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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]

The world has witnessed the cruelty of COVID-19 disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The association of COVID-19 with other secondary and bacterial co-infections has tremendously contributed to lung infections. An increased probability of having a secondary lung infection was observed among the post-COVID patients. The treatment of antibiotics has ameliorated the mortality rate. However, the stewardship of antibiotic treatment was linked to increased organ failure. Therefore, the paper discusses the interactions between the virus and host through the ACE2 receptors that contribute to COVID-19 development. Furthermore, the paper provides an invaluable compendium history of SARS-CoV-2 genomic composition. It revolves around most classes of antibiotics used to treat COVID-19 disease and post-COVID lung infections with the complete mechanism. This binds with the exertion of the antibiotics for bacterial infection associated with COVID-19 patients and how beneficial and effective responses have been recorded for the treatment. The application of nanotechnology and possible approaches of nanomedicines is also discussed to its potential usage. • COVID-19 with other secondary and bacterial co-infections has contributed to lung infections. • The treatment of antibiotics has ameliorated the mortality rate. However, the stewardship of antibiotic treatment was linked to increased organ failure. • Most classes of antibiotics are used to treat COVID-19 disease and post-COVID lung infections with the complete mechanism. • The application of nanotechnology and possible approaches of nanomedicines is also discussed to its potential usage. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a public health concern worldwide. Ensitrelvir (S-217622) has been evaluated as an antiviral treatment for COVID-19, targeting SARS-CoV-2 3C-like protease (3CLpro). Ensitrelvir has been reported to have comparable antiviral activity against some of the SARS-CoV-2 variants: alpha, beta, gamma, delta, and omicron (BA.1.18). In this paper, we describe that ensitrelvir is effective against newly emerging SARS-CoV-2 variants and globally prevalent 3CLpro mutations. Ensitrelvir exhibited comparable antiviral activity against SARS-CoV-2 variants, including recently emerging ones: omicron (BA1.1, BA.2, BA.2.75, BA.4, BA.5, BQ.1.1, XBB.1, and XE), mu, lambda, and theta. Genetic surveillance of SARS-CoV-2 3CLpro, the target of ensitrelvir, was conducted using a public database and identified 11 major 3CLpro mutations circulating globally (G15S, T21I, T24I, K88R, L89F, K90R, P108S, P132H, A193V, H246Y, and A255V). The 3CLpro mutation from proline to histidine at amino acid position 132 was especially identified in the omicron variant, with prevalence of 99.69%. Enzyme kinetic assay revealed that these 3CLpro mutants have enzymatic activity comparable to that of the wild type (WT). Next, we assessed the inhibitory effect of ensitrelvir against mutated 3CLpro, with it showing inhibitory effects similar to that against the WT. These in vitro data suggest that ensitrelvir will be effective against currently circulating SARS-CoV-2 variants, including omicron variants and those carrying 3CLpro mutations, which emerging novel SARS-CoV-2 variants could carry. • Ensitrelvir showed comparable antiviral activity against various SARS-CoV-2 variants. • Genetic surveillance of SARS-CoV-2 3CLpro revealed 11 major 3CLpro mutations. • The IC 50 s of ensitrelvir against these mutants were similar to those of the wild type. [ABSTRACT FROM AUTHOR]

The Novel Coronavirus 2019 (COVID-19) is a global pandemic which has a devastating impact. Due to its quick transmission, a prominent challenge in confronting this pandemic is the rapid diagnosis. Currently, the commonly-used diagnosis is the specific molecular tests aided with the medical imaging modalities such as chest X-ray (CXR). However, with the large demand, the diagnoses of CXR are time-consuming and laborious. Deep learning is promising for automatically diagnosing COVID-19 to ease the burden on medical systems. At present, the most applied neural networks are large, which hardly satisfy the rapid yet inexpensive requirements of COVID-19 detection. To reduce huge computation and memory demands, in this paper, we focus on implementing lightweight networks for COVID-19 detection in CXR. Concretely, we first augment data based on clinical visual features of CXR from expertise. Then, according to the fact that all the input data are CXR, we design a targeted four-layer network with either 11 × 11 or 3 × 3 kernels to recognize regional features and detail features. A pruning criterion based on the weights importance is also proposed to further prune the network. Experiments on a public COVID-19 dataset validate the effectiveness and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

• An average case fatality ratio over the first six months after the outbreak of COVID-19 in Poland was 5.43% (95% CI: 5.08% – 5.73%), while among hospitalized cases 16.9% (15.8% – 17.9%). • The case fatality rate had a decreasing trend in time starting from 7.83% (7.08% – 8.61%) during first eight weeks after the outbreak (March – April), to reach 2.52% (2.06% – 3.02%) during the summer season (July – August). • Recent medical care as well as the identification of the source contact, independently of the age, sex and comorbidities, significantly impact an individual mortality risk. After more than one and a half year since the COVID-19 pandemics outbreak the scientific world is constantly trying to understand its dynamics. In this paper of the case fatality rates (CFR) for COVID-19 we study the historic data regarding mortality in Poland during the first six months of pandemic, when no SARS-CoV-2 variants of concern were present among infected. To this end, we apply competing risk models to perform both uni- and multivariate analyses on specific subpopulations selected by different factors including the key indicators: age, sex, hospitalization. The study explores the case fatality rate to find out its decreasing trend in time. Furthermore, we describe the differences in mortality among hospitalized and other cases indicating a sudden increase of mortality among hospitalized cases at the end of the 2020 spring season. Exploratory and multivariate analysis revealed the real impact of each variable and besides the expected factors indicating increased mortality (age, comorbidities) we track more non-obvious indicators. Recent medical care as well as the identification of the source contact, independently of the comorbidities, significantly impact an individual mortality risk. As a result, the study provides a twofold insight into the COVID-19 mortality in Poland. On one hand we explore mortality in different groups with respect to different variables, on the other we indicate novel factors that may be crucial in reducing mortality. The later can be coped, e.g. by more efficient contact tracing and proper organization and management of the health care system to accompany those who need medical care independently of comorbidities or COVID-19 infection. [ABSTRACT FROM AUTHOR]

Rapid detection of nucleic acids is essential for clinical diagnosis of a wide range of infectious and non-infectious diseases. CRISPR-based diagnostic platforms are well-established for rapid and specific detection of nucleic acids but suffer from a low detection sensitivity without a target pre-amplification step. Our recently developed detection system, called CRISPR-ENHANCE, employs engineered crRNAs and optimized conditions to achieve a significantly higher sensitivity and enable femtomolar levels of nucleic acid detection even without target pre-amplification. Using the CRISPR-ENHANCE platform and following the methodology detailed in this paper, nucleic acid detection for low copy numbers can be achieved in less than an hour through either a fluorescence-based detection or a lateral flow assay. The step-by-step instructions provided, in addition to describing how to perform both assays, incorporate details on a LAMP/RT-LAMP-based target amplification step to enable detection of RNA, ssDNA and dsDNA. Furthermore, a protocol for in-house expression and purification of LbCas12a using CL7/lm7-based affinity chromatography, which has been used to achieve a high yield and purity of the enzyme in a single-step, is provided. [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]

• Network-based approach improve SARS-CoV-2 drug repositioning performance • Aggregating local network information can promote non-linear feature interaction • Graph convolutional network utilize drug-disease-target reduce the data sparsity • Doxycycline, Cefuroxime, and Erythromycin can be used for SARS-CoV-2 treatment The coronavirus disease 2019 (COVID-19) has outbreak since early December 2019, and COVID-19 has caused over 100 million cases and 2 million deaths around the world. After one year of the COVID-19 outbreak, there is no certain and approve medicine against it. Drug repositioning has become one line of scientific research that is being pursued to develop an effective drug. However, due to the lack of COVID-19 data, there is still no specific drug repositioning targeting the COVID-19. In this paper, we propose a framework for COVID-19 drug repositioning. This framework has several advantages that can be exploited: one is that a local graph aggregating representation is used across a heterogeneous network to address the data sparsity problem; another is the multi-hop neighbors of the heterogeneous graph are aggregated to recall as many COVID-19 potential drugs as possible. Our experimental results show that our COVDR framework performs significantly better than baseline methods, and the docking simulation verifies that our three potential drugs have the ability to against COVID-19 disease. [ABSTRACT FROM AUTHOR]

In the pre-clinical phase, SARS-CoV-2 vaccines were tested in animal models, including exposure trials, to investigate protection against SARS-CoV-2. These studies paved the way for clinical development. The objective of our review was to provide an overview of published animal exposure results, focussing on the capacity of vaccines to reduce/prevent viral shedding. Using Medline, we retrieved eighteen papers on eight different vaccine platforms in four animal models. Data were extracted on presence/absence of viral RNA in nose, throat, or lungs, and neutralizing antibody levels in the blood. All vaccines showed a tendency of reduced viral load after exposure. Particularly nasal swab results are likely to give an indication about the impact on virus excretion in the environment. Similarly, the reduction or prevention of viral replication in the bronchoalveolar environment might be related with disease prevention, explaining the high efficacy in clinical trials. Although it remains difficult to compare the results directly, the potential for a strong reduction of transmission was shown, indicating that the animal models predicted what is observed in the field after large scale human vaccination. This merits further attention for standardization of exposure experiments, with the intention to speed up future vaccine development. • All SARS-CoV-2 vaccine candidates reduce viral load in different organs in animal models. • Viral load in nasal swab results provide an indication about the impact of vaccines on virus excretion. • Reduced viral replication in the bronchoalveolar environment might be related with disease prevention. • Standardization of exposure experiments may help to speed up future vaccine development. [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]

After the new Coronavirus disease (COVID-19) emerged in the end of January 2020 in Germany, a large number of individuals suffered from severe symptoms and eventually needed intensive care in hospitals. Due to the rapid spread of the disease, the number of deceased individuals increased as well, which is a motivation to prevent as many new infections as possible. Therefore, the knowledge about the current evolution of the virus spread is crucial to predict its future behavior and to react with suitable interventions. In this paper, the evolution of the COVID-19 pandemic in Germany is forecasted by a network-based inference method, in which the interactions of individuals are taken into account using a contact matrix. Then the results are compared to the predictions without considering a contact matrix as well as to the logistic regression, which shows the advantage of incorporating the contact matrix. Furthermore, the basic reproduction number of the pandemic in Germany using a neural network approach is estimated and used for further predictions of the evolution of COVID-19 in Germany. In order to mathematically model the different compartments of the population in the considered regions, the classical SIR model is employed. In this work, we deploy the LASSO (Least Absolute Shrinkage and Selection Operator) for the unknown parameter estimation. Furthermore, we calculate and illustrate the MAPE (Mean Absolute Percentage Error) of the estimations to show the accuracy of the predictions. The results include model parameter estimation and model validation, as well as the outbreak forecasting using network-informed algorithms. Our findings show that the network-inference based approach outperforms the logistic regression as well as the neural network approach and the SIR model calibration without a contact network. Furthermore according to the results, the network-inference based approach is particularly suitable for short- to mid-term predictions, even when there is not much information about the new disease. Moreover, the predictions based on the estimation of the reproduction number in Germany can yield more reliable results with increasing the availability of data, but could not outperform the network-inference based algorithm. • The evolution of the COVID-19 pandemic in Germany and Bavaria state is forecasted. • The approach takes into account the interactions of individuals via a contact matrix. • The Mean Absolute Percentage Error (MAPE) of the estimation is calculated. • The prediction results are compared with the true data, NNs and logistic regression. • The predictions outperform the results of estimations without contact matrix. • The network-based approach is suitable for short- to mid-term predictions. • The predictions are informative for decision-makers to set protective measures. [ABSTRACT FROM AUTHOR]

Understanding the relationship between social factors and persistent COVID-19 health outcomes, such as onset of a disability after a SARS-CoV-2 (the virus that causes COVID-19) infection, is an increasingly important public health issue. The purpose of this paper is to examine associations between social vulnerability and new onset of a mobility disability post-COVID-19 diagnosis. We used data from the Michigan COVID-19 Recovery Surveillance Study, a population-based probability survey of adults with PCR-confirmed SARS-CoV-2 infection in Michigan between January 2020–May 2022 (n = 4295). We used the Minority Health Social Vulnerability Index (MHSVI), with high county-level social vulnerability defined at or above the 75th percentile. Mobility disability was defined as new difficulty walking or climbing stairs. We regressed mobility disability on the overall MHSVI, as well as sub-themes of the index (socioeconomic status, household composition/disability, minority and language, housing type, healthcare access, and medical vulnerability), using multivariable logistic regression, adjusting for age, race, sex, education, employment, and income. Living in a county with high (vs. low) social vulnerability was associated with 1.38 times higher odds (95% confidence interval [CI]:1.18–1.61) of reporting a new mobility disability after a COVID-19 diagnosis after adjustment. Similar results were observed for the socioeconomic status and household composition/disability sub-themes. In contrast, residents of highly racially diverse counties had lower odds (odds ratio 0.74, 95% CI: 0.61, 0.89) of reporting a new mobility disability compared to low diversity counties. Mitigating the effects of social vulnerabilities requires additional resources and attention to support affected individuals. • After a COVID-19 infection: Social vulnerability is associated with higher odds of new mobility disability. • Socially vulnerable housing conditions contribute to the association. • High area concentration of racial minorities had lower odds of mobility disability. [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]

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]

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]

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 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]

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]

We develop a lattice-based, hybrid discrete-continuum modeling framework for SARS-CoV-2 exposure and infection in the human lung alveolar region, or parenchyma, the massive surface area for gas exchange. COVID-19 pneumonia is alveolar infection by the SARS-CoV-2 virus significant enough to compromise gas exchange. The modeling framework orchestrates the onset and progression of alveolar infection, spatially and temporally, beginning with a pre-immunity baseline, upon which we superimpose multiple mechanisms of immune protection conveyed by interferons and antibodies. The modeling framework is tunable to individual profiles, focusing here on degrees of innate immunity, and to the evolving infection–replication properties of SARS-CoV-2 variant strains. The model employs partial differential equations for virion, interferon, and antibody concentrations governed by diffusion in the thin fluid coating of alveolar cells, species and lattice interactions corresponding to sources and sinks for each species, and multiple immune protections signaled by interferons. The spatial domain is a two-dimensional, rectangular lattice of alveolar type I (non-infectable) and type II (infectable) cells with a stochastic, species-concentration-governed, switching dynamics of type II lattice sites from healthy to infected. Once infected, type II cells evolve through three phases: an eclipse phase during which RNA copies (virions) are assembled; a shedding phase during which virions and interferons are released; and then cell death. Model simulations yield the dynamic spread of, and immune protection against, alveolar infection and viral load from initial sites of exposure. We focus in this paper on model illustrations of the diversity of outcomes possible from alveolar infection, first absent of immune protection, and then with varying degrees of four known mechanisms of interferon-induced innate immune protection. We defer model illustrations of antibody protection to future studies. Results presented reinforce previous recognition that interferons produced solely by infected cells are insufficient to maintain a high efficacy level of immune protection, compelling additional mechanisms to clear alveolar infection, such as interferon production by immune cells and adaptive immunity (e.g., T cells). This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics". • Stochastic hybrid discrete continuum platform for SARS-CoV-2 alveolar infection. • Infection outcomes of pre-immune and innate immune protection. • Incorporation of autocrine and paracrine interferon immune effects. • Interferon driven virion and infected cell elimination by immune cells. • Adaptable modeling framework to other alveolar virus infections. [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]

[Display omitted] • We modify a model of zoonosis emergence to predict coronavirus intermediate hosts. • This technique requires only host species ecological and epidemiological information. • We accurately predict the intermediate hosts for SARS and MERS. • We find mink, pangolins, and ferrets as potential intermediate hosts for SARS-CoV-2. Intermediate host species provide a crucial link in the emergence of zoonotic infectious diseases, serving as a population where an emerging pathogen can mutate to become human-transmissible. Identifying such species is thus a key component of predicting and possibly mitigating future epidemics. Despite this importance, intermediate host species have not been investigated in much detail, and have generally only been identified by testing for the presence of pathogens in multiple candidate species. In this paper, we present a mathematical model able to identify likely intermediate host species for emerging zoonoses based on ecological data for the candidates and epidemiological data for the pathogen. Since coronaviruses frequently emerge through intermediate host species and, at the time of writing, pose an urgent pandemic threat, we apply the model to the three emerging coronaviruses of the twenty-first century, accurately predicting palm civets as intermediate hosts for SARS-CoV-1 and dromedary camels as intermediate hosts for MERS. Further, we suggest mink, pangolins, and ferrets as intermediate host species for SARS-CoV-2. With the capacity to evaluate intermediate host likelihood among different species, researchers can focus testing for possible infection sources and interventions more effectively. [ABSTRACT FROM AUTHOR]

The Russian government took strong containment measures to prevent the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with rigid hygiene protocols and restrictions on daily living, such as social distancing and closing businesses and schools. While these measures were crucial to stop the diffusion of SARS-CoV-2, numerous voices highlighted their disorderly psychological, social, and economic impacts on food consumption behavior and lifestyle. Therefore, this paper aims to understand how consumers' food-related habits in Russia have shifted due to the COVID-19 pandemic and potential problems and opportunities this might bring for the Russian food system. The study is based on an online cross-sectional survey using a structured questionnaire administered in Russian through the Survey Monkey platform. A total of 1297 valid answers was collected. The results reveal that diet and food shopping, preparation, and use have been widely affected. Indeed, the survey results suggested (i) a change in the modality of acquiring food, consumers reduced the number of shopping trips and buying more on each trip to minimize store visits; (ii) a surge of stockpiling of non-perishable food items; (iii) a shift toward healthier diets; (iv) an increase in culinary capabilities; (v) a decrease of food waste. The results are expected to inform current emergency plans as well as long-term food-related strategies in Russia. [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]

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]