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Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan
Information on the spatiotemporal variability of respirable suspended particulate pollutant matter concentrations, especially of particles having size of 2.5 μm and climate are the important factors in relation to emerging COVID-19 cases around the world. This study aims at examining the association...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797023/ https://www.ncbi.nlm.nih.gov/pubmed/33482526 http://dx.doi.org/10.1016/j.chemosphere.2021.129584 |
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author | Mehmood, Khalid Bao, Yansong Abrar, Muhammad Mohsin Petropoulos, George P. Saifullah Soban, Ahmad Saud, Shah Khan, Zalan Alam Khan, Shah Masud Fahad, Shah |
author_facet | Mehmood, Khalid Bao, Yansong Abrar, Muhammad Mohsin Petropoulos, George P. Saifullah Soban, Ahmad Saud, Shah Khan, Zalan Alam Khan, Shah Masud Fahad, Shah |
author_sort | Mehmood, Khalid |
collection | PubMed |
description | Information on the spatiotemporal variability of respirable suspended particulate pollutant matter concentrations, especially of particles having size of 2.5 μm and climate are the important factors in relation to emerging COVID-19 cases around the world. This study aims at examining the association between COVID-19 cases, air pollution, climatic and socioeconomic factors using geospatial techniques in three provincial capital cities and the federal capital city of Pakistan. A series of relevant data was acquired from 3 out of 4 provinces of Pakistan (Punjab, Sindh, Khyber Pakhtunkhwa (KPK) including the daily numbers of COVID-19 cases, PM(2.5) concentration (μgm(−3)), a climatic factors including temperature (°F), wind speed (m/s), humidity (%), dew point (%), and pressure (Hg) from June 1 2020, to July 31 2020. Further, the possible relationships between population density and COVID-19 cases was determined. The generalized linear model (GLM) was employed to quantify the effect of PM(2.5), temperature, dew point, humidity, wind speed, and pressure range on the daily COVID-19 cases. The grey relational analysis (GRA) was also implemented to examine the changes in COVID-19 cases with PM(2.5) concentrations for the provincial city Lahore. About 1,92, 819 COVID-19 cases were reported in Punjab, Sindh, KPK, and Islamabad during the study period. Results indicated a significant relationship between COVID-19 cases and PM(2.5) and climatic factors at p < 0.05 except for Lahore in case of humidity (r = 0.175). However, mixed correlations existed across Lahore, Karachi, Peshawar, and Islamabad. The R(2) value indicates a moderate relationship between COVID-19 and population density. Findings of this study, although are preliminary, offers the first line of evidence for epidemiologists and may assist the local community to expedient for the growth of effective COVID-19 infection and health risk management guidelines. This remains to be seen. |
format | Online Article Text |
id | pubmed-7797023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77970232021-01-11 Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan Mehmood, Khalid Bao, Yansong Abrar, Muhammad Mohsin Petropoulos, George P. Saifullah Soban, Ahmad Saud, Shah Khan, Zalan Alam Khan, Shah Masud Fahad, Shah Chemosphere Article Information on the spatiotemporal variability of respirable suspended particulate pollutant matter concentrations, especially of particles having size of 2.5 μm and climate are the important factors in relation to emerging COVID-19 cases around the world. This study aims at examining the association between COVID-19 cases, air pollution, climatic and socioeconomic factors using geospatial techniques in three provincial capital cities and the federal capital city of Pakistan. A series of relevant data was acquired from 3 out of 4 provinces of Pakistan (Punjab, Sindh, Khyber Pakhtunkhwa (KPK) including the daily numbers of COVID-19 cases, PM(2.5) concentration (μgm(−3)), a climatic factors including temperature (°F), wind speed (m/s), humidity (%), dew point (%), and pressure (Hg) from June 1 2020, to July 31 2020. Further, the possible relationships between population density and COVID-19 cases was determined. The generalized linear model (GLM) was employed to quantify the effect of PM(2.5), temperature, dew point, humidity, wind speed, and pressure range on the daily COVID-19 cases. The grey relational analysis (GRA) was also implemented to examine the changes in COVID-19 cases with PM(2.5) concentrations for the provincial city Lahore. About 1,92, 819 COVID-19 cases were reported in Punjab, Sindh, KPK, and Islamabad during the study period. Results indicated a significant relationship between COVID-19 cases and PM(2.5) and climatic factors at p < 0.05 except for Lahore in case of humidity (r = 0.175). However, mixed correlations existed across Lahore, Karachi, Peshawar, and Islamabad. The R(2) value indicates a moderate relationship between COVID-19 and population density. Findings of this study, although are preliminary, offers the first line of evidence for epidemiologists and may assist the local community to expedient for the growth of effective COVID-19 infection and health risk management guidelines. This remains to be seen. Elsevier Ltd. 2021-05 2021-01-10 /pmc/articles/PMC7797023/ /pubmed/33482526 http://dx.doi.org/10.1016/j.chemosphere.2021.129584 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 Mehmood, Khalid Bao, Yansong Abrar, Muhammad Mohsin Petropoulos, George P. Saifullah Soban, Ahmad Saud, Shah Khan, Zalan Alam Khan, Shah Masud Fahad, Shah Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan |
title | Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan |
title_full | Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan |
title_fullStr | Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan |
title_full_unstemmed | Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan |
title_short | Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan |
title_sort | spatiotemporal variability of covid-19 pandemic in relation to air pollution, climate and socioeconomic factors in pakistan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797023/ https://www.ncbi.nlm.nih.gov/pubmed/33482526 http://dx.doi.org/10.1016/j.chemosphere.2021.129584 |
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