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新冠疫情的数学视角:确定性和随机模型中的疾病灭绝标准。

Mathematical perspective of Covid-19 pandemic: Disease extinction criteria in deterministic and stochastic models.

作者信息

Adak Debadatta, Majumder Abhijit, Bairagi Nandadulal

机构信息

Department of Applied Mathematics, Maharaja Bir Bikram University, Agartala, Tripura, 799004, India.

Centre for Mathematical Biology and Ecology, Department of Mathematics, Jadavpur University, Kolkata 700032, India.

出版信息

Chaos Solitons Fractals. 2021 Jan;142:110381. doi: 10.1016/j.chaos.2020.110381. Epub 2020 Oct 20.

Abstract

The world has been facing the biggest virological invasion in the form of Covid-19 pandemic since the beginning of the year 2020. In this paper, we consider a deterministic epidemic model of four compartments based on the health status of the populations of a given country to capture the disease progression. A stochastic extension of the deterministic model is further considered to capture the uncertainty or variation observed in the disease transmissibility. In the case of a deterministic system, the disease-free equilibrium will be globally asymptotically stable if the basic reproduction number is less than unity, otherwise, the disease persists. Using Lyapunov functional methods, we prove that the infected population of the stochastic system tends to zero exponentially almost surely if the basic reproduction number is less than unity. The stochastic system has no interior equilibrium, however, its asymptotic solution is shown to fluctuate around the endemic equilibrium of the deterministic system under some parametric restrictions, implying that the infection persists. A case study with the Covid-19 epidemic data of Spain is presented and various analytical results have been demonstrated. The epidemic curve in Spain clearly shows two waves of infection. The first wave was observed during March-April and the second wave started in the middle of July and not completed yet. A real-time reproduction number has been given to illustrate the epidemiological status of Spain throughout the study period. Estimated cumulative numbers of confirmed and death cases are 1,613,626 and 42,899, respectively, with case fatality rate 2.66% till the deadly virus is eliminated from Spain.

摘要

自2020年初以来,世界一直面临着以新冠疫情大流行形式出现的最大规模病毒入侵。在本文中,我们基于给定国家人口的健康状况,考虑一个四分区确定性流行病模型,以描述疾病的发展过程。进一步考虑确定性模型的随机扩展,以捕捉疾病传播中观察到的不确定性或变化。在确定性系统的情况下,如果基本再生数小于1,则无病平衡点将是全局渐近稳定的,否则,疾病将持续存在。使用李雅普诺夫泛函方法,我们证明如果基本再生数小于1,则随机系统的感染人群几乎肯定会指数趋于零。随机系统没有内部平衡点,然而,在一些参数限制下,其渐近解被证明会围绕确定性系统的地方病平衡点波动,这意味着感染会持续存在。给出了一个使用西班牙新冠疫情数据的案例研究,并展示了各种分析结果。西班牙的疫情曲线清楚地显示出两波感染。第一波感染在3月至4月期间出现,第二波于7月中旬开始且尚未结束。给出了实时再生数,以说明整个研究期间西班牙的流行病学状况。截至从西班牙消除这种致命病毒时,估计的确诊病例和死亡病例累计数分别为1,613,626例和42,899例,病死率为2.66%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b44/7574710/e1d0ac0ec806/gr1_lrg.jpg

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