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

Investigation of potential collider bias in estimating the association between long-term exposure to air pollution and COVID-19 mortality

Background

Patient-based cohorts were frequently used to investigate air pollution-related coronavirus disease 2019 (COVID-19) evidence, which can be subject to collider bias. However, this bias has not been explored. We aimed to quantify and adjust the collider bias by limiting study population to patients with COVID-19 when estimating the association between long-term exposure to air pollution (LTAP) and COVID-19 mortality.

Methods

In a register-based cohort study including 3,721,813 residents aged 30 or older in Denmark, we followed them from 1 March 2020 to 26 April 2021. We estimated the hazard ratios of COVID-19 mortality associated with LTAP. We calculated the relative hazard ratios (RHR) by comparing the hazard ratios of COVID-19 mortality among the general population and patients (infected or hospitalized) to quantify the impact of collider bias, and further applied inverse probability weighting (IPW) to adjust the potential collider bias.

Result

We detected 138,742 positive for SARS-CoV-2, 11,270 COVID-19 hospitalizations, and 2557 deaths from COVID-19 during the study period. Although the demographic and socioeconomic characteristics differed among the three populations (general population, infected individuals, and hospitalized patients), infected and hospitalized patients experienced higher air pollution exposure compared with the general population. We observed greater associations of exposure to air pollution with COVID-19 mortality in the general population compared with the COVID-19 infected and hospitalized patients, with RHR of 0.88 (0.82, 0.95) and 0.85 (0.74, 0.97) per 0.55 µg/m3 increase in fine particulate matter (PM2.5) when we limited to infected and hospitalized patients, respectively. Similar association was also observed with nitrogen dioxide exposure. After applying IPW, we observed moderate increase in the estimated association, with RHR altered to null.

Conclusion

Our findings suggest that associations between LTAP and COVID-19 mortality are likely underestimated in patient-based cohorts due to potential collider bias, while IPW could be a useful tool to adjust such bias.

Impact of weather, air pollution and virus variant on COVID-19 with acute respiratory failure in the emergency department

BACKGROUND

Air pollution and meteorological factors are thought to contribute to increased risk of severe COVID-19, but the evidence is still controversial. This study aimed to assess the effects of weather, air pollution and SARS-CoV-2 variants on COVID-19 with acute respiratory failure (ARF) and investigate the respiratory management in the emergency department (ED).

METHODS

We conducted a prospective observational study of 469 COVID-19 ED visits from March 1, 2020 to December 31, 2023. Data on air pollutant levels and weather variables was obtained from Taiwan Central Weather Bureau (CWB) and Environmental Protection Administration (EPA). The generalized linear models extending bivariate and multivariable Poisson regression models were used to estimate the association between the weather variables, air pollutants, virus variants, and COVID-19 patients with ARF.

RESULTS

Among the 469 patients, 64 % were male, and the mean age was 70 ± 6 years. Overall, 18 % (n = 84) of the cohort died, 43 % (n = 200) were intubated, and 70 % (n = 326) were admitted to the ICU. We observed significantly positive associations between PM2.5, PM10, temperature, and wind speed with ED visits for COVID-19 with ARF. Every 1 μg/m3 increase in PM2.5, PM10, each 1 m/s increase in wind speed, and 1 °C increase in temperature were significantly associated with a 34.1 % (95 % CI: 8.2 %-66.1 %), 45.4 % (95 % CI: 39.4 %-46.6 %), 19.0 % (95 % CI: 11.4 %-27.0 %), and 10.4 % (95 % CI: 6.9 %-13.9 %) increase in the average daily number of COVID-19 patients respectively. In contrast, NO2, SO2, relative humidity, and sunshine were significantly associated with lower average daily numbers of severe COVID-19 patients. Moreover, virus variants were significantly positive associations between humidity and sunshine, 53.9 % (95 % CI: 37.0 %-70.3 %) and 5.4 % (95 % CI: 0.6 %-10.4 %) respectively.

CONCLUSION

The relationship between air pollution, climate change, virus variants, and COVID-19 is highly intricate. Air pollution exacerbates the severity of COVID-19, climate change influences virus transmission and human immune responses, and viral variants make pandemic control more challenging. These interactions are critical for future prediction, prevention and responses to global health crises.

Time series analysis of the impact of air pollutants on influenza-like illness in Changchun, China

BACKGROUND

Emerging evidence links air pollution to respiratory infections, yet systematic assessments in cold regions remain limited. This study evaluates the short-term effects of six major air pollutants on influenza-like illness (ILI) incidence in Changchun, Northeast China, with implications for air quality management and respiratory disease prevention.

METHODS

ILI surveillance data from Changchun were extracted from "China Influenza Surveillance Network" and the ambient air quality monitoring data of the city were collected from 2017 to 2022. A generalized additive model (GAM) with quasi-Poisson regression analysis was employed to quantify pollutant-ILI associations, adjusting for meteorological factors and temporal trends.

RESULTS

Among 84,010 ILI cases, immediate exposure effects were observed: each 10 µg/m³ increase in PM2.5 (ER = 1.00%, 95% CI: 0.63-1.37%), PM10 (0.90%, 0.57-1.24%), and O3 (1.05%, 0.44-1.67%) significantly elevated ILI risks. Young and middle-aged individuals (25-59 years old) exhibited the highest susceptibility to five pollutants (PM2.5, PM10, SO2, O3, and CO), and age subgroups under 15 years old exhibited susceptibility to NO2. Post-COVID-19 outbreak showed amplified effects across all pollutants (p < 0.05 vs. pre-outbreak). The effects of PM2.5, PM10, SO2 and O3 on ILI cases were greater in the cold season (October to March) (p < 0.05).

CONCLUSIONS

PM2.5, PM10, and O3 exposure significantly increases ILI risks in Changchun, particularly among young/middle-aged populations during cold seasons and post-pandemic periods. These findings underscore the urgency for real-time air quality alerts and targeted protection strategies during high-risk periods to mitigate respiratory health burdens.

Independent and combined effects of long-term air pollution exposure and genetic predisposition on COVID-19 severity: A population-based cohort study

The relationships between air pollution, genetic susceptibility, and COVID-19-related outcomes, as well as the potential interplays between air pollution and genetic susceptibility, remain largely unexplored. The Cox proportional hazards model was used to assess associations between long-term exposure to air pollutants and the risk of COVID-19 outcomes (infection, hospitalization, and death) in a COVID-19-naive cohort (n = 458,396). Additionally, associations between air pollutants and the risk of COVID-19 severity (hospitalization and death) were evaluated in a COVID-19 infection cohort (n = 110,216). Furthermore, this study investigated the role of host genetic susceptibility in the relationships between exposure to air pollutants and the development of COVID-19-related outcomes. Long-term exposure to air pollutants was significantly associated with an increased risk of COVID-19-related outcomes in the COVID-19 naive cohort. Similarly, in COVID-19 infection cohort, hazard ratios (HRs) for COVID-19 hospital admission were 1.23 (1.19, 1.27) for PM2.5 and 1.22 (1.17, 1.26) for PM10, whereas HRs for COVID-19 death were 1.28 (1.18, 1.39) for PM2.5 and 1.25 (1.16, 1.36) for PM10. Notably, significant interactions were found between PM2.5/PM10 and genetic susceptibility in COVID-19 death. In COVID-19 infection cohort, participants with both high genetic risk and high air pollutants exposure had 1.86- to 1.97-fold and 1.91- to 2.14-fold higher risk of COVID-19 hospitalization and death compared to those with both low genetic risk and low air pollutants exposure. Exposure to air pollution is significantly associated with an increased burden of severe COVID-19, and air pollution-gene interactions may play a crucial role in the development of COVID-19-related outcomes.

Associations of long-term exposure to nitrogen oxides with all-cause and cause-specific mortality

Associations between long-term exposure to nitrogen oxides (NOx) and cause-specific mortality remain insufficiently explored. This study utilizes data from 502,040 participants registered in the UK Biobank. Time-varying Cox regression is used to estimate mortality risks associated with NOx. Cause-specific mortality risks, including non-accidental, accidental and 15 major disease categories across 103 subcategories, are assessed for each 10 μg/m3 increase in NOx. Positive associations are observed between NOx and mortality from all-cause (HR: 1.036; 95% CI: 1.024, 1.049) and non-accidental diseases (HR: 1.032; 95% CI: 1.019, 1.045). We further identify 20 specific diseases related to NOx, notably respiratory diseases, mental and behavioral disorders, and circulatory diseases, with generally linear exposure-response relationships. Sex and residential areas are potential modifiers of the observed associations. Our findings suggest long-term exposure to NOx may increase mortality risks from a range of diseases, emphasizing the urgent need for clean air policies to alleviate the health burden.

Association between long-term exposure to air pollutants with breakthrough SARS-CoV-2 infections and antibody responses among COVID-19 vaccinated older adults in Northern Italy

AIMS

To investigate the association between long-term exposure to PM2.5, PM10, NO2 and O3 with SARS-CoV-2 breakthrough infections and COVID-19 vaccine-induced antibody responses in a northern Italian population-based sample of older adults.

METHODS

Within an ongoing prospective population-based study, we followed-up 1326 vaccinated individuals aged 65-83 years, with no prior SARS-CoV-2 infection, for their first positive SARS-CoV-2 swab until December 31st, 2022. We assessed spike IgG antibody levels in most participants (n = 1206). The 2019 annual mean levels of air pollutants derived from combined use of chemical-transport and random-Forest models (spatial resolution: 1Kmq) were individually assigned based on the latest residence address. We estimated multivariable-adjusted associations (per 1 interquartile range increase, IQR) of air pollutants with breakthrough infections using Cox models with time-dependent vaccine exposure; and with percent change in the IgG geometric mean using generalized additive models.

RESULTS

The mean (SD) age was 74.9 ± 4.1 years, and 50% were women. An IQR (1.2 μg/m3) increase in long-term PM2.5 exposure was associated with a 52% increase in breakthrough infection risk following a second vaccine and a 26% increase following a third vaccine. The effect vanished with the further increment of vaccination doses. Associations for NO2 were inconsistent. Ozone was negatively associated with breakthrough infection risk, but this association reversed in bi-pollutant models adjusting for PM2.5. PM2.5 was associated with a -7.3% (-13.9% to -0.2%) reduction in vaccine-induced IgG levels. The reduction became more pronounced as the time delay from vaccination increased, and with adjustment for NO2 co-exposure.

CONCLUSION

In our population of vaccinated older adults, fine particulate matter exposure was independently associated with a higher risk of SARS-CoV-2 breakthrough infection and a lower antibody response, both effects being influenced by timely and repeated vaccination schedule.

Long-term exposure to air pollution and lower respiratory infections in a large population-based adult cohort in Catalonia

BACKGROUND

Evidence is limited regarding the role of air pollution in acute lower respiratory infections among adults. We assessed the influence of long-term air pollution exposure on hospital admission for lower respiratory infections and whether there are vulnerable subgroups.

METHODS

We used a populational cohort in Catalonia, Spain, comprising 3,817,820 adults residing in Catalonia as of January 1, 2015. Air pollution exposure was assigned to individuaĺs residential address using locally-developed models. We characterized the concentration-response functions between long-term air pollution exposure and hospital admission for lower respiratory infections between 2015 and 2019. We assessed interaction between exposure and clinical and socio-economic factors on multiplicative and additive scales.

RESULTS

An interquartile range exposure increase was associated with an 8 % (95 % Confidence Interval: 5 %-11 %) for Nitrogen Dioxide, 10 % (95 % Confidence Interval: 8 %-13 %) for Particulate Matter with diameter equal to or smaller than 2.5 µm, 5 % (95 % Confidence Interval: 3 %-7%) for Particulate Matter with diameter equal to or smaller than 10 µm and 18 % (95 % Confidence Interval: 14 %-22%) for ozone (adjusted by Nitrogen Dioxide) increase in hospital admissions for respiratory infections. Concentration-response functions were non-linear, with steeper slopes at exposures below the median or at most extreme high values. Associations were consistently greater for individuals over 65 years or with hypertension diagnosis and males.

CONCLUSIONS

Long-term exposure to air pollution was positively associated with hospital admission for lower respiratory infections. Individuals who were older than 65 years, hypertensive or male were most vulnerable.

Interactive Effects of Long-term Exposure to Air Pollutants on SARS-CoV-2 Infection and Severity: A Northern Italian Population-based Cohort Study

BACKGROUND

We examined interactions, to our knowledge not yet explored, between long-term exposures to particulate matter (PM 10 ) with nitrogen dioxide (NO 2 ) and ozone (O 3 ) on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity and severity.

METHODS

We followed 709,864 adult residents of Varese Province from 1 February 2020 until the first positive test, COVID-19 hospitalization, or death, up to 31 December 2020. We estimated residential annual means of PM 10 , NO 2 , and O 3 in 2019 from chemical transport and random-forest models. We estimated the interactive effects of pollutants with urbanicity on SARS-CoV-2 infectivity, hospitalization, and mortality endpoints using Cox regression models adjusted for socio-demographic factors and comorbidities, and additional cases due to interactions using Poisson models.

RESULTS

In total 41,065 individuals were infected, 5203 were hospitalized and 1543 died from COVID-19 during follow-up. Mean PM 10 was 1.6 times higher and NO 2 2.6 times higher than WHO limits, with wide gradients between urban and nonurban areas. PM 10 and NO 2 were positively associated with SARS-CoV-2 infectivity and mortality, and PM 10 with hospitalizations in urban areas. Interaction analyses estimated that the effect of PM 10 (per 3.5 µg/m 3 ) on infectivity was strongest in urban areas [hazard ratio (HR) = 1.12; 95% CI =1.09, 1.16], corresponding to 854 additional cases per 100,000 person-years, and in areas at high NO 2 co-exposure (HR = 1.15; 1.08, 1.22). At higher levels of PM 10 co-exposure, the protective association of O 3 reversed (HR =1.32, 1.17, 1.49), yielding 278 additional cases per µg/m 3 increase in O 3 . We estimated similar interactive effects for severity endpoints.

CONCLUSIONS

We estimate that interactive effects between pollutants exacerbated the burden of the SARS-CoV-2 pandemic in urban areas.

Residential greenspace and COVID-19 morbidity and mortality: A nationwide cohort study in Denmark

BACKGROUND

Identifying modifiable environmental determinants of health is important for improving the resilience of populations to infectious disease. We examined the association between residential greenspace and COVID-19 morbidity and mortality using a Danish Nationwide Cohort, and estimate the potential health benefits of greening initiatives.

METHODS

We followed all Danish adults aged 50 or older (N = 2,111,233) using the Danish National COVID-19 Surveillance System for COVID-19 incident infection, hospitalization and mortality, from 1 March 2020 to 26 April 2021. Greenspace was characterized using Normalized Difference Vegetation Index (NDVI) at 300x300m grid-cell level and linked to residential addresses. We used Cox regression to assess the association between greenspace and COVID-19 morbidity and mortality, and applied effect modification analyses to identify the most susceptible groups by sociodemographic status and comorbidity. Following a health impact assessment (HIA), we also estimated the preventable burden of disease attributable to greenspace under different counterfactual scenarios.

RESULTS

During an average of 14 months follow-up, 62,880 participants were infected with SARS-CoV-2, of whom 8,759 were hospitalized, and 2,382 died, with COVID-19. We observed a negative association between residential greenspace and COVID-19 morbidity and mortality, with hazard ratios (95 % confidence interval) of 0.98 (0.97, 0.99) for SARS-CoV-2 infection, 0.97 (0.94, 0.99) for COVID-19 hospitalization, and 0.96 (0.91, 1.01) for COVID-19 mortality per interquartile range (0.08 unit) increase in NDVI. Stronger associations were observed in the elderly, those with lower SES, and major chronic diseases than their corresponding groups. Regarding the HIA, we estimated that increasing greenspace around residences up to WHO recommended levels would have prevented 8-14 % of COVID-19 events during the first 14 months, with the largest benefits among those with the lowest income, education, or without employment.

CONCLUSION

Greening initiatives in urban areas could help prevent COVID-19, and likely other infectious disease, with socially disadvantaged groups benefiting most.

Shedding light on the cellular mechanisms involved in the combined adverse effects of fine particulate matter and SARS-CoV-2 on human lung cells

Airborne pathogens represent a topic of scientific relevance, especially considering the recent COVID-19 pandemic. Air pollution, and particulate matter (PM) in particular, has been proposed as a possible risk factor for the onset and spread of pathogen-driven respiratory diseases. Regarding SARS-CoV-2 infection, exposure to fine PM (PM2.5, particles with an aerodynamic diameter < 2.5 μm) has been associated with increased incidence of the COVID-19 disease. To provide useful insights into the mechanisms through which PM might be involved in infection, we exposed human lung cells (A549) to PM2.5 and SARS-CoV-2, to evaluate the toxicological properties and the molecular pathways activated when airborne particles are combined with viral particles. Winter PM2.5 was collected in a metropolitan urban area and its physico-chemical composition was analyzed. A549 cells were exposed to SARS-CoV-2 concomitantly or after pre-treatment with PM2.5. Inflammation, oxidative stress and xenobiotic metabolism were the main pathways investigated. Results showed that after 72 h of exposure PM2.5 significantly increased the expression of the angiotensin-converting enzyme 2 (ACE2) receptor, which is one of the keys used by the virus to infect host cells. We also analyzed the endosomal route in the process of internalization, by studying the expression of RAB5 and RAB7. The results show that in cells pre-activated with PM and then exposed to SARS-CoV-2, RAB5 expression is significantly increased. The activation of the inflammatory process was then studied. Our findings show an increase of pro-inflammatory markers (NF-kB and IL-8) in cells pre-activated with PM for 72 h and subsequently exposed to the virus for a further 24 h, further demonstrating that the interaction between PM and SARS-CoV-2 determines the severity of the inflammatory responses in lung epithelial cells. In conclusion, the study provides mechanistic biological evidence of PM contribution to the onset and progression of viral respiratory diseases in exposed populations.

Epidemiology and SARIMA model of deaths in a tertiary comprehensive hospital in Hangzhou from 2015 to 2022

BACKGROUND

By analysing the deaths of inpatients in a tertiary hospital in Hangzhou, this study aimed to understand the epidemiological distribution characteristics and the composition of the causes of death. Additionally, this study aimed to predict the changing trend in the number of deaths, providing valuable insights for hospitals to formulate relevant strategies and measures aimed at reducing mortality rates.

METHODS

In this study, data on inpatient mortality at a tertiary hospital in Hangzhou from 2015 to 2022 were obtained via the population information registration system of the Chinese Center for Disease Control and Prevention. The death data of inpatients were described and analysed through a retrospective study. Excel 2016 was utilized for data sorting, and SPSS 22.0 software was employed for data analysis. The statistical inference of single factor differences was conducted via χ2 tests. The SARIMA model was established via the forecast, aTSA, and tseries software packages (version 4.3.0) to forecast future changes in the number of deaths.

RESULTS

A total of 1938 inpatients died at the tertiary hospital in Hangzhou, with the greatest number of deaths occurring in 2022 (262, 13.52%). The sex ratio was 2.22:1, and there were significant differences between sexes in terms of age, marital status, educational level, and place of residence (P < 0.05). The percentage of males in the groups aged of 20 to 29 and 30 to 39 years was significantly greater than that of females (χ2 = 46.905, P < 0.001). More females than males died in the widowed group, and divorced and married males experienced a greater number of deaths than divorced and married females did (χ2 = 61.130, P < 0.001). The proportions of male students with a junior college and senior high school education were significantly greater than that of female students (χ2 = 12.310, P < 0.05). The primary causes of mortality within the hospital setting included circulatory system diseases, injury, poisoning, tumours, and respiratory system diseases. These leading factors accounted for 86.12% of all recorded deaths. Finally, the SARIMA (2, 1, 1) (1, 1, 1)12 model was determined to be the optimal model, with an AIC of 380.23, a BIC of 392.79, and an AICc of 381.81. The MAPE was 14.99%, indicating a satisfactory overall fit of this model. The relative error between the predicted and actual number of deaths in 2022 was 8.02%. Therefore, the SARIMA (2, 1, 1) (1, 1, 1)12 model demonstrates good predictive performance.

CONCLUSIONS

Hospitals should enhance the management of sudden cardiac death, acute myocardial infarction, severe craniocerebral injury, lung cancer, and lung infection to reduce the mortality rate. The SARIMA model can be employed for predicting the number of deaths.

Air Pollution in Relation to COVID-19 Morbidity and Mortality: A Large Population-Based Cohort Study in Catalonia, Spain (COVAIR-CAT)

INTRODUCTION

Evidence from epidemiological studies based on individual-level data indicates that air pollution may be associated with coronavirus disease 2019 (COVID-19) severity. We aimed to test whether (1) long-term exposure to air pollution is associated with COVID-19-related hospital admission or mortality in the general population; (2) short-term exposure to air pollution is associated with COVID-19-related hospital admission following COVID-19 diagnosis; (3) there are vulnerable population subgroups; and (4) the influence of long-term air pollution exposure on COVID-19-related hospital admissions differed from that for other respiratory infections.

METHODS

We constructed a cohort covering nearly the full population of Catalonia through registry linkage, with follow- up from January 1, 2015, to December 31, 2020. Exposures at residential addresses were estimated using newly developed spatiotemporal models of nitrogen dioxide (NO23), particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5), particulate matter ≤10 μm in aerodynamic diameter (PM10), and maximum 8-hr-average ozone (O3) at a spatial resolution of 250 m for the period 2018-2020.

RESULTS

The general population cohort included 4,660,502 individuals; in 2020 there were 340,608 COVID-19 diagnoses, 47,174 COVID-19-related hospital admissions, and 10,001 COVID-19 deaths. Mean (standard deviation) annual exposures were 26.2 (10.3) μg/m3 for NO2, 13.8 (2.2) μg/m3 for PM2.5, and 91.6 (8.2) μg/m3 for O3. In Aim 1, an increase of 16.1 μg/m3 NO2 was associated with a 25% (95% confidence interval [CI]: 22%-29%) increase in hospitalizations and an 18% (10%-27%) increase in deaths. In Aim 2, cumulative air pollution exposure over the previous 7 days was positively associated with COVID-19-related hospital admission in the second pandemic wave (June 20 to December 31, 2020). Associations of exposure were driven by exposure on the day of the hospital admission (lag0). Associations between short-term exposure to air pollution and COVID-19-related hospital admission were similar in all population subgroups. In Aim 3, individuals with lower individual- and area-level socioeconomic status (SES) were identified as particularly vulnerable to the effects of long-term exposure to NO2 and PM2.5 on COVID-19-related hospital admission. In Aim 4, long-term exposure to air pollution was associated with hospital admission for influenza and pneumonia: (6%; 95% CI: 2-11 per 16.4-μg/m3 NO2 and 5%; 1-8 per 2.6-μg/m3 PM2.5) as well as for all lower respiratory infections (LRIs) (18%; 14-22 per 16.4-μg/m3 NO2 and 14%; 11-17 per 2.6-μg/m3 PM2.5) before the COVID-19 pandemic. Associations for COVID-19-related hospital admission were larger than those for influenza or pneumonia for NO2, PM2.5, and O3 when adjusted for NO2.

CONCLUSIONS

Linkage across several registries allowed the construction of a large population-based cohort, tracking COVID-19 cases from primary care and testing data to hospital admissions, and death. Long- and short-term exposure to ambient air pollution were positively associated with severe COVID-19 events. The effects of long-term air pollution exposure on COVID-19 severity were greater among those with lower individual- and area-level SES.

Long-Term Exposure to Air Pollution and Risk of Acute Lower Respiratory Infections in the Danish Nurse Cohort

Rationale: Air pollution is a major risk factor for chronic cardiorespiratory diseases, affecting the immune and respiratory systems' functionality, but epidemiological evidence in respiratory infections remains sparse. Objectives: We aimed to assess the association of long-term exposure to ambient air pollution with the risk of developing new and recurrent acute lower respiratory infections (ALRIs), characterized by persistently severe symptoms necessitating hospital contact, and identify the potential susceptible populations by socioeconomic status, smoking, physical activity status, overweight, and comorbidity with chronic lung disease. Methods: We followed 23,912 female nurses from the Danish Nurse Cohort (age >44 yr) from baseline (1993 or 1999) until 2018 for incident and recurrent ALRIs defined by hospital contact (inpatient, outpatient, and emergency room) data from the National Patient Register. Residential annual mean concentrations of fine particulate matter, nitrogen dioxide (NO2), and black carbon were modeled using the Danish Eulerian Hemispheric Model/Urban Background Model/Air Geographic Information System. We used marginal Cox models with time-varying exposures to assess the association of 3-year running mean air pollution level with incident and recurrent ALRIs and examined effect modification by age, socioeconomic status, smoking, physical activity, body mass index, and comorbidity with asthma or chronic obstructive pulmonary disease (COPD). Results: During a 21.3-year mean follow-up, 4,746 ALRIs were observed, of which 2,553 were incident. We observed strong positive associations of all three pollutants with incident ALRIs, with hazard ratios and 95% confidence intervals of 1.19 (1.08-1.31) per 2.5 μg/m3 for fine particulate matter, 1.17 (1.11-1.24) per 8.0 μg/m3 for NO2, and 1.09 (1.05-1.12) per 0.3 μg/m3 for black carbon, and slightly stronger associations with recurrent ALRIs. Associations were strongest in patients with COPD and nurses with low physical activity. Conclusions: Long-term exposure to air pollution at low levels was associated with risks of new and recurrent ALRIs, with patients with COPD and physically inactive subjects most vulnerable.

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.

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.

Environmental and geographical factors influencing the spread of SARS-CoV-2 over 2 years: a fine-scale spatiotemporal analysis

Introduction

Since its emergence in late 2019, the SARS-CoV-2 virus has led to a global health crisis, affecting millions and reshaping societies and economies worldwide. Investigating the determinants of SARS-CoV-2 diffusion and their spatiotemporal dynamics at high spatial resolution is critical for public health and policymaking.

Methods

This study analyses 194,682 georeferenced SARS-CoV-2 RT-PCR tests from March 2020 and April 2022 in the canton of Vaud, Switzerland. We characterized five distinct pandemic periods using metrics of spatial and temporal clustering like inverse Shannon entropy, the Hoover index, Lloyd's index of mean crowding, and the modified space-time DBSCAN algorithm. We assessed the demographic, socioeconomic, and environmental factors contributing to cluster persistence during each period using eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), to consider non-linear and spatial effects.

Results

Our findings reveal important variations in the spatial and temporal clustering of cases. Notably, areas with flatter epidemics had higher total attack rate. Air pollution emerged as a factor showing a consistent positive association with higher cluster persistence, substantiated by both immission models and, to a lesser extent, tropospheric NO2 estimations. Factors including population density, testing rates, and geographical coordinates, also showed important positive associations with higher cluster persistence. The socioeconomic index showed no significant contribution to cluster persistence, suggesting its limited role in the observed dynamics, which warrants further research.

Discussion

Overall, the determinants of cluster persistence remained across the study periods. These findings highlight the need for effective air quality management strategies to mitigate air pollution's adverse impacts on public health, particularly in the context of respiratory viral diseases like COVID-19.

Association between long-term ozone exposure and readmission for chronic obstructive pulmonary disease exacerbation

The relationship between long-term ozone (O₃) exposure and readmission for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) remains elusive. In this study, we collected individual-level information on AECOPD hospitalizations from a standardized electronic database in Guangzhou from January 1, 2014, to December 31, 2015. We calculated the annual mean O₃ concentration prior to the dates of the index hospitalization for AECOPD using patients' residential addresses. Employing Cox proportional hazards models, we assessed the association between long-term O₃ concentration and the risk of AECOPD readmission across several time frames (30 days, 90 days, 180 days, and 365 days). We estimated the disease and economic burden of AECOPD readmissions attributable to O₃ using a counterfactual approach. Of the 4574 patients included in the study, 1398 (30.6%) were readmitted during the study period, with 262 (5.7%) readmitted within 30 days. The annual mean O₃ concentration was 90.3 μg/m3 (standard deviation [SD] = 8.2 μg/m3). A 10-μg/m3 increase in long-term O₃ concentration resulted in a hazard ratio (HR) for AECOPD readmission within 30 days of 1.28 (95% confidence interval [CI], 1.09 to 1.49), with similar results for readmission within 90, 180, and 365 days. Older patients (aged 75 years or above) and males were more susceptible (HR, 1.33; 95% CI, 1.10-1.61 and HR, 1.29; 95% CI, 1.09-1.53, respectively). The population attributable fraction for 30-day readmission due to O₃ exposure was 29.0% (95% CI, 28.4%-30.0%), and the attributable mean cost per participant was 362.3 USD (354.5-370.2). Long-term exposure to elevated O₃ concentrations is associated with an increased risk of AECOPD readmission, contributing to a significant disease and economic burden.

Investigating distributions of inhaled aerosols in the lungs of post-COVID-19 clusters through a unified imaging and modeling approach

BACKGROUND

Recent studies, based on clinical data, have identified sex and age as significant factors associated with an increased risk of long COVID. These two factors align with the two post-COVID-19 clusters identified by a deep learning algorithm in computed tomography (CT) lung scans: Cluster 1 (C1), comprising predominantly females with small airway diseases, and Cluster 2 (C2), characterized by older individuals with fibrotic-like patterns. This study aims to assess the distributions of inhaled aerosols in these clusters.

METHODS

140 COVID survivors examined around 112 days post-diagnosis, along with 105 uninfected, non-smoking healthy controls, were studied. Their demographic data and CT scans at full inspiration and expiration were analyzed using a combined imaging and modeling approach. A subject-specific CT-based computational model analysis was utilized to predict airway resistance and particle deposition among C1 and C2 subjects. The cluster-specific structure and function relationships were explored.

RESULTS

In C1 subjects, distinctive features included airway narrowing, a reduced homothety ratio of daughter over parent branch diameter, and increased airway resistance. Airway resistance was concentrated in the distal region, with a higher fraction of particle deposition in the proximal airways. On the other hand, C2 subjects exhibited airway dilation, an increased homothety ratio, reduced airway resistance, and a shift of resistance concentration towards the proximal region, allowing for deeper particle penetration into the lungs.

CONCLUSIONS

This study revealed unique mechanistic phenotypes of airway resistance and particle deposition in the two post-COVID-19 clusters. The implications of these findings for inhaled drug delivery effectiveness and susceptibility to air pollutants were explored.

ERS International Congress 2023: highlights from the Basic and Translational Sciences Assembly

Early career members of Assembly 3 (Basic and Translational Sciences) of the European Respiratory Society (ERS) summarise the key messages discussed during six selected sessions that took place at the ERS International Congress 2023 in Milan, Italy. Aligned with the theme of the congress, the first session covered is "Micro- and macro-environments and respiratory health", which is followed by a summary of the "Scientific year in review" session. Next, recent advances in experimental methodologies and new technologies are discussed from the "Tissue modelling and remodelling" session and a summary provided of the translational science session, "What did you always want to know about omics analyses for clinical practice?", which was organised as part of the ERS Translational Science initiative's aims. The "Lost in translation: new insights into cell-to-cell crosstalk in lung disease" session highlighted how next-generation sequencing can be integrated with laboratory methods, and a final summary of studies is presented from the "From the transcriptome landscape to innovative preclinical models in lung diseases" session, which links the transcriptome landscape with innovative preclinical models. The wide range of topics covered in the selected sessions and the high quality of the research discussed demonstrate the strength of the basic and translational science being presented at the international respiratory conference organised by the ERS.

Indoor air humidity revisited: Impact on acute symptoms, work productivity, and risk of influenza and COVID-19 infection

Recent epidemiological and experimental findings reconfirm that low indoor air humidity (dry air) increases the prevalence of acute eye and airway symptoms in offices, result in lower mucociliary clearance in the airways, less efficient immune defense, and deteriorate the work productivity. New epidemiological and experimental research also support that the environmental conditions for the risk of infection of influenza and COVID-19 virus is lowest in the Goldilocks zone of 40-60% relative humidity (RH) by decrease of the airways' susceptibility, which can be elevated by particle exposure. Furthermore, low RH increases the generation of infectious virus laden aerosols exhaled from infected people. In general, elevation of the indoor air humidity from dry air increases the health of the airways concomitantly with lower viability of infectious virus. Thus, the negative effects of ventilation with dry outdoor air (low absolute air humidity) should be assessed according to 1) weakened health and functionality of the airways, 2) increased viability and possible increased transmissibility of infectious virus, and 3) evaporation of virus containing droplets to dry out to droplet nuclei (also possible at high room temperature), which increases their floating time in the indoor air. The removal of acid-containing ambient aerosols from the indoor air by filtration increases pH, viability of infectious viruses, and the risk of infection, which synergistically may further increase by particle exposure. Thus, the dilution of indoor air pollutants and virus aerosols by dry outdoor air ventilation should be assessed and compared with the beneficial health effects by control of the center zone of 40-60% RH, an essential factor for optimal functionality of the airways, and with the additional positive impact on acute symptoms, work productivity, and reduced risk of infection.

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.

Air pollution deaths attributable to fossil fuels: observational and modelling study

OBJECTIVES

To estimate all cause and cause specific deaths that are attributable to fossil fuel related air pollution and to assess potential health benefits from policies that replace fossil fuels with clean, renewable energy sources.

DESIGN

Observational and modelling study.

METHODS

An updated atmospheric composition model, a newly developed relative risk model, and satellite based data were used to determine exposure to ambient air pollution, estimate all cause and disease specific mortality, and attribute them to emission categories.

DATA SOURCES

Data from the global burden of disease 2019 study, observational fine particulate matter and population data from National Aeronautics and Space Administration (NASA) satellites, and atmospheric chemistry, aerosol, and relative risk modelling for 2019.

RESULTS

Globally, all cause excess deaths due to fine particulate and ozone air pollution are estimated at 8.34 million (95% confidence interval 5.63 to 11.19) deaths per year. Most (52%) of the mortality burden is related to cardiometabolic conditions, particularly ischaemic heart disease (30%). Stroke and chronic obstructive pulmonary disease both account for 16% of mortality burden. About 20% of all cause mortality is undefined, with arterial hypertension and neurodegenerative diseases possibly implicated. An estimated 5.13 million (3.63 to 6.32) excess deaths per year globally are attributable to ambient air pollution from fossil fuel use and therefore could potentially be avoided by phasing out fossil fuels. This figure corresponds to 82% of the maximum number of air pollution deaths that could be averted by controlling all anthropogenic emissions. Smaller reductions, rather than a complete phase-out, indicate that the responses are not strongly non-linear. Reductions in emission related to fossil fuels at all levels of air pollution can decrease the number of attributable deaths substantially. Estimates of avoidable excess deaths are markedly higher in this study than most previous studies for these reasons: the new relative risk model has implications for high income (largely fossil fuel intensive) countries and for low and middle income countries where the use of fossil fuels is increasing; this study accounts for all cause mortality in addition to disease specific mortality; and the large reduction in air pollution from a fossil fuel phase-out can greatly reduce exposure.

CONCLUSION

Phasing out fossil fuels is deemed to be an effective intervention to improve health and save lives as part the United Nations' goal of climate neutrality by 2050. Ambient air pollution would no longer be a leading, environmental health risk factor if the use of fossil fuels were superseded by equitable access to clean sources of renewable energy.

Cytokine fields and the polarization of the immune response

Certain cells that participate in the immune response are known to become polarized in their production of cytokines. It is postulated that, after initial polarization at the site of antigenic encounter, the different types of cell arriving at this site are induced to conform to the local cytokine field, implying that they share common regulatory circuits. As they migrate, these cells might, in turn, spread the particular cytokine field. Therefore, the field is 'infectious' in nature. Propagation of the cytokine field must be regulated somehow. The invasion of the cytokine field into an organ or the entire body could have major immunological consequences.