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The spread of 2019-nCoV in China was primarily driven by population density. Comment on “Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China” by Zhu et al.
Recently, an article published in the journal Science of the Total Environment and authored by Zhu et al. has claimed the “Association between short-term exposure to air pollution and COVID-19 infection” (doi: https://doi.org/10.1016/j.scitotenv.2020.138704). This note shows that the stated dependen...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365069/ https://www.ncbi.nlm.nih.gov/pubmed/32711328 http://dx.doi.org/10.1016/j.scitotenv.2020.141028 |
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author | Copiello, Sergio Grillenzoni, Carlo |
author_facet | Copiello, Sergio Grillenzoni, Carlo |
author_sort | Copiello, Sergio |
collection | PubMed |
description | Recently, an article published in the journal Science of the Total Environment and authored by Zhu et al. has claimed the “Association between short-term exposure to air pollution and COVID-19 infection” (doi: https://doi.org/10.1016/j.scitotenv.2020.138704). This note shows that the stated dependence between the diffusion of the infection and air pollution may be the result of spurious correlation due to the omission of a common factor, namely, population density. To this end, the relationship between demographic, socio-economic, and environmental conditions and the spread of the novel coronavirus in China is analyzed with spatial regression models on variables deflated by population size. The infection rate - as measured by the number of cases per 100 thousand inhabitants - is found to be strongly related to the population density. At the same time, the association with air pollution is detected with a negative sign, which is difficult to interpret. |
format | Online Article Text |
id | pubmed-7365069 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73650692020-07-17 The spread of 2019-nCoV in China was primarily driven by population density. Comment on “Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China” by Zhu et al. Copiello, Sergio Grillenzoni, Carlo Sci Total Environ Article Recently, an article published in the journal Science of the Total Environment and authored by Zhu et al. has claimed the “Association between short-term exposure to air pollution and COVID-19 infection” (doi: https://doi.org/10.1016/j.scitotenv.2020.138704). This note shows that the stated dependence between the diffusion of the infection and air pollution may be the result of spurious correlation due to the omission of a common factor, namely, population density. To this end, the relationship between demographic, socio-economic, and environmental conditions and the spread of the novel coronavirus in China is analyzed with spatial regression models on variables deflated by population size. The infection rate - as measured by the number of cases per 100 thousand inhabitants - is found to be strongly related to the population density. At the same time, the association with air pollution is detected with a negative sign, which is difficult to interpret. Elsevier B.V. 2020-11-20 2020-07-16 /pmc/articles/PMC7365069/ /pubmed/32711328 http://dx.doi.org/10.1016/j.scitotenv.2020.141028 Text en © 2020 Elsevier B.V. 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 Copiello, Sergio Grillenzoni, Carlo The spread of 2019-nCoV in China was primarily driven by population density. Comment on “Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China” by Zhu et al. |
title | The spread of 2019-nCoV in China was primarily driven by population density. Comment on “Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China” by Zhu et al. |
title_full | The spread of 2019-nCoV in China was primarily driven by population density. Comment on “Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China” by Zhu et al. |
title_fullStr | The spread of 2019-nCoV in China was primarily driven by population density. Comment on “Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China” by Zhu et al. |
title_full_unstemmed | The spread of 2019-nCoV in China was primarily driven by population density. Comment on “Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China” by Zhu et al. |
title_short | The spread of 2019-nCoV in China was primarily driven by population density. Comment on “Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China” by Zhu et al. |
title_sort | spread of 2019-ncov in china was primarily driven by population density. comment on “association between short-term exposure to air pollution and covid-19 infection: evidence from china” by zhu et al. |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365069/ https://www.ncbi.nlm.nih.gov/pubmed/32711328 http://dx.doi.org/10.1016/j.scitotenv.2020.141028 |
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