Dataset Information

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

ABSTRACT: 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 matter<2.5 ?m (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.

SUBMITTER: Hendryx M

PROVIDER: S-EPMC7320861 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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

Hendryx Michael M Luo Juhua J

Environmental pollution (Barking, Essex : 1987) 20200627 Pt A

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 Cou ...[more]

PMID: 32806422

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Project description:Background:The novel human coronavirus disease 2019 (COVID-19) pandemic has claimed more than 240,000 lives worldwide, causing tremendous public health, social, and economic damages. While the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis. Methods:We conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010-2016) county-level exposures to NO2, PM2.5 and O3 and county-level COVID-19 case-fatality and mortality rates in the US. We used both single and multipollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level healthcare capacity, phase-of-epidemic, population mobility, sociodemographic, socioeconomic status, behavior risk factors, and meteorological factors. Results:1,027,799 COVID-19 cases and 58,489 deaths were reported in 3,122 US counties from January 22, 2020 to April 29, 2020, with an overall observed case-fatality rate of 5.8%. Spatial variations were observed for both COVID-19 death outcomes and long-term ambient air pollutant levels. County-level average NO2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models (p-values<0.05). Per inter-quartile range (IQR) increase in NO2 (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 7.1% (95% CI 1.2% to 13.4%) and 11.2% (95% CI 3.4% to 19.5%), respectively. We did not observe significant associations between long-term exposures to PM2.5 or O3 and COVID-19 death outcomes (p-values>0.05), although per IQR increase in PM2.5 (3.4 ug/m3) was marginally associated with 10.8% (95% CI: -1.1% to 24.1%) increase in COVID-19 mortality rate. Discussions and Conclusions:Long-term exposure to NO2, which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of long-term PM2.5 and O3 exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO2 levels. Moreover, continuation of current efforts to lower traffic emissions and ambient air pollution levels may be an important component of reducing population-level risk of COVID-19 deaths.

Project description:BackgroundThe novel human coronavirus disease 2019 (COVID-19) pandemic has claimed more than 600,000 lives worldwide, causing tremendous public health, social, and economic damages. Although the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis.MethodsWe conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010-2016) county-level exposures to NO2, PM2.5, and O3 and county-level COVID-19 case-fatality and mortality rates in the United States. We used both single- and multi-pollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level health care capacity, phase of epidemic, population mobility, population density, sociodemographics, socioeconomic status, race and ethnicity, behavioral risk factors, and meteorology.ResultsFrom January 22, 2020, to July 17, 2020, 3,659,828 COVID-19 cases and 138,552 deaths were reported in 3,076 US counties, with an overall observed case-fatality rate of 3.8%. County-level average NO2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models. When adjusted for co-pollutants, per interquartile-range (IQR) increase in NO2 (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 11.3% (95% CI 4.9%-18.2%) and 16.2% (95% CI 8.7%-24.0%), respectively. We did not observe significant associations between COVID-19 case-fatality rate and long-term exposure to PM2.5 or O3, although per IQR increase in PM2.5 (2.6 μg/m3) was marginally associated, with a 14.9% (95% CI 0.0%-31.9%) increase in COVID-19 mortality rate when adjusted for co-pollutants.DiscussionLong-term exposure to NO2, which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of long-term PM2.5 and O3 exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO2 levels. Continuation of current efforts to lower traffic emissions and ambient air pollution may be an important component of reducing population-level risk of COVID-19 case fatality and mortality.

Project description:ImportanceEmerging evidence indicates that exposure to fine particulate matter (PM2.5) air pollution may increase dementia risk in older adults. Although this evidence suggests opportunities for intervention, little is known about the relative importance of PM2.5 from different emission sources.ObjectiveTo examine associations of long-term exposure of total and source-specific PM2.5 with incident dementia in older adults.Design, setting, and participantsThe Environmental Predictors of Cognitive Health and Aging study used biennial survey data from January 1, 1998, to December 31, 2016, for participants in the Health and Retirement Study, which is a nationally representative, population-based cohort study in the US. The present cohort study included all participants older than 50 years who were without dementia at baseline and had available exposure, outcome, and demographic data between 1998 and 2016 (N = 27 857). Analyses were performed from January 31 to May 1, 2022.ExposuresThe 10-year mean total PM2.5 and PM2.5 from 9 emission sources at participant residences for each month during follow-up using spatiotemporal and chemical transport models.Main outcomes and measuresThe main outcome was incident dementia as classified by a validated algorithm incorporating respondent-based cognitive testing and proxy respondent reports. Adjusted hazard ratios (HRs) were estimated for incident dementia per IQR of residential PM2.5 concentrations using time-varying, weighted Cox proportional hazards regression models with adjustment for the individual- and area-level risk factors.ResultsAmong 27 857 participants (mean [SD] age, 61 [10] years; 15 747 [56.5%] female), 4105 (15%) developed dementia during a mean (SD) follow-up of 10.2 [5.6] years. Higher concentrations of total PM2.5 were associated with greater rates of incident dementia (HR, 1.08 per IQR; 95% CI, 1.01-1.17). In single pollutant models, PM2.5 from all sources, except dust, were associated with increased rates of dementia, with the strongest associations for agriculture, traffic, coal combustion, and wildfires. After control for PM2.5 from all other sources and copollutants, only PM2.5 from agriculture (HR, 1.13; 95% CI, 1.01-1.27) and wildfires (HR, 1.05; 95% CI, 1.02-1.08) were robustly associated with greater rates of dementia.Conclusion and relevanceIn this cohort study, higher residential PM2.5 levels, especially from agriculture and wildfires, were associated with higher rates of incident dementia, providing further evidence supporting PM2.5 reduction as a population-based approach to promote healthy cognitive aging. These findings also indicate that intervening on key emission sources might have value, although more research is needed to confirm these findings.

Project description:Stringent pollution control measures are generally applied to improve air quality, especially in the Spring Festival in China. Meanwhile, human activities are reduced significantly due to nationwide lockdown measures to curtail the COVID-19 spreading in 2020. Herein, to better understand the influence of control measures and meteorology on air pollution, this study compared the variation of pollution source and their health risk during the 2019 and 2020 Spring Festival in Linfen, China. Results revealed that the average concentration of PM2.5 in 2020 decreased by 39.0% when compared to the 2019 Spring Festival. Organic carbon (OC) and SO42- were the primary contributor to PM2.5 with the value of 19.5% (21.1%) and 23.5% (25.5%) in 2019 (2020) Spring Festival, respectively. Based on the positive matrix factorization (PMF) model, six pollution sources of PM2.5 were indicated. Vehicle emissions (VE) had the maximum reduction in pollution source concentration (28.39 μg· m-3), followed by dust fall (DF) (11.47 μg· m-3), firework burning (FB) (10.39 μg· m-3), coal combustion (CC) (8.54 μg· m-3), and secondary inorganic aerosol (SIA) (3.95 μg· m-3). However, the apportionment concentration of biomass burning (BB) increased by 78.7%, indicating a significant increase in biomass combustion under control measures. PAHs-lifetime lung cancer risk (ILCR) of VE, CC, FB, BB, and DF, decreased by 44.6%, 43.2%, 34.1%, 21.3%, and 2.0%, respectively. Additionally, the average contribution of meteorological conditions on PM2.5 in 2020 increased by 20.21% compared to 2019 Spring Festival, demonstrating that meteorological conditions played a crucial role in located air pollution. This study revealed that the existing control measures in Linfen were efficient to reduce air pollution and health risk, whereas more BB emissions were worthy of further attention. Furthermore, the result was conducive to developing more effective control measures and putting more attention into unfavorable meteorological conditions in Linfen.

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

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

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