Air Pollution and the Novel Covid-19 Disease: a Putative Disease Risk Factor

Diesel exhaust particle inhalation in conjunction with high-fat diet consumption alters the expression of pulmonary SARS-COV-2 infection pathways, which is mitigated by probiotic treatment in C57BL/6 male mice

BACKGROUND

Both exposure to air pollutants and obesity are associated with increased incidence and severity of COVID-19 infection; however, the mechanistic pathways involved are not well-characterized. After being primed by the transmembrane protease serine 2 (TMPRSS2) or furin protease, SARS-CoV-2 uses the angiotensin-converting enzyme (ACE)-2 receptor to enter respiratory epithelial cells. The androgen receptor (AR) is known to regulate both TMPRSS2 and ACE2 expression, and neuropilin-1 (NRP1) is a proposed coreceptor for SARS-CoV-2; thus, altered expression of these factors may promote susceptibility to infection. As such, this study investigated the hypothesis that inhalational exposure to traffic-generated particulate matter (diesel exhaust particulate; DEP) increases the expression of those pathways that mediate SARS-CoV-2 infection and susceptibility, which is exacerbated by the consumption of a high-fat (HF) diet.

METHODS

Four- to six-week-old male C57BL/6 mice fed either regular chow or a HF diet (HF, 45% kcal from fat) were randomly assigned to be exposed via oropharyngeal aspiration to 35 µg DEP suspended in 35 µl 0.9% sterile saline or sterile saline only (control) twice a week for 30 days. Furthermore, as previous studies have shown that probiotic treatment can protect against exposure-related inflammatory outcomes in the lungs, a subset of study animals fed a HF diet were concurrently treated with 0.3 g/day Winclove Ecologic® Barrier probiotics in their drinking water throughout the study.

RESULTS

Our results revealed that the expression of ACE2 protein increased with DEP exposure and that TMPRSS2, AR, NRP1, and furin protein expression increased with DEP exposure in conjunction with a HF diet. These DEP ± HF diet-mediated increases in expression were mitigated with probiotic treatment.

CONCLUSION

These findings suggest that inhalational exposure to air pollutants in conjunction with the consumption of a HF diet contributes to a more susceptible lung environment to SARS-CoV-2 infection and that probiotic treatment could be beneficial as a preventative measure.

Exploring the association between ambient air pollution and COVID-19 risk: A comprehensive meta-analysis with meta-regression modelling

Introduction

Air pollution is speculated to increase the risk of Coronavirus disease-2019 (COVID-19). Nevertheless, the results remain inconsistent and inconclusive. This study aimed to explore the association between ambient air pollution (AAP) and COVID-19 risks using a meta-analysis with meta-regression modelling.

Methods

The inclusion criteria were: original studies quantifying the association using effect sizes and 95 % confidence intervals (CIs); time-series, cohort, ecological or case-crossover peer-reviewed studies in English. Exclusion criteria encompassed non-original studies, animal studies, and data with common errors. PubMed, Web of Science, Embase and Google Scholar electronic databases were systemically searched for eligible literature, up to 31, March 2023. The risk of bias (ROB) was assessed following the Agency for Healthcare Research and Quality parameters. A random-effects model was used to calculate pooled risk ratios (RRs) and their 95 % CIs.

Results

A total of 58 studies, between 2020 and 2023, met the inclusion criteria. The global representation was skewed, with major contributions from the USA (24.1 %) and China (22.4 %). The distribution included studies on short-term (43.1 %) and long-term (56.9 %) air pollution exposure. Ecological studies constituted 51.7 %, time-series-27.6 %, cohorts-17.2 %, and case crossover-3.4 %. ROB assessment showed low (86.2 %) and moderate (13.8 %) risk. The COVID-19 incidences increased with a 10 μg/m3 increase in PM2.5 [RR = 4.9045; 95 % CI (4.1548-5.7895)], PM10 [RR = 2.9427: (2.2290-3.8850)], NO2 [RR = 3.2750: (3.1420-3.4136)], SO2 [RR = 3.3400: (2.7931-3.9940)], CO [RR = 2.6244: (2.5208-2.7322)] and O3 [RR = 2.4008: (2.1859-2.6368)] concentrations. A 10 μg/m3 increase in concentrations of PM2.5 [RR = 3.0418: (2.7344-3.3838)], PM10 [RR = 2.6202: (2.1602-3.1781)], NO2 [RR = 3.2226: (2.1411-4.8504)], CO [RR = 1.8021 (0.8045-4.0370)] and O3 [RR = 2.3270 (1.5906-3.4045)] was significantly associated with COVID-19 mortality. Stratified analysis showed that study design, exposure period, and country influenced exposure-response associations. Meta-regression model indicated significant predictors for air pollution-COVID-19 incidence associations.

Conclusion

The study, while robust, lacks causality demonstration and focuses only on the USA and China, limiting its generalizability. Regardless, the study provides a strong evidence base for air pollution-COVID-19-risks associations, offering valuable insights for intervention measures for COVID-19.

Conditioning factors in the spreading of Covid-19 - Does geography matter?

There is evidence in literature that the spread of COVID-19 can be influenced by various geographic factors, including territorial features, climate, population density, socioeconomic conditions, and mobility. The objective of the paper is to provide an updated literature review on geographical studies analysing the factors which influenced COVID-19 spreading. This literature review took into account not only the geographical aspects but also the COVID-19-related outcomes (infections and deaths) allowing to discern the potential influencing role of the geographic factors per type of outcome. A total of 112 scientific articles were selected, reviewed and categorized according to subject area, aim, country/region of study, considered geographic and COVID-19 variables, spatial and temporal units of analysis, methodologies, and main findings. Our literature review showed that territorial features may have played a role in determining the uneven geography of COVID-19; for instance, a certain agreement was found regarding the direct relationship between urbanization degree and COVID-19 infections. For what concerns climatic factors, temperature was the variable that correlated the best with COVID-19 infections. Together with climatic factors, socio-demographic ones were extensively taken into account. Most of the analysed studies agreed that population density and human mobility had a significant and direct relationship with COVID-19 infections and deaths. The analysis of the different approaches used to investigate the role of geographic factors in the spreading of the COVID-19 pandemic revealed that the significance/representativeness of the outputs is influenced by the scale considered due to the great spatial variability of geographic aspects. In fact, a more robust and significant association between geographic factors and COVID-19 was found by studies conducted at subnational or local scale rather than at country scale.

Development and Effectiveness of the School-Based Education Program for Coping With Particulate Matter

BACKGROUND

Adolescents are considered to be vulnerable to particulate matter (PM). This study aims to develop and verify the effectiveness of the "school-based education program for coping with particulate matter (SEPC_PM)." This program was designed by employing the health belief model.

METHODS

High school students between the ages of 15 and 18 in South Korea participated in the program. This study employed a nonequivalent control group pretest-posttest design. A total of 113 students participated in the study; of these, 56 students participated in the intervention group, and 57 in the control group. The intervention group received 8 intervention sessions the SEPC_PM over the course of 4 weeks.

RESULTS

After the completion of the program, the intervention group's knowledge about PM showed a statistically significant increase (t = 4.79, p < .001). The practice of engaging in health-managing behaviors to protect against PM also showed statistically significant improvement in the intervention group, with the greatest progress in practicing precaution when outdoors (t = 2.22, p = .029). No statistically significant changes were observed regarding other dependent variables. However, a subdomain of the variable of perceived self-efficacy for engaging in health-managing behaviors to protect against PM (degree of body cleansing after returning home) demonstrated a statistically significant increase in the intervention group (t = 1.99, p = .049).

CONCLUSIONS

The SEPC_PM may be proposed for incorporation into regular high school curricula to improve students' health by encouraging them to take necessary actions against PM.

Experimental and in silico evaluations of the possible molecular interaction between airborne particulate matter and SARS-CoV-2

During the early stage of the COVID-19 pandemic (winter 2020), the northern part of Italy has been significantly affected by viral infection compared to the rest of the country leading the scientific community to hypothesize that airborne particulate matter (PM) could act as a carrier for the SARS-CoV-2. To address this controversial issue, we first verified and demonstrated the presence of SARS-CoV-2 RNA genome on PM2.5 samples, collected in the city of Bologna (Northern Italy) in winter 2021. Then, we employed classical molecular dynamics (MD) simulations to investigate the possible recognition mechanism(s) between a newly modelled PM2.5 fragment and the SARS-CoV-2 Spike protein. The potential molecular interaction highlighted by MD simulations suggests that the glycans covering the upper Spike protein regions would mediate the direct contact with the PM2.5 carbon core surface, while a cloud of organic and inorganic PM2.5 components surround the glycoprotein with a network of non-bonded interactions resulting in up to 4769 total contacts. Moreover, a binding free energy of -207.2 ± 3.9 kcal/mol was calculated for the PM-Spike interface through the MM/GBSA method, and structural analyses also suggested that PM attachment does not alter the protein conformational dynamics. Although the association between the PM and SARS-CoV-2 appears plausible, this simulation does not assess whether these established interactions are sufficiently stable to carry the virus in the atmosphere, or whether the virion retains its infectiousness after the transport. While these key aspects should be verified by further experimental analyses, for the first time, this pioneering study gains insights into the molecular interactions between PM and SARS-CoV-2 Spike protein and will support further research aiming at clarifying the possible relationship between PM abundance and the airborne diffusion of viruses.

Impact of outdoor air pollution on severity and mortality in COVID-19 pneumonia

The relationship between exposure to air pollution and the severity of coronavirus disease 2019 (COVID-19) pneumonia and other outcomes is poorly understood. Beyond age and comorbidity, risk factors for adverse outcomes including death have been poorly studied. The main objective of our study was to examine the relationship between exposure to outdoor air pollution and the risk of death in patients with COVID-19 pneumonia using individual-level data. The secondary objective was to investigate the impact of air pollutants on gas exchange and systemic inflammation in this disease. This cohort study included 1548 patients hospitalised for COVID-19 pneumonia between February and May 2020 in one of four hospitals. Local agencies supplied daily data on environmental air pollutants (PM10, PM2.5, O3, NO2, NO and NOX) and meteorological conditions (temperature and humidity) in the year before hospital admission (from January 2019 to December 2019). Daily exposure to pollution and meteorological conditions by individual postcode of residence was estimated using geospatial Bayesian generalised additive models. The influence of air pollution on pneumonia severity was studied using generalised additive models which included: age, sex, Charlson comorbidity index, hospital, average income, air temperature and humidity, and exposure to each pollutant. Additionally, generalised additive models were generated for exploring the effect of air pollution on C-reactive protein (CRP) level and SpO2/FiO2 at admission. According to our results, both risk of COVID-19 death and CRP level increased significantly with median exposure to PM10, NO2, NO and NOX, while higher exposure to NO2, NO and NOX was associated with lower SpO2/FiO2 ratios. In conclusion, after controlling for socioeconomic, demographic and health-related variables, we found evidence of a significant positive relationship between air pollution and mortality in patients hospitalised for COVID-19 pneumonia. Additionally, inflammation (CRP) and gas exchange (SpO2/FiO2) in these patients were significantly related to exposure to air pollution.

Exploring the spatial pattern of community urban green spaces and COVID-19 risk in Wuhan based on a random forest model

Since 2019, COVID-19 has triggered a renewed investigation of the urban environment and disease outbreak. While the results have been inconsistent, it has been observed that the quantity of urban green spaces (UGS) is correlated with the risk of COVID-19. However, the spatial pattern has largely been ignored, especially on the community scale. In high-density communities where it is difficult to increase UGS quantity, UGS spatial pattern could be a crucial predictive variable. Thus, this study investigated the relative contribution of quantity and spatial patterns of UGS on COVID-19 risk at the community scale using a random forest (RF) regression model based on (n = 44) communities in Wuhan. Findings suggested that 8 UGS indicators can explain 35% of the risk of COVID-19, and the four spatial pattern metrics that contributed most were core, edge, loop, and branch whereas UGS quantity contributed least. The potential mechanisms between UGS and COVID-19 are discussed, including the influence of UGS on residents' social distance and environmental factors in the community. This study offers a new perspective on optimizing UGS for public health and sustainable city design to combat pandemics and inspire future research on the specific relationship between UGS spatial patterns and pandemics and therefore help establish mechanisms of UGS and pandemics.

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.

Linkages between COVID-19, solar UV radiation, and the Montreal Protocol

There are several connections between coronavirus disease 2019 (COVID-19), solar UV radiation, and the Montreal Protocol. Exposure to ambient solar UV radiation inactivates SARS-CoV-2, the virus responsible for COVID-19. An action spectrum describing the wavelength dependence of the inactivation of SARS-CoV-2 by UV and visible radiation has recently been published. In contrast to action spectra that have been assumed in the past for estimating the effect of UV radiation on SARS-CoV-2, the new action spectrum has a large sensitivity in the UV-A (315-400 nm) range. If this "UV-A tail" is correct, solar UV radiation could be much more efficient in inactivating the virus responsible for COVID-19 than previously thought. Furthermore, the sensitivity of inactivation rates to the total column ozone would be reduced because ozone absorbs only a small amount of UV-A radiation. Using solar simulators, the times for inactivating SARS-CoV-2 have been determined by several groups; however, many measurements are affected by poorly defined experimental setups. The most reliable data suggest that 90% of viral particles embedded in saliva are inactivated within ~ 7 min by solar radiation for a solar zenith angle (SZA) of 16.5° and within ~ 13 min for a SZA of 63.4°. Slightly longer inactivation times were found for aerosolised virus particles. These times can become considerably longer during cloudy conditions or if virus particles are shielded from solar radiation. Many publications have provided evidence of an inverse relationship between ambient solar UV radiation and the incidence or severity of COVID-19, but the reasons for these negative correlations have not been unambiguously identified and could also be explained by confounders, such as ambient temperature, humidity, visible radiation, daylength, temporal changes in risk and disease management, and the proximity of people to other people. Meta-analyses of observational studies indicate inverse associations between serum 25-hydroxy vitamin D (25(OH)D) concentration and the risk of SARS-CoV-2 positivity or severity of COVID-19, although the quality of these studies is largely low. Mendelian randomisation studies have not found statistically significant evidence of a causal effect of 25(OH)D concentration on COVID-19 susceptibility or severity, but a potential link between vitamin D status and disease severity cannot be excluded as some randomised trials suggest that vitamin D supplementation is beneficial for people admitted to a hospital. Several studies indicate significant positive associations between air pollution and COVID-19 incidence and fatality rates. Conversely, well-established cohort studies indicate no association between long-term exposure to air pollution and infection with SARS-CoV-2. By limiting increases in UV radiation, the Montreal Protocol has also suppressed the inactivation rates of pathogens exposed to UV radiation. However, there is insufficient evidence to conclude that the expected larger inactivation rates without the Montreal Protocol would have had tangible consequences on the progress of the COVID-19 pandemic.

Stratospheric ozone, UV radiation, and climate interactions

This assessment provides a comprehensive update of the effects of changes in stratospheric ozone and other factors (aerosols, surface reflectivity, solar activity, and climate) on the intensity of ultraviolet (UV) radiation at the Earth's surface. The assessment is performed in the context of the Montreal Protocol on Substances that Deplete the Ozone Layer and its Amendments and Adjustments. Changes in UV radiation at low- and mid-latitudes (0-60°) during the last 25 years have generally been small (e.g., typically less than 4% per decade, increasing at some sites and decreasing at others) and were mostly driven by changes in cloud cover and atmospheric aerosol content, caused partly by climate change and partly by measures to control tropospheric pollution. Without the Montreal Protocol, erythemal (sunburning) UV irradiance at northern and southern latitudes of less than 50° would have increased by 10-20% between 1996 and 2020. For southern latitudes exceeding 50°, the UV Index (UVI) would have surged by between 25% (year-round at the southern tip of South America) and more than 100% (South Pole in spring). Variability of erythemal irradiance in Antarctica was very large during the last four years. In spring 2019, erythemal UV radiation was at the minimum of the historical (1991-2018) range at the South Pole, while near record-high values were observed in spring 2020, which were up to 80% above the historical mean. In the Arctic, some of the highest erythemal irradiances on record were measured in March and April 2020. For example in March 2020, the monthly average UVI over a site in the Canadian Arctic was up to 70% higher than the historical (2005-2019) average, often exceeding this mean by three standard deviations. Under the presumption that all countries will adhere to the Montreal Protocol in the future and that atmospheric aerosol concentrations remain constant, erythemal irradiance at mid-latitudes (30-60°) is projected to decrease between 2015 and 2090 by 2-5% in the north and by 4-6% in the south due to recovering ozone. Changes projected for the tropics are ≤ 3%. However, in industrial regions that are currently affected by air pollution, UV radiation will increase as measures to reduce air pollutants will gradually restore UV radiation intensities to those of a cleaner atmosphere. Since most substances controlled by the Montreal Protocol are also greenhouse gases, the phase-out of these substances may have avoided warming by 0.5-1.0 °C over mid-latitude regions of the continents, and by more than 1.0 °C in the Arctic; however, the uncertainty of these calculations is large. We also assess the effects of changes in stratospheric ozone on climate, focusing on the poleward shift of climate zones, and discuss the role of the small Antarctic ozone hole in 2019 on the devastating "Black Summer" fires in Australia. Additional topics include the assessment of advances in measuring and modeling of UV radiation; methods for determining personal UV exposure; the effect of solar radiation management (stratospheric aerosol injections) on UV radiation relevant for plants; and possible revisions to the vitamin D action spectrum, which describes the wavelength dependence of the synthesis of previtamin D3 in human skin upon exposure to UV radiation.

Long-Term Exposure to Ambient Air Pollution and Mortality among Four Million COVID-19 Cases in Italy: The EpiCovAir Study

BACKGROUND

The role of chronic exposure to ambient air pollutants in increasing COVID-19 fatality is still unclear.

OBJECTIVES

The study aimed to investigate the association between long-term exposure to air pollutants and mortality among 4 million COVID-19 cases in Italy.

METHODS

We obtained individual records of all COVID-19 cases identified in Italy from February 2020 to June 2021. We assigned 2016-2019 mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10μm (PM10), PM with aerodynamic diameter ≤2.5μm (PM2.5), and nitrogen dioxide (NO2) to each municipality (n=7,800) as estimates of chronic exposures. We applied a principal component analysis (PCA) and a generalized propensity score (GPS) approach to an extensive list of area-level covariates to account for major determinants of the spatial distribution of COVID-19 case-fatality rates. Then, we applied generalized negative binomial models matched on GPS, age, sex, province, and month. As additional analyses, we fit separate models by pandemic periods, age, and sex; we quantified the numbers of COVID-19 deaths attributable to exceedances in annual air pollutant concentrations above predefined thresholds; and we explored associations between air pollution and alternative outcomes of COVID-19 severity, namely hospitalizations or accesses to intensive care units.

RESULTS

We analyzed 3,995,202 COVID-19 cases, which generated 124,346 deaths. Overall, case-fatality rates increased by 0.7% [95% confidence interval (CI): 0.5%, 0.9%], 0.3% (95% CI: 0.2%, 0.5%), and 0.6% (95% CI: 0.5%, 0.8%) per 1 μg/m3 increment in PM2.5, PM10, and NO2, respectively. Associations were higher among elderly subjects and during the first (February 2020-June 2020) and the third (December 2020-June 2021) pandemic waves. We estimated ∼8% COVID-19 deaths were attributable to pollutant levels above the World Health Organization 2021 air quality guidelines.

DISCUSSION

We found suggestive evidence of an association between long-term exposure to ambient air pollutants with mortality among 4 million COVID-19 cases in Italy. https://doi.org/10.1289/EHP11882.

Modeling the Climatic Suitability of COVID-19 Cases in Brazil

Studies have shown that climate may affect the distribution of coronavirus disease (COVID-19) and its incidence and fatality rates. Here, we applied an ensemble niche modeling approach to project the climatic suitability of COVID-19 cases in Brazil. We estimated the cumulative incidence, mortality rate, and fatality rate of COVID-19 between 2020 and 2021. Seven statistical algorithms (MAXENT, MARS, RF, FDA, CTA, GAM, and GLM) were selected to model the climate suitability for COVID-19 cases from diverse climate data, including temperature, precipitation, and humidity. The annual temperature range and precipitation seasonality showed a relatively high contribution to the models, partially explaining the distribution of COVID-19 cases in Brazil based on the climatic suitability of the territory. We observed a high probability of climatic suitability for high incidence in the North and South regions and a high probability of mortality and fatality rates in the Midwest and Southeast regions. Despite the social, viral, and human aspects regulating COVID-19 cases and death distribution, we suggest that climate may play an important role as a co-factor in the spread of cases. In Brazil, there are regions with a high probability that climatic suitability will contribute to the high incidence and fatality rates of COVID-19 in 2020 and 2021.

Causality and dynamic spillover effects of megacities on regional industrial pollution reduction

Regional economic power and local environmental policies have a substantial impact on pollution reduction in urban agglomerations (UAs); however, whether megacities in UAs exert spillover effects of pollution reduction on surrounding cities remains unknown. This study presents a causal analytic framework to evaluate the spillover effects of megacities on regional industrial pollution reduction in three major UAs in China between 2005 and 2016. The interaction between industrial pollution reduction and infrastructure investment indicators was also examined. Results indicated a good fit for spatial spillover of sulfur dioxide reduction (SR) in the Pearl River Delta (PRD) and Yangtze River Delta (YRD) but not in the Beijing-Hebei-Tianjin cluster (JJJ). Spatial spillover of dust reduction (DR) was evident in the PRD and JJJ but not the YRD. Spatial analysis showed that infrastructure investment indicators, at megacity and UA levels, had short-term spillover effects on surrounding cities for DR but not SR. However, spatial spillover effects, at both the city and UA levels, were substantial over the long term. In addition, the results of the spatial-time lag analysis suggest a linear relationship between pollution control-related infrastructure investment indicators and long-term pollution reduction. This study provides new information regarding the spatial spillover effects of megacities on regional industrial pollution reduction in UAs.

Global Human Threat: The Potential Synergism between Mercury Intoxication and COVID-19

The COVID-19 pandemic affected billions of people worldwide, and exposure to toxic metals has emerged as an important risk factor for COVID-19 severity. Mercury is currently ranked as the third toxic substance of global concern for human health, and its emissions to the atmosphere have increased globally. Both COVID-19 and mercury exposure present a high prevalence in similar regions: East and Southeast Asia, South America and Sub-Saharan Africa. Since both factors represent a multiorgan threat, a possible synergism could be exacerbating health injuries. Here, we discuss key aspects in mercury intoxication and SARS-CoV-2 infection, describing the similarities shared in clinical manifestations (especially neurological and cardiovascular outcomes), molecular mechanisms (with a hypothesis in the renin-angiotensin system) and genetic susceptibility (mainly by apolipoprotein E, paraoxonase 1 and glutathione family genes). Literature gaps on epidemiological data are also highlighted, considering the coincident prevalence. Furthermore, based on the most recent evidence, we justify and propose a case study of the vulnerable populations of the Brazilian Amazon. An understanding of the possible adverse synergism between these two factors is crucial and urgent for developing future strategies for reducing disparities between developed and underdeveloped/developing countries and the proper management of their vulnerable populations, particularly considering the long-term sequelae of COVID-19.

Substantial Changes in Selected Volatile Organic Compounds (VOCs) and Associations with Health Risk Assessments in Industrial Areas during the COVID-19 Pandemic

During the COVID-19 pandemic, governments in many countries worldwide, including India, imposed several restriction measures, including lockdowns, to prevent the spread of the infection. COVID-19 lockdowns led to a reduction in gaseous and particulate pollutants in ambient air. In the present study, we investigated the substantial changes in selected volatile organic compounds (VOCs) after the outbreak of the coronavirus pandemic and associations with health risk assessments in industrial areas. VOC data from 1 January 2019 to 31 December 2021 were collected from the Central Pollution Control Board (CPCB) website, to identify percentage changes in VOC levels before, during, and after COVID-19. The mean TVOC levels at all monitoring stations were 47.22 ± 30.15, 37.19 ± 37.19, and 32.81 ± 32.81 µg/m³ for 2019, 2020, and 2021, respectively. As a result, the TVOC levels gradually declined in consecutive years due to the pandemic in India. The mean TVOC levels at all monitoring stations declined from 9 to 61% during the pandemic period as compared with the pre-pandemic period. In the current study, the T/B ratio values ranged from 2.16 (PG) to 26.38 (NL), which indicated that the major pollutant contributors were traffic and non-traffic sources during the pre-pandemic period. The present findings indicated that TVOC levels had positive but low correlations with SR, BP, RF, and WD, with correlation coefficients (r) of 0.034, 0.118, 0.012, and 0.007, respectively, whereas negative correlations were observed with AT and WS, with correlation coefficients (r) of -0.168 and -0.150, respectively. The lifetime cancer risk (LCR) value for benzene was reported to be higher in children, followed by females and males, for the pre-pandemic, pandemic, and post-pandemic periods. A nationwide scale-up of this study's findings might be useful in formulating future air pollution reduction policies associated with a reduction in health risk factors. Furthermore, the present study provides baseline data for future studies on the impacts of anthropogenic activities on the air quality of a region.

Developmental Programming in Animal Models: Critical Evidence of Current Environmental Negative Changes

The Developmental Origins of Health and Disease (DOHaD) approach answers questions surrounding the early events suffered by the mother during reproductive stages that can either partially or permanently influence the developmental programming of children, predisposing them to be either healthy or exhibit negative health outcomes in adulthood. Globally, vulnerable populations tend to present high obesity rates, including among school-age children and women of reproductive age. In addition, adults suffer from high rates of diabetes, hypertension, cardiovascular, and other metabolic diseases. The increase in metabolic outcomes has been associated with the combination of maternal womb conditions and adult lifestyle-related factors such as malnutrition and obesity, smoking habits, and alcoholism. However, to date, "new environmental changes" have recently been considered negative factors of development, such as maternal sedentary lifestyle, lack of maternal attachment during lactation, overcrowding, smog, overurbanization, industrialization, noise pollution, and psychosocial stress experienced during the current SARS-CoV-2 pandemic. Therefore, it is important to recognize how all these factors impact offspring development during pregnancy and lactation, a period in which the subject cannot protect itself from these mechanisms. This review aims to introduce the importance of studying DOHaD, discuss classical programming studies, and address the importance of studying new emerging programming mechanisms, known as actual lifestyle factors, during pregnancy and lactation.

Impact of Air Pollution and COVID-19 Infection on Periprocedural Death in Patients with Acute Coronary Syndrome

Air pollution and COVID-19 infection affect the pathogenesis of cardiovascular disease. The impact of these factors on the course of ACS treatment is not well defined. The purpose of this study was to evaluate the effects of air pollution, COVID-19 infection, and selected clinical factors on the occurrence of perioperative death in patients with acute coronary syndrome (ACS) by developing a neural network model. This retrospective study included 53,076 patients with ACS from the ORPKI registry (National Registry of Invasive Cardiology Procedures) including 2395 COVID-19 (+) patients and 34,547 COVID-19 (-) patients. The neural network model developed included 57 variables, had high performance in predicting perioperative patient death, and had an error risk of 0.03%. Based on the analysis of the effect of permutation on the variable, the variables with the greatest impact on the prediction of perioperative death were identified to be vascular access, critical stenosis of the left main coronary artery (LMCA) or left anterior descending coronary artery (LAD). Air pollutants and COVID-19 had weaker effects on end-point prediction. The neural network model developed has high performance in predicting the occurrence of perioperative death. Although COVID-19 and air pollutants affect the prediction of perioperative death, the key predictors remain vascular access and critical LMCA or LAD stenosis.

Spike in pollution to ignite the bursting of COVID-19 second wave is more dangerous than spike of SAR-CoV-2 under environmental ignorance in long term: a review

Specific areas in many countries such as Italy, India, China, Brazil, Germany and the USA have witnessed that air pollution increases the risk of COVID-19 severity as particulate matters transmit the virus SARS-CoV-2 and causes high expression of ACE2, the receptor for spike protein of the virus, especially under exposure to NO2, SO2 and NOx emissions. Wastewater-based epidemiology of COVID-19 is also noticed in many countries such as the Netherlands, the USA, Paris, France, Australia, Spain, Italy, Switzerland China, India and Hungary. Soil is also found to be contaminated by the RNA of SARS-CoV-2. Activities including defecation and urination by infected people contribute to the source for soil contamination, while release of wastewater containing cough, urine and stool of infected people from hospitals and home isolation contributes to the source of SARS-CoV-2 RNA in both water and soil. Detection of the virus early before the outbreak of the disease supports this fact. Based on this information, spike in pollution is found to be more dangerous in long-term than the spike protein of SARS-CoV-2. It is because the later one may be controlled in future within months or few years by vaccination and with specific drugs, but the former one provides base for many diseases including the current and any future pandemics. Although such predictions and the positive effects of SARS-CoV-2 on environment was already forecasted after the first wave of COVID-19, the learnt lesson as spotlight was not considered as one of the measures for which 2nd wave has quickly hit the world.

Proteolysis and Deficiency of α1-Proteinase Inhibitor in SARS-CoV-2 Infection

The SARS-CoV-2 pandemic had stimulated the emergence of numerous publications on the α1-proteinase inhibitor (α1-PI, α1-antitrypsin), especially when it was found that the regions of high mortality corresponded to the regions with deficient α1-PI alleles. By analogy with the data obtained in the last century, when the first cause of the genetic deficiency of α1-antitrypsin leading to elastase activation in pulmonary emphysema was proven, it can be supposed that proteolysis hyperactivation in COVID-19 may be associated with the impaired functions of α1-PI. The purpose of this review was to systematize the scientific data and critical directions for translational studies on the role of α1-PI in SARS-CoV-2-induced proteolysis hyperactivation as a diagnostic marker and a therapeutic target. This review describes the proteinase-dependent stages of viral infection: the reception and penetration of the virus into a cell and the imbalance of the plasma aldosterone-angiotensin-renin, kinin, and blood clotting systems. The role of ACE2, TMPRSS, ADAM17, furin, cathepsins, trypsin- and elastase-like serine proteinases in the virus tropism, the activation of proteolytic cascades in blood, and the COVID-19-dependent complications is considered. The scientific reports on α1-PI involvement in the SARS-CoV-2-induced inflammation, the relationship with the severity of infection and comorbidities were analyzed. Particular attention is paid to the acquired α1-PI deficiency in assessing the state of patients with proteolysis overactivation and chronic non-inflammatory diseases, which are accompanied by the risk factors for comorbidity progression and the long-term consequences of COVID-19. Essential data on the search and application of protease inhibitor drugs in the therapy for bronchopulmonary and cardiovascular pathologies were analyzed. The evidence of antiviral, anti-inflammatory, anticoagulant, and anti-apoptotic effects of α1-PI, as well as the prominent data and prospects for its application as a targeted drug in the SARS-CoV-2 acquired pneumonia and related disorders, are presented.

A review about COVID-19 in the MENA region: environmental concerns and machine learning applications

Coronavirus disease 2019 (COVID-19) has delayed global economic growth, which has affected the economic life globally. On the one hand, numerous elements in the environment impact the transmission of this new coronavirus. Every country in the Middle East and North Africa (MENA) area has a different population density, air quality and contaminants, and water- and land-related conditions, all of which influence coronavirus transmission. The World Health Organization (WHO) has advocated fast evaluations to guide policymakers with timely evidence to respond to the situation. This review makes four unique contributions. One, many data about the transmission of the new coronavirus in various sorts of settings to provide clear answers to the current dispute over the virus's transmission were reviewed. Two, highlight the most significant application of machine learning to forecast and diagnose severe acute respiratory syndrome coronavirus (SARS-CoV-2). Three, our insights provide timely and accurate information along with compelling suggestions and methodical directions for investigators. Four, the present study provides decision-makers and community leaders with information on the effectiveness of environmental controls for COVID-19 dissemination.

Lockdown Amid COVID-19 Ascendancy over Ambient Particulate Matter Pollution Anomaly

Air is a diverse mixture of gaseous and suspended solid particles. Several new substances are being added to the air daily, polluting it and causing human health effects. Particulate matter (PM) is the primary health concern among these air toxins. The World Health Organization (WHO) addressed the fact that particulate pollution affects human health more severely than other air pollutants. The spread of air pollution and viruses, two of our millennium's most serious concerns, have been linked closely. Coronavirus disease 2019 (COVID-19) can spread through the air, and PM could act as a host to spread the virus beyond those in close contact. Studies on COVID-19 cover diverse environmental segments and become complicated with time. As PM pollution is related to everyday life, an essential awareness regarding PM-impacted COVID-19 among the masses is required, which can help researchers understand the various features of ambient particulate pollution, particularly in the era of COVID-19. Given this, the present work provides an overview of the recent developments in COVID-19 research linked to ambient particulate studies. This review summarizes the effect of the lockdown on the characteristics of ambient particulate matter pollution, the transmission mechanism of COVID-19, and the combined health repercussions of PM pollution. In addition to a comprehensive evaluation of the implementation of the lockdown, its rationales-based on topographic and socioeconomic dynamics-are also discussed in detail. The current review is expected to encourage and motivate academics to concentrate on improving air quality management and COVID-19 control.

Statistical modeling approach for PM10 prediction before and during confinement by COVID-19 in South Lima, Perú

A total of 188,859 meteorological-PM$$_{10}$$ 10 data validated before (2019) and during the COVID-19 pandemic (2020) were used. In order to predict PM$$_{10}$$ 10 in two districts of South Lima in Peru, hourly, daily, monthly and seasonal variations of the data were analyzed. Principal Component Analysis (PCA) and linear/nonlinear modeling were applied. The results showed the highest annual average PM$$_{10}$$ 10 for San Juan de Miraflores (SJM) (PM$$_{10}$$ 10 -SJM: 78.7 $$\upmu$$ μ g/m$$^{3}$$ 3 ) and the lowest in Santiago de Surco (SS) (PM$$_{10}$$ 10 -SS: 40.2 $$\upmu$$ μ g/m$$^{3}$$ 3 ). The PCA showed the influence of relative humidity (RH)-atmospheric pressure (AP)-temperature (T)/dew point (DP)-wind speed (WS)-wind direction (WD) combinations. Cool months with higher humidity and atmospheric instability decreased PM$$_{10}$$ 10 values in SJM and warm months increased it, favored by thermal inversion (TI). Dust resuspension, vehicular transport and stationary sources contributed more PM$$_{10}$$ 10 at peak times in the morning and evening. The Multiple linear regression (MLR) showed the best correlation (r = 0.6166), followed by the three-dimensional model LogAP-LogWD-LogPM$$_{10}$$ 10 (r = 0.5753); the RMSE-MLR (12.92) exceeded that found in the 3D models (RMSE $$<0.3$$ < 0.3 ) and the NSE-MLR criterion (0.3804) was acceptable. PM$$_{10}$$ 10 prediction was modeled using the algorithmic approach in any scenario to optimize urban management decisions in times of pandemic.

Effects of meteorological factors and air pollutants on the incidence of COVID-19 in South Korea

Air pollution and meteorological factors can exacerbate susceptibility to respiratory viral infections. To establish appropriate prevention and intervention strategies, it is important to determine whether these factors affect the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, this study examined the effects of sunshine, temperature, wind, and air pollutants including sulfur dioxide (SO₂), carbon monoxide (CO), ozone (O₃), nitrogen dioxide (NO₂), particulate matter ≤2.5 μm (PM_2.5), and particulate matter ≤10 μm (PM₁₀) on the age-standardized incidence ratio of coronavirus disease (COVID-19) in South Korea between January 2020 and April 2020. Propensity score weighting was used to randomly select observations into groups according to whether the case was cluster-related, to reduce selection bias. Multivariable logistic regression analyses were used to identify factors associated with COVID-19 incidence. Age 60 years or over (odds ratio [OR], 1.29; 95% CI, 1.24-1.35), exposure to ambient air pollutants, especially SO₂ (OR, 5.19; 95% CI, 1.13-23.9) and CO (OR, 1.17; 95% CI, 1.07-1.27), and non-cluster infection (OR, 1.28; 95% CI, 1.24-1.32) were associated with SARS-CoV-2 infection. To manage and control COVID-19 effectively, further studies are warranted to confirm these findings and to develop appropriate guidelines to minimize SARS-CoV-2 transmission.

Exploring the impact of air pollution on COVID-19 admitted cases

In urban areas, air pollution is one of the most serious global environmental issues. Using time-series approaches, this study looked into the validity of the relationship between air pollution and COVID-19 hospitalization. This time series research was carried out in the state of Kuwait; stationarity test, cointegration test, Granger causality and stability test, and test on multivariate time-series using the Vector Error Correction Model (VECM) technique. The findings reveal that the concentration rate of air pollutants ($$\hbox {O}_3$$ O 3 , $$\hbox {SO}_2$$ SO 2 , $$\hbox {NO}_2$$ NO 2 , $$\hbox {CO}$$ CO , and $$\hbox {PM}_{10}$$ PM 10 ) has an effect on COVID-19 admitted cases via Granger-cause. The Granger causation test shows that the concentration rate of air pollutants ($$\hbox {O}_3$$ O 3 , $$\hbox {PM}_{10}$$ PM 10 , $$\hbox {NO}_2$$ NO 2 , temperature and wind speed) influences and predicts the COVID-19 admitted cases. The findings suggest that sulfur dioxide ($$\hbox {SO}_2$$ SO 2 ), $$\hbox {NO}_2$$ NO 2 , temperature, and wind speed induce an increase in COVID-19 admitted cases in the short term according to VECM analysis. The evidence of a positive long-run association between COVID-19 admitted cases and environmental air pollution might be shown in the cointegration test and the VECM. There is an affirmation that the usage of air pollutants ($$\hbox {O}_3$$ O 3 , $$\hbox {SO}_2$$ SO 2 , $$\hbox {NO}_2$$ NO 2 , $$\hbox {CO}$$ CO , and $$\hbox {PM}_{10}$$ PM 10 ) has a significant impact on COVID-19-admitted cases’ prediction and its explained about 24% of increasing COVID-19 admitted cases in Kuwait.

Recent Insights into Particulate Matter (PM2.5)-Mediated Toxicity in Humans: An Overview

Several epidemiologic and toxicological studies have commonly viewed ambient fine particulate matter (PM_2.5), defined as particles having an aerodynamic diameter of less than 2.5 µm, as a significant potential danger to human health. PM_2.5 is mostly absorbed through the respiratory system, where it can infiltrate the lung alveoli and reach the bloodstream. In the respiratory system, reactive oxygen or nitrogen species (ROS, RNS) and oxidative stress stimulate the generation of mediators of pulmonary inflammation and begin or promote numerous illnesses. According to the most recent data, fine particulate matter, or PM_2.5, is responsible for nearly 4 million deaths globally from cardiopulmonary illnesses such as heart disease, respiratory infections, chronic lung disease, cancers, preterm births, and other illnesses. There has been increased worry in recent years about the negative impacts of this worldwide danger. The causal associations between PM_2.5 and human health, the toxic effects and potential mechanisms of PM_2.5, and molecular pathways have been described in this review.

[Proteolysis and deficiency of α1-proteinase inhibitor in SARS-CoV-2 infection]

The SARS-CoV-2 pandemia had stimulated the numerous publications emergence on the α1-proteinase inhibitor (α1-PI, α1-antitrypsin), primarily when it was found that high mortality in some regions corresponded to the regions with deficient α1-PI alleles. By analogy with the last century's data, when the root cause of the α1-antitrypsin, genetic deficiency leading to the elastase activation in pulmonary emphysema, was proven. It is evident that proteolysis hyperactivation in COVID-19 may be associated with α1-PI impaired functions. The purpose of this review is to systematize scientific data, critical directions for translational studies on the role of α1-PI in SARS-CoV-2-induced proteolysis hyperactivation as a diagnostic marker and a target in therapy. This review describes the proteinase-dependent stages of a viral infection: the reception and virus penetration into the cell, the plasma aldosterone-angiotensin-renin, kinins, blood clotting systems imbalance. The ACE2, TMPRSS, ADAM17, furin, cathepsins, trypsin- and elastase-like serine proteinases role in the virus tropism, proteolytic cascades activation in blood, and the COVID-19-dependent complications is presented. The analysis of scientific reports on the α1-PI implementation in the SARS-CoV-2-induced inflammation, the links with the infection severity, and comorbidities were carried out. Particular attention is paid to the acquired α1-PI deficiency in assessing the patients with the proteolysis overactivation and chronic non-inflammatory diseases that are accompanied by the risk factors for the comorbidities progression, and the long-term consequences of COVID-19 initiation. Analyzed data on the search and proteases inhibitory drugs usage in the bronchopulmonary cardiovascular pathologies therapy are essential. It becomes evident the antiviral, anti-inflammatory, anticoagulant, anti-apoptotic effect of α1-PI. The prominent data and prospects for its application as a targeted drug in the SARS-CoV-2 acquired pneumonia and related disorders are presented.

A Longitudinal Research on the Distribution and Prognosis of Intracerebral Hemorrhage During the COVID-19 Pandemic

Purpose

Globally, intracerebral hemorrhage (ICH) is a common cerebrovascular disease. At the beginning of 2020, due to the coronavirus disease 2019 (COVID-19) pandemic, the allocation of medical resources and the patient treatment and referrals were affected to varying degrees. We aimed to determine the characteristics and prognoses and associated factors of patients with ICH.

Patients and Methods

The baseline demographic characteristics and ICH outcomes were compared between patients diagnosed with ICH between January and June 2020 (the 2020 group) and between January and June 2019 (the 2019 group). COVID-19 positive patients were excluded from the study. A 30-day data from patients in the 2019 and 2020 groups were analyzed to create survival curves for these patients. We also used regression models to identify the significant determinants of poor outcomes [modified Rankin score (mRS): 3-6] and death.

Results

The number of patients diagnosed with ICH was slightly lower in the 2020 group (n = 707) than in the 2019 group (n = 719). During the lockdown period (February 2020), the admission rates for ICH decreased greatly by 35.1%. The distribution of the patients' domicile (P = 0.002) and the mRS (P < 0.001) differed significantly between the years. The survival curve revealed that the highest risk of death was in the acute stage (especially in the first 5 days) of ICH. At 30 days, mortality was 19.8% in February 2019 and 29.4% in February 2020 (P = 0.119). Multivariate analysis revealed age, baseline mRS, postoperative complications, massive brainstem hemorrhage, and creatinine as factors significantly associated with poor outcomes and death following ICH. Neurosurgery and massive supratentorial hemorrhage were only correlated with the risk of death.

Conclusion

During the lockdown period, the COVID-19 pandemic caused a decrease in the admission rates and severe conditions at admission due to strict traffic constraints for infection control. This led to high mortality and disability in patients with ICH. It is necessary to ensure an effective green channel and allocate adequate medical resources for patients to receive timely treatment and neurosurgery.

Lower COVID-19 Incidence in Low-Continentality West-Coast Areas of Europe

In March 2020, the first known cases of COVID-19 occurred in Europe. Subsequently, the pandemic developed a seasonal pattern. The incidence of COVID-19 comprises spatial heterogeneity and seasonal variations, with lower and/or shorter peaks resulting in lower total incidence and higher and/or longer peaks resulting higher total incidence. The reason behind this phenomena is still unclear. Unraveling factors that explain why certain places have higher versus lower total COVID-19 incidence can help health decision makers understand and plan for future waves of the pandemic. We test whether differences in the total incidence of COVID-19 within five European countries (Norway, Sweden, Germany, Italy, and Spain), correlate with two environmental factors: the Köppen-Geiger climate zones and the Continentality Index, while statistically controlling for crowding. Our results show that during the first 16 months of the pandemic (March 2020 to July 2021), climate zones with larger annual differences in temperature and annually distributed precipitation show a higher total incidence than climate zones with smaller differences in temperature and dry seasons. This coincides with lower continentality values. Total incidence increases with continentality, up to a Continentality Index value of 19, where a peak is reached in the semicontinental zone. Low continentality (high oceanic influence) appears to be a strong suppressing factor for COVID-19 spread. The incidence in our study area is lowest at open low continentality west coast areas.

Influence of meteorological patterns on the 2020 COVID-19 pandemic in the Mexico City region

Meteorology is a critical factor affecting respiratory infectious diseases such as MERS, SARS, and influenza, but its effect on the spread of the COVID-19 disease remains controversial. Nevertheless, since the infected people cough-jets produce plumes of droplets and aerosols that can travel for several meters in the atmosphere, the possible influence of wind circulation and atmospheric turbulence on the infectious plume's fate cannot be ignored. This paper applied cluster analysis for identifying the near surface wind circulation patterns and associated temperature and humidity distributions in the Mexico City Metropolitan Area (MCMA), then their influence on the spread of the COVID-19 disease during the 2020 pandemic was discussed. Meteorology data and daily numbers of confirmed COVID-19 infections were obtained from public sources. An intense infection activity occurred from October to December 2020, and notable spreading of the disease toward the southwest and south MCMA was observed. In the same period, temperature and humidity conditions that could favor the virus stability and replication were detected in the same sectors, besides 60% of the wind observations revealed considerable northerly components. These findings suggested the existence of correlations between both phenomena. For assessing the possible relationship, the Pearson coefficients between the daily confirmed infections and the temperature and inward flux were estimated, and values from -0.32 to -0.55 and 0.62 to 0.70 were obtained. Correlation was negligible for relative humidity. Multilinear regression for the daily infections in response to the meteorological variables produced coefficients of determination from 0.3839 to 0.6138. Because of its implications for public health, this topic deserves a more in-depth investigation.

Multispecies entanglements in the virosphere: Rethinking the Anthropocene in light of the 2019 coronavirus outbreak

In this essay, we reevaluate the 2019 outbreak of a novel coronavirus (SARS-CoV-2) from the perspective of multispecies entanglements. It is argued that anthropogenic alterations in the biosphere will most likely accelerate the rate of multispecies pandemics in the Anthropocene. Using a textual analysis approach of anthropological and historical sources on the example of coronaviruses and live animal markets in China, we trace how the virosphere of wild animals from tropical regions comes into contact with the virosphere of humans and farmed animals in highly industrialized landscapes. We suggest that adopting a multispecies perspective on viruses can allow them to be understood as living processes that interact with other species in a realm called the virosphere. The rate at which novel infectious diseases are transmitted by bacteria and viruses has increased in recent decades. We argue that this is caused by side effects of the Anthropocene, such as deforestation, the surge in population growth and density, and anthropogenic climate change, which give rise to an increased number of unusual encounters between humans, nonhuman companion species, and wild animals. In this way, the virospheres of host organisms, which were formerly partly isolated, are allowed to converge and freely exchange infectious diseases, leading to a more homogenized virosphere. As anthropogenic alterations are set to continue in the future, we suggest that multispecies pandemics will likely increase in the following decades.

"SARS-CoV-2 is transmitted by particulate air pollution": Misinterpretations of statistical data, skewed citation practices, and misuse of specific terminology spreading the misconception

In epidemiology, there are still outdated myths associated with the spread of respiratory infections. Recently, we have witnessed the origination of a new misconception, to the effect that SARS-CoV-2 is transmitted in the open air by way of particulate air pollution (atmospheric particulate matter (PM)). There is no evidence to support the idea behind this misconception. Nevertheless, more and more people are involved in animated debate and the number of studies concerning atmospheric PM as a carrier of SARS-CoV-2 is growing rapidly. In this work, the origin of the misconception was investigated, and the published papers which have contributed to the spread of this myth were analyzed. The results show that the following factors lie behind the origin and spread of the misconception: a) The specific terminology is not always clearly defined or consistently used by scientists. In particular, the terms 'particulate matter', 'atmospheric aerosol particles', 'air pollutants', and 'atmospheric aerosols' need to be clarified, and besides they are often equated to 'infectious aerosols', 'virus-bearing aerosols', 'bio-aerosols', 'virus-laden particles', 'respiratory aerosol/droplets', and 'droplet nuclei'. b) Authors misinterpret statistical data and information from other sources. Interpretation of the correlation between PM levels and the increasing incidence and severity of COVID-19 infection, is often changed from "PM may reflect the indirect action of certain atmospheric conditions that maintain infectious nuclei suspended for prolonged periods, parameters that also act on atmospheric pollutants" to "PM could cause an increase in infectious droplets/aerosols containing SARS-CoV-2." This is a dramatic change to the meaning. Moreover, it is often not taken into account that PM may reflect activities in areas with high population density and this population density at the same time contributes to the spread COVID-19. c) Skewed citation practices. Many authors cite a hypothetical conclusion from an original study, then other authors cite the papers of these authors as primary sources. This practice leads to the effect that there are many witnesses to a 'phenomenon' that did not ever occur. Thus, the terminology used in interdisciplinary communications should be more nuanced and defined precisely. Authors should be more careful when citing unconfirmed data (and hypotheses) as well as in interpreting statistical data so as to avoid confusion and spreading false information. This is especially important now in the era of the COVID-19 pandemic.

Long-term exposure to fine particulate matter air pollution: An ecological study of its effect on COVID-19 cases and fatality in Germany

BACKGROUND

COVID-19 is a lung disease, and there is medical evidence that air pollution is one of the external causes of lung diseases. Fine particulate matter is one of the air pollutants that damages pulmonary tissue. The combination of the coronavirus and fine particulate matter air pollution may exacerbate the coronavirus' effect on human health.

RESEARCH QUESTION

This paper considers whether the long-term concentration of fine particulate matter of different sizes changes the number of detected coronavirus infections and the number of COVID-19 fatalities in Germany.

STUDY DESIGN

Data from 400 German counties for fine particulate air pollution from 2002 to 2020 are used to measure the long-term impact of air pollution. Kriging interpolation is applied to complement data gaps. With an ecological study, the correlation between average particulate matter air pollution and COVID-19 cases, as well as fatalities, are estimated with OLS regressions. Thereby, socioeconomic and demographic covariates are included.

MAIN FINDINGS

An increase in the average long-term air pollution of 1 μg/m3 particulate matter PM2.5 is correlated with 199.46 (SD = 29.66) more COVID-19 cases per 100,000 inhabitants in Germany. For PM10 the respective increase is 52.38 (SD = 12.99) more cases per 100,000 inhabitants. The number of COVID-19 deaths were also positively correlated with PM2.5 and PM10 (6.18, SD = 1.44, respectively 2.11, SD = 0.71, additional COVID-19 deaths per 100,000 inhabitants).

CONCLUSION

Long-term fine particulate air pollution is suspected as causing higher numbers of COVID-19 cases. Higher long-term air pollution may even increase COVID-19 death rates. We find that the results of the correlation analysis without controls are retained in a regression analysis with controls for relevant confounding factors. Nevertheless, additional epidemiological investigations are required to test the causality of particulate matter air pollution for COVID-19 cases and the severity.

Association between air pollution and COVID-19 mortality and morbidity

Coronavirus disease (COVID-19) pandemic is affecting the world unevenly. One of the highest numbers of cases were recorded in the most polluted regions worldwide. The risk factors for severe COVID-19 include diabetes, cardiovascular, and respiratory diseases. It has been known that the same disease might be worsened by chronic exposure to air pollution. The study aimed to determine whether long-term average exposure to air pollution is associated with an increased risk of COVID-19 cases and deaths in Poland. The cumulative number of COVID-19 cases and deaths for each voivodeship (the main administrative level of jurisdictions) in Poland were collected from March 4, 2020, to May 15, 2020. Based on the official data published by Chief Inspectorate of Environmental Protection voivodeship-level long-term exposure to main air pollution: PM2.5, PM10, NO2, SO2, O3 (averaged from 2013 to 2018) was established. There were statistically significant correlation between COVID-19 cases (per 100,000 population) and annual average concentration of PM2.5 (R2 = 0.367, p = 0.016), PM10 (R2 = 0.415, p = 0.009), SO2 (R2 = 0.489, p = 0.003), and O3 (R2 = 0.537, p = 0.0018). Moreover, COVID-19 deaths (per 100,000 population) were associated with annual average concentration of PM2.5 (R2 = 0.290, p = 0.038), NO2 (R2 = 0.319, p = 0.028), O3 (R2 = 0.452, p = 0.006). The long-term exposure to air pollution, especially PM2.5, PM10, SO2, NO2, O3 seems to play an essential role in COVID-19 prevalence and mortality. Long-term exposure to air pollution might increase the susceptibility to the infection, exacerbates the severity of SARS-CoV-2 infections, and worsens the patients' prognosis. The study provides generalized and possible universal trends. Detailed analyzes of the phenomenon dedicated to a given region require taking into account data on comorbidities and socioeconomic variables as well as information about the long-term exposure to air pollution and COVID-19 cases and deaths at smaller administrative level of jurisdictions (community or at least district level).

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.

Assessing the impact of air pollution and climate seasonality on COVID-19 multiwaves in Madrid, Spain

While the COVID-19 pandemic is still in progress, being under the fifth COVID-19 wave in Madrid, over more than one year, Spain experienced a four wave pattern. The transmission of SARS-CoV-2 pathogens in Madrid metropolitan region was investigated from an urban context associated with seasonal variability of climate and air pollution drivers. Based on descriptive statistics and regression methods of in-situ and geospatial daily time series data, this study provides a comparative analysis between COVID-19 waves incidence and mortality cases in Madrid under different air quality and climate conditions. During analyzed period 1 January 2020-1 July 2021, for each of the four COVID-19 waves in Madrid were recorded anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere and favorable stability conditions for COVID-19 disease fast spreading. As airborne microbial temporal pattern is most affected by seasonal changes, this paper found: 1) a significant negative correlation of air temperature, Planetary Boundary Layer height, and surface solar irradiance with daily new COVID-19 incidence and deaths; 2) a similar mutual seasonality with climate variables of the first and the fourth COVID-waves from spring seasons of 2020 and 2021 years. Such information may help the health decision makers and public plan for the future.

The impact of air pollution on COVID-19 pandemic varied within different cities in South America using different models

There is a rising concern that air pollution plays an important role in the COVID-19 pandemic. However, the results were not consistent on the association between air pollution and the spread of COVID-19. In the study, air pollution data and the confirmed cases of COVID-19 were both gathered from five severe cities across three countries in South America. Daily real-time population regeneration (R_t) was calculated to assess the spread of COVID-19. Two frequently used models, generalized additive models (GAM) and multiple linear regression, were both used to explore the impact of environmental pollutants on the epidemic. Wide ranges of all six air pollutants were detected across the five cities. Spearman's correlation analysis confirmed the positive correlation within six pollutants. Rt value showed a gradual decline in all the five cities. Further analysis showed that the association between air pollution and COVID-19 varied across five cities. According to our research results, even for the same region, varied models gave inconsistent results. For example, in Sao Paulo, both models show SO₂ and O₃ are significant independent variables, however, the GAM model shows that PM₁₀ has a nonlinear negative correlation with R_t, while PM₁₀ has no significant correlation in the multiple linear model. Moreover, in the case of multiple regions, currently used models should be selected according to local conditions. Our results indicate that there is a significant relationship between air pollution and COVID-19 infection, which will help states, health practitioners, and policy makers in combating the COVID-19 pandemic in South America.

Prediction of COVID-19 Cases from the Nexus of Air Quality and Meteorological Phenomena: Bangladesh Perspective

An integrated approach was used to estimate the number of COVID-19 patients related to air quality and meteorological phenomena. Additionally, the air quality during pre-lockdown, lockdown, and post-lockdown stages of the COVID-19 pandemic was assessed to determine the effect of the infection containment measures taken in Bangladesh during the pandemic. The air quality was assessed based on measurements of nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), carbon monoxide (CO), black carbon, particulate matter (PM_2.5 and PM₁₀), and aerosol optical depth. Time-averaged maps of these parameters have been generated from NASA's (National Aeronautics and Space Administration) website. Values of these parameters have also been collected from a continuous air monitoring station (CAMS) located in Bangladesh's north-western city Rajshahi. The comparison shows that lockdown during the pandemic has brought significant improvements in air quality. However, the improvement was not sustained, since rapid increases in the air pollutant concentrations were observed in the post-lockdown period. Furthermore, Pearson correlation coefficients between each air quality variable and the daily new COVID-19 case rates were calculated. Different meteorological variables during the same time periods were determined to observe the variation in Rajshahi city. Relationships of these variables with the case rates were also established. Additionally, statistical analyses of the obtained data have been conducted for the measured variables using the Kruskal-Wallis test to assess the differences in the observed data among the pre-lockdown, lockdown, and post-lockdown periods. Dunn's "Q" test was employed to test if the variables showed significance statistical difference during the Kruskal-Wallis test for pairwise comparisons. From the study, it has been observed that both meteorological variables and air quality parameters have significant relationship with daily new COVID-19 case rates. Both positive and negative associations of these parameters with the COVID-19 case rates have been observed. Very high air pollution has been observed in the post-lockdown period. Thus, it is recommended that appropriate authorities undertake corrective measures to protect the environment in cities with large populations. This study provides guidance for decision makers and health officials for future research and potentially reducing the spread of COVID-19.

Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of COVID-19 Diffusion in the Lombardy Region (Italy)

Background: the Lombardy region in Italy was the first area in Europe to record an outbreak of COVID-19 and one of the most affected worldwide. As this territory is strongly polluted, it was hypothesized that pollution had a role in facilitating the diffusion of the epidemic, but results are uncertain. Aim: the paper explores the effect of air pollutants in the first spread of COVID-19 in Lombardy, with a novel geomatics approach addressing the possible confounding factors, the reliability of data, the measurement of diffusion speed, and the biasing effect of the lockdown measures. Methods and results: all municipalities were assigned to one of five possible territorial classes (TC) according to land-use and socio-economic status, and they were grouped into districts of 100,000 residents. For each district, the speed of COVID-19 diffusion was estimated from the ambulance dispatches and related to indicators of mean concentration of air pollutants over 1, 6, and 12 months, grouping districts in the same TC. Significant exponential correlations were found for ammonia (NH₃) in both prevalently agricultural (R² = 0.565) and mildly urbanized (R² = 0.688) areas. Conclusions: this is the first study relating COVID-19 estimated speed of diffusion with indicators of exposure to NH₃. As NH₃ could induce oxidative stress, its role in creating a pre-existing fragility that could have facilitated SARS-CoV-2 replication and worsening of patient conditions could be speculated.

Phytoremediation: The Sustainable Strategy for Improving Indoor and Outdoor Air Quality

Most of the world’s population is exposed to highly polluted air conditions exceeding the WHO limits, causing various human diseases that lead towards increased morbidity as well as mortality. Expenditures on air purification and costs spent on the related health issues are rapidly increasing. To overcome this burden, plants are potential candidates to remove pollutants through diverse biological mechanisms involving accumulation, immobilization, volatilization, and degradation. This eco-friendly, cost-effective, and non-invasive method is considered as a complementary or alternative tool compared to engineering-based remediation techniques. Various plant species remove indoor and outdoor air pollutants, depending on their morphology, growth condition, and microbial communities. Hence, appropriate plant selection with optimized growth conditions can enhance the remediation capacity significantly. Furthermore, suitable supplementary treatments, or finding the best combination junction with other methods, can optimize the phytoremediation process.

COVID-19 and a Green Recovery?

Preliminary evidence indicates that pollution increases the severity and likelihood of COVID-19 infections similar to many other infectious diseases. This paper models the interaction of pollution and disease preventive actions, either pharmaceutical or non-pharmaceutical interventions, on transmission of infectious diseases in a neoclassical growth framework. There are two externalities - households do not take into account how their actions affect disease transmission, and productive activity results in pollution which increases the likelihood of infections. The disease dynamics are modeled to be of SIS type. We study the difference in health and economic outcomes between the decentralized economy, where households do not internalize externalities, and socially optimal outcomes, and characterize the taxes and subsidies that decentralize the latter. Thus, we examine the question whether there are sufficient incentives to reduce pollution, at both private and public levels, once its effects on disease transmission is considered. In competitive outcomes, pollution increases with increased productivity. The socially efficient outcome has higher pollution than a competitive outcome, despite increase in abatement, as the effect of higher productivity and larger labor supply dominates. The results question the hopes of a Green Recovery.

Effect of Anti-COVID-19 Measures on Atmospheric Pollutants Correlated with the Economies of Medium-sized Cities in 10 Urban Areas of Grand Est Region, France

Using Sentinel-5P data, this study investigated the magnitude of change in the concentration of air pollutants (NO₂, HCHO, SO₂, O₃, CO, and aerosol index) in the air of ten cities and urban areas of the French region of Grand Est as a result of the first lockdown imposed between March 17, 2020 and May 11, 2020. The results showed that the air quality in the urban environments of Grand Est improved significantly compared to the same period in 2019 without lockdown. NO₂, O₃, aerosol index and CO were the pollutants that exhibited maximum reductions by an average of -33.98%, -5.94%, -26.82% and -0.66%, respectively (the observed maximum decreases were -54.7%, -7.7%, -13.1%, and -5.3%, respectively). The largest decrease occurred in the Public Establishments of Inter-municipal Cooperation (EPCI, in French: Établissement public de coopération intercommunale) areas of Eurométropole de Strasbourg, CA Colmar, and CA Mulhouse Alsace. The maximum decrease in air pollution first occurred in land cover classes close to cities, followed by built-up urban areas. In this study, a global depollution index known as the atmospheric clearance index (ACI) was developed, which involved several air pollution parameters, and quantitatively analyzed the decrease in contamination levels of the atmosphere in this region. In addition, the correlation between the novel ACI and other population and economic development indices was studied. The results indicated that there was a negative and statistically significant correlation between ACI and population density, gross domestic product, gross value added (GVA) at basic prices, number of employees, and active enterprises.

Ambient Air Pollution in Relation to SARS-CoV-2 Infection, Antibody Response, and COVID-19 Disease: A Cohort Study in Catalonia, Spain (COVICAT Study)

BACKGROUND

Emerging evidence links ambient air pollution with coronavirus 2019 (COVID-19) disease, an association that is methodologically challenging to investigate.

OBJECTIVES

We examined the association between long-term exposure to air pollution with SARS-CoV-2 infection measured through antibody response, level of antibody response among those infected, and COVID-19 disease.

METHODS

We contacted 9,605 adult participants from a population-based cohort study in Catalonia between June and November 2020; most participants were between 40 and 65 years of age. We drew blood samples from 4,103 participants and measured immunoglobulin M (IgM), IgA, and IgG antibodies against five viral target antigens to establish infection to the virus and levels of antibody response among those infected. We defined COVID-19 disease using self-reported hospital admission, prior positive diagnostic test, or more than three self-reported COVID-19 symptoms after contact with a COVID-19 case. We estimated prepandemic (2018-2019) exposure to fine particulate matter [PM with an aerodynamic diameter of ≤ 2.5 μ m (PM 2.5 )], nitrogen dioxide (NO 2 ), black carbon (BC), and ozone (O 3 ) at the residential address using hybrid land-use regression models. We calculated log-binomial risk ratios (RRs), adjusting for individual- and area-level covariates.

RESULTS

Among those tested for SARS-CoV-2 antibodies, 743 (18.1%) were seropositive. Air pollution levels were not statistically significantly associated with SARS-CoV-2 infection: Adjusted RRs per interquartile range were 1.07 (95% CI: 0.97, 1.18) for NO 2 , 1.04 (95% CI: 0.94, 1.14) for PM 2.5 , 1.00 (95% CI: 0.92, 1.09) for BC, and 0.97 (95% CI: 0.89, 1.06) for O 3 . Among infected participants, exposure to NO 2 and PM 2.5 were positively associated with IgG levels for all viral target antigens. Among all participants, 481 (5.0%) had COVID-19 disease. Air pollution levels were associated with COVID-19 disease: adjusted RRs = 1.14 (95% CI: 1.00, 1.29) for NO 2 and 1.17 (95% CI: 1.03, 1.32) for PM 2.5 . Exposure to O 3 was associated with a slightly decreased risk (RR = 0.92 ; 95% CI: 0.83, 1.03). Associations of air pollution with COVID-19 disease were more pronounced for severe COVID-19, with RRs = 1.26 (95% CI: 0.89, 1.79) for NO 2 and 1.51 (95% CI: 1.06, 2.16) for PM 2.5 .

DISCUSSION

Exposure to air pollution was associated with a higher risk of COVID-19 disease and level of antibody response among infected but not with SARS-CoV-2 infection. https://doi.org/10.1289/EHP9726.

The Potential Impact of Smog Spell on Humans' Health Amid COVID-19 Rages

Rapid and unchecked industrialization and the combustion of fossil fuels have engendered a state of fear in urban settlements. Smog is a visible form of air pollution that arises due to the over-emissions of some primary pollutants like volatile organic compounds (VOCs), hydrocarbons, SO₂, NO, and NO₂ which further react in the atmosphere and give rise to toxic and carcinogenic secondary smog components. Smog reduces the visibility on roads and results in road accidents and cancellation of flights. Uptake of primary and secondary pollutants of smog is responsible for several deleterious diseases of which respiratory disorders, cardiovascular dysfunction, neurological disorders, and cancer are discussed here. Children and pregnant women are more prone to the hazards of smog. The worsening menace of smog on one hand and occurrence of pandemic i.e., COVID-19 on the other may increase the mortality rate. But the implementation of lockdown during pandemics has favored the atmosphere in some ways, which will be highlighted in the article. On the whole, the focus of this article will be on the dubious relationship between smog and coronavirus.

The Effect of Pollution on the Spread of COVID-19 in Europe

This study investigates empirically how air pollution in earlier periods as measured by three air pollutants, namely N O 2, P M 10, and P M 2.5 may have affected the spread and fatality of COVID-19 in 31 European countries. Using panel data with fixed effects to examine the relationship between previous exposure to air pollution and COVID-19 new cases and COVID-19 deaths, we find that previous air pollution levels have both acted as an important factor in explaining the COVID-19 spread and its high fatality rate. This result may explain the negative impact that these pollutants may have on health and in particular on the respiratory functions that are mainly attacked by the virus.

Supplementary Information

The online version contains supplementary material available at doi:10.1007/s41885-021-00099-y.

International trade as critical parameter of COVID-19 spread that outclasses demographic, economic, environmental, and pollution factors

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the Coronavirus Disease 2019 (COVID-19), generating high numbers of COVID-19 related infected individuals and deaths, is still circulating in 2021 with new variants of the coronavirus, such that the state of emergency remains in manifold countries. Currently, there is still a lack of a full understanding of the factors determining the COVID-19 diffusion that clarify the causes of the variability of infections across different provinces and regions within countries. The main goal of this study is to explain new and main determinants underlying the diffusion of COVID-19 in society. This study focuses on international trade because this factor, in a globalized world, can synthetize different drivers of virus spread, such as mobility patterns, economic potentialities, and social interactions of an investigated areas. A case study research is performed on 107 provinces of Italy, one of the first countries to experience a rapid increase in confirmed cases and deaths. Statistical analyses from March 2020 to February 2021 suggest that total import and export of provinces has a high association with confirmed cases over time (average r > 0.78, p-value <.001). Overall, then, this study suggests total import and export as complex indicator of COVID-19 transmission dynamics that outclasses other common parameters used to justify the COVID-19 spread, given by economic, demographic, environmental, and climate factors. In addition, this study proposes, for the first time, a time-dependent correlation analysis between trade data and COVID-19 infection cases to explain the relation between confirmed cases and social interactions that are a main source of the diffusion of SARS-CoV-2 and subsequent negative impact in society. These novel findings have main theoretical and practical implications directed to include a new parameter in modelling of the diffusion of COVID-19 pandemic to support effective policy responses of crisis management directed to constrain the impact of COVID-19 pandemic and similar infectious diseases in society.

Early Warning Systems for COVID-19 Infections Based on Low-Cost Indoor Air-Quality Sensors and LPWANs

During the last two years, the COVID-19 pandemic continues to wreak havoc in many areas of the world, as the infection spreads through person-to-person contact. Transmission and prognosis, once infected, are potentially influenced by many factors, including indoor air pollution. Particulate Matter (PM) is a complex mixture of solid and/or liquid particles suspended in the air that can vary in size, shape, and composition and recent scientific work correlate this index with a considerable risk of COVID-19 infections. Early Warning Systems (EWS) and the Internet of Things (IoT) have given rise to the development of Low Power Wide Area Networks (LPWAN) based on sensors, which measure PM levels and monitor In-door Air pollution Quality (IAQ) in real-time. This article proposes an open-source platform architecture and presents the development of a Long Range (LoRa) based sensor network for IAQ and PM measurement. A few air quality sensors were tested, a network platform was implemented after simulating setup topologies, emphasizing feasible low-cost open platform architecture.

The Impact of COVID-19 Lockdowns on Air Quality—A Global Review

The outbreak of the COVID-19 pandemic has emerged as a serious public health threat and has had a tremendous impact on all spheres of the environment. The air quality across the world improved because of COVID-19 lockdowns. Since the outbreak of COVID-19, large numbers of studies have been carried out on the impact of lockdowns on air quality around the world, but no studies have been carried out on the systematic review on the impact of lockdowns on air quality. This study aims to systematically assess the bibliographic review on the impact of lockdowns on air quality around the globe. A total of 237 studies were identified after rigorous review, and 144 studies met the criteria for the review. The literature was surveyed from Scopus, Google Scholar, PubMed, Web of Science, and the Google search engine. The results reveal that (i) most of the studies were carried out on Asia (about 65%), followed by Europe (18%), North America (6%), South America (5%), and Africa (3%); (ii) in the case of countries, the highest number of studies was performed on India (29%), followed by China (23%), the U.S. (5%), the UK (4%), and Italy; (iii) more than 60% of the studies included NO2 for study, followed by PM2.5 (about 50%), PM10, SO2, and CO; (iv) most of the studies were published by Science of the Total Environment (29%), followed by Aerosol and Air Quality Research (23%), Air Quality, Atmosphere & Health (9%), and Environmental Pollution (5%); (v) the studies reveal that there were significant improvements in air quality during lockdowns in comparison with previous time periods. Thus, this diversified study conducted on the impact of lockdowns on air quality will surely assist in identifying any gaps, as it outlines the insights of the current scientific research.

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.

Associations of acute exposure to airborne pollutants with COVID-19 infection: evidence from China

The outbreak of COVID-19, caused by SARS-CoV-2, has spread across many countries globally. Greatly, there are limited studies concerned with the effect of airborne pollutants on COVID-19 infection, while exposure to airborne pollutants may harm human health. This paper aimed to examine the associations of acute exposure to ambient atmospheric pollutants to daily newly COVID-19 confirmed cases in 41 Chinese cities. Using a generalized additive model with Poisson distribution controlling for temperature and relative humidity, we evaluated the association between pollutant concentrations and daily COVID-19 confirmation at single-city level and multicity levels. We observed a 10-μg/m³ rise in levels of PM_2.5 (lag 0-14), O₃ (lag 0-1), SO₂ (lag 0), and NO₂ (lag 0-14) were positively associated with relative risks of 1.050 (95% CI: 1.028, 1.073), 1.011 (1.007, 1.015), 1.052 (1.022, 1.083), and 1.094 (1.028, 1.164) of daily newly confirmed cases, respectively. Further adjustment for other pollutants did not change the associations materially (excepting in the model for SO₂). Our results indicated that COVID-19 incidence may be susceptible to airborne pollutants such as PM_2.5, O₃, SO₂, and NO₂, and mitigation strategies of environmental factors are required to prevent spreading.

Impaired immune response mediated by prostaglandin E2 promotes severe COVID-19 disease

The SARS-CoV-2 coronavirus has led to a pandemic with millions of people affected. The present study finds that risk-factors for severe COVID-19 disease courses, i.e. male sex, older age and sedentary life style are associated with higher prostaglandin E2 (PGE2) serum levels in blood samples from unaffected subjects. In COVID-19 patients, PGE2 blood levels are markedly elevated and correlate positively with disease severity. SARS-CoV-2 induces PGE2 generation and secretion in infected lung epithelial cells by upregulating cyclo-oxygenase (COX)-2 and reducing the PG-degrading enzyme 15-hydroxyprostaglandin-dehydrogenase. Also living human precision cut lung slices (PCLS) infected with SARS-CoV-2 display upregulated COX-2. Regular exercise in aged individuals lowers PGE2 serum levels, which leads to increased Paired-Box-Protein-Pax-5 (PAX5) expression, a master regulator of B-cell survival, proliferation and differentiation also towards long lived memory B-cells, in human pre-B-cell lines. Moreover, PGE2 levels in serum of COVID-19 patients lowers the expression of PAX5 in human pre-B-cell lines. The PGE2 inhibitor Taxifolin reduces SARS-CoV-2-induced PGE2 production. In conclusion, SARS-CoV-2, male sex, old age, and sedentary life style increase PGE2 levels, which may reduce the early anti-viral defense as well as the development of immunity promoting severe disease courses and multiple infections. Regular exercise and Taxifolin treatment may reduce these risks and prevent severe disease courses.