Diesel exhaust enhances influenza virus infections in respiratory epithelial cells

Short-term effects of PM2.5 components on the respiratory infectious disease: a global perspective

Although previous research has reached agreement on the significant impact of particulate matter (PM2.5) on respiratory infectious diseases, PM2.5 acts as an aggregation of miscellaneous pollutants and the individual effect of each component has not been examined. Here, we investigate the effects of PM2.5 components, including black carbon (BC), organic carbon (OC), sulfate ion (SO4), dust, and sea salt (SS), on the morbidity and mortality of the recent respiratory disease, i.e. COVID-19. The daily data of 236 countries and provinces/states (e.g., in the United States and China) worldwide during 2020-2022 are utilized. To derive the pollutant-specific causal effects, optimal instrumental variables for each pollutant are selected from a large set of atmospheric variables. We find that one µg/m3 increase in OC increases the number of cases and death by about 3% to 6% from the mean worldwide during a lag of one day up to three days. Our findings remain consistent and robust when we change control variables such as the flight index and weather proxies, and also when applying a sine transformation to the positivity and death rate. When analyzing health effects among different areas, we find stronger impact in China, for its higher local OC concentration, as opposed to the impact in the United States. Health benefits from PM2.5 pollution reduction are comparatively high for developed regions, yet decreases in cases and deaths number are rather overt in less developing regions. Our research provides inspiration and reference for dealing with other respiratory diseases in the post-pandemic era.

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.

Modification effects of long-term air pollution levels on the relationship between short-term exposure to meteorological factors and hand, foot, and mouth disease: A distributed lag non-linear model-based study in Shandong Province, China

The occurrence of hand, foot, and mouth disease (HFMD) is closely related to meteorological factors. However, location-specific characteristics, such as persistent air pollution, may increase the complexity of the impact of meteorological factors on HFMD, and studies across different areas and populations are largely lacking. In this study, a two-stage multisite time-series analysis was conducted using data from 16 cities in Shandong Province from 2015 to 2019. In the first stage, we obtained the cumulative exposure-response curves of meteorological factors and the number of HFMD cases for each city. In the second stage, we merged the estimations from the first stage and included city-specific air pollution variables to identify significant effect modifiers and how they modified the short-term relationship between HFMD and meteorological factors. High concentrations of air pollutants may reduce the risk effects of high average temperature on HFMD and lead to a distinct peak in the cumulative exposure-response curve, while lower concentrations may increase the risk effects of high relative humidity. Furthermore, the effects of average wind speed on HFMD were different at different levels of air pollution. The differences in modification effects between subgroups were mainly manifested in the diversity and quantity of significant modifiers. The modification effects of long-term air pollution levels on the relationship between sunshine hours and HFMD may vary significantly depending on geographical location. The people in age＜3 and male groups were more susceptible to long-term air pollution. These findings contribute to a deepening understanding of the relationship between meteorological factors and HFMD and provide evidence for relevant public health decision-making.

Alleviation of PM2.5-associated Risk of Daily Influenza Hospitalization by COVID-19 Lockdown Measures: A Time-series Study in Northeastern Thailand

OBJECTIVES

Abrupt changes in air pollution levels associated with the coronavirus disease 2019 (COVID-19) outbreak present a unique opportunity to evaluate the effects of air pollution on influenza risk, at a time when emission sources were less active and personal hygiene practices were more rigorous.

METHODS

This time-series study examined the relationship between influenza cases (n=22 874) and air pollutant concentrations from 2018 to 2021, comparing the timeframes before and during the COVID-19 pandemic in and around Thailand's Khon Kaen province. Poisson generalized additive modeling was employed to estimate the relative risk of hospitalization for influenza associated with air pollutant levels.

RESULTS

Before the COVID-19 outbreak, both the average daily number of influenza hospitalizations and particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) concentration exceeded those later observed during the pandemic (p<0.001). In single-pollutant models, a 10 μg/m3 increase in PM2.5 before COVID-19 was significantly associated with increased influenza risk upon exposure to cumulative-day lags, specifically lags 0-5 and 0-6 (p<0.01). After adjustment for co-pollutants, PM2.5 demonstrated the strongest effects at lags 0 and 4, with elevated risk found across all cumulative-day lags (0-1, 0-2, 0-3, 0-4, 0-5, and 0-6) and significantly greater risk in the winter and summer at lag 0-5 (p<0.01). However, the PM2.5 level was not significantly associated with influenza risk during the COVID-19 outbreak.

CONCLUSIONS

Lockdown measures implemented during the COVID-19 pandemic could mitigate the risk of PM2.5-induced influenza. Effective regulatory actions in the context of COVID-19 may decrease PM2.5 emissions and improve hygiene practices, thereby reducing influenza hospitalizations.

Impact of diesel exhaust particles on infections with Mycobacterium bovis BCG in in vitro human macrophages and an in vivo Galleria mellonella model

There are strong suggestions for a link between pulmonary tuberculosis (TB) and air quality. Diesel exhaust is one of the main contributors to pollution and it is reported to be able to modify susceptibility to lung infections. In this study we exposed THP-1 human macrophages and Mycobacterium bovis BCG to diesel exhaust particles (DEPs). High cytotoxicity and activation of apoptosis was found in THP-1 cells at 3 and 6 days, but no effect was found on the growth of M. bovis BCG. Infection of THP-1 cells exposed to a non-cytotoxic DEP concentration showed a limited capacity to engulf latex beads. However, M. bovis BCG infection of macrophages did not result in an increase in the bacterial burden, but it did result in an increase in the bacteria recovered from the extracellular media, suggesting a poor contention of M. bovis BCG. We also observed that DEP exposure limited the production of cytokines. Using the Galleria mellonella model of infection, we observed that larvae exposed to low levels of DEPs were less able to survive after infection with M. bovis BCG and had a higher internal bacterial load after 4 days of infection. Unraveling the links between air pollution and impairment of human antimycobacterial immunity is vital, because pollution is rapidly increasing in areas where TB incidence is extremely high.

Impact of short-term ambient air pollution exposure on the risk of severe COVID-19

Ecological studies suggested a link between air pollution and severe COVID-19 outcomes, while studies accounting for individual-level characteristics are limited. In the present study, we aimed to investigate the impact of short-term ambient air pollution exposure on disease severity among a cohort of 569 laboratory confirmed COVID-19 patients admitted to designated hospitals in Zhejiang province, China, from January 17 to March 3, 2020, and elucidate the possible biological processes involved using transcriptomics. Compared with mild cases, severe cases had higher proportion of medical conditions as well as unfavorable results in most of the laboratory tests, and manifested higher air pollution exposure levels. Higher exposure to air pollutants was associated with increased risk of severe COVID-19 with odds ratio (OR) of 1.89 (95% confidence interval (CI): 1.01, 3.53), 2.35 (95% CI: 1.20, 4.61), 2.87 (95% CI: 1.68, 4.91), and 2.01 (95% CI: 1.10, 3.69) for PM2.5, PM10, NO2 and CO, respectively. OR for NO2 remained significant in two-pollutant models after adjusting for other pollutants. Transcriptional analysis showed 884 differentially expressed genes which mainly were enriched in virus clearance related biological processes between patients with high and low NO2 exposure levels, indicating that compromised immune response might be a potential underlying mechanistic pathway. These findings highlight the impact of short-term air pollution exposure, particularly for NO2, on COVID-19 severity, and emphasize the significance in mitigating the COVID-19 burden of commitments to improve air quality.

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.

Lagging effects and prediction of pollutants and their interaction modifiers on influenza in northeastern China

BACKGROUND

Previous studies have typically explored the daily lagged relations between influenza and meteorology, but few have explored seasonally the monthly lagged relationship, interaction and multiple prediction between influenza and pollution. Our specific objectives are to evaluate the lagged and interaction effects of pollution factors and construct models for estimating influenza incidence in a hierarchical manner.

METHODS

Our researchers collect influenza case data from 2005 to 2018 with meteorological and contaminative factors in Northeast China. We develop a generalized additive model with up to 6 months of maximum lag to analyze the impact of pollution factors on influenza cases and their interaction effects. We employ LASSO regression to identify the most significant environmental factors and conduct multiple complex regression analysis. In addition, quantile regression is taken to model the relation between influenza morbidity and specific percentiles (or quantiles) of meteorological factors.

RESULTS

The influenza epidemic in Northeast China has shown an upward trend year by year. The excessive incidence of influenza in Northeast China may be attributed to the suspected primary air pollutant, NO2, which has been observed to have overall low levels during January, March, and June. The Age 15-24 group shows an increase in the relative risk of influenza with an increase in PM2.5 concentration, with a lag of 0-6 months (ERR 1.08, 95% CI 0.10-2.07). In the quantitative analysis of the interaction model, PM10 at the level of 100-120 μg/m3, PM2.5 at the level of 60-80 μg/m3, and NO2 at the level of 60 μg/m3 or more have the greatest effect on the onset of influenza. The GPR model behaves better among prediction models.

CONCLUSIONS

Exposure to the air pollutant NO2 is associated with an increased risk of influenza with a cumulative lag effect. Prioritizing winter and spring pollution monitoring and influenza prediction modeling should be our focus.

High-throughput bioprinting of the nasal epithelium using patient-derived nasal epithelial cells

Progenitor human nasal epithelial cells (hNECs) are an essential cell source for the reconstruction of the respiratory pseudostratified columnar epithelium composed of multiple cell types in the context of infection studies and disease modeling. Hitherto, manual seeding has been the dominant method for creating nasal epithelial tissue models through biofabrication. However, this approach has limitations in terms of achieving the intricate three-dimensional (3D) structure of the natural nasal epithelium. 3D bioprinting has been utilized to reconstruct various epithelial tissue models, such as cutaneous, intestinal, alveolar, and bronchial epithelium, but there has been no attempt to use of 3D bioprinting technologies for reconstruction of the nasal epithelium. In this study, for the first time, we demonstrate the reconstruction of the nasal epithelium with the use of primary hNECs deposited on Transwell inserts via droplet-based bioprinting (DBB), which enabled high-throughput fabrication of the nasal epithelium in Transwell inserts of 24-well plates. DBB of progenitor hNECs ranging from one-tenth to one-half of the cell seeding density employed during the conventional cell seeding approach enabled a high degree of differentiation with the presence of cilia and tight-junctions over a 4 weeks air-liquid interface culture. Single cell RNA sequencing of these cultures identified five major epithelial cells populations, including basal, suprabasal, goblet, club, and ciliated cells. These cultures recapitulated the pseudostratified columnar epithelial architecture present in the native nasal epithelium and were permissive to respiratory virus infection. These results denote the potential of 3D bioprinting for high-throughput fabrication of nasal epithelial tissue models not only for infection studies but also for other purposes, such as disease modeling, immunological studies, and drug screening.

Protective effects of inhaled antioxidants against air pollution-induced pathological responses

As the public health burden of air pollution continues to increase, new strategies to mitigate harmful health effects are needed. Dietary antioxidants have previously been explored to protect against air pollution-induced lung injury producing inconclusive results. Inhaled (pulmonary or nasal) administration of antioxidants presents a more promising approach as it could directly increase antioxidant levels in the airway surface liquid (ASL), providing protection against oxidative damage from air pollution. Several antioxidants have been shown to exhibit antioxidant, anti-inflammatory, and anti-microbial properties in in vitro and in vivo models of air pollution exposure; however, little work has been done to translate these basic research findings into practice. This narrative review summarizes these findings and data from human studies using inhaled antioxidants in response to air pollution, which have produced positive results, indicating further investigation is warranted. In addition to human studies, cell and murine studies should be conducted using more relevant models of exposure such as air-liquid interface (ALI) cultures of primary cells and non-aqueous apical delivery of antioxidants and pollutants. Inhalation of antioxidants shows promise as a protective intervention to prevent air pollution-induced lung injury and exacerbation of existing lung disease.

The Notorious Triumvirate in Pediatric Health: Air Pollution, Respiratory Allergy, and Infection

A plausible association is suspected among air pollution, respiratory allergic disorder, and infection. These three factors could cause uncontrollable chronic inflammation in the airway tract, creating a negative impact on the physiology of the respiratory system. This review aims to understand the underlying pathophysiology in explaining the association among air pollution, respiratory allergy, and infection in the pediatric population and to capture the public's attention regarding the interaction among these three factors, as they synergistically reduce the health status of children living in polluted countries globally, including Indonesia.

Potential mechanisms mediating PM2.5-induced alterations of H3N2 influenza virus infection and cytokine production in human bronchial epithelial cells

Exposure to particulate matter (PM) has been associated with increased hospital admissions for influenza. Airway epithelial cells are a primary target for inhaled environmental insults including fine PM (PM_2.5) and influenza viruses. The potentiation of PM_2.5 exposure on the effects of influenza virus on airway epithelial cells has not been adequately elucidated. In this study, the effects of PM_2.5 exposure on influenza virus (H3N2) infection and downstream modulation of inflammation and antiviral immune response were investigated using a human bronchial epithelial cell line, BEAS-2B. The results showed that PM_2.5 exposure alone increased the production of pro-inflammatory cytokines including interleukin-6 (IL-6) and IL-8 but decreased the production of the antiviral cytokine interferon-β (IFN-β) in BEAS-2B cells while H3N2 exposure alone increased the production of IL-6, IL-8, and IFN-β. Importantly, prior exposure to PM_2.5 enhanced subsequent H3N2 infectivity, expression of viral hemagglutinin protein, as well as upregulation of IL-6 and IL-8, but reduced H3N2-induced IFN-β production. Pre-treatment with a pharmacological inhibitor of nuclear factor-κB (NF-κB) suppressed pro-inflammatory cytokine production induced by PM_2.5, H3N2, as well as PM_2.5-primed H3N2 infection. Moreover, antibody-mediated neutralization of Toll-like receptor 4 (TLR4) blocked cytokine production triggered by PM_2.5 or PM_2.5-primed H3N2 infection, but not H3N2 alone. Taken together, exposure to PM_2.5 alters H3N2-induced cytokine production and markers of replication in BEAS-2B cells, which in turn are regulated by NF-κB and TLR4.

High-Throughput Bioprinting of the Nasal Epithelium using Patient-derived Nasal Epithelial Cells

Human nasal epithelial cells (hNECs) are an essential cell source for the reconstruction of the respiratory pseudostratified columnar epithelium composed of multiple cell types in the context of infection studies and disease modeling. Hitherto, manual seeding has been the dominant method for creating nasal epithelial tissue models. However, the manual approach is slow, low-throughput and has limitations in terms of achieving the intricate 3D structure of the natural nasal epithelium in a uniform manner. 3D Bioprinting has been utilized to reconstruct various epithelial tissue models, such as cutaneous, intestinal, alveolar, and bronchial epithelium, but there has been no attempt to use of 3D bioprinting technologies for reconstruction of the nasal epithelium. In this study, for the first time, we demonstrate the reconstruction of the nasal epithelium with the use of primary hNECs deposited on Transwell inserts via droplet-based bioprinting (DBB), which enabled high-throughput fabrication of the nasal epithelium in Transwell inserts of 24-well plates. DBB of nasal progenitor cells ranging from one-tenth to one-half of the cell seeding density employed during the conventional cell seeding approach enabled a high degree of differentiation with the presence of cilia and tight-junctions over a 4-week air-liquid interface culture. Single cell RNA sequencing of these cultures identified five major epithelial cells populations, including basal, suprabasal, goblet, club, and ciliated cells. These cultures recapitulated the pseudostratified columnar epithelial architecture present in the native nasal epithelium and were permissive to respiratory virus infection. These results denote the potential of 3D bioprinting for high-throughput fabrication of nasal epithelial tissue models not only for infection studies but also for other purposes such as disease modeling, immunological studies, and drug screening.

Stronger susceptibilities to air pollutants of influenza A than B were identified in subtropical Shenzhen, China

Air pollution was indicated to be a key factor contributing to the aggressive spread of influenza viruses, whereas uncertainty still exists regarding to whether distinctions exist between influenza subtypes. Our study quantified the impact of five air pollutants on influenza subtype outbreaks in Shenzhen, China, a densely populated and highly urbanized megacity. Daily influenza outbreak data of laboratory-confirmed positive cases were obtained from the Shenzhen CDC, from May 1, 2013 to Dec 31, 2015. Concentrations of nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matters ≤2.5 μm (PM_2.5), particulate matters ≤10 μm (PM₁₀), and ozone (O₃), were retrieved from the 18 national monitoring stations. The generalized additive model (GAM) and distributed lag non-linear model (DLNM) were used to calculate the concentration-response relationships between environmental inducers and outbreak epidemics, respectively for influenza A (Flu-A) and B (Flu-B). There were 1687 positive specimens were confirmed during the study period. The cold season was restricted from Nov. 4th to Apr. 20th, covering all seasons other than the long-lasting summer. Relatively heavy fine particle matter (PM_2.5) and NO₂ pollution was observed in cold months, with mean concentrations of 46.06 μg/m³ and 40.03 μg/m³, respectively. Time-series analysis indicated that high concentrations of NO₂, PM_2.5, PM₁₀, and O₃ were associated with more influenza outbreaks at short lag periods (0-5 d). Although more Flu-B (679 cases) epidemics occurred than Flu-A (382 cases) in the cold season, Flu-A generally showed higher susceptibility to air pollutants. A 10 μg/m³ increment in concentrations of PM_2.5, PM₁₀, and O₃ at lag 04, was associated with a 2.103 (95%CI: 1.528-2.893), 1.618 (95%CI: 1.311-1.996), and 1.569 (95%CI: 1.214-2.028) of the relative risk (RR) of Flu-A, respectively. A 5 μg/m³ increase in NO₂ was associated with higher risk of Flu-A at lag 03 (RR = 1.646, 95%CI: 1.295-2.092) and of Flu-B at lag 04 (RR = 1.319, 95%CI: 1.095-1.588). Nevertheless, barely significant effect of particulate matters (PM_2.5, PM₁₀) on Flu-B and SO₂ on both subtypes was detected. Further, the effect estimates of NO₂ increased for both subtypes when coexisting with other pollutants. This study provides evidence that declining concentrations of main pollutants including NO₂, O₃, and particulate matters, could substantially decrease influenza risk in subtropical Shenzhen, especially for influenza A.

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

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

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.

Community-level ambient fine particulate matter and seasonal influenza among children in Guangzhou, China: A Bayesian spatiotemporal analysis

BACKGROUND

Influenza is a major preventable infectious respiratory disease. However, there is little detailed long-term evidence of its associations with PM_2.5 among children. We examined the community-level associations between exposure to ambient PM_2.5 and incident influenza in Guangzhou, China.

METHODS

We used data from the city-wide influenza surveillance system collected by Guangzhou Centre for Disease Control and Prevention (GZCDC) over the period 2013 and 2019. Incident influenza was defined as daily new influenza (both clinically diagnosed and laboratory confirmed) cases as per standard diagnostic criteria. A 200-meter city-wide grid of daily ambient PM_2.5 exposure was generated using a random forest model. We developed spatiotemporal Bayesian hierarchical models to examine the community-level associations between PM_2.5 and the influenza adjusting for meteorological and socioeconomic variables and accounting for spatial autocorrelation. We also calculated community-wide influenza cases attributable to PM_2.5 levels exceeding the China Grade 1 and World Health Organization (WHO) regulatory thresholds.

RESULTS

Our study comprised N = 191,846 children from Guangzhou aged ≤19 years and diagnosed with influenza between January 1, 2013 and December 31, 2019. Each 10 μg/m³ increment in community-level PM_2.5 measured on the day of case confirmation (lag 0) and over a 6-day moving average (lag 0-5 days) was associated with higher risks of influenza (RR = 1.05, 95% CI: 1.05-1.06 for lag 0 and RR = 1.15, 95% CI: 1.14-1.16 for lag 05). We estimated that 8.10% (95%CI: 7.23%-8.57%) and 20.11% (95%CI: 17.64%-21.48%) influenza cases respectively were attributable to daily PM_2.5 exposure exceeding the China Grade I (35 μg/m³) and the WHO limits (25 μg/m³). The risks associated with PM_2.5 exposures were more pronounced among children of the age-group 10-14 compared to other age groups.

CONCLUSIONS

More targeted non-pharmaceutical interventions aimed at reducing PM_2.5 exposures at home, school and during commutes among children may constitute additional influenza prevention and control polices.

The Impact of Air Pollution on Gut Microbiota and Children’s Health: An Expert Consensus

Air pollution is an unseen threat to children’s health because it may increase the risk of respiratory infection, atopy, and asthma, and also alter gut microbiota compositions. The impact of air pollution on children’s health has not been firmly established. A literature review followed by a series of discussions among experts were performed to develop a theoretical framework on how air pollution could affect various bodily organs and functions in children. We invited experts from different backgrounds, such as paediatricians, nutritionists, environmental health experts, and occupational health experts, to provide their views on this matter. This report summarizes the discussion of multidisciplinary experts on the impact of air pollution on children’s health. The report begins with a review of air pollution’s impact on allergy and immunology, neurodevelopment, and cardiometabolic risks, and ends with the conceptualization of a theoretical framework. While the allergic and immunological pathway is one of the most significant pathways for air pollution affecting children’s health in which microbiotas also play a role, several pathways have been proposed regarding the ability to affect neurodevelopment and cardiometabolic risk. Further research is required to confirm the link between air pollution and the gut microbiota pathway.

Woodsmoke particle exposure prior to SARS-CoV-2 infection alters antiviral response gene expression in human nasal epithelial cells in a sex-dependent manner

Inhalational exposure to particulate matter (PM) derived from natural or anthropogenic sources alters gene expression in the airways and increases susceptibility to respiratory viral infection. Woodsmoke-derived ambient PM from wildfire events during 2020 was associated with higher COVID-19 case rates in the western United States. We hypothesized that exposure to suspensions of woodsmoke particles (WSPs) or diesel exhaust particles (DEPs) prior to SARS-CoV-2 infection would alter host immune gene expression at the transcript level. Primary human nasal epithelial cells (hNECs) from both sexes were exposed to WSPs or DEPs (22 μg/cm2) for 2 h, followed by infection with SARS-CoV-2 at a multiplicity of infection of 0.5. Forty-six genes related to SARS-CoV-2 entry and host response were assessed. Particle exposure alone minimally affected gene expression, whereas SARS-CoV-2 infection alone induced a robust transcriptional response in hNECs, upregulating type I and III interferons, interferon-stimulated genes, and chemokines by 72 h postinfection (p.i.). This upregulation was higher overall in cells from male donors. However, exposure to WSPs prior to infection dampened expression of antiviral, interferon, and chemokine mRNAs. Sex stratification of these results revealed that WSP exposure downregulated gene expression in cells from females more so than males. We next hypothesized that hNECs exposed to particles would have increased apical viral loads compared with unexposed cells. Although apical viral load was correlated to expression of host response genes, viral titer did not differ between groups. These data indicate that WSPs alter epithelial immune responses in a sex-dependent manner, potentially suppressing host defense to SARS-CoV-2 infection.

Association between ozone exposure and prevalence of mumps: a time-series study in a Megacity of Southwest China

In the present study, we aim to evaluate the delayed and cumulative effect of ozone (O₃) exposure on mumps in a megacity with high population density and high humidity. We took Chongqing, a megacity in Southwest China, as the research area and 2013-2017 as the research period. A total of 49,258 confirmed mumps cases were collected from 122 hospitals of Chongqing. We employed the distributed lag nonlinear models with quasi-Poisson link to investigate the relationship between prevalence of mumps and O₃ exposure after adjusting for the effects of meteorological conditions. The results show that the effect of O₃ exposure on mumps was mainly manifested in the lag of 0-7 days. The single-day ;lag effect was the most obvious on the 4th day, with the relative risk (RR) of mumps occurs of 1.006 (95% CI: 1.003-1.007) per 10 μg/m³ in the O₃ exposure. The cumulative RR within 7 days was 1.025 (95% CI: 1.013-1.038). Our results suggest that O₃ exposure can increase the risk of mumps infection, which fills the gap of relevant research in mountainous areas with high population density and high humidity.

Impact of inhaled pollutants on response to viral infection in controlled exposures

Air pollutants are a major source of increased risk of disease, hospitalization, morbidity, and mortality worldwide. The respiratory tract is a primary target of potential concurrent exposure to both inhaled pollutants and pathogens, including viruses. Although there are various associative studies linking adverse outcomes to co- or subsequent exposures to inhaled pollutants and viruses, knowledge about causal linkages and mechanisms by which pollutant exposure may alter human respiratory responses to viral infection is more limited. In this article, we review what is known about the impact of pollutant exposure on antiviral host defense responses and describe potential mechanisms by which pollutants can alter the viral infection cycle. This review focuses on evidence from human observational and controlled exposure, ex vivo, and in vitro studies. Overall, there are a myriad of points throughout the viral infection cycle that inhaled pollutants can alter to modulate appropriate host defense responses. These alterations may contribute to observed increases in rates of viral infection and associated morbidity and mortality in areas of the world with high ambient pollution levels or in people using tobacco products. Although the understanding of mechanisms of interaction is advancing through controlled in vivo and in vitro exposure models, more studies are needed because emerging infectious pathogens, such as severe acute respiratory syndrome coronavirus 2, present a significant threat to public health.

The effect of air pollution on the transcriptomics of the immune response to respiratory infection

Combustion related particulate matter air pollution (PM) is associated with an increased risk of respiratory infections in adults. The exact mechanism underlying this association has not been determined. We hypothesized that increased concentrations of combustion related PM would result in dysregulation of the innate immune system. This epidemiological study includes 111 adult patients hospitalized with respiratory infections who underwent transcriptional analysis of their peripheral blood. We examined the association between gene expression at the time of hospitalization and ambient measurements of particulate air pollutants in the 28 days prior to hospitalization. For each pollutant and time lag, gene-specific linear models adjusting for infection type were fit using LIMMA (Linear Models For Microarray Data), and pathway/gene set analyses were performed using the CAMERA (Correlation Adjusted Mean Rank) program. Comparing patients with viral and/or bacterial infection, the expression patterns associated with air pollution exposure differed. Adjusting for the type of infection, increased concentrations of Delta-C (a marker of biomass smoke) and other PM were associated with upregulation of iron homeostasis and protein folding. Increased concentrations of black carbon (BC) were associated with upregulation of viral related gene pathways and downregulation of pathways related to antigen presentation. The pollutant/pathway associations differed by lag time and by type of infection. This study suggests that the effect of air pollution on the pathogenesis of respiratory infection may be pollutant, timing, and infection specific.

Diesel exposure increases susceptibility of primary human nasal epithelial cells to rhinovirus infection

Nasal epithelial cells (NECs) are among the first cells to be exposed to air pollutants and respiratory viruses. Although it is known that air pollution exposure and rhinovirus infections increase the risk for asthma development independently, it is unclear how these risk factors interact on a cellular level. Therefore, we aimed to investigate how exposure to diesel particulate matter (DPM) modifies the response of primary NECs to rhinovirus (RV) infection in vitro. Exposure of re-differentiated, primary NECs (49 healthy children [0-7 years], 12 adults) to DPM modified the mRNA expression of viral cell-surface receptors, pattern recognition receptors, and pro-inflammatory response (also protein levels). After exposure to DPM, we additionally infected the NECs with RV-1b and RV-16. Viral loads (assessed by titration assays) were significantly higher in DPM-exposed compared with non-exposed NECs. Exposure to DPM prior to RV infection resulted in a significant upregulation of pro-inflammatory cytokines (mRNA and protein level) and β-defensins mRNA, and significant downregulation of pattern recognition receptors mRNA and CXCL10 (mRNA and protein levels). There was no difference between all outcomes of NECs from children and adults. We can conclude that exposure to DPM prior to RV infection increases viral loads by downregulation of viral defense receptors and upregulation of pro-inflammatory cytokines. Our findings indicate a strong interaction between air pollution and the antiviral response to RV infection in NECs. We provide mechanistic evidence that exposure to air pollution increases susceptibility to RV infection.

Woodsmoke particulates alter expression of antiviral host response genes in human nasal epithelial cells infected with SARS-CoV-2 in a sex-dependent manner

We have previously shown that exposure to particulate air pollution, both from natural and anthropogenic sources, alters gene expression in the airways and increases susceptibility to respiratory viral infection. Additionally, we have shown that woodsmoke particulates (WSP) affect responses to influenza in a sex-dependent manner. In the present study, we used human nasal epithelial cells (hNECs) from both sexes to investigate how particulate exposure could modulate gene expression in the context of SARS-CoV-2 infection. We used diesel exhaust particulate (DEP) as well as WSP derived from eucalyptus or red oak wood. HNECs were exposed to particulates at a concentration of 22 μg/cm ² for 2 h then immediately infected with SARS-CoV-2 at a MOI (multiplicity of infection) of 0.5. Exposure to particulates had no significant effects on viral load recovered from infected cells. Without particulate exposure, hNECs from both sexes displayed a robust upregulation of antiviral host response genes, though the response was greater in males. However, WSP exposure before infection dampened expression of genes related to the antiviral host response by 72 h post infection. Specifically, red oak WSP downregulated IFIT1, IFITM3, IFNB1, MX1, CCL3, CCL5, CXCL11, CXCL10 , and DDX58 , among others. After sex stratification of these results, we found that exposure to WSP prior to SARS-CoV-2 infection downregulated anti-viral gene expression in hNECs from females more so than males. These data indicate that WSP, specifically from red oak, alter virus-induced gene expression in a sex-dependent manner and potentially suppress antiviral host defense responses following SARS-CoV-2 infection.

Allergic rhinitis aggravated by air pollutants in Latin America: A systematic review

The aim of this systematic review (SR) was to evaluate the most frequent pollutants and their effect on allergic rhinitis in Latin American countries. Observational studies up to December 2020 and comparing different indoor and outdoor pollutants that had allergic rhinitis (AR) as an outcome were included in the systematic review. Random-effect meta-analyses were conducted for the presence of allergic rhinitis. Estimates were presented as pooled odds ratios (ORs) and their respective 95% confidence intervals (CIs). Twenty-two publications comprised this review according to the inclusion and exclusion criteria and 12 had data that could be analyzed statistically. The most frequent pollutant was PM10, followed by NO2 /O3 and PM2.5 in studies conducted in Argentina, Brazil, Bolivia, Chile, Colombia, Costa Rica, and Peru. The OR of an exposed subject experiencing allergic rhinitis was 1.43 (95% CI 1.026; 1.980). The OR of children and adolescents experiencing of allergic rhinitis was 1.359 (95% CI 1.051; 1.759). Asymmetry and great variability in the effect estimated from the selected studies were observed. The publication bias was quantified by Kendall's correlation and Egger's test resulted in 0.152 (p-value = 0.493). Egger's test provided an intercept equal to 2.511 and a p-value = 0.398. The I2 statistic was 89.3% and reinforces the hypothesis of heterogeneity. This first systematic review conducted in Latin America confirmed the chance of a person exposed to pollutants and experiencing allergic rhinitis is 43% greater than that of a non-exposed person, reinforcing the importance of policies to reduce pollutant exposure and the use of protection systems for workforces exposed to occupational pollutants in work environments.

Residential Proximity to Biorefinery Sources of Air Pollution and Respiratory Diseases in New York State

Understanding potential health risks associated with biofuel production is critical to sustainably combating energy insecurity and climate change. However, the specific health impacts associated with biorefinery-related emissions are not yet well characterized. We evaluated the relationship between respiratory emergency department (ED) visits (2011-2015) and residential exposure to biorefineries by comparing 15 biorefinery sites to 15 control areas across New York (NY) State. We further examined these associations by biorefinery types (e.g., corn, wood, or soybean), seasons, and lower respiratory disease subtypes. We measured biorefinery exposure using residential proximity in a cross-sectional study and estimation of biorefinery emission via AERMOD-simulated modeling. After controlling for multiple confounders, we consistently found that respiratory ED visit rates among residents living within 10 km of biorefineries were significantly higher (rate ratios (RRs) range from 1.03 to 3.64) than those in control areas across our two types of exposure indices. This relationship held across biorefinery types (higher in corn and soybean biorefineries), seasons (higher in spring and winter), air pollutant types (highest for NO₂), and respiratory subtypes (highest for emphysema). Further research is needed to confirm our findings.

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.

Impact of biometeorological conditions and air pollution on influenza-like illnesses incidence in Warsaw

In order to assess the influence of atmospheric conditions and particulate matter (PM) on the seasonally varying incidence of influenza-like illnesses (ILI) in the capital of Poland-Warsaw, we analysed time series of ILI reported for the about 1.75 million residents in total and for different age groups in 288 approximately weekly periods, covering 6 years 2013-2018. Using Poisson regression, we predicted ILI by the Universal Thermal Climate Index (UTCI) as biometeorological indicator, and by PM2.5 and PM10, respectively, as air quality measures accounting for lagged effects spanning up to 3 weeks. Excess ILI incidence after adjusting for seasonal and annual trends was calculated by fitting generalized additive models. ILI morbidity increased with rising PM concentrations, for both PM2.5 and PM10, and with cooler atmospheric conditions as indicated by decreasing UTCI. While the PM effect focused on the actual reporting period, the atmospheric influence exhibited a more evenly distributed lagged effect pattern over the considered 3-week period. Though ILI incidence adjusted for population size significantly declined with age, age did not significantly modify the effect sizes of both PM and UTCI. These findings contribute to better understanding environmental conditionings of influenza seasonality in a temperate climate. This will be beneficial to forecasting future dynamics of ILI and to planning clinical and public health resources under climate change scenarios.

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.

Polluted Air Exposure Compromises Corneal Immunity and Exacerbates Inflammation in Acute Herpes Simplex Keratitis

Air pollution is a serious environmental issue worldwide in developing countries’ megacities, affecting the population’s health, including the ocular surface, by predisposing or exacerbating other ocular diseases. Herpes simplex keratitis (HSK) is caused by the herpes simplex virus type 1 (HSV-1). The primary or recurring infection in the ocular site causes progressive corneal scarring that may result in visual impairment. The present study was designed to study the immunopathological changes of acute HSK under urban polluted air, using the acute HSK model combined with an experimental urban polluted air exposure from Buenos Aires City. We evaluated the corneal clinical outcomes, viral DNA and pro-inflammatory cytokines by RT-PCR and ELISA assays, respectively. Then, we determined the innate and adaptive immune responses in both cornea and local lymph nodes after HSV-1 corneal by immunofluorescence staining and flow cytometry. Our results showed that mice exposed to polluted air develop a severe form of HSK with increased corneal opacity, neovascularization, HSV-1 DNA and production of TNF-α, IL-1β, IFN-γ, and CCL2. A high number of corneal resident immune cells, including activated dendritic cells, was observed in mice exposed to polluted air; with a further significant influx of bone marrow-derived cells including GR1+ cells (neutrophils and inflammatory monocytes), CD11c+ cells (dendritic cells), and CD3+ (T cells) during acute corneal HSK. Moreover, mice exposed to polluted air showed a predominant Th1 type T cell response over Tregs in local lymph nodes during acute HSK with decreased corneal Tregs. These findings provide strong evidence that urban polluted air might trigger a local imbalance of innate and adaptive immune responses that exacerbate HSK severity. Taking this study into account, urban air pollution should be considered a key factor in developing ocular inflammatory diseases.

Electronic-Cigarette Use Alters Nasal Mucosal Immune Response to Live-attenuated Influenza Virus. A Clinical Trial

Inhalation of tobacco smoke has been linked to increased risk of viral infection, such as influenza. Inhalation of electronic-cigarette (e-cigarette) aerosol has also recently been linked to immune suppression within the respiratory tract, specifically the nasal mucosa. We propose that changes in the nasal mucosal immune response modify antiviral host-defense responses in e-cigarette users. Nonsmokers, cigarette smokers, and e-cigarette users were inoculated with live-attenuated influenza virus (LAIV) to safely examine the innate immune response to influenza infection. Before and after LAIV inoculation, we collected nasal epithelial-lining fluid, nasal lavage fluid, nasal-scrape biopsy specimens, urine, and blood. Endpoints examined include cytokines and chemokines, influenza-specific IgA, immune-gene expression, and markers of viral load. Statistical analysis included primary comparisons of cigarette and e-cigarette groups with nonsmokers, as well as secondary analysis of demographic factors as potential modifiers. Markers of viral load did not differ among the three groups. Nasal-lavage-fluid anti-LAIV IgA levels increased in nonsmokers after LAIV inoculation but did not increase in e-cigarette users and cigarette smokers. LAIV-induced gene-expression changes in nasal biopsy specimens differed in cigarette smokers and e-cigarette users as compared with nonsmokers, with a greater number of genes changed in e-cigarette users, mostly resulting in decreased expression. The top downregulated genes in cigarette smokers were SMPD3, NOS2A, and KLRB1, and the top downregulated genes in e-cigarette users were MR1, NT5E, and HRAS. Similarly, LAIV-induced cytokine levels in nasal epithelial-lining fluid differed among the three groups, including decreased antiviral host-defense mediators (IFNγ, IL6, and IL12p40). We also detected that sex interacted with tobacco-product exposure to modify LAIV-induced immune-gene expression. Our results demonstrate that e-cigarette use altered nasal LAIV-induced immune responses, including gene expression, cytokine and chemokine release, and LAIV-specific IgA levels. Together, these data suggest that e-cigarette use induces changes in the nasal mucosa that are consistent with the potential for altered respiratory antiviral host-defense function.

Clinical trial registered with www.clinicaltrials.gov (NCT 02019745).

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.

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.

Inflammatory effects of particulate matter air pollution

Air pollution is an important cause of non-communicable diseases globally with particulate matter (PM) as one of the main air pollutants. PM is composed of microscopic particles that contain a mixture of chemicals and biological elements that can be harmful to human health. The aerodynamic diameter of PM facilitates their deposition when inhaled. For instance, coarse PM having a diameter of < 10 μm is deposited mainly in the large conducting airways, but PM of < 2.5 μm can cross the alveolar-capillary barrier, traveling to other organs within the body. Epidemiological studies have shown the association between PM exposure and risk of disease, namely those of the respiratory system such as lung cancer, asthma, and chronic obstructive pulmonary disease (COPD). However, cardiovascular and neurological diseases have also been reported, including hypertension, atherosclerosis, acute myocardial infarction, stroke, loss of cognitive function, anxiety, and Parkinson's and Alzheimer's diseases. Inflammation is a common hallmark in the pathogenesis of many of these diseases associated with exposure to a variety of air pollutants, including PM. This review focuses on the main effects of PM on human health, with an emphasis on the role of inflammation.

A review of current knowledge on Pollution, Cigarette Smoking and COVID-19 diffusion and their relationship with inflammation

Coronavirus disease (COVID-19) is an infectious disease caused by the newly discovered coronavirus, Sars-Cov-2. This infection can cause mild to very severe respiratory and systemic illness mainly related with a cytokine storm. The epidemiology of COVID-19 is under continuous evolution, and studies are ongoing aiming at identifying the possible factors facilitating the diffusion of this infection. (www.actabiomedica.it)

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.

COVID-19 prevalence and fatality rates in association with air pollution emission concentrations and emission sources

The novel coronavirus disease (COVID-19) is primarily respiratory in nature, and as such, there is interest in examining whether air pollution might contribute to disease susceptibility or outcome. We merged data on COVID-19 cumulative prevalence and fatality rates as of May 31, 2020 with 2014-2019 pollution data from the US Environmental Protection Agency Environmental Justice Screen (EJSCREEN), with control for state testing rates, population density, and population covariate data from the County Health Rankings. Pollution data included three types of air emission concentrations (particulate matter<2.5 μm (PM2.5), ozone and diesel particulate matter (DPM)), and four pollution source variables (proximity to traffic, National Priority List sites, Risk Management Plan (RMP) sites, and hazardous waste treatment, storage and disposal facilities (TSDFs)). Results of mixed model linear multiple regression analyses indicated that, controlling for covariates, COVID-19 prevalence and fatality rates were significantly associated with greater DPM. Proximity to TSDFs was associated to greater fatality rates, and proximity to RMPs was associated with greater prevalence rates. Results are consistent with previous research indicating that air pollution increases susceptibility to respiratory viral pathogens. Results should be interpreted cautiously given the ecological design, the time lag between exposure and outcome, and the uncertainties in measuring COVID-19 prevalence. Areas with worse prior air quality, especially higher concentrations of diesel exhaust, may be at greater COVID-19 risk, although further studies are needed to confirm these relationships.

Immunopathological features of air pollution and its impact on inflammatory airway diseases (IAD)

Air pollution causes significant morbidity and mortality in patients with inflammatory airway diseases (IAD) such as allergic rhinitis (AR), chronic rhinosinusitis (CRS), asthma, and chronic obstructive pulmonary disease (COPD). Oxidative stress in patients with IAD can induce eosinophilic inflammation in the airways, augment atopic allergic sensitization, and increase susceptibility to infection. We reviewed emerging data depicting the involvement of oxidative stress in IAD patients. We evaluated biomarkers, outcome measures and immunopathological alterations across the airway mucosal barrier following exposure, particularly when accentuated by an infectious insult.

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.

Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID

This study has two goals. The first is to explain the geo-environmental determinants of the accelerated diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats similar to COVID-19 having an accelerated viral infectivity in society. Using data on sample of N = 55 Italian province capitals, and data of infected individuals at as of April 7th, 2020, results reveal that the accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution of cities measured with days exceeding the limits set for PM10 (particulate matter 10 μm or less in diameter) or ozone. In particular, hinterland cities with average high number of days exceeding the limits set for PM10 (and also having a low wind speed) have a very high number of infected people on 7th April 2020 (arithmetic mean is about 2200 infected individuals, with average polluted days greater than 80 days per year), whereas coastal cities also having days exceeding the limits set for PM10 or ozone but with high wind speed have about 944.70 average infected individuals, with about 60 average polluted days per year; moreover, cities having more than 100 days of air pollution (exceeding the limits set for PM10), they have a very high average number of infected people (about 3350 infected individuals, 7th April 2020), whereas cities having less than 100 days of air pollution per year, they have a lower average number of infected people (about 1014 individuals). The findings here also suggest that to minimize the impact of future epidemics similar to COVID-19, the max number of days per year that Italian provincial capitals or similar industrialized cities can exceed the limits set for PM10 or for ozone, considering their meteorological conditions, is about 48 days. Moreover, results here reveal that the explanatory variable of air pollution in cities seems to be a more important predictor in the initial phase of diffusion of viral infectivity (on 17th March 2020, b1 = 1.27, p < 0.001) than interpersonal contacts (b2 = 0.31, p < 0.05). In the second phase of maturity of the transmission dynamics of COVID-19, air pollution reduces intensity (on 7th April 2020 with b'1 = 0.81, p < 0.001) also because of the indirect effect of lockdown, whereas regression coefficient of transmission based on interpersonal contacts has a stable level (b'2 = 0.31, p < 0.01). This result reveals that accelerated transmission dynamics of COVID-19 is due to mainly to the mechanism of "air pollution-to-human transmission" (airborne viral infectivity) rather than "human-to-human transmission". Overall, then, transmission dynamics of viral infectivity, such as COVID-19, is due to systemic causes: general factors that are the same for all regions (e.g., biological characteristics of virus, incubation period, etc.) and specific factors which are different for each region and/or city (e.g., complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity) and health level of individuals (habits, immune system, age, sex, etc.). Lessons learned for COVID-19 in the case study here suggest that a proactive strategy to cope with future epidemics is also to apply especially an environmental and sustainable policy based on reduction of levels of air pollution mainly in hinterland and polluting cities- (having low wind speed, high percentage of moisture and number of fog days) -that seem to have an environment that foster a fast transmission dynamics of viral infectivity in society. Hence, in the presence of polluting industrialization in regions that can trigger the mechanism of air pollution-to-human transmission dynamics of viral infectivity, this study must conclude that a comprehensive strategy to prevent future epidemics similar to COVID-19 has to be also designed in environmental and socioeconomic terms, that is also based on sustainability science and environmental science, and not only in terms of biology, medicine, healthcare and health sector.

The correlation between atmospheric visibility and influenza in Wuxi city, China

Influenza is an acute respiratory infectious disease that poses a threat to public health. We assessed the association between atmospheric visibility and influenza and influenza-like illness (ILI) in Wuxi city, China.Daily meteorological data, ILI activity, and influenza virus infection rates were collected between 31 December 2012 and 31 December 2017. A distributed lag non-linear model (DLNM) was used to analyze the exposure-lag-response of ILI and influenza activity and daily average visibility.A total of 12,800 cases were detected; 1046 cases (8.17%) were of Flu-A and 527 (4.12%) were of Flu-B infection. Our analysis suggested a non-linear relationship between atmospheric visibility and influenza: U-shaped for ILI, and L-shaped for Flu-A and Flu-B. Comparing low visibility (2.5 km) to ILI cases, the risk appeared between day 1 and day 2. For Flu-A, the risk appeared between days 5 and 9, whereas for Flu-B, the risk effect was much stronger and had a longer reaction delay, staying above zero until day 9. The protective effects of high visibility (14 km) on ILI and Flu-B occurred the same day or one day later. However, we found no association between high visibility and Flu-A.In conclusion, our study contributes novel evidence for the effects of atmospheric visibility on influenza. These findings are important for the development of influenza surveillance and early warning systems in Wuxi city.

Human rhinovirus infection and COPD: role in exacerbations and potential for therapeutic targets

INTRODUCTION

Respiratory virus infections (predominantly rhinoviruses) are the commonly identified in COPD exacerbations but debate about their role as a trigger of exacerbations continues. Experimental infection studies have provided significant new evidence establishing a causal relationship between virus infection and COPD exacerbations and contributed to a better understanding of the mechanisms of virus-induced exacerbations. However as yet no anti-viral treatments have undergone clinical trials in COPD patients.

AREAS COVERED

This review discusses the evidence for and against respiratory viruses being the main trigger of COPD exacerbations from both epidemiological studies and experimental infection studies. The host immune response to rhinovirus infection and how abnormalities in host immunity may underlie increased susceptibility to virus infection in COPD are discussed and the role of dual viral-bacterial infection in COPD exacerbations. Finally the current state of anti-viral therapy is discussed and how these may be used in the future treatment of COPD exacerbations.

EXPERT OPINION

Respiratory virus infections are the trigger of a substantial proportion of COPD exacerbations and rhinoviruses are the most common virus type. Clinical trials of anti-viral agents are needed in COPD patients to determine whether they are effective in virus-induced COPD exacerbations.

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.

Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics (Preprint).. [DOI: 10.2196/preprints.19331]

BACKGROUND

Coronavirus disease 2019 (COVID-19) is viral infection that generates a severe acute respiratory syndrome with serious pneumonia that may result in progressive respiratory failure and death.

OBJECTIVE

This study has two goals. The first is to explain the main factors determining the diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats with of accelerated viral infectivity in society.

METHODS

Correlation and regression analyses on on data of N=55 Italian province capitals, and data of infected individuals at as of April 2020.

RESULTS

The main results are: o The accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution. o Hinterland cities have average days of exceeding the limits set for PM10 (particulate matter 10 micrometers or less in diameter) equal to 80 days, and an average number of infected more than 2,000 individuals as of April 1st, 2020, coastal cities have days of exceeding the limits set for PM10 equal to 60 days and have about 700 infected in average. o Cities that average number of 125 days exceeding the limits set for PM10, last year, they have an average number of infected individual higher than 3,200 units, whereas cities having less than 100 days (average number of 48 days) exceeding the limits set for PM10, they have an average number of about 900 infected individuals. o The results reveal that accelerated transmission dynamics of COVID-19 in specific environments is due to two mechanisms given by: air pollution-to-human transmission and human-to-human transmission; in particular, the mechanisms of air pollution-to-human transmission play a critical role rather than human-to-human transmission. o The finding here suggests that to minimize future epidemic similar to COVID-19, the max number of days per year in which cities can exceed the limits set for PM10 or for ozone, considering their meteorological condition, is less than 50 days. After this critical threshold, the analytical output here suggests that environmental inconsistencies because of the combination between air pollution and meteorological conditions (with high moisture%, low wind speed and fog) trigger a take-off of viral infectivity (accelerated epidemic diffusion) with damages for health of population, economy and society.

CONCLUSIONS

Considering the complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity, lessons learned for COVID-19 have to be applied for a proactive socioeconomic strategy to cope with future epidemics, especially an environmental policy based on reduction of air pollution mainly in hinterland zones of countries, having low wind speed, high percentage of moisture and fog that create an environment that can damage immune system of people and foster a fast transmission of viral infectivity similar to the COVID-19.

CLINICALTRIAL

not applicable

Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics.. [DOI: 10.1101/2020.04.06.20055657]

What is COVID-19?

Coronavirus disease 2019 (COVID-19) is viral infection that generates a severe acute respiratory syndrome with serious pneumonia that may result in progressive respiratory failure and death.

What are the goals of this investigation?

This study explains the geo-environmental determinants of the accelerated diffusion of COVID-19 in Italy that is generating a high level of deaths and suggests general lessons learned for a strategy to cope with future epidemics similar to COVID-19 to reduce viral infectivity and negative impacts in economic systems and society.

What are the results of this study?

The main results are:

What is a socioeconomic strategy to prevent future epidemics similar to COVID-19?

Considering the complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity, lessons learned for COVID-19 have to be applied for a proactive socioeconomic strategy to cope with future epidemics, especially an environmental policy based on reduction of air pollution mainly in hinterland zones of countries, having low wind speed, high percentage of moisture and fog that create an environment that can damage immune system of people and foster a fast transmission of viral infectivity similar to the COVID-19.

This study must conclude that a strategy to prevent future epidemics similar to COVID 19 has also to be designed in environmental and sustainability science and not only in terms of biology.

Short-term Effect of Air Pollution on Tuberculosis Based on Kriged Data: A Time-series Analysis

Tuberculosis (TB) has a very high mortality rate worldwide. However, only a few studies have examined the associations between short-term exposure to air pollution and TB incidence. Our objectives were to estimate associations between short-term exposure to air pollutants and TB incidence in Wuhan city, China, during the 2015–2016 period. We applied a generalized additive model to access the short-term association of air pollution with TB. Daily exposure to each air pollutant in Wuhan was determined using ordinary kriging. The air pollutants included in the analysis were particulate matter (PM) with an aerodynamic diameter less than or equal to 2.5 micrometers (PM_2.5), PM with an aerodynamic diameter less than or equal to 10 micrometers (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ground-level ozone (O₃). Daily incident cases of TB were obtained from the Hubei Provincial Center for Disease Control and Prevention (Hubei CDC). Both single- and multiple-pollutant models were used to examine the associations between air pollution and TB. Seasonal variation was assessed by splitting the all-year data into warm (May–October) and cold (November–April) seasons. In the single-pollutant model, for a 10 μg/m³ increase in PM_2.5, PM₁₀, and O₃ at lag 7, the associated TB risk increased by 17.03% (95% CI: 6.39, 28.74), 11.08% (95% CI: 6.39, 28.74), and 16.15% (95% CI: 1.88, 32.42), respectively. In the multi-pollutant model, the effect of PM_2.5 on TB remained statistically significant, while the effects of other pollutants were attenuated. The seasonal analysis showed that there was not much difference regarding the impact of air pollution on TB between the warm season and the cold season. Our study reveals that the mechanism linking air pollution and TB is still complex. Further research is warranted to explore the interaction of air pollution and TB.

Exposure to diesel exhaust particles increases susceptibility to invasive pneumococcal disease

BACKGROUND

The World Health Organization estimates that air pollution is responsible for 7 million deaths per annum, with 7% of these attributable to pneumonia. Many of these fatalities have been linked to exposure to high levels of airborne particulates, such as diesel exhaust particles (DEPs).

OBJECTIVES

We sought to determine whether exposure to DEPs could promote the progression of asymptomatic nasopharyngeal carriage of Streptococcus pneumoniae to invasive pneumococcal disease.

METHODS

We used mouse models and in vitro assays to provide a mechanistic understanding of the link between DEP exposure and pneumococcal disease risk, and we confirmed our findings by using induced sputum macrophages isolated from healthy human volunteers.

RESULTS

We demonstrate that inhaled exposure to DEPs disrupts asymptomatic nasopharyngeal carriage of S pneumoniae in mice, leading to dissemination to lungs and blood. Pneumococci are transported from the nasopharynx to the lungs following exposure to DEPs, leading to increased proinflammatory cytokine production, reduced phagocytic function of alveolar macrophages, and consequently, increased pneumococcal loads within the lungs and translocation into blood. These findings were confirmed by using DEP-exposed induced sputum macrophages isolated from healthy volunteers, demonstrating that impaired innate immune mechanisms following DEP exposure are also at play in humans.

CONCLUSION

Lung inhaled DEPs increase susceptibility to pneumococcal disease by leading to loss of immunological control of pneumococcal colonisation, increased inflammation, tissue damage, and systemic bacterial dissemination.

Peaks of Fine Particulate Matter May Modulate the Spreading and Virulence of COVID-19

A probe of a patient, seeking help in an emergency ward of a French hospital in late December 2019 because of Influenza like symptoms, was retrospectively tested positive to COVID-19. Despite the early appearance of the virus in Europe, the prevalence and virulence appeared to be low for several weeks, before the spread and severity of symptoms increased exponentially, yet with marked spatial and temporal differences. Here, we compare the possible linkages between peaks of fine particulate matter (PM2.5) and the sudden, explosive increase of hospitalizations and mortality rates in the Swiss Canton of Ticino, and the Greater Paris and London regions. We argue that these peaks of fine particulate matter are primarily occurring during thermal inversion of the boundary layer of the atmosphere. We also discuss the influence of Saharan dust intrusions on the COVID-19 outbreak observed in early 2020 on the Canary Islands. We deem it both reasonable and plausible that high PM2.5 concentrations-favored by air temperature inversions or Saharan dust intrusions-are not only modulating but even more so boosting severe outbreaks of COVID-19. Moreover, desert dust events-besides enhancing PM2.5 concentrations-can be a vector for fungal diseases, thereby exacerbating COVID-19 morbidity and mortality. We conclude that the overburdening of the health services and hospitals as well as the high over-mortality observed in various regions of Europe in spring 2020 may be linked to peaks of PM2.5 and likely particular weather situations that have favored the spread and enhanced the virulence of the virus. In the future, we recommended to monitor not only the prevalence of the virus, but also to consider the occurrence of weather situations that can lead to sudden, very explosive COVID-19 outbreaks.

What explains cross-city variation in mortality during the 1918 influenza pandemic? Evidence from 438 U.S. cities

Disparities in cross-city pandemic severity during the 1918 Influenza Pandemic remain poorly understood. This paper uses newly assembled historical data on annual mortality across 438 U.S. cities to explore the determinants of pandemic mortality. We assess the role of three broad factors: i) pre-pandemic population health and poverty, ii) air pollution, and iii) the timing of onset and proximity to military bases. Using regression analysis, we find that cities in the top tercile of the distribution of pre-pandemic infant mortality had 21 excess deaths per 10,000 residents in 1918 relative to cities in the bottom tercile. Similarly, cities in the top tercile of the distribution of proportion of illiterate residents had 21.3 excess deaths per 10,000 residents during the pandemic relative to cities in the bottom tercile. Cities in the top tercile of the distribution of coal-fired electricity generating capacity, an important source of urban air pollution, had 9.1 excess deaths per 10,000 residents in 1918 relative to cities in the bottom tercile. There was no statistically significant relationship between excess mortality and city proximity to World War I bases or the timing of onset. In a counterfactual analysis, the three statistically significant factors accounted for 50 percent of cross-city variation in excess mortality in 1918.