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A global association between Covid-19 cases and airborne particulate matter at regional level
Evidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and cli...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7973572/ https://www.ncbi.nlm.nih.gov/pubmed/33737616 http://dx.doi.org/10.1038/s41598-021-85751-z |
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author | Solimini, Angelo Filipponi, F. Fegatelli, D. Alunni Caputo, B. De Marco, C. M. Spagnoli, A. Vestri, A. R. |
author_facet | Solimini, Angelo Filipponi, F. Fegatelli, D. Alunni Caputo, B. De Marco, C. M. Spagnoli, A. Vestri, A. R. |
author_sort | Solimini, Angelo |
collection | PubMed |
description | Evidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM(10), PM(2.5)), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m(3) increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM(2.5) and PM(10) respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19. |
format | Online Article Text |
id | pubmed-7973572 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79735722021-03-19 A global association between Covid-19 cases and airborne particulate matter at regional level Solimini, Angelo Filipponi, F. Fegatelli, D. Alunni Caputo, B. De Marco, C. M. Spagnoli, A. Vestri, A. R. Sci Rep Article Evidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM(10), PM(2.5)), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m(3) increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM(2.5) and PM(10) respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19. Nature Publishing Group UK 2021-03-18 /pmc/articles/PMC7973572/ /pubmed/33737616 http://dx.doi.org/10.1038/s41598-021-85751-z Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Solimini, Angelo Filipponi, F. Fegatelli, D. Alunni Caputo, B. De Marco, C. M. Spagnoli, A. Vestri, A. R. A global association between Covid-19 cases and airborne particulate matter at regional level |
title | A global association between Covid-19 cases and airborne particulate matter at regional level |
title_full | A global association between Covid-19 cases and airborne particulate matter at regional level |
title_fullStr | A global association between Covid-19 cases and airborne particulate matter at regional level |
title_full_unstemmed | A global association between Covid-19 cases and airborne particulate matter at regional level |
title_short | A global association between Covid-19 cases and airborne particulate matter at regional level |
title_sort | global association between covid-19 cases and airborne particulate matter at regional level |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7973572/ https://www.ncbi.nlm.nih.gov/pubmed/33737616 http://dx.doi.org/10.1038/s41598-021-85751-z |
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