含无症状感染者的SIR模型和应用
首发时间:2020-03-03
摘要:2019年12月在湖北武汉爆发了一种新型冠状病毒所致的肺炎(COVID-19). 至今已确认有超过30万COVID-19的感染者,波及除南极洲外的6大洲、180余个国家和地区. 建立流行性传染病动力学数学模型为理解流行性传染病的机理,制定和评估防控策略起到了重要作用. COVID-19迅速传播的重要因素之一是存在无症状的新型冠状病毒带毒者. 本文基于易感者-感染者-恢复者(SIR)数学模型提出了一个包括无症状带毒者的4个变量的微分方程模型(NSIR). 得到了NSIR的无病平衡点局部稳定和局部不稳定的判别式; 给出了与无症状带毒者, 感染者,传播速度,治愈率和病亡率等有关的流行病传播判别式. 首先利用北京市新型冠状病毒肺炎疫情的数据, 在一些假设下确定了NSIR在不同时期的参数取值. 数值模拟结果表明北京市5月中旬的COVID -19现有确认感染者的人数将降为0, 病亡人数在7人左右. 其次在假设不采取防控措施(群体免疫group immunity)下,对北京COVID -19疫情的进展进行了模拟.数值模拟结果表明 疫情的峰值约在2月中旬出现.11月上旬的COVID -19现有确认感染者的人数将降为0,病亡人数将高达21.5万人. 接下来在假设采取松散防控措施下,既只完全阻断有症状感染者的感染而不阻断无症状病毒携带者的感染,对北京COVID -19疫情的进展进行了模拟. 数值模拟结果显示至11月上旬疫情仍然不能结束,病亡人数达到近20万人. 这些结果似表明我国采取的全民严格防控COVID-19策略不但是行之有效的而且是完全必要的.简介了黑猩猩急性乙型肝炎病毒(HBV)感染实验与模拟,介绍了人群在受病毒感染后分为4类人群的假说. 建议COVID-19重症监护室进行插管操作的医务人员使用类似防化兵的面部防护设备. 期望本文的研究结果能为更好的认识与掌控流行病的防控提供值得参考的新的理论工具与理念.
关键词: 流行病与卫生统计学 新型冠状病毒 HBV急性感染 疾病传播 数学模型, 北京疫情预测 群体免疫 松散免疫
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An SIR Model Including Asymptomatic Virus Carriers with Application
Abstract: In December, 2019, a novel coronavirus-induced pneumonia (COVID-19) broke out in Wuhan, Hubei. To date, more than 300,000 people infected with COVID-19 have been identified. It affects more than 180 countries and regions on 6 continents except Antarctica. Establishing a mathematical model for epidemic infectious diseases has played an important role in the formulation, evaluation, and prevention of control strategies. One of the important factors for the rapid spread of COVID-19 is the presence of asymptomatic new coronavirus carriers. Based on the mathematical model of susceptible-infected-recoverer (SIR), a 4-variable differential equation model (NSIR) including asymptomatic virus carriers has been set up. The disease-free equilibrium point of NSIR was obtained. The discriminants of local stability and local unstability have been given. It gives discrimination of epidemic spread which related to disease transmission speed, cure rate and mortality rate, number of initial asymptomatic virus carriers, and number of initial infected individuals. Utilizing data from the Beijing New Coronavirus Pneumonia epidemic, first it was determined that the model parameters with different periods. Numerical simulation results show that the number of current infected COVID-19 individuals in Beijing will reduce to zero about mid-April; the death case was about 7 people. Second numerical simulation results estimate that if there were not prevention and control intervening, that is, implement a group immunity strategy, the number of infected COVID-19 individuals in Beijing will reach a peak in the mid-February, the infected cases are about 11.87 millions people. The further simulations show that the Beijing epidemic will end in the begin-November with death cases about 21,5000 people. Further more if implements loose prevention and control strategies, that is, only prevent and control infected individuals but not asymptomatic virus carriers. Then the Beijing epidemic will not end in the begin-November, and death cases will increase to about 20,0000 people. It seems that the whole nation's strict prevention and control strategies implemented in China are not only very effective but also completely necessary. Introduced the experimental and simulation of acute hepatitis B virus (HBV) infection in chimpanzees. It introduces the hypothesis that people are divided into 4 categories after virus infection. It points out the necessity of the current COVID-19 related prevention and control policy of the Chinese government. Medical staff in the intensive care unit of the COVID-19 intensive care unit are recommended to use face protection equipment similar to chemical soldiers. The research results can provide new theoretical tools and idea worthy of reference for better understanding and control of epidemic prevention and control.
Keywords: Epidemic and health statistics; new coronavirus; acute HBV infection; disease transmission; mathematical model; estimation of epidemic risk in Beijingord group immunity group immunity, loose immunity
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