The association between COVID-19 deaths and short-term ambient air pollution/meteorological condition exposure: a retrospective study from Wuhan, China

Impact of short-term exposure to ambient air pollutants and meteorological factors on COVID-19 incidence and mortality: A retrospective study from Dammam, Saudi Arabia

The symptoms of COVID-19 included fever with or without respiratory syndrome, but patients subsequently developed pulmonary abnormalities. Exposure to air pollution, meanwhile, is associated with complications such as acute respiratory inflammations, asthma attack, and deaths from cardiorespiratory disease. To analyze the association of the air quality index (AQI), ambient air pollutants (PM10, SO2 and O3) and meteorological parameters (temperature and relative humidity [RH]) with COVID-19 incidence and mortality, a retrospective study was conducted to examine COVID-19 infection, meteorological parameters, ambient air quality and ambient air pollutants in Dammam from 1 January to 30 April 2021. Data of COVID-19 incidence and mortality for Dammam were retrieved from Saudi Arabia Ministry of Health's publicly accessible database. Meteorological data, AQI and average PM10, SO2 and O3 values were extracted from the publicly available website of Ministry of Environment, Water and Agriculture. The correlation of COVID-19 incidence and mortality with the independent variables was analysed by Pearson's correlation test or Spearman's rho test as applicable, and a p-value less than 0.05 was considered significant. COVID-19 incidence exhibited a positive correlation with temperature (r = 0.537, p = .0001) and a negative correlation with RH (r=-0.487, p=.0001). No correlation was observed between the meteorological variables and COVID-19 mortality. COVID-19 incidence showed a positive correlation with AQI (r=0.269, p=.015) and with the ambient air pollutants SO2 and O3 (r=0.258, p=.018), and COVID-19 mortality showed a positive correlation with PM10 (r s  = 0.344, p=.002). Short-term exposure to O3, SO2 and higher temperature had direct relationship with COVID-19 incidence, while RH had inverse relationship. PM10 is positively associated with COVID-19 mortality.

The Lag -Effects of Air Pollutants and Meteorological Factors on COVID-19 Infection Transmission and Severity: Using Machine Learning Techniques

BACKGROUND

Exposure to air pollution is a major health problem worldwide. This study aimed to investigate the effect of the level of air pollutants and meteorological parameters with their related lag time on the transmission and severity of coronavirus disease 19 (COVID-19) using machine learning (ML) techniques in Shiraz, Iran. Study Design: An ecological study.

METHODS

In this ecological research, three main ML techniques, including decision trees, random forest, and extreme gradient boosting (XGBoost), have been applied to correlate meteorological parameters and air pollutants with infection transmission, hospitalization, and death due to COVID-19 from 1 October 2020 to 1 March 2022. These parameters and pollutants included particulate matter (PM2), sulfur dioxide (SO2 ), nitrogen dioxide (NO2 ), nitric oxide (NO), ozone (O3 ), carbon monoxide (CO), temperature (T), relative humidity (RH), dew point (DP), air pressure (AP), and wind speed (WS).

RESULTS

Based on the three ML techniques, NO2 (lag 5 day), CO (lag 4), and T (lag 25) were the most important environmental features affecting the spread of COVID-19 infection. In addition, the most important features contributing to hospitalization due to COVID-19 included RH (lag 28), T (lag 11), and O3 (lag 10). After adjusting for the number of infections, the most important features affecting the number of deaths caused by COVID-19 were NO2 (lag 20), O3 (lag 22), and NO (lag 23).

CONCLUSION

Our findings suggested that epidemics caused by COVID-19 and (possibly) similarly viral transmitted infections, including flu, air pollutants, and meteorological parameters, can be used to predict their burden on the community and health system. In addition, meteorological and air quality data should be included in preventive measures.

Observational studies generate misleading results about the health effects of air pollution: Evidence from chronic air pollution and COVID-19 outcomes

Several observational studies from locations around the globe have documented a positive correlation between air pollution and the severity of COVID-19 disease. Observational studies cannot identify the causal link between air quality and the severity of COVID-19 outcomes, and these studies face three key identification challenges: 1) air pollution is not randomly distributed across geographies; 2) air-quality monitoring networks are sparse spatially; and 3) defensive behaviors to mediate exposure to air pollution and COVID-19 are not equally available to all, leading to large measurement error bias when using rate-based COVID-19 outcome measures (e.g., incidence rate or mortality rate). Using a quasi-experimental design, we explore whether traffic-related air pollutants cause people with COVID-19 to suffer more extreme health outcomes in New York City (NYC). When we address the previously overlooked challenges to identification, we do not detect causal impacts of increased chronic concentrations of traffic-related air pollutants on COVID-19 death or hospitalization counts in NYC census tracts.

Environmental factors are associated to hospital outcomes in COVID-19 patients during lockdown and post-lockdown in 2020: A nationwide study

OBJECTIVE

This study analyzed, at a postcode detailed level, the relation-ship between short-term exposure to environmental factors and hospital ad-missions, in-hospital mortality, ICU admission, and ICU mortality due to COVID-19 during the lockdown and post-lockdown 2020 period in Spain.

METHODS

We performed a nationwide population-based retrospective study on 208,744 patients admitted to Spanish hospitals due to COVID-19 based on the Minimum Basic Data Set (MBDS) during the first two waves of the pandemic in 2020. Environmental data were obtained from Copernicus Atmosphere Monitoring Service. The association was assessed by a generalized additive model.

RESULTS

PM2.5 was the most critical environmental factor related to hospital admissions and hospital mortality due to COVID-19 during the lockdown in Spain, PM10, NO2, and SO2and also showed associations. The effect was considerably reduced during the post-lockdown period. ICU admissions in COVID-19 patients were mainly associated with PM2.5, PM10, NO2, and SO2 during the lockdown as well. During the lockdown, exposure to PM2.5 and PM10 were the most critical environmental factors related to ICU mortality in COVID-19.

CONCLUSION

Short-term exposure to air pollutants impacts COVID-19 out-comes during the lockdown, especially PM2.5, PM10, NO2, and SO2. These pollutants are associated with hospital admission, hospital mortality and ICU admission, while ICU mortality is mainly associated with PM2.5 and PM10. Our findings reveal the importance of monitoring air pollutants in respiratory infectious diseases.

A Literature Review of the Effects of Air Pollution on COVID-19 Health Outcomes Worldwide: Statistical Challenges and Data Visualization

Several peer-reviewed papers and reviews have examined the relationship between exposure to air pollution and COVID-19 spread and severity. However, many of the existing reviews on this topic do not extensively present the statistical challenges associated with this field, do not provide comprehensive guidelines for future researchers, and review only the results of a relatively small number of papers. We reviewed 139 papers, 127 of which reported a statistically significant positive association between air pollution and adverse COVID-19 health outcomes. Here, we summarize the evidence, describe the statistical challenges, and make recommendations for future research. To summarize the 139 papers with data from geographical locations around the world, we also present anopen-source data visualization tool that summarizes these studies and allows the research community to contribute evidence as new research papers are published.

Air pollution and respiratory infections: the past, present, and future

Air pollution levels across the globe continue to rise despite government regulations. The increase in global air pollution levels drives detrimental human health effects, including 7 million premature deaths every year. Many of these deaths are attributable to increased incidence of respiratory infections. Considering the COVID-19 pandemic, an unprecedented public health crisis that has claimed the lives of over 6.5 million people globally, respiratory infections as a driver of human mortality is a pressing concern. Therefore, it is more important than ever to understand the relationship between air pollution and respiratory infections so that public health measures can be implemented to ameliorate further morbidity and mortality. This article aims to review the current epidemiologic and basic science research on interactions between air pollution exposure and respiratory infections. The first section will present epidemiologic studies organized by pathogen, followed by a review of basic science research investigating the mechanisms of infection, and then conclude with a discussion of areas that require future investigation.

What are the Effects of Climate Variables on COVID-19 Pandemic? A Systematic Review and Current Update

The climatological parameters can be different in various geographical locations. Moreover, they have possible impacts on COVID-19 incidence. Therefore, the purpose of this systematic review article was to describe the effects of climatic variables on COVID-19 pandemic in different countries. Systematic literature search was performed in Scopus, ISI Web of Science, and PubMed databases using ("Climate" OR "Climate Change" OR "Global Warming" OR "Global Climate Change" OR "Meteorological Parameters" OR "Temperature" OR "Precipitation" OR "Relative Humidity" OR "Wind Speed" OR "Sunshine" OR "Climate Extremes" OR "Weather Extremes") AND ("COVID" OR "Coronavirus disease 2019" OR "COVID-19" OR "SARS-CoV-2" OR "Novel Coronavirus") keywords. From 5229 articles, 424 were screened and 149 were selected for further analysis. The relationship between meteorological parameters is variable in different geographical locations. The results indicate that among the climatic indicators, the temperature is the most significant factor that influences on COVID-19 pandemic in most countries. Some studies were proved that warm and wet climates can decrease COVID-19 incidence; however, the other studies represented that warm location can be a high risk of COVID-19 incidence. It could be suggested that all climate variables such as temperature, humidity, rainfall, precipitation, solar radiation, ultraviolet index, and wind speed could cause spread of COVID-19. Thus, it is recommended that future studies will survey the role of all meteorological variables and interaction between them on COVID-19 spread in specific small areas such as cities of each country and comparison between them.

Correlation between UV Index, Temperature and Humidity with Respect to Incidence and Severity of COVID 19 in Spain

BACKGROUND

Various studies support the inverse correlation between solar exposure and Coronavirus SARS-CoV-2 infection. In Spain, from the Canary Islands to the northern part of the country, the global incidence of COVID-19 is different depending on latitude, which could be related to different meteorological conditions such as temperature, humidity, and ultraviolet index (UVI). The objective of the present work was to analyze the association between UVI, other relevant environmental factors such as temperature and humidity, and the incidence, severity, and mortality of COVID-19 at different latitudes in Spain.

METHODS

An observational prospective study was conducted, recording the numbers of new cases, hospitalizations, patients in critical units, mortality rates, and annual variations related to UVI, temperature, and humidity in five different provinces of Spain from January 2020 to February 2021.

RESULTS

Statistically significant inverse correlations (Spearman coefficients) were observed between UVI, temperature, annual changes, and the incidence of COVID-19 cases at almost all latitudes.

CONCLUSION

Higher ultraviolet radiation levels and mean temperatures could contribute to reducing COVID-19 incidence, hospitalizations, and mortality.

Air pollution attributed disease burden and economic growth in India: Estimating trends and inequality between states

Background

Air pollution is one of the major contributors to the disease burden in India after malnutrition. We examined the relation, and state-wise disparities in air pollution attributed to disease burden (APADB) concerning gross state domestic product (GSDP) and growth in motor vehicles in India.

Methods

We retrieved disability-adjusted life year (DALY) estimates for India due to air pollution from the Global Burden of Disease Studies, injuries, and Risk Factors Study (GBD). We examined the association between APADB with GSDP and the growth in the number of registered motor vehicles in India during the 2011 to 2019 period. Concentration indices and Lorenz curves were used to explore the variation in APADB across individual states.

Findings

Except for a few states, APADB is inversely proportional to GSDP. Growth in motor vehicles was also negatively correlated with the APADB in n=19 states. The concentration index explained a 47% inequality in APADB between individual states and exhibited a decline (45%) during 2019 compared to 2011. The unevenness in APADB among Indian states is evident from the analysis as the states occupying the 6^th or 7^th decile and above in terms of GDP, urbanization and population contribute more than 60 per cent of the total APADB.

Interpretation

The APADB is inversely correlated with GSDP for most of the states, and the negative correlations were conspicuous when APADB per 100,000 population was analysed. The concentration index and Lorenz revealed the presence of APADB inequality between states in terms of GSDP, population, urbanisation, and total factories.

Funding

Not applicable.

Ambient air pollution and COVID-19 in Delhi, India: a time-series evidence

This study aimed to explore the short-term health effects of ambient air pollutants PM2.5, PM10, SO2, NO2, O3, and CO on COVID-19 daily new cases and COVID-19 daily new deaths. A time-series design used in this study. Data were obtained from 1 April 2020 to 31 December 2020 in the National Capital Territory (NCT) of Delhi, India. The generalized additive models (GAMs) were applied to explore the associations of six air pollutants with COVID-19 daily new cases and COVID-19 daily new deaths. The GAMs revealed statistically significant associations of ambient air pollutants with COVID-19 daily new cases and COVID-19 daily new deaths. These findings suggest that governments need to give greater considerations to regions with higher concentrations of PM2.5, PM10, SO2, NO2, O3, and CO, since these areas may experience a more serious COVID-19 pandemic or, in general, any respiratory disease.

Impact of Different Air Pollutants (PM10, PM2.5, NO2, and Bacterial Aerosols) on COVID-19 Cases in Gliwice, Southern Poland

Many studies have shown that air pollution may be closely associated with increased morbidity and mortality due to COVID-19. It has been observed that exposure to air pollution leads to reduced immune response, thereby facilitating viral penetration and replication. In our study, we combined information on confirmed COVID-19 daily new cases (DNCs) in one of the most polluted regions in the European Union (EU) with air-quality monitoring data, including meteorological parameters (temperature, relative humidity, atmospheric pressure, wind speed, and direction) and concentrations of particulate matter (PM₁₀ and PM_2.5), sulfur dioxide (SO₂), nitrogen oxides (NO and NO₂), ozone (O₃), and carbon monoxide (CO). Additionally, the relationship between bacterial aerosol (BA) concentration and COVID-19 spread was analyzed. We confirmed a significant positive correlation (p < 0.05) between NO₂ concentrations and numbers of confirmed DNCs and observed positive correlations (p < 0.05) between BA concentrations and DNCs, which may point to coronavirus air transmission by surface deposits on bioaerosol particles. In addition, wind direction information was used to show that the highest numbers of DNCs were associated with the dominant wind directions in the region (southern and southwestern parts).

Did unprecedented air pollution levels cause spike in Delhi's COVID cases during second wave?

The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM2.5: 67 µg m-3 (lockdown) versus 81 µg m-3 (pre-lockdown); PM10: 171 µg m-3 versus 235 µg m-3; CO: 0.9 mg m-3 versus 1.1 mg m-3) except ozone which increased during the lockdown period (57 µg m-3 versus 39 µg m-3). The variation in pollutant concentrations revealed that PM2.5, PM10 and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.

A Spatiotemporal Analytical Outlook of the Exposure to Air Pollution and COVID-19 Mortality in the USA

The world is experiencing a pandemic due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), also known as COVID-19. The USA is also suffering from a catastrophic death toll from COVID-19. Several studies are providing preliminary evidence that short- and long-term exposure to air pollution might increase the severity of COVID-19 outcomes, including a higher risk of death. In this study, we develop a spatiotemporal model to estimate the association between exposure to fine particulate matter PM2.5 and mortality accounting for several social and environmental factors. More specifically, we implement a Bayesian zero-inflated negative binomial regression model with random effects that vary in time and space. Our goal is to estimate the association between air pollution and mortality accounting for the spatiotemporal variability that remained unexplained by the measured confounders. We applied our model to four regions of the USA with weekly data available for each county within each region. We analyze the data separately for each region because each region shows a different disease spread pattern. We found a positive association between long-term exposure to PM2.5 and the mortality from the COVID-19 disease for all four regions with three of four being statistically significant. Data and code are available at our GitHub repository. Supplementary materials accompanying this paper appear on-line.

Assessing the impact of temperature and humidity exposures during early infection stages on case-fatality of COVID-19: A modelling study in Europe

Background Although associations between key weather indicators (i.e. temperature and humidity) and COVID-19 mortality have been reported, the relationship between these exposures at different timings in early infection stages (from virus exposure up to a few days after symptom onset) and the probability of death after infection (also called case fatality rate, CFR) has yet to be determined. Methods We estimated the instantaneous CFR of eight European countries using Bayesian inference in conjunction with stochastic transmission models, taking account of delays in reporting the number of newly confirmed cases and deaths. The exposure-lag-response associations between fatality rate and weather conditions to which patients were exposed at different timings were obtained using distributed lag nonlinear models coupled with mixed-effect models. Results Our results show that the Odds Ratio (OR) of death is negatively associated with the temperature, with two maxima (OR = 1.29 (95% CI: 1.23, 1.35) at -0.1°C; OR = 1.12 (95% CI: 1.08, 1.16) at 0.1°C) occurring at the time of virus exposure and after symptom onset. Two minima (OR = 0.81 (95% CI: 0.71, 0.92) at 23.2°C; OR = 0.71 (95% CI: 0.63, 0.80) at 21.7°C) also occurred at these two distinct periods correspondingly. Low humidity (below 50%) during the early stages and high humidity (approximately 89%) after symptom onset were related to the lower fatality. Conclusion Environmental conditions may affect not only the initial viral load when patients are exposed to the virus, but also individuals' immune response around symptom onset. Warmer temperatures and higher humidity after symptom onset were linked to lower fatality.

Air pollution and COVID-19 mortality and hospitalization: An ecological study in Iran

Exposure to air pollution can exacerbate the severe COVID-19 conditions, subsequently causing an increase in the death rate. In this study, we investigated the association between long-term exposure to air pollution and risks of COVID-19 hospitalization and mortality in Arak, Iran. Air pollution data was obtained from air quality monitoring stations located in Arak, including particulate matter (PM), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃) and carbon monoxide (CO). Daily numbers of Covid-19 cases including hospital admissions (hospitalization) and deaths (mortality) were obtained from a national data registry recorded by Arak University of Medical Sciences. A Poisson regression model with natural spline functions was applied to set the effects of air pollution on COVID-19 hospitalization and mortality. The percent change of COVID-19 hospitalization per 10 μg/m³ increase in PM_2.5 and PM₁₀ were 8.5% (95% CI 7.6 to 11.5) and 4.8% (95% CI 3 to 6.5), respectively. An increase of 10 μg/m³ in PM_2.5 resulting in 5.6% (95% CI: 3.1-8.3%) increase in COVID-19 mortality. The percent change of hospitalization (7.7%, 95% CI 2.2 to 13.3) and mortality (4.5%, 95% CI 0.3 to 9.5) were positively significant per one ppb increment in SO₂, while NO₂, O₃ and CO were inversely associated with hospitalization and mortality. Our findings strongly suggesting that a small increase in long-term exposure to PM_2.5, PM₁₀ and SO2 elevating risks of hospitalization and mortality related to COVID-19.

County-Level Assessment of Vulnerability to COVID-19 in Alabama

The COVID-19 pandemic has posed an unprecedented challenge to public health across the world and has further exposed health disparities and the vulnerability of marginal groups. Since the pandemic has exhibited marked regional differences, it is necessary to better understand the levels of vulnerability to the disease at local levels and provide policymakers with additional tools that will allow them to develop finely targeted policies. In this study, we develop for the State of Alabama (USA) a composite vulnerability index at county level that can be used as a tool that will help in the management of the pandemic. Twenty-four indicators were assigned to the following three categories: exposure, sensitivity, and adaptive capacity. The resulting subindices were aggregated into a composite index that depicts the vulnerability to COVID-19. A multivariate analysis was used to assign factor loadings and weights to indicators, and the results were mapped using Geographic Information Systems. The vulnerability index captured health disparities very well. Many of the most vulnerable counties were found in the Alabama Black Belt region. A deconstruction of the overall index and subindices allowed the development of individual county profiles and the detection of local strengths and weaknesses. We expect the model developed in this study to be an efficient planning tool for decision-makers.

Assessment of the association between dust storms and COVID-19 infection rate in southwest Iran

This study assesses a plausible correlation between a dust intrusion episode and a daily increase in COVID-19 cases. A surge in COVID-19 cases was observed a few days after a Middle East Dust (MED) event that peaked on 25th April 2020 in southwest Iran. To investigate potential causal factors for the spike in number of cases, cross-correlations between daily combined aerosol optical depths (AODs) and confirmed cases were computed for Khuzestan, Iran. Additionally, atmospheric stability data time series were assessed by covering before, during, and after dust intrusion, producing four statistically clustered distinct city groups. Groups 1 and 2 had different peak lag times of 10 and 4-5 days, respectively. Since there were statistically significant associations between AOD levels and confirmed cases in both groups, dust incursion may have increased population susceptibility to COVID-19 disease. Group 3 was utilized as a control group with neither a significant level of dust incursion during the episodic period nor any significant associations. Group 4 cities, which experienced high dust incursion levels, showed no significant correlation with confirmed case count increases. Random Forest Analysis assessed the influence of wind speed and AOD, showing relative importance of 0.31 and 0.23 on the daily increase percent of confirmed cases, respectively. This study may serve as a reference for better understanding and predicting factors affecting COVID-19 transmission and diffusion routes, focusing on the role of MED intrusions.

Modeling of the air temperature using the Extreme Value Theory for selected biomes in Mato Grosso do Sul (Brazil)

This paper aims to find probabilities of extreme values of the air temperature for the Cerrado, Pantanal and Atlantic Forest biomes in Mato Grosso do Sul in Brazil. In this case a maximum likelihood estimation was employed for the probability distributions fitting the extreme monthly air temperatures for 2007-2018. Using the Extreme Value Theory approach this work estimates three probability distributions: the Generalized Distribution of Extreme Values (GEV), the Gumbel (GUM) and the Log-Normal (LN). The Kolmogorov-Smirnov test, the corrected Akaike criterion AIC c , the Bayesian information criterion BIC, the root of the mean square error RMSE and the determination coefficient R 2 were applied to measure the goodness-of-fit. The estimated distributions were used to calculate the probabilities of occurrence of maximum monthly air temperatures over 28-32 °C. Temperature predictions were done for the 2-, 5-, 10-, 30-, 50- and 100-year return periods. The GEV and GUM distributions are recommended to be used in the warmer months. In the coldest months, the LN distribution gave a better fit to a series of extreme air temperatures. Deforestation, combustion and extensive fires, and the related aerosol emissions contribute, alongside climate change, to the generation of extreme air temperatures in the studied biomes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00477-022-02206-1.

Impacts of air pollution on COVID-19 case fatality rate: a global analysis

The coronavirus disease 2019 (COVID-19) pandemic is still rapidly spreading globally. To probe high-risk cities and the impacts of air pollution on public health, this study explores the relationship between the long-term average concentration of air pollution and the city-level case fatality rate (CFR) of COVID-19 globally. Then, geographically weighted regression (GWR) is applied to examine the spatial variability of the relationships. Six air pollution factors, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), PM_2.5 (particles with diameter ≤2.5 μm), PM₁₀ (particles with diameter ≤10 μm), and air quality index (AQI), are positively associated with the city-level COVID-19 CFR. Our results indicate that a 1-unit increase in NO₂ (part per billion, PPB), SO₂ (PPB), O₃ (PPB), PM_2.5 (microgram per cubic meter, μg/m³), PM₁₀ (μg/m³), AQI (score), is related to a 1.450%, 1.005%, 0.992%, 0.860%, 0.568%, and 0.776% increase in the city-level COVID-19 CFR, respectively. Additionally, the effects of NO₂, O₃, PM_2.5, AQI, and probability of living with poor AQI on COVID-19 spatially vary in view of the estimation of the GWR. In other words, the adverse impacts of air pollution on health are different among the cities. In summary, long-term exposure to air pollution is negatively related to the COVID-19 health outcome, and the relationship is spatially non-stationary. Our research sheds light on the impacts of slashing air pollution on public health in the COVID-19 pandemic to help governments formulate air pollution policies in light of the local situations.

Air pollution impact on the Covid-19 mortality in Iran considering the comorbidity (obesity, diabetes, and hypertension) correlations

Since the rise of the Covid-19 pandemic, several researchers stated the possibility of a positive relationship between Covid-19 spread and climatic parameters. An ecological study in 12 Iranian cities using the report of daily deaths from Covid-19 (March to August 2020) and validated data on air pollutants, considering average concentrations in each city in the last year used to analyze the association between chronic exposure to air pollutants and the death rate from Covid-19 in Iran. Poisson regression models were used, with generalized additive models and adjustment variables. A significant increase of 2.7% (IC(95%) 2.6-4.4) was found in the mortality rate due to Covid-19 due to an increase of 1 μg/m³ of NO₂. The results suggest an association between Covid-19 mortality and NO₂ exposure. As a risk approximation associated with air pollution, more precise analysis is done. The results also show a good consistency with studies from other regions; this paper's results can be useful for the public health policymakers and decision-making to control the Covid-19 spread.

Ambient air pollution and COVID-19 risk: Evidence from 35 observational studies

BACKGROUND AND AIMS

The coronavirus disease 2019 (COVID-19) pandemic is severely threatening and challenging public health worldwide. Epidemiological studies focused on the influence of outdoor air pollution (AP) on COVID-19 risk have produced inconsistent conclusions. We aimed to quantitatively explore this association using a meta-analysis.

METHODS

We searched for studies related to outdoor AP and COVID-19 risk in the Embase, PubMed, and Web of Science databases. No language restriction was utilized. The search date entries were up to August 13, 2021. Pooled estimates and 95% confidence intervals (CIs) were obtained with random-/fixed-effects models. PROSPERO registration number: CRD42021244656.

RESULTS

A total of 35 articles were eligible for the meta-analysis. For long-term exposure to AP, COVID-19 incidence was positively associated with 1 μg/m3 increase in nitrogen dioxide (NO2; effect size = 1.042, 95% CI 1.017-1.068), particulate matter with diameter <2.5 μm (PM2.5; effect size = 1.056, 95% CI 1.039-1.072), and sulfur dioxide (SO2; effect size = 1.071, 95% CI 1.002-1.145). The COVID-19 mortality was positively associated with 1 μg/m3 increase in nitrogen dioxide (NO2; effect size = 1.034, 95% CI 1.006-1.063), PM2.5 (effect size = 1.047, 95% CI 1.025-1.1071). For short-term exposure to air pollutants, COVID-19 incidence was positively associated with 1 unit increase in air quality index (effect size = 1.001, 95% CI 1.001-1.002), 1 μg/m3 increase NO2 (effect size = 1.014, 95% CI 1.011-1.016), particulate matter with diameter <10 μm (PM10; effect size = 1.005, 95% CI 1.003-1.008), PM2.5 (effect size = 1.003, 95% CI 1.002-1.004), and SO2 (effect size = 1.015, 95% CI 1.007-1.023).

CONCLUSIONS

Outdoor air pollutants are detrimental factors to COVID-19 outcomes. Measurements beneficial to reducing pollutant levels might also reduce the burden of the pandemic.

Implications of COVID-19 on global environmental pollution and carbon emissions with strategies for sustainability in the COVID-19 era

The impacts of COVID-19 on global environmental pollution since its onset in December 2019 require special attention. The rapid spread of COVID-19 globally has led countries to lock down cities, restrict traffic travel and impose strict safety measures, all of which have implications on the environment. This review aims to systematically and comprehensively present and analyze the positive and negative impacts of COVID-19 on global environmental pollution and carbon emissions. It also aims to propose strategies to prolong the beneficial, while minimize the adverse environmental impacts of COVID-19. It systematically and comprehensively reviewed more than 100 peer-reviewed papers and publications related to the impacts of COVID-19 on air, water and soil pollution, carbon emissions as well as the sustainable strategies forward. It revealed that PM2.5, PM10, NO2, and CO levels reduced in most regions globally but SO2 and O3 levels increased or did not show significant changes. Surface water, coastal water and groundwater quality improved globally during COVID-19 lockdown except few reservoirs and coastal areas. Soil contamination worsened mainly due to waste from the use of personal protective equipment particularly masks and the packaging, besides household waste. Carbon emissions were reduced primarily due to travel restrictions and less usage of utilities though emissions from certain ships did not change significantly to maintain supply of the essentials. Sustainable strategies post-COVID-19 include the development and adoption of nanomaterial adsorption and microbial remediation technologies, integrated waste management measures, "sterilization wave" technology and energy-efficient technologies. This review provides important insight and novel coverage of the environmental implications of COVID-19 in more than 25 countries across different global regions to permit formulation of specific pollution control and sustainability strategies in the COVID-19 and post-COVID-19 eras for better environmental quality and human health.

Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China

Ambient concentrations of volatile organic compounds (VOCs) vary with emission rates, meteorology, and chemistry. Conventional positive matrix factorization (PMF) loses information because of dilution variations and chemical losses. Multiply improved PMF incorporates the ventilation coefficient, and total solar radiation or oxidants to reduce the effects of dispersion and chemical loss. These methods were applied to hourly speciated VOC data from November 2019 to March 2020 including during the COVID-19 shutdown. Various comparisons were made to assess the influences of these fluctuation drivers by time of day. Dispersion normalized PMF (DN-PMF) reduced the dispersion variations. Dispersion-radiation normalized PMF (DRN-PMF) reduced the impact of chemical loss, especially at night, which was better than Dispersion-O_x normalized PMF (DON-PMF). The conditional bivariate probability function (CBPF) plots of DRN-PMF results were consist with actual source locations. The DN-PMF, DRN-PMF, and DON-PMF results were consistent between 10:00 and 15:00, suggesting dispersion was significantly more influential than photochemical reactions during these times. The DRN-PMF results indicated that the highest VOC contributors during the COVID-19 shutdown were liquefied petroleum gas (LPG) (28.8%), natural gas (25.2%), and pulverized coal boilers emissions (19.6%). Except for petrochemical-related enterprises and LPG, the contribution concentrations of all other sources decreased substantially during the COVID-19 shutdown, by 94.7%, 90.6%, and 86.8% for vehicle emissions, gasoline evaporation, and the mixed source of diesel evaporation and solvent use, respectively. Controlling the use of motor vehicles and related volatilization of diesel fuel and gasoline can be effective in controlling VOCs in the future.

Evaluation of the combined effect of mobility and seasonality on the COVID-19 pandemic: a Lombardy-based study

Restrictions to human mobility had a significant role in limiting SARS-CoV-2 spread. It has been suggested that seasonality might affect viral transmissibility. Our study retrospectively investigates the combined effect that seasonal environmental factors and human mobility played on transmissibility of SARS-CoV-2 in Lombardy, Italy, in 2020. Environmental data were collected from accredited open-source web services. Aggregated mobility data for different points of interests were collected from Google Community Reports. The Reproduction number (Rt), based on the weekly counts of confirmed symptomatic COVID-19, non-imported cases, was used as a proxy for SARS-CoV-2 transmissibility. Assuming a non-linear correlation between selected variables, we used a Generalized Additive Model (GAM) to investigate with univariate and multivariate analyses the association between seasonal environmental factors (UV-index, temperature, humidity, and atmospheric pressure), location-specific mobility indices, and Rt. UV-index was the most effective environmental variable in predicting Rt. An optimal two-week lag-effect between changes in explanatory variables and Rt was selected. The association between Rt variations and individually taken mobility indices differed: Grocery & Pharmacy, Transit Station and Workplaces displayed the best performances in predicting Rt when individually added to the multivariate model together with UV-index, accounting for 85.0%, 85.5% and 82.6% of Rt variance, respectively. According to our results, both seasonality and social interaction policies played a significant role in curbing the pandemic. Non-linear models including UV-index and location-specific mobility indices can predict a considerable amount of SARS-CoV-2 transmissibility in Lombardy during 2020, emphasizing the importance of social distancing policies to keep viral transmissibility under control, especially during colder months.

Exposure to air pollution and COVID-19 severity: A review of current insights, management, and challenges

Several epidemiological studies have suggested a link between air pollution and respiratory tract infections. The outbreak of coronavirus disease 2019 (COVID-19) poses a great threat to public health worldwide. However, some parts of the globe have been worse affected in terms of prevalence and deaths than others. The causes and conditions of such variations have yet to be explored. Although some studies indicated a possible correlation between air pollution and COVID-19 severity, there is yet insufficient data for a meaningful answer. This review summarizes the impact of air pollution on COVID-19 infections and severity and discusses the possible management strategies and challenges involved. The available literature investigating the correlation between air pollution and COVID-19 infections and mortality are included in the review. The studies reviewed here suggest that exposure to air pollution, particularly to PM_2.5 and NO₂ , is positively correlated with COVID-19 infections and mortality. Some data indicate that air pollution can play an important role in the airborne transmission of SARS-CoV-2. A high percentage of COVID-19 incidences has been reported in the most polluted areas, where patients needed hospital admission. The available data also show that both short-term and long-term air pollution may enhance COVID-19 severity. However, most of the studies that showed a link between air pollution and COVID-19 infections and mortality did not consider potential confounders during the correlation analysis. Therefore, more specific studies need to be performed focusing on some additional confounders such as individual age, population density, and pre-existing comorbidities to determine the impact of air pollution on COVID-19 infections and deaths. Integr Environ Assess Manag 2021;17:1114-1122. © 2021 SETAC.

COVID-19 restrictions and their influences on ambient air, surface water and plastic waste in a coastal megacity, Chennai, India

Anthropogenic activities experienced a pause due to the nationwide lockdown, imposed to contain the rapid spread of COVID-19 in the third week of March 2020. The impacts of suspension of industrial activities, vehicular transport and other businesses for three months (25 March-30 June) on the environmental settings of Chennai, a coastal megacity was assessed. A significant reduction in the key urban air pollutants [PM2.5 (66.5%), PM10 (39.5%), NO2 (94.1%), CO (29%), O3 (45.3%)] was recorded as an immediate consequence of the reduced anthropogenic activities. Comparison of water quality of an urban river Adyar, between pre-lockdown and lockdown, showed a substantial drop in the dissolved inorganic N (47%) and suspended particulate matter (41%) during the latter period. During the pandemic, biomedical wastes in India showed an overall surge of 17%, which were predominantly plastic. FTIR-ATR analysis confirmed the polymers such as polypropylene (25.4%) and polyester (15.4%) in the personal protective equipment.

COVID-19 and environmental concerns: A rapid review

COVID-19 has slowed global economic growth and consequently impacted the environment as well. Parallelly, the environment also influences the transmission of this novel coronavirus through various factors. Every nation deals with varied population density and size; air quality and pollutants; the nature of land and water, which significantly impact the transmission of coronavirus. The WHO (Ziaeepour et al., 2008) [1] has recommended rapid reviews to provide timely evidence to the policymakers to respond to the emergency. The present study follows a rapid review along with a brief bibliometric analysis of 328 research papers, which synthesizes the evidence regarding the environmental concerns of COVID-19. The novel contribution of this rapid review is threefold. One, we take stock of the diverse findings as regards the transmission of the novel coronavirus in different types of environments for providing conclusive directions to the ongoing debate regarding the transmission of the virus. Two, our findings provide topical insights as well as methodological guidance for future researchers in the field. Three, we inform the policymakers on the efficacy of environmental measures for controlling the spread of COVID-19.

Investigating the roles of meteorological factors in COVID-19 transmission in Northern Italy

The novel COVID-19 is a highly invasive, pathogenic, and transmittable disease that has stressed the health care sector and hampered global development. Information of other viral respiratory diseases indicates that COVID-19 transmission could be affected by varying weather conditions; however, the impact of meteorological factors on the COVID-19 death counts remains unexplored. By investigating the impact of meteorological factors (absolute humidity, relative humidity, and temperature), this study will contribute both theoretically and practically to the concerned domain of pandemic management to be better prepared to control the spread of the disease. For this study, data is collected from 23 February to 31 March 2020 for Milan, Northern Italy, one of the badly hit regions by COVID-19. The generalized additive model (GAM) is applied, and a nonlinear relationship is examined with penalized spline methods. A sensitivity analysis is conducted for the verification of model results. The results reveal that temperature, relative humidity, and absolute humidity have a significant but negative relationship with the COVID-19 mortality rate. Therefore, it is possible to postulate that cool and dry environmental conditions promote virus transmission, leading to an increase in COVID-19 death counts. The results may facilitate health care policymakers in developing and implementing effective control measures in a timely and efficient way.

Exploring short term spatio-temporal pattern of PM2.5 and PM10 and their relationship with meteorological parameters during COVID-19 in Delhi

Present study aims to examine the impact of lockdown on spatio-temporal concentration of PM2.5 and PM10 - categorized and recorded based on its levels during pre-lockdown, lockdown and unlock phases while noting the relationship of these levels with meteorological parameters (temperature, wind speed, relative humidity, rainfall, pressure, sun hour and cloud cover) in Delhi. To aid the study, a comparison was made with the last two years (2018 to 2019), covering the same periods of pre-lockdown, lockdown and unlock phases of 2020. Correlation analysis, linear regression (LR) was used to examine the impact of meteorological parameters on particulate matter (PM) concentrations in Delhi, India. The findings showed that (i) substantial decline of PM concentration in Delhi during lockdown period, (ii) there were substantial seasonal variation of particulate matter concentration in city and (iii) meteorological parameters have close associations with PM concentrations. The findings will help planners and policy makers to understand the impact of air pollutants and meteorological parameters on infectious disease and to adopt effective strategies for future.

The Effect of Ambient Environmental Conditions on COVID-19 Mortality: A Systematic Review

Weather conditions may have an impact on SARS-CoV-2 virus transmission, as has been shown for seasonal influenza. Virus transmission most likely favors low temperature and low humidity conditions. This systematic review aimed to collect evidence on the impact of temperature and humidity on COVID-19 mortality. This review was registered with PROSPERO (registration no. CRD42020196055). We searched the Pubmed, Embase, and Cochrane COVID-19 databases for observational epidemiological studies. Two independent reviewers screened the title/abstracts and full texts of the studies. Two reviewers also performed data extraction and quality assessment. From 5051 identified studies, 11 were included in the review. Although the results were inconsistent, most studies imply that a decrease in temperature and humidity contributes to an increase in mortality. To establish the association with greater certainty, future studies should consider accurate exposure measurements and important covariates, such as government lockdowns and population density, sufficient lag times, and non-linear associations.

Association between short-term exposure to air pollution and COVID-19 hospital admission/mortality during warm seasons

COVID-19 is a new viral infection that is usually accompanied by respiratory complications. Air pollution has been linked to cardiorespiratory-related diseases and even premature mortality. The short-term exposure to air pollution may aggravate pulmonary symptoms in COVID-19 patients. The relationship between the short-term exposure to air pollution and hospital admission and mortality resulting from COVID-19 will be examined in Tehran, Iran, during the spring and summer of 2020. The statistics of PM_2.5, PM₁₀, and 8-h maximum ozone (O₃) concentrations, meteorological conditions, and COVID-19 hospital admissions/mortality were analyzed. The cross-correlation and temporal relationship between the daily concentration of the aforementioned pollutants (as well as the meteorological conditions) and the COVID-19 hospital admissions/mortality rate was calculated for each month. The concentration of PM_2.5, PM₁₀, and 8-h maximum O₃, along with temperature, increased in the summer. The hospital admissions and mortality associated with COVID-19 decreased from the first peak in the spring and then increased to its second peak in the summer. The short-term exposure to ambient PM_2.5, PM₁₀, O₃, and elevated temperatures is associated with higher rates of COVID-19-related hospital admissions/mortality throughout the summer. Among these variables, the correlation with O₃ was statistically significant in more summer months. The short-term exposure to air pollution (especially O₃) may increase the susceptibility of the population infected with COVID-19 and, therefore, increases the rate of hospital admissions and mortality even during the warm seasons.

Multiple relationships between aerosol and COVID-19: A framework for global studies

COVID-19 (Corona Virus Disease 2019) is a severe respiratory syndrome currently causing a human global pandemic. The original virus, along with newer variants, is highly transmissible. Aerosols are a multiphase system consisting of the atmosphere with suspended solid and liquid particles, which can carry toxic and harmful substances; especially the liquid components. The degree to which aerosols can carry the virus and cause COVID-19 disease is of significant research importance. In this study, we have discussed aerosol transmission as the pathway of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), and the aerosol pollution reduction as a consequence of the COVID-19 lockdown. The aerosol transmission routes of the SARS-CoV-2 can be further subdivided into proximal human-exhaled aerosol transmission and potentially more distal ambient aerosol transmission. The human-exhaled aerosol transmission is a direct dispersion of the SARS-CoV-2. The ambient aerosol transmission is an indirect dispersion of the SARS-CoV-2 in which the aerosol acts as a carrier to spread the virus. This indirect dispersion can also stimulate the up-regulation of the expression of SARS-CoV-2 receptor ACE-2 (Angiotensin Converting Enzyme 2) and protease TMPRSS2 (Transmembrane Serine Protease 2), thereby increasing the incidence and mortality of COVID-19. From the aerosol quality data around the World, it can be seen that often atmospheric pollution has significantly decreased due to factors such as the reduction of traffic, industry, cooking and coal-burning emissions during the COVID-19 lockdown. The airborne transmission potential of SARS-CoV-2, the infectivity of the virus in ambient aerosols, and the reduction of aerosol pollution levels due to the lockdowns are crucial research subjects.

Emerging role of air pollution and meteorological parameters in COVID-19

Exposure to air pollutants has been associated with respiratory viral infections. Epidemiological studies have shown that air pollution exposure is related to increased cases of SARS-COV-2 infection and COVID-19-associated mortality. In addition, the changes of meteorological parameters have also been implicated in the occurrence and development of COVID-19. However, the molecular mechanisms by which pollutant exposure and changes of meteorological parameters affects COVID-19 remains unknown. This review summarizes the biology of COVID-19 and the route of viral transmission, and elaborates on the relationship between air pollution and climate indicators and COVID-19. Finally, we envisaged the potential roles of air pollution and meteorological parameters in COVID-19.

Regional scenario of air pollution in lockdown due to COVID-19 pandemic: Evidence from major urban agglomerations of India

Air pollution in India during COVID-19 lockdown, which imposed on 25th March to 31st May 2020, has brought a significant improvement in air quality. The present paper mainly focuses on the scenario of air pollution level (PM_2.5, PM₁₀, SO₂, NO₂ and O₃) across 57 urban agglomerations (UAs) of India during lockdown. For analysis, India has been divided into six regions - Northern, Western, Central, Southern, Eastern and North-Eastern. Various spatial statistical modelling with composite air quality index (CAQI) have been utilised to examine the spatial pattern of air pollution level. The result shows that concentration of all air pollutants decreased significantly (except O₃) during lockdown. The maximum decrease is the concentration of NO₂ (40%) followed by PM_2.5 (32%), PM₁₀ (24%) and SO₂ (18%). Among 57 UA's, only five - Panipat (1.00), Ghaziabad (0.76), Delhi (0.74), Gurugram (0.72) and Varanasi (0.71) had least improvement in air pollution level considering entire lockdown period. The outcome of this study has an immense scope to understand the regional scenario of air pollution level and to implement effective strategies for environmental sustainability.

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.

Impact of lockdown on particulate matter concentrations in Colombia during the COVID-19 pandemic

The first confirmed case of COVID-19 in Colombia was reported on March 6, 2020. For this reason, on March 25, preventive isolation was declared mandatory. These measures involved the suspension of economic activities and drastically reduced the number of vehicles on the road. The objective of this study is to evaluate the impact of the lockdown due to the COVID-19 pandemic on PM_2.5 concentrations at 5 monitoring stations and aerosol optical depth values of the Terra/MODIS satellite. We analyzed and compared the weekly and monthly concentrations of PM_2.5 before and during the lockdown between the week of January 6 to June 22, 2020, and compared the daily values obtained from the Terra/MODIS satellite for the months of January-June during the years 2018-2020 to elucidate the effects of the lockdown. Similar to other monitored sites in the world, we observed substantial reductions in weekly PM_2.5 concentrations, from 41 to 84% (Bogotá), from 13 to 66% (Funza), from 17 to 57% (Boyacá), from 35 to 86% (Valledupar) and 31 at 60% (Risaralda). Unlike other studies, the aerosol optical depth values increased up to 59% during the months of lockdown compared to previous years and up to 70% of the weekly mean when compared to before the lockdown. These spatiotemporal behaviors of PM_2.5 and the aerosol optical depth in Colombia are influenced by reductions in vehicular flow during quarantine, regional rainfall, and height of the planetary boundary layer. Emissions from economic activities affect pollutant levels in the area. The analysis of the levels of pollutants during the lockdown provides a baseline for regulatory agencies to establish mitigation plans.

Air pollution and critical air pollutant assessment during and after COVID-19 lockdowns: Evidence from pandemic hotspots in China, the Republic of Korea, Japan, and India

The COVID-19 virus outbreak has been declared a "global pandemic". Therefore, "lockdown" was issued in affected countries to control the spread of the virus. To assess air pollution during and after lockdowns, this study selected pandemic hotspots in China (Wuhan), Japan (Tokyo), the Republic of Korea (Daegu), and India (Mumbai) and compared the Air Quality Index (AQI) in these areas for the past three years. The results indicated that air pollution levels were positively correlated with a reduction in pollutant levels during and after lockdowns in these cities. In Tokyo, low levels of air pollution, no significant change in the distribution of "good" and "moderate" days was observed during lockdown. In Daegu, mid-level air pollution, the percentage of "unhealthy" days (AQI>100) markedly reduced during lockdown; however, this reverted after lockdown was lifted. In Wuhan and Mumbai, high air pollution levels, the percentage of unhealthy days remarkably decreased during lockdown and continued to reduce after lockdown. It was found that PM2.5 was the critical pollutant for all cities because its sub-AQI was the largest of the six pollutant species for the majority of days. In addition, PM10 dominated the overall AQI for 2.2-9.6% of the period in Wuhan and Mumbai, and its sub-AQI reduced during lockdown. The mean sub-AQI for NO2, SO2, CO, and O3 was within the "good" category for all cities. In conclusion, the lockdown policy reduced air pollution in general and this reduction was more significant for regions with high air pollution levels.

The Effects of Air Pollution on COVID-19 Infection and Mortality-A Review on Recent Evidence

The outbreak of COVID-19 has created a serious public health concern worldwide. Although, most of the regions around the globe have been affected by COVID-19 infections; some regions are more badly affected in terms of infections and fatality rates than others. The exact reasons for such variations are not clear yet. This review discussed the possible effects of air pollution on COVID-19 infections and mortality based on some recent evidence. The findings of most studies reviewed here demonstrate that both short-term and long-term exposure to air pollution especially PM2.5 and nitrogen dioxide (NO2) may contribute significantly to higher rates of COVID-19 infections and mortalities with a lesser extent also PM10. A significant correlation has been found between air pollution and COVID-19 infections and mortality in some countries in the world. The available data also indicate that exposure to air pollution may influence COVID-19 transmission. Moreover, exposure to air pollution may increase vulnerability and have harmful effects on the prognosis of patients affected by COVID-19 infections. Further research should be conducted considering some potential confounders such as age and pre-existing medical conditions along with exposure to NO2, PM2.5 and other air pollutants to confirm their detrimental effects on mortalities from COVID-19.

Numerical simulation and experimental validation of the ventilation system performance in a heated room

The time spent by the occupant indoor the building is significant; therefore, the central objective of the major research was the evaluation of the thermal sensation for the existing people. This study examines the numerical simulation in a room containing a manikin sitting in front of a computer. The computational fluid dynamics (CFD) tools were considered using ANSYS Fluent 16.2 software. This software exploits the finite volume method that is based on the resolution of the Navier-Stokes equations. The distribution of the temperature, velocity, static pressure, turbulent kinetic energy, turbulent viscosity, and turbulent dissipation is tested in different planes and different directions to characterize the airflow indoor a heated room. Equally, the thermal comfort is examined by calculating the predicted mean vote (PMV). The comparison between the numerical results and the experimental data founded from the literature prove that the supply of airflow was affected by the presence of the heat sources and the thermal climate is considered as a slightly hot. The use of the adequate meshes is in a good agreement with the experimental data and confirms the validity of the numerical approach.