分析COVID-19大流行传播行为、封锁影响和传染性的可靠性方法

A. Puls, S. Bracke
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引用次数: 0

摘要

2021年,2019冠状病毒病大流行继续挑战全球化的世界。对公共生活的限制和不同特点的封锁定义了许多国家的生活。本文以2019冠状病毒病大流行的第一年(01-28-2020至01-15-2021)为重点。作为可靠性工程中分析感染发生的方法的转移,本文采用威布尔分布模型来评估COVID-19的传播行为。本研究的重点问题是大流行第一阶段和第二阶段传播行为的差异以及不同特征(硬、轻)的封锁措施的不同影响。因此,以代表欧洲传播行为的德国为例,详细分析了在有和没有封锁措施的规范时间段内感染的发生情况。应用参数易于解释的威布尔分布模型,生成了与SIR模型等经典感染分析模型相比的附加信息,并概述了COVID-19的动态发展。进一步,将COVID-19感染的发生与德国其他常见传染病(如流感或诺如病毒)联系起来,评估其传染性。与这些众所周知的传染病相比,2019冠状病毒病在不同大流行阶段的传播行为存在差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RELIABILITY METHODS FOR ANALYZING COVID-19 PANDEMIC SPREADING BEHAVIOR, LOCKDOWN IMPACT AND INFECTIOUSNESS
In 2021, the COVID-19 pandemic continues to challenge the globalized world. Restrictions on the public life and lockdowns of different characteristics define the life in many countries. This paper focuses on the first year of the COVID-19 pandemic (01-28-2020 to 01-15-2021). As a transfer of methods used in reliability engineering for analyzing occurrence of infection, Weibull distribution models are used to evaluate the spreading behavior of COVID-19. Key issues of this study are the differences of spreading behavior in first and second pandemic phase and the various impacts of lockdown measures with different characteristics (hard, light). Therefore, the occurrence of infection in normed time periods with and without lockdown measures are analyzed in detail on the example of Germany representing the spreading behavior in Europe. Additional information in comparison to classical infection analyzes models like SIR model is generated by the application of Weibull distribution models with easy interpretable parameters and the dynamic development of COVID-19 is outlined. In a further step, the occurrence of infection of COVID-19 is put into the context of other common infectious diseases in Germany like Influenza or Norovirus to evaluate the infectiousness. Differences in spreading behavior of COVID-19 in comparison to these well-known infectious diseases are underlined for different pandemic phases.
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