Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach

被引：54
|
作者：
Irfan, Muhammad [1 ,2 ]
Razzaq, Asif [3 ,4 ]
Suksatan, Wanich [5 ]
Sharif, Arshian [6 ]
Elavarasan, Rajvikram Madurai [7 ,8 ]
Yang, Chuxiao [1 ,2 ]
Hao, Yu [1 ,2 ,9 ,10 ,11 ]
Rauf, Abdul [12 ]
机构：
[1] Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Ctr Energy & Environm Policy Res, Beijing 100081, Peoples R China
[3] Dalian Univ Technol, Sch Management & Econ, Dalian, Peoples R China
[4] ILMA Univ, Dept Business Adm, Karachi, Pakistan
[5] Chulabhorn Royal Acad, HRH Princess Chulabhorn Coll Med Sci, Bangkok 10210, Thailand
[6] Univ Utara Malaysia, Othman Yeop Abdullah Grad Sch Business, Sintok 06010, Kedah, Malaysia
[7] Thiagarajar Coll Engn, Dept Elect & Elect Engn, Madurai 625015, Tamil Nadu, India
[8] Nestl Pvt Ltd, Res & Dev Div Power & Energy, Chennai 600091, Tamil Nadu, India
[9] Beijing Key Lab Energy Econ & Environm Management, Beijing 100081, Peoples R China
[10] Sustainable Dev Res Inst Econ & Soc Beijing, Beijing 100081, Peoples R China
[11] Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing 100081, Peoples R China
[12] Nanjing Univ Informat Sci & Technol NUIST, Sch Management Sci & Engn, 219 Ningliu Rd, Nanjing, Jiangsu, Peoples R China
来源：
JOURNAL OF THERMAL BIOLOGY | 2022年 / 104卷
基金：
中国国家自然科学基金;
关键词：
Temperature; COVID-19; Transmissibility; Quantile-on-quantile regression; India; CO2; EMISSIONS; MORTALITY; CHINA; NEXUS;
D O I：
10.1016/j.jtherbio.2021.103101
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
The emergence of new coronavirus (SARS-CoV-2) has become a significant public health issue worldwide. Some researchers have identified a positive link between temperature and COVID-19 cases. However, no detailed research has highlighted the impact of temperature on COVID-19 spread in India. This study aims to fill this research gap by investigating the impact of temperature on COVID-19 spread in the five most affected Indian states. Quantile-on-Quantile regression (QQR) approach is employed to examine in what manner the quantiles of temperature influence the quantiles of COVID-19 cases. Empirical results confirm an asymmetric and heterogenous impact of temperature on COVID-19 spread across lower and higher quantiles of both variables. The results indicate a significant positive impact of temperature on COVID-19 spread in the three Indian states (Maharashtra, Andhra Pradesh, and Karnataka), predominantly in both low and high quantiles. Whereas, the other two states (Tamil Nadu and Uttar Pradesh) exhibit a mixed trend, as the lower quantiles in both states have a negative effect. However, this negative effect becomes weak at middle and higher quantiles. These research findings offer valuable policy recommendations.
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页数：10
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