Asymmetric nexus between temperature and COVID-19 in the top ten affected provinces of China: A current application of quantile-on-quantile approach
Asymmetric nexus between temperature and COVID-19 in the top ten affected provinces of China: A current application of quantile-on-quantile approach
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DOI：
10.1016/j.scitotenv.2020.139115
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发表时间：
2020-09-20
影响因子：
9.8
通讯作者：
Ahmad, Fayyaz
中科院分区：
文献类型：
--
作者：
Shahzad, Farrukh;Shahzad, Umer;Ahmad, Fayyaz
本研究探讨2020年1月22日至2020年3月31日期间，中国10个受影响最严重省份的气温对COVID-19（冠状病毒病）的不对称影响。这项研究使用Sim & Zhou的分位数对分位数（QQ）方法来分析温度量如何影响COVID-19的不同分位数。每日COVID-19及温度数据分别自中国国家卫生健康委员会及Weather Underground Company（WUC）的官方网站收集。实证结果表明，湖北、湖南和安徽的气温与COVID-19的关系大多为正，而浙江和山东的气温与COVID-19的关系大多为负。其余五个省份广东、河南、江西、江苏和黑龙江呈现出喜忧参半的趋势。各省之间的这些差异可以通过COVID-19病例数量、温度和该省整体医院设施的差异来解释。该研究得出结论，在COVID-19治疗期间为患者保持安全舒适的氛围可能是合理的。(c)2020爱思唯尔B. V.保留所有权利。
The present study examines the asymmetrical effect of temperature on COVID-19 (Coronavirus Disease) from 22 January 2020 to 31 March 2020 in the 10 most affected provinces in China. This study used the Sim & Zhou' quantile-on-quantile (QQ) approach to analyze how the temperature quantities affect the different quantiles of COVID-19. Daily COVID-19 and, temperature data collected from the official websites of the Chinese National Health Commission and Weather Underground Company (WUC) respectively. Empirical results have shown that the relationship between temperature and COVID-19 is mostly positive for Hubei, Hunan, and Anhui, while mostly negative for Zhejiang and Shandong provinces. The remaining five provinces Guangdong, Henan, Jiangxi, Jiangsu, and Heilongjiang are showing the mixed trends. These differences among the provinces can be explained by the differences in the number of COVID-19 cases, temperature, and the province's overall hospital facilitations. The study concludes that maintaining a safe and comfortable atmosphere for patients while COVID-19 is being treated may be rational. (c) 2020 Elsevier B.V. All rights reserved.