Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach. (February 2022)

• Record Type: Journal Article
• Authors: Irfan, Muhammad; Razzaq, Asif; Suksatan, Wanich; Sharif, Arshian; Madurai Elavarasan, Rajvikram; Yang, Chuxiao; Hao, Yu; Rauf, Abdul
• Is Part Of: Journal of thermal biology. Volume 104(2022)
• Publication Date: 2022-02
• Subjects: Temperature -- COVID-19 -- Transmissibility -- Quantile-on-quantile regression -- India; Thermobiology -- Periodicals; Temperature -- Periodicals; Biology -- Periodicals; Thermobiologie -- Périodiques; Thermobiology; Periodicals; 571.46
• DOI: 10.1016/j.jtherbio.2021.103101
• Languages: English
• ISSNs: 0306-4565

Abstract

Abstract: 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. Graphical abstract: Image 1 Highlights: Examined the impact of temperature on COVID-19 spread in India. The QQR approach is used for data analysis purposes. A positive impact is found for Maharashtra, Andhra Pradesh and Karnataka states. Tamil Nadu and Uttar Pradesh states showed mixed trend. These results may have useful policy implications to control COVID-19 spread.