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

The Association between Exposure to Fine Particulate Air Pollution and the Trajectory of Internalizing and Externalizing Behaviors during Late Childhood and Early Adolescence: Evidence from the Adolescent Brain Cognitive Development (ABCD) Study

BACKGROUND

Exposure to high levels of fine particulate matter (PM) with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) via air pollution may be a risk factor for psychiatric disorders during adulthood. Yet few studies have examined associations between exposure and the trajectory of symptoms across late childhood and early adolescence.

OBJECTIVE

The current study evaluated whether PM 2.5 exposure at 9-11 y of age affects both concurrent symptoms as well as the longitudinal trajectory of internalizing and externalizing behaviors across the following 3 y. This issue was examined using multiple measures of exposure and separate measures of symptoms of internalizing disorders (e.g., depression, anxiety) and externalizing disorders (e.g., conduct disorder), respectively.

METHODS

In a sample of more than 10,000 youth from the Adolescent Brain Cognitive Development (ABCD) Study, we used a dataset of historical PM 2.5 levels and growth curve modeling to evaluate associations of PM 2.5 exposure with internalizing and externalizing symptom trajectories, as assessed by the Child Behavioral Check List. Three distinct measures of PM 2.5 exposure were investigated: annual average concentration during 2016, number of days in 2016 above the US Environmental Protection Agency (US EPA) 24-h PM 2.5 standards, and maximum 24-h concentration during 2016.

RESULTS

At baseline, higher number of days with PM 2.5 levels above US EPA standards was associated with higher parent-reported internalizing symptoms in the same year. This association remained significant up to a year following exposure and after controlling for PM 2.5 annual average, maximum 24-h level, and informant psychopathology. There was also evidence of an association between PM 2.5 annual average and externalizing symptom levels at baseline in females only.

DISCUSSION

Results suggested PM 2.5 exposure during childhood is associated with higher symptoms of internalizing and externalizing disorders at the time of exposure and 1 y later. In addition, effects of PM 2.5 exposure on youth internalizing symptoms may be most impacted by the number of days of exposure above US EPA standards in comparison with annual average and maximum daily exposure. https://doi.org/10.1289/EHP13427.

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.

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.

A conceptional model integrating geographic information systems (GIS) and social media data for disease exposure assessment

Although previous studies have acknowledged the potential of geographic information systems (GIS) and social media data (SMD) in assessment of exposure to various environmental risks, none has presented a simple, effective and user-friendly tool. This study introduces a conceptual model that integrates individual mobility patterns extracted from social media, with the geographic footprints of infectious diseases and other environmental agents utilizing GIS. The efficacy of the model was independently evaluated for selected case studies involving lead in the ground; particulate matter in the air; and an infectious, viral disease (COVID- 19). A graphical user interface (GUI) was developed as the final output of this study. Overall, the evaluation of the model demonstrated feasibility in successfully extracting individual mobility patterns, identifying potential exposure sites and quantifying the frequency and magnitude of exposure. Importantly, the novelty of the developed model lies not merely in its efficiency in integrating GIS and SMD for exposure assessment, but also in considering the practical requirements of health practitioners. Although the conceptual model, developed together with its associated GUI, presents a promising and practical approach to assessment of the exposure to environmental risks discussed here, its applicability, versatility and efficacy extends beyond the case studies presented in this study.

Household air pollution and risk of pulmonary tuberculosis in HIV-Infected adults

BACKGROUND

In low- and middle-income countries countries, millions of deaths occur annually from household air pollution (HAP), pulmonary tuberculosis (PTB), and HIV-infection. However, it is unknown whether HAP influences PTB risk among people living with HIV-infection.

METHODS

We conducted a case-control study among 1,277 HIV-infected adults in Bukavu, eastern Democratic Republic of Congo (February 2018 - March 2019). Cases had current or recent (<5y) PTB (positive sputum smear or Xpert MTB/RIF), controls had no PTB. Daily and lifetime HAP exposure were assessed by questionnaire and, in a random sub-sample (n=270), by 24-hour measurements of personal carbon monoxide (CO) at home. We used multivariable logistic regression to examine the associations between HAP and PTB.

RESULTS

We recruited 435 cases and 842 controls (median age 41 years, [IQR] 33-50; 76% female). Cases were more likely to be female than male (63% vs 37%). Participants reporting cooking for >3h/day and ≥2 times/day and ≥5 days/week were more likely to have PTB (aOR 1·36; 95%CI 1·06-1·75) than those spending less time in the kitchen. Time-weighted average 24h personal CO exposure was related dose-dependently with the likelihood of having PTB, with aOR 4·64 (95%CI 1·1-20·7) for the highest quintile [12·3-76·2 ppm] compared to the lowest quintile [0·1-1·9 ppm].

CONCLUSION

Time spent cooking and personal CO exposure were independently associated with increased risk of PTB among people living with HIV. Considering the high burden of TB-HIV coinfection in the region, effective interventions are required to decrease HAP exposure caused by cooking with biomass among people living with HIV, especially women.

From pandemic to syndemic: microbiota, pregnancy, and environment at a crossroad

Aim: SARS-CoV2 is the latest pandemic that have plagued the socio-health system as an epiphenomenon resulting from planetary resources abuse, crucial for biodiversity. The Anthropocene best defines the present epoch in which human activity irreversibly manipulates intricate and delicate geological and biological balances established over eons. The devastating ecological and socio-economic implications of COVID-19, underline the importance of updating the present pandemic framework to a syndemic. This paper stems from the need to suggest to scientists, doctors, and patients a mission that integrates responsibility from individual to collective health, from present to trans-generational, from human to the entire biotic network. Today's choices are crucial for the perspective on all levels: political, economic, and health as well as cultural.Methods: Research on PubMed and other specific web-sites journal was performed on the topic "Microbiota", "Covid-19", "Pandemic", "Zoonosis", "SARS-CoV-2", "Environmental Pollutants", "Epigenetics", "Fetal Programming", "Human Extinction". Data collected were analysed for an integrative model of interconnection between environment, pregnancy, SARS-CoV-2 infection, and microbiota. Moreover, systematic literature review allowed to summarise in a table information about the worst pandemics that afflicted the human species recently.Results: This paper offers a broad view of the current pandemic starting with pregnancy, the moment when a new life begins and the health trajectories of the unborn child are defined, which will inevitably have repercussions on his well-being. The fundamental role of the biodiversity-rich microbiota in avoiding the development of severe infectious diseases, is therefore highlighted. It is imperative to adjust the current reductionist paradigm based on mostly immediate symptom management towards a broader understanding of the spatial interconnection of ecological niches with human health and the impacts of today's choices on the future. Health and healthcare are elitist rather than egalitarian, therefore focusing on environmental health forces us to make a concerted and systemic effort that challenges political and economic barriers, which are biologically senseless. A healthy microbiota is essential to well-being, both by preventing chronic degenerative conditions, the infectiousness and pathogenicity of bacterial and viral diseases. SARS-CoV-2 should not be an exception. The human microbiota, forged by the first 1,000 days of life, is fundamental in shaping the health-disease trajectories, and by the everlasting exposome that is dramatically affected by the ecological disaster. Individual health is one world health whereas single and global well-being are interdependent in a space-time perspective.Conclusions: Is it not a convenient reductionism not to consider the COVID-19 emergency as a bio-social epiphenomenon of a far more devastating and multi-faceted crisis whose common denominator is the global biotic network loss of which humans are still part?

Using a time-varying LCAR-based strategy to investigate the spatiotemporal pattern of association between short-term exposure to particulate matter and COVID-19 incidence: a case study in the continental USA

Numerous studies have demonstrated that short-term exposure to particulate matter less than 10 μm (PM10) is positively associated with the COVID-19 incidence. However, no study has investigated the spatiotemporal pattern in this association, which plays important roles in identifying high-susceptibility regions and stages of epidemic. In this work, taking the 49 native states in America as an example, we used an advanced strategy to investigate this issue. First, time-series generalized additive model (GAM) were independently constructed to obtain the state-specific associations between short-term exposure to PM10 and the daily COVID-19 cases from 1 April 2020 to 31 December 2021. Then, a Leroux-prior-based conditional autoregression (LCAR) was used to spatially smoothen the associations. Third, the temporal variation of association and the reasons underlying the spatiotemporal heterogeneity were investigated by incorporating the time-varying GAM into LCAR. Results showed that PM10 was adversely associated with COVID-19 incidence in all the states. On average, a 10 μg/m3 increase of PM10 was associated with a 7.38% (95% CI 5.20-9.64%) increase in COVID-19 cases. A substantial spatial heterogeneity was observed, with strong associations in the middle and northeastern regions and weak associations in the western regions. The temporal trend of association presented a U shape, with the strongest association in the end of 2021. The vaccination rate was examined as a significant effect modifier. Our study provided the first evidence about the spatiotemporal pattern in PM10-COVID-19 associations and suggested that air pollution deserves more attention in the post-pandemic era and in the middle and northeastern regions in America for COVID-19 control and prevention.

Household Air Pollution and Risk of Pulmonary Tuberculosis in HIV-Infected Adults

Background

In developing countries, millions of deaths occur annually from household air pollution (HAP), pulmonary tuberculosis (PTB), and HIV-infection. However, it is unknown whether HAP influences PTB risk among people living with HIV-infection.

Methods

We conducted a case-control study among 1,277 HIV-infected adults in Bukavu, eastern Democratic Republic of Congo (February 2018 - March 2019). Cases had current or recent (<5y) PTB (positive sputum smear or Xpert MTB/RIF), controls had no PTB. Daily and lifetime HAP exposure were assessed by questionnaire and, in a random sub-sample (n=270), by 24-hour measurements of personal carbon monoxide (CO) at home. We used multivariable logistic regression to examine the associations between HAP and PTB.

Results

We recruited 435 cases and 842 controls (median age 41 years, [IQR] 33-50; 76% female). Cases were more likely to be female than male (63% vs 37%). Participants reporting cooking for >3h/day and ≥2 times/day and ≥5 days/weekwere more likely to have PTB (aOR 1·36; 95%CI 1·06-1·75) than those spending less time in the kitchen. Time-weighted average 24h personal CO exposure was related dose-dependently with the likelihood of having PTB, with aOR 4·64 (95%CI 1·1-20·7) for the highest quintile [12·3-76·2 ppm] compared to the lowest quintile [0·1-1·9 ppm].

Conclusion

Time spent cooking and personal CO exposure were independently associated with increased risk of PTB among people living with HIV. Considering the high burden of TB-HIV coinfection in the region, effective interventions are required to decrease HAP exposure caused by cooking with biomass among people living with HIV, especially women.

Exposure to ambient air pollutants and acute respiratory distress syndrome risk in sepsis

PURPOSE

Exposures to ambient air pollutants may prime the lung enhancing risk of acute respiratory distress syndrome (ARDS) in sepsis. Our objective was to determine the association of short-, medium-, and long-term pollutant exposures and ARDS risk in critically ill sepsis patients.

METHODS

We analyzed a prospective cohort of 1858 critically ill patients with sepsis, and estimated short- (3 days), medium- (6 weeks), and long- (5 years) term exposures to ozone, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 μm (PM2.5), and PM < 10 μm (PM10) using weighted averages of daily levels from monitors within 50 km of subjects' residences. Subjects were followed for 6 days for ARDS by the Berlin Criteria. The association between each pollutant and ARDS was determined using multivariable logistic regression adjusting for preselected confounders. In 764 subjects, we measured plasma concentrations of inflammatory proteins at presentation and tested for an association between pollutant exposure and protein concentration via linear regression.

RESULTS

ARDS developed in 754 (41%) subjects. Short- and long-term exposures to SO2, NO2, and PM2.5 were associated with ARDS risk (SO2: odds ratio (OR) for the comparison of the 75-25th long-term exposure percentile 1.43 (95% confidence interval (CI) 1.16, 1.77); p < 0.01; NO2: 1.36 (1.06, 1.74); p = 0.04, PM2.5: 1.21 (1.04, 1.41); p = 0.03). Long-term exposures to these three pollutants were also associated with plasma interleukin-1 receptor antagonist and soluble tumor necrosis factor receptor-1 concentrations.

CONCLUSION

Short and long-term exposures to ambient SO2, PM2.5, and NO2 are associated with increased ARDS risk in sepsis, representing potentially modifiable environmental risk factors for sepsis-associated ARDS.

Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States

Numerous studies have investigated the associations between COVID-19 risks and long-term exposure to air pollutants, revealing considerable heterogeneity and even contradictory regional results. Studying the spatial heterogeneity of the associations is essential for developing region-specific and cost-effective air-pollutant-related public health policies for the prevention and control of COVID-19. However, few studies have investigated this issue. Using the USA as an example, we constructed single/two-pollutant conditional autoregressions with random coefficients and random intercepts to map the associations between five air pollutants (PM_2.5, O₃, SO₂, NO₂, and CO) and two COVID-19 outcomes (incidence and mortality) at the state level. The attributed cases and deaths were then mapped at the county level. This study included 3108 counties from 49 states within the continental USA. The county-level air pollutant concentrations from 2017 to 2019 were used as long-term exposures, and the county-level cumulative COVID-19 cases and deaths through May 13, 2022, were used as outcomes. Results showed that considerably heterogeneous associations and attributable COVID-19 burdens were found in the USA. The COVID-19 outcomes in the western and northeastern states appeared to be unaffected by any of the five pollutants. The east of the USA bore the greatest COVID-19 burdens attributable to air pollution because of its high pollutant concentrations and significantly positive associations. PM_2.5 and CO were significantly positively associated with COVID-19 incidence in 49 states on average, whereas NO₂ and SO₂ were significantly positively associated with COVID-19 mortality. The remaining associations between air pollutants and COVID-19 outcomes were not statistically significant. Our study provided implications regarding where a major concern should be placed on a specific air pollutant for COVID-19 control and prevention, as well as where and how to conduct additional individual-based validation research in a cost-effective manner.

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

Ecological evidence links ambient particulate matter ≤2.5 mm (PM_2.5) and the rate of COVID-19 infections, severity, and deaths. However, such studies are unable to account for individual-level differences in major confounders like socioeconomic status and often rely on imprecise measures of PM_2.5. We conducted a systematic review of case-control and cohort studies, which rely on individual-level data, searching Medline, Embase, and the WHO COVID-19 database up to 30 June 2022. Study quality was evaluated using the Newcastle-Ottawa Scale. Results were pooled with a random effects meta-analysis, with Egger's regression, funnel plots, and leave-one-out/trim-and-fill sensitivity analyses to account for publication bias. N = 18 studies met inclusion criteria. A 10 μg/m³ increase in PM_2.5 was associated with 66 % (95 % CI: 1.31-2.11) greater odds of COVID-19 infection (N = 7) and 127 % (95 % CI: 1.41-3.66) odds of severe illness (hospitalisation, ICU admission, or requiring respiratory support) (N = 6). Pooled mortality results (N = 5) indicated increased deaths due to PM_2.5 but were non-significant (OR 1.40; 0.94 to 2.10). Most studies were rated "good" quality (14/18 studies), though there were numerous methodological issues; few used individual-level data to adjust for socioeconomic status (4/18 studies), instead using area-based indicators (11/18 studies) or no such adjustments (3/18 studies). Most severity (9/10 studies) and mortality studies (5/6 studies) were based on people already diagnosed COVID-19, potentially introducing collider bias. There was evidence of publication bias in studies of infection (p = 0.012) but not severity (p = 0.132) or mortality (p = 0.100). While methodological limits and evidence of bias require cautious interpretation of the findings, we found compelling evidence that PM_2.5 increases the risk of COVID-19 infection and severe disease, and weaker evidence of an increase in mortality risk.

The relationship among air pollution, meteorological factors and COVID-19 in the Brussels Capital Region

In great metropoles, there is a need for a better understanding of the spread of COVID-19 in an outdoor context with environmental parameters. Many studies on this topic have been carried out worldwide. However, there is conflicting evidence regarding the influence of environmental variables on the transmission, hospitalizations and deaths from COVID-19, even though there are plausible scientific explanations that support this, especially air quality and meteorological factors. Different urban contexts, methodological approaches and even the limitations of ecological studies are some possible explanations for this issue. That is why methodological experimentations in different regions of the world are important so that scientific knowledge can advance in this aspect. This research analyses the relationship between air pollution, meteorological factors and COVID-19 in the Brussels Capital Region. We use a data mining approach that is capable of extracting patterns in large databases with diverse taxonomies. Data on air pollution, meteorological, and epidemiological variables were processed in time series for the multivariate analysis and the classification based on association. The environmental variables associated with COVID-19-related deaths, cases and hospitalization were PM_2.5, O₃, NO₂, black carbon, radiation, air pressure, wind speed, dew point, temperature and precipitation. These environmental variables combined with epidemiological factors were able to predict intervals of hospitalization, cases and deaths from COVID-19. These findings confirm the influence of meteorological and air quality variables in the Brussels region on deaths and cases of COVID-19 and can guide public policies and provide useful insights for high-level governmental decision-making concerning COVID-19. However, it is necessary to consider intrinsic elements of this study that may have influenced our results, such as the use of air quality aggregated data, ecological fallacy, focus on acute effects in the time-series study, the underreporting of COVID-19, and the lack of behavioral factors.

Bayesian profile regression to study the ecologic associations of correlated environmental exposures with excess mortality risk during the first year of the Covid-19 epidemic in lombardy, Italy

Many countries, including Italy, have experienced significant social and spatial inequalities in mortality during the Covid-19 pandemic. This study applies a multiple exposures framework to investigate how joint place-based factors influence spatial inequalities of excess mortality during the first year of the Covid -19 pandemic in the Lombardy region of Italy. For the Lombardy region, we integrated municipality-level data on all-cause mortality between 2015 and 2020 with 13 spatial covariates, including 5-year average concentrations of six air pollutants, the average temperature in 2020, and multiple socio-demographic factors, and health facilities per capita. Using the clustering algorithm Bayesian profile regression, we fit spatial covariates jointly to identify clusters of municipalities with similar exposure profiles and estimated associations between clusters and excess mortality in 2020. Cluster analysis resulted in 13 clusters. Controlling for spatial autocorrelation of excess mortality and health-protective agency, two clusters had significantly elevated excess mortality than the rest of Lombardy. Municipalities in these highest-risk clusters are in Bergamo, Brescia, and Cremona provinces. The highest risk cluster (C11) had the highest long-term particulate matter air pollution levels (PM2.5 and PM10) and significantly elevated NO2 and CO air pollutants, temperature, proportion ≤18 years, and male-to-female ratio. This cluster is significantly lower for income and ≥65 years. The other high-risk cluster, Cluster 10 (C10), is elevated significantly for ozone but significantly lower for other air pollutants. Covariates with elevated levels for C10 include proportion 65 years or older and a male-to-female ratio. Cluster 10 is significantly lower for income, temperature, per capita health facilities, ≤18 years, and population density. Our results suggest that joint built, natural, and socio-demographic factors influenced spatial inequalities of excess mortality in Lombardy in 2020. Studies must apply a multiple exposures framework to guide policy decisions addressing the complex and multi-dimensional nature of spatial inequalities of Covid-19-related mortality.

The impact of air pollution on COVID-19 incidence, severity, and mortality: A systematic review of studies in Europe and North America

BACKGROUND

Air pollution is speculated to increase the risks of COVID-19 spread, severity, and mortality.

OBJECTIVES

We systematically reviewed studies investigating the relationship between air pollution and COVID-19 cases, non-fatal severity, and mortality in North America and Europe.

METHODS

We searched PubMed, Web of Science, and Scopus for studies investigating the effects of harmful pollutants, including particulate matter with diameter ≤2.5 or 10 μm (PM2.5 or PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO), on COVID-19 cases, severity, and deaths in Europe and North America through to June 19, 2021. Articles were included if they quantitatively measured the relationship between exposure to air pollution and COVID-19 health outcomes.

RESULTS

From 2,482 articles screened, we included 116 studies reporting 355 separate pollutant-COVID-19 estimates. Approximately half of all evaluations on incidence were positive and significant associations (52.7%); for mortality the corresponding figure was similar (48.1%), while for non-fatal severity this figure was lower (41.2%). Longer-term exposure to pollutants appeared more likely to be positively associated with COVID-19 incidence (63.8%). PM2.5, PM10, O3, NO2, and CO were most strongly positively associated with COVID-19 incidence, while PM2.5 and NO2 with COVID-19 deaths. All studies were observational and most exhibited high risk of confounding and outcome measurement bias.

DISCUSSION

Air pollution may be associated with worse COVID-19 outcomes. Future research is needed to better test the air pollution-COVID-19 hypothesis, particularly using more robust study designs and COVID-19 measures that are less prone to measurement error and by considering co-pollutant interactions.

Post-COVID-19 Syndrome in Outpatients and Its Association with Viral Load

INTRODUCTION

The COVID-19 pandemic is the result of the SARS-CoV-2 virus, which has caused more than 100 million infections and more than 2.5 million deaths worldwide, representing a serious public health problem. The gold method for detecting this virus is qRT-PCR, which is a semiquantitative technique where the viral load can be established through its cycle threshold (Ct). It has also been reported that COVID-19 generates long-term symptoms (post-COVID-19).

METHODS

After three months, a survey was performed on 70 COVID-19 confirmed patients; subsequently, we divided them into four groups (persistent symptoms, chemo-sensitive, cognitive issues, and changes in habit) in order to determine the correlation between viral load and post-COVID-19 symptoms.

RESULTS

Data show that fatigue, nervousness, anosmia, and diet changes are common long-term symptoms; in addition, a negative correlation was found between viral load and the number of post-COVID-19 symptoms.

CONCLUSION

COVID-19 generates long-term symptoms which can cause problems with psychological and social repercussions.

Independent associations of short- and long-term air pollution exposure with COVID-19 mortality among Californians

The growing literature demonstrating air pollution associations on COVID-19 mortality contains studies predominantly examining long-term exposure, with few on short-term exposure, and rarely both together to estimate independent associations. Because mechanisms by which air pollution may impact COVID-19 mortality risk function over timescales ranging from years to days, and given correlation among exposure time windows, consideration of both short- and long-term exposure is of importance. We assessed the independent associations between COVID-19 mortality rates with short- and long-term air pollution exposure by modeling both concurrently. Using California death certificate data COVID-19-related deaths were identified, and decedent residential information used to assess short- (4-week mean) and long-term (6-year mean) exposure to particulate matter <2.5µm (PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃). Negative binomial mixed models were fitted on weekly census tract COVID-19 mortality adjusting for potential confounders with random effects for county and census tract and an offset for population. Data were evaluated separately for two time periods March 16, 2020-October 18, 2020 and October 19, 2020-April 25, 2021, representing the Spring/Summer surges and Winter surge. Independent positive associations with COVID-19 mortality were observed for short- and long-term PM_2.5 in both study periods, with strongest associations observed in the first study period: COVID-19 mortality rate ratio for a 2-μg/m³ increase in long-term PM_2.5 was 1.13 (95%CI:1.09,1.17) and for a 4.7-μg/m³ increase in short-term PM_2.5 was 1.05 (95%CI:1.02,1.08). Statistically significant positive associations were seen for both short- and long-term NO₂ in study period 1, but short-term NO₂ was not statistically significant in study period 2. Results for long-term O₃ indicate positive associations, however, only marginal significance is achieved in study period 1. These findings support an adverse effect of long-term PM_2.5 and NO₂ exposure on COVID-19 mortality risk, independent of short-term exposure, and a possible independent effect of short-term PM_2.5.

Mobilizing COVID-19 level public health interventions for climate breakdown is necessary

The COVID-19 pandemic has proven that extraordinary public health measures can pivot every aspect of society. Norms, politics, economics, and business practices rapidly responded to coordinated simultaneous policies worldwide. This begs the question of why such advancements have not yet been similarly executed to reduce the short- and long-term morbidity and mortality due to environmental destruction and climate change. This article reviews various reasons explaining the discrepancy between the policies of these two health threats, using a terror management theory lens. Exploring how anthropogenic climate change potentiated the contagion and outcomes of COVID-19, the environmental determinants of health deserve increased attention in public discourse. The industry-driven response to COVID-19 also has exacerbated preexisting health inequalities and vulnerabilities, suggesting that a just transition for climate change must not repeat some of the same mistakes taken in global pandemic measures. Finally, addressing emergency health harms in ways that create increased environmental health harms is deemed iatrogenic, displacing rather than truly treating disease. Thus, a planetary health model focused on multisolving health issues is recommended for the basis of addressing COVID-19 and other health disasters.

Clinical, sociodemographic and environmental factors impact post-COVID-19 syndrome

Background

Sociodemographic and environmental factors are associated with incidence, severity, and mortality of COVID-19. However, little is known about the role of such factors in persisting symptoms among recovering patients. We designed a cohort study of hospitalized COVID-19 survivors to describe persistent symptoms and identify factors associated with post-COVID-19 syndrome.

Methods

We included patients hospitalized between March to August 2020 who were alive six months after hospitalization. We collected individual and clinical characteristics during hospitalization and at follow-up assessed ten symptoms with standardized scales, 19 yes/no symptoms, a functional status and a quality-of-life scale and performed four clinical tests. We examined individual exposure to greenspace and air pollution and considered neighbourhood´s population density and socioeconomic conditions as contextual factors in multilevel regression analysis.

Results

We included 749 patients with a median follow-up of 200 (IQR = 185-235) days, and 618 (83%) had at least one of the ten symptoms measured with scales. Pain (41%), fatigue (38%) and posttraumatic stress disorder (35%) were the most frequent. COVID-19 severity, comorbidities, BMI, female sex, younger age, and low socioeconomic position were associated with different symptoms. Exposure to ambient air pollution was associated with higher dyspnoea and fatigue scores and lower functional status.

Conclusions

We identified a high frequency of persistent symptoms among COVID-19 survivors that were associated with clinical, sociodemographic, and environmental variables. These findings indicate that most patients recovering from COVID-19 will need post-discharge care, and an additional burden to health care systems, especially in LMICs, should be expected.

Health and Clinical Impacts of Air Pollution and Linkages with Climate Change

Air Pollution Impacts and Climate Change LinksAs part of the NEJM Group series on climate change, Keswani and colleagues review the linkages between climate change and air pollution and suggest strategies that clinicians may use to mitigate the adverse health impacts of air pollution.

Air pollution and health impacts during the COVID-19 lockdowns in Grenoble, France

It is undeniable that exposure to outdoor air pollution impacts the health of populations and therefore constitutes a public health problem. Any actions or events causing variations in air quality have repercussions on populations' health. Faced with the worldwide COVID-19 health crisis that began at the end of 2019, the governments of several countries were forced, in the beginning of 2020, to put in place very strict containment measures that could have led to changes in air quality. While many works in the literature have studied the issue of changes in the levels of air pollutants during the confinements in different countries, very few have focused on the impact of these changes on health risks. In this work, we compare the 2020 period, which includes two lockdowns (March 16 - May 10 and a partial shutdown Oct. 30 - Dec. 15) to a reference period 2015-2019 to determine how these government-mandated lockdowns affected concentrations of NO₂, O₃, PM_2.5, and PM₁₀, and how that affected human health factors, including low birth weight, lung cancer, mortality, asthma, non-accidental mortality, respiratory, and cardiovascular illnesses. To this end, we structured 2020 into four periods, alternating phases of freedom and lockdowns characterized by a stringency index. For each period, we calculated (1) the differences in pollutant levels between 2020 and a reference period (2015-2019) at both background and traffic stations; and (2) the resulting variations in the epidemiological based relative risks of health outcomes. As a result, we found that relative changes in pollutant levels during the 2020 restriction period were as follows: NO₂ (-32%), PM_2.5 (-22%), PM₁₀ (-15%), and O₃ (+10.6%). The pollutants associated with the highest health risk reductions in 2020 were PM_2.5 and NO_2, while PM₁₀ and O₃ changes had almost no effect on health outcomes. Reductions in short-term risks were related to reductions in PM_2.5 (-3.2% in child emergency room visits for asthma during the second lockdown) and NO₂ (-1.5% in hospitalizations for respiratory causes). Long-term risk reductions related to PM_2.5 were low birth weight (-8%), mortality (-3.3%), and lung cancer (-2%), and to NO₂ for mortality (-0.96%). Overall, our findings indicate that the confinement period in 2020 resulted in a substantial improvement in air quality in the Grenoble area.

Probiotics, prebiotics, and synbiotics to prevent or combat air pollution consequences: The gut-lung axis

Air pollution exposure is a public health emergency, which attributes globally to an estimated seven million deaths on a yearly basis We are all exposed to air pollutants, varying from ambient air pollution hanging over cities to dust inside the home. It is a mixture of airborne particulate matter and gases that can be subdivided into three categories based on particle diameter. The smallest category called PM_0.1 is the most abundant. A fraction of the particles included in this category might enter the blood stream spreading to other parts of the body. As air pollutants can enter the body via the lungs and gut, growing evidence links its exposure to gastrointestinal and respiratory impairments and diseases, like asthma, rhinitis, respiratory tract infections, Crohn's disease, ulcerative colitis, and abdominal pain. It has become evident that there exists a crosstalk between the respiratory and gastrointestinal tracts, commonly referred to as the gut-lung axis. Via microbial secretions, metabolites, immune mediators and lipid profiles, these two separate organ systems can influence each other. Well-known immunomodulators and gut health stimulators are probiotics, prebiotics, together called synbiotics. They might combat air pollution-induced systemic inflammation and oxidative stress by optimizing the microbiota composition and microbial metabolites, thereby stimulating anti-inflammatory pathways and strengthening mucosal and epithelial barriers. Although clinical studies investigating the role of probiotics, prebiotics, and synbiotics in an air pollution setting are lacking, these interventions show promising health promoting effects by affecting the gastrointestinal- and respiratory tract. This review summarizes the current data on how air pollution can affect the gut-lung axis and might impact gut and lung health. It will further elaborate on the potential role of probiotics, prebiotics and synbiotics on the gut-lung axis, and gut and lung health.

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study

Background:

The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system.

Methods:

We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and ground-level ozone (O₃), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals’ long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage.

Results:

Among the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM_2.5 (1.70 μg/m³), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01–1.12), 1.09 (95% CI 0.98–1.21) and 1.00 (95% CI 0.90–1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO₂. We also estimated odds ratios of 1.15 (95% CI 1.06–1.23), 1.30 (95% CI 1.12–1.50) and 1.18 (95% CI 1.02–1.36) per interquartile range increase of 5.14 ppb in O₃ for hospital admission, ICU admission and death, respectively.

Interpretation:

Chronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O₃.

Impacts of air pollution on COVID-19 case fatality rate: a global analysis

The coronavirus disease 2019 (COVID-19) pandemic is still rapidly spreading globally. To probe high-risk cities and the impacts of air pollution on public health, this study explores the relationship between the long-term average concentration of air pollution and the city-level case fatality rate (CFR) of COVID-19 globally. Then, geographically weighted regression (GWR) is applied to examine the spatial variability of the relationships. Six air pollution factors, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), PM_2.5 (particles with diameter ≤2.5 μm), PM₁₀ (particles with diameter ≤10 μm), and air quality index (AQI), are positively associated with the city-level COVID-19 CFR. Our results indicate that a 1-unit increase in NO₂ (part per billion, PPB), SO₂ (PPB), O₃ (PPB), PM_2.5 (microgram per cubic meter, μg/m³), PM₁₀ (μg/m³), AQI (score), is related to a 1.450%, 1.005%, 0.992%, 0.860%, 0.568%, and 0.776% increase in the city-level COVID-19 CFR, respectively. Additionally, the effects of NO₂, O₃, PM_2.5, AQI, and probability of living with poor AQI on COVID-19 spatially vary in view of the estimation of the GWR. In other words, the adverse impacts of air pollution on health are different among the cities. In summary, long-term exposure to air pollution is negatively related to the COVID-19 health outcome, and the relationship is spatially non-stationary. Our research sheds light on the impacts of slashing air pollution on public health in the COVID-19 pandemic to help governments formulate air pollution policies in light of the local situations.

Short-term exposure to ambient air pollution and individual emergency department visits for COVID-19: a case-crossover study in Canada

Background

Ambient air pollution is thought to contribute to increased risk of COVID-19, but the evidence is controversial.

Objective

To evaluate the associations between short-term variations in outdoor concentrations of ambient air pollution and COVID-19 emergency department (ED) visits.

Methods

We conducted a case-crossover study of 78 255 COVID-19 ED visits in Alberta and Ontario, Canada between 1 March 2020 and 31 March 2021. Daily air pollution data (ie, fine particulate matter with diameter less than 2.5 µm (PM_2.5), nitrogen dioxide (NO₂) and ozone were assigned to individual case of COVID-19 in 10 km × 10 km grid resolution. Conditional logistic regression was used to estimate associations between air pollution and ED visits for COVID-19.

Results

Cumulative ambient exposure over 0–3 days to PM2.5 (OR 1.010; 95% CI 1.004 to 1.015, per 6.2 µg/m³) and NO₂ (OR 1.021; 95% CI 1.015 to 1.028, per 7.7 ppb) concentrations were associated with ED visits for COVID-19. We found that the association between PM_2.5 and COVID-19 ED visits was stronger among those hospitalised following an ED visit, as a measure of disease severity, (OR 1.023; 95% CI 1.015 to 1.031) compared with those not hospitalised (OR 0.992; 95% CI 0.980 to 1.004) (p value for effect modification=0.04).

Conclusions

We found associations between short-term exposure to ambient air pollutants and COVID-19 ED visits. Exposure to air pollution may also lead to more severe COVID-19 disease.

Removal of Environmental Nanoparticles Increases Protein Synthesis and Energy Production in Healthy Humans

Currently, industrial activity causes the environmental release of nanoparticles that have multiple adverse effects on population health. There is a clear correlation between the increase in particulate air pollution and the increases in mortality and morbidity rates in both adults and children, which demonstrates the toxic effects of these particles. However, the effect of particle removal on healthy individuals is unknown. Thus, in this preliminary study, we showed, for the first time, how the filtering equipment that we used significantly reduced a large amount of nanoparticles in a minimum time and induced a reduction of oxidative damage in healthy individuals of both sexes after 25, 50 and 100 days of exposure. These effects led to increased protein synthesis and enhanced mitochondrial efficiency, thus resulting in a highly significant triggering of ATP synthesis. These results not only provide insight into the chronic effects that environmental nanoparticles have on individuals prior to the development of pathologies but also demonstrate a system capable of reversing nanoparticle toxicity and allowing cellular energy recovery.

Long-term exposure to air pollution and COVID-19 incidence: a prospective study of residents in the city of Varese, Northern Italy

OBJECTIVES

To investigate the association between long-term exposure to airborne pollutants and the incidence of SARS-CoV-2 up to March 2021 in a prospective study of residents in Varese city.

METHODS

Citizens of Varese aged ≥18 years as of 31 December 2019 were linked by residential address to 2018 average annual exposure to outdoor concentrations of PM2.5, PM10, NO2, NO and ozone modelled using the Flexible Air quality Regional Model (FARM) chemical transport model. Citizens were further linked to regional datasets for COVID-19 case ascertainment (positive nasopharyngeal swab specimens) and to define age, sex, living in a residential care home, population density and comorbidities. We estimated rate ratios and additional numbers of cases per 1 µg/m3 increase in air pollutants from single- and bi-pollutant Poisson regression models.

RESULTS

The 62 848 residents generated 4408 cases. Yearly average PM2.5 exposure was 12.5 µg/m3. Age, living in a residential care home, history of stroke and medications for diabetes, hypertension and obstructive airway diseases were independently associated with COVID-19. In single-pollutant multivariate models, PM2.5 was associated with a 5.1% increase in the rate of COVID-19 (95% CI 2.7% to 7.5%), corresponding to 294 additional cases per 100 000 person-years. The association was confirmed in bi-pollutant models; excluding subjects in residential care homes; and further adjusting for area-based indicators of socioeconomic level and use of public transportation. Similar findings were observed for PM10, NO2 and NO. Ozone was associated with a 2% decrease in disease rate, the association being reversed in bi-pollutant models.

CONCLUSIONS

Long-term exposure to low levels of air pollutants, especially PM2.5, increased the incidence of COVID-19. The causality warrants confirmation in future studies; meanwhile, government efforts to further reduce air pollution should continue.

Appraisal of COVID-19 lockdown and unlocking effects on the air quality of North India

The COVID-19 pandemic lockdown supposedly provided a 'window' of reinstatement to natural resources including the air quality, but the scenario after the phased unlocking is yet to be explored. Consequently, here we evaluated the status of air quality during the 8th phase of unlocking of COVID-19 lockdown (January 2021) at three locations of North India. The first site (S1) was located at Punjab Agricultural University, Ludhiana-PPCB; the second site (S2) at Yamunapuram, Bulandshahr-UPPCB; and the third site (S3) at Okhla Phase-2, Delhi-DPCC. The levels of PM2.5 showed a significant increase of 525.2%, 281.2%, and 185.0% at sites S1, S2 and S3, respectively in the unlock 8 (January 2021), in comparison to its concentration in the lockdown phase. Coherently, the levels of PM10 also showed a prominent increase of 284.5%, 189.1%, and 103.9% at sites S3, S1, and S2, respectively during the unlock 8 as compared to its concentration in the lockdown phase. This rise in the concentration of PM2.5 and PM10 could be primarily attributed to the use of biomass fuel, industrial and vehicular emissions, stubble burning considering the agricultural activities at sites S1 and S2. Site S3 is a major industrial hub and has the highest population density among all three sites. Consequently, the maximum increase (295.7%) in the NO₂ levels during the unlock 8 was witnessed at site S3. The strong correlation between PM2.5, PM10, and CO, along with the PM2.5/PM10 ratio confirmed the similar origin of these pollutants at all the three sites. The improvements in the levels of air quality during the COVID-19 lockdown were major overtaken during the various phases of unlocking consequent to the initiation of anthropogenic processes.

COVID-19: Regional Differences in Austria

In the turbulent year 2020, overshadowed by the global COVID-19 pandemic, Austria experienced multiple waves of increased case incidence. While governmental measures to curb the numbers were based on current knowledge of infection risk factors, a retrospective analysis of incidence and lethality at the district level revealed correlations of relative infection risk with socioeconomic, geographical, and behavioral population parameters. We identified unexpected correlations between political orientation and smoking behavior and COVID-19 infection risk and/or mortality. For example, a decrease in daily smokers by 2.3 percentage points would be associated with an increase in cumulative incidence by 10% in the adjusted model, and an increase in voters of the right-wing populist party by 1.6 percentage points with an increase in cumulative mortality by 10%. While these parameters are apparently only single elements of complex causal chains that finally lead to individual susceptibility and vulnerability levels, our findings might have identified ecological parameters that can be utilized to develop fine-tuned communications and measures in upcoming challenges of this and other pandemics.

Long-term air pollution and COVID-19 mortality rates in California: Findings from the Spring/Summer and Winter surges of COVID-19

A growing number of studies report associations between air pollution and COVID-19 mortality. Most were ecological studies at the county or regional level which disregard important local variability and relied on data from only the first few months of the pandemic. Using COVID-19 deaths identified from death certificates in California, we evaluated whether long-term ambient air pollution was related to weekly COVID-19 mortality at the census tract-level during the first ∼12 months of the pandemic. Weekly COVID-19 mortality for each census tract was calculated based on geocoded death certificate data. Annual average concentrations of ambient particulate matter <2.5 μm (PM_2.5) and <10 μm (PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃) over 2014-2019 were assessed for all census tracts using inverse distance-squared weighting based on data from the ambient air quality monitoring system. Negative binomial mixed models related weekly census tract COVID-19 mortality counts to a natural cubic spline for calendar week. We included adjustments for potential confounders (census tract demographic and socioeconomic factors), random effects for census tract and county, and an offset for census tract population. Data were analyzed as two study periods: Spring/Summer (March 16-October 18, 2020) and Winter (October 19, 2020-March 7, 2021). Mean (standard deviation) concentrations were 10.3 (2.1) μg/m³ for PM_2.5, 25.5 (7.1) μg/m³ for PM₁₀, 11.3 (4.0) ppb for NO₂, and 42.8 (6.9) ppb for O₃. For Spring/Summer, adjusted rate ratios per standard deviation increase were 1.13 (95% confidence interval: 1.09, 1.17) for PM_2.5, 1.16 (1.11, 1.21) for PM₁₀, 1.06 (1.02, 1.10) for NO₂, and 1.09 (1.04, 1.14) for O₃. Associations were replicated in Winter, although they were attenuated for PM_2.5 and PM₁₀. Study findings support a relation between long-term ambient air pollution exposure and COVID-19 mortality. Communities with historically high pollution levels might be at higher risk of COVID-19 mortality.

Positive association between outdoor air pollution and the incidence and severity of COVID-19. A review of the recent scientific evidences

In June 2020, we published a review focused on assessing the influence of various air pollutants on the transmission of SARS-CoV-2, and the severity of COVID-19 in patients infected by the coronavirus. The results of most of those reviewed studies suggested that chronic exposure to certain air pollutants might lead to more severe and lethal forms of COVID-19, as well as delays/complications in the recovery of the patients. Since then, a notable number of studies on this topic have been published, including also various reviews. Given the importance of this issue, we have updated the information published since our previous review. Taking together the previous results and those of most investigations now reviewed, we have concluded that there is a significant association between chronic exposure to various outdoor air pollutants: PM2.5, PM10, O3, NO2, SO2 and CO, and the incidence/risk of COVID-19 cases, as well as the severity/mortality of the disease. Unfortunately, studies on the potential influence of other important air pollutants such as VOCs, dioxins and furans, or metals, are not available in the scientific literature. In relation to the influence of outdoor air pollutants on the transmission of SARS-CoV-2, although the scientific evidence is much more limited, some studies point to PM2.5 and PM10 as potential airborne transmitters of the virus. Anyhow, it is clear that environmental air pollution plays an important negative role in COVID-19, increasing its incidence and mortality.

Air quality index variation before and after the onset of COVID-19 pandemic: a comprehensive study on 87 capital, industrial and polluted cities of the world

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic provided an opportunity for the environment to reduce ambient pollution despite the economic, social and health disruption to the world. The purpose of this study was to investigate the changes in the air quality indexes (AQI) in industrial, densely populated and capital cities in different countries of the world before and after 2020. In this ecological study, we used AQI obtained from the free available databases such as the World Air Quality Index (WAQI). Bivariate correlation analysis was used to explore the correlations between meteorological and AQI variables. Mean differences (standard deviation: SD) of AQI parameters of different years were tested using paired-sample t-test or Wilcoxon signed-rank test as appropriate. Multivariable linear regression analysis was conducted to recognize meteorological variables affecting the AQI parameters.

RESULTS

AQI-PM2.5, AQI-PM10 and AQI-NO2 changes were significantly higher before and after 2020, simultaneously with COVID-19 restrictions in different cities of the world. The overall changes of AQI-PM2.5, AQI-PM10 and AQI-NO2 in 2020 were - 7.36%, - 17.52% and - 20.54% compared to 2019. On the other hand, these results became reversed in 2021 (+ 4.25%, + 9.08% and + 7.48%). In general, the temperature and relative humidity were inversely correlated with AQI-PM2.5, AQI-PM10 and AQI-NO2. Also, after adjusting for other meteorological factors, the relative humidity was inversely associated with AQI-PM2.5, AQI-PM10 and AQI-NO2 (β = - 1.55, β = - 0.88 and β = - 0.10, P < 0.01, respectively).

CONCLUSIONS

The results indicated that air quality generally improved for all pollutants except carbon monoxide and ozone in 2020; however, changes in 2021 have been reversed, which may be due to the reduction of some countries' restrictions. Although this quality improvement was temporary, it is an important result for planning to control environmental pollutants.

Environment-lockdown, air pollution and related diseases: could we learn something and make it last?

Although the pandemic has caused substantial losses in economic prosperity and human lives, it has also some positive impacts on the environment. Restricted mobility, complete closure, less traffic and industry have led to improved air quality especially in urban settings. Not only is air pollution an important determinant of chronic diseases, such as heart and lung disorders, but it has also been shown that poor air quality increases the risk of COVID-19. In this article, we review some of the findings on changes in air quality during the pandemic, and its potential effects on health. We need to continue to monitor the effects of change in air quality, due to COVID-19 lockdown or other factors, but also keep all our efforts to improve air quality even faster and more persistent, bringing the pollution levels below what WHO recommends are safe to live with.

The effect of air pollution on COVID-19 severity in a sample of patients with multiple sclerosis

Background and purpose

Some studies have shown that air pollution, often assessed by thin particulate matter with diameter below 2.5 µg/m³ (PM2.5), may contribute to severe COVID‐19 courses, as well as play a role in the onset and evolution of multiple sclerosis (MS). However, the impact of air pollution on COVID‐19 has never been explored specifically amongst patients with MS (PwMS). This retrospective observational study aims to explore associations between PM2.5 and COVID‐19 severity amongst PwMS.

Methods

Data were retrieved from an Italian web‐based platform (MuSC‐19) which includes PwMS with COVID‐19. PM2.5 2016–2018 average concentrations were provided by the Copernicus Atmospheric Monitoring Service. Italian patients inserted in the platform from 15 January 2020 to 9 April 2021 with a COVID‐19 positive test were included. Ordered logistic regression models were used to study associations between PM2.5 and COVID‐19 severity.

Results

In all, 1087 patients, of whom 13% required hospitalization and 2% were admitted to an intensive care unit or died, were included. Based on the multivariate analysis, higher concentrations of PM2.5 increased the risk of worse COVID‐19 course (odds ratio 1.90; p = 0.009).

Conclusions

Even if several other factors explain the unfavourable course of COVID‐19 in PwMS, the role of air pollutants must be considered and further investigated.