一种优化COVID - 19可用控制措施的数学模型

IF 3.1 3区 环境科学与生态学 Q2 ECOLOGY Ecological Complexity Pub Date : 2021-03-01 DOI:10.1016/j.ecocom.2021.100930
Isa Abdullahi Baba , Bashir Ahmad Nasidi , Dumitru Baleanu , Sultan Hamed Saadi
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引用次数: 4

摘要

在缺乏治疗大流行冠状病毒(COVID-19)感染的有效药物或疫苗的情况下,其他控制策略如;隔离、保持社交距离、自我隔离、卫生和使用个人防护装备是预防和遏制疾病传播的有效手段。在本文中,我们提出了一个数学模型来研究COVID-19的动态。然后,我们制定了一个最优控制问题,目的是研究最有效的控制策略,以防止疾病的扩散。建立了最优控制函数的存在性,并应用庞特里亚金极大值原理对控制器进行表征。平衡解(DFE &发现地方性)是局部渐近稳定的,然后得到基本繁殖数。数值模拟支持了分析结果,并明确显示了控制的意义。结果表明,隔离感染者是目前最好的控制措施。
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A mathematical model to optimize the available control measures of COVID – 19

In the absence of valid medicine or vaccine for treating the pandemic Coronavirus (COVID-19) infection, other control strategies like; quarantine, social distancing, self- isolation, sanitation and use of personal protective equipment are effective tool used to prevent and curtail the spread of the disease. In this paper, we present a mathematical model to study the dynamics of COVID-19. We then formulate an optimal control problem with the aim to study the most effective control strategies to prevent the proliferation of the disease. The existence of an optimal control function is established and the Pontryagin maximum principle is applied for the characterization of the controller. The equilibrium solutions (DFE & endemic) are found to be locally asymptotically stable and subsequently the basic reproduction number is obtained. Numerical simulations are carried out to support the analytic results and to explicitly show the significance of the control. It is shown that Quarantine/isolating those infected with the disease is the best control measure at the moment.

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来源期刊
Ecological Complexity
Ecological Complexity 环境科学-生态学
CiteScore
7.10
自引率
0.00%
发文量
24
审稿时长
3 months
期刊介绍: Ecological Complexity is an international journal devoted to the publication of high quality, peer-reviewed articles on all aspects of biocomplexity in the environment, theoretical ecology, and special issues on topics of current interest. The scope of the journal is wide and interdisciplinary with an integrated and quantitative approach. The journal particularly encourages submission of papers that integrate natural and social processes at appropriately broad spatio-temporal scales. Ecological Complexity will publish research into the following areas: • All aspects of biocomplexity in the environment and theoretical ecology • Ecosystems and biospheres as complex adaptive systems • Self-organization of spatially extended ecosystems • Emergent properties and structures of complex ecosystems • Ecological pattern formation in space and time • The role of biophysical constraints and evolutionary attractors on species assemblages • Ecological scaling (scale invariance, scale covariance and across scale dynamics), allometry, and hierarchy theory • Ecological topology and networks • Studies towards an ecology of complex systems • Complex systems approaches for the study of dynamic human-environment interactions • Using knowledge of nonlinear phenomena to better guide policy development for adaptation strategies and mitigation to environmental change • New tools and methods for studying ecological complexity
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