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

OBJECTIVE: To determine whether ambient air pollutants and meteorological variables are associated with daily COVID-19 incidence. DESIGN: A retrospective cohort from January 25 to February 29, 2020. SETTING: Cities of Wuhan, Xiaogan, and Huanggang, China. PATIENTS: The COVID-19 cases detected each day. METHODS: We collected daily data of COVID-19 incidence, 8 ambient air pollutants (particulate matter of ≤2.5 µm [PM2.5], particulate matter ≤10 µm [PM10], sulfur dioxide [SO2], carbon monoxide [CO], nitrogen dioxide [NO2], and maximum 8-h moving average concentrations for ozone [O3-8h]) and 3 meteorological variables (temperature, relative humidity, and wind) in China's 3 worst COVID-19-stricken cities during the study period. The multivariate Poisson regression was performed to understand their correlation. RESULTS: Daily COVID-19 incidence was positively associated with PM2.5 and humidity in all cities. Specifically, the relative risk (RR) of PM2.5 for daily COVID-19 incidences were 1.036 (95% confidence interval [CI], 1.032-1.039) in Wuhan, 1.059 (95% CI, 1.046-1.072) in Xiaogan, and 1.144 (95% CI, 1.12-1.169) in Huanggang. The RR of humidity for daily COVID-19 incidence was consistently lower than that of PM2.5, and this difference ranged from 0.027 to 0.111. Moreover, PM10 and temperature also exhibited a notable correlation with daily COVID-19 incidence, but in a negative pattern The RR of PM10 for daily COVID-19 incidence ranged from 0.915 (95% CI, 0.896-0.934) to 0.961 (95% CI, 0.95-0.972, while that of temperature ranged from 0.738 (95% CI, 0.717-0.759) to 0.969 (95% CI, 0.966-0.973). CONCLUSIONS: Our data show that PM2.5 and humidity are substantially associated with an increased risk of COVID-19 and that PM10 and temperature are substantially associated with a decreased risk of COVID-19.

An Epidemiological Study to Investigate Links between Atmospheric Pollution from Farming and SARS-CoV-2 Mortality.

Exposure to atmospheric particulate matter and nitrogen dioxide has been linked to SARS-CoV-2 infection and death. We hypothesized that long-term exposure to farming-related air pollutants might predispose to an increased risk of COVID-19-related death. To test this hypothesis, we performed an ecological study of five Italian Regions (Piedmont, Lombardy, Veneto, Emilia-Romagna and Sicily), linking all-cause mortality by province (administrative entities within regions) to data on atmospheric concentrations of particulate matter (PM2.5 and PM10) and ammonia (NH3), which are mainly produced by agricultural activities. The study outcome was change in all-cause mortality during March-April 2020 compared with March-April 2015-2019 (period). We estimated all-cause mortality rate ratios (MRRs) by multivariate negative binomial regression models adjusting for air temperature, humidity, international import-export, gross domestic product and population density. We documented a 6.9% excess in MRR (proxy for COVID-19 mortality) for each tonne/km2 increase in NH3 emissions, explained by the interaction of the period variable with NH3 exposure, considering all pollutants together. Despite the limitations of the ecological design of the study, following the precautionary principle, we recommend the implementation of public health measures to limit environmental NH3 exposure, particularly while the COVID-19 pandemic continues. Future studies are needed to investigate any causal link between COVID-19 and farming-related pollution.

COVID-19, air quality and space monitoring.

Due to the worldwide spread of the coronavirus disease 2019 (COVID-19), human mobility and economic activity have slowed down considerably since early 2020. A relatively high number of those infected develop serious pneumonia leading to progressive respiratory failure, system disease and often death. Apart from close human-to-human contact, the acceleration and global diffusion of this pandemic has been shown to be associated with changes in atmospheric chemistry and air pollution by microscopic particulate matter (PM). Breathing air with high concentrations of nitrogen dioxide and PM can result in over-expression of the angiotensin converting enzyme-2 (ACE-2) leading to stress of organs, such as heart and kidneys. Satellite monitoring can play a crucial role in spatio-temporal surveillance of the disease by producing data on pollution as proxy for industrial activity, transport and traffic circulation. Real-time monitoring of COVID-19 in air and chemical pollution of the atmospheric boundary layer available from Earth-observing satellites commuting with Health Information Systems (HIS) would be useful for decision makers involved with public health.

Role of air pollutants mediated oxidative stress in respiratory diseases.

Airborne particulate (PM) components from fossil fuel combustion can induce oxidative stress initiated by reactive oxygen species (ROS) that are strongly correlated with airway inflammation and asthma. A valid biomarker of airway inflammation is fractionated exhaled nitric oxide (FENO). The oxidative potential of PM2.5 can be evaluated with the dithiothreitol (DTT) dosage, which represents both ROS chemically produced and intracellular ROS of macrophages. This correlates with quality indicators of the internal environment and ventilation strategies such as dilution and removal of airborne contaminants.

Human Serum Albumin Cys34 Adducts in Newborn Dried Blood Spots: Associations With Air Pollution Exposure During Pregnancy.

Background: Increasing evidence suggests that exposure to air pollution during pregnancy is associated with adverse pregnancy outcomes. However, biomarkers associated with air pollution exposure are widely lacking and often transient. In addition, ascertaining biospecimens during pregnacy to assess the prenatal environment remains largely infeasible. Objectives: To address these challenges, we investigated relationships between air pollution exposure during pregnancy and human serum albumin Cys34 (HSA-Cys34) adducts in newborn dried blood spots (DBS) samples, which captures an integration of perinatal exposures to small reactive molecules in circulating blood. Methods: Newborn DBS were obtained from a state archive for a cohort of 120 children born at one Kaiser Permanente Southern California (KPSC) hospitals in 2007. These children were selected to maximize the range of residential air pollution exposure during the entire pregnancy to PM2.5, PM10, NO2, O3, based on monthly estimates interpolated from regulatory monitoring sites. HSA-Cys34 adducts were selected based on previously reported relationships with air pollution exposure and oxidative stress. Results: Six adducts measured in newborn DBS samples were associated with air pollution exposures during pregnancy; these included direct oxidation products, adducts formed with small thiol compounds, and adducts formed with reactive aldehydes. Two general trends were identified: Exposure to air pollution late in pregnancy (i.e., in the last 30 days) was associated with increased oxidative stress, and exposure to air pollution earlier in pregnancy (i.e., not in the last 30 days) was associated with decreased oxidative stress around the time of birth. Discussion: Air pollution exposure occurring during pregnancy can alter biology and leave measurable impacts on the developing infant captured in the newborn DBS adductome, which represents a promising tool for investigating adverse birth outcomes in population-based studies.

Household Air Pollution and Respiratory Symptoms a Month Before and During the Stringent COVID-19 Lockdown Levels 5 and 4 in South Africa.

Background: Household air pollution (HAP) is associated with adverse human health impacts. During COVID-19 Lockdown Levels 5 and 4 (the most stringent levels), South Africans remained at home, potentially increasing their exposure to HAP. Objectives: To investigate changes in fuel use behaviours/patterns of use affecting HAP exposure and associated HAP-related respiratory health outcomes during COVID-19 Lockdown Levels 5 and 4. Methods: This was a cross-sectional online and telephonic survey of participants from an existing database. Logistic regression and McNemar's test were used to analyse household-level data. Results: Among 2 505 participants, while electricity was the main energy source for cooking and heating the month before and during Lockdown Levels 5 and 4, some households used less electricity during Lockdown Levels 5 and 4 or switched to "dirty fuels." One third of participants reported presence of environmental tobacco smoke in the home, a source of HAP associated with respiratory illnesses. Prevalence of HAP-related respiratory health outcomes were <10% (except dry cough). Majority of households reported cooking more, cleaning more and spending more time indoors during Lockdown Levels 5 and 4 - potentially exposed to HAP. Conclusion: Should South Africa return to Lockdown Levels 5 or 4, awareness raising about the risks associated with HAP as well as messaging information for prevention of exposure to HAP, including environmental tobacco smoke, and associated adverse health impacts will be necessary.

Exposure to air pollution is associated with congenital anomalies in the population born by in vitro fertilization.

BACKGROUND: Congenital anomalies (CAs) are the leading causes for children's disabilities and mortalities worldwide. The associations between air pollution and CAs are not fully characterized in fetuses born by in vitro fertilization (IVF) who are at high risk of congenital anomalies. METHODS: We conducted a cross-sectional study including 16,971 IVF cycles from three hospitals in Hebei Province, China, 2014-2019. Air quality data was obtained from 149 air monitoring stations. Individual average daily concentrations of PM2.5, PM10, NO2, SO2, CO, and O3 were estimated by spatiotemporal kriging method. Exposure windows were divided into 5: preantral follicle period, antral follicle period, germinal period, embryonic period and early fetal period. Logistic generalized estimating equations were used to estimate the associations between air pollutants and overall or organ-system specific congenital anomalies. Negative control exposure method was used to detect and reduce bias of estimation. RESULTS: We found increasing levels of PM2.5 and PM10 were associated with higher risk of overall congenital anomalies during early fetal period, equating gestation 10-12 weeks (OR: 1.05, 95% CI: 1.02-1.09, p = 0.013 for a 10 µg/m3 increase of PM2.5; OR: 1.03, 95% CI: 1.01-1.06, p = 0.021 for a 10 µg/m3 increase of PM10). Cleft lip and cleft palate were associated with PM10 in germinal period and early fetal period. The CAs of eye, ear, face and neck were related to CO in preantral follicle stage. We did not find an association between chromosome abnormalities and air pollution exposure. CONCLUSIONS: We concluded that ambient air pollution was a risk factor for congenital anomalies in the fetuses conceived through IVF, especially exposure in early fetal period.

Air Pollution in Poland: A 2022 Narrative Review with Focus on Respiratory Diseases.

According to the World Bank Group, 36 of the 50 most polluted cities in the European Union are in Poland. Thus, ambient air pollution and its detrimental health effects are a matter of immense importance in Poland. This narrative review aims to analyse current findings on air pollution and health in Poland, with a focus on respiratory diseases, including COVID-19, as well as the Poles' awareness of air pollution. PubMed, Scopus and Google Scholar databases were searched. In total, results from 71 research papers were summarized qualitatively. In Poland, increased air pollution levels are linked to increased general and respiratory disease mortality rates, higher prevalence of respiratory diseases, including asthma, lung cancer and COVID-19 infections, reduced forced expiratory volume in one second (FEV1) and forced vital capacity (FVC). The proximity of high traffic areas exacerbates respiratory health problems. People living in more polluted regions (south of Poland) and in the winter season have a higher level of air pollution awareness. There is an urgent need to reduce air pollution levels and increase public awareness of this threat. A larger number of multi-city studies are needed in Poland to consistently track the burden of diseases attributable to air pollution.

COVID-19 and Air Pollution: A Spatial Analysis of Particulate Matter Concentration and Pandemic-Associated Mortality in the US.

In 2019, a novel coronavirus, SARS-CoV-2, was first reported in Wuhan, China. The virus causes the disease commonly known as COVID-19, and, since its emergence, it has infected over 252 million individuals globally and taken the lives of over 5 million in the same time span. Primary research on SARS-CoV-2 and COVID-19 focused on understanding the biomolecular composition of the virus. This research has led to the development of multiple vaccines with great efficacy and antiviral treatments for the disease. The development of biomedical interventions has been crucial to combating this pandemic; additionally, environmental confounding variables that could have exacerbated the pandemic need further assessment. In this research study, we conducted a spatial analysis of particulate matter (PM) concentration and its association with COVID-19 mortality in the United States. Results of this study demonstrate a significant positive correlation between PM concentration levels and COVID-19 mortality; however, this does not necessarily imply a causal relationship. These results are consistent with similar studies in Italy and China, where significant COVID-19 cases and corresponding deaths were exhibited. Furthermore, maps of the data demonstrate clustering of COVID-19 mortality which suggest further investigation into the social determinants of health impacting the pandemic.

Negative-Binomial and quasi-poisson regressions between COVID-19, mobility and environment in São Paulo, Brazil.

Brazil, the country most impacted by the coronavirus disease 2019 (COVID-19) on the southern hemisphere, use intensive care admissions per day, mobility and other indices to monitor quarantines and prevent the transmissions of SARS-CoV-2. In this study we quantified the associations between residential mobility index (RMI), air pollution, meteorology, and daily cases and deaths of COVID-19 in São Paulo, Brazil. We applied a semiparametric generalized additive model (GAM) to estimate: 1) the association between RMI and COVID-19, accounting for ambient particulate matter (PM2.5), ozone (O3), relative humidity, temperature and delayed exposure between 4 and 21 days, and 2) the association between COVID-19 and exposure to for ambient particulate matter (PM2.5), ozone (O3), accounting for relative humidity, temperature and mobility. We found that an RMI of 45.28% results in 1212 cases (95% CI: 1189 to 1235) and 44 deaths (95% CI: 40 to 47). Increasing the isolation from 45.28% to 50% would avoid 438 cases and 21 deaths. Also, we found that an increment of 10 µg⋅m-³ of PM2.5 results in a risk of 1.140 (95% CI: 1.021 to 1.274) for cases and 1.086 (95% CI: 1.008 to 1.170) for deaths, while O3 produces a relative risk of 1.075 (95% CI: 1.006 to 1.150) for cases and 1.063 (95% CI: 1.006 to 1.124) for deaths, respectively. We compared our results with observations and literature review, finding well agreement. Policymakers can use such mobility indices as tools to control social distance activities. Spatial distancing is an important factor to control COVID-19, however, measuring face-mask usage would enhance the understanding the pandemic dynamic. Small increments of air pollution result in an increased number of COVID-19 cases and deaths.

Short- and medium-term impacts of strict anti-contagion policies on non-COVID-19 mortality in China.

The effects of coronavirus disease-19 (COVID-19) public health policies on non-COVID-19-related mortality are unclear. Here, using death registries based on 300 million Chinese people and a difference-in-differences design, we find that China's strict anti-contagion policies during the COVID-19 pandemic significantly reduced non-COVID-19 mortality outside Wuhan (by 4.6%). The health benefits persisted and became even greater after the measures were loosened: mortality was reduced by 12.5% in the medium term. Significant changes in people's behaviours (for example, wearing masks and practising social distancing) and reductions in air pollution and traffic accidents could have driven these results. We estimate that 54,000 lives could have been saved from non-COVID-19 causes during the 50 days of strict policies and 293,000 in the subsequent 115 days. The results suggest that virus countermeasures not only effectively controlled COVID-19 in China but also brought about unintended and substantial public health benefits.

Exposure to PM2.5 and PM10 and COVID-19 infection rates and mortality: A one-year observational study in Poland.

BACKGROUND: Atmospheric contamination, especially particulate matter (PM), can be associated viral infections connected with respiratory failure. Literature data indicates that intensity of SARS-CoV-2 infections worldwide can be associated with PM pollution levels. OBJECTIVES: The aim of the study was to examine the relationship between atmospheric contamination, measured as PM2.5 and PM10 levels, and the number of COVID-19 cases and related deaths in Poland in a one-year observation study. METHODS: Number and geographical distribution of COVID-19 incidents and related deaths, as well as PM2.5 and PM10 exposure levels in Poland were obtained from publicly accessible databases. Average monthly values of these parameters for individual provinces were calculated. Multiple regression analysis was performed for the period between March 2020 and February 2021, taking into account average monthly exposure to PM2.5 and PM10, monthly COVID-19 incidence and mortality rates per 100,000 inhabitants and the population density across Polish provinces. RESULTS: Only December 2020 the number of new infections was significantly related to the three analyzed factors: PM2.5, population density and the number of laboratory COVID-19 tests (R2 = 0.882). For COVID-19 mortality, a model with all three significant factors: PM10, population density and number of tests was obtained as significant only in November 2020 (R2 = 0.468). CONCLUSION: The distribution of COVID-19 incidents across Poland was independent from annual levels of particulate matter concentration in provinces. Exposure to PM2.5 and PM10 was associated with COVID-19 incidence and mortality in different provinces only in certain months. Other cofactors such as population density and the number of performed COVID-19 tests also corresponded with both COVID-19-related infections and deaths only in certain months. Particulate matter should not be treated as the sole determinant of the spread and severity of the COVID-19 pandemic but its importance in the incidence of infectious diseases should not be forgotten.

Cumulative effects of ambient particulate matter pollution on deaths: A multicity analysis of mortality displacement.

BACKGROUND: Systematic evaluations of the cumulative effects and mortality displacement of ambient particulate matter (PM) pollution on deaths are lacking. We aimed to discern the cumulative effect profile of PM exposure, and investigate the presence of mortality displacement in a large-scale population. METHODS: We conducted a time-series analysis with different exposure-lag models on 13 cities in Jiangsu, China, to estimate the effects of PM pollution on non-accidental, cardiovascular, and respiratory mortality (2015-2019). Over-dispersed Poisson generalized additive models were integrated with distributed lag models to estimate cumulative exposure effects, and assess mortality displacement. RESULTS: Pooled cumulative effect estimates with lags of 0-7 and 0-14 days were substantially larger than those with single-day and 2-day moving average lags. For each 10 µg/m3 increment in PM2.5 concentration with a cumulative lag of 0-7 days, we estimated an increase of 0.50 % (95 % CI: 0.29, 0.72), 0.63 % (95 % CI: 0.38, 0.88), and 0.50 % (95 % CI: 0.01, 1.01) in pooled estimates of non-accidental, cardiovascular, and respiratory mortality, respectively. Both PM10 and PM2.5 were associated with significant increases in non-accidental and cardiovascular mortality with a cumulative lag of 0-14 days. We observed mortality displacement within 30 days for non-accidental, cardiovascular, and respiratory deaths. CONCLUSIONS: Our findings suggest that risk assessment based on single-day or 2-day moving average lag structures may underestimate the adverse effects of PM pollution. The cumulative effects of PM exposure on non-accidental and cardiovascular mortality can last up to 14 days. Evidence of mortality displacement for non-accidental, cardiovascular, and respiratory deaths was found.

Long-term exposure to air pollution and COVID-19 incidence: A multi-country study.

The study of the impacts of air pollution on COVID-19 has gained increasing attention. However, most of the existing studies are based on a single country, with a high degree of variation in the results reported in different papers. We attempt to inform the debate about the long-term effects of air pollution on COVID-19 by conducting a multi-country analysis using a spatial ecological design, including Canada, Italy, England and the United States. The model allows the residual spatial autocorrelation after accounting for covariates. It is concluded that the effects of PM2.5 and NO2 are inconsistent across countries. Specifically, NO2 was not found to be an important factor affecting COVID-19 infection, while a large effect for PM2.5 in the US is not found in the other three countries. The Population Attributable Fraction for COVID-19 incidence ranges from 3.4% in Canada to 45.9% in Italy, although with considerable uncertainty in these estimates.

Understanding the environmental factors related to the decrease in Pediatric Emergency Department referrals for acute asthma during the SARS-CoV-2 pandemic.

BACKGROUND: Lockdown measures during the SARS-CoV-2 pandemic determined radical changes to behavioral and social habits, that were reflected by a reduction in the transmission of respiratory pathogens and in anthropogenic atmospheric emissions. OBJECTIVE: This ecological study aims to provide a descriptive evaluation on how restrictive measures during the SARS-CoV-2 pandemic impacted Pediatric Emergency Department (PED) referrals for asthma exacerbations, and their potentially associated environmental triggers in Bologna, a densely populated urban area in Northern Italy. METHODS: Files of children evaluated for acute asthma during 2015 to 2020 at the PED of Sant'Orsola University Hospital of Bologna were retrospectively reviewed. Historical daily concentration records of particulate (PM2.5 , PM10 ) and gaseous (NO2 , C6 H6 ) air pollutants, and pollen were concurrently evaluated, including specific PM chemical tracers for traffic-related air pollution (TRAP). RESULTS: In 2020, asthma-related PED referrals decreased compared to referral rates of the previous 5 years (p < 0.01). This effect was particularly marked during the first lockdown period (March to May), when the drastic drop in PED referrals was associated with a reduction of high-priority cases up to 85% and by 54%, on average. A concomitant reduction in the concentrations of traffic-related air pollutants was observed in the range of 40%-60% (p < 0.01). CONCLUSIONS: The lower rate of asthma exacerbations in childhood was in this study paralleled with reduced TRAP levels during the pandemic. Synergic interactions of the multiple consequences of lockdowns likely contributed to the reduced exacerbations, including decreased exposure to ambient pollutants and fewer respiratory infections, identified as the most important factor in the literature.

The effect of known and unknown confounders on the relationship between air pollution and Covid-19 mortality in Italy: A sensitivity analysis of an ecological study based on the E-value.

Back in December 2019, the novel coronavirus disease 2019 (Covid-19) started rapidly spreading worldwide, especially in Italy that was among the most affected countries. The geographical distribution of air pollution and Covid-19 mortality in Italy suggested atmospheric pollution as a worsening factor of severe Covid-19 health outcomes. The present nationwide ecological study focused on all 107 Italian territorial areas, aiming to assess the potential association between Particulate Matter concentration, less than 2.5 µm in diameter (exposure), and Covid-19 mortality rate (outcome) throughout 2020, by looking at 28 potential confounders. A potential positive association between exposure and outcome was observed when performing a multivariate regression analysis with a Negative Binomial model, suggesting that an increase of 1 µg/m3 in the exposure is associated with an increase of 9.0% (95% CI: 6.5%-11.6%) in the average Covid-19 mortality rate, conditional on all 28 potential confounders. A sensitivity analysis, based on the E-value, shows that a hypothetical unmeasured confounder would have to be associated with both PM2.5 concentration and Covid-19 mortality rate by a rate ratio of at least 1.40-fold each to explain away the exposure-outcome association, conditional on all 28 covariates included in the main analysis model. Moreover, the Observed Covariate E-value (OCE) was reported to provide a contextualization of the E-value on the observed covariates included in the study. The OCE sensitivity analysis shows that a set of unknown confounders similar in size and magnitude to the set of the considered climatic factors could potentially explain away the estimated exposure-outcome association. Consequently, the role of climatic factors in the Covid-19 pandemic is worth of further investigation.

Temperature, humidity and outdoor air quality indicators influence COVID-19 spread rate and mortality in major cities of Saudi Arabia.

There is an increasing evidence that meteorological (temperature, relative humidity, dew) and air quality indicators (PM2.5, PM10, NO2, SO2, CO) are affecting the COVID-19 transmission rate and the number of deaths in many countries around the globe. However, there are contradictory results due to limited observations of these parameters and absence of conclusive evidence on such relationships in cold or hot arid tropical and subtropical desert climate of Gulf region. This is the first study exploring the relationships of the meteorological (temperature, relative humidity, and dew) and air quality indicators (PM10,CO, and SO2) with daily COVID-19 infections and death cases for a period of six months (1st March to August 31, 2020) in six selected cities of the Kingdom of Saudi Arabia by using generalized additive model. The Akaike information criterion (AIC) was used to assess factors affecting the infections rate and deaths through the selection of best model whereas overfitting of multivariate model was avoided by using cross-validation. Spearman correlation indicated that exponentially weighted moving average (EWMA) temperature and relative humidity (R > 0.5, P < 0.0001) are the main variables affecting the daily COVID-19 infections and deaths. EWMA temperature and relative humidity showed non linear relationships with the number of COVID-19 infections and deaths (DF > 1, P < 0.0001). Daily COVID-19 infections showed a positive relationship at temperature between 23 and 34.5 °C and relative humidity ranging from 30 to 60%; a negative relationship was found below and/or above these ranges. Similarly, the number of deaths had a positive relationship at temperature ˃28.7 °C and with relative humidity ˂40%, showing higher number of deaths above this temperature and below this relative humidity rate. All air quality indicators had linear relationships with the number of COVID-19 infections and deaths (P < 0.0001). Hence, variation in temperature, relative humidity and air pollution indicators could be important factors influencing the COVID-19 spread and mortality. Under the current scenario with rising temperature and relative humidity, the number of cases is increasing, hence it justifies an active government policy to lessen COVID-19 infection rate.

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.

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

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