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.

By November 2021, COVID-19 had caused more than 5 million deaths globally¹ and more than 29 400 in Canada.² The clinical manifestations of SARS-CoV-2 infection range from being asymptomatic to multiple organ failure and death. Identifying risk factors for COVID-19 severity is important to better understand etiological mechanisms and identify populations to prioritize for screening, vaccination and medical treatment. Risk factors for severity of COVID-19 include male sex, older age, pre-existing medical conditions and being from racialized communities.^3–5 More recently, ambient air pollution has been implicated as a potential driver of COVID-19 severity.^6–10Long-term exposure to ambient air pollution, a major contributor to global disease burden,¹¹ could increase the risk of severe COVID-19 outcomes by several mechanisms. Air pollutants can reduce individuals’ pulmonary immune responses and antimicrobial activities, boosting viral loads.⁸ Air pollution can also induce chronic inflammation and overexpression of the alveolar angiotensin-converting enzyme 2 (ACE) receptor,⁷ the key receptor that facilitates SARS-CoV-2 entry into cells.^12,13 Exposure to air pollution contributes to chronic conditions, such as cardiovascular disease, that are associated with unfavourable COVID-19 prognosis, possibly owing to persistent immune activation and excessive amplification of cytokine development.¹⁰ Thus, greater exposure to long-term air pollution may lead to severe COVID-19 outcomes.Reports exist of positive associations between long-term exposure to particulate matter with diameters equal to or smaller than 2.5 or 10 μm (PM_2.5 and PM₁₀), ground-level ozone (O₃) and nitrogen dioxide (NO₂), and metrics of COVID-19 severity (e.g., mortality and case fatality rate).^8–10 However, most studies to date have used ecological and cross-sectional designs, owing to limited access to individual data, which leads to ambiguity in interpreting the results, thus hindering their influence on policy. ^6,14 Ecological designs do not allow for disentangling the relative impacts of air pollution on individual susceptibility to infection and disease severity.¹⁴ Residual confounding by factors such as population mobility and social interactions is also problematic. Therefore, a cohort study with data on individuals with SARS-CoV-2 is a more appropriate design.^6,14 Studies that have used individual data were conducted in specific subpopulations^15,16 or populations with few severe cases,¹⁷ or had limited data on individual exposure to air pollutants.¹⁸ In Canada, 1 ecological study found a positive association between long-term exposure to PM_2.5 and COVID-19 incidence,¹⁹ but no published study has explored the association between air pollution and COVID-19 severity.We aimed to examine the associations between long-term exposure to 3 common air pollutants (PM_2.5, NO₂ and O₃) and key indicators of COVID-19 severity, including hospital admission, intensive care unit (ICU) admission and death, using a large prospective cohort of people with confirmed SARS-CoV-2 infection in Ontario, Canada, in 2020. The air contaminants PM_2.5, NO₂ and O₃ are regularly monitored by the Canadian government, and are key pollutants that are considered when setting air-quality policies. They originate from varying sources (NO₂ is primarily emitted during combustion of fuel, O₃ is primarily formed in air by chemical reactions of nitrogen oxides and volatile organic compounds, and PM_2.5 can be emitted during combustion or formed by reactions of chemicals like sulphur dioxide and nitrogen oxides in air) and they may affect human health differently.^20,21,22     

Species specificity and intraspecific variation in the chemical profiles of Heliconius butterflies across a large geographic range

In many animals, mate choice is important for the maintenance of reproductive isolation between species. Traits important for mate choice and behavioral isolation are predicted to be under strong stabilizing selection within species; however, such traits can also exhibit variation at the population level driven by neutral and adaptive evolutionary processes. Here, we describe patterns of divergence among androconial and genital chemical profiles at inter‐ and intraspecific levels in mimetic Heliconius butterflies. Most variation in chemical bouquets was found between species, but there were also quantitative differences at the population level. We found a strong correlation between interspecific chemical and genetic divergence, but this correlation varied in intraspecific comparisons. We identified “indicator” compounds characteristic of particular species that included compounds already known to elicit a behavioral response, suggesting an approach for identification of candidate compounds for future behavioral studies in novel systems. Overall, the strong signal of species identity suggests a role for these compounds in species recognition, but with additional potentially neutral variation at the population level.     

Signs of stabilisation and stable coexistence

Many empirical studies motivated by an interest in stable coexistence have quantified negative density dependence, negative frequency dependence, or negative plant–soil feedback, but the links between these empirical results and ecological theory are not straightforward. Here, we relate these analyses to theoretical conditions for stabilisation and stable coexistence in classical competition models. By stabilisation, we mean an excess of intraspecific competition relative to interspecific competition that inherently slows or even prevents competitive exclusion. We show that most, though not all, tests demonstrating negative density dependence, negative frequency dependence, and negative plant–soil feedback constitute sufficient conditions for stabilisation of two‐species interactions if applied to data for per capita population growth rates of pairs of species, but none are necessary or sufficient conditions for stable coexistence of two species. Potential inferences are even more limited when communities involve more than two species, and when performance is measured at a single life stage or vital rate. We then discuss two approaches that enable stronger tests for stable coexistence‐invasibility experiments and model parameterisation. The model parameterisation approach can be applied to typical density‐dependence, frequency‐dependence, and plant–soil feedback data sets, and generally enables better links with mechanisms and greater insights, as demonstrated by recent studies.     

Cellular morphogenesis in the Saccharomyces cerevisiae cell cycle: localization of the CDC3 gene product and the timing of events at the budding site

Budding cells of the yeast Saccharomyces cerevisiae possess a ring of 10-nm-diameter filaments, of unknown biochemical nature, that lies just inside the plasma membrane in the neck connecting the mother cell to its bud. Electron microscopic observations suggest that these filaments assemble at the budding site coincident with bud emergence and disassemble shortly before cytokinesis (Byers, B. and L. Goetsch. 1976. J. Cell Biol. 69:717-721). Mutants defective in any of four genes (CDC3, CDC10, CDC11, or CDC12) lack these filaments and display a pleiotropic phenotype that involves abnormal bud growth and an inability to complete cytokinesis. We showed previously by immunofluorescence that the CDC12 gene product is probably a constituent of the ring of 10-nm filaments (Haarer, B. and J. Pringle. 1987. Mol. Cell. Biol. 7:3678-3687). We now report the use of fusion proteins to generate polyclonal antibodies specific for the CDC3 gene product. In immunofluorescence experiments, these antibodies decorated the neck regions of wild-type and mutant cells in patterns suggesting that the CDC3 gene product is also a constituent of the ring of 10-nm filaments. We also used the CDC3-specific and CDC12-specific antibodies to investigate the timing of localization of these proteins to the budding site. The results suggest that the CDC3 protein is organized into a ring at the budding site well before bud emergence and remains so organized for some time after cytokinesis. The CDC12 product appears to behave similarly, but may arrive at the budding site closer to the time of bud emergence, and disappear from that site more quickly after cytokinesis, than does the CDC3 product. Examination of mating cells and cells responding to purified mating pheromone revealed novel arrangements of the CDC3 and CDC12 products in the regions of cell wall reorganization. Both proteins were present in normal-looking ring structures at the bases of the first zygotic buds.     

Partial protection from cyclical selection generates a high level of polymorphism at multiple non‐neutral sites

Temporally varying selection is known to maintain genetic polymorphism under certain restricted conditions. However, if part of a population can escape from selective pressure, a condition called the “storage effect” is produced, which greatly promotes balanced polymorphism. We investigate whether seasonally fluctuating selection can maintain polymorphism at multiple loci, if cyclically fluctuating selection is not acting on a subpopulation called a “refuge.” A phenotype with a seasonally oscillating optimum is determined by alleles at multiple sites, across which the effects of mutations on phenotype are distributed randomly. This model resulted in long‐term polymorphism at multiple sites, during which allele frequencies oscillate heavily, greatly increasing the level of nonneutral polymorphism. The level of polymorphism at linked neutral sites was either higher or lower than expected for unlinked neutral loci. Overall, these results suggest that for a protein‐coding sequence, the nonsynonymous‐to‐synonymous ratio of polymorphism may exceed one. In addition, under randomly perturbed environmental oscillation, different sets of sites may take turns harboring long‐term polymorphism, thus making trans‐species polymorphism (which has been predicted as a classical signature of balancing selection) less likely.     

Environmental Supply Chain Cooperation and Its Effect on the Circular Economy Practice‐Performance Relationship Among Chinese Manufacturers

Due to resource scarcity and environmental degradation, a new development concept emphasizing environmental concerns, called the circular economy (CE), has been enacted in legislation in China. This environmental management concept can be implemented at three levels, namely, region, industrial zone, and individual enterprise, with the objective of boosting economic development while lessening environmental and resource challenges. Environmental supply chain cooperation (ESCC), an approach that utilizes customer and supplier cooperation in environmental management, has been initiated among Chinese enterprises. Using survey data collected from 396 Chinese manufacturers, we examine the role of ESCC practices in influencing the relationship between implementing CE practices and the achievement of performance outcomes by testing the moderation and mediation effects of ESCC practices on the CE practice‐performance relationship through hierarchical regression analysis. Our data analyses indicate that ESCC practices are useful by moderation and, in some cases, essential by mediation, for Chinese manufacturers seeking to realize the performance targets desired in CE practices. The results highlight the need for Chinese manufacturers to improve supply chain coordination in their implementation of CE. On the policy side, our research findings suggest that ESCC practices are beneficial and, in some cases, necessary for the development of CE in China.     

Kinetic Monte Carlo simulation for the striation distribution of void defects in Czochralski silicon growth

Unique crystal-originated pit (COP) distribution, similar to a striation pattern, is well matched with the oxygen profile in experimental analysis. It shows the strong relationship between oxygen concentration and COP distribution. In this paper, we study the generation of void defects and the relationship between interstitial oxygen and vacancy using the kinetic lattice Monte Carlo (KLMC) method. The KLMC method has been applied extensively in various forms to the study of micro-defects in silicon wafers. It explained well the formation of void defects such as vacancy–oxygen complex and vacancy–vacancy complex. The formation of clusters is strongly affected by oxygen concentration, which showed the relationship between COP distribution and oxygen concentration. The unique COP distribution could be correctly explained with KLMC results, and this kind of meso-scale results has not yet been reported.