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Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis
Various countries across the globe have been affected by different COVID-19 waves at different points in time and with varying levels of virulence. With the backdrop of the two COVID-19 waves that broke out in Delhi, this study examines the variations in the concentrations of criteria pollutants, ai...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8610833/ https://www.ncbi.nlm.nih.gov/pubmed/34841120 http://dx.doi.org/10.1016/j.heliyon.2021.e08468 |
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author | Dutta, Abhishek Dutta, Gautam |
author_facet | Dutta, Abhishek Dutta, Gautam |
author_sort | Dutta, Abhishek |
collection | PubMed |
description | Various countries across the globe have been affected by different COVID-19 waves at different points in time and with varying levels of virulence. With the backdrop of the two COVID-19 waves that broke out in Delhi, this study examines the variations in the concentrations of criteria pollutants, air quality, and meteorological variables across the waves and their influence on COVID-19 morbidity/mortality. Descriptive statistics, violin plots, and Spearman rank correlation tests were employed to assess the variations in environmental parameters and investigate their associations with COVID-19 incidence under the two waves. The susceptible-infected-recovered model and multiple linear regression were used to assess the wave-wise basic reproduction number (R0) and infection spreading trajectory of the virus. Our results show that the first wave in Delhi had three successive peaks and valleys, and the first peak of the second wave was the tallest, indicating the severity of per-day infection cases. During the analysed period (April 2020 and April 2021), concentrations of criteria pollutants varied across the waves, and air pollution was substantially higher during the second wave. In addition, the results revealed that during the second wave, NO(2) maintained a significant negative relationship with COVID-19 (cases per day), while SO(2) had a negative relationship with COVID-19 (cumulative cases) during the first wave. Our results also show a significant positive association of O(3) with COVID-19 deaths during the first wave and cumulative cases and deaths during the second wave. The study indicates that a higher relative humidity in Delhi had a negative relation with COVID-19 cumulative cases and mortality during the first wave. The study confirms that the estimated R0 was marginally different during the two waves, and the spread of COVID-19 new cases followed a cubic growth trajectory. The findings of this study provide valuable information for policymakers in handling COVID-19 waves in various cities. |
format | Online Article Text |
id | pubmed-8610833 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-86108332021-11-24 Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis Dutta, Abhishek Dutta, Gautam Heliyon Research Article Various countries across the globe have been affected by different COVID-19 waves at different points in time and with varying levels of virulence. With the backdrop of the two COVID-19 waves that broke out in Delhi, this study examines the variations in the concentrations of criteria pollutants, air quality, and meteorological variables across the waves and their influence on COVID-19 morbidity/mortality. Descriptive statistics, violin plots, and Spearman rank correlation tests were employed to assess the variations in environmental parameters and investigate their associations with COVID-19 incidence under the two waves. The susceptible-infected-recovered model and multiple linear regression were used to assess the wave-wise basic reproduction number (R0) and infection spreading trajectory of the virus. Our results show that the first wave in Delhi had three successive peaks and valleys, and the first peak of the second wave was the tallest, indicating the severity of per-day infection cases. During the analysed period (April 2020 and April 2021), concentrations of criteria pollutants varied across the waves, and air pollution was substantially higher during the second wave. In addition, the results revealed that during the second wave, NO(2) maintained a significant negative relationship with COVID-19 (cases per day), while SO(2) had a negative relationship with COVID-19 (cumulative cases) during the first wave. Our results also show a significant positive association of O(3) with COVID-19 deaths during the first wave and cumulative cases and deaths during the second wave. The study indicates that a higher relative humidity in Delhi had a negative relation with COVID-19 cumulative cases and mortality during the first wave. The study confirms that the estimated R0 was marginally different during the two waves, and the spread of COVID-19 new cases followed a cubic growth trajectory. The findings of this study provide valuable information for policymakers in handling COVID-19 waves in various cities. Elsevier 2021-11-24 /pmc/articles/PMC8610833/ /pubmed/34841120 http://dx.doi.org/10.1016/j.heliyon.2021.e08468 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Dutta, Abhishek Dutta, Gautam Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis |
title | Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis |
title_full | Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis |
title_fullStr | Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis |
title_full_unstemmed | Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis |
title_short | Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis |
title_sort | association of air pollution and meteorological variables with the two waves of covid-19 pandemic in delhi: a critical analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8610833/ https://www.ncbi.nlm.nih.gov/pubmed/34841120 http://dx.doi.org/10.1016/j.heliyon.2021.e08468 |
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