PM2.5 in Beijing - temporal pattern and its association with influenza

Exposure to PM2.5 modulate the pro-inflammatory and interferon responses against influenza virus infection in a human 3D bronchial epithelium model

Epidemiological studies showed a positive association between exposure to PM2.5 and the severity of influenza virus infection. However, the mechanisms by which PM2.5 can disrupt antiviral defence are still unclear. From this perspective, the objective of this study was to evaluate the effects of PM2.5 on antiviral signalling in the respiratory epithelium using the bronchial Calu-3 cell line grown at the air-liquid interface. Pre-exposure to PM2.5 before infection with the influenza virus was investigated, as well as a co-exposure. Although a physical interaction between the virus and the particles seems possible, no effect of PM2.5 on viral replication was observed during co-exposure, although a downregulation of IFN-β release was associated to PM2.5 exposure. However, pre-exposure slightly increased the viral nucleoprotein production and the pro-inflammatory response. Conversely, the level of the myxovirus resistance protein A (MxA), an interferon-stimulated gene (ISG) induced by IFN-β, was reduced. Therefore, these results suggest that pre-exposure to PM2.5 could alter the antiviral response of bronchial epithelial cells, increasing their susceptibility to viral infection.

Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States

BACKGROUND

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important.

METHODS

We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season.

RESULTS

For asthma, increases of 1 µg/m3 in PM2.5 exposure 7-13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6-12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4-10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods.

CONCLUSIONS

Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs.

Impact of the coronavirus disease 2019 pandemic on the diversity of notifiable infectious diseases: a case study in Shanghai, China

The outbreak of coronavirus disease 2019 (COVID-19) has not only posed significant challenges to public health but has also impacted every aspect of society and the environment. In this study, we propose an index of notifiable disease outbreaks (NDOI) to assess the impact of COVID-19 on other notifiable diseases in Shanghai, China. Additionally, we identify the critical factors influencing these diseases using multivariate statistical analysis. We collected monthly data on 34 notifiable infectious diseases (NIDs) and corresponding environmental and socioeconomic factors (17 indicators) from January 2017 to December 2020. The results revealed that the total number of cases and NDOI of all notifiable diseases decreased by 47.1% and 52.6%, respectively, compared to the period before the COVID-19 pandemic. Moreover, the COVID-19 pandemic has led to improved air quality as well as impacted the social economy and human life. Redundancy analysis (RDA) showed that population mobility, particulate matter (PM2.5), atmospheric pressure, and temperature were the primary factors influencing the spread of notifiable diseases. The NDOI is beneficial in establishing an early warning system for infectious disease epidemics at different scales. Furthermore, our findings also provide insight into the response mechanisms of notifiable diseases influenced by social and environmental factors.

Long-term exposure to ambient PM2.5, particulate constituents and hospital admissions from non-respiratory infection

The association between PM2.5 and non-respiratory infections is unclear. Using data from Medicare beneficiaries and high-resolution datasets of PM2.5 and its constituents across 39,296 ZIP codes in the U.S between 2000 and 2016, we investigated the associations between annual PM2.5, PM2.5 constituents, source-specific PM2.5, and hospital admissions from non-respiratory infections. Each standard deviation (3.7-μg m-3) increase in PM2.5 was associated with a 10.8% (95%CI 10.8-11.2%) increase in rate of hospital admissions from non-respiratory infections. Sulfates (30.8%), Nickel (22.5%) and Copper (15.3%) contributed the largest weights in the observed associations. Each standard deviation increase in PM2.5 components sourced from oil combustion, coal burning, traffic, dirt, and regionally transported nitrates was associated with 14.5% (95%CI 7.6-21.8%), 18.2% (95%CI 7.2-30.2%), 20.6% (95%CI 5.6-37.9%), 8.9% (95%CI 0.3-18.4%) and 7.8% (95%CI 0.6-15.5%) increases in hospital admissions from non-respiratory infections. Our results suggested that non-respiratory infections are an under-appreciated health effect of PM2.5.

Ambient atmospheric PM worsens mouse lung injury induced by influenza A virus through lysosomal dysfunction

BACKGROUND

Particulate matter (PM) air pollution poses a significant risk to respiratory health and is especially linked with various infectious respiratory diseases such as influenza. Our previous studies have shown that H5N1 virus infection could induce alveolar epithelial A549 cell death by enhancing lysosomal dysfunction. This study aims to investigate the mechanisms underlying the effects of PM on influenza virus infections, with a particular focus on lysosomal dysfunction.

RESULTS

Here, we showed that PM nanoparticles such as silica and alumina could induce A549 cell death and lysosomal dysfunction, and degradation of lysosomal-associated membrane proteins (LAMPs), which are the most abundant lysosomal membrane proteins. The knockdown of LAMPs with siRNA facilitated cellular entry of both H1N1 and H5N1 influenza viruses. Furthermore, we demonstrated that silica and alumina synergistically increased alveolar epithelial cell death induced by H1N1 and H5N1 influenza viruses by enhancing lysosomal dysfunction via LAMP degradation and promoting viral entry. In vivo, lung injury in the H5N1 virus infection-induced model was exacerbated by pre-exposure to silica, resulting in an increase in the wet/dry ratio and histopathological score.

CONCLUSIONS

Our findings reveal the mechanism underlying the synergistic effect of nanoparticles in the early stage of the influenza virus life cycle and may explain the increased number of respiratory patients during periods of air pollution.

Short-Term Exposure to Ambient Air Pollution and Influenza: A Multicity Study in China

BACKGROUND

Air pollution is a major risk factor for planetary health and has long been suspected of predisposing humans to respiratory diseases induced by pathogens like influenza viruses. However, epidemiological evidence remains elusive due to lack of longitudinal data from large cohorts.

OBJECTIVE

Our aim is to quantify the short-term association of influenza incidence with exposure to ambient air pollutants in Chinese cities.

METHODS

Based on air pollutant data and influenza surveillance data from 82 cities in China over a period of 5 years, we applied a two-stage time series analysis to assess the association of daily incidence of reported influenza cases with six common air pollutants [particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ), particulate matter with aerodynamic diameter ≤ 10 μ m (PM 10 ), NO 2 , SO 2 , CO, and O 3 ], while adjusting for potential confounders including temperature, relative humidity, seasonality, and holiday effects. We built a distributed lag Poisson model for one or multiple pollutants in each individual city in the first stage and conducted a meta-analysis to pool city-specific estimates in the second stage.

RESULTS

A total of 3,735,934 influenza cases were reported in 82 cities from 2015 to 2019, accounting for 72.71% of the overall case number reported in the mainland of China. The time series models for each pollutant alone showed that the daily incidence of reported influenza cases was positively associated with almost all air pollutants except for ozone. The most prominent short-term associations were found for SO 2 and NO 2 with cumulative risk ratios of 1.094 [95% confidence interval (CI): 1.054, 1.136] and 1.093 (95% CI: 1.067, 1.119), respectively, for each 10   μ g / m 3 increase in the concentration at each of the lags of 1-7 d. Only NO 2 showed a significant association with the daily incidence of influenza cases in the multipollutant model that adjusts all six air pollutants together. The impact of air pollutants on influenza was generally found to be greater in children, in subtropical cities, and during cold months.

DISCUSSION

Increased exposure to ambient air pollutants, particularly NO 2 , is associated with a higher risk of influenza-associated illness. Policies on reducing air pollution levels may help alleviate the disease burden due to influenza infection. https://doi.org/10.1289/EHP12146.

Transcriptomics profile of human bronchial epithelial cells exposed to ambient fine particles and influenza virus (H3N2)

Fine particulate matter (PM2.5) pollution remains a major threat to public health. As the physical barrier against inhaled air pollutants, airway epithelium is a primary target for PM2.5 and influenza viruses, two major environmental insults. Recent studies have shown that PM2.5 and influenza viruses may interact to aggravate airway inflammation, an essential event in the pathogenesis of diverse pulmonary diseases. Airway epithelium plays a critical role in lung health and disorders. Thus far, the mechanisms for the interactive effect of PM2.5 and the influenza virus on gene transcription of airway epithelial cells have not been fully uncovered. In this present pilot study, the transcriptome sequencing approach was introduced to identify responsive genes following individual and co-exposure to PM2.5 and influenza A (H3N2) viruses in a human bronchial epithelial cell line (BEAS-2B). Enrichment analysis revealed the function of differentially expressed genes (DEGs). Specifically, the DEGs enriched in the xenobiotic metabolism by the cytochrome P450 pathway were linked to PM2.5 exposure. In contrast, the DEGs enriched in environmental information processing and human diseases, such as viral protein interaction with cytokines and cytokine receptors and epithelial cell signaling in bacterial infection, were significantly related to H3N2 exposure. Meanwhile, co-exposure to PM2.5 and H3N2 affected G protein-coupled receptors on the cell surface. Thus, the results from this study provides insights into PM2.5- and influenza virus-induced airway inflammation and potential mechanisms.

Seasonal extreme temperatures and short-term fine particulate matter increases child respiratory hospitalizations in a sparsely populated region of the intermountain western United States

Background

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Few studies have evaluated these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health.

Methods

We explored short-term exposure to air pollution on childhood respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated hospitalizations. The main outcome measure included all respiratory-related hospital admissions for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for all individuals aged 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis and distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 15 prior-days modified by temperature or season.

Results

Short-term exposure increases of 1 μg/m3 in PM2.5 were associated with elevated odds of all three respiratory hospital admission categories. PM2.5 was associated with the largest increased odds of hospitalizations for asthma at lag 7-13 days [1.87(1.17-2.97)], for LRTI at lag 6-12 days [2.18(1.20-3.97)], and for URTI at a cumulative lag of 13 days [1.29(1.07-1.57)]. The impact of PM2.5 varied by temperature and season for each respiratory outcome scenario. For asthma, PM2.5 was associated most strongly during colder temperatures [3.11(1.40-6.89)] and the winter season [3.26(1.07-9.95)]. Also in colder temperatures, PM2.5 was associated with increased odds of LRTI hospitalization [2.61(1.15-5.94)], but no seasonal effect was observed. Finally, 13 days of cumulative PM2.5 prior to admissions date was associated with the greatest increased odds of URTI hospitalization during summer days [3.35(1.85-6.04)] and hotter temperatures [1.71(1.31-2.22)].

Conclusions

Children's respiratory-related hospital admissions were associated with short-term exposure to PM2.5. PM2.5 associations with asthma and LRTI hospitalizations were strongest during cold periods, whereas associations with URTI were largest during hot periods.

Classification

environmental public health, fine particulate matter air pollution, respiratory infections.

Acute and subchronic exposure to urban atmospheric pollutants aggravate acute respiratory failure in infants

Urban air pollution is a major factor that affects the respiratory health of children and adolescents. Less studied is exposure during the first two years of life. This study analyzed the influence of acute and subchronic exposure to urban air pollutants on the severity of acute respiratory failure (ARF) in the first two years of life. This population-based study included 7364 infants hospitalized with ARF. Acute exposure was considered to have occurred 1, 3 and 7 days before hospitalization and subchronic exposure was considered the mean of the last 30 and 60 days. We found that for acute exposure, significant increases in days of hospitalization (LOS) occurred at lag 1 day for NO2 (0.24), SO2 (6.64), and CO (1.86); lag 3 days for PM10 (0.30), PM2.5 (0.37), SO2 (10.8), and CO (0.71); and lag 7 days for NO2 (0.16), SO2 (5.07) and CO (0.87). Increases in the risk of death occurred at lag 1 day for NO2 (1.06), SO2 (3.64), and CO (1.28); and lag 3 days for NO2 (1.04), SO2 (2.04), and CO (1.19). Subchronic exposures at 30 and 60 days occurred for SO2 (9.18, 3.77) and CO (6.53, 2.97), respectively. The associations were more pronounced with higher temperatures and lower relative humidity levels. We concluded that acute and subchronic exposure to higher atmospheric concentrations of all the pollutants studied were associated with greater severity of ARF. The greatest increases in LOS and risk of death occurred with hot and dry weather.

Spatio-temporal evolution patterns of influenza incidence and its nonlinear spatial correlation with environmental pollutants in China

BACKGROUND

Currently, the influenza epidemic in China is at a high level and mixed with other respiratory diseases. Current studies focus on regional influenza and the impact of environmental pollutants on time series, and lack of overall studies on the national influenza epidemic and the nonlinear correlation between environmental pollutants and influenza. The unclear spatial and temporal evolution patterns of influenza as well as the unclear correlation effect between environmental pollutants and influenza epidemic have greatly hindered the prevention and treatment of influenza epidemic by relevant departments, resulting in unnecessary economic and human losses.

METHOD

This study used Chinese influenza incidence data for 2007-2017 released by the China CDC and air pollutant site monitoring data. Seasonal as well as inter monthly differences in influenza incidence across 31 provinces of China have been clarified through time series. Space-Time Cube model (STC) was used to investigate the spatio-temporal evolution of influenza incidence in 315 Chinese cities during 2007-2017. Then, based on the spatial heterogeneity of influenza incidence in China, Generalized additive model (GAM) was used to identify the correlation effect of environmental pollutants (PM2.5, PM10, CO, SO2, NO2, O3) and influenza incidence.

RESULT

The influenza incidence in China had obvious seasonal changes, with frequent outbreaks in winter and spring. The influenza incidence decreased significantly after March, with only sporadic outbreaks occurring in some areas. In the past 11 years, the influenza epidemic had gradually worsened, and the clustering of influenza had gradually expanded, which had become a serious public health problem. The correlation between environmental pollutants and influenza incidence was nonlinear. Generally, PM2.5, CO and NO2 were positively correlated at high concentrations, while PM10 and SO2 were negatively correlated. O3 was not strongly correlated with the influenza incidence.

CONCLUSION

The study found that the influenza epidemic in China was in a rapidly rising stage, and several regions had a multi-year outbreak trend and the hot spots continue to expand outward. The association between environmental pollutants and influenza incidence was nonlinear and spatially heterogeneous. Relevant departments should improve the monitoring of influenza epidemic, optimize the allocation of resources, reduce environmental pollution, and strengthen vaccination to effectively prevent the aggravation and spread of influenza epidemic in the high incidence season and areas.

Seasonal associations between air pollutants and influenza in 10 cities of southern China

Few studies have explored the associations between air pollutants and influenza across seasons, especially at large scales. This study aimed to evaluate seasons' modifying effects on associations between air pollutants and influenza from 10 cities of southern China. Through scientific evidence, it provides mitigation and adaptation strategies with practical guidelines to local health authorities and environmental protection agencies. Daily influenza incidence, meteorological, and air pollutants data from 2016 to 2019 were collected. Quasi-Poisson regression with a distributed lag nonlinear model was used to evaluate city-specific air pollutants and influenza associations. Meta-analysis was used to pool site-specific estimates. Attributable fractions (AFs) of influenza incidence due to pollutants were calculated. Stratified analyses were conducted by season, sex, and age. Overall, the cumulative relative risk (CRR) of influenza incidence for a 10-unit increase in PM_2.5, PM₁₀, SO₂, NO₂, and CO was 1.45 (95% CI: 1.25, 1.68), 1.53 (95% CI: 1.29, 1.81), 1.87 (95% CI: 1.40, 2.48), 1.74 (95% CI: 1.49, 2.03), and 1.19 (95% CI: 1.04, 1.36), respectively. Children aged 0-17 were more sensitive to air pollutants in spring and winter. PM₁₀ had greater effect on influenza than PM_2.5 in autumn, winter, and overall, lesser in spring. The overall AF due to PM_2.5, PM₁₀, SO₂, NO_2, and CO was 4.46% (95% eCI: 2.43%, 6.43%), 5.03% (95% eCI: 2.33%, 7.56%), 5.36% (95% eCI: 3.12%, 7.58%), 24.88% (95% eCI: 18.02%, 31.67%), and 23.22% (95% eCI: 17.56%, 28.61%), respectively. AF due to O₃ was 10.00% (95% eCI: 4.76%, 14.95%) and 3.65% (95% eCI: 0.50%, 6.59%) in spring and summer, respectively. The seasonal variations in the associations between air pollutants and influenza in southern China would provide evidence to service providers for tailored intervention, especially for vulnerable populations.

Inferring a Causal Relationship between Environmental Factors and Respiratory Infections Using Convergent Cross-Mapping

The incidence of respiratory infections in the population is related to many factors, among which environmental factors such as air quality, temperature, and humidity have attracted much attention. In particular, air pollution has caused widespread discomfort and concern in developing countries. Although the correlation between respiratory infections and air pollution is well known, establishing causality between them remains elusive. In this study, by conducting theoretical analysis, we updated the procedure of performing the extended convergent cross-mapping (CCM, a method of causal inference) to infer the causality between periodic variables. Consistently, we validated this new procedure on the synthetic data generated by a mathematical model. For real data in Shaanxi province of China in the period of 1 January 2010 to 15 November 2016, we first confirmed that the refined method is applicable by investigating the periodicity of influenza-like illness cases, an air quality index, temperature, and humidity through wavelet analysis. We next illustrated that air quality (quantified by AQI), temperature, and humidity affect the daily influenza-like illness cases, and, in particular, the respiratory infection cases increased progressively with increased AQI with a time delay of 11 days.

Impact of PM2.5 and ozone on incidence of influenza in Shijiazhuang, China: a time-series study

Most of the studies are focused on influenza and meteorological factors for influenza. There are still few studies focused on the relationship between pollution factors and influenza, and the results are not consistent. This study conducted distributed lag nonlinear model and attributable risk on the relationship between influenza and pollution factors, aiming to quantify the association and provide a basis for the prevention of influenza and the formulation of relevant policies. Environmental data in Shijiazhuang from 2014 to 2019, as well as the data on hospital-confirmed influenza, were collected. When the concentration of PM_2.5 was the highest (621 μg/m³), the relative risk was the highest (RR: 2.39, 95% CI: 1.10-5.17). For extremely high concentration PM_2.5 (348 μg/m³), analysis of cumulative lag effect showed statistical significance from cumulative lag0-1 to lag0-6 day, and the minimum cumulative lag effect appeared in lag0-2 (RR: 0.760, 95% CI: 0.655-0.882). In terms of ozone, the RR value was 2.28(1.19,4.38), when O₃ concentration was 310 μg/m³, and the RR was 1.65(1.26,2.15), when O₃ concentration was 0 μg/m³. The RR of this lag effect increased with the increase of lag days, and reached the maximum at lag0-7 days, RR and 95% CI of slightly low concentration and extremely high concentration were 1.217(1.108,1.337) and 1.440(1.012,2.047), respectively. Stratified analysis showed that there was little difference in gender, but in different age groups, the cumulative lag effect of these two pollutants on influenza was significantly different. Our study found a non-linear relationship between two pollutants and influenza; slightly low concentrations were more associated with contaminant-related influenza. Health workers should encourage patients to get the influenza vaccine and wear masks when going out during flu seasons.

The influence of air quality and meteorological variations on influenza A and B virus infections in a paediatric population in Singapore

INTRODUCTION

Influenza is an important cause of paediatric illness across the globe. However, information about the relationships between air pollution, meteorological variability and paediatric influenza A and B infections in tropical settings is limited.

METHODS

We analysed all daily reports of influenza A and B infections in children <5 years old obtained from the largest specialist women and children's hospital in Singapore. In separate negative binomial regression models, we assessed the dependence of paediatric influenza A and B infections on air quality and meteorological variability, using multivariable fractional polynomial modelling and adjusting for time-varying confounders.

RESULTS

Approximately 80% of 7329 laboratory-confirmed reports were caused by influenza A. We observed positive associations between sulphur dioxide (SO₂) exposure and the subsequent risk of infection with both influenza types. We observed evidence of a harvesting effect of SO₂ on Influenza A but not Influenza B. Ambient temperature was associated with a decline in influenza A reports (Relative Risk at lag 5 [RR_lag5]: 0.949, 95% CI: 0.916-0.983). Rainfall was positively associated with a subsequent increase in influenza A reports (RR_lag3: 1.044, 95% CI: 1.017-1.071). Nitrogen dioxide (NO₂) concentration was positively associated with influenza B reports (RR_lag5: 1.015, 95% CI: 1.005-1.025). There was a non-linear association between CO and influenza B reports. Absolute humidity increased the ensuing risk of influenza B (RR_lag5: 4.799, 95% CI: 2.277-10.118). Influenza A and B infections displayed dissimilar but predictable within-year seasonal patterns.

CONCLUSIONS

We observed different independent associations between air quality and meteorological variability with paediatric influenza A and B infections. Anticipated seasonal infection peaks and variations in air quality and meteorological parameters can inform the timing of community measures aimed at reducing influenza infection risk.

Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PM2.5) from biomass combustion using bioinformatics analysis

BACKGROUND

Long-term exposure to PM2.5 from burning domestic substances has been linked to an increased risk of lung disease, but the underlying mechanisms are unclear. This study is to explore the hub genes and pathways involved in PM2.5 toxicity in human bronchial epithelial BEAS-2B cells.

METHODS

The GSE158954 dataset is downloaded from the GEO database. Differentially expressed genes (DEGs) were screened using the limma package in RStudio (version 4.2.1). In addition, DEGs analysis was performed by Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A protein-protein interaction (PPI) network was constructed, MCODE plug-in and the cytoHubba plug-in in Cytoscape software was used to identify the hub genes. Finally, CytoHubba and DEGs were used to integrate the hub genes, and preliminary validation was performed by comparing the toxicology genomics database (CTD). Differential immune cell infiltration was investigated using the CIBERSORT algorithm.

RESULTS

A total of 135 DEGs were identified, of which 57 were up-regulated and 78 were down-regulated. Functional enrichment analyses in the GO and KEGG indicated the potential involvement of DEGs was mainly enriched in the regulation of endopeptidase activity and influenza A. Gene Set Enrichment Analysis revealed that Chemical Carcinogenesis - DNA adducts were remarkably enriched in PM2.5 groups. 53 nodes and 198 edges composed the PPI network. Besides, 5 direct-acting genes were filtered at the intersection of cytohubba plug-in, MCODE plug-in and CTD database. There is a decreasing trend of dendritic cells resting after BEAS-2B cells long-term exposure to PM2.5.

CONCLUSIONS

The identified DEGs, modules, pathways, and hub genes provide clues and shed light on the potential molecular mechanisms of BEAS-2B cells upon long-term exposure to PM2.5.

Effects of the COVID-19 lockdown and recovery on People's mobility and air quality in the United Arab Emirates using satellite and ground observations

The stringent COVID-19 lockdown measures in 2020 significantly impacted people's mobility and air quality worldwide. This study presents an assessment of the impacts of the lockdown and the subsequent reopening on air quality and people's mobility in the United Arab Emirates (UAE). Google's community mobility reports and UAE's government lockdown measures were used to assess the changes in the mobility patterns. Time-series and statistical analyses of various air pollutants levels (NO₂, O₃, SO₂, PM₁₀, and aerosol optical depth-AOD) obtained from satellite images and ground monitoring stations were used to assess air quality. The levels of pollutants during the initial lockdown (March to June 2020) and the subsequent gradual reopening in 2020 and 2021 were compared with their average levels during 2015-2019. During the lockdown, people's mobility in the workplace, parks, shops and pharmacies, transit stations, and retail and recreation sectors decreased by about 34%-79%. However, the mobility in the residential sector increased by up to 29%. The satellite-based data indicated significant reductions in NO₂ (up to 22%), SO₂ (up to 17%), and AOD (up to 40%) with small changes in O₃ (up to 5%) during the lockdown. Similarly, data from the ground monitoring stations showed significant reductions in NO₂ (49% - 57%) and PM₁₀ (19% - 64%); however, the SO₂ and O₃ levels showed inconsistent trends. The ground and satellite-based air quality levels were positively correlated for NO₂, PM₁₀, and AOD. The data also demonstrated significant correlations between the mobility and NO₂ and AOD levels during the lockdown and recovery periods. The study documents the impacts of the lockdown on people's mobility and air quality and provides useful data and analyses for researchers, planners, and policymakers relevant to managing risk, mobility, and air quality.

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.

Does air pollution explain COVID-19 fatality and mortality rates? A multi-city study in São Paulo state, Brazil

Since air pollution compromise the respiratory system and COVID-19 disease is caused by a respiratory virus, it is expected that air pollution plays an important role in the current COVID-19 pandemic. Exploratory studies have observed positive associations between air pollution and COVID-19 cases, deaths, fatality, and mortality rate. However, no study focused on Brazil, one of the most affected countries by the pandemic. Thus, this study aimed to understand how long-term exposure to PM₁₀, PM_2.5, and NO₂ contributed to COVID-19 fatality and mortality rates in São Paulo state in 2020. Air quality data between 2015 and 2019 in 64 monitoring stations within 36 municipalities were considered. The COVID-19 fatality was calculated considering cases and deaths from the government's official data and the mortality rate was calculated considering the 2020 population. Linear regression models were well-fitted for PM_2.5 concentration and fatality (R² = 0.416; p = 0.003), NO₂ concentration and fatality (R² = 0.232; p = 0.005), and NO₂ concentration and mortality (R² = 0.273; p = 0.002). This study corroborates other authors' findings and enriches the discussion for having considered a longer time series to represent long-term exposure to the pollutants and for having considered one of the regions with the highest incidence of COVID-19 in the world. Thus, it reinforces measures to reduce the concentration of air pollutants which are essential for public health and will increase the chance to survive in future respiratory disease epidemics.

Short-term air pollution exposure and COVID-19 infection in the United States

The Sars-CoV-2 disease (known as COVID-19) has become a global public health emergency. Researchers have been unveiling the transmission mechanisms and disclosing possible contributing factors. Studies have theorized plausible linkage mechanisms between air pollution exposure and COVID-19 infection and have divided the air pollution exposure into two types: long-term exposure and short-term exposure. However, present studies on impacts of short-term exposure have not reached a conclusive result and are mostly focusing on Asian and European countries. In this study, we conduct a nationwide analysis to examine the association between short-term air pollution exposure and COVID-19 infection in the United States. Daily confirmed cases, air pollution information, and meteorological factors at the county level were collected between March 1st and June 30th, 2020. A total of 806 (out of 3143) counties were included in this study, with 554 counties for PM2.5 and 670 counties for ozone (O3), which account for around 2.1 million cumulative confirmed cases, i.e., about 80% of all confirmed cases in the U.S. over the study period. A generalized additive model was applied to investigate the relationship between short-term exposure to PM2.5/O3 and COVID-19 confirmed cases. The statistically significant results indicate that, with every 10 μg/m3 increase in mean pollutant concentration, the number of daily confirmed cases increases by 9.41% (CI: 8.77%-10.04%) for PM2.5 and by 2.42% (CI: 1.56%-3.28%) for O3. The relative risks associated with short-term PM2.5 exposure remain positive after isolating the impacts of long-term exposure. The results of this study suggest that short-term exposure to air pollution, especially to PM2.5, may contribute to the spread and course of the pandemic. This finding has important implications for policymakers and the public to take preventive measures such as staying at home on polluted days while improving ventilation indoors to lower the probability of infection.

Long-Term Air Pollution Exposure and COVID-19 Mortality: A Patient-Level Analysis from New York City

RATIONALE

Risk factors for COVID-19 mortality may include environmental exposures, such as air pollution.

OBJECTIVES

Determine whether, amongst adults hospitalized with PCR-confirmed COVID-19, long-term air pollution exposure is associated with risk for mortality, intensive care unit (ICU) admission or intubation.

METHODS

We performed a retrospective analysis of SARS-CoV-2 PCR positive patients admitted to seven New York City hospitals from March 8, 2020 to August 30, 2020. The primary outcome was mortality; secondary outcomes were ICU admission and intubation. We estimated the annual average fine particulate matter (PM2.5), nitrogen dioxide (NO2) and black carbon (BC) concentrations at patients' residential addresses. We employed double-robust Poisson regression to analyze associations between annual average PM2.5, NO2 and BC exposure and COVID-19 outcomes, adjusting for age, sex, race/ethnicity, hospital, insurance and time from onset of the pandemic.

RESULTS

Of the 6,542 patients, 41% were female and aged median 65 years (IQR 53, 77). Over 50% self-identified as a person of color [N=1,687 (26%) Hispanic, N=1,659 (25%) Black]. Air pollution exposures were generally low. Overall, 31% (N=2,044) of the cohort died, 19% (N=1,237) were admitted to the ICU and 16% (1,051) were intubated. In multivariable models, higher long-term exposure to PM2.5 was associated with increased risk of mortality (RR 1.11, 95% CI 1.02, 1.21 per 1µg/m3 increase in PM2.5) and ICU admission (RR 1.13, 95% CI 1.00, 1.28 per 1µg/m3 increase in PM2.5). In multivariable models, neither NO2 nor BC exposure was associated with COVID-19 mortality, ICU admission or intubation.

CONCLUSIONS

Amongst patients hospitalized with COVID-19, higher long-term PM2.5 exposure was associated with increased risk of mortality and ICU admission. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of COVID-19 Diffusion in the Lombardy Region (Italy)

Background: the Lombardy region in Italy was the first area in Europe to record an outbreak of COVID-19 and one of the most affected worldwide. As this territory is strongly polluted, it was hypothesized that pollution had a role in facilitating the diffusion of the epidemic, but results are uncertain. Aim: the paper explores the effect of air pollutants in the first spread of COVID-19 in Lombardy, with a novel geomatics approach addressing the possible confounding factors, the reliability of data, the measurement of diffusion speed, and the biasing effect of the lockdown measures. Methods and results: all municipalities were assigned to one of five possible territorial classes (TC) according to land-use and socio-economic status, and they were grouped into districts of 100,000 residents. For each district, the speed of COVID-19 diffusion was estimated from the ambulance dispatches and related to indicators of mean concentration of air pollutants over 1, 6, and 12 months, grouping districts in the same TC. Significant exponential correlations were found for ammonia (NH₃) in both prevalently agricultural (R² = 0.565) and mildly urbanized (R² = 0.688) areas. Conclusions: this is the first study relating COVID-19 estimated speed of diffusion with indicators of exposure to NH₃. As NH₃ could induce oxidative stress, its role in creating a pre-existing fragility that could have facilitated SARS-CoV-2 replication and worsening of patient conditions could be speculated.

COVID-19 and a Green Recovery?

Preliminary evidence indicates that pollution increases the severity and likelihood of COVID-19 infections similar to many other infectious diseases. This paper models the interaction of pollution and disease preventive actions, either pharmaceutical or non-pharmaceutical interventions, on transmission of infectious diseases in a neoclassical growth framework. There are two externalities - households do not take into account how their actions affect disease transmission, and productive activity results in pollution which increases the likelihood of infections. The disease dynamics are modeled to be of SIS type. We study the difference in health and economic outcomes between the decentralized economy, where households do not internalize externalities, and socially optimal outcomes, and characterize the taxes and subsidies that decentralize the latter. Thus, we examine the question whether there are sufficient incentives to reduce pollution, at both private and public levels, once its effects on disease transmission is considered. In competitive outcomes, pollution increases with increased productivity. The socially efficient outcome has higher pollution than a competitive outcome, despite increase in abatement, as the effect of higher productivity and larger labor supply dominates. The results question the hopes of a Green Recovery.

Viral respiratory infections and air pollutants

Air pollution is a public health issue of global importance and a risk factor for developing cardiorespiratory diseases. These contaminants induce reactive oxygen species (ROS) and increased pro-inflammatory cytokines such as IL-1β, IL-6, and IL-8, triggering the inflammatory response that alters cell and tissue homeostasis and facilitates the development of diseases. The effects of air pollutants such as ozone, particulate matter (PM10, PM2.5, and PM0.1), and indoor air pollutants on respiratory health have been widely reported. For instance, epidemiological and experimental studies have shown associations between hospital admissions for individual diseases and increased air pollutant levels. This review describes the association and relationships between exposure to air pollutants and respiratory viral infections, especially those caused by the respiratory syncytial virus and influenza virus. The evidence suggests that exposure to air contaminants induces inflammatory states, modulates the immune system, and increases molecules' expression that favors respiratory viruses' pathogenesis and affects the respiratory system. However, the mechanisms underlying these interactions have not yet been fully elucidated, so it is necessary to develop new studies to obtain information that will allow health and policy decisions to be made for the adequate control of respiratory infections, especially in the most vulnerable population, during periods of maximum air pollution.

The role of airborne particles and environmental considerations in the transmission of SARS-CoV-2

Corona Virus Disease 2019 (COVID-19) caused by the novel coronavirus, results in an acute respiratory condition coronavirus 2 (SARS-CoV-2) and is highly infectious. The recent spread of this virus has caused a global pandemic. Currently, the transmission routes of SARS-CoV-2 are being established, especially the role of environmental transmission. Here we review the environmental transmission routes and persistence of SARS-CoV-2. Recent studies have established that the transmission of this virus may occur, amongst others, in the air, water, soil, cold-chain, biota, and surface contact. It has also been found that the survival potential of the SARS-CoV-2 virus is dependent on different environmental conditions and pollution. Potentially important pathways include aerosol and fecal matter. Particulate matter may also be a carrier for SARS-CoV-2. Since microscopic particles can be easily absorbed by humans, more attention must be focused on the dissemination of these particles. These considerations are required to evolve a theoretical platform for epidemic control and to minimize the global threat from future epidemics.

Advances on the immunotoxicity of outdoor particulate matter: A focus on physical and chemical properties and respiratory defence mechanisms

Particulate matter (PM) is acknowledged to have multiple detrimental effects on human health. In this review, we report literature results on the possible link between outdoor PM and health outcomes with a focus on pulmonary infections and the mechanisms responsible for observed negative effects. PM physical and chemical properties, such as size and chemical composition, as well as major emission sources are described for a more comprehensive view about the role played by atmospheric PM in the observed adverse health effects; to this aim, major processes leading to the deposition of PM in the respiratory tract and how this can pave the way to the onset of pathologies are also presented. From the literature works here reviewed, two ways in which PM can threaten human health promoting respiratory infectious diseases are mostly taken into account. The first pathway is related to an enhanced susceptibility and here we will also report on molecular mechanisms in the lung immune system responsible for the augmented susceptibility to pathogens, such as the damage of mechanical defensive barriers, the alteration of the innate immune response, and the generation of oxidative stress. The second one deals with the relationship between infectious agents and PM; here we recall that viruses and bacteria (BioPM) are themselves part of atmospheric PM and are collected during sampling together with particles of different origin; so, data should be analysed with caution in order to avoid any false cause-effect relation. To face these issues a multidisciplinary approach is mandatory as also evident from the ongoing research about the mechanisms hypothesized for the SARS-CoV-2 airborne spreading, which is still controversial and claims for further investigation. Therefore, we preferred not to include papers dealing with SARS-CoV-2.

Pandemic meets pollution: Poor air quality increases deaths by COVID-19

We study the impact of short-term exposure to ambient air pollution on the spread and severity of COVID-19 in Germany. We combine data at the county-by-day level on confirmed cases and deaths with information on local air quality and weather conditions. Following Deryugina et al. (2019), we instrument short-term variation in local concentrations of particulate matter (PM10) by region-specific daily variation in wind directions. We find significant positive effects of PM10 concentration on death numbers from four days before to ten days after the onset of symptoms. Specifically, for elderly patients (80+ years) an increase in ambient PM10 concentration by one standard deviation between two and four days after developing symptoms increases the number of deaths by 19 percent of a standard deviation. In addition, higher levels air pollution raise the number of confirmed cases of COVID-19 for all age groups. The timing of effects surrounding the onset of illness suggests that air pollution affects the severity of already-realized infections. We discuss the implications of our results for immediate policy levers to reduce the exposure and level of ambient air pollution, as well as for cost-benefit considerations of policies aiming at sustainable longer-term reductions of pollution levels.

Independent association between meteorological factors, PM2.5, and seasonal influenza activity in Hangzhou, Zhejiang province, China

BACKGROUND

Due to variations in climatic conditions, the effects of meteorological factors and PM2.5 on influenza activity, particularly in subtropical regions, vary in existing literature. In this study, we examined the relationship between influenza activity, meteorological parameters, and PM2.5 .

METHODS

A total of 20 165 laboratory-confirmed influenza cases in Hangzhou, Zhejiang province, were documented in our dataset and aggregated into weekly counts for downstream analysis. We employed a combination of the quasi-Poisson-generalized additive model and the distributed lag non-linear model to examine the relationship of interest, controlling for long-term trends, seasonal trends, and holidays.

RESULTS

A hockey-stick association was found between absolute humidity and the risk of influenza infections. The overall cumulative adjusted relative risk (ARR) was statistically significant when weekly mean absolute humidity was low (<10 µg/m3 ) and high (>17.5 µg/m3 ). A slightly higher ARR was observed when weekly mean temperature reached over 30.5°C. A statistically significantly higher ARR was observed when weekly mean relative humidity dropped below 67%. ARR increased statistically significantly with increasing rainfall. For PM2.5 , the ARR was marginally statistically insignificant. In brief, high temperature, wet and dry conditions, and heavy rainfall were the major risk factors associated with a higher risk of influenza infections.

CONCLUSIONS

The present study contributes additional knowledge to the understanding of the effects of various environmental factors on influenza activities. Our findings shall be useful and important for the development of influenza surveillance and early warning systems.

Air pollutants and outpatient visits for influenza-like illness in Beijing, China

Background

Air pollution leads to many adverse health conditions, mainly manifested by respiratory or cardiac symptoms. Previous studies are limited as to whether air pollutants were associated to influenza-like illness (ILI). This study aimed to explore the association between air pollutants and outpatient visits for ILI, especially during an outbreak of influenza.

Methods

Daily counts of hospital visits for ILI were obtained from Peking University Third Hospital between January 1, 2015, and March 31, 2018. A generalized additive Poisson model was applied to examine the associations between air pollutants concentrations and daily outpatient visits for ILI when adjusted for the meteorological parameters.

Results

There were 35862 outpatient visits at the fever clinic for ILI cases. Air quality index (AQI), PM_2.5, PM₁₀, CO and O₃ on lag0 days, as well as nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) on lag1 days, were significantly associated with an increased risk of outpatient visits for ILI from January 2015 to November 2017. From December 2017 to March 2018, on lag0 days, air pollutants PM_2.5 [risk ratio (RR) = 0.971, 95% CI: 0.963-0.979], SO₂ (RR = 0.892, 95% CI: 0.840–0.948) and CO (RR = 0.306, 95% CI: 0.153–0.612) were significantly associated with a decreased risk of outpatient visits for ILI. Interestingly, on the lag2 days, all the pollutants were significantly associated with a reduced risk of outpatient visits for ILI except for O₃. We did not observe the linear correlations between the outpatient visits for ILI and any of air pollutants, which were instead associated via a curvilinear relationship.

Conclusions

We found that the air pollutants may be associated with an increased risk of outpatient visits for ILI during the non-outbreak period and with a decreased risk during the outbreak period, which may be linked with the use of disposable face masks and the change of outdoor activities. These findings expand the current knowledge of ILI outpatient visits correlated with air pollutants during an influenza pandemic.

Relationship between Air Pollutant Exposure and Gynecologic Cancer Risk

Exposure to air pollution has been suggested to be associated with an increased risk of women's health disorders. However, it remains unknown to what extent changes in ambient air pollution affect gynecological cancer. In our case-control study, the logistic regression model was combined with the restricted cubic spline to examine the association of short-term exposure to air pollution with gynecological cancer events using the clinical data of 35,989 women in Beijing from December 2008 to December 2017. We assessed the women's exposure to air pollutants using the monitor located nearest to each woman's residence and working places, adjusting for age, occupation, ambient temperature, and ambient humidity. The adjusted odds ratios (ORs) were examined to evaluate gynecologic cancer risk in six time windows (Phase 1-Phase 6) of women's exposure to air pollutants (PM2.5, CO, O3, and SO2) and the highest ORs were found in Phase 4 (240 days). Then, the higher adjusted ORs were found associated with the increased concentrations of each pollutant (PM2.5, CO, O3, and SO2) in Phase 4. For instance, the adjusted OR of gynecological cancer risk for a 1.0-mg m-3 increase in CO exposures was 1.010 (95% CI: 0.881-1.139) below 0.8 mg m-3, 1.032 (95% CI: 0.871-1.194) at 0.8-1.0 mg m-3, 1.059 (95% CI: 0.973-1.145) at 1.0-1.4 mg m-3, and 1.120 (95% CI: 0.993-1.246) above 1.4 mg m-3. The ORs calculated in different air pollution levels accessed us to identify the nonlinear association between women's exposure to air pollutants (PM2.5, CO, O3, and SO2) and the gynecological cancer risk. This study supports that the gynecologic risks associated with air pollution should be considered in improved public health preventive measures and policymaking to minimize the dangerous effects of air pollution.

Cumulative Effects of Particulate Matter Pollution and Meteorological Variables on the Risk of Influenza-Like Illness

The cold season is usually accompanied by an increased incidence of respiratory infections and increased air pollution from combustion sources. As we are facing growing numbers of COVID-19 cases caused by the novel SARS-CoV-2 coronavirus, an understanding of the impact of air pollutants and meteorological variables on the incidence of respiratory infections is crucial. The incidence of influenza-like illness (ILI) can be used as a close proxy for the circulation of influenza viruses. Recently, SARS-CoV-2 has also been detected in patients with ILI. Using distributed lag nonlinear models, we analyzed the association between ILI, meteorological variables and particulate matter concentration in Bialystok, Poland, from 2013–2019. We found an exponential relationship between cumulative PM_2.5 pollution and the incidence of ILI, which remained significant after adjusting for air temperatures and a long-term trend. Pollution had the greatest effect during the same week, but the risk of ILI was increased for the four following weeks. The risk of ILI was also increased by low air temperatures, low absolute humidity, and high wind speed. Altogether, our results show that all measures implemented to decrease PM_2.5 concentrations would be beneficial to reduce the transmission of SARS-CoV-2 and other respiratory infections.

Relationship between ambient PM2.5 exposure and blood cadmium level in children under 14 years in Beijing, China

Ambient PM_2.5 pollution is a global environmental problem. PM_2.5 can act as a carrier of heavy metals. However, the relationship between PM_2.5 exposure and blood cadmium (Cd) level in children was less understood. Based on the data of hourly collected PM_2.5 and blood Cd level of 13,626 children aged 0-14 years from Apr. 2008 to Feb. 2013 in Beijing of China, we investigated the short-term effects of PM_2.5 exposure on blood Cd level. Generalized linear mixed models (GLMMs) were utilized to explore the potential association between PM_2.5 exposure and blood Cd level of children. The results showed that the mean blood Cd level was 0.64 μg/L. There was a significant association between PM_2.5 exposure and blood Cd level (P < 0.05). Age was negatively associated with blood Cd level (P < 0.05), and the younger children were more sensitive to Cd from PM_2.5 exposure. There wasn't a significant difference in PM_2.5 concentration between heating and non-heating seasons in winter (P > 0.05); there was also no gender difference of children on blood Cd level (P > 0.05). The present study demonstrates the importance of controlling the PM_2.5 bound Cd exposure, and environmental countermeasures should be implemented stringently to reduce their impact on children's health.

SARS-CoV-2 infection, COVID-19 pathogenesis, and exposure to air pollution: What is the connection?

Exposure to air pollutants has been previously associated with respiratory viral infections, including influenza, measles, mumps, rhinovirus, and respiratory syncytial virus. Epidemiological studies have also suggested that air pollution exposure is associated with increased cases of SARS-CoV-2 infection and COVID-19-associated mortality, although the molecular mechanisms by which pollutant exposure affects viral infection and pathogenesis of COVID-19 remain unknown. In this review, we suggest potential molecular mechanisms that could account for this association. We have focused on the potential effect of exposure to nitrogen dioxide (NO2 ), ozone (O3 ), and particulate matter (PM) since there are studies investigating how exposure to these pollutants affects the life cycle of other viruses. We have concluded that pollutant exposure may affect different stages of the viral life cycle, including inhibition of mucociliary clearance, alteration of viral receptors and proteases required for entry, changes to antiviral interferon production and viral replication, changes in viral assembly mediated by autophagy, prevention of uptake by macrophages, and promotion of viral spread by increasing epithelial permeability. We believe that exposure to pollutants skews adaptive immune responses toward bacterial/allergic immune responses, as opposed to antiviral responses. Exposure to air pollutants could also predispose exposed populations toward developing COIVD-19-associated immunopathology, enhancing virus-induced tissue inflammation and damage.

Double trouble: combined cardiovascular effects of particulate matter exposure and coronavirus disease 2019

The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly grown into a pandemic. According to initial reports, the lungs were thought to be the primary target, but recent case studies have shown its reach can extend to other organs including the heart and blood vessels. The severity of cardiac complications of COVID-19 depends on multiple underlying factors, with air pollutant exposure being one of them, as reported by several recent studies. Airborne particulate matter (PM) attracts heightened attention due to its implication in various diseases, especially respiratory and cardiovascular diseases. Inhaled PM not only carries microorganisms inside the body but also elicits local and systemic inflammatory responses resulting in altering the host’s immunity and increasing susceptibility to infection. Previous and recent studies have documented that PM acts as a ‘carrier’ for the virus and aids in spreading viral infections. This review presents the mechanisms and effects of viral entry and how pollution can potentially modulate pathophysiological processes in the heart. We aimed to concisely summarize studies examining cardiovascular outcomes in COVID-19 patients and postulate on how PM can influence these outcomes. We have also reviewed evidence on the use of renin–angiotensin system inhibitors, namely angiotensin-converting enzyme inhibitors and angiotensin receptor blockers, in patients with COVID-19. The interplay of pollution and SARS-CoV-2 is essential to understanding the effects of accentuated cardiovascular effects of COVID-19 and deserves in-depth experimental investigations.

Short-term effects of ambient air pollution on the incidence of influenza in Wuhan, China: A time-series analysis

BACKGROUND

Evidence suggests that air pollution is associated with many adverse health outcomes such as cardiovascular diseases (CVD), respiratory diseases, cancer, and birth defects. Yet few studies dig into the relationship between air pollution and airborne infectious diseases.

METHODS

Daily data on influenza incidence were obtained from Hubei Provincial Center for Disease Control and Prevention (Hubei CDC). Data on air pollutants including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ground-level ozone (O₃), particulate matter (PM) with aerodynamic diameter ≤ 2.5 μm (PM_2.5), and PM with aerodynamic diameter ≤ 10 μm (PM₁₀) were retrieved from ten national air sampling stations located at Wuhan. We applied generalized additive model (GAM) to estimate the associations between air pollution and the risk of influenza in Wuhan, China during 2015-2017.

RESULTS

In the single-day lag model, the largest effect estimates were observed at lag 0. An increased relative risk (RR) of influenza was significantly associated with a 10 μg/m³ increase in SO₂ (RR: 1.099; 95% confidence interval [CI]: 1.011-1.195), NO₂ (RR: 1.039; 95% CI: 1.013-1.065), and O₃ (RR: 1.005; 95% CI: 0.994-1.016), respectively. In the multi-day lag model, concentrations of SO₂, NO₂, and O₃ were statistically significantly associated with the risk of influenza at lag 0-1. The seasonal analysis suggests that the influence of air pollution on influenza is greater in the cold season as compared in the warm season in the early lag days. The multi-pollutant model indicates that NO₂ may be a potential confounder for co-pollutants.

CONCLUSIONS

Our study shows that air pollution may be associated with the risk of influenza in a broad sense. Therefore, when formulating policies to deal with influenza outbreaks in the future, factors regarding air pollution should be taken into consideration.

Machine learning reveals that prolonged exposure to air pollution is associated with SARS-CoV-2 mortality and infectivity in Italy

Air pollution can increase the risk of respiratory diseases, enhancing the susceptibility to viral and bacterial infections. Some studies suggest that small air particles facilitate the spread of viruses and also of the new coronavirus, besides the direct person-to-person contagion. However, the effects of the exposure to particulate matter and other contaminants on SARS-CoV-2 has been poorly explored. Here we examined the possible reasons why the new coronavirus differently impacted on Italian regional and provincial populations. With the help of artificial intelligence, we studied the importance of air pollution for mortality and positivity rates of the SARS-CoV-2 outbreak in Italy. We discovered that among several environmental, health, and socio-economic factors, air pollution and fine particulate matter (PM2.5), as its main component, resulted as the most important predictors of SARS-CoV-2 effects. We also found that the emissions from industries, farms, and road traffic - in order of importance - might be responsible for more than 70% of the deaths associated with SARS-CoV-2 nationwide. Given the major contribution played by air pollution (much more important than other health and socio-economic factors, as we discovered), we projected that, with an increase of 5-10% in air pollution, similar future pathogens may inflate the epidemic toll of Italy by 21-32% additional cases, whose 19-28% more positives and 4-14% more deaths. Our findings, demonstrating that fine-particulate (PM2.5) pollutant level is the most important factor to predict SARS-CoV-2 effects that would worsen even with a slight decrease of air quality, highlight that the imperative of productivity before health and environmental protection is, indeed, a short-term/small-minded resolution.

Regional and global contributions of air pollution to risk of death from COVID-19

AIMS

The risk of mortality from the coronavirus disease that emerged in 2019 (COVID-19) is increased by comorbidity from cardiovascular and pulmonary diseases. Air pollution also causes excess mortality from these conditions. Analysis of the first severe acute respiratory syndrome coronavirus (SARS-CoV-1) outcomes in 2003, and preliminary investigations of those for SARS-CoV-2 since 2019, provide evidence that the incidence and severity are related to ambient air pollution. We estimated the fraction of COVID-19 mortality that is attributable to the long-term exposure to ambient fine particulate air pollution.

METHODS AND RESULTS

We characterized global exposure to fine particulates based on satellite data, and calculated the anthropogenic fraction with an atmospheric chemistry model. The degree to which air pollution influences COVID-19 mortality was derived from epidemiological data in the USA and China. We estimate that particulate air pollution contributed ∼15% (95% confidence interval 7-33%) to COVID-19 mortality worldwide, 27% (13 - 46%) in East Asia, 19% (8-41%) in Europe, and 17% (6-39%) in North America. Globally, ∼50-60% of the attributable, anthropogenic fraction is related to fossil fuel use, up to 70-80% in Europe, West Asia, and North America.

CONCLUSION

Our results suggest that air pollution is an important cofactor increasing the risk of mortality from COVID-19. This provides extra motivation for combining ambitious policies to reduce air pollution with measures to control the transmission of COVID-19.

The role of air pollution (PM and NO2) in COVID-19 spread and lethality: A systematic review

A new coronavirus (SARS-CoV-2) has determined a pneumonia outbreak in China (Wuhan, Hubei Province) in December 2019, called COVID-19 disease. In addition to the person-to person transmission dynamic of the novel respiratory virus, it has been recently studied the role of environmental factors in accelerate SARS-CoV-2 spread and its lethality. The time being, air pollution has been identified as the largest environmental cause of disease and premature death in the world. It affects body's immunity, making people more vulnerable to pathogens. The hypothesis that air pollution, resulting from a combination of factors such as meteorological data, level of industrialization as well as regional topography, can acts both as a carrier of the infection and as a worsening factor of the health impact of COVID-19 disease, has been raised recently. With this review, we want to provide an update state of art relating the role of air pollution, in particular PM_2.5, PM₁₀ and NO₂, in COVID-19 spread and lethality. The Authors, who first investigated this association, often used different research methods or not all include confounding factors whenever possible. In addition, to date incidence data are underestimated in all countries and to a lesser extent also mortality data. For this reason, the cases included in the reviewed studies cannot be considered conclusive. Although it determines important limitations for direct comparison of results, and more studies are needed to strengthen scientific evidences and support firm conclusions, major findings are consistent, highlighting the important contribution of PM_2.5 and NO₂ as triggering of the COVID-19 spread and lethality, and with a less extent also PM₁₀, although the potential effect of airborne virus exposure it has not been still demonstrated.

Linkages Between Air Pollution and the Health Burden From COVID-19: Methodological Challenges and Opportunities

The COVID-19 pandemic revealed and exacerbated existing social and economic health disparities and actionable epidemiological evidence is needed to identify potential vulnerability factors to help inform targeted responses. In this commentary, methodological challenges and opportunities regarding the links between air pollution and COVID-19 are discussed with a focus on: i) the role of differential exposure to air pollution across populations and explain spatio-temporal variability of the epidemic spread and resultant mortality; ii) the indirect impacts of interventions treated as natural experiments to control COVID-19 person-to-person spread on air pollution and population health. I first discuss the potential mechanisms between exposure to air pollution and COVID-19 and the opportunity to clearly formulate causal questions of interest through the target trial framework. Then, I discuss challenges regarding the use of quasi-experimental designs that capitalize on the differential timing of COVID-19 policies including the selection of control groups and potential violations of the common shock assumption. Finally, I discuss environmental justice implications of this many-headed beast of a crisis.

Airborne particulate matter, population mobility and COVID-19: a multi-city study in China

BACKGROUND

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease, which has caused numerous deaths and health problems worldwide. This study aims to examine the effects of airborne particulate matter (PM) pollution and population mobility on COVID-19 across China.

METHODS

We obtained daily confirmed cases of COVID-19, air particulate matter (PM_2.5, PM₁₀), weather parameters such as ambient temperature (AT) and absolute humidity (AH), and population mobility scale index (MSI) in 63 cities of China on a daily basis (excluding Wuhan) from January 01 to March 02, 2020. Then, the Generalized additive models (GAM) with a quasi-Poisson distribution were fitted to estimate the effects of PM₁₀, PM_2.5 and MSI on daily confirmed COVID-19 cases.

RESULTS

We found each 1 unit increase in daily MSI was significantly positively associated with daily confirmed cases of COVID-19 in all lag days and the strongest estimated RR (1.21, 95% CIs:1.14 ~ 1.28) was observed at lag 014. In PM analysis, we found each 10 μg/m³ increase in the concentration of PM₁₀ and PM_2.5 was positively associated with the confirmed cases of COVID-19, and the estimated strongest RRs (both at lag 7) were 1.05 (95% CIs: 1.04, 1.07) and 1.06 (95% CIs: 1.04, 1.07), respectively. A similar trend was also found in all cumulative lag periods (from lag 01 to lag 014). The strongest effects for both PM₁₀ and PM_2.5 were at lag 014, and the RRs of each 10 μg/m³ increase were 1.18 (95% CIs:1.14, 1.22) and 1.23 (95% CIs:1.18, 1.29), respectively.

CONCLUSIONS

Population mobility and airborne particulate matter may be associated with an increased risk of COVID-19 transmission.

Understanding the knowledge gaps between air pollution controls and health impacts including pathogen epidemic

Sustainable development calls for a blue sky with quality air. Encouragingly, the current mass reduction-oriented pollution control is making substantial achievements, as the data from Chinese Environmental Monitoring Stations show a significant drop in the annual average concentrations of particulate matters (i.e., PM₁₀ and PM_2.5) and SO₂. But many challenges and knowledge gaps are still confronted nowadays. On one hand, long-term health impacts of fine air particles have to be closely probed through both epidemiological and laboratory studies, and the toxic effects owing to the interactions between particles and associated chemical pollutants should be differentially teased out. On the other hand, due to sole mass control, there are significant changes of overall pollutant fingerprint, such as the increase of ground-level ozone concentration, which should be taken into account for altered health effects relative to the past. Moreover, the interplays with air pollutants and air-borne pathogens should be scrutinized in more details. In other words, it is worth investigating likely spread of pathogens (even for SARS-CoV-2) with aid of aerosols. Here, we recapitulate the current knowledge gaps between air pollution controls and health impacts including pathogen epidemic, and we also propose future research directions to support policy making in balance mass control and health impacts.

Possible environmental effects on the spread of COVID-19 in China

At the end of 2019, a novel coronavirus, designated as SARS-CoV-2, emerged in Wuhan, China and was identified as the causal pathogen of COVID-19. The epidemic scale of COVID-19 has increased dramatically, with confirmed cases increasing across China and globally. Understanding the potential affecting factors involved in COVID-19 transmission will be of great significance in containing the spread of the epidemic. Environmental and meteorological factors might impact the occurrence of COVID-19, as these have been linked to various diseases, including severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), whose causative pathogens belong to the same virus family as SARS-CoV-2. We collected daily data of COVID-19 confirmed cases, air quality and meteorological variables of 33 locations in China for the outbreak period of 29 January 2020 to 15 February 2020. The association between air quality index (AQI) and confirmed cases was estimated through a Poisson regression model, and the effects of temperature and humidity on the AQI-confirmed cases association were analyzed. The results show that the effect of AQI on confirmed cases associated with an increase in each unit of AQI was statistically significant in several cities. The lag effect of AQI on the confirmed cases was statistically significant on lag day 1 (relative risk (RR) = 1.0009, 95% confidence interval (CI): 1.0004, 1.0013), day 2 (RR = 1.0007, 95% CI: 1.0003, 1.0012) and day 3 (RR = 1.0008, 95% CI: 1.0003, 1.0012). The AQI effect on the confirmed cases might be stronger in the temperature range of 10 °C ≤ T < 20 °C than in other temperature ranges, while the RR of COVID-19 transmission associated with AQI was higher in the relative humidity (RH) range of 10% ≤ RH < 20%. Results may suggest an enhanced impact of AQI on the COVID-19 spread under low RH.

PM2.5 compromises antiviral immunity in influenza infection by inhibiting activation of NLRP3 inflammasome and expression of interferon-β

PM2.5, a major component of air pollutants, has caused severe health problems. It has been reported that PM2.5 index is closely associated with severity of influenza A virus (IAV) infection. However, the underlying mechanisms have not been addressed. NLRP3 inflammasome and type I interferon signaling regulate host defense against influenza infection. The present study investigated the potential effects of air pollutants on host defense against influenza infection in vitro and in vivo. In this study, different concentrations of PM2.5 were pre-exposed to macrophages and mice before IAV infection to assess the negative effects of air pollutants in virus infection. We found that exposure to PM2.5 deteriorated influenza virus infection via compromising innate immune responses manifested by a decrease IL-1β and IFN-β production in vitro. Meanwhile, mice exposed with PM2.5 were susceptible to PR8 virus infection due to down-regulation of IL-1β and IFN-β. Mechanistically, PM 2.5 exposure suppressed the NLRP3 inflammasome activation and the AHR-TIPARP signaling pathway, by which compromised the anti-influenza immunity. Thus, our study revealed that PM2.5 could alter macrophage inflammatory responses by suppressing LPS-induced activation of NLRP3 inflammasome and expression of IFN-β during influenza infection. These findings provided us new insights in understanding that PM2.5 combining with influenza infection could enhance the severity of pneumonia.

Particulate Matter and COVID-19 Disease Diffusion in Emilia-Romagna (Italy). Already a Cold Case?

As we prepare to emerge from an extensive and unprecedented lockdown period, due to the COVID-19 virus infection that hit the Northern regions of Italy with the Europe’s highest death toll, it becomes clear that what has gone wrong rests upon a combination of demographic, healthcare, political, business, organizational, and climatic factors that are out of our scientific scope. Nonetheless, looking at this problem from a patient’s perspective, it is indisputable that risk factors, considered as associated with the development of the virus disease, include older age, history of smoking, hypertension and heart disease. While several studies have already shown that many of these diseases can also be favored by a protracted exposure to air pollution, there has been recently an insurgence of negative commentary against authors who have correlated the fatal consequences of COVID-19 (also) to the exposition of specific air pollutants. Well aware that understanding the real connection between the spread of this fatal virus and air pollutants would require many other investigations at a level appropriate to the scale of this phenomenon (e.g., biological, chemical, and physical), we propose the results of a study, where a series of the measures of the daily values of PM2.5, PM10, and NO2 were considered over time, while the Granger causality statistical hypothesis test was used for determining the presence of a possible correlation with the series of the new daily COVID19 infections, in the period February–April 2020, in Emilia-Romagna. Results taken both before and after the governmental lockdown decisions show a clear correlation, although strictly seen from a Granger causality perspective. Moving beyond the relevance of our results towards the real extent of such a correlation, our scientific efforts aim at reinvigorating the debate on a relevant case, that should not remain unsolved or no longer investigated.

Effects of short-term fine particulate matter exposure on acute respiratory infection in children

BACKGROUND

Previous studies on the association between fine particulate matter (PM_2.5) exposure and acute respiratory infection in children are scarce and present inconsistent results. We estimated the association between short-term PM_2.5 exposure and acute respiratory infection among children aged 0-4 years using a difference-in-differences approach.

METHODS

We used data on the daily PM_2.5 concentrations, hospital admissions for acute respiratory infection, and meteorological factors of the 15 regions in the Republic of Korea (2013-2015). To estimate the cumulative effects, we used a difference-in-differences approach generalized to multiple spatial units (regions) and time periods (day) with distributed lag non-linear models.

RESULTS

With PM_2.5 levels of 20.0 μg/m³ as a reference, PM_2.5 levels of 30.0 μg/m³ were positively associated with the risk of acute upper respiratory infection (relative risk (RR) = 1.048, 95% confidence interval (CI): 1.028, 1.069) and bronchitis or bronchiolitis (RR = 1.060, 95% CI: 1.038, 1.082) but not with the risk of acute lower respiratory infection and pneumonia. PM_2.5 levels of 40.0 μg/m³ were also positively associated with the risk of acute upper respiratory infection (RR = 1.083, 95% CI: 1.046, 1.122) and bronchitis or bronchiolitis (RR = 1.094, 95% CI: 1.054, 1.136).

CONCLUSIONS

We found the associations of short-term PM_2.5 exposure with acute upper respiratory infection and bronchitis or bronchiolitis among children aged 0-4 years. As causal inference methods can provide more convincing evidence of the effects of PM_2.5 levels on respiratory infections, public health policies and guidelines regarding PM_2.5 need to be strengthened accordingly.

The delayed effect of wildfire season particulate matter on subsequent influenza season in a mountain west region of the USA

Particularly in rural settings, there has been little research regarding the health impacts of fine particulate matter (PM2.5) during the wildfire season smoke exposure period on respiratory diseases, such as influenza, and their associated outbreaks months later. We examined the delayed effects of PM2.5 concentrations for the short-lag (1-4 weeks prior) and the long-lag (during the prior wildfire season months) on the following winter influenza season in Montana, a mountainous state in the western United States. We created gridded maps of surface PM2.5 for the state of Montana from 2009 to 2018 using spatial regression models fit with station observations and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness data. We used a seasonal quasi-Poisson model with generalized estimating equations to estimate weekly, county-specific, influenza counts for Montana, associated with delayed PM2.5 concentration periods (short-lag and long-lag effects), adjusted for temperature and seasonal trend. We did not detect an acute, short-lag PM2.5 effect nor short-lag temperature effect on influenza in Montana. Higher daily average PM2.5 concentrations during the wildfire season was positively associated with increased influenza in the following winter influenza season (expected 16% or 22% increase in influenza rate per 1 μg/m3 increase in average daily summer PM2.5 based on two analyses, p = 0.04 or 0.008). This is one of the first observations of a relationship between PM2.5 during wildfire season and influenza months later.

Effect of ambient air pollutants and meteorological variables on COVID-19 incidence

Objective:

To determine whether ambient air pollutants and meteorological variables are associated with daily COVID-19 incidence.

Design:

A retrospective cohort from January 25 to February 29, 2020.

Setting:

Cities of Wuhan, Xiaogan, and Huanggang, China.

Patients:

The COVID-19 cases detected each day.

Methods:

We collected daily data of COVID-19 incidence, 8 ambient air pollutants (particulate matter of ≤2.5 µm [PM_2.5], particulate matter ≤10 µm [PM₁₀], sulfur dioxide [SO₂], carbon monoxide [CO], nitrogen dioxide [NO₂], and maximum 8-h moving average concentrations for ozone [O₃-8h]) and 3 meteorological variables (temperature, relative humidity, and wind) in China’s 3 worst COVID-19–stricken cities during the study period. The multivariate Poisson regression was performed to understand their correlation.

Results:

Daily COVID-19 incidence was positively associated with PM_2.5 and humidity in all cities. Specifically, the relative risk (RR) of PM_2.5 for daily COVID-19 incidences were 1.036 (95% confidence interval [CI], 1.032–1.039) in Wuhan, 1.059 (95% CI, 1.046–1.072) in Xiaogan, and 1.144 (95% CI, 1.12–1.169) in Huanggang. The RR of humidity for daily COVID-19 incidence was consistently lower than that of PM_2.5, and this difference ranged from 0.027 to 0.111. Moreover, PM₁₀ and temperature also exhibited a notable correlation with daily COVID-19 incidence, but in a negative pattern The RR of PM₁₀ for daily COVID-19 incidence ranged from 0.915 (95% CI, 0.896–0.934) to 0.961 (95% CI, 0.95–0.972, while that of temperature ranged from 0.738 (95% CI, 0.717–0.759) to 0.969 (95% CI, 0.966–0.973).

Conclusions:

Our data show that PM_2.5 and humidity are substantially associated with an increased risk of COVID-19 and that PM₁₀ and temperature are substantially associated with a decreased risk of COVID-19.

Environmental complex exposure and the risk of influenza-like illness among housewives: A case study in Shanxi Province, China

The association between environmental pollution and risk of influenza-like illness (ILI) among general population has been reported. However, the relationships between the individual pollutants and ILI risk are still under discussion. Our study aimed to explore the associations of the typical environmental polycyclic aromatic hydrocarbons (PAHs) and metal(loid)s with ILI risk among women population. We carried out a cross-sectional study and included a total of 396 housewives in Shanxi Province, China. The information on their general characteristics and ILI frequency was collected by questionnaire. We collected their hair samples and analyzed the concentrations of PAHs and various metal(loid)s. The results indicated that only acenaphthylene concentration of the nine detected PAH congeners in the hair was significantly associated with ILI risk with adjusted odds ratio (AOR) and 95% confidence interval (95% CI) of 0.58 (0.38 - 0.91). Among the concerned 4 toxic metal(loid)s and 15 rare earth elements, only the hair concentration of arsenic had a positive dose-response relationship with ILI risk. In addition, we found that there were negative dose-response associations of the three essential trace elements (i.e. chromium, cobalt, and nickel), and four essential alkaline earth elements (i.e. magnesium, calcium, strontium, barium) with ILI risk. It was concluded that the environmental exposure to certain compounds of housewives may contribute to their ILI development.

Joint Governance Regions and Major Prevention Periods of PM2.5 Pollution in China Based on Wavelet Analysis and Concentration-Weighted Trajectory

China has made some progress in controlling PM2.5 (particulate matter with an aerodynamic diameter of ≤2.5 μm) pollution, but there are still some key areas that need further strengthening. Considering that excessive prevention and control efforts affect economic development, this paper combined an empirical orthogonal function, a continuous wavelet transform, and a concentration-weighted trajectory method to study joint regional governance during key pollution periods to provide suggestions for the efficient control of PM2.5. The results from our panel of data of PM2.5 in China from 2016 to 2018 could be decomposed into two modes. In the first mode, the pollution center was in central Shaanxi Province, and the main eruption period was from November to January of the following year. As the center of this region, Xi’an should cooperate with the four cities in eastern Sichuan (Nanchong, Guangan, Bazhong, and Dazhou) to control PM2.5, since the eruption occurred in this area. Moreover, governance should last for at least two cycles, where one cycle is at least 23 days. The pollution center of the second mode was in the western part of Xinjiang. Therefore, after the prevention and control efforts during the first mode are completed, the regional city of Kashgar should continue to build a joint governance zone for PM2.5 along the Tianshan mountains in the east, focusing on prevention and control over two cycles (where one cycle is 28 days).