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Impacts of transportation and meteorological factors on the transmission of COVID-19
The ongoing pandemic of 2019 novel coronavirus disease (COVID-19) is challenging global public health response system. We aim to identify the risk factors for the transmission of COVID-19 using data on mainland China. We estimated attack rate (AR) at county level. Logistic regression was used to exp...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier GmbH.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7448770/ https://www.ncbi.nlm.nih.gov/pubmed/32896785 http://dx.doi.org/10.1016/j.ijheh.2020.113610 |
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author | Wei, Jia-Te Liu, Yun-Xia Zhu, Yu-Chen Qian, Jie Ye, Run-Ze Li, Chun-Yu Ji, Xiao-Kang Li, Hong-Kai Qi, Chang Wang, Ying Yang, Fan Zhou, Yu-Hao Yan, Ran Cui, Xiao-Ming Liu, Yuan-Li Jia, Na Li, Shi-Xue Li, Xiu-Jun Xue, Fu-Zhong Zhao, Lin Cao, Wu-Chun |
author_facet | Wei, Jia-Te Liu, Yun-Xia Zhu, Yu-Chen Qian, Jie Ye, Run-Ze Li, Chun-Yu Ji, Xiao-Kang Li, Hong-Kai Qi, Chang Wang, Ying Yang, Fan Zhou, Yu-Hao Yan, Ran Cui, Xiao-Ming Liu, Yuan-Li Jia, Na Li, Shi-Xue Li, Xiu-Jun Xue, Fu-Zhong Zhao, Lin Cao, Wu-Chun |
author_sort | Wei, Jia-Te |
collection | PubMed |
description | The ongoing pandemic of 2019 novel coronavirus disease (COVID-19) is challenging global public health response system. We aim to identify the risk factors for the transmission of COVID-19 using data on mainland China. We estimated attack rate (AR) at county level. Logistic regression was used to explore the role of transportation in the nationwide spread. Generalized additive model and stratified linear mixed-effects model were developed to identify the effects of multiple meteorological factors on local transmission. The ARs in affected counties ranged from 0.6 to 9750.4 per million persons, with a median of 8.8. The counties being intersected by railways, freeways, national highways or having airports had significantly higher risk for COVID-19 with adjusted odds ratios (ORs) of 1.40 (p = 0.001), 2.07 (p < 0.001), 1.31 (p = 0.04), and 1.70 (p < 0.001), respectively. The higher AR of COVID-19 was significantly associated with lower average temperature, moderate cumulative precipitation and higher wind speed. Significant pairwise interactions were found among above three meteorological factors with higher risk of COVID-19 under low temperature and moderate precipitation. Warm areas can also be in higher risk of the disease with the increasing wind speed. In conclusion, transportation and meteorological factors may play important roles in the transmission of COVID-19 in mainland China, and could be integrated in consideration by public health alarm systems to better prevent the disease. |
format | Online Article Text |
id | pubmed-7448770 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier GmbH. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74487702020-08-27 Impacts of transportation and meteorological factors on the transmission of COVID-19 Wei, Jia-Te Liu, Yun-Xia Zhu, Yu-Chen Qian, Jie Ye, Run-Ze Li, Chun-Yu Ji, Xiao-Kang Li, Hong-Kai Qi, Chang Wang, Ying Yang, Fan Zhou, Yu-Hao Yan, Ran Cui, Xiao-Ming Liu, Yuan-Li Jia, Na Li, Shi-Xue Li, Xiu-Jun Xue, Fu-Zhong Zhao, Lin Cao, Wu-Chun Int J Hyg Environ Health Article The ongoing pandemic of 2019 novel coronavirus disease (COVID-19) is challenging global public health response system. We aim to identify the risk factors for the transmission of COVID-19 using data on mainland China. We estimated attack rate (AR) at county level. Logistic regression was used to explore the role of transportation in the nationwide spread. Generalized additive model and stratified linear mixed-effects model were developed to identify the effects of multiple meteorological factors on local transmission. The ARs in affected counties ranged from 0.6 to 9750.4 per million persons, with a median of 8.8. The counties being intersected by railways, freeways, national highways or having airports had significantly higher risk for COVID-19 with adjusted odds ratios (ORs) of 1.40 (p = 0.001), 2.07 (p < 0.001), 1.31 (p = 0.04), and 1.70 (p < 0.001), respectively. The higher AR of COVID-19 was significantly associated with lower average temperature, moderate cumulative precipitation and higher wind speed. Significant pairwise interactions were found among above three meteorological factors with higher risk of COVID-19 under low temperature and moderate precipitation. Warm areas can also be in higher risk of the disease with the increasing wind speed. In conclusion, transportation and meteorological factors may play important roles in the transmission of COVID-19 in mainland China, and could be integrated in consideration by public health alarm systems to better prevent the disease. Elsevier GmbH. 2020-09 2020-08-26 /pmc/articles/PMC7448770/ /pubmed/32896785 http://dx.doi.org/10.1016/j.ijheh.2020.113610 Text en © 2020 Elsevier GmbH. 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 Wei, Jia-Te Liu, Yun-Xia Zhu, Yu-Chen Qian, Jie Ye, Run-Ze Li, Chun-Yu Ji, Xiao-Kang Li, Hong-Kai Qi, Chang Wang, Ying Yang, Fan Zhou, Yu-Hao Yan, Ran Cui, Xiao-Ming Liu, Yuan-Li Jia, Na Li, Shi-Xue Li, Xiu-Jun Xue, Fu-Zhong Zhao, Lin Cao, Wu-Chun Impacts of transportation and meteorological factors on the transmission of COVID-19 |
title | Impacts of transportation and meteorological factors on the transmission of COVID-19 |
title_full | Impacts of transportation and meteorological factors on the transmission of COVID-19 |
title_fullStr | Impacts of transportation and meteorological factors on the transmission of COVID-19 |
title_full_unstemmed | Impacts of transportation and meteorological factors on the transmission of COVID-19 |
title_short | Impacts of transportation and meteorological factors on the transmission of COVID-19 |
title_sort | impacts of transportation and meteorological factors on the transmission of covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7448770/ https://www.ncbi.nlm.nih.gov/pubmed/32896785 http://dx.doi.org/10.1016/j.ijheh.2020.113610 |
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