Long-term exposure to air pollution and COVID-19 severity: A cohort study in Greater Manchester, United Kingdom

Greenness, air pollution, and temperature exposure effects in predicting premature mortality and morbidity: A small-area study using spatial random forest model

BACKGROUND

Although studies have provided negative impacts of air pollution, heat or cold exposure on mortality and morbidity, and positive effects of increased greenness on reducing them, a few studies have focused on exploring combined and synergetic effects of these exposures in predicting these health outcomes, and most had ignored the spatial autocorrelation in analyzing their health effects. This study aims to investigate the health effects of air pollution, greenness, and temperature exposure on premature mortality and morbidity within a spatial machine-learning modeling framework.

METHODS

Years of potential life lost reflecting premature mortality and comparative illness and disability ratio reflecting chronic morbidity from 1673 small areas covering Greater Manchester for the year 2008-2013 obtained. Average annual levels of NO2 concentration, normalized difference vegetation index (NDVI) representing greenness, and annual average air temperature were utilized to assess exposure in each area. These exposures were linked to health outcomes using non-spatial and spatial random forest (RF) models while accounting for spatial autocorrelation.

RESULTS

Spatial-RF models provided the best predictive accuracy when accounted for spatial autocorrelation. Among the exposures considered, air pollution emerged as the most influential in predicting mortality and morbidity, followed by NDVI and temperature exposure. Nonlinear exposure-response relations were observed, and interactions between exposures illustrated specific ranges or sweet and sour spots of exposure thresholds where combined effects either exacerbate or moderate health conditions.

CONCLUSION

Air pollution exposure had a greater negative impact on health compared to greenness and temperature exposure. Combined exposure effects may indicate the highest influence of premature mortality and morbidity burden.

Long-Term Particulate Matter Exposure and Mortality in Hospitalized Patients with COVID-19 in South Korea

Rationale: Particulate matter (PM) exposure exacerbates health outcomes by causing lung damage. Objectives: To investigate whether prior exposure to particulate matter ⩽10 μm and ⩽2.5 μm in aerodynamic diameter (PM10 and PM2.5) was associated with clinical outcomes among patients with coronavirus disease (COVID-19). Methods: Data from the nationwide registration database of the National Health Insurance and Korea Disease Control and Prevention Agency in South Korea were used. The study included adult patients who were admitted to monitoring centers or hospitals between October 8, 2020 and December 31, 2021, after COVID-19 confirmation. AirKOREA database, which compiles air pollutant data from 642 stations in 162 cities and counties across South Korea, was used to extract data on PM levels. Average values of monthly exposure to PM10 and PM2.5 from the year previous to hospital admission because of COVID-19 to the date of confirmation of COVID-19 were calculated and used to define PM exposures of patients with COVID-19. Results: In total, 322,289 patients with COVID-19 were included, and 4,633 (1.4%) died during hospitalization. After adjusting for covariates, a 1-μg/m3 increase in PM10 and PM2.5 exposure was associated with 4% (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.03-1.05; P < 0.001) and 6% (OR, 1.06; 95% CI, 1.04-1.07; P < 0.001) increase in the risk of in-hospital mortality, respectively. In addition, a 1-μg/m3 increase in PM10 and PM2.5 was associated with 5% (OR, 1.05; 95% CI, 1.04-1.07; P < 0.001) and 8% (OR, 1.08; 95% CI, 1.06-1.10; P < 0.001) increase in the risks of requiring intensive care unit (ICU) admission and mechanical ventilation, respectively. Conclusions: PM10 and PM2.5 exposure was associated with increased in-hospital mortality and the need for ICU admission and mechanical ventilation among patients with COVID-19 in South Korea.

Long-term air pollution exposure and risk of SARS-CoV-2 infection: A UK-wide cohort study

BACKGROUND

The association between air quality and risk of SARS-CoV-2 infection is poorly understood. We investigated this association using serological individual-level data adjusting for a wide range of confounders, in a large population-based cohort (COVIDENCE UK).

METHODS

We assessed the associations between long-term (2015-19) nitrogen dioxide (NO2) and fine particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5), exposures with SARS-CoV-2 infection, level of antibody response among those infected, and COVID-19 disease severity. We used serological data from 10,489 participants in the COVIDENCE UK cohort, and estimated annual average air pollution exposure at each participant's home postcode.

RESULTS

After controlling for potential confounders, we found a positive association between 5-year NO2 and PM2.5 exposures and the risk of seropositivity: 10 unit increase in NO2 (μg/m3) was associated with an increasing risk of seropositivity by 1.092 (95% CI 1.02 to 1.17; p-for-trend 0.012). For PM2.5, 10 unit increase (μg/m3) was associated with an increasing risk of seropositivity by 1.65 (95% CI 1.015-2.68; p-for-trend 0·049). In addition, we found that NO2 was positively associated with higher antibody titres (p-for-trend 0·013) among seropositive participants, with no evidence of an association for PM2.5.

CONCLUSION

Our findings suggest that the long-term burden of air pollution increased the risks of SARS-CoV-2 infection and has important implications for future pandemic preparedness. This evidence strengthens the case for reducing long-term air pollution exposures to reduce the vulnerability of individuals to respiratory viruses.

Effects of long-term exposure to outdoor air pollution on COVID-19 incidence: A population-based cohort study accounting for SARS-CoV-2 exposure levels in the Netherlands

Several studies have linked air pollution to COVID-19 morbidity and severity. However, these studies do not account for exposure levels to SARS-CoV-2, nor for different sources of air pollution. We analyzed individual-level data for 8.3 million adults in the Netherlands to assess associations between long-term exposure to ambient air pollution and SARS-CoV-2 infection (i.e., positive test) and COVID-19 hospitalisation risks, accounting for spatiotemporal variation in SARS-CoV-2 exposure levels during the first two major epidemic waves (February 2020-February 2021). We estimated average annual concentrations of PM10, PM2.5 and NO2 at residential addresses, overall and by PM source (road traffic, industry, livestock, other agricultural sources, foreign sources, other Dutch sources), at 1 × 1 km resolution, and weekly SARS-CoV-2 exposure at municipal level. Using generalized additive models, we performed interval-censored survival analyses to assess associations between individuals' average exposure to PM10, PM2.5 and NO2 in the three years before the pandemic (2017-2019) and COVID-19-outcomes, adjusting for SARS-CoV-2 exposure, individual and area-specific confounders. In single-pollutant models, per interquartile (IQR) increase in exposure, PM10 was associated with 7% increased infection risk and 16% increased hospitalisation risk, PM2.5 with 8% increased infection risk and 18% increased hospitalisation risk, and NO2 with 3% increased infection risk and 11% increased hospitalisation risk. Bi-pollutant models suggested that effects were mainly driven by PM. Associations for PM were confirmed when stratifying by urbanization degree, epidemic wave and testing policy. All emission sources of PM, except industry, showed adverse effects on both outcomes. Livestock showed the most detrimental effects per unit exposure, whereas road traffic affected severity (hospitalisation) more than infection risk. This study shows that long-term exposure to air pollution increases both SARS-CoV-2 infection and COVID-19 hospitalisation risks, even after controlling for SARS-CoV-2 exposure levels, and that PM may have differential effects on these COVID-19 outcomes depending on the emission source.

Who is more vulnerable to effects of long-term exposure to air pollution on COVID-19 hospitalisation?

OBJECTIVE

Factors that shape individuals' vulnerability to the effects of air pollution on COVID-19 severity remain poorly understood. We evaluated whether the association between long-term exposure to ambient NO2, PM2.5, and PM10 and COVID-19 hospitalisation differs by age, sex, individual income, area-level socioeconomic status, arterial hypertension, diabetes mellitus, and chronic obstructive pulmonary disease.

METHODS

We analysed a population-based cohort of 4,639,184 adults in Catalonia, Spain, during 2020. We fitted Cox proportional hazard models adjusted for several potential confounding factors and evaluated the interaction effect between vulnerability indicators and the 2019 annual average of NO2, PM2.5, and PM10. We evaluated interaction on both additive and multiplicative scales.

RESULTS

Overall, the association was additive between air pollution and the vulnerable groups. Air pollution and vulnerability indicators had a synergistic (greater than additive) effect for males and individuals with low income or living in the most deprived neighbourhoods. The Relative Excess Risk due to Interaction (RERI) was 0.21, 95 % CI, 0.15 to 0.27 for NO2 and 0.16, 95 % CI, 0.11 to 0.22 for PM2.5 for males; 0.13, 95 % CI, 0.09 to 0.18 for NO2 and 0.10, 95 % CI, 0.05 to 0.14 for PM2.5 for lower individual income and 0.17, 95 % CI, 0.12 to 0.22 for NO2 and 0.09, 95 % CI, 0.05 to 0.14 for PM2.5 for lower area-level socioeconomic status. Results for PM10 were similar to PM2.5. Results on multiplicative scale were inconsistent.

CONCLUSIONS

Long-term exposure to air pollution had a larger synergistic effect on COVID-19 hospitalisation for males and those with lower individual- and area-level socioeconomic status.

Association of air pollution and weather conditions during infection course with COVID-19 case fatality rate in the United Kingdom

Although the relationship between the environmental factors, such as weather conditions and air pollution, and COVID-19 case fatality rate (CFR) has been found, the impacts of these factors to which infected cases are exposed at different infectious stages (e.g., virus exposure time, incubation period, and at or after symptom onset) are still unknown. Understanding this link can help reduce mortality rates. During the first wave of COVID-19 in the United Kingdom (UK), the CFR varied widely between and among the four countries of the UK, allowing such differential impacts to be assessed. We developed a generalized linear mixed-effect model combined with distributed lag nonlinear models to estimate the odds ratio of the weather factors (i.e., temperature, sunlight, relative humidity, and rainfall) and air pollution (i.e., ozone, [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text]) using data between March 26, 2020 and September 15, 2020 in the UK. After retrospectively time adjusted CFR was estimated using back-projection technique, the stepwise model selection method was used to choose the best model based on Akaike information criteria and the closeness between the predicted and observed values of CFR. The risk of death reached its maximum level when the low temperature (6 °C) occurred 1 day before (OR 1.59; 95% CI 1.52-1.63), prolonged sunlight duration (11-14 h) 3 days after (OR 1.24; 95% CI 1.18-1.30) and increased [Formula: see text] (19 μg/m3) 1 day after the onset of symptom (OR 1.12; 95% CI 1.09-1.16). After reopening, many COVID-19 cases will be identified after their symptoms appear. The findings highlight the importance of designing different preventive measures against severe illness or death considering the time before and after symptom onset.

Impact of Ambient Air Pollution Exposure on Long COVID-19 Symptoms: A Cohort Study within the Saudi Arabian Population

Evidence suggests that air pollution, specifically the particulate matters PM2.5 and PM10, plays a key role in exacerbating the risk of prolonged symptoms following COVID-19 infection.

AIM

This study endeavors to elucidate the potential interaction between chronic air pollution exposure and the manifestation of long COVID symptoms within a cohort based in Makkah, Saudi Arabia.

METHODS

Participants included residents from the Makkah region who had recovered from COVID-19 between 2022 and 2023. A comprehensive questionnaire was utilized to gather detailed demographic data and assess the persistent symptoms seen during the post-COVID period. To gauge the environmental exposure to potential risk factors, air sampling for PM10 and PM2.5 was systematically conducted in various locations in Makkah over a year.

RESULTS

Significant positive associations were found between PM2.5 and PM10 exposure and long COVID. Furthermore, specific symptom analysis revealed a significant association between air pollution and shortness of breath (for PM2.5). Only PM2.5 exposure remained statistically significant (RR = 1.32, 95% CI: 1.05, 1.67). In contrast, the association with PM10 remained on the cusp of significance, with an RR of 1.27 (95% CI: 1.00, 1.61).

CONCLUSION

This study highlights the importance of reducing air pollution levels to mitigate the long-term health consequences of COVID-19.

Short-term exposure to ambient air pollution and COVID-19 severity during SARS-CoV-2 Delta and Omicron waves: A multicenter study

Air pollution may affect the clinical course of respiratory diseases, including COVID-19. This study aimed to evaluate the relationship between exposure of adult patients to mean 24 h levels of particulate matter sized <10 μm (PM₁₀ ) and <2.5 μm (PM_2.5 ) and benzo(a)pyrene (B(a)P) during a week before their hospitalization due to SARS-CoV-2 infection and symptomatology, hyperinflammation, coagulopathy, the clinical course of disease, and outcome. The analyses were conducted during two pandemic waves: (i) dominated by highly pathogenic Delta variant (n = 1440) and (ii) clinically less-severe Omicron (n = 785), while the analyzed associations were adjusted for patient's age, BMI, gender, and comorbidities. The exposure to mean 24 h B(a)P exceeding the limits was associated with increased odds of fever and fatigue as early COVID-19 symptoms, hyperinflammation due to serum C-reactive protein >200 mg/L and interleukin-6 >100 pg/mL, coagulopathy due to  d-dimer >2 mg/L and fatal outcome. Elevated PM₁₀ and PM_{2. 5} levels were associated with higher odds of respiratory symptoms, procalcitonin >0.25 ng/mL and interleukin >100 pg/mL, lower oxygen saturation, need for oxygen support, and death. The significant relationships between exposure to air pollutants and the course and outcomes of COVID-19 were observed during both pandemic waves. Short-term exposure to elevated PM and B(a)P levels can be associated with a worse clinical course of COVID-19 in patients requiring hospitalization and, ultimately, contribute to the health burden caused by SARS-CoV-2 variants of higher and lower clinical significance.

Long-term exposure to air pollution and risk of SARS-CoV-2 infection and COVID-19 hospitalisation or death: Danish nationwide cohort study

BACKGROUND

Early ecological studies have suggested links between air pollution and risk of coronavirus disease 2019 (COVID-19), but evidence from individual-level cohort studies is still sparse. We examined whether long-term exposure to air pollution is associated with risk of COVID-19 and who is most susceptible.

METHODS

We followed 3 721 810 Danish residents aged ≥30 years on 1 March 2020 in the National COVID-19 Surveillance System until the date of first positive test (incidence), COVID-19 hospitalisation or death until 26 April 2021. We estimated residential annual mean particulate matter with diameter ≤2.5 μm (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) in 2019 by the Danish DEHM/UBM model, and used Cox proportional hazards regression models to estimate the associations of air pollutants with COVID-19 outcomes, adjusting for age, sex, individual- and area-level socioeconomic status, and population density.

RESULTS

138 742 individuals were infected, 11 270 were hospitalised and 2557 died from COVID-19 during 14 months. We detected associations of PM2.5 (per 0.53 μg·m-3) and NO2 (per 3.59 μg·m-3) with COVID-19 incidence (hazard ratio (HR) 1.10 (95% CI 1.05-1.14) and HR 1.18 (95% CI 1.14-1.23), respectively), hospitalisations (HR 1.09 (95% CI 1.01-1.17) and HR 1.19 (95% CI 1.12-1.27), respectively) and death (HR 1.23 (95% CI 1.04-1.44) and HR 1.18 (95% CI 1.03-1.34), respectively), which were strongest in the lowest socioeconomic groups and among patients with chronic respiratory, cardiometabolic and neurodegenerative diseases. We found positive associations with BC and negative associations with O3.

CONCLUSION

Long-term exposure to air pollution may contribute to increased risk of contracting severe acute respiratory syndrome coronavirus 2 infection as well as developing severe COVID-19 disease requiring hospitalisation or resulting in death.

Effects of fine particulate matter (PM2.5) and meteorological factors on the daily confirmed cases of COVID-19 in Bangkok during 2020-2021, Thailand

The ongoing global pandemic caused by the SARS-CoV-2 virus, known as COVID-19, has disrupted public health, businesses, and economies worldwide due to its widespread transmission. While previous research has suggested a possible link between environmental factors and increased COVID-19 cases, the evidence regarding this connection remains inconclusive. The purpose of this research is to determine whether or not there is a connection between the presence of fine particulate matter (PM2.5) and meteorological conditions and COVID-19 infection rates in Bangkok, Thailand. The study employs a statistical method called Generalized Additive Model (GAM) to find a positive and non-linear association between RH, AH, and R and the number of verified COVID-19 cases. The impacts of the seasons (especially summer) and rainfall on the trajectory of COVID-19 cases were also highlighted, with an adjusted R-square of 0.852 and a deviance explained of 85.60%, both of which were statistically significant (p < 0.05). The study results assist in preventing the future seasonal spread of COVID-19, and public health authorities may use these findings to make informed decisions and assess their policies.

Peculiar weather patterns effects on air pollution and COVID-19 spread in Tokyo metropolis

As a pandemic hotspot in Japan, between March 1, 2020-October 1, 2022, Tokyo metropolis experienced seven COVID-19 waves. Motivated by the high rate of COVID-19 incidence and mortality during the seventh wave, and environmental/health challenges we conducted a time-series analysis to investigate the long-term interaction of air quality and climate variability with viral pandemic in Tokyo. Through daily time series geospatial and observational air pollution/climate data, and COVID-19 incidence and death cases, this study compared the environmental conditions during COVID-19 multiwaves. In spite of five State of Emergency (SOEs) restrictions associated with COVID-19 pandemic, during (2020-2022) period air quality recorded low improvements relative to (2015-2019) average annual values, namely: Aerosol Optical Depth increased by 9.13% in 2020 year, and declined by 6.64% in 2021, and 12.03% in 2022; particulate matter PM2.5 and PM10 decreased during 2020, 2021, and 2022 years by 10.22%, 62.26%, 0.39%, and respectively by 4.42%, 3.95%, 5.76%. For (2021-2022) period the average ratio of PM2.5/PM10 was (0.319 ± 0.1640), showing a higher contribution to aerosol loading of traffic-related coarse particles in comparison with fine particles. The highest rates of the daily recorded COVID-19 incidence and death cases in Tokyo during the seventh COVID-19 wave (1 July 2022-1 October 2022) may be attributed to accumulation near the ground of high levels of air pollutants and viral pathogens due to: 1) peculiar persistent atmospheric anticyclonic circulation with strong positive anomalies of geopotential height at 500 hPa; 2) lower levels of Planetary Boundary Layer (PBL) heights; 3) high daily maximum air temperature and land surface temperature due to the prolonged heat waves (HWs) in summer 2022; 4) no imposed restrictions. Such findings can guide public decision-makers to design proper strategies to curb pandemics under persistent stable anticyclonic weather conditions and summer HWs in large metropolitan areas.