Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China
Lin, Shaowei1; Wei, Donghong1,2; Sun, Yi1; Chen, Kun1; Yang, Le1; Liu, Bang1; Huang, Qing1; Wu, Siying1; Bastos Paoliello, Monica Maria3,4; Li, Huangyuan1
2020-07
发表期刊ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
ISSN0147-6513
EISSN1090-2414
摘要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 Ro 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 Ro, while nitrogen dioxide (NO2), 24-h average concentration of nitrogen dioxide (NO2_24 h) and daily maximum temperature were inversely correlated to Ro, 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.
关键词COVID-19 Basic reproductive ratio Meteorological parameter Air pollutant
DOI10.1016/j.ecoenv.2020.111035
WOS关键词AMBIENT CARBON-MONOXIDE ; DAILY MORTALITY ; POLLUTION ; OUTBREAK ; DISEASE ; SARS
WOS研究方向Environmental Sciences & Ecology ; Toxicology
WOS类目Environmental Sciences ; Toxicology
出版者ACADEMIC PRESS INC ELSEVIER SCIENCE
引用统计
文献类型期刊论文
专题新冠肺炎
循证社会科学证据集成
作者单位1.Fujian Med Univ;
2.Quanzhou Med Coll;
3.Albert Einstein Coll Med;
4.Univ Estadual Londrina
推荐引用方式
GB/T 7714
Lin, Shaowei,Wei, Donghong,Sun, Yi,et al. Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China[J]. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY,2020.
APA Lin, Shaowei.,Wei, Donghong.,Sun, Yi.,Chen, Kun.,Yang, Le.,...&Li, Huangyuan.(2020).Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China.ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY.
MLA Lin, Shaowei,et al."Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China".ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY (2020).
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Region-specific air (2228KB)期刊论文出版稿开放获取CC BY-NC-SA浏览 下载
个性服务
查看访问统计
谷歌学术
谷歌学术中相似的文章
[Lin, Shaowei]的文章
[Wei, Donghong]的文章
[Sun, Yi]的文章
百度学术
百度学术中相似的文章
[Lin, Shaowei]的文章
[Wei, Donghong]的文章
[Sun, Yi]的文章
必应学术
必应学术中相似的文章
[Lin, Shaowei]的文章
[Wei, Donghong]的文章
[Sun, Yi]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Region-specific air pollutants and meteorological parameters influence COVID-19 A study from mainland China.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。

元出版是什么?

元出版是融合预印本出版、数据出版、结构化信息出版等当前开放出版实践与理念为一体的开放出版新模式,旨在提供一个科学工作者完全融入的泛在沉浸式开放知识交流机制。

MetaPub团队

  • 关于我们
  • 编委会
  • 审稿专家
  • 编辑部

开放研究

  • 学科领域
  • 入驻期刊
  • 入驻会议
  • 开放数据集

帮助

  • 元作品投稿流程
  • 元作品写作要求
  • 元作品出版声明
  • 元作品出版标准
  • 审稿注意事项
地址:四川天府新区群贤南街289号 邮编:610299 电子邮箱:liucj@clas.ac.cn
版权所有 蜀ICP备05003827号