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冠状病毒的流行病学、遗传学、疫苗及 2019 年冠状病毒病(COVID-19)大流行的现状:模糊集方法。

Epidemiology of coronaviruses, genetics, vaccines, and scenario of current pandemic of coronavirus diseases 2019 (COVID-19): a fuzzy set approach.

机构信息

Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China.

International College, University of Chinese Academy of Sciences, Beijing, China.

出版信息

Hum Vaccin Immunother. 2021 May 4;17(5):1296-1303. doi: 10.1080/21645515.2020.1798697. Epub 2021 Mar 15.

Abstract

Human coronaviruses (HCoVs) are associated with a range of respiratory complications. In the last two decades, three major outbreaks have been reported due to HCoVs including the current pandemic. In December 2019, a newly emerged virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Wuhan city, China. This paper presents a detailed review of the literature and discusses the uncertain spread of coronavirus disease 2019 (COVID-19) using fuzzy set as classical set theory logic to measure uncertainty and vagueness of COVID-19 in China. Our findings show that both infection and death rate touched the peak (normal fuzzy sets) and have shown a decline. The graphs are not convex, which shows that there remains much uncertainty in the spread of COVID-19. Effective vaccines are clearly needed to control and prevent the COVID-19 pandemic.

摘要

人冠状病毒(HCoVs)与一系列呼吸道并发症有关。在过去的二十年中,由于 HCoVs 导致了三次重大疫情爆发,包括目前的大流行。2019 年 12 月,一种新型病毒——严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)在中国武汉市首次报告。本文对文献进行了详细综述,并使用模糊集作为经典集合论逻辑,讨论了新型冠状病毒肺炎(COVID-19)在中国的传播不确定性。我们的研究结果表明,感染率和死亡率均达到峰值(正态模糊集),并呈下降趋势。图形不是凸的,这表明 COVID-19 的传播仍存在很大的不确定性。显然需要有效的疫苗来控制和预防 COVID-19 大流行。

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