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Analysis the Dynamics of SIHR Model: Covid-19 Case in Djibouti 被引量:2
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作者 Yahyeh Souleiman Abdoulrazack Mohamed Liban Ismail 《Applied Mathematics》 2021年第10期867-881,共15页
The Covid-19 epidemic is an emerging infectious disease of the viral zoonosis type caused by the coronavirus strain SARS-CoV-2, it is classified as a human-to-human communicable disease and is currently a pandemic wor... The Covid-19 epidemic is an emerging infectious disease of the viral zoonosis type caused by the coronavirus strain SARS-CoV-2, it is classified as a human-to-human communicable disease and is currently a pandemic worldwide. In this paper, we propose conceptual mathematical models of the epidemic dynamics of four compartments. We have collected data from the Djibouti health ministry. We study the positivity, boundedness, existence and uniqueness of the weak solution. Next, we define the Basic reproduction number by the method of the DFE and EEP. Then, we study the local and global stability and the bifurcation analysis of equilibrium to examine its epidemiological relevance. Finally, we analyze the fit of the data in comparison with the result of our mathematical results, to validate the model and estimate the important model parameters and prediction about the disease. We consider the real cases of Djibouti from 15th March to 15th May 2021. 展开更多
关键词 sihr model Covid-19 Basic Reproduction Number Stability Analysis Mod-el Validation
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信息茧房中随机SIHR谣言模型的建立与分析
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作者 王雪芹 徐鑫 田宝单 《纯粹数学与应用数学》 2025年第3期532-546,共15页
考虑谣言传播与传染病传播过程的相似性,本文基于经典的SIR传染病模型,考虑谣言传播中的信息茧房特性与人群遗忘机制,建立了一类随机的SIHR谣言传播模型.首先对确定性模型的基本再生数进行计算,利用李雅普诺夫函数讨论随机模型全局正解... 考虑谣言传播与传染病传播过程的相似性,本文基于经典的SIR传染病模型,考虑谣言传播中的信息茧房特性与人群遗忘机制,建立了一类随机的SIHR谣言传播模型.首先对确定性模型的基本再生数进行计算,利用李雅普诺夫函数讨论随机模型全局正解的存在唯一性,再对系统无病平衡点和正平衡点附近的渐近性质进行了分析与证明,最后通过两个数值例子对前面的理论进行验证. 展开更多
关键词 随机sihr谣言传播模型 信息茧房 基本再生数 渐近性质
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具有Beddington-DeAngelis函数的随机SIHRS模型性质 被引量:1
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作者 王珊 王锋 《数学的实践与认识》 北大核心 2024年第11期172-182,共11页
研究了具有Beddington-DeAngelis函数的随机SIHRS模型,利用分析的方法得到模型不同动力学性质的阈值,也即当Δ<0时,模型将以指数形式趋于灭绝,当Δ> 0时疾病将在均值意义下持续存在.结果表明提高感染群体确诊的比例将有利于疾病... 研究了具有Beddington-DeAngelis函数的随机SIHRS模型,利用分析的方法得到模型不同动力学性质的阈值,也即当Δ<0时,模型将以指数形式趋于灭绝,当Δ> 0时疾病将在均值意义下持续存在.结果表明提高感染群体确诊的比例将有利于疾病的控制.最后列举几个例子和模拟来验证所得结论. 展开更多
关键词 随机sihrS模型 Beddington-DeAngelis函数 灭绝性 持久性
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Optimal control strategy for COVID-19 concerning both life and economy based on deep reinforcement learning
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作者 Wei Deng Guoyuan Qi Xinchen Yu 《Chinese Physics B》 SCIE EI CAS CSCD 2021年第12期28-40,共13页
At present, the global COVID-19 is still severe. More and more countries have experienced second or even third outbreaks. The epidemic is far from over until the vaccine is successfully developed and put on the market... At present, the global COVID-19 is still severe. More and more countries have experienced second or even third outbreaks. The epidemic is far from over until the vaccine is successfully developed and put on the market on a large scale.Inappropriate epidemic control strategies may bring catastrophic consequences. It is essential to maximize the epidemic restraining and to mitigate economic damage. However, the study on the optimal control strategy concerning both sides is rare, and no optimal model has been built. In this paper, the Susceptible-Infectious-Hospitalized-Recovered(SIHR)compartment model is expanded to simulate the epidemic's spread concerning isolation rate. An economic model affected by epidemic isolation measures is established. The effective reproduction number and the eigenvalues at the equilibrium point are introduced as the indicators of controllability and stability of the model and verified the effectiveness of the SIHR model. Based on the Deep Q Network(DQN), one of the deep reinforcement learning(RL) methods, the blocking policy is studied to maximize the economic output under the premise of controlling the number of infections in different stages.The epidemic control strategies given by deep RL under different learning strategies are compared for different reward coefficients. The study demonstrates that optimal policies may differ in various countries depending on disease spread and anti-economic risk ability. The results show that the more economical strategy, the less economic loss in the short term,which can save economically fragile countries from economic crises. In the second or third outbreak stage, the earlier the government adopts the control strategy, the smaller the economic loss. We recommend the method of deep RL to specify a policy which can control the epidemic while making quarantine economically viable. 展开更多
关键词 COVID-19 sihr model deep reinforcement learning DQN secondary outbreak ECONOMY
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