Particulate matter air pollution and COVID-19 infection, severity, and mortality: A systematic review and meta-analysis

Respiratory symptoms after coalmine fire and pandemic: A longitudinal analysis of the Hazelwood Health Study adult cohort

The aim of this study was to determine whether the effects of extreme but discrete PM2.5 exposure from a coal mine fire on respiratory symptoms abated, persisted, or worsened over time, and whether they were exacerbated by COVID-19. We analysed longitudinal survey data from a cohort residing near a 2014 coalmine fire in regional Australia. A 2016/2017 survey included 4,056 participants, of whom 612 were followed-up in 2022. Items included respiratory symptoms, history of COVID-19, and time-location diaries from the mine fire period, which were combined with geospatial and temporal models of fire-related PM2.5. Longitudinal effects of fire-related PM2.5 were examined using a mixed-effects logistic regression model. Exacerbation due to COVID-19 was examined using a logistic regression model. PM2.5 exposure was associated with chronic cough and possibly current wheeze, chest tightness, and current nasal symptoms 2-3 years post-fire, and chronic cough and current wheeze 8.5-9 years post-fire. Further, the association between PM2.5 and chronic cough and possibly current wheeze appeared to increase between the survey periods. While there were no detectable interactions between PM2.5 and COVID-19, PM2.5 exposure was associated with additional respiratory symptoms among participants who reported a history of COVID-19. In summary, medium-duration exposure to extreme levels of fire-related PM2.5 may have increased the long-term risk of chronic cough and current wheeze. While the COVID-19 pandemic started several years after the mine fire, contracting this illness may have exacerbated the effect of fire-related PM2.5 through development of additional respiratory symptoms.

The association between different timeframes of air pollution exposure and COVID-19 incidence, morbidity and mortality in German counties in 2020

BACKGROUND

Ambient air pollution is a known risk factor for several chronic health conditions, including pulmonary dysfunction. In recent years, studies have shown a positive association between exposure to air pollutants and the incidence, morbidity, and mortality of a COVID-19 infection, however the time period for which air pollution exposure is most relevant for the COVID-19 outcome is still not defined. The aim of this study was to analyze the difference in association when varying the time period of air pollution exposure considered on COVID-19 infection within the same cohort during the first wave of the pandemic in 2020.

METHODS

We conducted a cross-sectional study analyzing the association between long- (10- and 2-years) and short-term (28 days, 7 days, and 2 days) exposure to NO2 and PM2.5 on SARS-CoV-2 incidence, morbidity, and mortality at the level of county during the first outbreak of the pandemic in spring 2020. Health data were extracted from the German national public health institute (Robert-Koch-Institute) and from the German Interdisciplinary Association for Intensive Care and Emergency Medicine. Air pollution data were taken from the APExpose dataset (version 2.0). We used negative binomial models, including adjustment for risk factors (age, sex, days since first COVID-19 case, population density, socio-economic and health parameters).

RESULTS

We found that PM2.5 and NO2 exposure 28 days before COVID-19 infection had the highest association with infection, morbidity as well as mortality, as compared to long-term or short-term (2 or 7 days) air pollutant exposure. A 1 μg/m3 increase in PM2.5 was associated with a 31.7% increase in incidence, a 20.6% need for ICU treatment, a 23.1% need for mechanical ventilation, and a 55.3% increase in mortality; an increase of 1 μg/m3 of NO2 was associated with an increase for all outcomes by 25.2 - 29.4%.

CONCLUSIONS

Our findings show a positive association between PM2.5 and NO2 exposure and the clinical course of a SARS-CoV2 infection, with the strongest association to 28 days of exposure to air pollution. This finding provides an indication as to the primary underlying pathophysiology, and can therefore help to improve the resilience of societies by implementing adequate measures to reduce the air pollutant impact on health outcomes.

TRIAL REGISTRATION

Not applicable.

Association between ambient particulate matter and latent tuberculosis infection among 198 275 students

Background

Numerous studies have estimated the impact of outdoor particulate matter (PM) on tuberculosis risk. Nevertheless, whether there is an association between ambient PM and latent tuberculosis infection (LTBI) risk remains uncertain.

Methods

We collected the basic information and LTBI test results of students who underwent freshmen enrolment physical examinations in 68 middle schools from six prefecture-level cities located in eastern China between 2018 and 2021. We also extracted data on air pollutant concentrations and meteorological factors in six cities between 2015 and 2021. We applied the generalised additive model (GAM) to assess the effect of PM on LTBI risk.

Results

We included 198 275 students in the final analysis, of whom 11 721 were diagnosed with LTBI. The LTBI group had higher proportions of males (P < 0.001), individuals of Han nationality (P < 0.001), and body mass index compared to the non-LTBI group (P < 0.001). For each 1-μg/m3 increase in PM10 concentration, the LTBI risk increased by 0.82% (95% confidence interval (CI) = 0.65-1.00), 0.90% (95% CI = 0.73-1.08), and 0.86% (95% CI = 0.69-1.03) when lagged at one, two, and three years, respectively. For PM2.5, the LTBI risk increased by 0.91% (95% CI = 0.63-1.20), 1.05% (95% CI = 0.75-1.36), and 1.32% (95% CI = 0.96-1.69) when lagged at one, two, and three years, respectively.

Conclusions

Outdoor PM concentration was positively correlated with LTBI risk. Considering that many developing countries are facing the dual challenges of high LTBI rates and serious ambient air pollution, reducing outdoor PM concentration would contribute to alleviating their tuberculosis burden.

Environmental Risk Factors for Acute Respiratory Distress Syndrome

Several environmental exposures increase susceptibility to the acute respiratory distress syndrome (ARDS). Specifically, chronic exposure to ambient air pollution, cigarette smoke, and alcohol "prime" the lung via epithelial injury, endothelial dysfunction, and immunomodulatory mechanisms, increasing the risk and severity of ARDS following an array of acute insults. Future research of these pathways may reveal therapeutic targets. Relevant emerging threats, such as electronic cigarettes and vaping, wildfire smoke, and the environmental hazards associated with climate change, may also be associated with ARDS. Building upon existing public policy interventions can prevent substantial morbidity and mortality from ARDS.

Social health gradient and risk factors among patients hospitalized for COVID-19 and pre-pandemic respiratory infections. A linked national individual case-control study in Belgium

Introduction

The literature establishes a clear social gradient in health for transmissible respiratory diseases. However, this gradient's extent remains largely unexplored in the context of COVID-19, and it is uncertain whether the pandemic has exacerbated this gradient. The study aims to compare the socio-economic profiles and comorbidities during the COVID-19 pandemic with a control population affected by viral pneumonia/respiratory disease in 2019.

Methods

This case-control study analyzed linked data from all patients hospitalized for COVID-19 in 2020 (n = 22,087) and for respiratory diseases in 2019 (n = 7,586). Socio-economic data from the social security database were linked to clinical data from the hospital registry. We analyzed the socio-demographic and clinical factors associated with COVID-19 hospitalization (control group, wave 1, and wave 2) using multinomial regressions and logistic regression models and the length of stay during hospitalization using binomial negative regressions.

Results

A social health gradient was observed in both the COVID-19 and control groups, with a significant increase across waves for COVID-19 (p-trend < 0.0001). Men, people over the age of 45, those with comorbidities, high population density, lower income, lower socio-economic status, and people living in Brussels capital were at higher risk of COVID-19 hospitalization and longer length of stay compared to the control group. Except for sub-Saharan Africans, all patients of foreign nationality had a significantly increased risk of hospitalization (p < 0.001), but a shorter length of stay compared to Belgians.

Conclusion

The socio-health gradient for COVID-19 followed the same pattern as that observed in pre-pandemic respiratory diseases, intensifying in the second wave and among the most deprived groups. This study emphasizes the importance of collecting social data alongside clinical data for a better understanding of social health inequalities and for tailoring health prevention policies.

Health benefits of air pollution reduction: Evidence from economic slowdown in India

This paper evaluates health benefits associated with the impact of air pollution reduction on infant mortality in India. Leveraging plausibly exogenous geographic variation in air pollution due to the post-2010 economic slowdown-a period largely overlooked in the literature-I find that improvements in air quality resulted in a significant decline in infant mortality, particularly through respiratory diseases and biological pathways such as in utero and post-birth exposure. The associated health benefits correspond to 1338 saved infant lives, translating to monetary gains of $312.5 million. The paper advances our understanding of the link between air pollution and human health in settings with elevated air pollution and suboptimal regulatory frameworks.

Residential greenspace and COVID-19 Severity: A cohort study of 313,657 individuals in Greater Manchester, United Kingdom

BACKGROUND

Greenspaces contribute positively to mental and physical well-being, promote social cohesion, and alleviate environmental stressors, such as air pollution. Ecological studies suggest that greenspace may affect incidence and severity of Coronavirus Disease 2019 (COVID-19).

OBJECTIVE

This study examines the association between residential greenspace and COVID-19 related hospitalization and death.

METHOD

In this retrospective cohort based on patient records from the Greater Manchester Care Records, all first COVID-19 cases diagnosed between March 1, 2020, and May 31, 2022 were followed until COVID-19 related hospitalization or death within 28 days. Residential greenspace availability was assessed using the Normalized Difference Vegetation Index per lower super output area in Greater Manchester. The association of greenspace with COVID-19 hospitalization and mortality were estimated using multivariate logistic regression models after adjusting for potential individual, temporal, and spatial confounders. We explored potential effect modifications of the associations with greenspace and COVID-19 severity by age, sex, body mass index, smoking, deprivation, and certain comorbidities. Combined effects of greenspace and air pollution (NO2 and PM2.5) were investigated by mutually adjusting pairs with correlation coefficients ≤ 0·7.

RESULTS

Significant negative associations were observed between greenspace availability and COVID-19 hospitalization and mortality with odds ratios [OR] (95 % Confidence Intervals [CI]) of 0·96 (0·94-0·97) and 0·84 (0·80-0·88) (per interquartile range [IQR]), respectively. These were significantly modified by deprivation (P-value for interaction < 0.05), showing that those most deprived obtained largest benefits from greenspace. Inclusion of NO2 and PM2.5 diminished associations to null for COVID-19 hospitalization, but only reduced them slightly for mortality, where inverse associations remained.

CONCLUSION

In the Greater Manchester area, residential greenspace is associated with reduced risk of hospitalization or death in individuals with COVID-19, with deprived groups obtaining the greatest benefits. Associations were strongest for COVID-19 mortality, which were robust to inclusion of air pollutants in the models.

Correlation between Exposure to UFP and ACE/ACE2 Pathway: Looking for Possible Involvement in COVID-19 Pandemic

The overlap between the geographic distribution of COVID-19 outbreaks and pollution levels confirmed a correlation between exposure to atmospheric particulate matter (PM) and the SARS-CoV-2 pandemic. The RAS system is essential in the pathogenesis of inflammatory diseases caused by pollution: the ACE/AngII/AT1 axis activates a pro-inflammatory pathway, which is counteracted by the ACE2/Ang(1-7)/MAS axis, which activates an anti-inflammatory and protective pathway. However, ACE2 is also known to act as a receptor through which SARS-CoV-2 enters host cells to replicate. Furthermore, in vivo systems have demonstrated that exposure to PM increases ACE2 expression. In this study, the effects of acute and sub-acute exposure to ultrafine particles (UFP), originating from different anthropogenic sources (DEP and BB), on the levels of ACE2, ACE, COX-2, HO-1, and iNOS in the lungs and other organs implicated in the pathogenesis of COVID-19 were analyzed in the in vivo BALB/c male mice model. Exposure to UFP alters the levels of ACE2 and/or ACE in all examined organs, and exposure to sub-acute DEP also results in the release of s-ACE2. Furthermore, as evidenced in this and our previous works, COX-2, HO-1, and iNOS levels also demonstrated organ-specific alterations. These proteins play a pivotal role in the UFP-induced inflammatory and oxidative stress responses, and their dysregulation is linked to the development of severe symptoms in individuals infected with SARS-CoV-2, suggesting a heightened vulnerability or a more severe clinical course of the disease. UFP and SARS-CoV-2 share common pathways; therefore, in a "risk stratification" concept, daily exposure to air pollution may significantly increase the likelihood of developing a severe form of COVID-19, explaining, at least in part, the greater lethality of the virus observed in highly polluted areas.

Viral respiratory infections and air pollution: A review focused on research in Poland

The COVID-19 pandemic has reinforced an interest in the relationship between air pollution and respiratory viral infections, indicating that their burden can be increased under poor air quality. This paper reviews the pathways through which air pollutants can enhance susceptibility to such infections and aggravate their clinical course and outcome. It also summarizes the research exploring the links between various viral infections and exposure to solid and gaseous pollution in Poland, a region characterized by poor air quality, especially during a heating season. The majority of studies focused on concentrations of particulate matter (PM; 86.7%); the other pollutants, i.e., BaP, benzene, CO, NOx, O3, and SO2, were studied less often and sometimes only in the context of a particular infection type. Most research concerned COVID-19, showing that elevated levels of PM and NO2 correlated with higher morbidity and mortality, while increased PM2.5 and benzo[a]pyrene levels were related to worse clinical course and outcome in hospitalized, regardless of age and dominant SARS-CoV-2 variant. PM10 and PM2.5 levels were also associated with the incidence of influenza-like illness and, along with NO2 concentrations, with a higher rate of children's hospitalizations due to lower respiratory tract RSV infections. Higher levels of air pollutants also increased hospitalization due to bronchitis (PM, NOx, and O3) and emergency department admission due to viral croup (PM10, PM2.5, NOx, CO, and benzene). Although the conducted studies imply only correlations and have other limitations, as discussed in the present paper, it appears that improving air quality through reducing combustion processes in energy production in Poland should be perceived as a part of multilayered protection measures against respiratory viral infections, decreasing the healthcare costs of COVID-19, lower tract RSV infections, influenza, and other respiratory viral diseases prevalent between autumn and early spring, in addition to other health and climate benefits.

Exploring the association between ambient air pollution and COVID-19 risk: A comprehensive meta-analysis with meta-regression modelling

Introduction

Air pollution is speculated to increase the risk of Coronavirus disease-2019 (COVID-19). Nevertheless, the results remain inconsistent and inconclusive. This study aimed to explore the association between ambient air pollution (AAP) and COVID-19 risks using a meta-analysis with meta-regression modelling.

Methods

The inclusion criteria were: original studies quantifying the association using effect sizes and 95 % confidence intervals (CIs); time-series, cohort, ecological or case-crossover peer-reviewed studies in English. Exclusion criteria encompassed non-original studies, animal studies, and data with common errors. PubMed, Web of Science, Embase and Google Scholar electronic databases were systemically searched for eligible literature, up to 31, March 2023. The risk of bias (ROB) was assessed following the Agency for Healthcare Research and Quality parameters. A random-effects model was used to calculate pooled risk ratios (RRs) and their 95 % CIs.

Results

A total of 58 studies, between 2020 and 2023, met the inclusion criteria. The global representation was skewed, with major contributions from the USA (24.1 %) and China (22.4 %). The distribution included studies on short-term (43.1 %) and long-term (56.9 %) air pollution exposure. Ecological studies constituted 51.7 %, time-series-27.6 %, cohorts-17.2 %, and case crossover-3.4 %. ROB assessment showed low (86.2 %) and moderate (13.8 %) risk. The COVID-19 incidences increased with a 10 μg/m3 increase in PM2.5 [RR = 4.9045; 95 % CI (4.1548-5.7895)], PM10 [RR = 2.9427: (2.2290-3.8850)], NO2 [RR = 3.2750: (3.1420-3.4136)], SO2 [RR = 3.3400: (2.7931-3.9940)], CO [RR = 2.6244: (2.5208-2.7322)] and O3 [RR = 2.4008: (2.1859-2.6368)] concentrations. A 10 μg/m3 increase in concentrations of PM2.5 [RR = 3.0418: (2.7344-3.3838)], PM10 [RR = 2.6202: (2.1602-3.1781)], NO2 [RR = 3.2226: (2.1411-4.8504)], CO [RR = 1.8021 (0.8045-4.0370)] and O3 [RR = 2.3270 (1.5906-3.4045)] was significantly associated with COVID-19 mortality. Stratified analysis showed that study design, exposure period, and country influenced exposure-response associations. Meta-regression model indicated significant predictors for air pollution-COVID-19 incidence associations.

Conclusion

The study, while robust, lacks causality demonstration and focuses only on the USA and China, limiting its generalizability. Regardless, the study provides a strong evidence base for air pollution-COVID-19-risks associations, offering valuable insights for intervention measures for COVID-19.

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.

The impact of ambient temperature and air pollution on SARS-CoV2 infection and Post COVID-19 condition in Belgium (2021-2022)

INTRODUCTION

The associations between non-optimal ambient temperature, air pollution and SARS-CoV-2 infection and post COVID-19 condition (PCC) remain constrained in current understanding. We conducted a retrospective analysis to explore how ambient temperature affected SARS-CoV-2 infection in individuals who later developed PCC compared to those who did not. We investigated if these associations were modified by air pollution.

METHODS

We conducted a bidirectional time-stratified case-crossover study among individuals who tested positive for SARS-CoV-2 between May 2021 and June 2022. We included 6302 infections, with 2850 PCC cases. We used conditional logistic regression and distributed lag non-linear models to obtain odds ratios (OR) and 95% confidence intervals (CI) for non-optimal temperatures relative to the period median temperature (10.6 °C) on lags 0 to 5. For effect modification, daily average PM2.5 concentrations were categorized using the period median concentration (8.8 μg/m3). Z-tests were used to compare the results by PCC status and PM2.5.

RESULTS

Non-optimal cold temperatures increased the cumulative odds of infection (OR = 1.93; 95%CI:1.67-2.23, OR = 3.53; 95%CI:2.72-4.58, for moderate and extreme cold, respectively), with the strongest associations observed for non-PCC cases. Non-optimal heat temperatures decreased the odds of infection except for moderate heat among PCC cases (OR = 1.32; 95%CI:0.89-1.96). When PM2.5 was >8.8 μg/m3, the associations with cold were stronger, and moderate heat doubled the odds of infection with later development of PCC (OR = 2.18; 95%CI:1.01-4.69). When PM2.5 was ≤8.8 μg/m3, exposure to non-optimal temperatures reduced the odds of infection.

CONCLUSION

Exposure to cold increases SARS-CoV2 risk, especially on days with moderate to high air pollution. Heated temperatures and moderate to high air pollution during infection may cause PCC. These findings stress the need for mitigation and adaptation strategies for climate change to reduce increasing trends in the frequency of weather extremes that have consequences on air pollution concentrations.

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.

Short-term exposure to air pollution and hospital admission after COVID-19 in Catalonia: the COVAIR-CAT study

BACKGROUND

A growing body of evidence has reported positive associations between long-term exposure to air pollution and poor COVID-19 outcomes. Inconsistent findings have been reported for short-term air pollution, mostly from ecological study designs. Using individual-level data, we studied the association between short-term variation in air pollutants [nitrogen dioxide (NO2), particulate matter with a diameter of <2.5 µm (PM2.5) and a diameter of <10 µm (PM10) and ozone (O3)] and hospital admission among individuals diagnosed with COVID-19.

METHODS

The COVAIR-CAT (Air pollution in relation to COVID-19 morbidity and mortality: a large population-based cohort study in Catalonia, Spain) cohort is a large population-based cohort in Catalonia, Spain including 240 902 individuals diagnosed with COVID-19 in the primary care system from 1 March until 31 December 2020. Our outcome was hospitalization within 30 days of COVID-19 diagnosis. We used individual residential address to assign daily air-pollution exposure, estimated using machine-learning methods for spatiotemporal prediction. For each pandemic wave, we fitted Cox proportional-hazards models accounting for non-linear-distributed lagged exposure over the previous 7 days.

RESULTS

Results differed considerably by pandemic wave. During the second wave, an interquartile-range increase in cumulative weekly exposure to air pollution (lag0_7) was associated with a 12% increase (95% CI: 4% to 20%) in COVID-19 hospitalizations for NO2, 8% (95% CI: 1% to 16%) for PM2.5 and 9% (95% CI: 3% to 15%) for PM10. We observed consistent positive associations for same-day (lag0) exposure, whereas lag-specific associations beyond lag0 were generally not statistically significant.

CONCLUSIONS

Our study suggests positive associations between NO2, PM2.5 and PM10 and hospitalization risk among individuals diagnosed with COVID-19 during the second wave. Cumulative hazard ratios were largely driven by exposure on the same day as hospitalization.

Respiratory Health Effects of Air Pollutants

Air pollution is a risk factor for asthma and respiratory infection. Avoidance of air pollution is the best approach to mitigating the impacts of pollution. Personal preventive strategies are possible, but policy interventions are the most effective ways to prevent pollution and its effect on asthma and respiratory infection.

Global association between air pollution and COVID-19 mortality: A systematic review and meta-analysis

BACKGROUND

The COVID-19 pandemic presents unprecedented challenge for global public health systems and exacerbates existing health disparities. Epidemiological evidence suggested a potential linkage between particulate and gaseous pollutants and COVID-19 mortality. We aimed to summarize the overall risk of COVID-19 mortality associated with ambient air pollutants over the short- and long-term.

METHODS

For the systematic review and meta-analysis, we searched five databases for studies evaluating the risk of COVID-19 mortality from exposure to air pollution. Inclusion of articles was assessed independently on the basis of research topic and availability of effect estimates. The risk estimates (relative risk) for each pollutant were pooled with a random-effect model. Potential heterogeneity was explored by subgroup analysis. Funnel plots and trim-and-fill methods were employed to assess and adjust for publication bias.

FINDINGS

The systematic review retrieved 2059 records, and finally included 43 original studies. PM2.5 (RR: 1.71, 95 % CI: 1.40-2.08, per 10 μg/m3 increase), NO2 (RR: 1.33, 1.07-1.65, per 10 ppb increase) and O3 (RR: 1.61, 1.00-2.57, per 10 ppb increase) were positively associated with COVID-19 mortality for long-term exposures. Accordingly, a higher risk of COVID-19 mortality was associated with PM2.5 (1.05, 1.02-1.08), PM10 (1.05, 1.01-1.08), and NO2 (1.40, 1.04-1.90) for short-term exposures. There was some heterogeneity across subgroups of income level and geographical areas.

CONCLUSION

Both long-term and short-term exposures to ambient air pollution may increase the risk of COVID-19 mortality. Future studies utilizing individual-level information on demographics, exposures, outcome ascertainment and confounders are warranted to improve the accuracy of estimates.

Long-term effects of extreme smoke exposure on COVID-19: A cohort study

BACKGROUND

In 2014, the Hazelwood coalmine fire shrouded the regional Australian town of Morwell in smoke and ash for 6 weeks. One of the fire's by-products, PM2.5 , is associated with an increased risk of COVID-19 and severe disease. However, it is unclear whether the effect persisted for years after exposure. In this study, we surveyed a cohort established prior to the pandemic to determine whether PM2.5 from the coalmine fire increased long-term vulnerability to COVID-19 and severe disease.

METHODS

From August to December 2022, 612 members of the Hazelwood Health Study's adult cohort, established in 2016/17, participated in a follow-up survey that included standardized items to capture COVID-19 cases, as well as questions about hospitalization and vaccinations. Associations were evaluated in crude and adjusted logistic regression models.

RESULTS

A total of 268 (44%) participants self-reported or met symptom criteria for having had COVID-19 at least once. All models found a positive association, with odds of COVID-19 increasing by between 4% and 30% for a 10 μg/m3 increase in coalmine fire-related PM2.5 exposure. However, the association was significant in only 2 of the 18 models. There were insufficient hospitalizations to examine severity (n = 7; 1%).

CONCLUSION

The findings are inconclusive on the effect of coalmine fire-related PM2.5 exposure on long-term vulnerability to COVID-19. Given the positive association that was robust to modelling variations as well as evidence for a causal mechanism, it would be prudent to treat PM2.5 from fire events as a long-term risk factor until more evidence accumulates.

Advancing Population Health Through Open Environmental Data Platforms

Data stand as the foundation for studying, evaluating, and addressing the multifaceted challenges within environmental health research. This chapter highlights the contributions of the Canadian Urban Environmental Health Research Consortium (CANUE) in generating and democratizing access to environmental exposure data across Canada. Through a consortium-driven approach, CANUE standardizes a variety of datasets - including air quality, greenness, neighborhood characteristics, and weather and climatic factors - into a centralized, analysis-ready, postal code-indexed database. CANUE's mandate extends beyond data integration, encompassing the design and development of environmental health-related web applications, facilitating the linkage of data to a wide range of health databases and sociodemographic data, and providing educational training and events such as webinars, summits, and workshops. The operational and technical aspects of CANUE are explored in this chapter, detailing its human resources, data sources, computational infrastructure, and data management practices. These efforts collectively enhance research capabilities and public awareness, fostering strategic collaboration and generating actionable insights that promote physical and mental health and well-being.

Long-Term Exposure to AIR Pollution and COVID-19 Mortality and Morbidity in DENmark: Who Is Most Susceptible? (AIRCODEN)

INTRODUCTION

Early ecological studies have suggested a link between air pollution and Coronavirus Diseases 2019 (COVID-19); however, the evidence from individual-level prospective cohort studies is still sparse. Here, we have examined, in a general population, whether long-term exposure to air pollution is associated with the risk of contracting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and developing severe COVID-19, resulting in hospitalization or death and who is most susceptible. We also examined whether long-term exposure to air pollution is associated with hospitalization or death due to COVID-19 in those who have tested positive for SARS-CoV-2.

METHODS

We included all Danish residents 30 years or older who resided in Denmark on March 1, 2020. and followed them in the National COVID-19 Surveillance System until first positive test (incidence), COVID-19 hospitalization, or death until April 26, 2021. We estimated mean levels of nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter <2.5 μm (PM2.5), black carbon (BC), and ozone (O3) at cohort participants' residence in 2019 by the Danish Eulerian Hemispheric Model/Urban Background Model. We used Cox proportional hazard models to estimate the associations of air pollutants with COVID-19 incidence, hospitalization, and mortality adjusting for age, sex, and socioeconomic status (SES) at the individual and area levels. We examined effect modification by age, sex, SES (education, income, wealth, employment), and comorbidities with cardiovascular disease, respiratory disease, acute lower respiratory infections, diabetes, lung cancer, and dementia. We used logistic regression to examine association of air pollutants with COVID-19-related hospitalization or death among SARS-CoV-2 positive patients, adjusting for age, sex, individual- and area-level SES.

RESULTS

Of 3,721,810 people, 138,742 were infected, 11,270 hospitalized, and 2,557 died from COVID-19 during 14 months of follow-up. We detected strong positive associations with COVID-19 incidence, with hazard ratio (HR) and 95% confidence interval (CI) of 1.10 (CI: 1.05-1.14) per 0.5-μg/m3 increase in PM2.5 and 1.18 (CI: 1.14-1.23) per 3.6-μg/m3 increase in NO2. For COVID-19 hospitalizations and for COVID-19 deaths, corresponding HRs and 95% CIs were 1.09 (CI: 1.01-1.17) and 1.19 (CI: 1.12-1.27), respectively for PM2.5, and 1.23 (CI: 1.04-1.44) and 1.18 (CI: 1.03-1.34), respectively for NO2. We also found strong positive and statistically significant associations with BC and negative associations with O3. Associations were strongest in those aged 65 years old or older, participants with the lowest SES, and patients with chronic cardiovascular, respiratory, metabolic, lung cancer, and neurodegenerative disease. Among 138,742 individuals who have tested positive for SARS-Cov-2, we detected positive association with COVID-19 hospitalizations (N = 11,270) with odds ratio and 95% CI of 1.04 (CI: 1.01- 1.08) per 0.5-μg/m3 increase in PM2.5 and 1.06 (CI: 1.01-1.12) per 3.6-μg/m3 increase in NO2, but no association with PM with an aerodynamic diameter <10 μm (PM10), BC, or O3, and no association between any of the pollutants and COVID-19 mortality (N = 2,557).

CONCLUSIONS

This large nationwide study provides strong new evidence in support of association between long-term exposure to air pollution and COVID-19.

Transcriptomic alterations in the olfactory bulb induced by exposure to air pollution: Identification of potential biomarkers and insights into olfactory system function

This study evaluated how exposure to the ubiquitous air pollution component, ultrafine particles (UFPs), alters the olfactory bulb (OB) transcriptome. The study utilised a whole-body inhalation chamber to simulate real-life conditions and focused on UFPs due to their high translocation and deposition ability in OBs as well as their prevalence in ambient air. Female C57BL/6J mice were exposed to clean air or to freshly generated combustion derived UFPs for two weeks, after which OBs were dissected and mRNA transcripts were investigated using RNA sequencing analysis. For the first time, transcriptomics was applied to determine changes in mRNA expression levels occurring after subacute exposure to UFPs in the OBs. We found forty-five newly described mRNAs to be involved in air pollution-induced responses, including genes involved in odorant binding, synaptic regulation, and myelination signalling pathway, providing new gene candidates for future research. This study provides new insights for the environmental science and neuroscience fields and nominates future research directions.