Worldwide Spread Of COVID-19 Research Articles

2D numerical model of downward push pull ventilation for protecting workers against airborne infection

Industrial clusters contributed significantly to the spread of Covid-19 worldwide, including in Indonesia. One of the causes is that maintaining a minimum distance of 1 to 2 meters between workers is often challenging due to the plant layout and work system design limitations. Therefore, an intervention to the workstation is needed to protect industrial workers from potential exposure to Covid-19 and other airborne infections. One technology that has a high potential to be applied to solve this problem is the air curtain/personalized ventilation. This research analyzes the effectiveness of downward push-pull air curtain in protecting workers from inhaling the infected microdroplet. The extent to which the downward push-pull ventilation can withstand the burst of microdroplets was studied by varying the air speed ratios of the air curtain. A 2D simulation was carried out with Salome, OpenFOAM, and ParaView softwares. Two scenarios were tested, i.e., the distance between the person who is coughing is 0,5 and 1 meter from the air curtain. For the distance of 0,5 meter, the results showed that the optimum velocity ratio between the pushed and pulled air was 0,17 with a droplet penetration percentage of 8,98 %. While for 1 m, the optimum velocity ratio was 0,25 with a droplet penetration percentage of 5,67 %.

The Impact of COVID-19 on China's Real Estate Industry and the Outlook for Industry Trends

Contemporarily, the worldwide spread of COVID-19 has had a negative impact on economic activities globally, and the property sector in China has inevitably been affected. This paper focuses on three main areas of analysis: firstly, the impact of COVID-19 on housing transactions, secondly, the impact of COVID-19 on house prices and thirdly, the impact of the COVID-19 outbreak on property supply. According to the analysis, the outbreak definitely has some negative impact on housing transactions, house prices and supply in the Chinese real estate market in the short term. However, the property market in China is currently relatively stable. For China's super tier 1 cities and new tier 1 cities, the real estate market will recover relatively quickly. With regard to the second-tier cities, owing to their own disadvantage of being relatively backward economically, the real estate market will have some difficulty in recovering through their own efforts, i.e., policy support and assistance are required. Overall, these results shed light on guiding policy implementation for real estate industry in China.

Impact of the place on human health during pandemic and methods to enhance

The spread of COVID-19 worldwide pushed many governments to impose curfews on citizens, that lead a major number of people to stay longer times at certain places in their homes. This is descriptive research, as this paper demonstrates the possibility of impact of the place on its occupant’s health, also it reviews the literature to present a framework to deal with that case in the future, whether there is a need for a new building or for just some modifications in existing ones. The research results showed that there is a certain impact of the place on the human physical and mental health, which results from one or both, the natural earth electromagnetic field and the shape design and proportions. In conclusion there are many methods and theories to deal with the energies of the place that have a negative impact on humans, one of them is to apply a regulatory energy that eliminates the negative impact of the existing energies, whether natural or artificial.

Candida auris and COVID-19: A health threatening combination.

Since its first emergence in December 2019, due to its fast distribution throughout the world, SARS-COV-2 become a global concern. With the extremely increased number of hospitalized patients, this situation provided a potential basis for the transmission of nosocomial infections. Candida auris is a multidrug-resistant pathogen with improved transmission dynamics and resistance traits. During the worldwide spread of COVID-19, cases or outbreaks of C. auris colonization or infection have been reported. Resistance to antifungal drugs has been observed in the causative agents of the majority of such cases. The focus in this review is on COVID-19-associated C. auris infections (case studies/outbreaks) and the pandemic's potential effect on antifungal drug resistance.

Mental and Sexual Health of Men in Times of COVID-19 Lockdown.

Due to the worldwide spread of COVID-19, some restrictions were introduced which could lead to the development of distress and somatic symptoms. This survey aimed to study the mental and sexual health of men during the COVID-19 outbreak. An online questionnaire was conducted to collect data on contact with people suspected of infection/infected with the SARS-CoV-2 virus, use of stimulants, and perceived mental and sexual health during isolation among Polish men. They were also asked to answer the Beck Depression Inventory (BDI) and the International Index of Erectile Function (IIEF-15) questionnaire. In total, 606 men with a mean age of 28.46 ± 9.17 years took part in the survey. Fear of contracting the COVID-19 infection had a negative impact on the mental health of 132 men (21.8%). Fear of the health condition of loved ones caused stress and a depressed mood in 253 men (41.7%), and media reports worsened the mental health of 185 men (30.2%). In the BDI, 71.95% of the respondents did not suffer from depressive symptoms, 17.33% were diagnosed with mild depression, 6.11% with moderate depression, and 4.62% had severe depression. The mean score in the IIEF-15 questionnaire in the erectile function domain was 22.27, orgasm-7.63, desire-8.25, satisfaction-10.17, and general satisfaction-6.84. Depressive symptoms indicated more severe sexual functioning disorders (p < 0.001). Fear, following the media, and loneliness were associated with more severe depressive and sexual disorders (p < 0.001). The libido level (p = 0.002) and frequency of sexual activity (p < 0.001) were also lower during the pandemic than before the lockdown. These data showed that the COVID-19 pandemic had a significant impact on male mental and sexual health.

Banking systemic risk estimating of China's banking industry during the COVID-19 pandemic—based on complex network theory

The spread of COVID-19 worldwide has led to significant fluctuations in the global financial market, and the banking industry has also been exposed to the dual impact of the real economy and the financial market. In this paper, Chinese bank networks in different COVID-19 periods were constructed using CoVaR model and least absolute shrinkage and selection operator (LASSO) regression, and the characteristics and risk changes of the proposed bank networks were analyzed based on complex network theory. Additionally, the index of complex network theory was combined with the non-performing loan ratio of banks to build a new index for evaluating and measuring the systemic risk of banks in different periods. It was found that the network density, clustering coefficient and average network strength of banking networks increased during the COVID-19 pandemic, while the level of inter-bank correlation, and the systemic risk of banking networks increased. It was suggested after using the new indicators that joint-stock commercial banks and rural commercial banks were the main risk spillovers in different periods, and the systemic risk of these banks had increased during COVID-19. Therefore, the supervision of joint-stock commercial and rural commercial banks should be strengthened to prevent the risks from spreading to these banks during the COVID-19 pandemic.

The impact of air travel on the precocity and severity of COVID-19 deaths in sub-national areas across 45 countries

Human travel fed the worldwide spread of COVID-19, but it remains unclear whether the volume of incoming air passengers and the centrality of airports in the global airline network made some regions more vulnerable to earlier and higher mortality. We assess whether the precocity and severity of COVID-19 deaths were contingent on these measures of air travel intensity, adjusting for differences in local non-pharmaceutical interventions and pre-pandemic structural characteristics of 502 sub-national areas on five continents in April–October 2020. Ordinary least squares (OLS) models of precocity (i.e., the timing of the 1st and 10th death outbreaks) reveal that neither airport centrality nor the volume of incoming passengers are impactful once we consider pre-pandemic demographic characteristics of the areas. We assess severity (i.e., the weekly death incidence of COVID-19) through the estimation of a generalized linear mixed model, employing a negative binomial link function. Results suggest that COVID-19 death incidence was insensitive to airport centrality, with no substantial changes over time. Higher air passenger volume tends to coincide with more COVID-19 deaths, but this relation weakened as the pandemic proceeded. Different models prove that either the lack of airports in a region or total travel bans did reduce mortality significantly. We conclude that COVID-19 importation through air travel followed a ‘travel as spark’ principle, whereby the absence of air travel reduced epidemic risk drastically. However, once some travel occurred, its impact on the severity of the pandemic was only in part associated with the number of incoming passengers, and not at all with the position of airports in the global network of airline connections.

Tracing Chinese international students' psychological and academic adjustments in uncertain times: An exploratory case study in the United Kingdom.

The worldwide spread of COVID-19 has exerted tremendous influences on the wellbeing of international students and the sustainable development of higher education. The current study adopts an 8-month exploratory case study to trace eight Chinese international students’ psychological and academic adjustments in the United Kingdom amid the COVID-19 pandemic. Emerging from the qualitative data constitutive of semi-structured interviews, self-reflection writings, memoing, together with stimulated-recall interviews, findings have demonstrated the three main types of obstruction for such students’ adjustments in the foreign land including COVID-specific challenges (i.e., the threat of infect, reduced access to university facilities and resources); COVID-enhanced challenges (i.e., anxiety exacerbated by parents and social media use, anti-Asian racism and hate incidents); and language barriers and cultural differences as long-standing issues. Students’ previous lockdown experience, individual resilience, development of monocultural friendship patterns, and institutional provision and support are all factors that have contributed to their ability to overcome or at least mitigate the psychological and academic difficulties. The study offers insight into the impacts of COVID-19 on international students, providing implications that could contribute to the sustainable adjustments of international students in times of disruptive events and inform future responses to global health crises from individual and higher education perspectives.

Identifying the High-Risk Population for COVID-19 Transmission in Hong Kong Leveraging Explainable Machine Learning.

The worldwide spread of COVID-19 has caused significant damage to people’s health and economics. Many works have leveraged machine learning models to facilitate the control and treatment of COVID-19. However, most of them focus on clinical medicine and few on understanding the spatial dynamics of the high-risk population for transmission of COVID-19 in real-world settings. This study aims to investigate the association between population features and COVID-19 transmission risk in Hong Kong, which can help guide the allocation of medical resources and the implementation of preventative measures to control the spread of the pandemic. First, we built machine learning models to predict the number of COVID-19 cases based on the population features of different tertiary planning units (TPUs). Then, we analyzed the distribution of cases and the prediction results to find specific characteristics of TPUs leading to large-scale outbreaks of COVID-19. We further evaluated the importance and influence of various population features on the prediction results using SHAP values to identify indicators for high-risk populations for COVID-19 transmission. The evaluation of COVID-19 cases and the TPU dataset in Hong Kong shows the effectiveness of the proposed methods. The top three most important indicators are identified as people in accommodation and food services, low income, and high population density.

Scientometric Analysis of Global Scientific Publications on COVID-19 and Diabetes with an Emphasis on Middle Eastern Countries.

Due to the worldwide spread of COVID-19, various countries have designed scientific studies on different aspects of the disease. Patients with diabetes mellitus (DM) have been proven to be at higher risk of COVID-19-related complications, hospitalization, and death. The aim was to conduct a scientometric analysis of scholarly outputs on diabetes and COVID-19. Web of Science was searched for scientific publications on diabetes and COVID-19 by Middle Eastern researchers until September 14, 2021. Collected data were analyzed for document type, subject area, countries, top journals, citation number, and authors' collaboration network using VOS viewer 1.6.15 and bibliometrix R-package 4.1.1. Overall, the characteristics of 603 documents on DM and COVID-19 were analyzed. The top three productive countries in the field were Iran, Turkey, and Saudi Arabia. The top affiliation was from Iran; "Tehran University of Medical Sciences" (n = 168), followed by "Shahid Beheshti University of Medical Sciences" (n = 82). The total citation number was 3704 times. The highest cited paper (348) was a systematic review from Iran, published in arch Acad Emerg Med. The top source was "Diabetes & Metabolic Syndrome: Clinical Research & Reviews," with 26 documents. The current study provides an overview of the quantity and quality of published scholarly documents on the intersection of DM and COVID-19 in the region. Our findings help scientists find the existing gaps, manage the research budgets, identify active authors and scientific institutes to collaborate with, and use their experience to produce new knowledge in the future.

Peculiarities of language teaching during the quarantine period at the Ferenc Rákóczi II Transcarpathian Hungarian College of Higher Education (the results of questionnaire data and of interviewing)

The year 2020 will be remembered for a long time for the worldwide spread of COVID-19, andall the unprecedented consequences it had caused. The extremely swift transition from in-class to online teachingmeant serious challenges for academia, both teachers and students. Aims. Therefore, our main objective wasto collect empirical evidence from instructors on how they coped with the tasks and challenges that they hadto face when starting teaching remotely. Methods. To better understand the undergoing processes and get insightsinto how language teachers at a higher educational establishment managed to solve the tasks they had to dealwith and complete successfully, we have created an online questionnaire for tutors to fill in during the first phaseof our investigation, while in the second one we used an interview, the results of which were analysed qualitatively.Results. The results revealed that for most of the instructors distance teaching was a completely new area ofexperience as they had not tried doing it before the pandemic. A crucial pedagogical implication derives fromВісник КНЛУ. Серія Педагогіка та психологія. Випуск 36. 202290this empirical evidence, namely, that it is of utmost importance that tutors be trained how to teach online.The factors that caused the most significant difficulties for the tutors were, among others, the assessment of studentperformance and knowledge. This finding also confirms the implication that tutors must be provided with thechance to develop their skills as online teachers. Conclusions. The second phase of our research highlighteda number of positive features of distance learning. First, students who were unable to participate in theeducational process prior to COVID-19, e.g. due to illness, are now able to join classes online, as the collegeprovides the technical background for this. Another benefit could be to involve renowned foreign speakersin the educational process. While our invited lecturers before COVID-19 came to our college in person andgave lectures to students, this is completely impossible due to the current crisis situation. However, the perfectsolution could be online connection.

Are private equity and venture capital helping small and medium-sized enterprises during the COVID-19 pandemic? Evidence from China

The rapid spread of COVID-19 worldwide since 2020 has, undeniably, negatively influenced the global economy and environment. Small and medium-sized enterprises (SMEs) are among the worst-hit victims of COVID-19, particularly in developing countries. As primary channels financing SMEs, what roles have private equity and venture capital (PE/VC) played in this crisis? Using the 2010–2021 data of 4462 listed companies, we aimed to assess the impact of PE/VC on financial risk among Chinese SMEs. We constructed a capital structure selection model to assess the risk preference of PE/VC and explored the roles of PE/VC in the financial risk management of enterprises during COVID-19. Based on both theory and empirical evidence, PE/VC negatively impacts the financial risk of enterprises, implying that intervention by the management of PE/VC can aggravate the financial risk. However, in reality, PE/VC positively impacted enterprise financial risk during COVID-19. Thus, the government should implement some easing policies to stimulate access and investment policies of PE/VC as well as provide more practical policies to support investment institutions in China and other counties.

Supervised Machine Learning Approach to COVID-19 Detection Based on Clinical Data.

Background: The new coronavirus has been spreading since the beginning of 2020, and many efforts have been made to develop vaccines to help patients recover. It is now clear that the world needs a rapid solution to curb the spread of COVID-19 worldwide with non-clinical approaches such as artificial intelligence techniques. These approaches can be effective in reducing the burden on the health care system to provide the best possible way to diagnose the COVID-19 epidemic. This study was conducted to use Machine Learning (ML) algorithms for the early detection of COVID-19 in patients. Methods: This retrospective study used data from hospitals affiliated with Shiraz University of Medical Sciences in Iran. This dataset was collected in the period March to October 2020 andcontained 10055 cases with 63 features. We selected and compared six algorithms: C4.5, support vector machine (SVM), Naive Bayes, logistic Regression (LR), Random Forest, and K-Nearest Neighbor algorithm using Rapid Miner software. The performance of algorithms was measured using evaluation metrics, such as precision, recall, accuracy, and f-measure. Results: The results of the study show that among the various used classification methods in the diagnosis of coronavirus, SVM (93.41% accuracy) and C4.5 (91.87% accuracy) achieved the highest performance. According to the C4.5 decision tree, "contact with a person who has COVID-19" was considered the most important diagnostic criterion based on the Gini index. Conclusion: We found that ML approaches enable a reasonable level of accuracy in the diagnosis of COVID-19.

Artificial intelligence and IoT based prediction of Covid-19 using chest X-ray images.

Coronavirus illness (COVID-19), discovered in late 2019, has spread rapidly worldwide, resulting in significant mortality. This study analyzed the performance of studies that employed machines and DL on chest X-ray pictures and CT scans for COVID-19 diagnosis. ML approaches on CT and X-ray images aided incorrectly in identifying COVID-19. The fast spread of COVID-19 worldwide and the growing number of deaths necessitates an immediate response from all sectors. Authorities will be able to deal with the effects more efficiently if such illnesses can be predicted in the future. Furthermore, it is crucial to maintain track of the number of infected persons through regular check-ups, and it is frequently required to confine affected people and implement medical treatments. In addition, various additional elements, such as environmental influences and commonalities among the most afflicted places, should be considered to slow the spread of COVID-19, and precautions should be taken. AI-based approaches for the prediction and diagnosis of COVID-19 were suggested in this paper. This Review Article discusses current advances in AI technology and its biological applications, particularly the coronavirus.

Mandatory Vaccination Against COVID-19: Twitter Poll Analysis on Public Health Opinion.

BackgroundOn January 30, 2020, the World Health Organization Emergency Committee declared the rapid worldwide spread of COVID-19 a global health emergency. By December 2020, the safety and efficacy of the first COVID-19 vaccines had been demonstrated. However, international vaccination coverage rates have remained below expectations (in Europe at the time of manuscript submission). Controversial mandatory vaccination is currently being discussed and has already been introduced in some countries (Austria, Greece, and Italy). We used the Twitter survey system as a viable method to quickly and comprehensively gather international public health insights on mandatory vaccination against COVID-19.ObjectiveThe purpose of this study was to better understand the public’s perception of mandatory COVID-19 vaccination in real time using Twitter polls.MethodsTwo Twitter polls were developed (in the English language) to seek the public’s opinion on the possibility of mandatory vaccination. The polls were pinned to the Digital Health and Patient Safety Platform’s (based in Vienna, Austria) Twitter timeline for 1 week in mid-November 2021, 3 days after the official public announcement of mandatory COVID-19 vaccination in Austria. Twitter users were asked to participate and retweet the polls to reach the largest possible audience.ResultsOur Twitter polls revealed two extremes on the topic of mandatory vaccination against COVID-19. Almost half of the 2545 respondents (n=1246, 49%) favor mandatory vaccination, at least in certain areas. This attitude contrasts with the 45.7% (n=1162) who categorically reject mandatory vaccination. Over one-quarter (n=621, 26.3%) of participating Twitter users said they would never get vaccinated, as reflected by the current Western European and North American vaccination coverage rate. Concatenating interpretation of these two polls should be done cautiously as participating populations might substantially differ.ConclusionsMandatory vaccination against COVID-19 (in at least certain areas) is favored by less than 50%, whereas it is opposed by almost half of the surveyed Twitter users. Since (social) media strongly influences public perceptions and views, and social media discussions and surveys are specifically susceptible to the “echo chamber effect,” the results should be interpreted as a momentary snapshot. Therefore, the results of this study need to be complemented by long-term surveys to maintain their validity.

Research on the Design Strategy of Healing Products for Anxious Users during COVID-19

With the spread of COVID-19 worldwide, various travel restrictions are becoming a significant trigger for anxiety. Although healing products could relieve anxiety, few scholars have proposed a practical design strategy. Therefore, we offer a design strategy for healing products that includes three phases: preparation, analysis, and verification. In Phase 1, 20 people with moderate or high anxiety are invited to rate 100 samples. Then, FCM is used to obtain representative samples. In Phase 2, a three-layer diagram (incl. the upper, middle, and lower layers) of healing products is obtained using the evaluation grid method. Subsequently, the middle layer is considered evaluation criteria. Additionally, 18 items in the lower layer are considered design guidelines. In Phase 3, we invite two teams to develop innovative designs based on design guidelines and personal experience, generating four alternatives. Finally, four alternatives and four healing commodities are evaluated using grey relation analysis and perceptual questionnaires. The consistency of both evaluations could confirm the validity of the evaluation criteria. The alternatives generated based on the design guidelines are better than other alternatives, demonstrating the effectiveness of the design guidelines. The design strategy is beneficial for developing and evaluating healing products to alleviate people’s anxiety during COVID-19.

해조류 바이오매스로부터 Lactic acid를 제조하는 방법에 관한 연구

With the spread of COVID-19 worldwide, non-face-to-face services have grown rapidly, but at the same time, the problem of plastic waste is getting worse. Accordingly, eco-friendly policies such as carbon neutrality and sustainable circular economy are being promoted worldwide. Due to the high demand for eco-friendly products, the packaging industry is trying to develop eco-friendly packaging materials using PLA and PBAT and create new business models. On the other hand, Ulva australis occurs in large quantities in the southern seas of Korea and off the coast of Jeju Island, causing marine environmental problems. In this study, lactic acid was produced through dilute acid pretreatment, enzymatic saccharification, and fermentation processes to utilize Ulva australis as a new alternative energy raw material. In general, seaweeds vary in carbohydrate content and sugar composition depending on the species, harvest location, and time. Seaweed is mainly composed of polysaccharides such as cellulose, alginate, mannan, and xylan, but does not contain lignin. It is difficult to expect high extraction yield of the complex polysaccharide constituting Ulva australis with only one process. However, the fusion process of dilute acid and enzymatic saccharification presented in this study can extract most of the sugars contained in Ulva australis. Therefore, the fusion process is considered to be able to expect high lactic acid production yield when a commercial-scale production process is established.

빅데이터를 토대로 분석한 포스트코로나 시대 트래블버블에 관한 연구 : 텍스트 마이닝 활용

With the spread of Covid-19 worldwide in 2020, the future of the aviation industry is facing a tremendous crisis. This study aims to predict the change in Korean Air travel behavior after Covid-19. To this end, this study intends to measure the public

How has the initial lockdown and reopening due to the COVID-19 pandemic affected physical activity level and well-being in Turkey?

Background/Aim: The worldwide spread of COVID-19 caused changes in daily routines. During the lockdown, parks and gyms were closed and access to outdoor areas was limited. After reopening, many restrictions were removed. Since this process may have altered physical activity and well-being levels, this study aimed to explore how physical activity (PA) levels and well-being of Turkish citizens were affected by the initial COVID-19 lockdown and the reopening. Methods: In this prospective, cross-sectional study, participants were asked to complete an online survey twice: first in May 2020 (when initial strictest partial lockdown procedures were applied) and second in July 2020 (after most restrictions had been removed). The online survey consisted of questions related to demographics, PA levels, and well-being. Categorical questions (expressed as either day per week or min per day) were used to assess vigorous and moderate PA, time spent sitting, etc. The WHO-5 Well-Being Index was used to assess well-being. Results: The mean age and the body mass indexes of 94 individuals (52 females, 42 males) were 36.16 (10.04) years and 25.14 (3.82) kg/m2, respectively. During both lockdown and after reopening, low levels of PA and well-being levels above the low mood limit (< 50) were identified. No significant change was found in either any of the PA-related variables or the well-being of participants between the initial and final assessments (P > 0.05). Conclusion: Our results showed that PA levels and well-being of Turkish citizens remained unchanged after the reopening process when compared to the initial lockdown due to COVID-19. These findings may also suggest that reopening was not a sufficient stimulant factor to alter physical activity and well-being. Despite all the negative effects brought on by the pandemic, it is essential to adopt approaches to keep PA levels and well-being high.

COVID-19 pandemic restrictions unmasks dangers of frequent injury mechanisms for common surgically treated pediatric fractures.

Purpose:This study examined the volume and characteristics of common surgically treated fractures in children during the COVID-19 pandemic. The worldwide spread of COVID-19 affected the society in numerous ways. Social distancing led to changes in the types of activities performed by individuals, including children. Physicians saw a shift in orthopedic trauma volume and distribution. We predicted that with the change in activities children participated in, the number or type of injuries sustained would change as well.Methods:A retrospective review was performed of children who sustained a surgically treated fracture of the forearm, supracondylar humerus, femur, or any open fracture during the COVID-19 pandemic compared to the previous 2 years (pre-pandemic). Patient demographics, insurance status, and mechanism of injury were recorded. Statistical analysis was performed.Results:Review of the medical records identified 791 children. The number of fractures decreased from an average of 295 per year pre-pandemic to 201 during the pandemic (p = 0.09). During the pandemic, there was a decrease in injuries resulting from a fall from the monkey bars for supracondylar humerus (21.2% to 8.2%, p < 0.01) and for forearm fractures (15.5% to 4.3%, p = 0.04). In contrast, the frequencies of falls from a skateboard, hoverboard, scooter, or bicycle and falls from household furniture increased during the pandemic.Conclusion:The observed decrease in monkey bar–related injuries provides further evidence as to the dangers of this piece of playground equipment in contributing to upper-extremity fractures in children.Level of evidence:Level III: Prognostic and Epidemiological.