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COVID-19 prevalence and fatality rates in association with air pollution emission concentrations and emission sources

机译:Covid-19与空气污染排放浓度和排放源相关的流行和死亡率

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摘要

The novel coronavirus disease (COVID-19) is primarily respiratory in nature, and as such, there is interest in examining whether air pollution might contribute to disease susceptibility or outcome. We merged data on COVID-19 cumulative prevalence and fatality rates as of May 31, 2020 with 2014-2019 pollution data from the US Environmental Protection Agency Environmental Justice Screen (EJSCREEN), with control for state testing rates, population density, and population covariate data from the County Health Rankings. Pollution data included three types of air emission concentrations (particulate matter2.5 mm (PM2.5), ozone and diesel particulate matter (DPM)), and four pollution source variables ( proximity to traffic, National Priority List sites, Risk Management Plan (RMP) sites, and hazardous waste treatment, storage and disposal facilities (TSDFs)). Results of mixed model linear multiple regression analyses indicated that, controlling for covariates, COVID-19 prevalence and fatality rates were significantly associated with greater DPM. Proximity to TSDFs was associated to greater fatality rates, and proximity to RMPs was associated with greater prevalence rates. Results are consistent with previous research indicating that air pollution increases susceptibility to respiratory viral pathogens. Results should be interpreted cautiously given the ecological design, the time lag between exposure and outcome, and the uncertainties in measuring COVID-19 prevalence. Areas with worse prior air quality, especially higher concentrations of diesel exhaust, may be at greater COVID-19 risk, although further studies are needed to confirm these relationships. (C) 2020 Elsevier Ltd. All rights reserved.
机译:新型冠状病毒疾病(Covid-19)主要是呼吸道,因此,有兴趣检查空气污染是否可能导致疾病易感性或结果有助于。我们将数据与2014 - 2019年5月31日的Covid-19累积流行和死亡率的数据合并,来自美国环境保护局环境司法屏幕(ejscreen),控制率控制率,人口密度和人口协变量来自县卫生排名的数据。污染数据包括三种类型的空气排放浓度(颗粒物<2.5mm(PM2.5),臭氧和柴油颗粒物(DPM)),以及四种污染源变量(交通障碍,国家优先列表网站,风险管理计划( RMP)网站,危险废物处理,储存和处置设施(TSDFS))。混合模型线性多元回归分析表明,控制协变量,CoVid-19流行和死亡率显着与更大的DPM显着相关。靠近TSDFS与更大的死亡率相关,并且接近RMPS与更高的流行率相关。结果与先前的研究一致,表明空气污染增加对呼吸道病病原菌的易感性。结果应谨慎地解释生态设计,暴露和结果之间的时间滞后,以及测量Covid-19流行的不确定性。较差的现有空气质量,特别是柴油排气浓度较差的区域可能是更大的Covid-19风险,尽管需要进一步研究以确认这些关系。 (c)2020 elestvier有限公司保留所有权利。

著录项

  • 来源
    《Environmental Pollution》 |2020年第1期|115126.1-115126.6|共6页
  • 作者

    Hendryx Michael; Luo Juhua;

  • 作者单位

    Indiana Univ Sch Publ Hlth Dept Environm & Occupat Hlth 1025 E 7th St Bloomington IN 47405 USA;

    Indiana Univ Sch Publ Hlth Dept Epidemiol & Biostat Bloomington IN USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    COVID-19; Air pollution; Hazardous waste sites; Diesel particulate matter;

    机译:covid-19;空气污染;危险废物;柴油颗粒物质;

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