID-19 infection can affect the temporal and geographic diversity of environmental pollution, thereby disrupting "planetary health" and livelihood. The consensus is that COVID-19 could have significant long-lasting effects on ecosystem and society. It is possible to reach an agreement to create and maintain an ecologically sound environment and a circular bio-economy to try to solve these issues. For the first time, a fractional mathematical model is formulated where the infection is considered due to unhygienic environment with a synergy between mathematical fractal parameters and biology of the disease transmission. Other mathematical analysis such as the boundedness of solutions, the wellposedness of the proposed model concerning existence results, etc. are investigated. Additionally, evaluation of vaccine-clearance equilibrium point is performed. Sensitivity parameters analysis and model's stability also steps in. To get numerical results, the "Adams-Bashforth-Moulton" method with slight modification in the kernel is used. The fractional parameters: memory effect and fractional diffusion shows a good performance of the proposed model in depicting the disease dynamics. Consequences of follow-up optimal control functions in Susceptives and Vaccinated individuals, where feasible strategies in terms of the control maps are presented.

摘要

根据世界卫生组织的报告,截至目前,印度已有约700万人死于新冠病毒感染。新冠病毒感染的传播会影响环境污染的时间和地理多样性,从而扰乱“地球健康”和人们的生计。人们的共识是,新冠病毒可能会对生态系统和社会产生重大的长期影响。达成一项协议,创建并维持一个生态健全的环境和循环生物经济,以试图解决这些问题是有可能的。首次建立了一个分数阶数学模型,该模型认为感染是由不卫生的环境引起的,且数学分形参数与疾病传播生物学之间存在协同作用。还研究了其他数学分析,如解的有界性、所提模型关于存在性结果的适定性等。此外,还对疫苗清除平衡点进行了评估。敏感性参数分析和模型稳定性也在研究范围内。为了得到数值结果,使用了内核略有修改的“亚当斯-巴什福思-莫尔顿”方法。分数阶参数:记忆效应和分数阶扩散表明所提模型在描述疾病动态方面表现良好。提出了在易感人群和接种疫苗人群中后续最优控制函数的结果,并给出了可行的控制策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/98a0/12118899/29aaae7cfd19/pone.0321195.g001.jpg

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