SARS-CoV-2 spread in Northern Italy: what about the pollution role?

Technology innovations in supply chains: Unlocking Sustainability and SDG Advancement

The study on the "Technology Innovations in Supply Chains: Unlocking Sustainability and SDG Advancement," offers a thorough examination of the intricate connections between technological innovation, supply chain management, sustainability development, and the advancement of the Sustainable Development Goals (SDGs) in various Chinese cities. The study explores how developments in artificial intelligence (A.I.), the Internet of Things (IoT), and big data have changed supply chain practices and their consequent effects on environmental and sustainability results. It does this by utilizing a substantial dataset spanning a decade. The findings showed that different patterns of technological adoption and their impacts might be seen in the assessed cities. While it is clear that technology innovation is essential for improving supply chain effectiveness and encouraging sustainability, not all regions see the same advantages. Variations in supply chain complexity, city size, technology advancement, and environmental legislation are all blamed for these discrepancies. The report also offers detailed knowledge of the connection between the development of modern supply chains and the advancement of the SDGs. Even though many cities showed high relationships, others showed less alignment, pointing to the importance of additional economic, sociopolitical, and environmental factors. The report concludes by highlighting the potential of technology to advance sustainability and the SDGs while emphasizing the necessity for a deliberate and context-specific approach to technology integration. Additionally, it emphasizes how crucial supportive regulations are in maximizing the advantages. These findings significantly impact business executives, educators, and legislators who want to use technology to advance sustainability and the SDGs.

Association between ABO blood groups and SARS-CoV-2 infection in blood donors of Puglia region

This is an observational multicentric cross-sectional study aiming at assessing the association between ABO blood groups and SARS-CoV-2 seroprevalence among the blood donors in Puglia region. Data on ABO and Rh blood groups and demographic characteristics were obtained from Blood Bank Information System. All donors were screened for SARS-CoV-2 IgG antibodies. Comparison of seroprevalence among blood groups and the association between the recorded variables and seroprevalence were evaluated. A total of 35,709 donors from 22 centers were included, with a seroprevalence of 6.8%. The distribution of ABO phenotypes was blood type O (46.8%), A (34.0%), B (14.7%), and AB (4.5%). Among the 2416 donors reactive for SARS-CoV-2 IgG, the prevalent phenotype was blood type O (43.1%), followed by A (37.7%), B (14.2%), and AB (5%). The seroprevalence of phenotype A and AB was 7.5%, followed by B (6.5%) and O (6.2%). According to the adjusted analysis, there was an increase in seroprevalence in groups A and AB, compared to group O, and an increase in males compared to females. A possible effect modification was observed after stratifying for sex (p = 0.0515). A significantly lower prevalence of blood type O was found compared to A and AB, whereas no association was observed between Rh factor and seroprevalence. We hypothesized that the A antigen present in blood type A and AB can play a role in the binding of SARS-CoV-2 to ACE2 receptors, resulting in an increased risk of infection. Furthermore, natural anti-A/anti-B antibodies produced in group O could block viral adhesion to cells and explain a lower risk of infection.

COVID-19 vaccine booster significantly decreases the risk of intensive care unit hospitalization in heart failure patients during the Omicron variant wave: A population-based study

Background

Heart failure (HF) patients are at higher risk of severe coronavirus disease 2019 (COVID-19). The Omicron variant has many novel mutations including those in the spike protein, leading to questions about vaccine effectiveness. The aim of this analysis was to evaluate the effectiveness of the COVID-19 vaccine with or without a booster (i.e., after the third dose) during the Omicron variant wave.

Methods

Chronic heart failure patients in the Czech Republic were included in the analysis. COVID-19 infection was monitored from January 1st 2022 to March 31st 2022. The analysis was conducted on data collected in the National Health Information System. Vaccine effectiveness of vaccinated (with or without booster) vs. unvaccinated patients was analyzed for incidence of COVID-19, COVID-19-related hospitalizations, COVID-19 related intensive care unit admissions, and COVID-19 related mechanical ventilation/extracorporeal membrane oxygenation treatment.

Findings

From a total 165,453 HF patients in the Czech Republic, 9,728 contracted COVID-19 (22.9% of them not vaccinated, 23.2% vaccinated and 53.8% vaccinated and boosted). Risk of intensive care unit (ICU) hospitalization was 7.6% in the unvaccinated group, 4.8% in the vaccinated group and 2.9% in the boosted group. The calculated effectiveness of the COVID-19 vaccine in prevention of ICU hospitalization in the vaccinated group was 41.9 and 76.6% in the boosted group.

Interpretation

The results demonstrated moderate vaccine effectiveness in the prevention of severe COVID-19 in vaccinated but not boosted HF patients. Much stronger effectiveness was found in those who were vaccinated and boosted.

Sustainable impact of COVID-19 on education projects: aspects of naturalism

History records show that pandemics and threats have always given new directions to the thinking, working, and learning styles. This article attempts to thoroughly document the positive core of coronavirus 2019 (COVID-19) and its impact on global social psychology, ecological stability, and development. Structural equation modeling (SEM) is used to test the hypotheses and comprehend the objectives of the study. The findings of the study reveals that the path coefficients for the variables health consciousness, naturalism, financial impact and self-development, sustainability, compassion, gregariousness, sympathy, and cooperation demonstrate that the factors have a positive and significant effect on COVID-19 prevention. Moreover, the content analysis was conducted on recently published reports, blog content, newspapers, and social media. The pieces of evidence from history have been cited to justify the perspective. Furthermore, to appraise the opinions of professionals of different walks of life, an online survey was conducted, and results were discussed with expert medical professionals. Outcomes establish that the pandemics give birth to creativity, instigate innovations, prompt inventions, establish human ties, and foster altruistic elements of compassion and emotionalism.

Examining the status of forest fire emission in 2020 and its connection to COVID-19 incidents in West Coast regions of the United States

Forest fires impact on soil, water, and biota resources. The current forest fires in the West Coast of the United States (US) profoundly impacted the atmosphere and air quality across the ecosystems and have caused severe environmental and public health burdens. Forest fire led emissions could significantly exacerbate the air pollution level and, therefore, would play a critical role if the same occurs together with any epidemic and pandemic health crisis. Limited research is done so far to examine its impact in connection to the current pandemic. As of October 21, nearly 8.2 million acres of forest area were burned, with more than 25 casualties reported so far. In-situ air pollution data were utilized to examine the effects of the 2020 forest fire on atmosphere and coronavirus (COVID-19) casualties. The spatial-temporal concentrations of particulate matter (PM_2.5 and PM₁₀) and Nitrogen Dioxide (NO₂) were collected from August 1 to October 30 for 2020 (the fire year) and 2019 (the reference year). Both spatial (Multiscale Geographically Weighted Regression) and non-spatial (Negative Binomial Regression) analyses were performed to assess the adverse effects of fire emission on human health. The in-situ data-led measurements showed that the maximum increases in PM_2.5, PM₁₀, and NO₂ concentrations (μg/m³) were clustered in the West Coastal fire-prone states during August 1 - October 30, 2020. The average concentration (μg/m³) of particulate matter (PM_2.5 and PM₁₀) and NO₂ was increased in all the fire states severely affected by forest fires. The average PM_2.5 concentrations (μg/m³) over the period were recorded as 7.9, 6.3, 5.5, and 5.2 for California, Colorado, Oregon, and Washington in 2019, increasing up to 24.9, 13.4, 25.0, and 17.0 in 2020. Both spatial and non-spatial regression models exhibited a statistically significant association between fire emission and COVID-19 incidents. Such association has been demonstrated robust and stable by a total of 30 models developed for analyzing the spatial non-stationary and local association. More in-depth research is needed to better understand the complex relationship between forest fire emission and human health.

The Role of ABO Blood Type in Patients with SARS-CoV-2 Infection: A Systematic Review

The SARS-CoV-2 infection has caused over 422 million contagions and 5.8 million deaths resulting in a global health crisis. Several studies have investigated the risk factors predisposing to the infection and reported that the host susceptibility can be linked to the ABO blood group, but the current evidence is controversial. We systematically searched for articles in EMBASE, PubMed, and Cochrane library published up to 7 May 2021 to explore the association of the ABO blood group with the susceptibility to SARS-CoV-2 infection. All studies in people undergoing SARS-CoV-2 test controls were included. Odds ratios were obtained in each study and then synthesised by using meta-analysis. Overall, 22 articles were selected and more than 1,200,000 individuals of whom 74,563 resulted positive to SARS-CoV-2 and 1,166,717 resulted negative, were included in the meta-analysis. Overall, 487,985 subjects had blood group A, 151,879 had group B, 52,621 had group AB, and 548,795 had group O. Group O was slightly less associated with infection, as compared to the other three blood groups (OR = 0.91, 95% CI = 0.85–0.99, p = 0.02). Conversely, group A was slightly more associated with infection, as compared to the other three groups (OR = 1.06, 95% CI = 1.00–1.13, p = 0.04). This meta-analysis shows associations between blood groups and SARS-CoV-2 infection and supports the hypothesis that blood type O may have a slightly lower risk of infection, whereas blood type A may have a slightly higher risk of infection.

Long-term exposure to PM10 above WHO guidelines exacerbates COVID-19 severity and mortality

BACKGROUND

Age, sex, race and comorbidities are insufficient to explain why some individuals remain asymptomatic after SARS-CoV-2 infection, while others die. In this sense, the increased risk caused by the long-term exposure to air pollution is being investigated to understand the high heterogeneity of the COVID-19 infection course.

OBJECTIVES

We aimed to assess the underlying effect of long-term exposure to NO2 and PM10 on the severity and mortality of COVID-19.

METHODS

A retrospective observational study was conducted with 2112 patients suffering COVID-19 infection. We built two sets of multivariate predictive models to assess the relationship between the long-term exposure to NO2 and PM10 and COVID-19 outcome. First, the probability of either death or severe COVID-19 outcome was predicted as a function of all the clinical variables together with the pollutants exposure by means of two regularized logistic regressions. Subsequently, two regularized linear regressions were constructed to predict the percentage of dead or severe patients. Finally, odds ratios and effects estimates were calculated.

RESULTS

We found that the long-term exposure to PM10 is a more important variable than some already stated comorbidities (i.e.: COPD/Asthma, diabetes, obesity) in the prediction of COVID-19 severity and mortality. PM10 showed the highest effects estimates (1.65, 95% CI 1.32-2.06) on COVID-19 severity. For mortality, the highest effect estimates corresponded to age (3.59, 95% CI 2.94-4.40), followed by PM10 (2.37, 95% CI 1.71-3.32). Finally, an increase of 1 µg/m3 in PM10 concentration causes an increase of 3.06% (95% CI 1.11%-4.25%) of patients suffering COVID-19 as a severe disease and an increase of 2.68% (95% CI 0.53%-5.58%) of deaths.

DISCUSSION

These results demonstrate that long-term PM10 burdens above WHO guidelines exacerbate COVID-19 health outcomes. Hence, WHO guidelines, the air quality standard established by the Directive 2008/50/EU, and that of the US-EPA should be updated accordingly to protect human health.

Analyzing the severity of coronavirus infections in relation to air pollution: evidence-based study from Saudi Arabia

COVID-19 is one of the major pandemics in history. It has caused various health problems to majority of countries in the world. Several researchers have examined and developed studies regarding concerns on air pollution being considered a major risk factor causing respiratory infections. Such infections are carried out by microorganisms, thus further affecting the immune system. The present study involves the relationship between air pollutants and the total COVID-19 infections along with the estimation of death rates in several regions of Saudi Arabia. The major goal of this study comprises the analysis of the relationship between air pollutants concentration, such as PM10, NO₂, CO, SO₂, and O₃, and the widespread outbreak of COVID-19. This scenario involves the transmission, number of patients, critical cases, and death rates. Results show that the estimation of recorded COVID-19 cases was in the most polluted regions; the mortality rate and critical cases were also more distinct in these regions than in other regions in Saudi Arabia. The finding of this study demonstrates a positive correlation between the mean values of PM10, NO₂, CO, and SO₂ pollutants. The results represent the significant relationship between air pollution resulting from a high concentration of NO₂ and COVID-19 infections and deaths. In addition, a null hypothesis of the relation between other pollutants and COVID-19 infections cannot be rejected. The study also indicates a significant correlation between the means of NO₂ and CO and the total number of critical cases. Negative correlations are obtained between the mean of O₃ and the total number of cases, total deaths, and critical case per cumulative days.

Long-term exposure to PM10 above WHO guidelines exacerbates COVID-19 severity and mortality

BACKGROUND

Age, sex, race and comorbidities are insufficient to explain why some individuals remain asymptomatic after SARS-CoV-2 infection, while others die. In this sense, the increased risk caused by the long-term exposure to air pollution is being investigated to understand the high heterogeneity of the COVID-19 infection course.

OBJECTIVES

We aimed to assess the underlying effect of long-term exposure to NO₂ and PM₁₀ on the severity and mortality of COVID-19.

METHODS

A retrospective observational study was conducted with 2112 patients suffering COVID-19 infection. We built two sets of multivariate predictive models to assess the relationship between the long-term exposure to NO₂ and PM₁₀ and COVID-19 outcome. First, the probability of either death or severe COVID-19 outcome was predicted as a function of all the clinical variables together with the pollutants exposure by means of two regularized logistic regressions. Subsequently, two regularized linear regressions were constructed to predict the percentage of dead or severe patients. Finally, odds ratios and effects estimates were calculated.

RESULTS

We found that the long-term exposure to PM₁₀ is a more important variable than some already stated comorbidities (i.e.: COPD/Asthma, diabetes, obesity) in the prediction of COVID-19 severity and mortality. PM₁₀ showed the highest effects estimates (1.65, 95% CI 1.32-2.06) on COVID-19 severity. For mortality, the highest effect estimates corresponded to age (3.59, 95% CI 2.94-4.40), followed by PM₁₀ (2.37, 95% CI 1.71-3.32). Finally, an increase of 1 µg/m³ in PM₁₀ concentration causes an increase of 3.06% (95% CI 1.11%-4.25%) of patients suffering COVID-19 as a severe disease and an increase of 2.68% (95% CI 0.53%-5.58%) of deaths.

DISCUSSION

These results demonstrate that long-term PM₁₀ burdens above WHO guidelines exacerbate COVID-19 health outcomes. Hence, WHO guidelines, the air quality standard established by the Directive 2008/50/EU, and that of the US-EPA should be updated accordingly to protect human health.

The effect of environmental diesel exhaust pollution on SARS-CoV-2 infection: The mechanism of pulmonary ground glass opacity

Diesel exhaust particles (DEP) are the major components of atmospheric particulate matter (PM) and chronic exposure is recognized to enhance respiratory system complications. Although the spread of SARS-CoV-2 was found to be associated with the PMs, the mechanism by which exposure to DEP increases the risk of SARS-CoV-2 infection is still under discussion. However, diesel fine PM (dPM) elevate the probability of SARS-CoV-2 infection, as it coincides with the increase in the number of ACE2 receptors. Expression of ACE2 and its colocalized activator, transmembrane protease serine 2 (TMPRSS2) facilitate the entry of SARS-CoV-2 into the alveolar epithelial cells exposed to dPM. Thus, the coexistence of PM and SARS-CoV-2 in the environment augments inflammation and exacerbates lung damage. Increased TGF-β1 expression due to DEP accompanies the proliferation of the extracellular matrix. In this case, "multifocal ground-glass opacity" (GGO) in a CT scan is an indication of a cytokine storm and severe pneumonia in COVID-19.

Why the COVID-19 Is Not Significantly Reduced in Iran?

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was transported from China to Iran via passengers. The virus is transmitted through droplets from coughing, sneezing, talking and contact with infected surfaces. Due to high transmissibility in places such as clinics, medical offices, buses and offices where there are large crowds, it spread rapidly in Iran and caused the mortality of a significant number of people, especially the elderly with underlying disease. Preventing travel and gatherings, as well as applying house quarantine in Apr 2020, reduced COVID-19 somewhat but then due to lack of attention to social distancing, reducing the use of masks by the people and inappropriate decisions by the national committee on combating coronavirus (NCCC), including reducing the working hours of public offices and shops, reducing the staff of government offices, monopoly on the distribution of essential materials and supplies, the presence of overcrowding in clinics of medical centers, hospitals, and private clinics caused the decline of the disease in the country to decrease. Measures can be taken to prevent the spread of the virus as much as possible, including: rapid detection of infected people, their isolation, contact tracing, quarantine of people over 65 and under 15, protection of the elderly, prevention of gatherings, forcing the use of protective equipment in possible gatherings, and electronicizing public services.

Role of ABO blood system in COVID-19: Findings from a southern Italian study

BACKGROUND

COVID-19 is a worldwide infection caused by SARS-CoV-2 and infects humans by binding to the ACE2 receptor. Blood group ABO glycoproteins can influence the binding of the virus to ACE2. The role of ABO blood system in the susceptibility to infection as well as in the clinical outcome of infected patients is still controversial and needs to be clarified.

METHODS

We conducted a retrospective study of 167 patients positive for SARS-CoV-2 who underwent nasopharyngeal swab, and of a control group represented by 891 subjects negative for SARS-CoV-2, to assess the association between ABO and Rh blood system and occurrence of SARS-CoV-2 infection, clinical presentation, and outcome of disease.

RESULTS

In the cohort of patients positive for SARS-CoV-2, no statistically significant difference in the distribution of ABO blood types compared with controls was observed. Patients with blood type A had a higher risk of developing symptomatic disease (p = 0.002; odds ratio [OR = 3.592]; 95% confidence interval [CI] = 1.576-8.187) compared to patients with blood types B, AB, and O. Patients with blood types B (p = 0.021; OR = 0.293; 95%CI = 0.099-0.869) and O (p = 0.018; OR = 0.417; 95%CI = 0.199-0.871) showed a lower risk in comparison to the other groups. The clinical progression to mild/moderate and severe/critical disease and the mortality showed no association. Moreover, no relationship with Rh blood type was found.

CONCLUSIONS

Our findings support a role of ABO blood type in the development of symptomatic disease with a higher risk in subjects with blood type A and a protective effect of blood types B and O. Blood types do not seem, however, to play a role in susceptibility, progression to severe disease, and death.

Inflammation at the Crossroads: the Combined Effects of COVID-19, Ageing, and Air Pollution

The global COVID-19 pandemic has highlighted different vulnerability profiles among individuals. With the highest mortality rate, the elderly are a very sensitive group. With regard to the main symptoms, a failure of the respiratory system, associated with deregulation of the immune system, has been observed. These symptoms may also be encountered in chronic exposure of susceptible populations to air pollution, including exacerbation of the inflammatory response. Is there a relationship between age, pollution exposure and the severity of COVID-19? Although it is unclear how these parameters are related, the same pathways can be activated and appear to find a common mechanism of action in inflammation.

Effect of COVID-19 on air quality and pollution in different countries

INTRODUCTION

COVID-19 is a pandemic that affected humans' lives and activities through the year 2020 in a way that was not witnessed in recent years. Many governments declared a complete lockdown as a try to stop the transmission of the disease. This lockdown resulted in a good recovery in environmental health, where air pollutants levels dramatically decreased.

THEORY

There are two relations between air pollution and COVID-19, one is before the disease spread, and the other is after. Before the disease spread, many areas had high levels of contaminants in the air due to industrial activities, transportation, and human density. These areas had the highest infection rates and death cases. This could be attributed to two reasons, the aerosol could help to spread the virus at a higher rate, and air pollutants could negatively affect peoples' lungs, which assisted the virus in attacking the patients brutally.

RESULTS

After the disease spread, the lockdown that was applied in the major industrial countries led to a decrease in the pollutants levels and an increase in the ozone level in the air. This lockdown improved the air quality worldwide to a level that all political conferences and agreements could not reach. In this review, we are showing the impact of COVID-19 on air pollutants in different countries.

SUMMARY

This paper provides information about pollutants' influence on human and environmental health that other researchers obtained in different areas of the globe before and after the pandemic. This could give ideas about the impact of humans on the environment and the possible ways of recovering the environment's health.

Community Risk Factors in the COVID-19 Incidence and Mortality in Catalonia (Spain). A Population-Based Study

The heterogenous distribution of both COVID-19 incidence and mortality in Catalonia (Spain) during the firsts moths of the pandemic suggests that differences in baseline risk factors across regions might play a relevant role in modulating the outcome of the pandemic. This paper investigates the associations between both COVID-19 incidence and mortality and air pollutant concentration levels, and screens the potential effect of the type of agri-food industry and the overall land use and cover (LULC) at area level. We used a main model with demographic, socioeconomic and comorbidity covariates highlighted in previous research as important predictors. This allowed us to take a glimpse of the independent effect of the explanatory variables when controlled for the main model covariates. Our findings are aligned with previous research showing that the baseline features of the regions in terms of general health status, pollutant concentration levels (here NO₂ and PM₁₀), type of agri-food industry, and type of land use and land cover have modulated the impact of COVID-19 at a regional scale. This study is among the first to explore the associations between COVID-19 and the type of agri-food industry and LULC data using a population-based approach. The results of this paper might serve as the basis to develop new research hypotheses using a more comprehensive approach, highlighting the inequalities of regions in terms of risk factors and their response to COVID-19, as well as fostering public policies towards more resilient and safer environments.

An updated systematic review on the association between atmospheric particulate matter pollution and prevalence of SARS-CoV-2

On December 31, 2019, the novel human coronavirus (COVID-19) was emerged in Wuhan city, China, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There is a much controversial debate about the major pathways of transmission of the virus including airborne route. The present work is a systematic literature review (SR) aimed to assess the association of air pollution especially particulate matter pollution in the transmission and acceleration of the spread of SARS-CoV-2. The systematic literature search was performed to identify the available studies published through October 31, 2020 concerning the transmission of the disease and particulate matter air pollution in four international electronic databases. From the results of the included studies, there are suggestions that atmospheric particulate matter pollution plays a role in the SARS-CoV-2 spread, but the literature has not confirmed that it enhances the transmission although some studies have proposed that atmospheric particulate matter can operate as a virus carrier, promoting its spread. Therefore, although PM concentration alone cannot be effective in spreading the COVID-19 disease, other meteorological and environmental parameters including size of particles in ambient air, weather conditions, wind speed, relative humidity (RH) and temperature are involved. Therefore, it is necessary to consider all influencing parameters to prevent the spreading of COVID-19 disease. More studies are required to strengthen the scientific evidence and support more definitive conclusions.

Does solar ultraviolet radiation play a role in COVID-19 infection and deaths? An environmental ecological study in Italy

A significantly stronger impact in mortality and morbidity by COVID-19 has been observed in the northern Italian regions compared to the southern ones. The reasons of this geographical pattern might involve several concurrent factors. The main objective of this work is to investigate whether any correlations exist between the spatial distribution of COVID-19 cases and deaths in the different Italian regions and the amount of solar ultraviolet (UV) radiation at the Earth's surface. To this purpose, in this environmental ecological study a mixed-effect exponential regression was built to explain the incidence of COVID-19 based on the environmental conditions, and demographic and pathophysiologic factors. Observations and estimates of the cumulative solar UV exposure have been included to quantify the amount of radiation available e.g., for pre-vitamin D3 synthesis or SARS-CoV-2 inactivation by sunlight. The analysis shows a significant correlation (p-value <5 × 10^-2) between the response variables (death percentage, incidence of infections and positive tests) and biologically effective solar UV radiation, residents in nursing homes per inhabitant (NHR), air temperature, death percentage due to the most frequent comorbidities. Among all factors, the amount of solar UV radiation is the variable contributing the most to the observed correlation, explaining up to 83.2% of the variance of the COVID-19 affected cases per population. While the statistical outcomes of the study do not directly entail a specific cause-effect relationship, our results are consistent with the hypothesis that solar UV radiation impacted on the development of the infection and on its complications, e.g. through the effect of vitamin D on the immune system or virus inactivation by sunlight. The analytical framework used in this study, based on commonly available data, can be easily replicated in other countries and geographical domains to identify possible correlations between exposure to solar UV radiation and the spread of the pandemic.

How do low wind speeds and high levels of air pollution support the spread of COVID-19?

The pandemic of coronavirus disease 2019 (COVID-19) is generating a high number of infected individuals and deaths. One of the current questions is how climatological factors and environmental pollution can affect the diffusion of COVID-19 in human society. This study endeavours to explain the relation between wind speed, air pollution and the diffusion of COVID-19 to provide insights to constrain and/or prevent future pandemics and epidemics. The statistical analysis here focuses on case study of Italy and reveals two main findings: 1) cities with high wind speed have lower numbers of COVID-19 related infected individuals; 2) cities located in hinterland zones (mostly those bordering large urban conurbations) with little wind speed and frequently high levels of air pollution had higher numbers of COVID-19 related infected individuals. Results here suggest that high concentrations of air pollutants, associated with low wind speeds, may promote a longer permanence of viral particles in polluted air of cities, thus favouring an indirect means of diffusion of the novel coronavirus (SARS-CoV-2), in addition to the direct diffusion with human-to-human transmission dynamics.

Particulate matter and SARS-CoV-2: A possible model of COVID-19 transmission

Coronavirus disease 2019 (COVID-19), an acute respiratory disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly developed into a pandemic throughout the world. This disease is a highly infectious novel coronavirus and can affect people of all ages. Previous reports observed that particulate matter (PM) provided a platform for intermixing with viruses (i.e., influenza). However, the role of PM in SARS-CoV-2 transmission remains unclear. In this paper, we propose that PM plays a direct role as a "carrier" of SARS-CoV-2. SARS-CoV-2 is reported to have a high affinity for the angiotensin-converting enzyme 2 (ACE2) receptor. Indirectly, exposure to PM increases ACE2 expression in the lungs which facilitates SARS-CoV-2 viral adhesion. Thus, the high risk of SARS-CoV-2 in heavily polluted regions can be explained by upregulation of ACE2 caused by PM. PM could be both a direct and indirect transmission model for SARS-CoV-2 infection.

Effects of air pollution on the potential transmission and mortality of COVID-19: A preliminary case-study in Tarragona Province (Catalonia, Spain)

The number of studies published on COVID-19 in recent months is certainly impressive. However, there are still important gaps to know a great number of characteristics of this disease. Among these, some potential ways of transmission of the SARS-CoV-2 and the different reasons for the severity of the disease in different people. Various studies have suggested that certain air pollutants could be increasing the transmission of the coronavirus, as well as the risks of COVID-19 incidence and mortality. In the present preliminary case-study conducted in Tarragona Province (Catalonia, Spain), we studied the potential association of COVID-19 with PM₁₀, NO₂ and O₃, as well as the differences in the incidence and lethality of this disease. This Province is divided into two "health regions": Camp de Tarragona, with an important industrial complex, and Terres de l'Ebre, with a great agricultural component. In spite of the notable limitations of the current study, our preliminary findings indicate that the industrialized/urban areas of Tarragona Province show a higher incidence and mortality of COVID-19 than the agricultural/rural zones. These - and previous - results would highlight the importance of conducting specific investigations focused on directly assessing whether air pollutants such as particulate matter can act as carriers of the SARS-CoV-2. If confirmed, the recommendation on keeping the "social distance" (1.5-2 m) might need to be adapted to this situation.

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.

Particulate matter (PM10) enhances RNA virus infection through modulation of innate immune responses

Sensing of pathogens by specialized receptors is the hallmark of the innate immunity. Innate immune response also mounts a defense response against various allergens and pollutants including particulate matter present in the atmosphere. Air pollution has been included as the top threat to global health declared by WHO which aims to cover more than three billion people against health emergencies from 2019 to 2023. Particulate matter (PM), one of the major components of air pollution, is a significant risk factor for many human diseases and its adverse effects include morbidity and premature deaths throughout the world. Several clinical and epidemiological studies have identified a key link between the PM existence and the prevalence of respiratory and inflammatory disorders. However, the underlying molecular mechanism is not well understood. Here, we investigated the influence of air pollutant, PM10 (particles with aerodynamic diameter less than 10 μm) during RNA virus infections using Highly Pathogenic Avian Influenza (HPAI) - H5N1 virus. We thus characterized the transcriptomic profile of lung epithelial cell line, A549 treated with PM10 prior to H5N1infection, which is known to cause severe lung damage and respiratory disease. We found that PM10 enhances vulnerability (by cellular damage) and regulates virus infectivity to enhance overall pathogenic burden in the lung cells. Additionally, the transcriptomic profile highlights the connection of host factors related to various metabolic pathways and immune responses which were dysregulated during virus infection. Collectively, our findings suggest a strong link between the prevalence of respiratory illness and its association with the air quality.

Impact of COVID-19 outbreak measures of lockdown on the Italian Carbon Footprint

Stringent lockdown measures implemented in Italy to mitigate the spread of COVID-19 are generating unprecedented economic impacts. However, the environmental consequences associated with the temporary shutdown and recovery of industrial and commercial activities are still not fully understood. Using the well-known carbon footprint (CF) indicator, this paper provides a comprehensive estimation of environmental effects due to the COVID-19 outbreak lockdown measures in Italy. Our aim was to quantify the CF associated with the consumption of energy by any economic activity and region in Italy during the lockdown, and then compare these environmental burdens with the CF calculated for analogous periods from 2015 to 2019 (~March and April). Complementarily, we also conducted a scenario analysis to estimate the post-lockdown CF impact in Italy. A consumption-based approach was applied according to the principles of the established Life Cycle Assessment method. The CF was therefore quantified as a sum of direct and indirect greenhouse gases (GHGs) released from domestically produced and imported energy metabolism flows, excluding the exports. Our findings indicate that the CF in the lockdown period is ~-20% lower than the mean CF calculated for the past. This means avoided GHGs in between ~5.6 and ~10.6 Mt CO₂e. Results further suggest that a tendency occurs towards higher impact savings in the Northern regions, on average ~230 kt CO₂e of GHGs avoided by province (against ~110-130 kt CO₂e in central and Southern provinces). Not surprisingly, these are the utmost industrialized areas of Italy and have been the ones mostly affected by the outbreak. Despite our CF estimates are not free of uncertainties, our research offers quantitative insights to start understanding the magnitude generated by such an exceptional lockdown event in Italy on climate change, and to complement current scientific efforts investigating the relationships between air pollution and the spread of COVID-19.

Influence of airborne transmission of SARS-CoV-2 on COVID-19 pandemic. A review

In recent years, a number of epidemiological studies have demonstrated that exposure to air pollution is associated with several adverse outcomes, such as acute lower respiratory infections, chronic obstructive pulmonary disease, asthma, cardiovascular diseases, and lung cancer among other serious diseases. Air pollutants such as sulfur oxides, nitrogen oxides, carbon monoxide and dioxide, particulate matter (PM), ozone and volatile organic compounds (VOCs) are commonly found at high levels in big cities and/or in the vicinity of different chemical industries. An association between air concentrations of these pollutants and human respiratory viruses interacting to adversely affect the respiratory system has been also reported. The present review was aimed at assessing the potential relationship between the concentrations of air pollutants on the airborne transmission of SARS-CoV-2 and the severity of COVID-19 in patients infected by this coronavirus. The results of most studies here reviewed suggest that chronic exposure to certain air pollutants leads to more severe and lethal forms of COVID-19 and delays/complicates the recovery of patients of this disease.