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全球卫生安全指数和环境因素如何影响新冠病毒的传播:国家层面分析

How the global health security index and environment factor influence the spread of COVID-19: A country level analysis.

作者信息

Leichtweis Bruno Grespan, de Faria Silva Letícia, da Silva Felipe Lopes, Peternelli Luiz Alexandre

机构信息

Federal University of Viçosa, Department of General Biology, Viçosa, Brazil.

Federal University of Viçosa, Department of Plant Science, Viçosa, Brazil.

出版信息

One Health. 2021 Jun;12:100235. doi: 10.1016/j.onehlt.2021.100235. Epub 2021 Mar 10.

Abstract

The progress of viral diseases such as the new coronavirus (COVID-19) can be influenced not only by social isolation policies, but also by climatic factors. Understanding how these factors affect the progress of the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be essential to know the risks each country is facing because of the disease. In this study, we verified the existence of a relationship between the basic reproduction number (R0) of SARS-CoV-2 with different climate variables, while also considering the Global Health Security Index (GHS). We collected data from confirmed cases of COVID-19 along with their respective GHS notes and climate data, from December 31, 2019 to April 13, 2020, for 52 countries. The generalized additive model (GAM) was applied to explore the effect of temperature, relative humidity, solar radiation index, and GHS score on the spread rate of COVID-19. The countries that showed similarity to each other were grouped into clusters using the Kohonen self-organizing map methodology to investigate the importance of each variable in the dissemination of the disease. The temperature variable presented a linear relationship ( < 0.001) with the R0, with an explained variation of 36.2%, while the relative humidity variable did not present a significant relationship with the R0. The response curve of the solar radiation variable presented a significant nonlinear relationship ( < 0.001) with an explained variation of 32.3%. The GHS index variable, with a significant nonlinear relationship ( < 0.001), presented the largest explanatory response in the control of COVID-19, with an explained variation of 38.4%; further, it was observed that the countries with the largest GHS index scores were less influenced by climate variables.

摘要

诸如新型冠状病毒(COVID-19)等病毒性疾病的进展不仅会受到社会隔离政策的影响,还会受到气候因素的影响。了解这些因素如何影响由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起的大流行的进展,对于了解每个国家因该疾病所面临的风险可能至关重要。在本研究中,我们验证了SARS-CoV-2的基本繁殖数(R0)与不同气候变量之间的关系,同时还考虑了全球卫生安全指数(GHS)。我们收集了2019年12月31日至2020年4月13日期间52个国家的COVID-19确诊病例数据及其各自的GHS评分和气候数据。应用广义相加模型(GAM)来探讨温度、相对湿度、太阳辐射指数和GHS评分对COVID-19传播速度的影响。使用Kohonen自组织映射方法将彼此相似的国家分组为集群,以研究每个变量在疾病传播中的重要性。温度变量与R0呈现线性关系(<0.001),解释变异为36.2%,而相对湿度变量与R0没有显著关系。太阳辐射变量的响应曲线呈现显著的非线性关系(<0.001),解释变异为32.3%。GHS指数变量呈现显著的非线性关系(<0.001),在COVID-19的控制中呈现出最大的解释性响应,解释变异为38.4%;此外,还观察到GHS指数得分最高的国家受气候变量的影响较小。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f16/7970356/8e31709b74db/ga1.jpg

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