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Air pollution and temperature are associated with increased COVID-19 incidence: A time series study

OBJECTIVES: Although COVID-19 is known to be caused by human-to-human transmission, it remains largely unclear whether ambient air pollutants and meteorological parameters could promote its transmission. METHODS: A retrospective study was conducted to study whether air quality index (AQI), four ambi...

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Autores principales: Li, He, Xu, Xiao-Long, Dai, Da-Wei, Huang, Zhen-Yu, Ma, Zhuang, Guan, Yan-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266595/
https://www.ncbi.nlm.nih.gov/pubmed/32502664
http://dx.doi.org/10.1016/j.ijid.2020.05.076
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author Li, He
Xu, Xiao-Long
Dai, Da-Wei
Huang, Zhen-Yu
Ma, Zhuang
Guan, Yan-Jun
author_facet Li, He
Xu, Xiao-Long
Dai, Da-Wei
Huang, Zhen-Yu
Ma, Zhuang
Guan, Yan-Jun
author_sort Li, He
collection PubMed
description OBJECTIVES: Although COVID-19 is known to be caused by human-to-human transmission, it remains largely unclear whether ambient air pollutants and meteorological parameters could promote its transmission. METHODS: A retrospective study was conducted to study whether air quality index (AQI), four ambient air pollutants (PM(2.5), PM(10), NO(2) and CO) and five meteorological variables (daily temperature, highest temperature, lowest temperature, temperature difference and sunshine duration) could increase COVID-19 incidence in Wuhan and XiaoGan between Jan 26th to Feb 29th in 2020. RESULTS: First, a significant correlation was found between COVID-19 incidence and AQI in both Wuhan (R(2) = 0.13, p < 0.05) and XiaoGan (R(2) = 0.223, p < 0.01). Specifically, among four pollutants, COVID-19 incidence was prominently correlated with PM(2.5) and NO(2) in both cities. In Wuhan, the tightest correlation was observed between NO(2) and COVID-19 incidence (R(2) = 0.329, p < 0.01). In XiaoGan, in addition to the PM(2.5) (R(2) = 0.117, p < 0.01) and NO(2) (R(2) = 0.015, p < 0.05), a notable correlation was also observed between the PM(10) and COVID-19 incidence (R(2) = 0.105, p < 0.05). Moreover, temperature is the only meteorological parameter that constantly correlated well with COVID-19 incidence in both Wuhan and XiaoGan, but in an inverse correlation (p < 0.05). CONCLUSIONS: AQI, PM(2.5), NO(2), and temperature are four variables that could promote the sustained transmission of COVID-19.
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spelling pubmed-72665952020-06-03 Air pollution and temperature are associated with increased COVID-19 incidence: A time series study Li, He Xu, Xiao-Long Dai, Da-Wei Huang, Zhen-Yu Ma, Zhuang Guan, Yan-Jun Int J Infect Dis Article OBJECTIVES: Although COVID-19 is known to be caused by human-to-human transmission, it remains largely unclear whether ambient air pollutants and meteorological parameters could promote its transmission. METHODS: A retrospective study was conducted to study whether air quality index (AQI), four ambient air pollutants (PM(2.5), PM(10), NO(2) and CO) and five meteorological variables (daily temperature, highest temperature, lowest temperature, temperature difference and sunshine duration) could increase COVID-19 incidence in Wuhan and XiaoGan between Jan 26th to Feb 29th in 2020. RESULTS: First, a significant correlation was found between COVID-19 incidence and AQI in both Wuhan (R(2) = 0.13, p < 0.05) and XiaoGan (R(2) = 0.223, p < 0.01). Specifically, among four pollutants, COVID-19 incidence was prominently correlated with PM(2.5) and NO(2) in both cities. In Wuhan, the tightest correlation was observed between NO(2) and COVID-19 incidence (R(2) = 0.329, p < 0.01). In XiaoGan, in addition to the PM(2.5) (R(2) = 0.117, p < 0.01) and NO(2) (R(2) = 0.015, p < 0.05), a notable correlation was also observed between the PM(10) and COVID-19 incidence (R(2) = 0.105, p < 0.05). Moreover, temperature is the only meteorological parameter that constantly correlated well with COVID-19 incidence in both Wuhan and XiaoGan, but in an inverse correlation (p < 0.05). CONCLUSIONS: AQI, PM(2.5), NO(2), and temperature are four variables that could promote the sustained transmission of COVID-19. The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. 2020-08 2020-06-02 /pmc/articles/PMC7266595/ /pubmed/32502664 http://dx.doi.org/10.1016/j.ijid.2020.05.076 Text en © 2020 The Authors 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
Li, He
Xu, Xiao-Long
Dai, Da-Wei
Huang, Zhen-Yu
Ma, Zhuang
Guan, Yan-Jun
Air pollution and temperature are associated with increased COVID-19 incidence: A time series study
title Air pollution and temperature are associated with increased COVID-19 incidence: A time series study
title_full Air pollution and temperature are associated with increased COVID-19 incidence: A time series study
title_fullStr Air pollution and temperature are associated with increased COVID-19 incidence: A time series study
title_full_unstemmed Air pollution and temperature are associated with increased COVID-19 incidence: A time series study
title_short Air pollution and temperature are associated with increased COVID-19 incidence: A time series study
title_sort air pollution and temperature are associated with increased covid-19 incidence: a time series study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266595/
https://www.ncbi.nlm.nih.gov/pubmed/32502664
http://dx.doi.org/10.1016/j.ijid.2020.05.076
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