scholarly journals Long-term exposure to air-pollution and COVID-19 mortality in England: a hierarchical spatial analysis

2020 ◽  
Author(s):  
Garyfallos Konstantinoudis ◽  
Tullia Padellini ◽  
James E Bennett ◽  
Bethan Davies ◽  
Majid Ezzati ◽  
...  
Keyword(s):  
Air Pollution ◽  
Spatial Autocorrelation ◽  
Environmental Protection Agency ◽  
Lower Layer ◽  
Credible Interval ◽  
Ecological Design ◽  
Bayesian Hierarchical ◽  
Small Areas ◽  
Confounding Adjustment

Background: Recent studies suggested a link between long-term exposure to air-pollution and COVID-19 mortality. However, due to their ecological design, based on large spatial units, they neglect the strong localised air-pollution patterns, and potentially lead to inadequate confounding adjustment. We investigated the effect of long-term exposure to NO2 and PM2.5 on COVID-19 deaths up to June 30, 2020 in England using high geographical resolution. Methods: We included 38 573 COVID-19 deaths up to June 30, 2020 at the Lower Layer Super Output Area level in England (n=32 844 small areas). We retrieved averaged NO2 and PM2.5 concentration during 2014-2018 from the Pollution Climate Mapping. We used Bayesian hierarchical models to quantify the effect of air-pollution while adjusting for a series of confounding and spatial autocorrelation. Findings: We find a 0.5% (95% credible interval: -0.2%-1.2%) and 1.4% (-2.1%-5.1%) increase in COVID-19 mortality rate for every 1μg/m3 increase in NO2 and PM2.5 respectively, after adjusting for confounding and spatial autocorrelation. This corresponds to a posterior probability of a positive effect of 0.93 and 0.78 respectively. The spatial relative risk at LSOA level revealed strong patterns, similar for the different pollutants. This potentially captures the spread of the disease during the first wave of the epidemic. Interpretation: Our study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2.5 remains more uncertain. Funding: Medical Research Council, Wellcome Trust, Environmental Protection Agency and National Institutes of Health.

scholarly journals Quantifying transmissibility of COVID-19 and impact of intervention within long-term health care facilities

2021 ◽  
Author(s):  
Jessica E. Stockdale ◽  
Sean C. Anderson ◽  
Andrew M. Edwards ◽  
Sarafa A. Iyaniwura ◽  
Nicola Mulberry ◽  
...  
Keyword(s):  
Health Care ◽  
Credible Interval ◽  
Health Care Facilities ◽  
Total Size ◽  
Bayesian Hierarchical ◽  
Standard Methods ◽  
Risk Environments ◽  
Global Pandemic ◽  
Care Facilities

AbstractEstimates of the basic reproduction number (R0) for Coronavirus disease 2019 (COVID-19) are particularly variable in the context of transmission within locations such as long-term health care (LTHC) facilities. We sought to characterise the heterogeneity of R0 across known outbreaks within these facilities. We used a unique comprehensive dataset of all outbreaks that have occurred within LTHC facilities in British Columbia, Canada. We estimated R0 with a Bayesian hierarchical dynamic model of susceptible, exposed, infected, and recovered individuals, that incorporates heterogeneity of R0 between facilities. We further compared these estimates to those obtained with standard methods that utilize the exponential growth rate and maximum likelihood. The total size of an outbreak varied dramatically, with a range of attack rates of 2%–86%. The Bayesian analysis provides more constrained overall estimates of R0 = 2.19 (90% CrI [credible interval] 0.19–6.69) than standard methods, with a range within facilities of 0.48–10.08. We further estimated that intervention led to 57% (47%–66%) of all cases being averted within the LTHC facilities, or 73% (63%–78%) when using a model with multi-level intervention effect. Understanding the risks and impact of intervention are essential in planning during the ongoing global pandemic, particularly in high-risk environments such as LTHC facilities.

scholarly journals Quantifying transmissibility of SARS-CoV-2 and impact of intervention within long-term healthcare facilities

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Jessica E. Stockdale ◽  
Sean C. Anderson ◽  
Andrew M. Edwards ◽  
Sarafa A. Iyaniwura ◽  
Nicola Mulberry ◽  
...  
Keyword(s):  
Population Level ◽  
Credible Interval ◽  
Total Size ◽  
Bayesian Hierarchical ◽  
Healthcare Facilities ◽  
Standard Methods ◽  
Risk Environments ◽  
Global Pandemic ◽  
Level Model

Estimates of the basic reproduction number ( R 0 ) for COVID-19 are particularly variable in the context of transmission within locations such as long-term healthcare (LTHC) facilities. We sought to characterize the heterogeneity of R 0 across known outbreaks within these facilities. We used a unique comprehensive dataset of all outbreaks that occurred within LTHC facilities in British Columbia, Canada as of 21 September 2020. We estimated R 0 in 18 LTHC outbreaks with a novel Bayesian hierarchical dynamic model of susceptible, exposed, infected and recovered individuals, incorporating heterogeneity of R 0 between facilities. We further compared these estimates to those obtained with standard methods that use the exponential growth rate and maximum likelihood. The total size of outbreaks varied dramatically, with range of attack rates 2%–86%. The Bayesian analysis provided an overall estimate of R 0 = 2.51 (90% credible interval 0.47–9.0), with individual facility estimates ranging between 0.56 and 9.17. Uncertainty in these estimates was more constrained than standard methods, particularly for smaller outbreaks informed by the population-level model. We further estimated that intervention led to 61% (52%–69%) of all potential cases being averted within the LTHC facilities, or 75% (68%–79%) when using a model with multi-level intervention effect. Understanding of transmission risks and impact of intervention are essential in planning during the ongoing global pandemic, particularly in high-risk environments such as LTHC facilities.

scholarly journals The long term effects of outdoor air pollution in urban environments on cardiovascular health: a global review

CommonHealth ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 122-133
Author(s):  
Lindsay Kraus ◽  
Heather Murphy
Keyword(s):  
Air Pollution ◽  
Cardiovascular Diseases ◽  
Environmental Protection Agency ◽  
Cardiovascular Health ◽  
Urban Environments ◽  
Outdoor Air ◽  
Long Term Effects ◽  
Outdoor Air Pollution ◽  
The Impact

The effect of air pollution on health is listed as a significant cause of death worldwide. Slightly over 3 million deaths per year are due to outdoor air pollution. Studies have shown that short term increases in exposure to particulate matter have increased the risk of cardiovascular diseases such as myocardial infarction, stroke, and heart failure. However, less is known about the longer term effects of air pollution on various cardiovascular diseases. The American Heart Association formally recognized PM2.5 as a significant cardiovascular risk factor in 2010. Since then, more prolonged term exposure to air pollution has been suggested to cause chronic cardiometabolic and cardiovascular problems. The effects of long term (>3 years) air pollution are significant, but not as much is known about how location affects this exposure. Associations with cardiovascular diseases and their risk factors are often increased in urban settings, which is attributed to a higher concentrations of outdoor air pollution, independent of ethnic groups and seasonal changes. Potential causes of long term air pollution concentrations in cities or metropolitan areas come from traffic exposure and traffic intensity. The Environmental Protection Agency and United Nations have suggested changes in air quality standards, implementation plans, and ways to reduce vehicle emissions specifically to improve human health and reduce the adverse effects of air pollution; however, more work still needs to be done. This review assesses the impact of the global long term (>3 years) air pollution exposure, specifically in urban environments on cardiovascular health and disease.

scholarly journals Acute and chronic exposure to air pollution in relation with incidence, prevalence, severity and mortality of COVID-19: a rapid systematic review

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Patrick D. M. C. Katoto ◽  
Amanda S. Brand ◽  
Buket Bakan ◽  
Paul Musa Obadia ◽  
Carsi Kuhangana ◽  
...  
Keyword(s):  
Air Pollution ◽  
Chronic Exposure ◽  
Ambient Air ◽  
Short Term ◽  
Incidence And Mortality ◽  
Acute And Chronic Exposure ◽  
Anthropogenic Pollutant ◽  
Incident Cases ◽  
Incidence Prevalence

Abstract Background Air pollution is one of the world’s leading mortality risk factors contributing to seven million deaths annually. COVID-19 pandemic has claimed about one million deaths in less than a year. However, it is unclear whether exposure to acute and chronic air pollution influences the COVID-19 epidemiologic curve. Methods We searched for relevant studies listed in six electronic databases between December 2019 and September 2020. We applied no language or publication status limits. Studies presented as original articles, studies that assessed risk, incidence, prevalence, or lethality of COVID-19 in relation with exposure to either short-term or long-term exposure to ambient air pollution were included. All patients regardless of age, sex and location diagnosed as having COVID-19 of any severity were taken into consideration. We synthesised results using harvest plots based on effect direction. Results Included studies were cross-sectional (n = 10), retrospective cohorts (n = 9), ecological (n = 6 of which two were time-series) and hypothesis (n = 1). Of these studies, 52 and 48% assessed the effect of short-term and long-term pollutant exposure, respectively and one evaluated both. Pollutants mostly studied were PM2.5 (64%), NO2 (50%), PM10 (43%) and O3 (29%) for acute effects and PM2.5 (85%), NO2 (39%) and O3 (23%) then PM10 (15%) for chronic effects. Most assessed COVID-19 outcomes were incidence and mortality rate. Acutely, pollutants independently associated with COVID-19 incidence and mortality were first PM2.5 then PM10, NO2 and O3 (only for incident cases). Chronically, similar relationships were found for PM2.5 and NO2. High overall risk of bias judgments (86 and 39% in short-term and long-term exposure studies, respectively) was predominantly due to a failure to adjust aggregated data for important confounders, and to a lesser extent because of a lack of comparative analysis. Conclusion The body of evidence indicates that both acute and chronic exposure to air pollution can affect COVID-19 epidemiology. The evidence is unclear for acute exposure due to a higher level of bias in existing studies as compared to moderate evidence with chronic exposure. Public health interventions that help minimize anthropogenic pollutant source and socio-economic injustice/disparities may reduce the planetary threat posed by both COVID-19 and air pollution pandemics.

scholarly journals Response to “Re: Long-term exposure to air-pollution and COVID-19 mortality in England: A hierarchical spatial analysis”

2021 ◽  
Vol 150 ◽  
pp. 106427
Author(s):  
Garyfallos Konstantinoudis ◽  
Tullia Padellini ◽  
James Bennett ◽  
Bethan Davies ◽  
Majid Ezzati ◽  
...  
Keyword(s):  
Air Pollution ◽  
Spatial Analysis

scholarly journals Systemic Inflammation (C-Reactive Protein) in Older Chinese Adults Is Associated with Long-Term Exposure to Ambient Air Pollution

2021 ◽  
Vol 18 (6) ◽  
pp. 3258
Author(s):  
Mona Elbarbary ◽  
Artem Oganesyan ◽  
Trenton Honda ◽  
Geoffrey Morgan ◽  
Yuming Guo ◽  
...  
Keyword(s):  
Air Pollution ◽  
Systemic Inflammation ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Chinese Adults ◽  
Reactive Protein ◽  
Hs Crp ◽  
Older Chinese ◽  
Older Chinese Adults

There is an established association between air pollution and cardiovascular disease (CVD), which is likely to be mediated by systemic inflammation. The present study evaluated links between long-term exposure to ambient air pollution and high-sensitivity C reactive protein (hs-CRP) in an older Chinese adult cohort (n = 7915) enrolled in the World Health Organization (WHO) study on global aging and adult health (SAGE) China Wave 1 in 2008–2010. Multilevel linear and logistic regression models were used to assess the associations of particulate matter (PM) and nitrogen dioxide (NO2) on log-transformed hs-CRP levels and odds ratios of CVD risk derived from CRP levels adjusted for confounders. A satellite-based spatial statistical model was applied to estimate the average community exposure to outdoor air pollutants (PM with an aerodynamic diameter of 10 μm or less (PM10), 2.5 μm or less (PM2.5), and 1 μm or less (PM1) and NO2) for each participant of the study. hs-CRP levels were drawn from dried blood spots of each participant. Each 10 μg/m3 increment in PM10, PM2.5, PM1, and NO2 was associated with 12.8% (95% confidence interval; (CI): 9.1, 16.6), 15.7% (95% CI: 10.9, 20.8), 10.2% (95% CI: 7.3, 13.2), and 11.8% (95% CI: 7.9, 15.8) higher serum levels of hs-CRP, respectively. Our findings suggest that air pollution may be an important factor in increasing systemic inflammation in older Chinese adults.

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