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Objective The aims of the study were: (1) to clarify the definitions of “migrant” used in occupational health research; (2) to summarize migrant workers’ industry sectors, occupations and employment conditions; (3) to identify the occupational health and safety services available to migrant workers; (4) to summarize work-related health problems found among migrant workers; (5) to identify the methodological challenges to research into occupational health of migrant workers; and (6) to recommend improvements in migrant occupational health research. Methods This position paper was prepared by researchers from several European countries and Australia, working within the EU COST Action OMEGA-NET. The paper drew on two recent systematic reviews on the occupational health of international migrant workers and other literature, and also identified uncertainties and gaps in the research literature. Migrants may, for example, be temporary or permanent, moving for specific jobs migrants or other reasons. Their ethnicity and language capabilities will affect their work opportunities. Results The occupational health literature seldom adequately identifies the heterogeneity or characteristics of the migrant group being studied. Migrants tend to work in more physically and mentally demanding environments with higher exposures than native workers. Migrants tend to have an increased risk of physical and mental ill health, but less access to health care services. This has been demonstrated recently by high rates of COVID-19 and less access to health care. There have been a number of cross-sectional studies of migrant health but few long-term cohort studies were identified. Other study designs, such as registry-based studies, surveys and qualitative studies may complement cross-sectional studies. Mixed-methodology studies would be valuable in research on migrants’ occupational health. Language and lack of trust are barriers to migrant research participation. Conclusion Targeted research, especially longitudinal, identifying how these economically important but often-vulnerable workers can be best assisted is needed. Researchers should identify the characteristics of the migrant workers that they are studying including visa/migration circumstances (temporary, permanent, undocumented), racial and ethnic characteristics, existing skills and language abilities.

Coronavirus disease 2019 (COVID-19) pandemic is currently a serious global health threat. While conventional laboratory tests such as quantitative real-time polymerase chain reaction (qPCR), serology tests, and chest computerized tomography (CT) scan allow diagnosis of COVID-19, these tests are time-consuming and laborious, and are limited in resource-limited settings or developing countries. Point-of-care (POC) biosensors such as chip-based and paper-based biosensors are typically rapid, portable, cost-effective, and user-friendly, which can be used for COVID-19 in remote settings. The escalating demand for rapid diagnosis of COVID-19 presents a strong need for a timely and comprehensive review on the POC biosensors for COVID-19 that meet ASSURED criteria: Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable to end users. In the present review, we discuss the importance of rapid and early diagnosis of COVID-19 and pathogenesis of COVID-19 along with the key diagnostic biomarkers. We critically review the most recent advances in POC biosensors which show great promise for the detection of COVID-19 based on three main categories: chip-based biosensors, paper-based biosensors, and other biosensors. We subsequently discuss the key benefits of these biosensors and their use for the detection of antigen, antibody, and viral nucleic acids. The commercial POC biosensors for COVID-19 are critically compared. Finally, we discuss the key challenges and future perspectives of developing emerging POC biosensors for COVID-19. This review would be very useful for guiding strategies for developing and commercializing rapid POC tests to manage the spread of infections.Graphical abstract.

In this paper, we examine the variation in the outbreak of COVID-19 across departments in continental France. We use information on the cumulated number of deaths, discharged patients and infections from COVID-19 at the department level, and study how these relate to income inequality, controlling for other factors. We find that unfortunately, inequality kills: departments with higher income inequality face more deaths, more discharged (gravely ill) patients and more infections. While other papers have studied the impact of the level of income on the severity of COVID-19, we find that it is in fact the dispersion across incomes within the same department that drives the results. Our results suggest that individuals in relatively more precarious conditions deserve dedicated policies, to avoid that temporary shocks such as COVID-19 lead to permanent increases in inequality.

The choices that researchers make while conducting a statistical analysis usually have a notable impact on the results. This fact has become evident in the ongoing research of the association between the environment and the evolution of the coronavirus disease 2019 (COVID-19) pandemic, in light of the hundreds of contradictory studies that have already been published on this issue in just a few months. In this paper, a COVID-19 dataset containing the number of daily cases registered in the regions of Catalonia (Spain) since the start of the pandemic to the end of August 2020 is analysed using statistical models of diverse levels of complexity. Specifically, the possible effect of several environmental variables (solar exposure, mean temperature, and wind speed) on the number of cases is assessed. Thus, the first objective of the paper is to show how the choice of a certain type of statistical model to conduct the analysis can have a severe impact on the associations that are inferred between the covariates and the response variable. Secondly, it is shown how the use of spatio-temporal models accounting for the nature of the data allows understanding the evolution of the pandemic in space and time. The results suggest that even though the models fitted to the data correctly capture the evolution of COVID-19 in space and time, determining whether there is an association between the spread of the pandemic and certain environmental conditions is complex, as it is severely affected by the choice of the model.

Non-pharmaceutical interventions aimed at reducing the spread of COVID-19 rely largely on voluntary compliance among the target population to be effective, since such measures, which are aimed at the entire population, are very hard to enforce. In this paper, we focus on the impact of different work ethics on the spread of COVID-19. There are indeed reasons to believe that populations with different attitudes toward work will react differently to stay-at-home orders and other policies that forbid people from working. By means of a quantitative analysis, using hybrid model estimators, we test the impact of different work ethics on COVID-19 diffusion in a sample of 30 European countries. Results show that the more a population holds certain beliefs about work-namely, that it is humiliating to receive money without working, that people who do not work become lazy, and that work always comes first-the higher contagion rates of COVID-19 are, ceteris paribus. On the other hand, the more a population perceives work as a social duty, the lower contagion rates are. All this suggests that different work ethics matter in the containment of COVID-19.

Within the elderly population, psychogeriatric patients may be particularly susceptible to negative mental health effects of the coronavirus crisis. Detailed information about the psychosocial well-being of psychogeriatric patients during the pandemic is still sparse. Here we examined which aspects of subjective experience of the COVID-19 pandemic especially affect levels of depression, anxiety and quality of life in psychogeriatric patients with and without cognitive impairment. A cross-sectional paper survey was conducted during the first German lockdown among patients with a diagnosed psychiatric disorder (≥ 60 years) or a diagnosed neurodegenerative disease (regardless of their age) from the department for neurodegenerative diseases and geriatric psychiatry at the University of Bonn. The WHO-5-, GAD-7- and WHOQOL-old score were used to determine levels of depression, anxiety and quality of life. The second part obtained information about the subjective experience of the COVID-19 pandemic. Statistical analysis included among others principal component analysis and multiple linear regression analysis. COVID-19-related, immediate distress was a strong predictor of elevated symptoms of depression, anxiety and a reduced quality of life. COVID-19-related concerns regarding health and financial security, however, were not significantly associated with negative mental health outcomes. The overall prevalence of symptoms of depression (50.8% [95% CI 43.8–57.6%]) and anxiety (32.7% [95% CI 26.4–39.2%]) among psychogeriatric patients was high. Our findings indicate that psychogeriatric patients are not significantly affected by COVID-19-related concerns but are primarily suffering from emotional consequences resulting from changed living conditions due to the pandemic. Supplementary Information The online version contains supplementary material available at 10.1007/s00406-021-01340-1.

The COVID-19 has been a worldwide pandemic and it needs for studies related to effect on people's demand for insurance during the pandemic which is an important way to transfer risk. However, there is a lack of research linking COVID-19 and people's demand for insurance. The objective of this paper is to investigate the impact of COVID-19 pandemic on issuance demand, using data covering 241 cities on confirmed COVID-19 cases and insurance company revenue in China. The empirical results show that more confirmed COVID-19 cases are associated with greater per capita insurance revenue and the results are robust when considering endogeneity concern. Economically, the per capita insurance revenue increases by 0.896 Yuan for each more confirmed case. In terms of insurance type, the greatest increased insurance revenue is for life insurance, followed by health insurance. We further consider the heterogeneity of regions and find that the impact of COVID-19 on insurance revenue only exists in regions with worse medical treatment conditions or higher medical burden.

This paper examines the robustness of the optimal lockdown strategy to the postulated social welfare criterion. We show that utilitarianism can, under some conditions, imply a COVID-19 variant of Parfit's (1984) Repugnant Conclusion: for any (interior) lockdown with life periods of low quality, there must be a stricter lockdown that is regarded as better, even though this reduces the quality of life periods even more. On the contrary, the ex post egalitarian criterion (giving priority to the worst-off ex post) implies zero lockdown. Varying between its minimal and its maximal levels, the optimal lockdown is not robust to the postulated ethical criterion. We also identify a general ethical dilemma between the goal of saving lives (modeled by the Survivors Number Count axiom) and the goal of giving priority to the worst-off (Hammond Equity).

Graphical abstract Recently, numerous diagnostic approaches from different disciplines have been developed for SARS-CoV-2 diagnosis to monitor and control the COVID-19 pandemic. These include MS-based assays, which provide analytical information on viral proteins. However, their sensitivity is limited, estimated to be 5 × 104 PFU/ml in clinical samples. Here, we present a reliable, specific, and rapid method for the identification of SARS-CoV-2 from nasopharyngeal (NP) specimens, which combines virus capture followed by LC–MS/MS(MRM) analysis of unique peptide markers. The capture of SARS-CoV-2 from the challenging matrix, prior to its tryptic digestion, was accomplished by magnetic beads coated with polyclonal IgG-α-SARS-CoV-2 antibodies, enabling sample concentration while significantly reducing background noise interrupting with LC–MS analysis. A sensitive and specific LC–MS/MS(MRM) analysis method was developed for the identification of selected tryptic peptide markers. The combined assay, which resulted in S/N ratio enhancement, achieved an improved sensitivity of more than 10-fold compared with previously described MS methods. The assay was validated in 29 naive NP specimens, 19 samples were spiked with SARS-CoV-2 and 10 were used as negative controls. Finally, the assay was successfully applied to clinical NP samples (n = 26) pre-determined as either positive or negative by RT-qPCR. This work describes for the first time a combined approach for immuno-magnetic viral isolation coupled with MS analysis. This method is highly reliable, specific, and sensitive; thus, it may potentially serve as a complementary assay to RT-qPCR, the gold standard test. This methodology can be applied to other viruses as well. Supplementary Information The online version contains supplementary material available at 10.1007/s00216-021-03831-5.

The pandemic caused by the COVID-19 virus affects the world widely and heavily. When examining the CT, X-ray, and ultrasound images, radiologists must first determine whether there are signs of COVID-19 in the images. That is, COVID-19/Healthy detection is made. The second determination is the separation of pneumonia caused by the COVID-19 virus and pneumonia caused by a bacteria or virus other than COVID-19. This distinction is key in determining the treatment and isolation procedure to be applied to the patient. In this study, which aims to diagnose COVID-19 early using X-ray images, automatic two-class classification was carried out in four different titles: COVID-19/Healthy, COVID-19 Pneumonia/Bacterial Pneumonia, COVID-19 Pneumonia/Viral Pneumonia, and COVID-19 Pneumonia/Other Pneumonia. For this study, 3405 COVID-19, 2780 Bacterial Pneumonia, 1493 Viral Pneumonia, and 1989 Healthy images obtained by combining eight different data sets with open access were used. In the study, besides using the original X-ray images alone, classification results were obtained by accessing the images obtained using Local Binary Pattern (LBP) and Local Entropy (LE). The classification procedures were repeated for the images that were combined with the original images, LBP, and LE images in various combinations. 2-D CNN (Two-Dimensional Convolutional Neural Networks) and 3-D CNN (Three-Dimensional Convolutional Neural Networks) architectures were used as classifiers within the scope of the study. Mobilenetv2, Resnet101, and Googlenet architectures were used in the study as a 2-D CNN. A 24-layer 3-D CNN architecture has also been designed and used. Our study is the first to analyze the effect of diversification of input data type on classification results of 2-D/3-D CNN architectures. The results obtained within the scope of the study indicate that diversifying X-ray images with tissue analysis methods in the diagnosis of COVID-19 and including CNN input provides significant improvements in the results. Also, it is understood that the 3-D CNN architecture can be an important alternative to achieve a high classification result.

COVID-19 disease is an outbreak that seriously affected the whole world, occurred in December 2019, and thus was declared a global epidemic by WHO (World Health Organization). To reduce the impact of the epidemic on humans, it is important to detect the symptoms of the disease in a timely and accurate manner. Recently, several new variants of COVID-19 have been identified in the United Kingdom (UK), South Africa, Brazil and India, and preliminary findings have been suggested that these mutations increase the transmissibility of the virus. Therefore, the aim of this study is to construct a support system based on fuzzy logic for experts to help detect of COVID-19 infection risk in a timely and accurate manner and to get a numerical output on symptoms of the virus from every person. The decision support system consists of three different sub and one main Mamdani type fuzzy inference systems (FIS). Subsystems are Common- Serious symptoms (First), Rare Symptoms (Second) and Personal Information (Third). The first FIS has five inputs, fever-time, cough-time, fatigue-time, shortness of breath and chest pain/dysfunction; the second FIS has four inputs, Loss of Taste/Smell, Body Aches, Conjuctivitis, and Nausea/Vomiting/Diarrhea; and the third FIS has three inputs, Age, Smoke, and Comorbidities. Then, we obtain personal risk index of individual by combining the outputs of these subsystems in a final FIS. The results can be used by health professionals and epidemiologists to make inferences about public health. Numerical output can also be useful for self-control of an individual. No sponsor

Background Proteinuria (both tubular and glomerular in origin) and its implications are well-known features of adult patients with COVID19. However currently studies addressing proteinuria and its role in the outcome of kidney and patients of pediatric COVID 19 is scarce. We aimed to evaluate the presence of microalbuminuria in order to detect early renal involvement in pediatric COVID 19 patients. Methods We prospectively evaluated 100 pediatric patients hospitalized with COVID 19 between April and July 2020. Clinical presentations, laboratory findings and outcomes were investigated. Microalbuminuria was compared with the age, gender, disease severity, and hemoglobin, platelet, leukocyte count and serum CRP levels of the patients. Results Twenty seven out of 100 patients had microalbuminuria. Fourteen patients had mild and fourteen had moderate disease. There was not any significant relation according to age and gender. Microalbuminuria was not related to the severity of the disease. Also the mean microalbuminuria level did not differ according to the disease course. Hemoglobin, platelet, leukocyte counts and serum CRP levels were also were not correlated with microalbuminuria levels. Conclusion Although there was no difference between the groups with different disease course; microalbuminuria is detected in an important ratio of pediatric patients with COVID 19 in this study. In the highlight of our findings we suggest that urinary findings of pediatric COVID patients should be carefully evaluated.

One of the lethal illnesses that humanity has ever seen is COVID-19 irrefutably. The speed of virus spread is high and happens through polluted surfaces, respiratory droplets, and bodily fluids. It was found that without an efficient vaccine or specific treatment using personal protective equipment, preventing contamination of hands, and social distancing are the best ways to stay safe during the present pandemic. In this line, polymers, nanotechnology, and additive manufacturing, or 3D printing technology have been considered to probe, sense, and treat COVID-19. All aforementioned fields showed undeniable roles during the COVID-19 pandemic, which their contributions have been reviewed here. Finally, the effect of COVID-19 on the environment, alongside its positive and negative effects has been mentioned.

In the era of autonomous robots, multi-targets search methods inspired researchers to develop adapted algorithms to robot constraints, and with the rising of Swarm Intelligence (SI) approaches, Swarm Robotics (SRs) became a very popular topic. In this paper, the problem of searching for an exponentially increasing number of targets in a complex and unknown environment is addressed. Our main objective is to propose a Robotic target search strategy based on the EHO (Elephants Herding Optimization) algorithm, namely Robotic-EHO (REHO). The main additions were the collision-free path planning strategy, the velocity limitation, and the extension to the multi-target version in discrete environments. The proposed method has been the subject of many experiments, emulating the search of infected individuals by COVID-19 in a context of containment within complex and unknown random environments, as well as in the real case study of USA. The particularity of these environments is their increasing targets' number and the dynamic Containment Rate (CR) that we propose. The experimental results show that REHO reacts much better in high Containment Rate, early start search mission, and where the robots' speed is higher than the virus spread speed.

In this paper, linear regression (LR), multi-linear regression (MLR) and polynomial regression (PR) techniques are applied to propose a model Li-MuLi-Poly. The model predicts COVID-19 deaths happening in the United States of America. The experiment was carried out on machine learning model, minimum mean square error model, and maximum likelihood ratio model. The best-fitting model was selected according to the measures of mean square error, adjusted mean square error, mean square error, root mean square error (RMSE) and maximum likelihood ratio, and the statistical t-test was used to verify the results. Data sets are analyzed, cleaned up and debated before being applied to the proposed regression model. The correlation of the selected independent parameters was determined by the heat map and the Carl Pearson correlation matrix. It was found that the accuracy of the LR model best-fits the dataset when all the independent parameters are used in modeling, however, RMSE and mean absolute error (MAE) are high as compared to PR models. The PR models of a high degree are required to best-fit the dataset when not much independent parameter is considered in modeling. However, the PR models of low degree best-fits the dataset when independent parameters from all dimensions are considered in modeling.

Engaging deep neural networks for textual sentiment analysis is an extensively practiced domain of research. Textual sentiment classification harnesses the full computational potential of deep learning models. Typically, these research works are carried either with a popular open-source data corpus, or self-extracted short phrase texts from Twitter, Reddit, or web-scrapped text data from other resources. Rarely do we see a large amount of data on a current ongoing event is being collected and cultured further. Also, an even more complex task would be to model the data from a currently ongoing event, not only for scaling the sentiment accuracy but also for making a predictive analysis for the same. In this paper, we propose a novel approach for achieving sentiment evaluation accuracy by using a deep neural network on live-streamed tweets on Coronavirus and future case growth prediction. We develop a large tweet corpus exclusively based on the Coronavirus tweets. We split the data into train and test sets, alongside we perform polarity classification and trend analysis. The refined outcome from the trend analysis helps to train the data to provide an incremental learning curvature for our neural network, and we obtain an accuracy of 90.67%. Finally, we provide a statistical-based future prediction for Coronavirus cases growth. Not only our model outperforms several previous state-of-art experiments in overall sentiment accuracy comparison for similar tasks, but it also maintains a throughout performance stability among all the test cases when tested with several popular open-source text corpora.

COVID-19 had led to severe clinical manifestations. In the current scenario, 98 794 942 people are infected, and it has responsible for 2 124 193 deaths around the world as reported by World Health Organization on 25 January 2021. Telemedicine has become a critical technology for providing medical care to patients by trying to reduce transmission of the virus among patients, families, and doctors. The economic consequences of coronavirus have affected the entire world and disrupted daily life in many countries. The development of telemedicine applications and eHealth services can significantly help to manage pandemic worldwide better. Consequently, the main objective of this paper is to present a systematic review of the implementation of telemedicine and e-health systems in the combat to COVID-19. The main contribution is to present a comprehensive description of the state of the art considering the domain areas, organizations, funding agencies, researcher units and authors involved. The results show that the United States and China have the most significant number of studies representing 42.11% and 31.58%, respectively. Furthermore, 35 different research units and 9 funding agencies are involved in the application of telemedicine systems to combat COVID-19.

Telehealth drastically reduces the time burden of appointments and increases access to care for homebound patients. During the COVID-19 pandemic, many outpatient practices closed, requiring an expansion of telemedicine capabilities. However, a significant number of patients remain unconnected to telehealth-capable patient portals. Currently, no literature exists on the success of and barriers to remote enrollment in telehealth patient portals. From March 26 to May 8, 2020, a total of 324 patients were discharged from Mount Sinai Beth Israel (MSBI), a teaching hospital in New York City. Study volunteers attempted to contact and enroll patients in the MyChart patient portal to allow the completion of a post-discharge video visit. If patients were unable to enroll, barriers were documented and coded for themes. Of the 324 patients discharged from MSBI during the study period, 277 (85%) were not yet enrolled in MyChart. Volunteers successfully contacted 136 patients (49% of those eligible), and 39 (14%) were successfully enrolled. Inability to contact patients was the most significant barrier. For those successfully contacted but not enrolled, the most frequent barrier was becoming lost to follow-up (29% of those contacted), followed by lack of interest in remote appointments (21%) and patient technological limitations (9%). Male patients, and those aged 40–59, were significantly less likely to successfully enroll compared to other patients. Telehealth is critical for healthcare delivery. Remote enrollment in a telemedicine-capable patient portal is feasible, yet underperforms compared to reported in-person enrollment rates. Health systems can improve telehealth infrastructure by incorporating patient portal enrollment into in-person workflows, educating on the importance of telehealth, and devising workarounds for technological barriers.

Little is known about the relationship of COVID-19 outcomes with onychomycosis. We investigated the relationship of onychomycosis with COVID-19 outcomes. A retrospective cohort study was performed on SARS-CoV-2 positive adult outpatients or inpatients who had onychomycosis and other skin diseases. Overall, 430 adults were identified with SARS-CoV-2 and a skin disease, including 98 with diagnosed onychomycosis. In bivariable logistic regression models, onychomycosis was associated with increased hospitalization {odds ratio(OR) [95% confidence interval (CI)]: 3.56 [2.18-5.80]}, initial inpatient vs. outpatient visits (OR [95% CI]: 2.24 [1.35-3.74]), use of oxygen therapy (OR [95% CI]: 2.77 [1.60-4.79]), severe-critical vs. asymptomatic-mild severity (OR [95% CI]: 2.28 [1.32-3.94]), and death (OR [95% CI]: 7.48 [1.83-30.47]) from COVID-19, but not prolonged hospitalization (OR [95% CI]: 1.03 [0.47-2.25]). In multivariable models adjusting for socio-demographics, comorbidities, and immunosuppressant medication use, the associations with onychomycosis remained significant for hospitalization, inpatient visits, oxygen therapy, severe-critical COVID-19. Onychomycosis was a significant independent risk factor for COVID-19 severity, hospitalization, and receiving supplemental oxygen therapy.

In this research, a dataset including 29 ketone-based covalent inhibitors with SARS-CoV-1 3CLpro inhibition activity was used to develop high predictive QSAR models. Twenty-two molecules were put in train set and seven molecules in test set. By using stepwise MLR method for molecules in train set, four molecular descriptors including Mor26p, Hy, GATS7p and Mor04v were selected to build QSAR models. MLR and ANN methods were used to create QSAR models for predicting the activity of molecules in both train and test sets. Both QSAR models were validated by calculating several statistical parameters. R2 values for the test set of MLR and ANN models were 0.93 and 0.95, respectively, and RMSE values for their test sets were 0.24 and 0.17, respectively. Other calculated statistical parameters (especially \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Q_{F3}^{2}$$\end{document}QF32 parameter) show that created ANN model has more predictive power with respect to developed MLR model (with four descriptor). Calculated leverages for all molecules show that predicted pIC50 (by both QSAR models) for all molecules is acceptable, and drawn residuals plots show that there is no systematic error in building both QSAR modes. Also, based on developed MLR model, used molecular descriptors were interpreted.

During SARS-CoV-2 proliferation, the translation of viral RNAs is usually the rate-limiting step. Understanding the molecular details of this step is beneficial for uncovering the origin and evolution of SARS-CoV-2 and even for controlling the pandemic. To date, it is unclear how SARS-CoV-2 competes with host mRNAs for ribosome binding and efficient translation. We retrieved the coding sequences of all human genes and SARS-CoV-2 genes. We systematically profiled the GC content and folding energy of each CDS. Considering that some fixed or polymorphic mutations exist in SARS-CoV-2 and human genomes, all algorithms and analyses were applied to both pre-mutate and post-mutate versions. In SARS-CoV-2 but not human, the 5-prime end of CDS had lower GC content and less RNA structure than the 3-prime part, which was favorable for ribosome binding and efficient translation initiation. Globally, the fixed and polymorphic mutations in SARS-CoV-2 had created an even lower GC content at the 5-prime end of CDS. In contrast, no similar patterns were observed for the fixed and polymorphic mutations in human genome. Compared with human RNAs, the SARS-CoV-2 RNAs have less RNA structure in the 5-prime end and thus are more favorable of fast translation initiation. The fixed and polymorphic mutations in SARS-CoV-2 are further amplifying this advantage. This might serve as a strategy for SARS-CoV-2 to adapt to the human host.

International student mobility is an important indicator of the internationalization of higher education, and an important way to cultivate talents with global has had a huge impact on the mobility of international students. Specifically, the scale of international student mobility has decreased, changes in the geographic pattern of international student mobility have intensified, the form of international student mobility has changed, and the competition in the international study abroad market has intensified. As a major country that sends and receives international students, China has adopted a series of response measures to reduce the impact of the pandemic on international student mobility and has formulated a long-term development strategy to promote the mobility of international students. To promote international student mobility in the post-epidemic period, countries should provide support for international students from home and abroad, promote the diversification of international student mobility, and strengthen internationalization at home.

In this paper, I use administrative data to estimate the number of deaths, the number of infections, and mortality rates from COVID-19 in Lombardia, the hot spot of the disease in Italy and Europe. The information will assist policy makers in reaching correct decisions and the public in adopting appropriate behaviors. As the available data suffer from sample selection bias, I use partial identification to derive the above quantities. Partial identification combines assumptions with the data to deliver a set of admissible values or bounds. Stronger assumptions yield stronger conclusions but decrease the credibility of the inference. Therefore, I start with assumptions that are always satisfied, then I impose increasingly more restrictive assumptions. Using my preferred bounds, during March 2020 in Lombardia, there were between 10,000 and 18,500 more deaths than in previous years. The narrowest bounds of mortality rates from COVID-19 are between 0.1 and 7.5%, much smaller than the 17.5% discussed in earlier reports. This finding suggests that the case of Lombardia may not be as special as some argue.

This position paper discusses emerging behavioral, social, and economic dynamics related to the COVID-19 pandemic and puts particular emphasis on two emerging issues: First, delayed effects (or second strikes) of pandemics caused by dread risk effects are discussed whereby two factors which might influence the existence of such effects are identified, namely the accessibility of (mis-)information and the effects of policy decisions on adaptive behavior. Second, the issue of individual preparedness to hazardous events is discussed. As events such as the COVID-19 pandemic unfolds complex behavioral patterns which are hard to predict, sophisticated models which account for behavioral, social, and economic dynamics are required to assess the effectivity and efficiency of decision-making., 7 pages. Mind & Society (2020)

Graphical abstract Currently, the enormous generation of contaminated disposed face masks raises many environmental concerns. The present study provides a novel route for efficient crude bio-oil production from disposed masks through co-hydrothermal liquefaction (Co-HTL) with Spirulina platensis grown in wastewater. Ultimate and proximate analysis confirmed that S. platensis contains relatively high nitrogen content (9.13%dw), which decreased by increasing the mask blend ratio. However, carbon and hydrogen contents were higher in masks (83.84 and 13.77%dw, respectively). In addition, masks showed 29.6% higher volatiles than S. platensis, which resulted in 94.2% lower ash content. Thermal decomposition of masks started at a higher temperature (≈330 °C) comparing to S. platensis (≈208 °C). The highest bio-oil yield was recorded by HTL of S. platensis and Co-HTL with 25% (w/w) masks at 300 °C, which showed insignificant differences with each other. GC/MS analysis of the bio-oil produced from HTL of algal biomass showed a high proportion of nitrogen- and oxygen-containing compounds (3.6% and 11.9%, respectively), with relatively low hydrocarbons (17.4%). Mask blend ratio at 25% reduced the nitrogen-containing compounds by 55.6% and enhanced the hydrocarbons by 43.7%. Moreover, blending of masks with S. platensis enhanced the compounds within the diesel range in favor of gasoline and heavy oil. Overall, the present study provides an innovative route for enhanced bio-oil production through mask recycling coupled with wastewater treatment. Supplementary Information The online version contains supplementary material available at 10.1007/s13399-021-01891-2.

Global annual deaths from Trauma are greater than any other single cause in the global working population, and, more than all contagious diseases added together including COVID-19. The number of people injured, either temporarily or permanently, is greater than any other medical condition. This problem affects Low and Middle Income Countries (LMICs) disproportionately. The numbers are so great as to cause “zone out” and present a human rights issue. This is a particular issue as Trauma presently receives less than 1% of global healthcare funding. This article will highlight and discuss many of the issues and raise some uncomfortable arguments showing that improvement is needed, necessary and achievable.

This article aims at analysing the role of international tourism attractiveness as a potential factor for the outbreak and the early spread of the recent COVID-19 disease across the world (also called the first wave) with a special focus on small Island economies. Econometric testing is implemented over a cross-country sample including 205 countries/territories (with 59 small islands) after controlling for several usual suspects. The results state a positive and significant relationship between COVID-19 prevalence and inbound tourism arrivals per capita. Thus in the early stages of the spread (before travel restrictions), international tourism could be seen as one of the main responsible factors for the recent pandemic, validating the “tourism-led vulnerability hypothesis”. Accordingly, considering that such health shocks should be more frequent in the near future, this finding suggests that the tourism specialization model in the context of small islands is too vulnerable to be considered as sustainable in the medium and long-run. Policymakers must opt for economic diversification when possible. Otherwise, building up a strong public-health system alongside a specialized tourism sector is required.

Purpose Rapid antigen-detecting tests (Ag-RDTs) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can transform pandemic control. Thus far, sensitivity (≤ 85%) of lateral-flow assays has limited scale-up. Conceivably, microfluidic immunofluorescence Ag-RDTs could increase sensitivity for SARS-CoV-2 detection. Methods This multi-centre diagnostic accuracy study investigated performance of the microfluidic immunofluorescence LumiraDx™ assay, enrolling symptomatic and asymptomatic participants with suspected SARS-CoV-2 infection. Participants collected a supervised nasal mid-turbinate (NMT) self-swab for Ag-RDT testing, in addition to a professionally collected nasopharyngeal (NP) swab for routine testing with reverse transcriptase polymerase chain reaction (RT-PCR). Results were compared to calculate sensitivity and specificity. Sub-analyses investigated the results by viral load, symptom presence and duration. An analytical study assessed exclusivity and limit-of-detection (LOD). In addition, we evaluated ease-of-use. Results The study was conducted between November 2nd 2020 and 4th of December 2020. 761 participants were enrolled, with 486 participants reporting symptoms on testing day. 120 out of 146 RT-PCR positive cases were detected positive by LumiraDx™, resulting in a sensitivity of 82.2% (95% CI 75.2–87.5%). Specificity was 99.3% (CI 98.3–99.7%). Sensitivity was increased in individuals with viral load ≥ 7 log10 SARS-CoV2 RNA copies/ml (93.8%; CI 86.2–97.3%). Testing against common respiratory commensals and pathogens showed no cross-reactivity and LOD was estimated to be 2–56 PFU/mL. The ease-of-use-assessment was favourable for lower throughput settings. Conclusion The LumiraDx™ assay showed excellent analytical sensitivity, exclusivity and clinical specificity with good clinical sensitivity using supervised NMT self-sampling. Trial registration number and registration date DRKS00021220 and 01.04.2020

Background The novel coronavirus pandemic (COVID-19) has catalyzed the development of online educational resources. Webinars provide opportunities for convenient distance-learning and provision of expert lectures, while reducing the financial and practical costs of attending conferences. This cross-sectional survey aims to collect subjective opinion on the usefulness of webinars as an educational platform compared to face-to-face interactions, and whether surgeons and surgeons-in-training want webinars to remain a permanent platform for training and development in the future. Methods A free-to-attend online series of international expert lectures on a range of plastic surgery topics was delivered. Attendees were invited to anonymously complete a survey on attitudes towards webinars as an educational platform over a 2-week period. Results A total of 883 complete responses were collected. Overall webinar attendance increased following the pandemic, with 97.4% of respondents reporting they view webinars for at least 1 h per week following implementation of COVID-19 restrictions. 90.4% respondents indicated that they intend to continue utilizing webinars even once COVID-19 restrictions are eased, and 77.8% stated they learn as much from online webinars as in-person lectures. However, irrespective of training grade, a significant proportion of respondents believe webinars should not replace face-to-face meetings. Conclusions This study provides evidence that, while face-to-face meetings remain a valued component of education in Plastic Surgery, webinars are a useful adjunct to conventional methods, and may feature more prominently in the educational landscape of the future. Level of evidence: Not gradable.

Novel Schiff base ligand was prepared by the condensation of 2,2-(ethylenedioxy)bis(ethylamine) and imidazole-2-carboxaldehyde in a 1:2 ratio, and its complexes with Cr(III), Mn(II), Fe(III), Co(II), Ni(II), Cu(II), and Cd(II) metal ions were synthesized in a 1:1 ratio. Various methods were used to identify the Schiff base ligand and complexes. Characterization techniques such as infrared, UV, and 1H NMR spectral tests, elemental analysis, molar conductivity, magnetic properties, thermal analysis, BET surface area, and theoretically by DFT were used to help further understanding of the complex structures. For all complexes, the ligand behaved as a neutral tetradentate ligand with NOON donor atoms and spectroscopic studies indicated an octahedral structure. The electrolytic behavior of the complexes was revealed by the molar conductivity measurements. In addition, thermogravimetric analysis was used to investigate the decomposition of the complexes and Schiff base ligand. According to the results obtained, the antibacterial activity of the metal complexes is higher than that of the Schiff base ligand against one or more bacterial species. The results showed that Cd(II) complex exhibits enhanced activity against Aspergillus flavus and Ni(II) complex against Candida albicans than the standard drug ketoconazole. The Mn(II) complex had stronger activity against human breast cancer cell line (MCF-7) than the other complexes. Antiviral drug development is critical in the latest outbreak of a novel coronavirus (SARS-CoV-2). The new coronavirus was screened using molecular docking. Supplementary Information The online version contains supplementary material available at 10.1007/s13738-021-02359-w.

A series of novel quinolone-based 4-(methoxymethyl)-1,2,3-triazole derivatives were synthesized, and their structures were characterized by 1H, 13C NMR and mass spectroscopy. The compounds (IXa- l ) were screened in vitro antibacterial activity against five gram-positive and five gram-negative bacterial strains, viz. M. Tuberculosis, M. Luteus, MRSA, B. Subtilis, B. Cereus, P. Aerginosa, K. Pneumonia, E. Coli, P. Vulgaris and S. Typhi, used and compared with standard gentamycin. The combination of the pharmacologically active moieties in a single scaffold results in their synergistic effect and high antimicrobial activity against several bacterial strains. COVID-19 has spread rapidly around the globe since its first identification in Wuhan, China, in December 2019. Coronavirus Disease 2019 (COVID‐19 Mpro) has become a major health problem causing severe acute respiratory illness in humans. The causative virus is called severe acute respiratory syndrome coronavirus 2, and the World Health Organization named the new epidemic disease Coronavirus Disease (COVID-19). Also, docking studies demonstrated that all derivatives exhibit a good theoretical affinity with Autodock 4.2 software score in between − 9.89 and − 13.4 kCal/mol against the main protease of COVID‐19 Mpro that caused worldwide epidemics. We believe that newly synthesized quinolone-based 4-(methoxymethyl)-1,2,3-triazole derivatives can guide many future studies in organic synthesis, medicine and pharmaceutical applications. [ABSTRACT FROM AUTHOR] Copyright of Journal of the Iranian Chemical Society is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The COVID-19 pandemic is an inherently stressful situation, which may lead to adverse psychosocial outcomes in various populations. Yet, individuals may not be affected equally by stressors posed by the pandemic and those with pre-existing mental disorders could be particularly vulnerable. To test this hypothesis, we assessed the psychological response to the pandemic in a case–control design. We used an age-, sex- and employment status-matched case–control sample (n = 216) of psychiatric inpatients, recruited from the LMU Psychiatry Biobank Munich study and non-clinical individuals from the general population. Participants completed validated self-report measures on stress, anxiety, depression, paranoia, rumination, loneliness, well-being, resilience, and a newly developed index of stressors associated with the COVID-19 pandemic. Multiple linear regression analyses were conducted to assess the effects of group, COVID-19-specific stressors, and their interaction on the different psychosocial outcomes. While psychiatric inpatients reported larger mental health difficulties overall, the impact of COVID-19-specific stressors was lower in patients and not associated with worse psychological functioning compared to non-clinical individuals. In contrast, depressive symptoms, rumination, loneliness, and well-being were more strongly associated with COVID-19-specific stressors in non-clinical individuals and similar to the severity of inpatients for those who experienced the greatest COVID-19-specific stressor impact Contrary to expectations, the psychological response to the pandemic may not be worse in psychiatric inpatients compared to non-clinical individuals. Yet, individuals from the general population, who were hit hardest by the pandemic, should be monitored and may be in need of mental health prevention and treatment efforts. Supplementary Information The online version contains supplementary material available at 10.1007/s00406-021-01291-7.

Aims Immunocompromised patients have been excluded from studies of SARS-CoV-2 messenger RNA vaccines. The immune response to vaccines against other infectious agents has been shown to be blunted in such patients. We aimed to analyse the humoral and cellular response to prime-boost vaccination with the BNT162b2 vaccine (Pfizer-BioNTech) in cardiothoracic transplant recipients. Methods and results A total of 50 transplant patients [1–3 years post heart (42), lung (7), or heart–lung (1) transplant, mean age 55 ± 10 years] and a control group of 50 healthy staff members were included. Blood samples were analysed 21 days after the prime and the boosting dose, respectively, to quantify anti-SARS-CoV-2 spike protein (S) immunoglobulin titres (tested by Abbott, Euroimmun and RocheElecsys Immunoassays, each) and the functional inhibitory capacity of neutralizing antibodies (Genscript). To test for a specific T-cell response, heparinized whole blood was stimulated with SARS-CoV-2 specific peptides, covering domains of the viral spike, nucleocapsid and membrane protein, and the interferon-γ release was measured (QuantiFERON Monitor ELISA, Qiagen). The vast majority of transplant patients (90%) showed neither a detectable humoral nor a T-cell response three weeks after the completed two-dose BNT162b2 vaccination; these results are in sharp contrast to the robust immunogenicity seen in the control group: 98% exhibited seroconversion after the prime dose already, with a further significant increase of IgG titres after the booster dose (average > tenfold increase), a more than 90% inhibition capability of neutralizing antibodies as well as evidence of a T-cell responsiveness. Conclusions The findings of poor immune responses to a two-dose BNT162b2 vaccination in cardiothoracic transplant patients have a significant impact for organ transplant recipients specifically and possibly for immunocompromised patients in general. It urges for a review of future vaccine strategies in these patients.

Purpose This executive summary of a national living guideline aims to provide rapid evidence based recommendations on the role of drug interventions in the treatment of hospitalized patients with COVID-19. Methods The guideline makes use of a systematic assessment and decision process using an evidence to decision framework (GRADE) as recommended standard WHO (2021). Recommendations are consented by an interdisciplinary panel. Evidence analysis and interpretation is supported by the CEOsys project providing extensive literature searches and living (meta-) analyses. For this executive summary, selected key recommendations on drug therapy are presented including the quality of the evidence and rationale for the level of recommendation. Results The guideline contains 11 key recommendations for COVID-19 drug therapy, eight of which are based on systematic review and/or meta-analysis, while three recommendations represent consensus expert opinion. Based on current evidence, the panel makes strong recommendations for corticosteroids (WHO scale 5–9) and prophylactic anticoagulation (all hospitalized patients with COVID-19) as standard of care. Intensified anticoagulation may be considered for patients with additional risk factors for venous thromboembolisms (VTE) and a low bleeding risk. The IL-6 antagonist tocilizumab may be added in case of high supplemental oxygen requirement and progressive disease (WHO scale 5–6). Treatment with nMABs may be considered for selected inpatients with an early SARS-CoV-2 infection that are not hospitalized for COVID-19. Convalescent plasma, azithromycin, ivermectin or vitamin D3 should not be used in COVID-19 routine care. Conclusion For COVID-19 drug therapy, there are several options that are sufficiently supported by evidence. The living guidance will be updated as new evidence emerges.

Graphical abstract Ferrocene and its derivatives are vital class of organometallic compounds having extensive biological activities. Six novel ferrocene-based thiosemicarbazones have been synthesized through the condensation reaction of acetyl ferrocene with differently substituted thiosemicarbazide. Furthermore, we used state-of-the-art computational docking approach to explore the theoretical aspects for possible antiviral potential of our synthesized compounds. All the six compounds were docked with Mpro protein of SARS-CoV-2, which is very crucial protein for viral replication. Among the six derivatives, compounds 2 and 4 showed higher binding affinities with binding energy of − 6.7 and − 6.9 kcal/mol, respectively. The visualization of intermolecular interactions between synthesized derivatives and Mpro protein illustrated that each of compounds 2 and 4 forms two hydrogen bonds accompanied by important hydrophobic interactions. The comparison of binding affinities with some recently approved drugs like remdesivir, chloroquine and hydroxychloroquine molecules are also made. The calculated binding energies of remdesivir, chloroquine and hydroxychloroquine molecules with Mpro of COVID-19 was found to be − 7.00, − 5.20 and − 5.60 kcal/mol, respectively. The binding energy of compound 4 (− 6.9 kcal/mol) was almost equal to the remdesivir and greater than the binding energies of chloroquine and hydroxychloroquine. It is expected from the current investigation that our synthesized ferrocene-based thiosemicarbazones might have potential for drug against SARS-CoV-2. Supplementary Information The online version contains supplementary material available at 10.1007/s13738-021-02346-1.

Background During the COVID-19 pandemic, compulsory masks became an integral part of outdoor sports such as jogging in crowded areas (e.g. city parks) as well as indoor sports in gyms and sports centers. This study, therefore, aimed to investigate the effects of medical face masks on performance and cardiorespiratory parameters in athletes. Methods In a randomized, cross-over design, 16 well-trained athletes (age 27 ± 7 years, peak oxygen consumption 56.2 ± 5.6 ml kg−1 min−1, maximum performance 5.1 ± 0.5 Watt kg−1) underwent three stepwise incremental exercise tests to exhaustion without mask (NM), with surgical mask (SM) and FFP2 mask (FFP2). Cardiorespiratory and metabolic responses were monitored by spiroergometry and blood lactate (BLa) testing throughout the tests. Results There was a large effect of masks on performance with a significant reduction of maximum performance with SM (355 ± 41 Watt) and FFP2 (364 ± 43 Watt) compared to NM (377 ± 40 Watt), respectively (p ηp2 = 0.50). A large interaction effect with a reduction of both oxygen consumption (p ηp2 = 0.34) and minute ventilation (p ηp2 = 0.39) was observed. At the termination of the test with SM 11 of 16 subjects reported acute dyspnea from the suction of the wet and deformed mask. No difference in performance was observed at the individual anaerobic threshold (p = 0.90). Conclusion Both SM and to a lesser extent FFP2 were associated with reduced maximum performance, minute ventilation, and oxygen consumption. For strenuous anaerobic exercise, an FFP2 mask may be preferred over an SM.

Purpose Hong Kong has experienced four waves of COVID-19 since the first case was confirmed in January 2020. Several studies have highlighted the psychological impacts of the outbreak in Hong Kong but have largely ignored the protective factors that contribute to resilience among vulnerable families. This study adopted an ecological resilience framework to explore the impact of this epidemic on members of families with youth with a delinquent tendency/mental health concerns and the ecological protective factors for these vulnerable families. Methods Random sampling based on a sampling frame provided by one of the largest local social service organizations in Hong Kong led to the recruitment of 407 respondents who were interviewed using a battery of standardized questionnaires. Results The results showed that 30.6% and 11.5% of respondents reported a moderate and a severe level of psychological distress, respectively, almost double the percentages reported in a previous study conducted in Hong Kong before the COVID-19 outbreak. Around 36.6% of respondents indicated they had encountered financial problems and almost 40% indicated aggravated financial circumstances since the outbreak. Hierarchical regression analysis revealed that financial stress was the strongest predictor of psychological distress. Structural equation modeling indicated that family support, indoor leisure activities and community resources significantly mediated the negative influence of COVID-19-related stressors on psychological distress of family members. Conclusion Family leisure activities, family support, community spirit and mutual help within the context of social-distancing restrictions may need to be promoted to benefit vulnerable families in Hong Kong under the COVID-19 epidemic.

In the absence of effective vaccination, mass testing and quarantining of positive cases and their contacts could help to mitigate pandemics and allow economies to stay open. We investigate the effects of repeated mass testing on the COVID-19 pandemic caused by the SARS-CoV-2 virus, using data from the first ever nationwide rapid antigen testing implemented in Slovakia in autumn 2020. After the first round of testing, only districts above an ex ante unknown threshold of test positivity were re-tested. Comparing districts above and below the threshold, we provide evidence that repeated mass antigen testing can temporarily reduce the number of new infections. Our results suggest that mass testing coupled with the quarantining of positive cases and their contacts could be an effective tool in mitigating pandemics. For lasting effects, re-testing at regular intervals would likely be necessary.

Purpose Limited mechanical ventilators (MV) during the Coronavirus disease (COVID-19) pandemic have led to the use of non-invasive ventilation (NIV) in hypoxemic patients, which has not been studied well. We aimed to assess the association of NIV versus MV with mortality and morbidity during respiratory intervention among hypoxemic patients admitted with COVID-19. Methods We performed a retrospective multi-center cohort study across 5 hospitals during March–April 2020. Outcomes included mortality, severe COVID-19-related symptoms, time to discharge, and final oxygen saturation (SpO2) at the conclusion of the respiratory intervention. Multivariable regression of outcomes was conducted in all hypoxemic participants, 4 subgroups, and propensity-matched analysis. Results Of 2381 participants with laboratory-confirmed SARS-CoV-2, 688 were included in the study who were hypoxemic upon initiation of respiratory intervention. During the study period, 299 participants died (43%), 163 were admitted to the ICU (24%), and 121 experienced severe COVID-19-related symptoms (18%). Participants on MV had increased mortality than those on NIV (128/154 [83%] versus 171/534 [32%], OR = 30, 95% CI 16–60) with a mean survival of 6 versus 15 days, respectively. The MV group experienced more severe COVID-19-related symptoms [55/154 (36%) versus 66/534 (12%), OR = 4.3, 95% CI 2.7–6.8], longer time to discharge (mean 17 versus 7.1 days), and lower final SpO2 (92 versus 94%). Across all subgroups and propensity-matched analysis, MV was associated with a greater OR of death than NIV. Conclusions NIV was associated with lower respiratory intervention mortality and morbidity than MV. However, findings may be liable to unmeasured confounding and further study from randomized controlled trials is needed to definitively determine the role of NIV in hypoxemic patients with COVID-19. Supplementary Information The online version contains supplementary material available at 10.1007/s15010-021-01633-6.

Worldwide spread out of COVID-19 in a short-time has brought a significant decline of road traffic, tourist flow and industrial ventures. During this emergency period, the restricted human dealings with nature have appeared as blessing for health of the total environment. The variation of atmospheric O3 may modulate the range of UV index (UVI) at any region of the earth. The objective of the study is to examine the variation of UV index over the megacities of India with respect to tropospheric O3 level modification during COVID-19 lockdown. The meteorological or environmental data (temperature in °C, gust in km/h, wind speed km/h, relative humidity in %, air pressure in mb and cloud cover in okta) of four selective megacities of India (Kolkata, Chennai, Delhi, Mumbai) during and pre lockdown period have been obtained to comprehend about the variation of UV index and tropospheric O3. The descriptive statistical applications i.e. standard deviation, standard errors and K-means clustering have been done through standard statistical software. In the present study, t-test has been used to understand level of significance of surface O3 and UVI during pre-lockdown (2019) and lockdown (2020) phase. The result shows that the four major megacities in India namely New Delhi, Mumbai, Kolkata and Chennai have experienced the vibrant diminution in terms of the concentration of UV index with slightly increasing the tropospheric O3 level during the lockdown phase. The higher accumulation of O3 during the lockdown in the lower atmosphere of four megacities does not exceed the permissible limit. The excess amount of O3 has remarkably contributed to trap the harmful UV radiation which has lowered the UVI in these worst polluted megacities of India. In the meantime, the prominent reduction of NOx during the lockdown period decreases the titration impact to O3 and this mechanism helps to revitalize the ozone concentration level. The uniqueness of the current study is highlighted the ground reality regarding reduction of UV index and amplification of tropospheric O3 concentration during lockdown phase. This study definitely assists to make new environmental policy, act and law for recover the health of the total environment.

The SARS-CoV-2 pandemic has revived the debate about the routes of virus transmission and their likelihoods. It is of utmost importance to assess the risks of contamination of susceptible people by infectious individuals and to evaluate the level of SARS-CoV-2 and other respiratory viruses transmission in the community. Most countries have imposed non-pharmaceutical measures to contain SARS-CoV-2 transmission, including physical distancing and mask wearing. Here we evaluated the spreading of viruses in open air using harmless Escherichia coli bacteriophages as a surrogate. Phages were sprayed towards Petri dishes seeded with bacteria at different lengths and angles. Our results showed that the transmission rate decreased exponentially with distance. The highest recorded transmission rate was \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$9\times 10^{-6}$$\end{document}9×10-6 PFU/plate when phages were sprayed from a 1 m distance, suggesting that the probability of transmission of a single virus at a 1 m distance is 1:100,000. Supplementary Information The online version contains supplementary material available at 10.1007/s00203-021-02382-8.

The main objective of this survey is to study the published articles to determine the most favorite data mining methods and gap of knowledge. Since the threat of pandemics has raised concerns for public health, data mining techniques were applied by researchers to reveal the hidden knowledge. Web of Science, Scopus, and PubMed databases were selected for systematic searches. Then, all of the retrieved articles were screened in the stepwise process according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist to select appropriate articles. All of the results were analyzed and summarized based on some classifications. Out of 335 citations were retrieved, 50 articles were determined as eligible articles through a scoping review. The review results showed that the most favorite DM belonged to Natural language processing (22%) and the most commonly proposed approach was revealing disease characteristics (22%). Regarding diseases, the most addressed disease was COVID-19. The studies show a predominance of applying supervised learning techniques (90%). Concerning healthcare scopes, we found that infectious disease (36%) to be the most frequent, closely followed by epidemiology discipline. The most common software used in the studies was SPSS (22%) and R (20%). The results revealed that some valuable researches conducted by employing the capabilities of knowledge discovery methods to understand the unknown dimensions of diseases in pandemics. But most researches will need in terms of treatment and disease control.

Purpose To review the potential ancillary cardiovascular and other health impacts of compliance with general adult vaccination series in the prostate cancer active surveillance (AS) population. No previous review has been published in regard to this specific topic. Methods Literature review of PubMed data up to December 2020 Results Compliance rates for adult vaccination are in the approximate anemic range of 25–50% with occasional higher rates of specific vaccines in the elderly population including annual influenza and pneumococcal prevention. Herpes zoster (HZ) and numerous other vaccine preventive illnesses are associated with an increased risk of cardiovascular events. Preliminary evidence suggests vaccine compliance could reduce overall morbidity and mortality, and adherence to heart healthy lifestyle changes and parameters could further improve vaccine efficacy and overall wellness. COVID-19 vaccine utilization and research should also continue to reinforce the direct and ancillary benefits of this entire preventive intervention category. Conclusions Multiple ancillary lifestyle change recommendations could be included in the AS criteria to potentially reduce morbidity and mortality in this population, and perhaps the most unsung intervention is to improve the inadequate rates of general adult vaccination compliance and other heart healthy behavioral changes that impact their efficacy. Heart health, prostate health, and immune system health are closely interlinked.