Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States

The long-term impact of coronavirus disease 2019 on environmental health: a review study of the bi-directional effect

BACKGROUND

When health systems worldwide grapple with the coronavirus disease 2019 (COVID-19) pandemic, its effect on the global environment is also a significant consideration factor. It is a two-way process where the pre-COVID climate factors influenced the landscape in which the disease proliferates globally and the consequences of the pandemic on our surroundings. The environmental health disparities will also have a long-lasting effect on public health response.

MAIN BODY

The ongoing research on the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and COVID-19 must also include the role of environmental factors in the process of infection and the differential severity of the disease. Studies have shown that the virus has created positive and negative ramifications on the world environment, especially in countries most critically affected by the pandemic. Contingency measures to slow down the virus, such as self-distancing and lockdowns have shown improvements in air, water, and noise quality with a concomitant decrease in greenhouse gas emissions. On the other hand, biohazard waste management is a cause for concern that can result in negative effects on planetary health. At the peak of the infection, most attention has been diverted to the medical aspects of the pandemic. Gradually, policymakers must shift their focus to social and economic avenues, environmental development, and sustainability.

CONCLUSION

The COVID-19 pandemic has profoundly impacted the environment, both directly and indirectly. On the one hand, the sudden halt in economic and industrial activities led to a decrease in air and water pollution, as well as a reduction in greenhouse gas emissions. On the other hand, the increased use of single-use plastics and a surge in e-commerce activities have had negative effects on the environment. As we move forward, we must consider the pandemic's long-term impacts on the environment and work toward a more sustainable future that balances economic growth and environmental protection. The study shall update the readers on the various facets of the interaction between this pandemic and environmental health with model development for long-term sustainability.

Associations between short-term exposure to ambient PM2.5 and incident cases of cerebrovascular disease in Yantai, China

There are limited studies examining the association between PM_2.5 exposure and incident cerebrovascular disease (CD) cases in China. In this study, daily counts of incident CD cases and daily PM_2.5 concentrations were obtained in Yantai, Shandong Province, China from 2014 to 2019. We used a combination of the Poisson-distribution generalized linear model (GLM) and a distributed lag nonlinear model (DLNM) to examine the association of short-term exposure to ambient PM_2.5 and incident cases of CD. The results revealed that for every 10 μg/m³ increment of PM_2.5 would increase the incident CD cases by 0.216% (RR:1.00216, 95%CI:1.0016-1.0028) at lag4. The stratified analysis demonstrated that the females and residents aged 65 years or above presented higher short-term PM_2.5-associated CD risks than the males and aged below 65 years. Targeted prevention strategies should be adopted to reduce the PM_2.5-related CD burden, especially for the susceptible population in China.

The Relationship between the Transmission of Different SARS-CoV-2 Strains and Air Quality: A Case Study in China

Coronavirus Disease 2019 (COVID-19) has been a global public health concern for almost three years, and the transmission characteristics vary among different virus variants. Previous studies have investigated the relationship between air pollutants and COVID-19 infection caused by the original strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, it is unclear whether individuals might be more susceptible to COVID-19 due to exposure to air pollutants, with the SARS-CoV-2 mutating faster and faster. This study aimed to explore the relationship between air pollutants and COVID-19 infection caused by three major SARS-CoV-2 strains (the original strain, Delta variant, and Omicron variant) in China. A generalized additive model was applied to investigate the associations of COVID-19 infection with six air pollutants (PM_2.5, PM₁₀, SO₂, CO, NO₂, and O₃). A positive correlation might be indicated between air pollutants (PM_2.5, PM₁₀, and NO₂) and confirmed cases of COVID-19 caused by different SARS-CoV-2 strains. It also suggested that the mutant variants appear to be more closely associated with air pollutants than the original strain. This study could provide valuable insight into control strategies that limit the concentration of air pollutants at lower levels and would better control the spread of COVID-19 even as the virus continues to mutate.

A correlational analysis of COVID-19 incidence and mortality and urban determinants of vitamin D status across the London boroughs

One of the biggest challenges of the COVID-19 pandemic is the heterogeneity in disease severity exhibited amongst patients. Among multiple factors, latest studies suggest vitamin D deficiency and pre-existing health conditions to be major contributors to death from COVID-19. It is known that certain urban form attributes can impact sun exposure and vitamin D synthesis. Also, long-term exposure to air pollution can play an independent role in vitamin D deficiency. We conducted a correlational analysis of urban form and air quality in relation to the demographics and COVID-19 incidence and mortality across 32 London boroughs between March 2020 and January 2021. We found total population, number of residents of Asian ethnicity, 4-year average PM₁₀ levels and road length to be positively correlated with COVID-19 cases and deaths. We also found percentage of households with access to total open space to be negatively correlated with COVID-19 deaths. Our findings link COVID-19 incidence and mortality across London with environmental variables linked to vitamin D status. Our study is entirely based on publicly available data and provides a reference framework for further research as more data are gathered and the syndemic dimension of COVID-19 becomes increasingly relevant in connection to health inequalities within large urban areas.

Comprehensive Analysis of the COVID-19: Based on the Social-Related Indexes From NUMBEO

Background

The COVID-19 has been spreading globally since 2019 and causes serious damage to the whole society. A macro perspective study to explore the changes of some social-related indexes of different countries is meaningful.

Methods

We collected nine social-related indexes and the score of COVID-safety-assessment. Data analysis is carried out using three time series models. In particular, a prediction-correction procedure was employed to explore the impact of the pandemic on the indexes of developed and developing countries.

Results

It shows that COVID-19 epidemic has an impact on the life of residents in various aspects, specifically in quality of life, purchasing power, and safety. Cluster analysis and bivariate statistical analysis further indicate that indexes affected by the pandemic in developed and developing countries are different.

Conclusion

This pandemic has altered the lives of residents in many ways. Our further research shows that the impacts of social-related indexes in developed and developing countries are different, which is bounded up with their epidemic severity and control measures. On the other hand, the climate is crucial for the control of COVID-19. Consequently, exploring the changes of social-related indexes is significative, and it is conducive to provide targeted governance strategies for various countries. Our article will contribute to countries with different levels of development pay more attention to social changes and take timely and effective measures to adjust social changes while trying to control this pandemic.

Modeling the contribution of Nitrogen Dioxide, Vertical pressure velocity and PM2.5 to COVID-19 fatalities

The COVID-19 caused by the severe acute respiratory syndrome coronavirus was reported in China in December 2019. The severity and lethality of this disease have been linked to poor air quality indicators such as tropospheric nitrogen dioxide (NO₂) and dust surface mass concentration particulate matter (PM2.5) as possible contributors. The Arab League has 22 member countries and is home to almost 420 million people. The primary objective of this study is to assess the relationship between NO₂, PM2.5 and vertical pressure velocity (hereafter: OMEGA) (extracted from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) database), socio-economic factors (the population and geographic area of each member country) and COVID-19 deaths using Bayesian model averaging. The total plausible models (2⁵) were estimated. The results show that the posterior inclusion probability (PIP), which indicates the probability that a particular indicator is included in the best model, was 0.69, 0.94, 0.68, 0.47, and 0.61 for OMEGA, PM2.5, NO₂, geographical area, and population, respectively, meaning that these variables are important contributors in predicting COVID-19 fatalities in the Arab League states. This study shows that atmospheric satellite measurements from MERRA-2 datasets are capable of being used to quantify trace gases in pandemic studies.

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

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

A multi-step machine learning approach to assess the impact of COVID-19 lockdown on NO2 attributable deaths in Milan and Rome, Italy

BACKGROUND

Air pollution is one of the main concerns for the health of European citizens, and cities are currently striving to accomplish EU air pollution regulation. The 2020 COVID-19 lockdown measures can be seen as an unintended but effective experiment to assess the impact of traffic restriction policies on air pollution. Our objective was to estimate the impact of the lockdown measures on NO2 concentrations and health in the two largest Italian cities.

METHODS

NO2 concentration datasets were built using data deriving from a 1-month citizen science monitoring campaign that took place in Milan and Rome just before the Italian lockdown period. Annual mean NO2 concentrations were estimated for a lockdown scenario (Scenario 1) and a scenario without lockdown (Scenario 2), by applying city-specific annual adjustment factors to the 1-month data. The latter were estimated deriving data from Air Quality Network stations and by applying a machine learning approach. NO2 spatial distribution was estimated at a neighbourhood scale by applying Land Use Random Forest models for the two scenarios. Finally, the impact of lockdown on health was estimated by subtracting attributable deaths for Scenario 1 and those for Scenario 2, both estimated by applying literature-based dose-response function on the counterfactual concentrations of 10 μg/m3.

RESULTS

The Land Use Random Forest models were able to capture 41-42% of the total NO2 variability. Passing from Scenario 2 (annual NO2 without lockdown) to Scenario 1 (annual NO2 with lockdown), the population-weighted exposure to NO2 for Milan and Rome decreased by 15.1% and 15.3% on an annual basis. Considering the 10 μg/m3 counterfactual, prevented deaths were respectively 213 and 604.

CONCLUSIONS

Our results show that the lockdown had a beneficial impact on air quality and human health. However, compliance with the current EU legal limit is not enough to avoid a high number of NO2 attributable deaths. This contribution reaffirms the potentiality of the citizen science approach and calls for more ambitious traffic calming policies and a re-evaluation of the legal annual limit value for NO2 for the protection of human health.

Long-Term Exposure to Low-Level NO2 and Mortality among the Elderly Population in the Southeastern United States

BACKGROUND

Mounting evidence has shown that long-term exposure to fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] and ozone (O3) can increase mortality. However, the health effects associated with long-term exposure to nitrogen dioxide (NO2) are less clear, in particular the evidence is scarce for NO2 at low levels that are below the current international guidelines.

METHODS

We constructed a population-based full cohort comprising all Medicare beneficiaries (aged ≥65, N=13,590,387) in the southeastern United States from 2000 to 2016, and we then further defined the below-guideline cohort that included only those who were always exposed to low-level NO2, that is, with annual means below the current World Health Organization guidelines (i.e., ≤21 ppb). We applied previously estimated spatially and temporally resolved NO2 concentrations and assigned annual means to study participants based on their ZIP code of residence. Cox proportional hazards models were used to examine the association between long-term exposure to low-level NO2 and all-cause mortality, adjusting for potential confounders.

RESULTS

About 71.1% of the Medicare beneficiaries in the southeastern United States were always exposed to low-level NO2 over the study period. We observed an association between long-term exposure to low-level NO2 and all-cause mortality, with a hazard ratio (HR)= 1.042 (95% CI: 1.040, 1.045) in single-pollutant models and a HR= 1.047 (95% CI: 1.045, 1.049) in multipollutant models (adjusting for PM2.5 and O3), per 10-ppb increase in annual NO2 concentrations. The penalized spline indicates a linear exposure-response relationship across the entire NO2 exposure range. Medicare enrollees who were White, female, and residing in urban areas were more vulnerable to long-term NO2 exposure.

CONCLUSION

Using a large and representative cohort, we provide epidemiological evidence that long-term exposure to NO2, even below the national and global ambient air quality guidelines, was approximately linearly associated with a higher risk of mortality among older adults, independent of PM2.5 and O3 exposure. Improving air quality by reducing NO2 emissions, therefore, may yield significant health benefits. https://doi.org/10.1289/EHP9044.

Environment-lockdown, air pollution and related diseases: could we learn something and make it last?

Although the pandemic has caused substantial losses in economic prosperity and human lives, it has also some positive impacts on the environment. Restricted mobility, complete closure, less traffic and industry have led to improved air quality especially in urban settings. Not only is air pollution an important determinant of chronic diseases, such as heart and lung disorders, but it has also been shown that poor air quality increases the risk of COVID-19. In this article, we review some of the findings on changes in air quality during the pandemic, and its potential effects on health. We need to continue to monitor the effects of change in air quality, due to COVID-19 lockdown or other factors, but also keep all our efforts to improve air quality even faster and more persistent, bringing the pollution levels below what WHO recommends are safe to live with.

SARS-CoV-2 Viral Shedding and Transmission Dynamics: Implications of WHO COVID-19 Discharge Guidelines

The evolving nature of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has necessitated periodic revisions of COVID-19 patient treatment and discharge guidelines. Since the identification of the first COVID-19 cases in November 2019, the World Health Organization (WHO) has played a crucial role in tackling the country-level pandemic preparedness and patient management protocols. Among others, the WHO provided a guideline on the clinical management of COVID-19 patients according to which patients can be released from isolation centers on the 10th day following clinical symptom manifestation, with a minimum of 72 additional hours following the resolution of symptoms. However, emerging direct evidence indicating the possibility of viral shedding 14 days after the onset of symptoms called for evaluation of the current WHO discharge recommendations. In this review article, we carried out comprehensive literature analysis of viral shedding with specific focus on the duration of viral shedding and infectivity in asymptomatic and symptomatic (mild, moderate, and severe forms) COVID-19 patients. Our literature search indicates that even though, there are specific instances where the current protocols may not be applicable ( such as in immune-compromised patients there is no strong evidence to contradict the current WHO discharge criteria.

The impacts of COVID-19 lockdown on PM10 and SO2 concentrations and association with human mobility across Turkey

The SARS-CoV-2 virus pandemic (COVID-19) has caused 2.25 million deaths worldwide by February 3, 2021 (JHU, 2021) and still causing severe health and economic disruptions with increasing rates. This study investigates the impact of lockdown measures on ambient air pollution and its association with human mobility in 81 cities of Turkey. We conducted a countrywide analysis using PM₁₀ and SO₂ measurement data by the Turkish Ministry of Environment and Urbanization and mobility data derived from cellular device movement by Google. We observed the most significant change in April 2020. PM₁₀ and SO₂ concentrations were lower in 67% and 59% of the cities, respectively in April 2020 compared to the previous five years (2015-2019). The correlation results show that Restaurant/Café, Transit, and Workplaces mobility is significantly correlated with PM₁₀ and SO₂ concentration levels in Turkey. This study is the first step of a long-term investigation to understand the air quality impacts on population susceptibility to COVID-19.

Individual and social determinants of SARS-CoV-2 testing and positivity in Ontario, Canada: a population-wide study

BACKGROUND

Optimizing the public health response to reduce the burden of COVID-19 necessitates characterizing population-level heterogeneity of risks for the disease. However, heterogeneity in SARS-CoV-2 testing may introduce biased estimates depending on analytic design. We aimed to explore the potential for collider bias in a large study of disease determinants, and evaluate individual, environmental and social determinants associated with SARS-CoV-2 testing and diagnosis among residents of Ontario, Canada.

METHODS

We explored the potential for collider bias and characterized individual, environmental and social determinants of being tested and testing positive for SARS-CoV-2 infection using cross-sectional analyses among 14.7 million community-dwelling people in Ontario, Canada. Among those with a diagnosis, we used separate analytic designs to compare predictors of people testing positive versus negative; symptomatic people testing positive versus testing negative; and people testing positive versus people not testing positive (i.e., testing negative or not being tested). Our analyses included tests conducted between Mar. 1 and June 20, 2020.

RESULTS

Of 14 695 579 people, we found that 758 691 were tested for SARS-CoV-2, of whom 25 030 (3.3%) had a positive test result. The further the odds of testing from the null, the more variability we generally observed in the odds of diagnosis across analytic design, particularly among individual factors. We found that there was less variability in testing by social determinants across analytic designs. Residing in areas with the highest household density (adjusted odds ratio [OR] 1.86, 95% confidence interval [CI] 1.75-1.98), highest proportion of essential workers (adjusted OR 1.58, 95% CI 1.48-1.69), lowest educational attainment (adjusted OR 1.33, 95% CI 1.26-1.41) and highest proportion of recent immigrants (adjusted OR 1.10, 95% CI 1.05-1.15) were consistently related to increased odds of SARS-CoV-2 diagnosis regardless of analytic design.

INTERPRETATION

Where testing is limited, our results suggest that risk factors may be better estimated using population comparators rather than test-negative comparators. Optimizing COVID-19 responses necessitates investment in and sufficient coverage of structural interventions tailored to heterogeneity in social determinants of risk, including household crowding, occupation and structural racism.

An Italian individual-level data study investigating on the association between air pollution exposure and Covid-19 severity in primary-care setting

BACKGROUND

Several studies have been focusing on the potential role of atmospheric pollutants in the diffusion and impact on health of Covid-19. This study's objective was to estimate the association between ≤10 μm diameter particulate matter (PM10) exposure and the likelihood of experiencing pneumonia due to Covid-19 using individual-level data in Italy.

METHODS

Information on Covid-19 patients was retrieved from the Italian IQVIA® Longitudinal Patient Database (LPD), a computerized network of general practitioners (GPs) including anonymous data on patients' consultations and treatments. All patients with a Covid-19 diagnosis during March 18th, 2020 - June 30th, 2020 were included in the study. The date of first Covid-19 registration was the starting point of the 3-month follow-up (Index Date). Patients were classified based on Covid-19-related pneumonia registrations on the Index date and/or during follow-up presence/absence. Each patient was assigned individual exposure by calculating average PM10 during the 30-day period preceding the Index Date, and according to GP's office province. A multiple generalized linear mixed model, mixed-effects logistic regression, was used to assess the association between PM10 exposure tertiles and the likelihood of experiencing pneumonia.

RESULTS

Among 6483 Covid-19 patients included, 1079 (16.6%) had a diagnosis of pneumonia. Pneumonia patients were older, more frequently men, more health-impaired, and had a higher individual-level exposure to PM10 during the month preceding Covid-19 diagnosis. The mixed-effects model showed that patients whose PM10 exposure level fell in the second tertile had a 30% higher likelihood of having pneumonia than that of first tertile patients, and the risk for those who were in the third tertile was almost doubled.

CONCLUSION

The consistent findings toward a positive association between PM10 levels and the likelihood of experiencing pneumonia due to Covid-19 make the implementation of new strategies to reduce air pollution more and more urgent.

Acute and chronic exposure to air pollution in relation with incidence, prevalence, severity and mortality of COVID-19: a rapid systematic review

BACKGROUND

Air pollution is one of the world's leading mortality risk factors contributing to seven million deaths annually. COVID-19 pandemic has claimed about one million deaths in less than a year. However, it is unclear whether exposure to acute and chronic air pollution influences the COVID-19 epidemiologic curve.

METHODS

We searched for relevant studies listed in six electronic databases between December 2019 and September 2020. We applied no language or publication status limits. Studies presented as original articles, studies that assessed risk, incidence, prevalence, or lethality of COVID-19 in relation with exposure to either short-term or long-term exposure to ambient air pollution were included. All patients regardless of age, sex and location diagnosed as having COVID-19 of any severity were taken into consideration. We synthesised results using harvest plots based on effect direction.

RESULTS

Included studies were cross-sectional (n = 10), retrospective cohorts (n = 9), ecological (n = 6 of which two were time-series) and hypothesis (n = 1). Of these studies, 52 and 48% assessed the effect of short-term and long-term pollutant exposure, respectively and one evaluated both. Pollutants mostly studied were PM2.5 (64%), NO2 (50%), PM10 (43%) and O3 (29%) for acute effects and PM2.5 (85%), NO2 (39%) and O3 (23%) then PM10 (15%) for chronic effects. Most assessed COVID-19 outcomes were incidence and mortality rate. Acutely, pollutants independently associated with COVID-19 incidence and mortality were first PM2.5 then PM10, NO2 and O3 (only for incident cases). Chronically, similar relationships were found for PM2.5 and NO2. High overall risk of bias judgments (86 and 39% in short-term and long-term exposure studies, respectively) was predominantly due to a failure to adjust aggregated data for important confounders, and to a lesser extent because of a lack of comparative analysis.

CONCLUSION

The body of evidence indicates that both acute and chronic exposure to air pollution can affect COVID-19 epidemiology. The evidence is unclear for acute exposure due to a higher level of bias in existing studies as compared to moderate evidence with chronic exposure. Public health interventions that help minimize anthropogenic pollutant source and socio-economic injustice/disparities may reduce the planetary threat posed by both COVID-19 and air pollution pandemics.

The impact of outdoor air pollution on COVID-19: a review of evidence from in vitro, animal, and human studies

Studies have pointed out that air pollution may be a contributing factor to the coronavirus disease 2019 (COVID-19) pandemic. However, the specific links between air pollution and severe acute respiratory syndrome-coronavirus-2 infection remain unclear. Here we provide evidence from in vitro, animal and human studies from the existing literature. Epidemiological investigations have related various air pollutants to COVID-19 morbidity and mortality at the population level, however, those studies suffer from several limitations. Air pollution may be linked to an increase in COVID-19 severity and lethality through its impact on chronic diseases, such as cardiopulmonary diseases and diabetes. Experimental studies have shown that exposure to air pollution leads to a decreased immune response, thus facilitating viral penetration and replication. Viruses may persist in air through complex interactions with particles and gases depending on: 1) chemical composition; 2) electric charges of particles; and 3) meteorological conditions such as relative humidity, ultraviolet (UV) radiation and temperature. In addition, by reducing UV radiation, air pollutants may promote viral persistence in air and reduce vitamin D synthesis. Further epidemiological studies are needed to better estimate the impact of air pollution on COVID-19. In vitro and in vivo studies are also strongly needed, in particular to more precisely explore the particle-virus interaction in air.

Impacts of implementing Healthy Building guidelines for daily PM2.5 limit on premature deaths and economic losses in urban China: A population-based modeling study

Given a large fraction of people's exposure to urban PM_2.5 occur indoors, reducing indoor PM_2.5 levels may offer a more feasible and immediate way to save substantial lives and economic losses attributable to PM_2.5 exposure. We aimed to estimate the premature mortality and economic loss reductions associated with achieving the newly established Chinese indoor air guideline and a few hypothetical indoor PM_2.5 guideline values. We used outdoor PM_2.5 concentrations from 1497 monitoring sites in 339 Chinese cities in 2015, coupled with a steady-state mass balance model, to estimate indoor concentrations of outdoor-infiltrated PM_2.5. Using province-specific time-activity patterns for urban residents, we estimated outdoor and indoor exposures to PM_2.5 of outdoor origin. We then proceeded to use localized census-based concentration-response models and the value of statistical life estimates to calculate premature deaths and economic losses attributable to PM_2.5 exposure across urban China. Finally, we estimated potentially avoidable mortality and corresponding economic losses by meeting the current 24-hour based guideline and various hypothetical indoor limits for PM_2.5. In 2015 in urban areas of mainland China, the city-specific annual mean outdoor and indoor PM_2.5 concentrations ranged 9-108 μg/m³ and 5-56 μg/m³, respectively. Indoor exposures contributed 62%-91% daily and 68%-83% annually to the total time-weighted exposures. The potential reductions in total deaths and economic losses for the scenario in which daily indoor concentrations met the current guideline of 75 μg/m³, 37.5 μg/m³, and 25 μg/m³ were 16.9 (95% CI: 0.7-62.1) thousand, 87.7 (95% CI: 9.7-197.7) thousand, and 165.5 (95% CI: 30.8-304.0) thousand, respectively. The corresponding reductions in economic losses were 5.7 (95% CI: 0.2-34.8) billion, 29.4 (95% CI: 2.4-109.6) billion, and 55.2 (95% CI: 7.7-168.0) billion US Dollars, respectively. Deaths and economic losses would be reduced exponentially within the range of 0-75 μg/m³ for hypothetical indoor PM_2.5 limits. The findings demonstrate the effectiveness of reducing indoor concentrations of outdoor-originated PM_2.5 in saving substantial lives and economic losses in China. The analysis provides quantitative evidence to support the implementation of an indoor air quality guideline or standard for PM_2.5.

Initiation of Post-Primary Tuberculosis of the Lungs: Exploring the Secret Role of Bone Marrow Derived Stem Cells

Mycobacterium tuberculosis (Mtb), the causative organism of pulmonary tuberculosis (PTB) now infects more than half of the world population. The efficient transmission strategy of the pathogen includes first remaining dormant inside the infected host, next undergoing reactivation to cause post-primary tuberculosis of the lungs (PPTBL) and then transmit via aerosol to the community. In this review, we are exploring recent findings on the role of bone marrow (BM) stem cell niche in Mtb dormancy and reactivation that may underlie the mechanisms of PPTBL development. We suggest that pathogen's interaction with the stem cell niche may be relevant in potential inflammation induced PPTBL reactivation, which need significant research attention for the future development of novel preventive and therapeutic strategies for PPTBL, especially in a post COVID-19 pandemic world. Finally, we put forward potential animal models to study the stem cell basis of Mtb dormancy and reactivation.

Topic evolution, disruption and resilience in early COVID-19 research

The COVID-19 pandemic presented a challenge to the global research community as scientists rushed to find solutions to the devastating crisis. Drawing expectations from resilience theory, this paper explores how the trajectory of and research community around the coronavirus research was affected by the COVID-19 pandemic. Characterizing epistemic clusters and pathways of knowledge through extracting terms featured in articles in early COVID-19 research, combined with evolutionary pathways and statistical analysis, the results reveal that the pandemic disrupted existing lines of coronavirus research to a large degree. While some communities of coronavirus research are similar pre- and during COVID-19, topics themselves change significantly and there is less cohesion amongst early COVID-19 research compared to that before the pandemic. We find that some lines of research revert to basic research pursued almost a decade earlier, whilst others pursue brand new trajectories. The epidemiology topic is the most resilient among the many subjects related to COVID-19 research. Chinese researchers in particular appear to be driving more novel research approaches in the early months of the pandemic. The findings raise questions about whether shifts are advantageous for global scientific progress, and whether the research community will return to the original equilibrium or reorganize into a different knowledge configuration.

Links between air pollution and COVID-19 in England

In December 2019, a novel disease, coronavirus disease 19 (COVID-19), emerged in Wuhan, People's Republic of China. COVID-19 is caused by a novel coronavirus (SARS-CoV-2) presumed to have jumped species from another mammal to humans. This virus has caused a rapidly spreading global pandemic. To date, over 300,000 cases of COVID-19 have been reported in England and over 40,000 patients have died. While progress has been achieved in managing this disease, the factors in addition to age that affect the severity and mortality of COVID-19 have not been clearly identified. Recent studies of COVID-19 in several countries identified links between air pollution and death rates. Here, we explored potential links between major fossil fuel-related air pollutants and SARS-CoV-2 mortality in England. We compared current SARS-CoV-2 cases and deaths from public databases to both regional and subregional air pollution data monitored at multiple sites across England. After controlling for population density, age and median income, we show positive relationships between air pollutant concentrations, particularly nitrogen oxides, and COVID-19 mortality and infectivity. Using detailed UK Biobank data, we further show that PM_2.5 was a major contributor to COVID-19 cases in England, as an increase of 1 m³ in the long-term average of PM_2.5 was associated with a 12% increase in COVID-19 cases. The relationship between air pollution and COVID-19 withstands variations in the temporal scale of assessments (single-year vs 5-year average) and remains significant after adjusting for socioeconomic, demographic and health-related variables. We conclude that a small increase in air pollution leads to a large increase in the COVID-19 infectivity and mortality rate in England. This study provides a framework to guide both health and emissions policies in countries affected by this pandemic.

Assessing correlations between short-term exposure to atmospheric pollutants and COVID-19 spread in all Italian territorial areas

The spread of SARS-CoV-2, the beta coronavirus responsible for the current pneumonia pandemic outbreak, has been speculated to be linked to short-term and long-term atmospheric pollutants exposure. The present work has been aimed at analyzing the atmospheric pollutants concentrations (PM10, PM2.5, NO2) and spatio-temporal distribution of cases and deaths (specifically incidence, mortality and lethality rates) across the whole Italian national territory, down to the level of each individual territorial area, with the goal of checking any potential short-term correlation between these two phenomena. The data analysis has been limited to the first quarter of 2020 to reduce the lockdown-dependent biased effects on the atmospheric pollutant levels as much as possible. The analysis looked at non-linear, monotonic correlations using the Spearman non-parametric correlation index. The statistical significance of the Spearman correlations has also been evaluated. The results of the statistical analysis suggest the hypothesis of a moderate-to-strong correlation between the number of days exceeding the annual regulatory limits of PM10, PM2.5 and NO2 atmospheric pollutants and COVID-19 incidence, mortality and lethality rates for all the 107 territorial areas in Italy. A weak-to-moderate correlation seems to exist when considering the 36 territorial areas in four of the most affected regions (Lombardy, Piedmont, Emilia-Romagna and Veneto). Overall, PM10 and PM2.5 showed a higher non-linear correlation than NO2 with incidence, mortality and lethality rates. As to particulate matters, PM10 profile has been compared with the incidence rate variation that occurred in three of the most affected territorial areas in Northern Italy (i.e., Milan, Brescia, and Bergamo). All areas showed a similar PM10 time trend but a different incidence rate variation, that was less severe in Milan compared with Brescia and Bergamo.

Reductions in mortality resulting from reduced air pollution levels due to COVID-19 mitigation measures

To control the novel coronavirus disease (COVID-19) outbreak, state and local governments in the United States have implemented several mitigation efforts that resulted in lower emissions of traffic-related air pollutants. This study examined the impacts of COVID-19 mitigation measures on air pollution levels and the subsequent reductions in mortality for urban areas in 10 US states and the District of Columbia. We calculated changes in levels of particulate matter with aerodynamic diameter no larger than 2.5 μm (PM2.5) during mitigation period versus the baseline period (pre-mitigation measure) using the difference-in-difference approach and the estimated avoided total and cause-specific mortality attributable to these changes in PM2.5 by state and district. We found that PM2.5 concentration during the mitigation period decreased for most states (except for 3 states) and the capital. Decreases of average PM2.5 concentration ranged from 0.25 μg/m3 (4.3%) in Maryland to 4.20 μg/m3 (45.1%) in California. On average, PM2.5 levels across 7 states and the capital reduced by 12.8%. We estimated that PM2.5 reduction during the mitigation period lowered air pollution-related total and cause-specific deaths. An estimated 483 (95% CI: 307, 665) PM2.5-related deaths was avoided in the urban areas of California. Our findings have implications for the effects of mitigation efforts and provide insight into the mortality reductions can be achieved from reduced air pollution levels.

Ozone exposure upregulates the expression of host susceptibility protein TMPRSS2 to SARS-CoV-2

Background

SARS-CoV-2, a novel coronavirus, and the etiologic agent for the current global health emergency, causes acute infection of the respiratory tract leading to severe disease and significant mortality. Ever since the start of SARS-CoV-2, also known as COVID-19 pandemic, countless uncertainties have been revolving around the pathogenesis and epidemiology of the SARS-CoV-2 infection. While air pollution has been shown to be strongly correlated to increased SARS-CoV-2 morbidity and mortality, whether environmental pollutants such as ground level ozone affects the susceptibility of individuals to SARS-CoV-2 is not yet established.

Objective

To investigate the impact of ozone inhalation on the expression levels of signatures associated with host susceptibility to SARS-CoV-2.

Methods

We analyzed lung tissues collected from mice that were sub-chronically exposed to air or 0.8ppm ozone for three weeks (4h/night, 5 nights/week), and analyzed the expression of signatures associated with host susceptibility to SARS-CoV-2.

Results

SARS-CoV-2 entry into the host cells requires proteolytic priming by the host-derived protease, transmembrane protease serine 2 (TMPRSS2). The TMPRSS2 protein and Tmprss2 transcripts were significantly elevated in the extrapulmonary airways, parenchyma, and alveolar macrophages from ozone-exposed mice. A significant proportion of additional known SARS-CoV-2 host susceptibility genes were upregulated in alveolar macrophages and parenchyma from ozone-exposed mice.

Conclusions

Our data indicate that the unhealthy levels of ozone in the environment may predispose individuals to severe SARS-CoV-2 infection. Given the severity of this pandemic, and the challenges associated with direct testing of host-environment interactions in clinical settings, we believe that this mice-ozone-exposure based study informs the scientific community of the potentially detrimental effects of the ambient ozone levels determining the host susceptibility to SARS-CoV-2.

The "Elderly" Lesson in a "Stressful" Life: Italian Holistic Approach to Increase COVID-19 Prevention and Awareness

It's a frightening time due to COVID-19, but the great elderly/centenarians, apparently with more frailty, seem to have a better response to the pandemic. "The South Italy" lifestyle seems an "effective strategy" promoting the well-being embedded in a holistic solution: healthy diet, less exposure to PM10 pollution, protected environment, and moderate physical activity. The European FP7 Project RISTOMED results, since 2010, have shown that dietary intervention improved a heathy status in the elderly people. Based on the RISTOMED results, in addition to sociocultural and environmental factors, the authors suggest an integrated approach for resilience to COVID-19. Such an approach during the next months could make the difference for the success of any government progress policy to fight COVID-19, finalizing long-term well-being and successful aging.

Bad Air Can Also Kill: Residential Indoor Air Quality and Pollutant Exposure Risk during the COVID-19 Crisis

During the first outbreak of the SARS-CoV-2 pandemic the population, focusing primarily on the risk of infection, was generally inattentive to the quality of indoor air. Spain, and the city of Madrid in particular, were among the world's coronavirus hotspots. The country's entire population was subject to a 24/7 lockdown for 45 days. This paper describes a comparative longitudinal survey of air quality in four types of housing in the city of Madrid before and during lockdown. The paper analysed indoor temperatures and variations in CO2, 2.5 μm particulate matter (PM2.5) and total volatile organic compound (TVOC) concentrations before and during lockdown. The mean daily outdoor PM2.5 concentration declined from 11.04 µg/m3 before to 7.10 µg/m3 during lockdown. Before lockdown the NO2 concentration values scored as 'very good' 46% of the time, compared to 90.9% during that period. Although the city's outdoor air quality improved, during lockdown the population's exposure to indoor pollutants was generally more acute and prolonged. Due primarily to concern over domestic energy savings, the lack of suitable ventilation and more intensive use of cleaning products and disinfectants during the covid-19 crisis, indoor pollutant levels were typically higher than compatible with healthy environments. Mean daily PM2.5 concentration rose by approximately 12% and mean TVOC concentration by 37% to 559%. The paper also puts forward a series of recommendations to improve indoor domestic environments in future pandemics and spells out urgent action to be taken around indoor air quality (IAQ) in the event of total or partial quarantining to protect residents from respiratory ailments and concomitantly enhanced susceptibility to SARS-CoV-2, as identified by international medical research.

Long-term exposure to air-pollution and COVID-19 mortality in England: a hierarchical spatial analysis

BACKGROUND

Recent studies suggested a link between long-term exposure to air-pollution and COVID-19 mortality. However, due to their ecological design, based on large spatial units, they neglect the strong localised air-pollution patterns, and potentially lead to inadequate confounding adjustment. We investigated the effect of long-term exposure to NO2 and PM2.5 on COVID-19 deaths up to June 30, 2020 in England using high geographical resolution.

METHODS

We included 38 573 COVID-19 deaths up to June 30, 2020 at the Lower Layer Super Output Area level in England (n=32 844 small areas). We retrieved averaged NO2 and PM2.5 concentration during 2014-2018 from the Pollution Climate Mapping. We used Bayesian hierarchical models to quantify the effect of air-pollution while adjusting for a series of confounding and spatial autocorrelation.

FINDINGS

We find a 0.5% (95% credible interval: -0.2%-1.2%) and 1.4% (-2.1%-5.1%) increase in COVID-19 mortality rate for every 1μg/m3 increase in NO2 and PM2.5 respectively, after adjusting for confounding and spatial autocorrelation. This corresponds to a posterior probability of a positive effect of 0.93 and 0.78 respectively. The spatial relative risk at LSOA level revealed strong patterns, similar for the different pollutants. This potentially captures the spread of the disease during the first wave of the epidemic.

INTERPRETATION

Our study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2.5 remains more uncertain.

FUNDING

Medical Research Council, Wellcome Trust, Environmental Protection Agency and National Institutes of Health.

Go slow to go fast: a plea for sustained scientific rigour in air pollution research during the COVID-19 pandemic

Researchers in the air pollution field are well aware that indoor and outdoor air pollution is associated with multiple disorders, including an increase in respiratory infection-related morbidity and mortality [1, 2]. Investigating associations linking air pollution and coronavirus disease 2019 (COVID-19) spread and prognosis of respiratory disease in COVID-19 patients is therefore timely, relevant and plausible. Over a 10-day period, three papers involving original research associating COVID-19 mortality and air pollution were published [3–5]. These publications attracted considerable attention from international news outlets and on social media [6, 7].

Present studies on the role of air pollution and COVID-19 spread, and the prognosis in patients, do not fulfil quality criteria and are not sufficiently informative https://bit.ly/3hGjd73