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Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China
Coronavirus disease 2019 (COVID-19) was first detected in December 2019 in Wuhan, China, with 11,669,259 positive cases and 539,906 deaths globally as of July 8, 2020. The objective of the present study was to determine whether meteorological parameters and air quality affect the transmission of COV...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406240/ https://www.ncbi.nlm.nih.gov/pubmed/32768746 http://dx.doi.org/10.1016/j.ecoenv.2020.111035 |
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author | Lin, Shaowei Wei, Donghong Sun, Yi Chen, Kun Yang, Le Liu, Bang Huang, Qing Paoliello, Monica Maria Bastos Li, Huangyuan Wu, Siying |
author_facet | Lin, Shaowei Wei, Donghong Sun, Yi Chen, Kun Yang, Le Liu, Bang Huang, Qing Paoliello, Monica Maria Bastos Li, Huangyuan Wu, Siying |
author_sort | Lin, Shaowei |
collection | PubMed |
description | Coronavirus disease 2019 (COVID-19) was first detected in December 2019 in Wuhan, China, with 11,669,259 positive cases and 539,906 deaths globally as of July 8, 2020. The objective of the present study was to determine whether meteorological parameters and air quality affect the transmission of COVID-19, analogous to SARS. We captured data from 29 provinces, including numbers of COVID-19 cases, meteorological parameters, air quality and population flow data, between Jan 21, 2020 and Apr 3, 2020. To evaluate the transmissibility of COVID-19, the basic reproductive ratio (R(0)) was calculated with the maximum likelihood “removal” method, which is based on chain-binomial model, and the association between COVID-19 and air pollutants or meteorological parameters was estimated by correlation analyses. The mean estimated value of R(0) was 1.79 ± 0.31 in 29 provinces, ranging from 1.08 to 2.45. The correlation between R(0) and the mean relative humidity was positive, with coefficient of 0.370. In provinces with high flow, indicators such as carbon monoxide (CO) and 24-h average concentration of carbon monoxide (CO_24 h) were positively correlated with R(0), while nitrogen dioxide (NO(2)), 24-h average concentration of nitrogen dioxide (NO(2)_24 h) and daily maximum temperature were inversely correlated to R(0), with coefficients of 0.644, 0.661, −0.636, −0.657, −0.645, respectively. In provinces with medium flow, only the weather factors were correlated with R(0), including mean/maximum/minimum air pressure and mean wind speed, with coefficients of −0.697, −0.697, −0.697 and −0.841, respectively. There was no correlation with R(0) and meteorological parameters or air pollutants in provinces with low flow. Our findings suggest that higher ambient CO concentration is a risk factor for increased transmissibility of the novel coronavirus, while higher temperature and air pressure, and efficient ventilation reduce its transmissibility. The effect of meteorological parameters and air pollutants varies in different regions, and requires that these issues be considered in future modeling disease transmissibility. |
format | Online Article Text |
id | pubmed-7406240 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74062402020-08-06 Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China Lin, Shaowei Wei, Donghong Sun, Yi Chen, Kun Yang, Le Liu, Bang Huang, Qing Paoliello, Monica Maria Bastos Li, Huangyuan Wu, Siying Ecotoxicol Environ Saf Article Coronavirus disease 2019 (COVID-19) was first detected in December 2019 in Wuhan, China, with 11,669,259 positive cases and 539,906 deaths globally as of July 8, 2020. The objective of the present study was to determine whether meteorological parameters and air quality affect the transmission of COVID-19, analogous to SARS. We captured data from 29 provinces, including numbers of COVID-19 cases, meteorological parameters, air quality and population flow data, between Jan 21, 2020 and Apr 3, 2020. To evaluate the transmissibility of COVID-19, the basic reproductive ratio (R(0)) was calculated with the maximum likelihood “removal” method, which is based on chain-binomial model, and the association between COVID-19 and air pollutants or meteorological parameters was estimated by correlation analyses. The mean estimated value of R(0) was 1.79 ± 0.31 in 29 provinces, ranging from 1.08 to 2.45. The correlation between R(0) and the mean relative humidity was positive, with coefficient of 0.370. In provinces with high flow, indicators such as carbon monoxide (CO) and 24-h average concentration of carbon monoxide (CO_24 h) were positively correlated with R(0), while nitrogen dioxide (NO(2)), 24-h average concentration of nitrogen dioxide (NO(2)_24 h) and daily maximum temperature were inversely correlated to R(0), with coefficients of 0.644, 0.661, −0.636, −0.657, −0.645, respectively. In provinces with medium flow, only the weather factors were correlated with R(0), including mean/maximum/minimum air pressure and mean wind speed, with coefficients of −0.697, −0.697, −0.697 and −0.841, respectively. There was no correlation with R(0) and meteorological parameters or air pollutants in provinces with low flow. Our findings suggest that higher ambient CO concentration is a risk factor for increased transmissibility of the novel coronavirus, while higher temperature and air pressure, and efficient ventilation reduce its transmissibility. The effect of meteorological parameters and air pollutants varies in different regions, and requires that these issues be considered in future modeling disease transmissibility. Elsevier Inc. 2020-11 2020-08-05 /pmc/articles/PMC7406240/ /pubmed/32768746 http://dx.doi.org/10.1016/j.ecoenv.2020.111035 Text en © 2020 Elsevier Inc. 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 Lin, Shaowei Wei, Donghong Sun, Yi Chen, Kun Yang, Le Liu, Bang Huang, Qing Paoliello, Monica Maria Bastos Li, Huangyuan Wu, Siying Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China |
title | Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China |
title_full | Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China |
title_fullStr | Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China |
title_full_unstemmed | Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China |
title_short | Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China |
title_sort | region-specific air pollutants and meteorological parameters influence covid-19: a study from mainland china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406240/ https://www.ncbi.nlm.nih.gov/pubmed/32768746 http://dx.doi.org/10.1016/j.ecoenv.2020.111035 |
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