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The impact investing literature largely focuses on private equity investing and overlooks the investments made through debt financing that actually dominate the market. To address this research gap, this paper investigates whether impact financing is associated with financial benefits. By using COVID-19 as an exogenous shock to China's stock market, this paper applies fixed effects panel data analysis with a difference-in-differences research design to provide robust empirical outcomes. The results reveal those financial institutions that better integrated environmental impacts into their financing process experienced positive stock return changes in response to the shock. This study answers the question of how well an impact scales. The findings suggest that impact financing is an effective model, as the impacts incorporated in the debt can be scaled up compared to impact investing funds with low volumes. Impact financing has enormous potential for financial institutions to engage in the green transition since they can derive pecuniary utility while delivering environmental impacts. The revelation of financial benefits also contributes to overcoming the lack of knowledge about impact financing and helps to remove the barriers that advance industry growth. • This paper studies whether impact financing is associated with financial benefits. • Financial firms that better integrate environmental impact in financing have positive stock return changes during COVID-19. • Financial firms can derive pecuniary utility from pursuing impact financing. • The findings suggest that impact financing can be an effective model to bring impact to a substantial scale. [ABSTRACT FROM AUTHOR]

The rapid spread of Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emphasized the importance of understanding and adapting to the indoor remediation of transmissible diseases to decrease the risk for future pandemic threats. While there were many precautions in place to hinder the spread of COVID-19, there has also been a substantial increase of new research on SARS-CoV-2 that can be utilized to further mitigate the transmission risk of this novel virus. This review paper aims to identify the building parameters of indoor spaces that could have considerable influence on the transmission of SARS-CoV-2. The following building parameters have been identified and analyzed, emphasizing their link with the indoor transmission of SARS-CoV-2: temperature and relative humidity, temperature differences between rooms, ventilation rate and access to natural ventilation, occupant density, surface type and finish, airflow direction and speed, air stability, indoor air pollution, central air conditioning systems, capacity of air handling system and HVAC filter efficiency, edge sealing of air filters, room layout and interior design, and compartmentalization of interior space. This paper also explains the interactions of SARS-CoV-2 with indoor environments and its persistence. Furthermore, the modifications of the key building parameters have been discussed for controlling the transmission of SARS-CoV-2 in indoor spaces. Understanding the information provided in this paper is crucial to develop effective health and safety measures that will aid in infection prevention. [ABSTRACT FROM AUTHOR]

This paper employs systematic literature network analysis, including a literature review and bibliometric network analysis, to explore the COVID-19 and air pollution literature. A total of 1208 relevant documents from the Scopus database were analyzed using VOSviewer and SciMAT to examine author, keyword, and country interconnections. The paper addresses three research questions: (1) the latest studies on COVID-19 and air pollution, (2) influential authors, documents, and sources in the field, and (3) the study's findings as a roadmap for future research. Visual representations of author and country networks highlight influential entities based on citation rate. Keyword cluster analysis via VOSviewer summarizes connections based on link strength. The strategic diagram generated by SciMAT offers insights into future research directions in specific thematic keywords: (1) air pollution, (2) nitrogen dioxide, (3) epidemiology, and (4) atmospheric aerosol. This analysis enhances understanding of COVID-19 and air pollution and guides future research endeavors. • Conducts a systematic review of the literature on COVID-19 and air pollution. • Utilizes bibliometric network analysis on a selection of documents. • Collects 1208 Scopus database documents from 2020 to 2023. • Identifies themes or keywords for further study on COVID-19 and air pollution. [ABSTRACT FROM AUTHOR]

The sudden outbreak of the COVID-19 pandemic forced organizations worldwide to switch to remote work paradigms. This paper examines how users adapted to online meeting environments, specifically in the context of official council meetings at a Brazilian university. Transitioning from traditional in-person to virtual meeting platforms required re-evaluating participation dynamics, including how council members and the public interact in these spaces. We interviewed 19 council members who were used to participating in in-person deliberative public meetings, aiming to delve into their adaptation process, examining how individuals adjusted to the virtual meeting format and related challenges. Our findings show that online meetings broadened attendance and engagement but also introduced complexities with meeting protocols and personal attention. We discuss how participants navigated the nuances of online meeting formats, from managing technical issues to redefining public and private meeting boundaries. Our analysis suggests that user adaptation is multifaceted, encompassing the adoption of new technologies and modifications in communication strategies and meeting etiquette. Through this lens, we reflect on the essential role of user-centric approaches in designing and facilitating online meetings to enhance collaborative outcomes and mitigate the potential for breakdowns. This research contributes to a deeper understanding of the resilience and flexibility of meeting cultures in response to unforeseen global changes. • Transition to online meetings: Explored cognitive and behavioral changes. • Maintaining professional integrity: Urgent need for updated conduct protocols. • Challenges faced: Technological gaps and the psychological impact of remote work. • Tool development: Essential for differentiating public and private spaces online. • Interface guidelines: Proposed for the new norms of remote collaboration. [ABSTRACT FROM AUTHOR]

Is there a "missing device" for respiratory personal protection? Does it exist an easy-to-use device, allowing extensive use in everyday settings by the population, maximizing tolerability and low visual and physical invasiveness protecting from a wide range of threats including airborne pathogens, hence including the particle range of fine and ultrafine particles? Looking at the recent past, in the urgency of finding ready-to-use solutions for the respiratory protection of the population during the outbreak of the SARS-CoV-2 pandemic, devices for occupational safety have been used, such as filtering face masks. These are devices intended for workers operating during work shifts in environments characterized by potential high risk, known a priori, often directly sensible; this makes wearers motivated to tolerate discomfort for a given period to face a localized risk, and safety managers determined to supervise compliance with usage specifications. Their use by general population has implied known shortcomings, such as weak compatibility with relational work and activities, low tolerability during prolonged use, low compliance with the proper use of the device, all of this lessening actual protection. The need for a new perspective has emerged, targeting effectiveness in whole daily life, rather than punctual efficacy. Nasal filters are promising candidates to protect individuals throughout the day during the most varied activities, but they lack a systematic definition as a device and as a product; it follows that the high complexity needed to reach an effective performance envelop is generally underestimated. By reviewing available literature, the present paper draws on the experience from the pandemic and infers systematic product specifications and characterization methods for a new, effective personal respiratory protection device; these specifications are compared with the stringent constraints associated with the endonasal applications and, based on air filtration state of the art, quantifies the need for technology disruption and outlining possible new development paths. • The SARS-COV-2 pandemic indicated that an adequately performing nasal filter has the potential to play a protective role in the population's daily life. • A nasal filter poses unique technological challenges due to its miniaturisation. • To trap allergens, pathogens and harmful particulate matter entering the nose, it is necessary to filter out particles classified as fine and ultrafine. • Fibrous mesh filters are inadequate to filter fine and ultrafine particles in a nasal filter as small as a nostril, due to their low filtration capacity and high breathing resistance. • The development of effective nasal filters in the field of fine and ultrafine particles requires the adoption of new technologies. [ABSTRACT FROM AUTHOR]

[Display omitted] • Green and efficient one-pot three-component synthesis of novel drug-like furo[2,3- d ]pyrimidines. • Computer-aided drug design (CADD) approaches for combat COVID-19. • Novel non-covalent inhibitors of the active site and putative allosteric hotspots modulators of both SARS-CoV-2 MPro and PLPro. • Potential COVID-19 drug candidates. • Molecular docking and in silico ADMET studies. • Molecular docking (protein‒ligand) studies on the human body temperature-dependent MPro protein contain zincII (ZnII) ion between His41/Cys145 catalytic dyad in the active site. In this paper, an environmentally benign, convenient, and efficient one-pot three-component reaction has been developed for the regioselective synthesis of novel 5-aroyl(or heteroaroyl)-6-(alkylamino)-1,3-dimethylfuro[2,3- d ]pyrimidine-2,4(1 H ,3 H)-diones (4a‒n) through the sequential condensation of aryl(or heteroaryl)glyoxal monohydrates (1a‒g), 1,3-dimethylbarbituric acid (2), and alkyl(viz. cyclohexyl or tert -butyl)isocyanides (3a or 3b) catalyzed by ultra-low loading ZrOCl 2 •8H 2 O (just 2 mol%) in water at 50 ˚C. After synthesis and characterization of the mentioned furo[2,3- d ]pyrimidines (4a‒n), their multi-targeting inhibitory properties were investigated against the active site and putative allosteric hotspots of both SARS-CoV-2 main protease (MPro) and papain-like protease (PLPro) based on molecular docking studies and compare the attained results with various medicinal compounds which approximately in three past years were used, introduced, and or repurposed to fight against COVID-19. Furthermore, drug-likeness properties of the mentioned small heterocyclic frameworks (4a‒n) have been explored using in silico ADMET analyses. Interestingly, the molecular docking studies and ADMET-related data revealed that the novel series of furo[2,3- d ]pyrimidines (4a‒n), especially 5-(3,4-methylendioxybenzoyl)-6-(cyclohexylamino)-1,3-dimethylfuro[2,3- d ]pyrimidine-2,4(1 H ,3 H)-dione (4g) as hit one is potential COVID-19 drug candidate, can subject to further in vitro and in vivo studies. It is worthwhile to note that the protein–ligand-type molecular docking studies on the human body temperature-dependent MPro protein that surprisingly contains zincII (ZnII) ion between His41/Cys145 catalytic dyad in the active site, which undoubtedly can make new plans for designing novel SARS-CoV-2 MPro inhibitors, is performed for the first time in this paper, to the best of our knowledge. [ABSTRACT FROM AUTHOR]

Even reaching the end of the year 2022, there is still a controversy on the origin of the SARS-CoV-2 virus. This Virtual Special Issue (VSI), focused on the "Scientific evidence on the origin of SARS-CoV-2", was launched some months ago with the aim of stimulating the submission of new high quality scientific research papers on the matter, to shed light on it. As indicated in the call for papers, the Editors involved in the VSI were aware of the difficulties of presenting concluding facts on that issue, however, bearing in mind that some teams of researchers had started investigations regarding this subject, a VSI like this (searching for stimulating the scientific controversy while requiring scientific evidence), could help to elucidate complicated aspects, going a step ahead in this way. The Editors made a call encouraging interested teams of researchers having solid results to submit high quality manuscripts dealing with this crucial theme. We thought -and we still think-that it is of maximum interest for the scientific community, as well as for the whole society, now and probably for the future. The VSI have received 50 submissions, which could be considered a limited number highlighting the difficulties of elaborating new high-quality manuscripts providing solid evidence on the matter. After a careful peer-review, those manuscripts considered to reach the highest scientific value were accepted for publication. The Editors think that the set of papers included in this VSI constitute interesting and high-quality contributions, providing further scientific knowledge on this issue. In this editorial piece, the Editors make some comments on the papers published, including some additional reflections. [ABSTRACT FROM AUTHOR]

More than two and a half years have already passed since the first case of COVID-19 was officially reported (December 2019), as well as more than two years since the WHO declared the current pandemic (March 2020). During these months, the advances on the knowledge of the COVID-19 and SARS-CoV-2, the coronavirus responsible of the infection, have been very significant. However, there are still some weak points on that knowledge, being the origin of SARS-CoV-2 one of the most notorious. One year ago, I published a review focused on what we knew and what we need to know about the origin of that coronavirus, a key point for the prevention of potential future pandemics of a similar nature. The analysis of the available publications until July 2021 did not allow drawing definitive conclusions on the origin of SARS-CoV-2. Given the great importance of that issue, the present review was aimed at updating the scientific information on that origin. Unfortunately, there have not been significant advances on that topic, remaining basically the same two hypotheses on it. One of them is the zoonotic origin of SARS-CoV-2, while the second one is the possible leak of this coronavirus from a laboratory. Most recent papers do not include observational or experimental studies, being discussions and positions on these two main hypotheses. Based on the information here reviewed, there is not yet a definitive and well demonstrated conclusion on the origin of SARS-CoV-2. • The origin of SARS-CoV-2 is not established, but most papers point out to a zoonotic origin of this coronavirus. • An important number of available papers on the origin of SARC-CoV-2 are not experimental studies. • The hypothesis of an unnatural origin of SARS-CoV-2 cannot be yet scientifically discarded. [ABSTRACT FROM AUTHOR]

Wastewater monitoring as a public health tool is well-established and the SARS-CoV-2 (COVID-19) pandemic has seen its widespread uptake. Given the significant potential of wastewater monitoring as a public health surveillance and decision support tool, it is important to understand what measures are required to allow the long-term benefits of wastewater monitoring to be fully realized, including how to establish and/or maintain public support. The potential for positive SARS-CoV-2 detections to trigger enforced, community-wide public health interventions (e.g., lockdowns and other impacts on civil liberties) further emphasises the need to better understand the role of public engagement in successful wastewater-based monitoring programs. This paper systematically reviews the processes of building and maintaining the social license to operate wastewater monitoring. We specifically explore the relationship between different stakeholder communities and highlight the information and actions that are required to establish a social license to operate and then prevent its loss. The paper adds to the literature on social license to operate by extending its application to new domains and offers a dynamic model of social license to help guide the agenda for researcher and practitioner communities. • The requirement for social license to undertake wastewater monitoring is systematically scrutinized. • A dynamic framework for social license to monitor for COVID-19 is developed and presented. • Important gaps and additional steps for maintaining social license are identified. [ABSTRACT FROM AUTHOR]

2019 Coronavirus disease (COVID-19) had a big impact in Italy, mainly concentrated in the northern part of the Country. All this was mainly due to similarities of this area with Wuhan in Hubei Province, according to geographical, environmental and socio-economic points of view. The basic hypothesis of this research was that the presence of atmospheric pollutants can generate stress on health conditions of the population and determine pre-conditions for the development of diseases of the respiratory system and complications related to them. In most cases the attention on environmental aspects is mainly concentrated on pollution, neglecting issues such as land management which, in some way, can contribute to reducing the impact of pollution. The reduction of land take and the decrease in the loss of ecosystem services can represent an important aspect in improving environmental quality. In order to integrate policies for environmental change and human health, the main factors analyzed in this paper can be summarized in environmental, climatic and land management. The main aim of this paper was to produce three different hazard scenarios respectively related to environmental, climatic and land management-related factors. A Spatial Analytical Hierarchy Process (AHP) method has been applied over thirteen informative layers grouped in aggregation classes of environmental, climatic and land management. The results of the health hazard maps show a disparity in the distribution of territorial responses to the pandemic in Italy. The environmental components play an extremely relevant role in the definition of the red zones of hazard, with a consequent urgent need to renew sustainable development strategies. The comparison of hazard maps related to different scenarios provides decision makers with tools to orient policy choices with a different degree of priority according to a place-based approach. In particular, the geospatial representation of risks could be a tool for legitimizing the measures chosen by decision-makers, proposing a renewed approach that highlights and takes account of the differences between the spatial contexts to be considered - Regions, Provinces, Municipalities - also in terms of climatic and environmental variables. • COVID-19 had a big impact in Italy, mainly in the northern part of the Country. • Reduction of land take and ecosystem services' loss improve environmental quality. • Environmental, climatic and land management can be leveraged for pandemic policies. • Geospatial representation of risks is a useful approach to support decision-makers. [ABSTRACT FROM AUTHOR]

Scientific evidence shows that acoustic analysis could be an indicator for diagnosing COVID-19. From analyzing recorded breath sounds on smartphones, it is discovered that patients with COVID-19 have different patterns in both the time domain and frequency domain. These patterns are used in this paper to diagnose the infection of COVID-19. Statistics of the sound signals, analysis in the frequency domain, and Mel-Frequency Cepstral Coefficients (MFCCs) are then calculated and applied in two classifiers, k-Nearest Neighbors (kNN) and Convolutional Neural Network (CNN), to diagnose whether a user is contracted with COVID-19 or not. Test results show that, amazingly, an accuracy of over 97% could be achieved with a CNN classifier and more than 85% on kNN with optimized features. Optimization methods for selecting the best features and using various metrics to evaluate the performance are also demonstrated in this paper. Owing to the high accuracy of the CNN model, the CNN model was implemented in an Android app to diagnose COVID-19 with a probability to indicate the confidence level. The initial medical test shows a similar test result between the method proposed in this paper and the lateral flow method, which indicates that the proposed method is feasible and effective. Because of the use of breath sound and tested on the smartphone, this method could be used by everybody regardless of the availability of other medical resources, which could be a powerful tool for society to diagnose COVID-19. [ABSTRACT FROM AUTHOR]

The technology development for point-of-care tests (POCTs) targeting respiratory diseases has witnessed a growing demand in the recent past. Investigating the presence of acoustic biomarkers in modalities such as cough, breathing and speech sounds, and using them for building POCTs can offer fast, contactless and inexpensive testing. In view of this, over the past year, we launched the "Coswara" project to collect cough, breathing and speech sound recordings via worldwide crowdsourcing. With this data, a call for development of diagnostic tools was announced in the Interspeech 2021 as a special session titled "Diagnostics of COVID-19 using Acoustics (DiCOVA) Challenge". The goal was to bring together researchers and practitioners interested in developing acoustics-based COVID-19 POCTs by enabling them to work on the same set of development and test datasets. As part of the challenge, datasets with breathing, cough, and speech sound samples from COVID-19 and non-COVID-19 individuals were released to the participants. The challenge consisted of two tracks. The Track-1 focused only on cough sounds, and participants competed in a leaderboard setting. In Track-2, breathing and speech samples were provided for the participants, without a competitive leaderboard. The challenge attracted 85 plus registrations with 29 final submissions for Track-1. This paper describes the challenge (datasets, tasks, baseline system), and presents a focused summary of the various systems submitted by the participating teams. An analysis of the results from the top four teams showed that a fusion of the scores from these teams yields an area-under-the-receiver operating curve (AUC-ROC) of 95.1% on the blind test data. By summarizing the lessons learned, we foresee the challenge overview in this paper to help accelerate technological development of acoustic-based POCTs. • Presents the DiCOVA dataset, the challenge task, and the baseline system. • Summarizes the systems and performances of the participating teams. • Analyzes systems of the top performing teams. • Discusses the lessons learnt and future directions. [ABSTRACT FROM AUTHOR]

Since the rise of the Covid-19 pandemic, several researchers stated the possibility of a positive relationship between Covid-19 spread and climatic parameters. An ecological study in 12 Iranian cities using the report of daily deaths from Covid-19 (March to August 2020) and validated data on air pollutants, considering average concentrations in each city in the last year used to analyze the association between chronic exposure to air pollutants and the death rate from Covid-19 in Iran. Poisson regression models were used, with generalized additive models and adjustment variables. A significant increase of 2.7% (IC(95%) 2.6–4.4) was found in the mortality rate due to Covid-19 due to an increase of 1 μg/m3 of NO 2. The results suggest an association between Covid-19 mortality and NO 2 exposure. As a risk approximation associated with air pollution, more precise analysis is done. The results also show a good consistency with studies from other regions; this paper's results can be useful for the public health policymakers and decision-making to control the Covid-19 spread. • A reliable Covid-19 data from Iran was used in this paper. • 12 cities were considered from all of the minor climate conditions of the country to minimize the climate bias. • Correlation of the air pollution and the other most effective diseases on the Covid-19 is also studied. • Nox was the most effective particle and had a significant impact on the Covid-19 mortality rate. • For a 1% increase in the NO 2 concentration, there will be a 2.7% increase in the Covid-19 mortality rate. [ABSTRACT FROM AUTHOR]

This review discusses the techniques available for detecting and inactivating of pathogens in municipal wastewater, landfill leachate, and solid waste. In view of the current COVID-19 pandemic, SARS-CoV-2 is being given special attention, with a thorough examination of all possible transmission pathways linked to the selected waste matrices. Despite the lack of works focused on landfill leachate, a systematic review method, based on cluster analysis, allows to analyze the available papers devoted to sewage sludge and wastewater, allowing to focalize the work on technologies able to detect and treat pathogens. In this work, great attention is also devoted to infectivity and transmission mechanisms of SARS-CoV-2. Moreover, the literature analysis shows that sewage sludge and landfill leachate seem to have a remote chance to act as a virus transmission route (pollution-to-human transmission) due to improper collection and treatment of municipal wastewater and solid waste. However due to the incertitude about virus infectivity, these possibilities cannot be excluded and need further investigation. As a conclusion, this paper shows that additional research is required not only on the coronavirus-specific disinfection, but also the regular surveillance or monitoring of viral loads in sewage sludge, wastewater, and landfill leachate. The disinfection strategies need to be optimized in terms of dosage and potential adverse impacts like antimicrobial resistance, among many other factors. Finally, the presence of SARS-CoV-2 and other pathogenic microorganisms in sewage sludge, wastewater, and landfill leachate can hamper the possibility to ensure safe water and public health in economically marginalized countries and hinder the realization of the United Nations' sustainable development goals (SDGs). • Pathogens including SARS-CoV-2 can be detected in municipal wastewater and solid waste. • SARS-CoV-2 seems pose remote infection risk through pollution-to-human transmission mechanism. • Standardized detection method is needed for environmental surveillance of SARS-CoV-2. • Disinfection needs to be optimized for SARS-CoV-2 and minimizing negative impacts. • The pandemic cause new challenges in achieving the UN SDGs related to water. [ABSTRACT FROM AUTHOR]

Enormous hope in the efficacy of vaccines became recently a successful reality in the fight against the COVID-19 pandemic. However, vaccine hesitancy, fueled by exposure to social media misinformation about COVID-19 vaccines became a major hurdle. Therefore, it is essential to automatically detect where misinformation about COVID-19 vaccines on social media is spread and what kind of misinformation is discussed, such that inoculation interventions can be delivered at the right time and in the right place, in addition to interventions designed to address vaccine hesitancy. This paper is addressing the first step in tackling hesitancy against COVID-19 vaccines, namely the automatic detection of known misinformation about the vaccines on Twitter, the social media platform that has the highest volume of conversations about COVID-19 and its vaccines. We present CoVaxLies, a new dataset of tweets judged relevant to several misinformation targets about COVID-19 vaccines on which a novel method of detecting misinformation was developed. Our method organizes CoVaxLies in a Misinformation Knowledge Graph as it casts misinformation detection as a graph link prediction problem. The misinformation detection method detailed in this paper takes advantage of the link scoring functions provided by several knowledge embedding methods. The experimental results demonstrate the superiority of this method when compared with classification-based methods, widely used currently. [ABSTRACT FROM AUTHOR]

Climate change is acknowledged to directly affect not only the environment, economy, and society but also the transmission dynamics of infectious diseases, thereby impacting public health. The recent experiences with the spread of SARS-CoV-2 and Monkeypox have highlighted the complex and interconnected nature of infectious diseases, which are strongly linked to various determinants of health. Considering these challenges, adopting a new vision such as the trans-disciplinary approach appears to be imperative. This paper proposes a new theory about viruses' spread, based on a biological model, accounting for the optimisation of energy and material resources for organisms' survival and reproduction in the environment. The approach applies Kleiber's law scaling theory, originally developed in biology, to model community dynamics in cities. A simple equation can be used to model pathogen spread without accounting for each species' physiology by leveraging the superlinear scaling of variables with population size. This general theory offers several advantages, including the ability to explain the rapid and surprising spread of both SARS-CoV-2 and Monkeypox. The proposed model shows similarities in the spreading processes of both viruses, based on the resulting scaling factors, and opens new avenues for research. By fostering cooperation and integrating knowledge from different disciplines to effectively tackle the multifaceted dimensions of disease outbreaks, we can work towards preventing future health emergencies. [Display omitted] [ABSTRACT FROM AUTHOR]

The aim of this paper is to examine the return connectedness and multiscale spillovers between the Clean Energy Index and the grain commodity market around COVID-19. Using daily data from January 4, 2017 to July 1, 2022, a time-varying parametric vector autoregressive (TVP-VAR) connectedness approach is first used to reveal connectedness patterns before and during COVID-19. We further used Baruník and Křehlík (2018)'s frequency domain spillover method to assess connectedness in different domain horizons. Our results show spillover effects over time and frequency, with COVID-19 significantly affecting the connectedness of the whole system. Dynamic connectedness peaks significantly after sudden bursts of COVID-19, validating the reported uncertainty. We also documented higher spillover levels in the short term than in the medium and long term. In addition, We find that (i) most clean energy indices are positively affected by the COVID-19 outbreak; (ii) the NASDAQ OMX Bio/Clean Fuels Index and NASDAQ OMX Geothermal Index send spillovers to all grain commodities throughout the sample period, while the WilderHill Clean Energy Index and NASDAQ OMX Wind Energy Index indices are the largest recipients of spillovers from other markets regardless of time horizon; (iii) the OMX Bio/Clean Fuels and OMX Geothermal Energy indices dominate spillover shocks to grain commodity markets. This is the first study to analyse the connectedness and time-frequency dynamics of returns in the green energy index and the grain commodity market. These results provide valuable insights to investors and key policymakers, especially at a time of more significant uncertainty. • Examine the return connectedness between the Clean Energy Index and the grain commodity market. • Dynamic connectedness peaks significantly after sudden bursts of COVID-19. • Higher spillover levels in the short term than in the medium and long term. • OMX Bio/Clean Fuels and OMX Geothermal Energy indices dominate spillover shocks to grain commodity markets. [ABSTRACT FROM AUTHOR]

The title of the Virtual Special Issue (VSI) "SARS-CoV-2 and other pathogenic microorganisms in the environment", clearly indicates a main focus not only on the virus causing the current pandemic, but also on other pathogenic microorganisms and their spatial and temporal dynamics in environmental compartments. Overall, the VSI has received more than 100 submissions relating to most of the possible fields connected to the pandemic, many of them of high scientific value. A rigorous peer-reviewing process has been carried out, with a panel of experts making a great work to evaluate that important number of submissions. As a result, those manuscripts reaching the highest scientific standards were selected for publication. We think that the papers included constitute a set of high-quality contributions, which should help to improve the overall scientific perspective regarding this crucial issue. In this piece, the Editors comment some issues on the papers accepted for publication, and include additional reflections. [ABSTRACT FROM AUTHOR]

We analyse the paper "The spread of SARS-CoV-2 in Spain: Hygiene habits, sociodemographic profile, mobility patterns and comorbidities" authored by Rodríguez-Barranco et al. (2021), published in Environmental Research, vol.192, January 2021. The study was carried out under challenging conditions and provides original data of great value for exploratory purposes. Nevertheless, we found that the authors have not considered the potential effect of the multiple hypothesis testing carried out until obtaining the final model on the increased occurrence of false discoveries by mere chance. After adjusting the results provided in the paper for the effects of multiple testing, we conclude that only one of the five factors cited as statistically significant and relevant in the article, living with someone who has suffered from COVID-19, remained significantly related to the relative prevalence of COVID-19. Therefore, the preeminent role given in the analysed work to walking the dog as one of the main transmission routes of COVID-19 probably does not correspond to an actual effect. Instead, until replicated by other studies, it should be considered a spurious discovery. [ABSTRACT FROM AUTHOR]

The use of electronic nicotine delivery systems (ENDS), or vaping, is a relatively recent phenomenon, and there are various gaps in our current knowledge regarding the specific effects of e-cigarettes, such as their immunological effects. The importance of this question became even more relevant in light of the COVID-19 pandemic. This literature review examines the relationship between the use of electronic nicotine delivery systems (ENDS) and immunological effects to examine available information and identify gaps in the current knowledge. Our search strategy included studies focusing on the effects of ENDS on the immune response during infectious respiratory diseases such as COVID-19 and pneumonia. Peer-reviewed studies presenting quantitative data published from 2007, the year that e-cigarettes were introduced to the US market until 2022 have been included. All studies were indexed in PubMed. We excluded papers on THC and EVALI (E-cigarette, or Vaping Product, Use Associated Lung Injury) as we wanted to focus on the effects of nicotine devices. Among the 21 articles that assessed the relationship between ENDS and immunological health effects, we found eight studies based on cell models, two articles based on both cell and mouse models, five articles based on mouse models, and six studies of human populations. Most of the articles identified in our review demonstrated a potential association between vaping and adverse immunological health effects. Overall, the evidence from the cell and animal studies indicates that there is a positive, statistically significant association between vaping and adverse immune response during infectious respiratory diseases. The evidence from human studies is not conclusive. [ABSTRACT FROM AUTHOR]

Several waves of COVID-19 caused by different SARS-CoV-2 variants have been recorded worldwide. During this period, many publications were released describing the influence of various factors, such as environmental, social and economic factors, on the spread of COVID-19. This paper presents the results of a detailed spatiotemporal analysis of the course of COVID-19 cases and deaths in five waves in Poland in relation to green‒blue spaces. The results, based on 380 counties, reveal that the negative correlation between the indicator of green‒blue space per inhabitant and the average daily number of COVID-19 cases and deaths was clearly visible during all waves. These relationships were described by a power equation (coefficient of determination ranging from 0.83 to 0.88) with a high level of significance. The second important discovery was the fact that the rates of COVID-19 cases and deaths were significantly higher in urban counties (low values of the green–blue space indicator in m2/people) than in rural areas. The developed models can be used in decision-making by local government authorities to organize anti-COVID-19 prevention measures, including local lockdowns, especially in urban areas. • Five waves of COVID-19 in Poland during 800 days of the pandemic were compared. • Green–blue spaces were negatively associated with COVID-19 cases and deaths. • There were many more COVID-19 incidences in urban areas in Poland than in rural areas. • Green–blue spaces can be used in the prevention of COVID-19 disease. [ABSTRACT FROM AUTHOR]

Recently Artificial Intelligence(AI) has not only been used to diagnose the disease but also to cure the disease. Researchers started using AI for drug discovery. Predicting the Adverse Drug Reactions(ADRs) caused by the drug in the manufacturing stage or in the clinical trial stage is a very important problem in drug discovery. ADRs have become a major concern resulting in injuries and also becoming fatal sometimes. Drug safety has gained much importance over the years propelling to the forefront investigation of predicting the ADRs. Although prior studies have queried diverse approaches to predict ADRs, very few were found to be effective. Also, the problem of having fewer reports makes the prediction of ADRs more difficult. To tackle this problem effectively, a novel method has been proposed in this paper. The proposed method is based on Knowledge Graph(KG) embedding. Using the KG embedding, we designed and trained a custom-made Deep Neural Network(DNN) called KGDNN(Knowledge Graph DNN) for predicting the ADRs. A KG has been constructed with 6 types of entities: drugs, ADRs, target proteins, indications, pathways, and genes. Using the Node2Vec algorithm, each node has been embedded into a feature space. Using those embeddings, the ADRs are classified by the KGDNN model. The proposed method has obtained an AUROC score of 0.917 and significantly outperformed the existing methods. Two case studies on drugs causing liver injury and COVID-19 recommended drugs have been performed to illustrate the model efficacy. [ABSTRACT FROM AUTHOR]

This paper examines and projects the water use and wastewater generation during and after the SARS-CoV-2 (COVID-19) in China, and discussed the water use/wastewater generation pattern changes among different sectors. Existing studies on the impact of pandemic spread-prevention measures on water consumption and wastewater treatment during the pandemic are reviewed. The water use and wastewater discharge in China through the COVID-19 period are then projected and analyzed using Multivariate Linear Regression. The projection is carried out for years 2019–2023 and covers an (estimated) full process of pre-pandemic, pandemic outbreak, and recovery phase and provides essential information for determining the complete phase impact of the COVID-19. Two scenarios, i.e. the recovery scenario and the business as usual scenario, are set to investigate the water use and wastewater generation characteristics after the pandemic. The results imply that in both scenarios, the water use in China shows a V-shaped trend from 2019 to 2023 and reached a low point in 2020 of 5,813✕108 m3. The wastewater discharge shows an increasing trend throughout the COVID period in both scenarios. The results are also compared with the water consumption and wastewater generation during the SARS-CoV-1 period. The implication for policymakers is the possible increase of water use and wastewater discharge in the post COVID period and the necessity to ensure the water supply and control of water pollution and wastewater discharge. • The impact of the SARS-CoV-2 pandemic on the water sector are reviewed. • Water use and wastewater discharge throughout the COVID-19 period are projected. • Water use in China shows a V-shaped trend from 2019 to 2023. • Wastewater discharge shows an increasing trend throughout the COVID period. • Water use and wastewater discharge during the SARS and the COVID-19 are compared. [ABSTRACT FROM AUTHOR]

Testing multiple treatments for heterogeneous (varying) effectiveness with respect to many underlying risk factors requires many pairwise tests; we would like to instead automatically discover and visualize patient archetypes and predictors of treatment effectiveness using multitask machine learning. In this paper, we present a method to estimate these heterogeneous treatment effects with an interpretable hierarchical framework that uses additive models to visualize expected treatment benefits as a function of patient factors (identifying personalized treatment benefits) and concurrent treatments (identifying combinatorial treatment benefits). This method achieves state-of-the-art predictive power for COVID-19 in-hospital mortality and interpretable identification of heterogeneous treatment benefits. We first validate this method on the large public MIMIC-IV dataset of ICU patients to test recovery of heterogeneous treatment effects. Next we apply this method to a proprietary dataset of over 3000 patients hospitalized for COVID-19, and find evidence of heterogeneous treatment effectiveness predicted largely by indicators of inflammation and thrombosis risk: patients with few indicators of thrombosis risk benefit most from treatments against inflammation, while patients with few indicators of inflammation risk benefit most from treatments against thrombosis. This approach provides an automated methodology to discover heterogeneous and individualized effectiveness of treatments. [ABSTRACT FROM AUTHOR]

This paper investigates at the world level the influence of climate on the transmission of the SARS-CoV-2 virus. For that purpose, panel regressions of the number of cases and deaths from 134 countries are run on a set of explanatory variables (air temperature, relative humidity, precipitation, and wind) along with control variables (government interventions and population size and density). The analysis is completed with a panel threshold regression to check for potential non-linearities of the weather variables on virus transmission. The main findings support the role of climate in the circulation of the virus across countries. The detailed analysis reveals that relative humidity reduces the number of cases and deaths in both low and high regimes, while temperature and wind reduce the number of deaths. [ABSTRACT FROM AUTHOR]

The impact of the SARS-CoV pandemic has gone well beyond health concerns, reaching the maritime industry. The study on the environmental impact of shipping industry during COVID-19 pandemic can provide useful insights to propose new management policies regarding shipping operations, both in-port and on the route. We present a case study centred in the Port of Barcelona covering a 30 nautical miles range in the period March to July 2020, during which different levels of restrictions and stringent lockdown measures were enforced. In this paper, we assess the impact of COVID-19 on maritime traffic and its related emissions in port cities using real-time Automatic Identification System (AIS) data. Interestingly, results show that the decline in maritime traffic is not correlated with a decrease in maritime emissions due to changes in vessel operation. During lockdown (March to June 2020), we observed a 27.9% reduction in the number of port calls compared to the pre-lockdown scenario, whereas pollutant emissions show a moderate decrease (1.8% for CO 2), no significant reduction (SO 2 and PM) or a slight increase (1.3% for NO x). This can be directly assigned to changes in vessel operation mode, i.e. vessels switched from Underway to At Anchor or Moored status, during which auxiliary engines are used at higher loads. • The pollutant emissions evolution from maritime activity is computed from AIS data during COVID-19 restrictions in 2020. • A significant reduction in ship calls was observed, with a mild reduction in maritime traffic in the same area. • Passenger vessels were responsible for more than 40% of fuel consumption and emissions, but represented 17% of all vessels • Ships underway dominated the total emissions during lockdown, although theydecreased during this period. [ABSTRACT FROM AUTHOR]

Counteracting the spread of the SARS-CoV-2 virus is a current and important problem. A crucial issue in this area is the disinfection of various surfaces, as well as the air itself. For this purpose, devices such as foggers, which have different designs, are used. The appropriate size of droplets and their distribution determines the effectiveness of disinfectants. The paper presents droplet size distributions and characteristic mean droplet diameters, which are obtained with the use of a conical pressure-swirl atomizer. For the purpose of the analysis, the laser diffraction method was used. The influence of gas pressure and the distance from the atomizer's orifice on the spray angle and the distance between the nozzles on the spray curtain was also demonstrated. • The laser diffraction method was used. • The droplet size distributions and droplet mean diameters were analyzed. • The effect of gas pressure and the distance from the orifice were presented. • The spray angle was determined. • The distribution of the nozzles on the curtain's support frame was analyzed. [ABSTRACT FROM AUTHOR]

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. 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. 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. An increase in the average long-term air pollution of 1 μg/m3 particulate matter PM 2.5 is correlated with 199.46 (SD = 29.66) more COVID-19 cases per 100,000 inhabitants in Germany. For PM 10 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 PM 2.5 and PM 10 (6.18, SD = 1.44, respectively 2.11, SD = 0.71, additional COVID-19 deaths per 100,000 inhabitants). 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. • COVID-19 infections are substantially positively correlated with long-term particulate matter concentration in German counties. • The correlation is robust to the inclusion of relevant control variables in multiple OLS regressions. • COVID-19 fatalities are also positively correlated with long-term particulate matter concentration. • The correlation between particulate matter concentration and COVID-19 fatalities was not robust. [ABSTRACT FROM AUTHOR]

Background: In this paper we propose a novel framework for the definition of Personas for healthcare workers based on an online survey, with the aim of highlighting different levels of risk of developing mental disorders induced by COVID-19 and tailor psychological support interventions.Methods: Data were gathered from Italian healthcare workers between April and May 2020. Information about socio-demographic characteristics, current lifestyle, occupational, COVID-19 infection, and psychological indexes (Maslach Burnout Inventory, Impact of Event Scale and Patient Health Questionnaire) was collected. Respondents were divided in four subgroups based on their health profession: physicians (P), nurses (N), other medical professionals (OMP) and technical-administrative (TA). For each sub-group, collected variables (46) were reduced using Principal Component Analysis and clustered by means of k-medoids clustering. Statistical analysis was then applied to define which variables were able to differentiate among the k clusters, leading to the generation of a Persona card (i.e., a template with textual and graphical information) for each of the obtained clusters.Results: From the 538 respondents (153 P, 175 N, 176 OMP, 344 TA), the highest stress level, workload impact and risk of mental disorders were found in the N subgroup. Two clusters were identified for P, three clusters for N, two for OMP and one for TA.Conclusions: The proposed framework was able to stratify different risk levels of possible development of mental health issues in healthcare workers due to COVID-19. This approach could represent the first step towards the development of mobile health tools to tailor psychological interventions in pandemic situations. [ABSTRACT FROM AUTHOR]

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. • Climate factors and air quality can trigger SARS-CoV-2 viral infection transmission. • Synoptic atmospheric circulation patterns are related to COVID-19 waves start-up. • 1st and 4th COVID-19 waves have similar correlations with environmental variables. • COVID-19 and climate driving factors have mutual seasonality patterns in Madrid. • Early health strategies are essential to control the COVID-19 pandemic in Madrid. [ABSTRACT FROM AUTHOR]

COVID-19 forced the human population to rethink its way of living. The threat posed by the potential spread of the virus via an airborne transmission mode through ventilation systems in buildings and enclosed spaces has been recognized as a major concern. To mitigate this threat, researchers have explored different technologies and methods that can remove or decrease the concentration of the virus in ventilation systems and enclosed spaces. Although many technologies and methods have already been researched, some are currently available on the market, but their effectiveness and safety concerns have not been fully investigated. To acquire a broader view and collective perspective of the current research and development status, this paper discusses a comprehensive review of various workable technologies and methods to combat airborne viruses, e.g., COVID-19, in ventilation systems and enclosed spaces. These technologies and methods include an increase in ventilation, high-efficiency air filtration, ionization of the air, environmental condition control, ultraviolet germicidal irradiation, non-thermal plasma and reactive oxygen species, filter coatings, chemical disinfectants, and heat inactivation. Research gaps have been identified and discussed, and recommendations for applying such technologies and methods have also been provided in this article. • Comprehensive review of COVID-19 mitigation methods focusing on HVAC systems. • Investigated methods include ventilation, filtration, and air ionization. • Other featured methods include environmental conditioning and ultraviolet light. • Developing technologies include heat, nanoparticles, chemical, and plasma methods. • Identified research gaps provide paths for future work and development. [ABSTRACT FROM AUTHOR]