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10.1016/j.scitotenv.2020.139115 http://scihub22266oqcxt.onion/10.1016/j.scitotenv.2020.139115 32470687!7194057!32470687     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32470687&cmd=llinks): Failed to open stream: HTTP request failed! 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Asymmetric nexus between temperature and COVID-19 in the top ten affected provinces of China: A current application of quantile-on-quantile approach |pdf=|usr=}}{{32470687}} gab.com Text Asymmetric nexus between temperature and COVID-19 in the top ten affected provinces of China: A current application of quantile-on-quantile approach JO: Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=32470687 #FOAvip 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. Twit Text FOAVip Asymmetric nexus between temperature and COVID-19 in the top ten affected provinces of China: A current application of quantile-on-quantile approach ????Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=32470687 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32470687 #FOAvip English Wikipedia <ref>{{Cite pmid|32470687}}</ref> Asymmetric nexus between temperature and COVID-19 in the top ten affected provinces of China: A current application of quantile-on-quantile approach #MMPMID32470687 Shahzad F; Shahzad U; Fareed Z; Iqbal N; Hashmi SH; Ahmad F Sci Total Environ 2020[Sep]; 736 (ä): 139115 PMID32470687show ga 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. |*Temperature[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Coronavirus Infections/*epidemiology[MESH] |Humans[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology[MESH]Asymmetric nexus between temperature and COVID-19 in the top ten affec(epmc).pdf DeepDyve Pubget Overpricing