Department of Business Administration, Universität der Bundeswehr München, Neubiberg, Germany.
Department of Computer Science, Swiss Distance University of Applied Sciences, Brig, Switzerland.
PLoS One. 2021 Mar 18;16(3):e0245728. doi: 10.1371/journal.pone.0245728. eCollection 2021.
At the beginning of 2020, the COVID-19 pandemic was able to spread quickly in Wuhan and in the province of Hubei due to a lack of experience with this novel virus. Additionally, authories had no proven experience with applying insufficient medical, communication and crisis management tools. For a considerable period of time, the actual number of people infected was unknown. There were great uncertainties regarding the dynamics and spread of the Covid-19 virus infection. In this paper, we develop a system dynamics model for the three connected regions (Wuhan, Hubei excl. Wuhan, China excl. Hubei) to understand the infection and spread dynamics of the virus and provide a more accurate estimate of the number of infected people in Wuhan and discuss the necessity and effectivity of protective measures against this epidemic, such as the quarantines imposed throughout China. We use the statistics of confirmed cases of China excl. Hubei. Also the daily data on travel activity within China was utilized, in order to determine the actual numerical development of the infected people in Wuhan City and Hubei Province. We used a multivariate Monte Carlo optimization to parameterize the model to match the official statistics. In particular, we used the model to calculate the infections, which had already broken out, but were not diagnosed for various reasons.
2020 年初,由于缺乏对这种新型病毒的经验,COVID-19 疫情能够在武汉和湖北省迅速传播。此外,当局在应用不足的医疗、沟通和危机管理工具方面没有经验。在相当长的一段时间里,实际感染人数未知。新冠病毒感染的动态和传播存在很大的不确定性。在本文中,我们为三个相连的地区(武汉、湖北除武汉、中国除湖北)开发了一个系统动力学模型,以了解病毒的感染和传播动态,并提供对武汉感染人数的更准确估计,并讨论针对这种流行病的保护措施的必要性和有效性,例如在中国实施的隔离措施。我们使用了中国除湖北的确诊病例统计数据。还利用了中国国内每日旅行活动的数据,以确定武汉市和湖北省实际感染人数的发展情况。我们使用多元蒙特卡罗优化来参数化模型,以匹配官方统计数据。特别是,我们使用该模型来计算因各种原因未确诊的已爆发的感染。