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Association between meteorological indicators and COVID-19 pandemic in Pakistan
This study was designed to investigate the impact of meteorological indicators (temperature, rainfall, and humidity) on total COVID-19 cases in Pakistan, its provinces, and administrative units from March 10, 2020, to August 25, 2020. The correlation analysis showed that COVID-19 cases and temperatu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7556579/ https://www.ncbi.nlm.nih.gov/pubmed/33052566 http://dx.doi.org/10.1007/s11356-020-11203-2 |
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author | Raza, Ali Khan, Muhammad Tariq Iqbal Ali, Qamar Hussain, Tanveer Narjis, Saadia |
author_facet | Raza, Ali Khan, Muhammad Tariq Iqbal Ali, Qamar Hussain, Tanveer Narjis, Saadia |
author_sort | Raza, Ali |
collection | PubMed |
description | This study was designed to investigate the impact of meteorological indicators (temperature, rainfall, and humidity) on total COVID-19 cases in Pakistan, its provinces, and administrative units from March 10, 2020, to August 25, 2020. The correlation analysis showed that COVID-19 cases and temperature showed a positive correlation. It implies that the increase in COVID-19 cases was reported due to an increase in the temperature in Pakistan, its provinces, and administrative units. The generalized Poisson regression showed that the rise in the expected log count of COVID-19 cases was 0.024 times for a 1 °C rise in the average temperature in Pakistan. Second, the correlation between rainfall and COVID-19 cases was negative in Pakistan. However, the regression coefficient between the expected log count of COVID-19 cases and rainfall was insignificant in Pakistan. Third, the correlation between humidity and the total COVID-19 cases was negative, which implies that the increase in humidity is beneficial to stop the transmission of COVID-19 in Pakistan, its provinces, and administrative units. The reduction in the expected log count of COVID-19 cases was 0.008 times for a 1% increase in the humidity per day in Pakistan. However, humidity and COVID-19 cases were positively correlated in Sindh province. It is required to create awareness among the general population, and the government should include the causes, symptoms, and precautions in the educational syllabus. Moreover, people should adopt the habit of hand wash, social distancing, personal hygiene, mask-wearing, and the use of hand sanitizers to control the COVID-19. |
format | Online Article Text |
id | pubmed-7556579 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-75565792020-10-15 Association between meteorological indicators and COVID-19 pandemic in Pakistan Raza, Ali Khan, Muhammad Tariq Iqbal Ali, Qamar Hussain, Tanveer Narjis, Saadia Environ Sci Pollut Res Int Environmental Factors and the Epidemics of COVID-19 This study was designed to investigate the impact of meteorological indicators (temperature, rainfall, and humidity) on total COVID-19 cases in Pakistan, its provinces, and administrative units from March 10, 2020, to August 25, 2020. The correlation analysis showed that COVID-19 cases and temperature showed a positive correlation. It implies that the increase in COVID-19 cases was reported due to an increase in the temperature in Pakistan, its provinces, and administrative units. The generalized Poisson regression showed that the rise in the expected log count of COVID-19 cases was 0.024 times for a 1 °C rise in the average temperature in Pakistan. Second, the correlation between rainfall and COVID-19 cases was negative in Pakistan. However, the regression coefficient between the expected log count of COVID-19 cases and rainfall was insignificant in Pakistan. Third, the correlation between humidity and the total COVID-19 cases was negative, which implies that the increase in humidity is beneficial to stop the transmission of COVID-19 in Pakistan, its provinces, and administrative units. The reduction in the expected log count of COVID-19 cases was 0.008 times for a 1% increase in the humidity per day in Pakistan. However, humidity and COVID-19 cases were positively correlated in Sindh province. It is required to create awareness among the general population, and the government should include the causes, symptoms, and precautions in the educational syllabus. Moreover, people should adopt the habit of hand wash, social distancing, personal hygiene, mask-wearing, and the use of hand sanitizers to control the COVID-19. Springer Berlin Heidelberg 2020-10-14 2021 /pmc/articles/PMC7556579/ /pubmed/33052566 http://dx.doi.org/10.1007/s11356-020-11203-2 Text en © Springer-Verlag GmbH Germany, part of Springer Nature 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Environmental Factors and the Epidemics of COVID-19 Raza, Ali Khan, Muhammad Tariq Iqbal Ali, Qamar Hussain, Tanveer Narjis, Saadia Association between meteorological indicators and COVID-19 pandemic in Pakistan |
title | Association between meteorological indicators and COVID-19 pandemic in Pakistan |
title_full | Association between meteorological indicators and COVID-19 pandemic in Pakistan |
title_fullStr | Association between meteorological indicators and COVID-19 pandemic in Pakistan |
title_full_unstemmed | Association between meteorological indicators and COVID-19 pandemic in Pakistan |
title_short | Association between meteorological indicators and COVID-19 pandemic in Pakistan |
title_sort | association between meteorological indicators and covid-19 pandemic in pakistan |
topic | Environmental Factors and the Epidemics of COVID-19 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7556579/ https://www.ncbi.nlm.nih.gov/pubmed/33052566 http://dx.doi.org/10.1007/s11356-020-11203-2 |
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