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Meteorological factors and COVID-19 incidence in 190 countries: An observational study
Novel corona virus disease 2019 (COVID-19), which first emerged in December 2019, has become a pandemic. This study aimed to investigate the associations between meteorological factors and COVID-19 incidence and mortality worldwide. This study included 1,908,197 confirmed cases of and 119,257 deaths...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682932/ https://www.ncbi.nlm.nih.gov/pubmed/33257056 http://dx.doi.org/10.1016/j.scitotenv.2020.143783 |
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author | Guo, Cui Bo, Yacong Lin, Changqing Li, Hao Bi Zeng, Yiqian Zhang, Yumiao Hossain, Md Shakhaoat Chan, Jimmy W.M. Yeung, David W. Kwok, Kin-on Wong, Samuel Y.S. Lau, Alexis K.H. Lao, Xiang Qian |
author_facet | Guo, Cui Bo, Yacong Lin, Changqing Li, Hao Bi Zeng, Yiqian Zhang, Yumiao Hossain, Md Shakhaoat Chan, Jimmy W.M. Yeung, David W. Kwok, Kin-on Wong, Samuel Y.S. Lau, Alexis K.H. Lao, Xiang Qian |
author_sort | Guo, Cui |
collection | PubMed |
description | Novel corona virus disease 2019 (COVID-19), which first emerged in December 2019, has become a pandemic. This study aimed to investigate the associations between meteorological factors and COVID-19 incidence and mortality worldwide. This study included 1,908,197 confirmed cases of and 119,257 deaths from COVID-19 from 190 countries between 23 January and 13 April, 2020. We used a distributed lag non-linear model with city-/country-level random intercept to investigate the associations between COVID19 incidence and daily temperature, relative humidity, and wind speed. A series of confounders were considered in the analysis including demographics, socioeconomics, geographic locations, and political strategies. Sensitivity analyses were performed to examine the robustness of the associations. The COVID-19 incidence showed a stronger association with temperature than with relative humidity or wind speed. An inverse association was identified between the COVID-19 incidence and temperature. The corresponding 14-day cumulative relative risk was 1.28 [95% confidence interval (CI), 1.20–1.36] at 5 °C, and 0.75 (95% CI, 0.65–0.86) at 22 °C with reference to the risk at 11 °C. An inverse J-shaped association was observed between relative humidity and the COVID-19 incidence, with the highest risk at 72%. A higher wind speed was associated with a generally lower incidence of COVID-19, although the associations were weak. Sensitivity analyses generally yielded similar results. The COVID-19 incidence decreased with the increase of temperature. Our study suggests that the spread of COVID-19 may slow during summer but may increase during winter. |
format | Online Article Text |
id | pubmed-7682932 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76829322020-11-24 Meteorological factors and COVID-19 incidence in 190 countries: An observational study Guo, Cui Bo, Yacong Lin, Changqing Li, Hao Bi Zeng, Yiqian Zhang, Yumiao Hossain, Md Shakhaoat Chan, Jimmy W.M. Yeung, David W. Kwok, Kin-on Wong, Samuel Y.S. Lau, Alexis K.H. Lao, Xiang Qian Sci Total Environ Article Novel corona virus disease 2019 (COVID-19), which first emerged in December 2019, has become a pandemic. This study aimed to investigate the associations between meteorological factors and COVID-19 incidence and mortality worldwide. This study included 1,908,197 confirmed cases of and 119,257 deaths from COVID-19 from 190 countries between 23 January and 13 April, 2020. We used a distributed lag non-linear model with city-/country-level random intercept to investigate the associations between COVID19 incidence and daily temperature, relative humidity, and wind speed. A series of confounders were considered in the analysis including demographics, socioeconomics, geographic locations, and political strategies. Sensitivity analyses were performed to examine the robustness of the associations. The COVID-19 incidence showed a stronger association with temperature than with relative humidity or wind speed. An inverse association was identified between the COVID-19 incidence and temperature. The corresponding 14-day cumulative relative risk was 1.28 [95% confidence interval (CI), 1.20–1.36] at 5 °C, and 0.75 (95% CI, 0.65–0.86) at 22 °C with reference to the risk at 11 °C. An inverse J-shaped association was observed between relative humidity and the COVID-19 incidence, with the highest risk at 72%. A higher wind speed was associated with a generally lower incidence of COVID-19, although the associations were weak. Sensitivity analyses generally yielded similar results. The COVID-19 incidence decreased with the increase of temperature. Our study suggests that the spread of COVID-19 may slow during summer but may increase during winter. Elsevier B.V. 2021-02-25 2020-11-23 /pmc/articles/PMC7682932/ /pubmed/33257056 http://dx.doi.org/10.1016/j.scitotenv.2020.143783 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 Guo, Cui Bo, Yacong Lin, Changqing Li, Hao Bi Zeng, Yiqian Zhang, Yumiao Hossain, Md Shakhaoat Chan, Jimmy W.M. Yeung, David W. Kwok, Kin-on Wong, Samuel Y.S. Lau, Alexis K.H. Lao, Xiang Qian Meteorological factors and COVID-19 incidence in 190 countries: An observational study |
title | Meteorological factors and COVID-19 incidence in 190 countries: An observational study |
title_full | Meteorological factors and COVID-19 incidence in 190 countries: An observational study |
title_fullStr | Meteorological factors and COVID-19 incidence in 190 countries: An observational study |
title_full_unstemmed | Meteorological factors and COVID-19 incidence in 190 countries: An observational study |
title_short | Meteorological factors and COVID-19 incidence in 190 countries: An observational study |
title_sort | meteorological factors and covid-19 incidence in 190 countries: an observational study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682932/ https://www.ncbi.nlm.nih.gov/pubmed/33257056 http://dx.doi.org/10.1016/j.scitotenv.2020.143783 |
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