The effect of known and unknown confounders on the relationship between air pollution and Covid-19 mortality in Italy: A sensitivity analysis of an ecological study based on the E-value

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

BACKGROUND

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

METHODS

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

FINDINGS

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

CONCLUSION

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

The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis

BACKGROUND

The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes.

METHODS

On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality.

RESULTS

A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM2.5. The meta-analyses revealed that a 1 μg/m3 increase in PM2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality.

CONCLUSION

This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors.

Air pollution-associated shifts in the human airway microbiome and exposure-associated molecular events

Publications addressing air pollution-induced human respiratory microbiome shifts are reviewed in this article. The healthy respiratory microbiota is characterized by a low density of bacteria, fungi and viruses with high diversity, and usually consists of Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria, Fusobacteria, viruses and fungi. The air's microbiome is highly dependent on air pollution levels and is directly reflected within the human respiratory microbiome. In addition, pollutants indirectly modify the local environment in human respiratory organs by reducing antioxidant capacity, misbalancing proteolysis and modulating inflammation, all of which regulate local microbiomes. Improving air quality leads to more diverse and healthy microbiomes of the local air and, subsequently, residents' airways.

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.

Long-term air pollution exposure and COVID-19 case-severity: An analysis of individual-level data from Switzerland

Several studies are pointing out that exposure to elevated air pollutants could contribute to increased COVID-19 mortality. However, literature on the associations between air pollution exposure and COVID-19 severe morbidity is rather sparse. In addition, the majority of the studies used an ecological study design and were applied in regions with rather high air pollution levels. Here, we study the differential effects of long-term exposure to air pollution on severe morbidity and mortality risks from COVID-19 in various population subgroups in Switzerland, a country known for clean air. We perform individual-level analyses using data covering the first two major waves of COVID-19 between February 2020 and May 2021. High-resolution maps of particulate matter (PM_2.5) and nitrogen dioxide (NO₂) concentrations were produced for the 6 years preceding the pandemic using Bayesian geostatistical models. Air pollution exposure for each patient was measured by the long-term average concentration across the municipality of residence. The models were adjusted for the effects of individual characteristics, socio-economic, health-system, and climatic factors. The variables with an important association to COVID-19 case-severity were identified using Bayesian spatial variable selection. The results have shown that the individual-level characteristics are important factors related to COVID-19 morbidity and mortality in all the models. Long-term exposure to air pollution appears to influence the severity of the disease only when analyzing data during the first wave; this effect is attenuated upon adjustment for health-system related factors during the entire study period. Our findings suggest that the burden of air pollution increased the risks of COVID-19 in Switzerland during the first wave of the pandemic, but not during the second wave, when the national health system was better prepared.

Association Between Air Pollution, Climate Change, and COVID-19 Pandemic: A Review of the Recent Scientific Evidence

Background: Recent studies indicated the possible relationship between climate change, environmental pollution, and Coronavirus Disease 2019 (COVID-19) pandemic. This study reviewed the effects of air pollution, climate parameters, and lockdown on the number of cases and deaths related to COVID-19. Methods: The present review was performed to determine the effects of weather and air pollution on the number of cases and deaths related to COVID-19 during the lockdown. Articles were collected by searching the existing online databases, such as PubMed, Science Direct, and Google Scholar, with no limitations on publication dates. Afterwards, this review focused on outdoor air pollution, including PM2.5, PM10, NO2, SO2, and O3, and weather conditions affecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/COVID-19. Results: Most reviewed investigations in the present study showed that exposure to air pollutants, particularly PM2.5 and NO2, is positively related to COVID-19 patients and mortality. Moreover, these studies showed that air pollution could be essential in transmitting COVID-19. Local meteorology plays a vital role in coronavirus spread and mortality. Temperature and humidity variables are negatively correlated with virus transmission. The evidence demonstrated that air pollution could lead to COVID-19 transmission. These results support decision-makers in curbing potential new outbreaks. Conclusions: Overall, in environmental perspective-based COVID-19 studies, efforts should be accelerated regarding effective policies for reducing human emissions, bringing about air pollution and weather change. Therefore, using clean and renewable energy sources will increase public health and environmental quality by improving global air quality.

A correlational analysis of COVID-19 incidence and mortality and urban determinants of vitamin D status across the London boroughs

One of the biggest challenges of the COVID-19 pandemic is the heterogeneity in disease severity exhibited amongst patients. Among multiple factors, latest studies suggest vitamin D deficiency and pre-existing health conditions to be major contributors to death from COVID-19. It is known that certain urban form attributes can impact sun exposure and vitamin D synthesis. Also, long-term exposure to air pollution can play an independent role in vitamin D deficiency. We conducted a correlational analysis of urban form and air quality in relation to the demographics and COVID-19 incidence and mortality across 32 London boroughs between March 2020 and January 2021. We found total population, number of residents of Asian ethnicity, 4-year average PM10 levels and road length to be positively correlated with COVID-19 cases and deaths. We also found percentage of households with access to total open space to be negatively correlated with COVID-19 deaths. Our findings link COVID-19 incidence and mortality across London with environmental variables linked to vitamin D status. Our study is entirely based on publicly available data and provides a reference framework for further research as more data are gathered and the syndemic dimension of COVID-19 becomes increasingly relevant in connection to health inequalities within large urban areas.

Exposure to particulate matter: Direct and indirect role in the COVID-19 pandemic

Knowing the transmission factors and the natural environment that favor the spread of a viral infection is crucial to stop outbreaks and develop effective preventive strategies. This work aims to evaluate the role of Particulate Matter (PM) in the COVID-19 pandemic, focusing especially on that of PM as a vector for SARS-CoV-2. Exposure to PM has been related to new cases and to the clinical severity of people infected by SARS-CoV-2, which can be explained by the oxidative stress and the inflammatory response generated by these particles when entering the respiratory system, as well as by the role of PM in the expression of ACE-2 in respiratory cells in human hosts. In addition, different authors have detected SARS-CoV-2 RNA in PM sampled both in outdoor and indoor environments. The results of various studies lead to the hypothesis that the aerosols emitted by an infected person could be deposited in other suspended particles, sometimes of natural but especially of anthropogenic origin, that form the basal PM. However, the viability of the virus in PM has not yet been demonstrated. Should PM be confirmed as a vector of transmission, prevention strategies ought to be adapted, and PM sampling in outdoor environments could become an indicator of viral load in a specific area.

Economic expectations and anxiety during the COVID-19 pandemic: a one-year longitudinal evaluation on Italian university students

The COVID-19 pandemic has produced an extensive aggravation of people's anxiety level. Different policies aimed at fighting the spread of the virus could affect anxiety in various ways. We built an ad hoc web-based survey, administered to the student population of three Italian universities at the beginning of the pandemic and at one year's distance, to collect information on retrospective and current anxiety levels and the underlining reasons. The survey also included questions concerning sociodemographic, economic, labor, lifestyle, academic career, and on-line teaching features, which prevents students from identifying the main survey topic to be anxiety. This research aims at assessing the change in anxiety levels between the analyzed periods and the main determinants of such change, focusing on students' economic expectancies. Results from a Poisson regression model show that anxiety has increased compared to both the pre-pandemic level and the one quantified during the first lockdown. This increase is revealed to be mostly driven by economic and career-related uncertainties, rather than by job loss and proximity to COVID-19. Thus, policymakers should take action to provide certainties both in terms of economic prospects and reopening strategies, especially to avoid that the resulting increase in anxiety translates into an amplified suicide risk.