COVID-19 in Moscow: prognoses and scenarios

M. Tamm
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引用次数: 22

Abstract

Aim:to present a mathematical model of the development of COVID-19 in Moscow along with the analysis of some scenarios of epidemic control and possible epidemic consequences.Materials and Methods.The modeling of the epidemics was based on the extended SEIR model proposed lately in the group of Prof. R. Neher and realized as a freely available software program. The authors based the choice of the parameters of modeling on published data on the epidemiological properties of the novel coronavirus SARS-CoV-2 and open access data on the registered cases of COVID-19 in Moscow for 8-27 March 2020.Results.Five potential scenarios of the development of COVID-19 epidemics are studied. The scenarios are differed by the levels of the control measures: Null Scenario corresponded to the lack of protective measures, Scenario A – mild measures of the epidemic control (closing of schools and universities, recommendations for senior citizens to stay inside), Scenario B – medium level of control (closing of all public places, recommendation for the citizens to stay inside), Scenarios C and D – complete lockdown (from the beginning of May 2020 within Scenario C and from the beginning of April 2020 within Scenario D). It was shown that within the Null Scenario, the lethality from the novel coronavirus in Moscow will exceed 100 thousand people, and the number of critically ill patients on the peak of the epidemics will exceed the capacities of the system of healthcare. Scenarios A and B did not provide for a radical decrease in the fatality rate, and the number of critically ill patients at the peak of epidemics will still exceed the capacities of the system of healthcare. Besides, within Scenario B, the epidemics will last for more than a year. Scenarios C and D will allow for the control of epidemics and a significant decrease in the rate of letha lity (by 30 and 400 times, respectively). At the same time, these two scenarios prevent the population from developing herd immunity, which would result in the population susceptibility to repeated epidemics outbreaks.Conclusion. The scenarios intended for the slow development of herd immunity in the conditions of epidemic control would not bring sufficient results: the lethality would remain unacceptably high, the capacities of the system of healthcare would be overloaded, and the time of limiting measures would be unacceptably long. Such measures as complete lockdown would stop the present epidemics. The earlier they are introduced, the more efficient will be the results. To prevent further repeated outbreaks of the epidemics, it is necessary to establish a system of available, quick, and efficient testing in combination with point isolation of the infected patients and their contacts. 
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2019冠状病毒病在莫斯科:预测和情景
目的:建立莫斯科新型冠状病毒肺炎疫情发展的数学模型,并分析疫情控制的一些情景和可能的疫情后果。材料与方法。流行病的建模是基于R. Neher教授小组最近提出的扩展SEIR模型,并作为一个免费的软件程序实现的。作者根据已发表的新型冠状病毒SARS-CoV-2流行病学特性数据和莫斯科2020年3月8日至27日COVID-19登记病例的开放获取数据选择建模参数。研究了新冠肺炎疫情发展的五种可能情景。这些情况因控制措施的程度而异:零情景对应于缺乏防护措施,情景A -温和的疫情控制措施(关闭学校和大学,建议老年人留在室内),情景B -中等控制水平(关闭所有公共场所,建议公民留在室内),情景C和D——完全封锁(情景C从2020年5月初开始,情景D从2020年4月初开始)。研究表明,在零情景下,莫斯科新型冠状病毒的致死人数将超过10万人,疫情高峰期的危重患者人数将超过医疗系统的能力。情景A和情景B并没有规定死亡率会急剧下降,而且在流行病高峰期,危重病人的人数仍将超过卫生保健系统的能力。此外,在情景B中,流行病将持续一年以上。方案C和D将使流行病得到控制,并使死亡率显著降低(分别降低30倍和400倍)。同时,这两种情况使人群无法产生群体免疫,从而导致人群对反复暴发的流行病易感性。在流行病得到控制的情况下,群体免疫力发展缓慢的设想不会带来足够的结果:死亡率仍将高得令人无法接受,保健系统的能力将超负荷,采取限制措施的时间将长得令人无法接受。完全封锁等措施将阻止目前的流行病。越早引入它们,结果就越有效。为防止疫情再次暴发,有必要建立一套可用、快速和有效的检测系统,并对受感染患者及其接触者进行点隔离。
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