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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]

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]

Coronaviruses are responsible on respiratory diseases in animal and human. The combination of numerical encoding techniques and digital signal processing methods are becoming increasingly important in handling large genomic data. In this paper, we propose to analyze the SARS-CoV-2 genomic signature using the combination of different nucleotide representations and signal processing tools in the aim to identify its genetic origin. The sequence of SARS-CoV-2 was compared with 21 relevant sequences including Bat, Yak and Pangolin coronavirus sequences. In addition, we developed a new algorithm to locate the nucleotide modifications. The results show that the Bat and Pangolin coronaviruses were the most related to SARS-CoV-2 with 96% and 86% of identity all along the genome. Within the S gene sequence, the Pangolin sequence presents local highest nucleotide identity. Those findings suggest genesis of SARS-Cov-2 through evolution from Bat and Pangolin strains. This study offers new ways to automatically characterize viruses. • We propose to analyze the SARS-CoV-2 genomic signature using the combination of different nucleotide representations in the aim to identify its genetic origin. • The SARS-CoV-2 sequence was compared with 21 relevant sequences including Bat, Yak and Pangolin coronavirus sequences. • the Bat and Pangolin coronaviruses were the most related to SARS-CoV-2 • Within the S gene sequence, the Pangolin sequence presents local highest nucleotide identity. • This study suggests genesis of SARS-Cov-2 through evolution from bat and pangolin strains. [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]

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]

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]

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]

We present an overview of the TREC-COVID Challenge, an information retrieval (IR) shared task to evaluate search on scientific literature related to COVID-19. The goals of TREC-COVID include the construction of a pandemic search test collection and the evaluation of IR methods for COVID-19. The challenge was conducted over five rounds from April to July 2020, with participation from 92 unique teams and 556 individual submissions. A total of 50 topics (sets of related queries) were used in the evaluation, starting at 30 topics for Round 1 and adding 5 new topics per round to target emerging topics at that state of the still-emerging pandemic. This paper provides a comprehensive overview of the structure and results of TREC-COVID. Specifically, the paper provides details on the background, task structure, topic structure, corpus, participation, pooling, assessment, judgments, results, top-performing systems, lessons learned, and benchmark datasets. [ABSTRACT FROM AUTHOR]

The emergence of the novel coronavirus has necessitated immense research efforts to understand how several non-environmental and environmental factors affect transmission. With the United States leading the path in terms of case incidence, it is important to investigate how weather variables influence the spread of the disease in the country. This paper assembles a detailed and comprehensive dataset comprising COVID-19 cases and climatological variables for all counties in the continental U.S. and uses a developed econometric approach to estimate the causal effect of certain weather factors on the growth rate of infection. The results indicate a non-linear and significant negative relationship between the individual weather measures and the growth rate of COVID-19 in the U.S. Specifically, the paper finds that a 1 °C rise in daily temperature will reduce daily covid growth rate in the U.S. by approximately 6 percent in the following week, while a marginal increase in relative humidity reduces the same outcome by 1 percent over a similar period. In comparison, a 1 m/s increase in daily wind speed will bring about an 8 percent drop in daily growth rate of COVID-19 in the country. These results differ by location and are robust to several sensitivity checks, so large deviations are unexpected. • This paper develops a temporal model to estimate daily weather fluctuation's effects on growth rate of COVID-19 infection. • Marginal increases in temperature, relative humidity and wind speed reduces COVID-19 growth rate. • The effect of weather fluctuations on COVID-19 growth rate is non-linear. • The impact of weather changes differ by geography. [ABSTRACT FROM AUTHOR]

There a lot of review papers addressing specific COVID-19 research sectors, then devoted to specialists. This review provides an in-depth summary of the available information about SARS-CoV-2 and the corresponding disease (also known as COVID-19), with a multi-disciplinary approach. After the paper introduction, the first section treats the virological characteristics of SARS-CoV-2, the medical implications of the infection, and the human susceptivity. Great attention is devoted to the factor affecting the infection routes, distinguishing among the possible human-to-human, environmental-to-human, and pollution-to-human transmission mechanisms. The second section is devoted to reporting the impact of SARS-CoV-2 not only on the healthcare systems but also on the economy and society. The third section is devoted to non-pharmaceutical behaviours against COVID-19. In this context, this review section presents an analysis of the European second wave allowing not only to focalize the importance of some restrictions, but also the relevance of social acceptance of some measures. The data reassumed in this work are very useful for interdisciplinary researchers that work in a team to find the basic available information about all the aspects connected with this pandemic (from virus diffusion mechanism to health information, from economic and social impacts to measures to reduce the pandemic spread), with great attention to social acceptance of restriction measures and of vaccines (that currently results to be insufficient to achieve community immunity). Then, this review paper highlights the fundamental role of the trans-multi-disciplinary research that is devoted not only to understand the basics of the pandemic to propose solutions but has also the commitment to find strategies to increase population resilience. For this aim, the authors strongly suggest the establishment of an international health-care trans-multi-disciplinary workforce devoted to investigate, mitigate, and control also future viral events. [Display omitted] • COVID-19 is a highly transmissible disease that has spread all over the globe. • The interdisciplinary research strategy in pandemic has a basic role. • Some concerns due to the reported transmission mechanisms must be better investigated. • The social acceptance of vaccine and restriction measures must be improved. • A health-care multidisciplinary workforce for pandemic study should be established. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has imposed a global emergency and also has raised issues with waste management practices. This study emphasized the challenges of increased waste disposal during the COVID-19 crisis and its response practices. Data obtained from the scientific research papers, publications from the governments and multilateral organizations, and media reports were used to quantify the effect of the pandemic towards waste generation. A huge increase in the amount of used personal protective equipments (facemasks, gloves, and other protective stuffs) and wide distribution of infectious wastes from hospitals, health care facilities, and quarantined households was found. The amount of food and plastic waste also increased during the pandemic. These factors caused waste treatment facilities to be overwhelmed, forcing emergency treatment and disposals (e.g., co-disposal in a municipal solid waste incinerator, cement kilns, industrial furnaces, and deep burial) to ramp up processing capacity. This paper discussed the ways the operation of those facilities must be improved to cope with the challenge of handling medical waste, as well as working around the restrictions imposed due to COVID-19. The study also highlights the need for short, mid, and longer-term responses towards waste management during the pandemic. Furthermore, the practices discussed in this paper may provide an option for alternative approaches and development of sustainable strategies for mitigating similar pandemics in the future. [Display omitted] • COVID-19 exhibited great challenges and practices on waste management. • The discarded facemask was estimated during COVID-19 pandemic. • Immediate responses and technological approach for COVID-19 crisis were reviewed. • MSW incinerator, industrial furnace, cement kiln can be used as emergency disposal. • Short and mid-longer term responses in waste management were provided. [ABSTRACT FROM AUTHOR]

The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in water and wastewater has recently been reported. According to the updated literature, the stools and masks of the patients diagnosed with coronavirus disease (COVID-19) were considered as the primary route of coronavirus transmission into water and wastewater. Most coronavirus types which attack human (possible for SARS-CoV-2) are often inactivated rapidly in water (i.e., the survival of human coronavirus 229E in water being 7 day at 23 °C). However, the survival period of coronavirus in water environments strongly depends on temperature, property of water, concentration of suspended solids and organic matter, solution pH, and dose of disinfectant used. The World Health Organization has stated that the current disinfection process of drinking water could effectively inactivate most of the bacterial and viral communities present in water, especially SARS-CoV-2 (more sensitive to disinfectant like free chlorine). A recent study confirmed that SARS-CoV-2 RNA was detected in inflow wastewater (but not detected in outflow one). Although the existence of SARS-CoV-2 in water influents has been confirmed, an important question is whether it can survive or infect after the disinfection process of drinking water. To date, only one study confirmed that the infectivity of SARS-CoV-2 in water for people was null based on the absence of cytopathic effect (CPE) in infectivity tests. Therefore, further studies should focus on the survival of SARS-CoV-2 in water and wastewater under different operational conditions (i.e., temperature and water matrix) and whether the transmission from COVID-19-contaminated water to human is an emerging concern. Although paper-based devices have been suggested for detecting the traces of SARS-CoV-2 in water, the protocols and appropriate devices should be developed soon. Wastewater and sewage workers should follow the procedures for safety precaution against SARS-CoV-2 exposure. • SARS-CoV-2 coronavirus detected in water and wastewater. • Transmission route of SARS-CoV-2 into water through stool and mask of infected patient. • Coronavirus often inactivated rapidly in water. • Paper-based devices suggested for detecting traces of SARS-CoV-2 in water. • Existing disinfection processes possibly sufficient to kill SARS-CoV-2 in water. [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]

The outbreak of coronavirus disease (COVID-19) not only affected health and economics, but also its effect extended to include other aspects, such as the environment. Using Egypt as a case study, this paper presents the impact of COVID-19 pandemic on air pollution levels by studying nitrogen dioxide (NO 2), ozone (O 3), particulate matter represented in absorbing aerosol index (AAI), carbon monoxide (CO), and greenhouse gas (GHG) emissions. The paper also highlights the impact of COVID-19 pandemic on other environmental indicators including environmental noise, medical and municipal solid wastes. The paper presents the Egyptian COVID-19 story from its different angles including the development of confirmed COVID-19 cases, containment measures from the government, the impact on the country's economy and the national energy consumption so as to effectively evaluate the effect on both the air pollution levels and the other studied environmental indicators. For the other environmental indicators, a strong link was observed between COVID-19 lockdown and the reduction in environmental noise, beaches, surface and groundwater pollution. For environmental noise, this has been confirmed by officially governmental announcements which reported that the level of environmental noise in Egypt was reduced by about 75% during the lockdown period. On the other hand, there are some negative effects, including an increase in medical solid waste (from 70 to 300 ton/day), municipal solid waste, as well as a less efficient solid waste recycling process. For air pollution levels, the data were obtained from National Aeronautics and Space Administration (NASA) and European Space Agency satellite data sets. The data for the lockdown period in 2020 have been extracted and compared to the corresponding months in the selected baseline period (2015–2019) to identify the effect that the lockdown period had on the air pollution levels in Egypt with focus on Cairo and Alexandria governorates. It was found that the AAI decreased by about 30%, the NO 2 decreased by 15 and 33% over Cairo and Alexandria governorates, respectively, and that the CO decreased by about 5% over both governorates. In addition, the GHG emissions in Egypt were reduced by at least 4% during the pandemic. In contrast, ozone levels increased by about 2% over Cairo and Alexandria governorates. It can be concluded that the implemented containment measures during COVID-19 pandemic had resulted in both positive and negative environmental impacts. The positive environmental impacts are not sustainable and deterioration on them is expected to occur after the lockdown as it was before the pandemic. Therefore, stricter laws must be enacted to protect the environment in Egypt. Image 1 • NO 2 decreased over Cairo (~ 15%) and Alexandria (~ 33%). • AAI and GHG emissions of Egypt decreased by about 30% and 4%, respectively. • An increase in ozone level (2%) and a reduction in CO (5%) over Cairo and Alexandria. • Reduction in environmental noise, beaches, surface and groundwater pollution. • Increase municipal and medical wastes and less efficient waste recycling. [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]

17 years after the outbreak of SARS, the 2019-nCoV broke out in December 2019. It's an unprecedented huge challenge and disaster for people all over the world. According to Web of Science database, The author found that 95,724 virology papers have been published in the past 17 years, 68,632 of which are supported by fund (71.7%). Meanwhile, 50,567 papers related to food safety have been published in the past 17 years, 28,165 of which are supported by fund (55.7%%). It seems that people's safety and global stability are greatly guaranteed. However, whether SARS or 2019-nCoV, scientists were targeting wildlife, the author found that only 515 studies on food safety related to wildlife have been published worldwide in the past 17 years. After SARS, the whole world did not pay enough attention to food safety related to wildlife. [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]

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]

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]

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]

Since the appearance of the first cases of COVID-19 in 2019, an unprecedented number of documents on that disease have been published in a short space of time. The current available information covers a large number of topics related with COVID-19 and/or the coronavirus (SARS-CoV-2) responsible of the disease. However, only a limited number of publications have been focused on a controversial issue: the origin of the SARS-CoV-2. In this paper, the scientific literature on the origin of SARS-CoV-2 has been reviewed. Documents published during 2020 and 2021 (January 1-July 19) in journals that are indexed in PubMed and/or Scopus has been considered. The revised studies were grouped according to these two potential origins: natural and unnatural. The analyses of the conclusions of the different documents here assessed show that even considering the zoonotic hypothesis as the most likely, with bats and pangolins being possibly in the origin of the coronavirus, today's date the intermediate source species of SARS-CoV-2 has not been confirmed yet. On the other hand, some researchers point to an unnatural origin of this coronavirus, but their conclusions are not strongly supported by a clear scientific evidence. Given the tremendous severity of the current pandemic, investigations to establish clearly and definitively the origin of SARS-CoV-2, are basic and essential in order to prevent potential future pandemics of similar nature. [ABSTRACT FROM AUTHOR]

COVID-19 virus can replicate in the infected individual's larynx independently, which is different from other viruses that replicate in lungs only, e.g. SARS. It might contribute to the fast spread of COVID-19. However, there are few scientific reports about quantitative comparison of COVID-19 exposure dose (inhalation dose and adhesion dose) for the susceptible individual when the viruses were released from the larynx or lungs. In this paper, a typical numerical model was built based on a breathing human model with real respiratory tract. By using a computational fluid dynamics (CFD) method, two kinds of virus released sites in the infected individual's respiratory tract (larynx, lungs), seven kinds of particle sizes between 1 and 50 μm, three kinds of expiratory flow rates: calm (10 L/min), moderate (30 L/min) and intense (90 L/min) were used to compare the particle deposition proportion and escape proportion. The inhalation dose and the adhesion dose of the susceptible individual were quantified. The results showed that COVID-19 virus-containing droplets and aerosols might be released into the environment at higher proportions (39.1%–44.2%) than viruses that replicate in lungs only (15.3%–37.1%). The exposure doses (inhalation dose and adhesion dose) of the susceptible individual in different situations were discussed. The susceptible individual suffered a higher exposure dose when the viruses were released from the larynx rather than lungs (the difference for 1 μm particles was 1.2–2.2 times). This study provides a possible explanation for the higher transmission risk of COVID-19 virus compared to other viruses and some control advice of COVID-19 in typical indoor environments were also discussed. • A possible explanation for the high infection rate of COVID-19 was proposed. • Particles released from larynx had a higher escape proportion than those from lungs. • Small particles might dominate the inhalation exposure dose even at a close range of 0.5 m. • Process of virus from infected individual's respiratory tract to the susceptible was constructed. [ABSTRACT FROM AUTHOR]

Many environmental justice communities face elevated exposures to multiple stressors, given biases in urban and environmental policy and planning. This paper aims to evaluate sound level exposure in a densely populated environmental justice city in close proximity to major roadways, a nearby airport and high levels of industrial activity. In this study we collected various sound level metrics to evaluate the loudness and frequency composition of the acoustical environment in Chelsea, Massachusetts, USA. A total of 29 week-long sites were collected from October 2019 to June 2020, a time period that also included the influence of the COVID-19 pandemic, which drastically altered activity patterns and corresponding sound level exposures. We found that Chelsea is exposed to high levels of sound, both day and night (65 dB (A), and 80 dB and 90 dB for low frequency, and infrasound sound levels). A spectral analysis shows that 63 Hz was the dominant frequency. Distance to major roads and flight activity (both arrivals and departures) were most strongly correlated with all metrics, most notably with metrics describing contributing from lower frequencies. Overall, we found similar patterns during the COVID-19 pandemic but at levels up to 10 dB lower. Our results demonstrate the importance of noise exposure assessments in environmental justice communities and the importance of using additional metrics to describe communities inundated with significant air, road, and industrial sound levels. It also provides a snapshot of how much quieter communities can be with careful and intentional urban and environmental policy and planning. • We conducted a noise exposure assessment before and during COVID-19 stay-at-home advisories in an environmental justice and sanctuary city. • Like many EJCs, this city is in close proximity to major rail, road, and air networks and industrial operations.Pre-pandemic, Chelsea was exposed to similar sound levels, both day and night, across all metrics. • A spectral analysis shows that 63 Hz was the dominant frequency.Distance to major roads and flight activity (both arrivals and departures) were most strongly correlated with all metrics, most notably with metrics describing contributing from lower frequencies. • Overall, we found similar patterns during the COVID-19 pandemic but at levels up to 10 decibels lower. • Comprehensive noise assessments in EJCs are particularly important as they house our most vulnerable residents. • We also show the importance of using additional metrics to describe communities inundated with significant air, road, and industrial sources. • We also provide a shot of how much quieter EJCs can be with careful and intentional urban and environmental policy and planning. [ABSTRACT FROM AUTHOR]

One of the problems hardly clarified in Coronavirus Disease 2019 (COVID-19) pandemic crisis is to identify factors associated with a lower mortality of COVID-19 between countries to design strategies to cope with future pandemics in society. The study here confronts this problem by developing a global analysis based on more than 160 countries. This paper proposes that Gross Domestic Product (GDP) per capita, healthcare spending and air pollution of nations are critical factors associated with fatality rate of COVID-19. The statistical evidence seems in general to support that countries with a low average COVID-19 fatality rate have high expenditures in health sector >7.5% of GDP, high health expenditures per capita >$2,300 and a lower exposure of population to days exceeding safe levels of particulate matter (PM 2.5). Another relevant finding here is that these countries have lower case fatality rates (CFRs) of COVID-19, regardless a higher percentage of population aged more than 65 years. Overall, then, this study finds that an effective and proactive strategy to reduce the negative impact of future pandemics, driven by novel viral agents, has to be based on a planning of enhancement of healthcare sector and of environmental sustainability that can reduce fatality rate of infectious diseases in society. • Expenditures in health sector >7.5% of GDP can reduce COVID-19 mortality between countries. • Health expenditures >$2,300 per capita can lessen COVID-19 mortality between countries. • Lower exposure of population to days having high levels of air pollution reduces COVID-19 mortality. • High health expenditures reduce COVID-19 mortality, though a high share of older population. • Efficient healthcare sector and environmental sustainability minimize case fatality rates of COVID-19. [ABSTRACT FROM AUTHOR]

The coronavirus has come to the world and spread with great wide among the countries of the world and has resulted in numerous infections that exceeded 167,181,023 million patients and are close to 3.5 deaths by September 2021. It also brought with it panic and fear, halted many activities, and led to the decline of the global economy. It changed human behavior and forced people to change their lifestyles to avoid infection. One of the most sectors that must be taken into consideration through pandemic coronavirus (COVID-19) around the globe is the air conditioning systems. The HVAC systems depend on the air as a heat transfer medium. The air contains a group of pollutants, viruses, and bacteria, and it affects and destroys human life. The air filter plays a major role as an important component in the air conditioning systems. Thus, it requires more effort by researchers to improve its design to prevent the ultra-size of particles loaded with coronavirus (COVID-19). This paper provides insight into the design of existing combined air-conditioners on their suitability and their impact on the spread of the hybrid coronavirus epidemic and review efforts to obtain a highly efficient air filter to get rid of super-sized particles for protection against epidemic infection. In addition, important guideline recommendations have been made to limit the spread of the COVID-19 virus and to obtain indoor air quality in air-conditioned places. • Indoor air quality is important in our society and provides healthy human comfort. • Increasing the temperatures and humidity dampen the activity of the COVID-19. • The air carries suspended particles of the COVID-19, which leads to an increase in infected cases. • Improper use of filters leads to spread of the bacterial and viruses' indoor environment. • Mandatory recommendations are drawn to benefit the global community to limit the spread of the deadly COVID-19. [ABSTRACT FROM AUTHOR]

Effective strategies to restrain COVID-19 pandemic need high attention to mitigate negatively impacted communal health and global economy, with the brim-full horizon yet to unfold. In the absence of effective antiviral and limited medical resources, many measures are recommended by WHO to control the infection rate and avoid exhausting the limited medical resources. Wearing a mask is among the non-pharmaceutical intervention measures that can be used to cut the primary source of SARS-CoV2 droplets expelled by an infected individual. Regardless of discourse on medical resources and diversities in masks, all countries are mandating coverings over the nose and mouth in public. To contribute towards communal health, this paper aims to devise a highly accurate and real-time technique that can efficiently detect non-mask faces in public and thus, enforcing to wear mask. The proposed technique is ensemble of one-stage and two-stage detectors to achieve low inference time and high accuracy. We start with ResNet50 as a baseline and applied the concept of transfer learning to fuse high-level semantic information in multiple feature maps. In addition, we also propose a bounding box transformation to improve localization performance during mask detection. The experiment is conducted with three popular baseline models viz. ResNet50, AlexNet and MobileNet. We explored the possibility of these models to plug-in with the proposed model so that highly accurate results can be achieved in less inference time. It is observed that the proposed technique achieves high accuracy (98.2%) when implemented with ResNet50. Besides, the proposed model generates 11.07% and 6.44% higher precision and recall in mask detection when compared to the recent public baseline model published as RetinaFaceMask detector. The outstanding performance of the proposed model is highly suitable for video surveillance devices. [ABSTRACT FROM AUTHOR]

In this paper we develop a simple model of the inhaled flow rate of aerosol particles of respiratory origin i.e. that have been exhaled by other people. A connection is made between the exposure dose and the probability of developing an airborne disease. This allows a simple assessment of the outdoor versus indoor risk of contamination to be made in a variety of meteorological situations. It is shown quantitatively that for most cases, the outdoor risk is orders of magnitude less than the indoor risk and that it can become comparable only for extremely specific meteorological and topographical situations. It sheds light on various observations of COVID-19 spreading in mountain valleys with temperature inversions while at the same time other areas are much less impacted. • Risk of COVID-19 airborne transmission. • Quantitative assessment of outdoor versus indoor airborne risk of transmission. • Meteorological and topographical influence on COVID-19 airborne transmission. [ABSTRACT FROM AUTHOR]

Heat waves and Covid-19 overlap, as this pandemic continues into summer 2021. Using a narrative review, we identified overlapping risk groups and propose coping strategies. The high-risk groups for heat-related health problems as well as for high-risk COVID-19 groups overlap considerably (elderly with pre-existing health conditions). Health care facilities will again be challenged by Covid-19 during heat waves. Health care personnel are also at risk of developing heat related health problems during hot periods due to the use of personal protective equipment to shield themselves from SARS-CoV-2 and must therefore be protected from excessive heat periods. Some existing recommendations for heat health protection contradict recommendations for COVID-19 protection. This paper provides a preliminary overview of possible strategies and interventions to tackle these ambiguities. The existing recommendations for protection against heat-related illnesses need revisions to determine whether they include essential aspects of infection control and occupational safety and how they may be supplemented. • Hot days and heat waves due to climate change are on the rise. • SARS-CoV-2 AND heat stress cause illnesses and fatalities. • Vulnerable groups are old and chronically ill people. • Recommendations to protect them against heat AND SARS-CoV-2 need to be adapted. • Adjusted heat health action plans need to be monitored and evaluated for effectiveness and lessons learnt. [ABSTRACT FROM AUTHOR]

Meteorological conditions may influence the incidence of many infectious diseases. Coronavirus disease-2019 (COVID-19) is a highly contagious, air-borne, emerging, viral disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). In 2020, the COVID-19 global pandemic affected more than 210 countries and territories worldwide including Saudi Arabia. There are contradictory research papers about the correlation between meteorological parameters and incidence of COVID-19 in some countries worldwide. The current study investigates the impact of outdoor and indoor meteorological conditions on the daily recorded COVID-19 cases in western region (Makkah and Madinah cities) of Saudi Arabia over a period of 8 months from March to October 2020. Reports of the daily confirmed COVID-19 cases from the webpage of Saudi Ministry of Health (MOH) were used. Considering, the incubation period of COVID-19 which ranged from 2 to 14 days, the relationships between daily COVID-19 cases and outdoor meteorological factors (temperature, relative humidity, and wind speed) using a lag time of 10 days are investigated. The results showed that the highest daily COVID-19 cases in Makkah and Madinah were reported during the hottest months of the year (April–July 2020) when outdoor temperature ranged from 26.51 to 40.71 °C in Makkah and of 23.89–41.20 °C in Madinah, respectively. Partial negative correlation was detected between outdoor relative humidity and daily recorded COVID-19 cases. No obvious correlation could be demonstrated between wind speed and daily COVID-19 cases. This indicated that most of SARS-CoV-2 infection occurred in the cool, air-conditioned, dry, and bad-ventilated indoor environment in the investigated cities. These results will help the epidemiologists to understand the correlation between both outdoor and indoor meteorological conditions and SARS-CoV-2 transmissibility. These findings would be also a useful supplement to assist the local healthcare policymakers to implement and apply a specific preventive measures and education programs for controlling of COVID-19 transmission. [Display omitted] • No significant correlation between outdoor temperature and daily reported COVID-19 cases in western region of Saudi Arabia. • Partial negative association of outdoor relative humidity with daily recorded COVID-19 cases. • Almost all COVID-19 cases result from indoor infection among the households. • Pre-symptomatic and asymptomatic infected individuals facilitate household infection spread. • Prevention of indoor infection assists COVID-19 control especially in tropical and hyper-arid countries. [ABSTRACT FROM AUTHOR]

Within the recent pandemic, scientists and clinicians are engaged in seeking new technology to stop or slow down the COVID-19 pandemic. The benefit of machine learning, as an essential aspect of artificial intelligence, on past epidemics offers a new line to tackle the novel Coronavirus outbreak. Accurate short-term forecasting of COVID-19 spread plays an essential role in improving the management of the overcrowding problem in hospitals and enables appropriate optimization of the available resources (i.e., materials and staff).This paper presents a comparative study of machine learning methods for COVID-19 transmission forecasting. We investigated the performances of deep learning methods, including the hybrid convolutional neural networks-Long short-term memory (LSTM-CNN), the hybrid gated recurrent unit-convolutional neural networks (GAN-GRU), GAN, CNN, LSTM, and Restricted Boltzmann Machine (RBM), as well as baseline machine learning methods, namely logistic regression (LR) and support vector regression (SVR). The employment of hybrid models (i.e., LSTM-CNN and GAN-GRU) is expected to eventually improve the forecasting accuracy of COVID-19 future trends. The performance of the investigated deep learning and machine learning models was tested using confirmed and recovered COVID-19 cases time-series data from seven impacted countries: Brazil, France, India, Mexico, Russia, Saudi Arabia, and the US. The results reveal that hybrid deep learning models can efficiently forecast COVID-19 cases. Also, results confirmed the superior performance of deep learning models compared to the two considered baseline machine learning models. Furthermore, results showed that LSTM-CNN achieved improved performances with an averaged mean absolute percentage error of 3.718%, among others. [ABSTRACT FROM AUTHOR]