Air pollution and COVID-19: clearing the air and charting a post-pandemic course: a joint workshop report of ERS, ISEE, HEI and WHO

Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality

BACKGROUND

There exists consistent empirical evidence in the literature pointing out ample heterogeneity in terms of the clinical evolution of patients with COVID-19. The identification of specific phenotypes underlying in the population might contribute towards a better understanding and characterization of the different courses of the disease. The aim of this study was to identify distinct clinical phenotypes among hospitalized patients with SARS-CoV-2 pneumonia using machine learning clustering, and to study their association with subsequent clinical outcomes as severity and mortality.

METHODS

Multicentric observational, prospective, longitudinal, cohort study conducted in four hospitals in Spain. We included adult patients admitted for in-hospital stay due to SARS-CoV-2 pneumonia. We collected a broad spectrum of variables to describe exhaustively each case: patient demographics, comorbidities, symptoms, physiological status, baseline examinations (blood analytics, arterial gas test), etc. For the development and internal validation of the clustering/phenotype models, the dataset was split into training and test sets (50% each). We proposed a sequence of machine learning stages: feature scaling, missing data imputation, reduction of data dimensionality via Kernel Principal Component Analysis (KPCA), and clustering with the k-means algorithm. The optimal cluster model parameters -including k, the number of phenotypes- were chosen automatically, by maximizing the average Silhouette score across the training set.

RESULTS

We enrolled 1548 patients, each of them characterized by 92 clinical attributes (d=109 features after variable encoding). Our clustering algorithm identified k=3 distinct phenotypes and 18 strongly informative variables: Phenotype A (788 cases [50.9% prevalence] - age ∼ 57, Charlson comorbidity ∼ 1, pneumonia CURB-65 score ∼ 0 to 1, respiratory rate at admission ∼ 18 min-1, FiO2 ∼ 21%, C-reactive protein CRP ∼ 49.5 mg/dL [median within cluster]); phenotype B (620 cases [40.0%] - age ∼ 75, Charlson ∼ 5, CURB-65 ∼ 1 to 2, respiration ∼ 20 min-1, FiO2 ∼ 21%, CRP ∼ 101.5 mg/dL); and phenotype C (140 cases [9.0%] - age ∼ 71, Charlson ∼ 4, CURB-65 ∼ 0 to 2, respiration ∼ 30 min-1, FiO2 ∼ 38%, CRP ∼ 152.3 mg/dL). Hypothesis testing provided solid statistical evidence supporting an interaction between phenotype and each clinical outcome: severity and mortality. By computing their corresponding odds ratios, a clear trend was found for higher frequencies of unfavourable evolution in phenotype C with respect to B, as well as more unfavourable in phenotype B than in A.

CONCLUSION

A compound unsupervised clustering technique (including a fully-automated optimization of its internal parameters) revealed the existence of three distinct groups of patients - phenotypes. In turn, these showed strong associations with the clinical severity in the progression of pneumonia, and with mortality.

Issue 4 - Impact of air pollution on COVID-19 mortality and morbidity: An epidemiological and mechanistic review

Air pollution is a major global environment and health concern. Recent studies have suggested an association between air pollution and COVID-19 mortality and morbidity. In this context, a close association between increased levels of air pollutants such as particulate matter ≤2.5 to 10 µM, ozone and nitrogen dioxide and SARS-CoV-2 infection, hospital admissions and mortality due to COVID 19 has been reported. Air pollutants can make individuals more susceptible to SARS-CoV-2 infection by inducing the expression of proteins such as angiotensin converting enzyme (ACE)2 and transmembrane protease, serine 2 (TMPRSS2) that are required for viral entry into the host cell, while causing impairment in the host defence system by damaging the epithelial barrier, muco-ciliary clearance, inhibiting the antiviral response and causing immune dysregulation. The aim of this review is to report the epidemiological evidence on impact of air pollutants on COVID 19 in an up-to-date manner, as well as to provide insights on in vivo and in vitro mechanisms.

Global respiratory health priorities at the beginning of the 21st century

Respiratory health has become a prevailing priority amid the diverse global health challenges that the 21st century brings, due to its substantial impact on individuals and communities on a global scale. Due to rapid advances in medicine, emerging knowledge gaps appear along with new challenges and ethical considerations. While breakthroughs in medical science can bring about encouraging possibilities for better treatments and interventions, they also lead to unanswered questions and areas where further research is warranted. A PubMed search on the topic "global respiratory health priorities" between the years 2000 and 2023 was conducted, which returned 236 articles. Of these, 55 were relevant and selected for inclusion in this article. The selection process took into account literature reviews, opinions from expert groups and careful analysis of existing gaps and challenges within the field; our selection encompasses specific infectious and noninfectious respiratory conditions in both adults and children. The global respiratory health priorities identified were selected on the basis that they have been recognised as critical areas of investigation and potential advancement and they span across clinical, translational, epidemiological and population health domains. Implementing these priorities will require a commitment to fostering collaboration and knowledge-sharing among experts in different fields with the ultimate aim to improve respiratory health outcomes for individuals and communities alike.

The joint effect of cumulative doses for outdoor air pollutants exposure in early life on asthma and wheezing among young children

BACKGROUND

Constrained by no proper way to assess cumulative exposure, the joint effect of air pollution cumulative exposure doses on childhood asthma and wheezing (AW) was not understood.

OBJECTIVE

To assess the association between cumulative exposure to multiple air pollutants in early life and childhood AW.

METHODS

We designed a nested case-control study based on the birth cohort in Jinan City. Children with AW followed up within 2 years after birth were treated as cases, and non-cases in this cohort were treated as the control source population, and the propensity score matching method was used to match each case to 5 controls. We calculated the individual cumulative outdoor exposure doses for each period using an inverse distance weighted model, alongside the complex Simpson's formula, accounting for outdoor time and respiratory volume. The Least absolute shrinkage and selection operator (Lasso) regression was performed to screen for covariates. To analyze the joint effects of pollutants, we employed the weighted quantile sum (WQS) regression model in conjunction with conditional logistic regression.

RESULTS

84 cases and 420 controls were included in this study. The odds ratio (OR) with 95% confidence interval (CI) of the impact of cumulative exposure (mg/m3) after birth on childhood AW was 1.78 (1.15-2.74) for SO2, 1.69 (1.11-2.57) for NO2, and 1.65 (1.09-2.52) for PM2.5, respectively. Furthermore, with each 25th percentile increase in the WQS index, the overall risk of cumulative doses for six pollutants exposure after birth on AW increased by an adjusted OR of 1.10 (1.03, 1.18), and SO2, PM2.5, and NO2 contributed the most to the WQS index. However, no statistically significant association was found between cumulative exposure to all pollutants before birth and childhood AW.

CONCLUSIONS

There was a joint effect of the cumulative exposure dose of outdoor air pollutants after birth on AW in children aged 0-2 years. And traffic-related pollutants (SO2, PM2.5, and NO2) make a greater contribution to the joint effect.

Epithelial MAPK signaling directs endothelial NRF2 signaling and IL-8 secretion in a tri-culture model of the alveolar-microvascular interface following diesel exhaust particulate (DEP) exposure

BACKGROUND

Particulate matter 2.5 (PM2.5) deposition in the lung's alveolar capillary region (ACR) is significantly associated with respiratory disease development, yet the molecular mechanisms are not completely understood. Adverse responses that promote respiratory disease development involve orchestrated, intercellular signaling between multiple cell types within the ACR. We investigated the molecular mechanisms elicited in response to PM2.5 deposition in the ACR, in an in vitro model that enables intercellular communication between multiple resident cell types of the ACR.

METHODS

An in vitro, tri-culture model of the ACR, incorporating alveolar-like epithelial cells (NCI-H441), pulmonary fibroblasts (IMR90), and pulmonary microvascular endothelial cells (HULEC) was developed to investigate cell type-specific molecular responses to a PM2.5 exposure in an in-vivo-like model. This tri-culture in vitro model was termed the alveolar capillary region exposure (ACRE) model. Alveolar epithelial cells in the ACRE model were exposed to a suspension of diesel exhaust particulates (DEP) (20 µg/cm2) with an average diameter of 2.5 µm. Alveolar epithelial barrier formation, and transcriptional and protein expression alterations in the directly exposed alveolar epithelial and the underlying endothelial cells were investigated over a 24 h DEP exposure.

RESULTS

Alveolar epithelial barrier formation was not perturbed by the 24 h DEP exposure. Despite no alteration in barrier formation, we demonstrate that alveolar epithelial DEP exposure induces transcriptional and protein changes in both the alveolar epithelial cells and the underlying microvascular endothelial cells. Specifically, we show that the underlying microvascular endothelial cells develop redox dysfunction and increase proinflammatory cytokine secretion. Furthermore, we demonstrate that alveolar epithelial MAPK signaling modulates the activation of NRF2 and IL-8 secretion in the underlying microvascular endothelial cells.

CONCLUSIONS

Endothelial redox dysfunction and increased proinflammatory cytokine secretion are two common events in respiratory disease development. These findings highlight new, cell-type specific roles of the alveolar epithelium and microvascular endothelium in the ACR in respiratory disease development following PM2.5 exposure. Ultimately, these data expand our current understanding of respiratory disease development following particle exposures and illustrate the utility of multicellular in vitro systems for investigating respiratory tract health.

Impact of outdoor air pollution on severity and mortality in COVID-19 pneumonia

The relationship between exposure to air pollution and the severity of coronavirus disease 2019 (COVID-19) pneumonia and other outcomes is poorly understood. Beyond age and comorbidity, risk factors for adverse outcomes including death have been poorly studied. The main objective of our study was to examine the relationship between exposure to outdoor air pollution and the risk of death in patients with COVID-19 pneumonia using individual-level data. The secondary objective was to investigate the impact of air pollutants on gas exchange and systemic inflammation in this disease. This cohort study included 1548 patients hospitalised for COVID-19 pneumonia between February and May 2020 in one of four hospitals. Local agencies supplied daily data on environmental air pollutants (PM10, PM2.5, O3, NO2, NO and NOX) and meteorological conditions (temperature and humidity) in the year before hospital admission (from January 2019 to December 2019). Daily exposure to pollution and meteorological conditions by individual postcode of residence was estimated using geospatial Bayesian generalised additive models. The influence of air pollution on pneumonia severity was studied using generalised additive models which included: age, sex, Charlson comorbidity index, hospital, average income, air temperature and humidity, and exposure to each pollutant. Additionally, generalised additive models were generated for exploring the effect of air pollution on C-reactive protein (CRP) level and SpO2/FiO2 at admission. According to our results, both risk of COVID-19 death and CRP level increased significantly with median exposure to PM10, NO2, NO and NOX, while higher exposure to NO2, NO and NOX was associated with lower SpO2/FiO2 ratios. In conclusion, after controlling for socioeconomic, demographic and health-related variables, we found evidence of a significant positive relationship between air pollution and mortality in patients hospitalised for COVID-19 pneumonia. Additionally, inflammation (CRP) and gas exchange (SpO2/FiO2) in these patients were significantly related to exposure to air pollution.

Climate change and respiratory disease: clinical guidance for healthcare professionals

Climate change is one of the major public health emergencies with already unprecedented impacts on our planet, environment and health. Climate change has already resulted in substantial increases in temperatures globally and more frequent and extreme weather in terms of heatwaves, droughts, dust storms, wildfires, rainstorms and flooding, with prolonged and altered allergen and microbial exposure as well as the introduction of new allergens to certain areas. All these exposures may have a major burden on patients with respiratory conditions, which will pose increasing challenges for respiratory clinicians and other healthcare providers. In addition, complex interactions between these different factors, along with other major environmental risk factors (e.g. air pollution), will exacerbate adverse health effects on the lung. For example, an increase in heat and sunlight in urban areas will lead to increases in ozone exposure among urban populations; effects of very high exposure to smoke and pollution from wildfires will be exacerbated by the accompanying heat and drought; and extreme precipitation events and flooding will increase exposure to humidity and mould indoors. This review aims to bring respiratory healthcare providers up to date with the newest research on the impacts of climate change on respiratory health. Respiratory clinicians and other healthcare providers need to be continually educated about the challenges of this emerging and growing public health problem and be equipped to be the key players in solutions to mitigate the impacts of climate change on patients with respiratory conditions.

Educational aims

To define climate change and describe major related environmental factors that pose a threat to patients with respiratory conditions.To provide an overview of the epidemiological evidence on climate change and respiratory diseases.To explain how climate change interacts with air pollution and other related environmental hazards to pose additional challenges for patients.To outline recommendations to protect the health of patients with respiratory conditions from climate-related environmental hazards in clinical practice.To outline recommendations to clinicians and patients with respiratory conditions on how to contribute to mitigating climate change.

Long-Term Exposure to Ambient Air Pollution and Mortality among Four Million COVID-19 Cases in Italy: The EpiCovAir Study

BACKGROUND

The role of chronic exposure to ambient air pollutants in increasing COVID-19 fatality is still unclear.

OBJECTIVES

The study aimed to investigate the association between long-term exposure to air pollutants and mortality among 4 million COVID-19 cases in Italy.

METHODS

We obtained individual records of all COVID-19 cases identified in Italy from February 2020 to June 2021. We assigned 2016-2019 mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10μm (PM10), PM with aerodynamic diameter ≤2.5μm (PM2.5), and nitrogen dioxide (NO2) to each municipality (n=7,800) as estimates of chronic exposures. We applied a principal component analysis (PCA) and a generalized propensity score (GPS) approach to an extensive list of area-level covariates to account for major determinants of the spatial distribution of COVID-19 case-fatality rates. Then, we applied generalized negative binomial models matched on GPS, age, sex, province, and month. As additional analyses, we fit separate models by pandemic periods, age, and sex; we quantified the numbers of COVID-19 deaths attributable to exceedances in annual air pollutant concentrations above predefined thresholds; and we explored associations between air pollution and alternative outcomes of COVID-19 severity, namely hospitalizations or accesses to intensive care units.

RESULTS

We analyzed 3,995,202 COVID-19 cases, which generated 124,346 deaths. Overall, case-fatality rates increased by 0.7% [95% confidence interval (CI): 0.5%, 0.9%], 0.3% (95% CI: 0.2%, 0.5%), and 0.6% (95% CI: 0.5%, 0.8%) per 1 μg/m3 increment in PM2.5, PM10, and NO2, respectively. Associations were higher among elderly subjects and during the first (February 2020-June 2020) and the third (December 2020-June 2021) pandemic waves. We estimated ∼8% COVID-19 deaths were attributable to pollutant levels above the World Health Organization 2021 air quality guidelines.

DISCUSSION

We found suggestive evidence of an association between long-term exposure to ambient air pollutants with mortality among 4 million COVID-19 cases in Italy. https://doi.org/10.1289/EHP11882.

An evaluation of the impact of COVID-19 safety measures in public transit spaces on riders' Worry of virus contraction

The coronavirus pandemic has brought about global change in travel behavior. Transit ridership volumes have dropped to record lows. Concerning environmental, health, and social consequences lie in store if transit networks are not able to regain a substantial portion of pre-pandemic users. Transit providers have implemented several interventions aimed at both slowing the spread of the virus and retaining riders as travel restrictions lift. While the effectiveness of these measures has been evaluated with respect to spread rate reduction, little consideration has been given to their impact on riders' feelings of worry regarding virus contraction. By deploying a photo-simulation approach in a randomized control trial, this study finds that level of compliance with safety measures and the conditions of transit spaces themselves significantly impact riders' levels of worry. Given these findings, a series of recommendations are made regarding compliance practices that are expected to lessen rider worry regarding the risks of COVID-19 infection.

Risk Factors for Respiratory Viral Infections: A Spotlight on Climate Change and Air Pollution

Climate change has both direct and indirect effects on human health, and some populations are more vulnerable to these effects than others. Viral respiratory infections are most common illnesses in humans, with estimated 17 billion incident infections globally in 2019. Anthropogenic drivers of climate change, chiefly the emission of greenhouse gases and toxic pollutants from burning of fossil fuels, and the consequential changes in temperature, precipitation, and frequency of extreme weather events have been linked with increased susceptibility to viral respiratory infections. Air pollutants like nitrogen dioxide, particulate matter, diesel exhaust particles, and ozone have been shown to impact susceptibility and immune responses to viral infections through various mechanisms, including exaggerated or impaired innate and adaptive immune responses, disruption of the airway epithelial barrier, altered cell surface receptor expression, and impaired cytotoxic function. An estimated 90% of the world's population is exposed to air pollution, making this a topic with high relevance to human health. This review summarizes the available epidemiologic and experimental evidence for an association between climate change, air pollution, and viral respiratory infection.

Cerebro-/Cardiovascular Collateral Damage During the COVID-19 Pandemic: Fact or Fiction?

Numerous observational studies have identified a decline in cerebro-/cardiovascular (CV) admissions during the initial phase of the COVID-19 pandemic. Recent studies and meta-analyses indicated that the overall decrease was smaller than that found in initial studies during the first months of 2020. Two years later we still do not have clear evidence about the potential causes and impacts of the reduction of CV hospitalizations during the COVID-19 pandemic. It has becoming increasingly evident that collateral damage (i.e., incidental damage to the public and patients) from the COVID-19 outbreak is the main underlying cause that at least somewhat reflects the effects of imposed measures such as social distancing and self-isolation. However, a smaller true decline in CV events in the community due to a lack of triggers associated with such acute syndromes cannot be excluded. There is currently indirect epidemiological evidence about the immediate impact that the collateral damage had on excess mortality, but possible late consequences including a rebound increase in CV events are yet to be observed. In the present narrative review, we present the reporting milestones in the literature of the rates of CV admissions and collateral damage during the last 2 years, and discuss all possible factors contributing to the decline in CV hospitalizations during the COVID-19 pandemic. Healthcare systems need to be prepared so that they can cope with the increased hospitalization rates for CV events in the near future.

Association between Ambient Air Pollution and Emergency Room Visits for Pediatric Respiratory Diseases: The Impact of COVID-19 Pandemic

The level and composition of air pollution have changed during the coronavirus disease 2019 (COVID-19) pandemic. However, the association between air pollution and pediatric respiratory disease emergency department (ED) visits during the COVID-19 pandemic remains unclear. The study was retrospectively conducted between 2017 and 2020 in Kaohsiung, Taiwan, from 1 January 2020 to 1 May 2020, defined as the period of the COVID-19 pandemic, and 1 January 2017 to 31 May 2019, defined as the pre-COVID-19 pandemic period. We enrolled patients under 17 years old who visited the ED in a medical center and were diagnosed with respiratory diseases such as pneumonia, asthma, bronchitis, and acute pharyngitis. Measurements of particulate matter (PM) with aerodynamic diameters of <10 μm (PM10) and < 2.5 μm (PM2.5), nitrogen dioxide (NO2), and Ozone (O3) were collected. During the COVID-19 pandemic, an increase in the interquartile range of PM2.5, PM10, and NO2 levels was associated with increases of 72.5% (95% confidence interval [CI], 50.5−97.7%), 98.0% (95% CI, 70.7−129.6%), and 54.7% (95% CI, 38.7−72.6%), respectively, in the risk of pediatric respiratory disease ED visits on lag 1, which were greater than those in the pre-COVID-19 pandemic period. After adjusting for temperature and humidity, the risk of pediatric respiratory diseases after exposure to PM2.5 (inter p = 0.001) and PM10 (inter p < 0.001) was higher during the COVID-19 pandemic. PM2.5, PM10, and NO2 may play important roles in pediatric respiratory events in Kaohsiung, Taiwan. Compared with the pre-COVID-19 pandemic period, the levels of PM2.5 and PM10 were lower; however, the levels were related to a greater increase in ED during the COVID-19 pandemic.

The determinants of the changing speed of spread of COVID-19 across Italy

The COVID-19 epidemic showed inter-regional differences in Italy. We used an ecological study design and publicly available data to compare the basic reproduction number (R 0), the doubling time of the infection (DT) and the COVID-19 cumulative incidence (CI), death rate, case fatality rate (CFR) and time lag to slow down up to a 50-days doubling time in the first and the second 2020 epidemic waves (δ DT50) by region. We also explored socio-economic, environmental and lifestyle variables with multiple regression analysis. COVID-19 CI and CFR changed in opposite directions in the second vs . the first wave: the CI increased sixfold with no evidence of a relationship with the testing rate; the CFR decreased in the regions where it was initially higher but increased where it was lower. The R 0 did not change; the initially mildly affected regions, but not those where the first wave had most severely hit, showed a greater δ DT50 amplitude. Vehicular traffic, average temperature, population density, average income, education and household size showed a correlation with COVID-19 outcomes. The deadly experience in the first epidemic wave and the varying preparedness of the local health systems might have contributed to the inter-regional differences in the second COVID-19 epidemic wave.

Association of Short-term Air Pollution Exposure With SARS-CoV-2 Infection Among Young Adults in Sweden

IMPORTANCE

Mounting ecological evidence shows an association between short-term air pollution exposure and COVID-19, yet no study has examined this association on an individual level.

OBJECTIVE

To estimate the association between short-term exposure to ambient air pollution and SARS-CoV-2 infection among Swedish young adults.

DESIGN, SETTING, AND PARTICIPANTS

This time-stratified case-crossover study linked the prospective BAMSE (Children, Allergy Milieu, Stockholm, Epidemiology [in Swedish]) birth cohort to the Swedish national infectious disease registry to identify cases with positive results for SARS-CoV-2 polymerase chain reaction (PCR) testing from May 5, 2020, to March 31, 2021. Case day was defined as the date of the PCR test, whereas the dates with the same day of the week within the same calendar month and year were selected as control days. Data analysis was conducted from September 1 to December 31, 2021.

EXPOSURES

Daily air pollutant levels (particulate matter with diameter ≤2.5 μm [PM2.5], particulate matter with diameter ≤10 μm [PM10], black carbon [BC], and nitrogen oxides [NOx]) at residential addresses were estimated using dispersion models with high spatiotemporal resolution.

MAIN OUTCOMES AND MEASURES

Confirmed SARS-CoV-2 infection among participants within the BAMSE cohort. Distributed-lag models combined with conditional logistic regression models were used to estimate the association.

RESULTS

A total of 425 cases were identified, of whom 229 (53.9%) were women, and the median age was 25.6 (IQR, 24.9-26.3) years. The median exposure level for PM2.5 was 4.4 [IQR, 2.6-6.8] μg/m3 on case days; for PM10, 7.7 [IQR, 4.6-11.3] μg/m3 on case days; for BC, 0.3 [IQR, 0.2-0.5] μg/m3 on case days; and for NOx, 8.2 [5.6-14.1] μg/m3 on case days. Median exposure levels on control days were 3.8 [IQR, 2.4-5.9] μg/m3 for PM2.5, 6.6 [IQR, 4.5-10.4] μg/m3 for PM10, 0.2 [IQR, 0.2-0.4] μg/m3 for BC, and 7.7 [IQR, 5.3-12.8] μg/m3 for NOx. Each IQR increase in short-term exposure to PM2.5 on lag 2 was associated with a relative increase in positive results of SARS-CoV-2 PCR testing of 6.8% (95% CI, 2.1%-11.8%); exposure to PM10 on lag 2, 6.9% (95% CI, 2.0%-12.1%); and exposure to BC on lag 1, 5.8% (95% CI, 0.3%-11.6%). These findings were not associated with NOx, nor were they modified by sex, smoking, or having asthma, overweight, or self-reported COVID-19 respiratory symptoms.

CONCLUSIONS AND RELEVANCE

The findings of this case-crossover study of Swedish young adults suggest that short-term exposure to particulate matter and BC was associated with increased risk of positive PRC test results for SARS-CoV-2, supporting the broad public health benefits of reducing ambient air pollution levels.

A Methodological Approach to Use Contextual Factors for Epidemiological Studies on Chronic Exposure to Air Pollution and COVID-19 in Italy

The large availability of both air pollution and COVID-19 data, and the simplicity to make geographical correlations between them, led to a proliferation of ecological studies relating the levels of pollution in administrative areas to COVID-19 incidence, mortality or lethality rates. However, the major drawback of these studies is the ecological fallacy that can lead to spurious associations. In this frame, an increasing concern has been addressed to clarify the possible role of contextual variables such as municipalities' characteristics (including urban, rural, semi-rural settings), those of the resident communities, the network of social relations, the mobility of people, and the responsiveness of the National Health Service (NHS), to better clarify the dynamics of the phenomenon. The objective of this paper is to identify and collect the municipalities' and community contextual factors and to synthesize their information content to produce suitable indicators in national environmental epidemiological studies, with specific emphasis on assessing the possible role of air pollution on the incidence and severity of the COVID-19 disease. A first step was to synthesize the content of spatial information, available at the municipal level, in a smaller set of "summary indexes" that can be more easily viewed and analyzed. For the 7903 Italian municipalities (1 January 2020-ISTAT), 44 variables were identified, collected, and grouped into five information dimensions a priori defined: (i) geographic characteristics of the municipality, (ii) demographic and anthropogenic characteristics, (iii) mobility, (iv) socio-economic-health area, and (v) healthcare offer (source: ISTAT, EUROSTAT or Ministry of Health, and further ad hoc elaborations (e.g., OpenStreetMaps)). Principal component analysis (PCA) was carried out for the five identified dimensions, with the aim of reducing the large number of initial variables into a smaller number of components, limiting as much as possible the loss of information content (variability). We also included in the analysis PM2.5, PM10 and NO2 population weighted exposure (PWE) values obtained using a four-stage approach based on the machine learning method, "random forest", which uses space-time predictors, satellite data, and air quality monitoring data estimated at the national level. Overall, the PCA made it possible to extract twelve components: three for the territorial characteristics dimension of the municipality (variance explained 72%), two for the demographic and anthropogenic characteristics dimension (variance explained 62%), three for the mobility dimension (variance explained 83%), two for the socio-economic-health sector (variance explained 58%) and two for the health offer dimension (variance explained 72%). All the components of the different dimensions are only marginally correlated with each other, demonstrating their potential ability to grasp different aspects of the spatial distribution of the COVID-19 pathology. This work provides a national repository of contextual variables at the municipality level collapsed into twelve informative factors suitable to be used in studies on the association between chronic exposure to air pollution and COVID-19 pathology, as well as for investigations on the role of air pollution on the health of the Italian population.

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.

Ecological studies of COVID-19 and air pollution: How useful are they?

Background:

Results from ecological studies have suggested that air pollution increases the risk of developing and dying from COVID-19. Drawing causal inferences from the measures of association reported in ecological studies is fraught with challenges given biases arising from an outcome whose ascertainment is incomplete, varies by region, time, and across sociodemographic characteristics, and cannot account for clustering or within-area heterogeneity. Through a series of analyses, we illustrate the dangers of using ecological studies to assess whether ambient air pollution increases the risk of dying from, or transmitting, COVID-19.

Methods:

We performed an ecological analysis in the continental United States using county-level ambient concentrations of fine particulate matter (PM_2.5) between 2000 and 2016 and cumulative COVID-19 mortality counts through June 2020, December 2020, and April 2021. To show that spurious associations can be obtained in ecological data, we modeled the association between PM_2.5 and the prevalence of human immunodeficiency virus (HIV). We fitted negative binomial models, with a logarithmic offset for county-specific population, to these data. Natural cubic splines were used to describe the shape of the exposure-response curves.

Results:

Our analyses revealed that the shape of the exposure-response curve between PM_2.5 and COVID-19 changed substantially over time. Analyses of COVID-19 mortality through June 30, 2021, suggested a positive linear relationship. In contrast, an inverse pattern was observed using county-level concentrations of PM_2.5 and the prevalence of HIV.

Conclusions:

Our analyses indicated that ecological analyses are prone to showing spurious relationships between ambient air pollution and mortality from COVID-19 as well as the prevalence of HIV. We discuss the many potential biases inherent in any ecological-based analysis of air pollution and COVID-19.

Variation in Cause-Specific Mortality Rates in Italy during the First Wave of the COVID-19 Pandemic: A Study Based on Nationwide Data

Italy was a country severely hit by the first coronavirus disease 2019 (COVID-19) pandemic wave in early 2020. Mortality studies have focused on the overall excess mortality observed during the pandemic. This paper investigates the cause-specific mortality in Italy from March 2020 to April 2020 and the variation in mortality rates compared with those in 2015-2019 regarding sex, age, and epidemic area. Causes of death were derived from the national cause-of-death register. COVID-19 was the leading cause of death among males and the second leading cause among females. Chronic diseases, such as diabetes and hypertensive, ischemic heart, and cerebrovascular diseases, with decreasing or stable mortality rates in 2015-2019, showed a reversal in the mortality trend. Moreover, mortality due to pneumonia and influenza increased. No increase in neoplasm mortality was observed. Among external causes of death, mortality increased for accidental falls but reduced for transport accidents and suicide. Mortality from causes other than COVID-19 increased similarly in both genders and more at ages 65 years or above. Compared with other areas in Italy, the Lombardy region showed the largest excess in mortality for all leading causes. Underdiagnosis of COVID-19 at the beginning of the pandemic may, to some extent, explain the mortality increase for some causes of death, especially pneumonia and other respiratory diseases.

The Social and Natural Environment's Impact on SARS-CoV-2 Infections in the UK Biobank

COVID-19 has caused a global pandemic with considerable impact. Studies have examined the influence of socioeconomic status and air pollution on COVID-19 risk but in low detail. This study seeks to further elucidate the nuances of socioeconomic status, as defined by the Index of Multiple Deprivation (IMD), air pollution, and their relationship. We examined the effect of IMD and air pollution on the likelihood of testing positive for SARS-CoV-2 among 66,732 UKB participants tested for SARS-CoV-2 from 16 March 2020 through 16 March 2021. Logistic regression was performed controlling for age, sex, ancestry and IMD or air pollution in the respective models. IMD and its sub-scores were significantly associated with increased risk of testing positive for SARS-CoV-2. All particulate matter less than 2.5 μm (PM2.5), nitrogen oxide (NO_x), and nitrogen dioxide (NO₂) levels were associated with increased likelihood of testing positive for SARS-CoV-2. Measures of green space and natural environment around participants' homes were associated with reduced likelihood of SARS-CoV-2. Socioeconomic status and air pollution have independent effects on the risk of testing positive for SARS-CoV-2. Green space and natural environment space in the proximity of people's homes may mediate the effect of air pollution on the risk of testing positive for SARS-CoV-2.

Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis

Various countries across the globe have been affected by different COVID-19 waves at different points in time and with varying levels of virulence. With the backdrop of the two COVID-19 waves that broke out in Delhi, this study examines the variations in the concentrations of criteria pollutants, air quality, and meteorological variables across the waves and their influence on COVID-19 morbidity/mortality. Descriptive statistics, violin plots, and Spearman rank correlation tests were employed to assess the variations in environmental parameters and investigate their associations with COVID-19 incidence under the two waves. The susceptible-infected-recovered model and multiple linear regression were used to assess the wave-wise basic reproduction number (R0) and infection spreading trajectory of the virus. Our results show that the first wave in Delhi had three successive peaks and valleys, and the first peak of the second wave was the tallest, indicating the severity of per-day infection cases. During the analysed period (April 2020 and April 2021), concentrations of criteria pollutants varied across the waves, and air pollution was substantially higher during the second wave. In addition, the results revealed that during the second wave, NO2 maintained a significant negative relationship with COVID-19 (cases per day), while SO2 had a negative relationship with COVID-19 (cumulative cases) during the first wave. Our results also show a significant positive association of O3 with COVID-19 deaths during the first wave and cumulative cases and deaths during the second wave. The study indicates that a higher relative humidity in Delhi had a negative relation with COVID-19 cumulative cases and mortality during the first wave. The study confirms that the estimated R0 was marginally different during the two waves, and the spread of COVID-19 new cases followed a cubic growth trajectory. The findings of this study provide valuable information for policymakers in handling COVID-19 waves in various cities.