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Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach
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 stu...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8450230/ https://www.ncbi.nlm.nih.gov/pubmed/35180949 http://dx.doi.org/10.1016/j.jtherbio.2021.103101 |
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author | Irfan, Muhammad Razzaq, Asif Suksatan, Wanich Sharif, Arshian Madurai Elavarasan, Rajvikram Yang, Chuxiao Hao, Yu Rauf, Abdul |
author_facet | Irfan, Muhammad Razzaq, Asif Suksatan, Wanich Sharif, Arshian Madurai Elavarasan, Rajvikram Yang, Chuxiao Hao, Yu Rauf, Abdul |
author_sort | Irfan, Muhammad |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8450230 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84502302021-09-20 Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach Irfan, Muhammad Razzaq, Asif Suksatan, Wanich Sharif, Arshian Madurai Elavarasan, Rajvikram Yang, Chuxiao Hao, Yu Rauf, Abdul J Therm Biol Article 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. Elsevier Ltd. 2022-02 2021-09-20 /pmc/articles/PMC8450230/ /pubmed/35180949 http://dx.doi.org/10.1016/j.jtherbio.2021.103101 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Irfan, Muhammad Razzaq, Asif Suksatan, Wanich Sharif, Arshian Madurai Elavarasan, Rajvikram Yang, Chuxiao Hao, Yu Rauf, Abdul Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach |
title | Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach |
title_full | Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach |
title_fullStr | Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach |
title_full_unstemmed | Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach |
title_short | Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach |
title_sort | asymmetric impact of temperature on covid-19 spread in india: evidence from quantile-on-quantile regression approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8450230/ https://www.ncbi.nlm.nih.gov/pubmed/35180949 http://dx.doi.org/10.1016/j.jtherbio.2021.103101 |
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