The association of airborne particulate matter and benzo[a]pyrene with the clinical course of COVID-19 in patients hospitalized in Poland

The detoxification ability of sex-role reversed seahorses determines the sexual dimorphism in immune responses to benzo[a]pyrene exposure

Sexual dimorphism in immune responses is an essential factor in environmental adaptation. However, the mechanisms involved remain obscure owing to the scarcity of data from sex-role-reversed species in stressed conditions. Benzo[a]pyrene (BaP) is one of the most pervasive and carcinogenic organic pollutants in coastal environments. In this study, we evaluated the potential effects on renal immunotoxicity of the sex-role-reversed lined seahorse (Hippocampus erectus) toward environmental concentrations BaP exposure. Our results discovered the presence of different energy-immunity trade-off strategies adopted by female and male seahorses during BaP exposure. BaP induced more severe renal damage in female seahorses in a concentration-dependent manner. BaP biotransformation and detoxification in seahorses resemble those in mammals. Benzo[a]pyrene-7,8-dihydrodiol-9,10-oxide (BPDE) and 9-hydroxybenzo[a]pyrene (9-OH-BaP) formed DNA adducts and disrupted Ca2+ homeostasis may together attribute the renal immunotoxicity. Sexual dimorphisms in detoxification of both BPDE and 9-OH-BaP, and in regulation of Ca2+, autophagy and inflammation, mainly determined the extent of renal damage. Moreover, the mechanism of sex hormones regulated sexual dimorphism in immune responses needs to be further elucidated. Collectively, these findings contribute to the understanding of sexual dimorphism in the immunotoxicity induced by BaP exposure in seahorses, which may attribute to the dramatic decline in the biodiversity of the genus.

Importance of soil ecoenzyme stoichiometry for efficient polycyclic aromatic hydrocarbon biodegradation

Efficient remediation of soil contaminated by polycyclic aromatic hydrocarbons (PAHs) is challenging. To determine whether soil ecoenzyme stoichiometry influences PAH degradation under biostimulation and bioaugmentation, this study initially characterized soil ecoenzyme stoichiometry via a PAH degradation experiment and subsequently designed a validation experiment to answer this question. The results showed that inoculation of PAH degradation consortia ZY-PHE plus vanillate efficiently degraded phenanthrene with a K value of 0.471 (depending on first-order kinetics), followed by treatment with ZY-PHE and control. Ecoenzyme stoichiometry data revealed that the EEAC:N, vector length and angle increased before day five and decreased during the degradation process. In contrast, EEAN:P decreased and then increased. These results indicated that the rapid PAH degradation period induced more C limitation and organic P mineralization. Correlation analysis indicated that the degradation rate K was negatively correlated with vector length, EEAC:P, and EEAN:P, suggesting that C limitation and relatively less efficient P mineralization could inhibit biodegradation. Therefore, incorporating liable carbon and acid phosphatase or soluble P promoted PAH degradation in soils with ZY-PHE. This study provides novel insights into the relationship between soil ecoenzyme stoichiometry and PAH degradation. It is suggested that soil ecoenzyme stoichiometry be evaluated before designing bioremeiation stragtegies for PAH contanminated soils.

Viral respiratory infections and air pollution: A review focused on research in Poland

The COVID-19 pandemic has reinforced an interest in the relationship between air pollution and respiratory viral infections, indicating that their burden can be increased under poor air quality. This paper reviews the pathways through which air pollutants can enhance susceptibility to such infections and aggravate their clinical course and outcome. It also summarizes the research exploring the links between various viral infections and exposure to solid and gaseous pollution in Poland, a region characterized by poor air quality, especially during a heating season. The majority of studies focused on concentrations of particulate matter (PM; 86.7%); the other pollutants, i.e., BaP, benzene, CO, NOx, O3, and SO2, were studied less often and sometimes only in the context of a particular infection type. Most research concerned COVID-19, showing that elevated levels of PM and NO2 correlated with higher morbidity and mortality, while increased PM2.5 and benzo[a]pyrene levels were related to worse clinical course and outcome in hospitalized, regardless of age and dominant SARS-CoV-2 variant. PM10 and PM2.5 levels were also associated with the incidence of influenza-like illness and, along with NO2 concentrations, with a higher rate of children's hospitalizations due to lower respiratory tract RSV infections. Higher levels of air pollutants also increased hospitalization due to bronchitis (PM, NOx, and O3) and emergency department admission due to viral croup (PM10, PM2.5, NOx, CO, and benzene). Although the conducted studies imply only correlations and have other limitations, as discussed in the present paper, it appears that improving air quality through reducing combustion processes in energy production in Poland should be perceived as a part of multilayered protection measures against respiratory viral infections, decreasing the healthcare costs of COVID-19, lower tract RSV infections, influenza, and other respiratory viral diseases prevalent between autumn and early spring, in addition to other health and climate benefits.

Long-term air pollution exposure and risk of SARS-CoV-2 infection: A UK-wide cohort study

BACKGROUND

The association between air quality and risk of SARS-CoV-2 infection is poorly understood. We investigated this association using serological individual-level data adjusting for a wide range of confounders, in a large population-based cohort (COVIDENCE UK).

METHODS

We assessed the associations between long-term (2015-19) nitrogen dioxide (NO2) and fine particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5), exposures with SARS-CoV-2 infection, level of antibody response among those infected, and COVID-19 disease severity. We used serological data from 10,489 participants in the COVIDENCE UK cohort, and estimated annual average air pollution exposure at each participant's home postcode.

RESULTS

After controlling for potential confounders, we found a positive association between 5-year NO2 and PM2.5 exposures and the risk of seropositivity: 10 unit increase in NO2 (μg/m3) was associated with an increasing risk of seropositivity by 1.092 (95% CI 1.02 to 1.17; p-for-trend 0.012). For PM2.5, 10 unit increase (μg/m3) was associated with an increasing risk of seropositivity by 1.65 (95% CI 1.015-2.68; p-for-trend 0·049). In addition, we found that NO2 was positively associated with higher antibody titres (p-for-trend 0·013) among seropositive participants, with no evidence of an association for PM2.5.

CONCLUSION

Our findings suggest that the long-term burden of air pollution increased the risks of SARS-CoV-2 infection and has important implications for future pandemic preparedness. This evidence strengthens the case for reducing long-term air pollution exposures to reduce the vulnerability of individuals to respiratory viruses.

Impact of short-term ambient air pollution exposure on the risk of severe COVID-19

Ecological studies suggested a link between air pollution and severe COVID-19 outcomes, while studies accounting for individual-level characteristics are limited. In the present study, we aimed to investigate the impact of short-term ambient air pollution exposure on disease severity among a cohort of 569 laboratory confirmed COVID-19 patients admitted to designated hospitals in Zhejiang province, China, from January 17 to March 3, 2020, and elucidate the possible biological processes involved using transcriptomics. Compared with mild cases, severe cases had higher proportion of medical conditions as well as unfavorable results in most of the laboratory tests, and manifested higher air pollution exposure levels. Higher exposure to air pollutants was associated with increased risk of severe COVID-19 with odds ratio (OR) of 1.89 (95% confidence interval (CI): 1.01, 3.53), 2.35 (95% CI: 1.20, 4.61), 2.87 (95% CI: 1.68, 4.91), and 2.01 (95% CI: 1.10, 3.69) for PM2.5, PM10, NO2 and CO, respectively. OR for NO2 remained significant in two-pollutant models after adjusting for other pollutants. Transcriptional analysis showed 884 differentially expressed genes which mainly were enriched in virus clearance related biological processes between patients with high and low NO2 exposure levels, indicating that compromised immune response might be a potential underlying mechanistic pathway. These findings highlight the impact of short-term air pollution exposure, particularly for NO2, on COVID-19 severity, and emphasize the significance in mitigating the COVID-19 burden of commitments to improve air quality.

The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis

BACKGROUND

The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes.

METHODS

On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality.

RESULTS

A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM2.5. The meta-analyses revealed that a 1 μg/m3 increase in PM2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality.

CONCLUSION

This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors.

Exogenous Chemicals Impact Virus Receptor Gene Transcription: Insights from Deep Learning

Despite the fact that coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been disrupting human life and health worldwide since the outbreak in late 2019, the impact of exogenous substance exposure on the viral infection remains unclear. It is well-known that, during viral infection, organism receptors play a significant role in mediating the entry of viruses to enter host cells. A major receptor of SARS-CoV-2 is the angiotensin-converting enzyme 2 (ACE2). This study proposes a deep learning model based on the graph convolutional network (GCN) that enables, for the first time, the prediction of exogenous substances that affect the transcriptional expression of the ACE2 gene. It outperforms other machine learning models, achieving an area under receiver operating characteristic curve (AUROC) of 0.712 and 0.703 on the validation and internal test set, respectively. In addition, quantitative polymerase chain reaction (qPCR) experiments provided additional supporting evidence for indoor air pollutants identified by the GCN model. More broadly, the proposed methodology can be applied to predict the effect of environmental chemicals on the gene transcription of other virus receptors as well. In contrast to typical deep learning models that are of black box nature, we further highlight the interpretability of the proposed GCN model and how it facilitates deeper understanding of gene change at the structural level.

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.

Smoke and Spike: Benzo[a]pyrene Enhances SARS-CoV-2 Infection by Boosting NR4A2-Induced ACE2 and TMPRSS2 Expression

Cigarette smoke aggravates severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, the underlying mechanisms remain unclear. Here, they show that benzo[a]pyrene in cigarette smoke extract facilitates SARS-CoV-2 infection via upregulating angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2). Benzo[a]pyrene trans-activates the promoters of ACE2 and TMPRSS2 by upregulating nuclear receptor subfamily 4 A number 2 (NR4A2) and promoting its binding of NR4A2 to their promoters, which is independent of functional genetic polymorphisms in ACE2 and TMPRSS2. Benzo[a]pyrene increases the susceptibility of lung epithelial cells to SARS-CoV-2 pseudoviruses and facilitates the infection of authentic Omicron BA.5 in primary human alveolar type II cells, lung organoids, and lung and testis of hamsters. Increased expression of Nr4a2, Ace2, and Tmprss2, as well as decreased methylation of CpG islands at the Nr4a2 promoter are observed in aged mice compared to their younger counterparts. NR4A2 knockdown or interferon-λ2/λ3 stimulation downregulates the expression of NR4A2, ACE2, and TMPRSS2, thereby inhibiting the infection. In conclusion, benzo[a]pyrene enhances SARS-CoV-2 infection by boosting NR4A2-induced ACE2 and TMPRSS2 expression. This study elucidates the mechanisms underlying the detrimental effects of cigarette smoking on SARS-CoV-2 infection and provides prophylactic options for coronavirus disease 2019, particularly for the elderly population.

Short-term exposure to ambient air pollution and COVID-19 severity during SARS-CoV-2 Delta and Omicron waves: A multicenter study

Air pollution may affect the clinical course of respiratory diseases, including COVID-19. This study aimed to evaluate the relationship between exposure of adult patients to mean 24 h levels of particulate matter sized <10 μm (PM₁₀ ) and <2.5 μm (PM_2.5 ) and benzo(a)pyrene (B(a)P) during a week before their hospitalization due to SARS-CoV-2 infection and symptomatology, hyperinflammation, coagulopathy, the clinical course of disease, and outcome. The analyses were conducted during two pandemic waves: (i) dominated by highly pathogenic Delta variant (n = 1440) and (ii) clinically less-severe Omicron (n = 785), while the analyzed associations were adjusted for patient's age, BMI, gender, and comorbidities. The exposure to mean 24 h B(a)P exceeding the limits was associated with increased odds of fever and fatigue as early COVID-19 symptoms, hyperinflammation due to serum C-reactive protein >200 mg/L and interleukin-6 >100 pg/mL, coagulopathy due to  d-dimer >2 mg/L and fatal outcome. Elevated PM₁₀ and PM_{2. 5} levels were associated with higher odds of respiratory symptoms, procalcitonin >0.25 ng/mL and interleukin >100 pg/mL, lower oxygen saturation, need for oxygen support, and death. The significant relationships between exposure to air pollutants and the course and outcomes of COVID-19 were observed during both pandemic waves. Short-term exposure to elevated PM and B(a)P levels can be associated with a worse clinical course of COVID-19 in patients requiring hospitalization and, ultimately, contribute to the health burden caused by SARS-CoV-2 variants of higher and lower clinical significance.

Particulate matter air pollution and COVID-19 infection, severity, and mortality: A systematic review and meta-analysis

Ecological evidence links ambient particulate matter ≤2.5 mm (PM_2.5) and the rate of COVID-19 infections, severity, and deaths. However, such studies are unable to account for individual-level differences in major confounders like socioeconomic status and often rely on imprecise measures of PM_2.5. We conducted a systematic review of case-control and cohort studies, which rely on individual-level data, searching Medline, Embase, and the WHO COVID-19 database up to 30 June 2022. Study quality was evaluated using the Newcastle-Ottawa Scale. Results were pooled with a random effects meta-analysis, with Egger's regression, funnel plots, and leave-one-out/trim-and-fill sensitivity analyses to account for publication bias. N = 18 studies met inclusion criteria. A 10 μg/m³ increase in PM_2.5 was associated with 66 % (95 % CI: 1.31-2.11) greater odds of COVID-19 infection (N = 7) and 127 % (95 % CI: 1.41-3.66) odds of severe illness (hospitalisation, ICU admission, or requiring respiratory support) (N = 6). Pooled mortality results (N = 5) indicated increased deaths due to PM_2.5 but were non-significant (OR 1.40; 0.94 to 2.10). Most studies were rated "good" quality (14/18 studies), though there were numerous methodological issues; few used individual-level data to adjust for socioeconomic status (4/18 studies), instead using area-based indicators (11/18 studies) or no such adjustments (3/18 studies). Most severity (9/10 studies) and mortality studies (5/6 studies) were based on people already diagnosed COVID-19, potentially introducing collider bias. There was evidence of publication bias in studies of infection (p = 0.012) but not severity (p = 0.132) or mortality (p = 0.100). While methodological limits and evidence of bias require cautious interpretation of the findings, we found compelling evidence that PM_2.5 increases the risk of COVID-19 infection and severe disease, and weaker evidence of an increase in mortality risk.

Diosmetin alleviates benzo[a]pyrene-exacerbated H1N1 influenza virus-induced acute lung injury and dysregulation of inflammation through modulation of the PPAR-γ-NF-κB/P38 MAPK signaling axis

The severity of a viral respiratory illness was greatly exacerbated after exposure to a contaminant containing benzo[a]pyrene (B[a]P). Flavonoid-rich fruit intake has gained intense interest due to their health-promoting benefits for viral respiratory diseases, including influenza viruses. In our study, diosmetin (3',5,7-trihydroxy-4'-methoxyflavone), a naturally occurring hydroxylated methoxyflavone that is abundant in Citrus fruits, was explored for its effects on B[a]P-exacerbated H1N1 influenza virus-mediated inflammation and lung injury. Initially, in vivo results demonstrated that diosmetin protected against H1N1 virus-elicited acute lung injury. Simultaneously, H1N1 virus or B[a]P-stimulated A549 cells treated with diosmetin inhibited NF-κB and P-P38 activation, resulting in suppression of pro-inflammatory cytokines and apoptosis. Interestingly, diosmetin obviously promoted the expression of PPAR-γ as well as nuclear translocation of PPAR-γ, whereas, PPAR-γ inhibition by GW9662 weakened the inhibitory effects of diosmetin on H1N1 virus or B[a]P-mediated activation of NF-κB and P-P38, elevated expression of pro-inflammatory mediators as well as apoptosis. Furthermore, it was surprising to discover that mice exposed to both B[a]P and H1N1 viruses contributed to exacerbated acute lung injury, which were significantly ameliorated by diosmetin administration. In vitro studies showed that A549 cells with the combination of B[a]P and H1N1 virus augmented NF-κB and P-P38 activation, accompanied by higher levels of pro-inflammatory mediators and apoptosis, all of which were also significantly reduced by diosmetin treatment. Repressing PPAR-γ abrogated the inhibitory effects of diosmetin on B[a]P-exacerbated H1N1 virus-mediated NF-κB and P-P38 activation, inflammation, and apoptosis in A549 cells. Our findings suggest that diosmetin protected against B[a]P-exacerbated H1N1 virus-mediated lung injury by suppressing the exacerbation of NF-κB and P38 kinase activation in a PPAR-γ-dependent manner, suggesting potential benefits for B[a]P-exacerbated influenza-related illness therapeutics.

Retrospective Analysis of the Effectiveness of Remdesivir in COVID-19 Treatment during Periods Dominated by Delta and Omicron SARS-CoV-2 Variants in Clinical Settings

Continuous evaluation of real-world treatment effectiveness of COVID-19 medicines is required due to the ongoing evolution of SARS-CoV-2 and the possible emergence of resistance. Therefore, this study aimed to analyze, in a retrospective manner, the outcomes in patients hospitalized with COVID-19 during the pandemic waves dominated by Delta and Omicron variants and treated with remdesivir (RDV) (n = 762) in comparison to a demographically and clinically matched group not treated with any antivirals (n = 1060). A logistic regression analysis revealed that RDV treatment was associated with a significantly lower risk of death during both Delta wave (OR = 0.42, 95%CI: 0.29-0.60; p < 0.0001) and Omicron-dominated period (OR = 0.56, 95%CI: 0.35-0.92; p = 0.02). Moreover, RDV-treated groups were characterized by a lower percentage of patients requiring mechanical ventilation, but the difference was not statistically significant. This study is the first real-world evidence that RDV remains effective during the dominance of more pathogenic SARS-CoV-2 variants and those that cause a milder course of the disease, and continues to be an essential element of COVID-19 therapy.

Long-term Exposure to Ambient Air Pollutants and Increased Risk of Pneumonia in the UK Biobank

BACKGROUND

Short-term exposure to air pollution has been linked to pneumonia risk. However, evidence on the long-term effects of air pollution on pneumonia morbidity is scarce and inconsistent. We investigated the associations of long-term air pollutants exposure with pneumonia and explored the potential interactions with smoking.

RESEARCH QUESTION

Is long-term exposure to ambient air pollution associated with the risk of pneumonia, and does smoking modify the associations?

STUDY DESIGN AND METHODS

We analyzed data in 445,473 participants without pneumonia within 1 year before baseline from the UK Biobank. Annual average concentrations of particulate matter (particulate matter with a diameter < 2.5 μm [PM_2.5] and particulate matter with a diameter < 10 μm [PM₁₀]), nitrogen dioxide (NO₂), and nitrogen oxides (NO_x) were estimated using land-use regression models. Cox proportional hazards models were used to assess the associations between air pollutants and pneumonia incidence. Potential interactions between air pollution and smoking were examined on both additive and multiplicative scales.

RESULTS

The hazard ratios of pneumonia for each interquartile range increase in PM_2.5, PM₁₀, NO₂, and NO_x concentrations were 1.06 (95% CI, 1.04-1.08), 1.10 (95% CI, 1.08-1.12), 1.12 (95% CI, 1.10-1.15), and 1.06 (95% CI, 1.04-1.07), respectively. There were significant additive and multiplicative interactions between air pollution and smoking. Compared with never smokers with low air pollution exposure, ever smokers with high air pollution exposure had the highest pneumonia risk (PM_2.5: HR, 1.78; 95% CI, 1.67-1.90; PM₁₀: HR, 1.94; 95% CI, 1.82-2.06; NO₂: HR, 2.06; 95% CI, 1.93-2.21; NO_x: HR, 1.88; 95% CI, 1.76-2.00). The associations between air pollutants and pneumonia risk persisted in participants exposed to air pollutants concentrations meeting the European Union limits.

INTERPRETATION

Long-term exposure to air pollutants was associated with an increased risk of pneumonia, especially in smokers.

Impact of air pollutants on influenza-like illness outpatient visits under COVID-19 pandemic in the subcenter of Beijing, China

This study aimed to explore the association between air pollutants and outpatient visits for influenza-like illnesses (ILI) under the coronavirus disease 2019 (COVID-19) stage in the subcenter of Beijing. The data on ILI in the subcenter of Beijing from January 1, 2018 to December 31, 2020 were obtained from the Beijing Influenza Surveillance Network. A generalized additive Poisson model was applied to examine the associations between the concentrations of air pollutants and daily outpatient visits for ILI when controlling meteorological factors and temporal trend. A total of 171 943 ILI patients were included. In the pre-coronavirus disease 2019 (COVID-19) stage, an increased risk of ILI outpatient visits was associated to a high air quality index (AQI) and the high concentrations of particulate matter less than 2.5 (PM_2.5 ), particulate matter 10 (PM₁₀ ), sulphur dioxide (SO₂ ), nitrogen dioxide (NO₂ ), and carbon monoxide (CO), and a low concentration of ozone (O₃ ) on lag0 day and lag1 day, while a higher increased risk of ILI outpatient visits was observed by the air pollutants in the COVID-19 stage on lag0 day. Except for PM₁₀ , the concentrations of other air pollutants on lag1 day were not significantly associated with an increased risk of ILI outpatient visits during the COVID-19 stage. The findings that air pollutants had enhanced immediate effects and diminished lag-effects on the risk of ILI outpatient visits during the COVID-19 pandemic, which is important for the development of public health and environmental governance strategies.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Variability in the Clinical Course of COVID-19 in a Retrospective Analysis of a Large Real-World Database

The COVID-19 pandemic proceeds in waves, with variable characteristics of the clinical picture resulting from the evolution of the SARS-CoV-2 virus. This study aimed to compare the epidemiological characteristics, symptomatology, and outcomes of the disease in patients hospitalized for COVID-19 during periods of different variants dominance. Comparing the periods of dominance of variants preceding the Delta variant, the Delta period was characterized by a higher share of hospitalized females, less frequent comorbidities among patients, and a different age distribution. The lowest need for oxygen therapy and mechanical ventilation was observed under Omicron dominance. The triad of classic COVID-19 symptoms, cough, fever, dyspnoea, and fatigue, were most prevalent during the Delta period, and significantly less common under the Omicron dominance. During the Omicron period, nearly twice as many patients as in the previous periods could be discharged from the hospital within 7 days; the overall 28-day mortality was significantly lower compared to that of the Delta period. It also did not differ between periods that were dominated by the BA.1 and BA.2 subvariants. The study indicates that the Omicron SARS-CoV-2 variant that dominated between January and June 2022 caused a disease which resembled the common cold, and was caused by seasonal alpha and beta-coronaviruses with a low pathogenicity for humans. However, one should note that this effect may not only have been related to biological features of the Omicron lineage, but may additionally have been driven by the increased levels of immunization through natural infections and vaccinations, for which we could not account for due to a lack of sufficient data.

Event-Specific Transmission Forecasting of SARS-CoV-2 in a Mixed-Mode Ventilated Office Room Using an ANN

The emerging novel variants and re-merging old variants of SARS-CoV-2 make it critical to study the transmission probability in mixed-mode ventilated office environments. Artificial neural network (ANN) and curve fitting (CF) models were created to forecast the R-Event. The R-Event is defined as the anticipated number of new infections that develop in particular events occurring over the course of time in any defined space. In the spring and summer of 2022, real-time data for an office environment were collected in India in a mixed-mode ventilated office space in a composite climate. The performances of the proposed CF and ANN models were compared with respect to traditional statistical indicators, such as the correlation coefficient, RMSE, MAE, MAPE, NS index, and a20-index, in order to determine the merit of the two approaches. Thirteen input features, namely the indoor temperature (T_In), indoor relative humidity (RH_In), area of opening (A_O), number of occupants (O), area per person (A_P), volume per person (V_P), CO₂ concentration (CO₂), air quality index (AQI), outer wind speed (W_S), outdoor temperature (T_Out), outdoor humidity (RH_Out), fan air speed (F_S), and air conditioning (AC), were selected to forecast the R-Event as the target. The main objective was to determine the relationship between the CO₂ level and R-Event, ultimately producing a model for forecasting infections in office building environments. The correlation coefficients for the CF and ANN models in this case study were 0.7439 and 0.9999, respectively. This demonstrates that the ANN model is more accurate in R-Event prediction than the curve fitting model. The results show that the proposed ANN model is reliable and significantly accurate in forecasting the R-Event values for mixed-mode ventilated offices.

Bioinformatics and systems biology approaches to identify molecular targeting mechanism influenced by COVID-19 on heart failure

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as a contemporary hazard to people. It has been known that COVID-19 can both induce heart failure (HF) and raise the risk of patient mortality. However, the mechanism underlying the association between COVID-19 and HF remains unclear. The common molecular pathways between COVID-19 and HF were identified using bioinformatic and systems biology techniques. Transcriptome analysis was performed to identify differentially expressed genes (DEGs). To identify gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways, common DEGs were used for enrichment analysis. The results showed that COVID-19 and HF have several common immune mechanisms, including differentiation of T helper (Th) 1, Th 2, Th 17 cells; activation of lymphocytes; and binding of major histocompatibility complex class I and II protein complexes. Furthermore, a protein-protein interaction network was constructed to identify hub genes, and immune cell infiltration analysis was performed. Six hub genes (FCGR3A, CD69, IFNG, CCR7, CCL5, and CCL4) were closely associated with COVID-19 and HF. These targets were associated with immune cells (central memory CD8 T cells, T follicular helper cells, regulatory T cells, myeloid-derived suppressor cells, plasmacytoid dendritic cells, macrophages, eosinophils, and neutrophils). Additionally, transcription factors, microRNAs, drugs, and chemicals that are closely associated with COVID-19 and HF were identified through the interaction network.

COVID-19 vaccinations and rates of infections, hospitalizations, ICU admissions, and deaths in Europe during SARS-CoV-2 Omicron wave in the first quarter of 2022

The vaccination campaigns brought hope to minimizing the coronavirus disease 2019 (COVID-19) burden. However, the emergence of novel, highly transmissible Omicron lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the waning of neutralizing antibodies a few months after vaccination has brought concerns over the vaccine efficacy. The present work analyzed the relationships between COVID-19 vaccine coverage (completion of primary course and booster dose intake) in the European Economic Area and rates of infection, hospitalizations, admissions to intensive care units (ICU), and deaths during the Omicron wave in the first quarter of 2022 (January-April). As demonstrated, infection rates were not correlated to vaccine coverage in any considered month. For January and February, the rates of hospitalizations, intensive care unit (ICU) admissions, and death due to COVID-19 were strongly negatively correlated (r =- 0.54 to -0.82) with the percentage of individuals who completed initial vaccination protocol and the percentage of those who received a booster dose. However, in March and April, the percentage of the population with primary vaccination course correlated negatively only with ICU admissions (r = -0.77 and -0.46, respectively). The uptake of boosters in March still remained in significant negative correlation with hospitalizations (r = -0.45), ICU admissions (r = -0.70) and deaths due to COVID-19 (r = -0.37), although in April these relationships were no longer observed. The percentage of individuals with confirmed SARS-CoV-2 infection did not correlate with the pandemic indices for any considered month. The study indicates that COVID-19 vaccination, including booster administration, was beneficial in decreasing the overwhelming of healthcare systems during the Omicron wave, but novel vaccine strategies may be required in the long term to enhance the effectiveness and durability of vaccine-induced protection during future waves of SARS-CoV-2 infections.

Air pollution might affect the clinical course of COVID-19 in pediatric patients

Air pollution, to which children are more susceptible than adults, can promote airway inflammation, potentially exaggerating the effects of respiratory viral infection. This study examined the association between the clinical manifestation of COVID-19 in unvaccinated pediatric patients hospitalized in Poland (n = 766) and levels of particulate matter 2.5 (PM_2.5) and benzo(a)pyrene (B(a)P) within a week before hospitalization. Children aged ≤ 12 years exposed to mean and max 24 h B(a)P levels > 1 ng/m³ revealed higher odds of cough, dyspnea, fever, and increased concentrations of inflammatory markers (C-reactive protein, interleukin-6, procalcitonin, white blood cell count). In older patients (13-17 years), elevated mean 24 h B(a)P levels increased odds of dyspnea, fever, and diarrhea, and higher concentrations of C-reactive protein and procalcitonin. Exposure to max 24 h PM_2.5 levels > 20 µg/m³ was associated with higher odds of cough, increased concentrations of C-reactive protein (group ≤12 years), and increased procalcitonin concentration (groups ≤12 years and 13-17 years). In both age groups, length of stay was extended in patients exposed to elevated levels of max 24 h PM_2.5, mean and max 24 h B(a)P. This study suggests that worse air quality, particularly reflected in increased B(a)P levels, might affect the clinical course of COVID-19 in pediatric patients and adds to the disease burden during a pandemic.