Is chlorhexidine mouthwash effective in lowering COVID-19 viral load? A systematic review.

OBJECTIVE: This review aims to determine whether there is considerable evidence that mouthwashes containing chlorhexidine (CHX) lower the COVID-19 virus load in saliva. MATERIALS AND METHODS: A comprehensive literature search was carried out in PubMed/Medline, EMBASE, LILACS, Scopus, Web of Science and Cochrane Library, Google Scholar, Open Gray, and ProQuest electronic databases using the keywords: "coronavirus infections" or "coronavirus" or "covid 2019" or "sars 2" or "sars-cov-2" or "sars-cov-19" or "severe acute respiratory syndrome coronavirus 2" or "coronavirus infection" or "severe acute respiratory pneumonia outbreak" and "CHX" or "CHX Hydrochloride" or "CHX Digluconate." A manual search of the articles was also conducted utilizing the reference lists of articles. The in vitro experimental and clinical studies that tested CHX mouthwash were included. Study selection was not restricted or limited to a specific gender, age, ethnicity of individuals, or time of publication. A mix of keywords and proper truncations were used to search for databases. RESULTS: Twelve studies (7 clinical and 5 in vitro) published between 2020 and 2021 were included in this systemic review. Five randomized controlled trials and one clinical case series demonstrated the effectiveness of CHX in reducing the oral viral load; one was inconclusive. Of the five in vitro studies, three showed that CHX is effective against SARS-CoV-2, and two studies denied the effectiveness of CHX. All in vitro studies tested CHX activity concentrations of 0.2, 0.12, and 0.1%. One study reported more than a 99.9% reduction in SARS-CoV-2 viral load in a minimal contact time of 30 seconds. CHX exhibited potent antiviral activity at higher concentrations without cytotoxicity. CONCLUSIONS: Despite differences in the published research, CHX at different concentrations may be effective in lowering the SARS-COV-2 viral load in saliva.

COVID-19, from Crisis to Opportunity: Assessing Teaching Programming Languages Online Using Statistical Methods

In early 2020, COVID-19 appeared and widely spread worldwide. It affected all vital sectors, including commercial activities and education. Most governments decided to temporarily close educational institutions, including schools and universities. Developed countries with adequate learning-management systems moved to the online teaching mode. Hence, the sudden transition from the traditional to online teaching mode has impacted learning outcomes. The ultimate goal of this paper is to develop a method for evaluating the experience of teaching online during epidemics. More precisely, it assesses the teaching of programming language courses in the computer science and engineering college at the University of Hail. It statistically measures the courses' learning outcomes in the online mode compared to the traditional mode. Perhaps surprisingly, the difference was not significant, which shed light on the positive side of the crisis. According to the obtained results, the experience of teaching online during an epidemic has led us to investigate the opportunities of using online teaching, especially for programming language courses. This highlighted opportunities for using online platforms as supportive teaching tools or even merging them with traditional teaching approaches at times when attending classes on campus is impossible. Finally, to ensure best practices, the author recommended some guidelines to follow. © 2022 IEEE.

Role of mouthwashes in combating SARS-COV 2 COVID-19 virus: Assessment of the knowledge of Middle Eastern Dentists

Background: Mouthwashes are deemed an effective measure in mitigating the risk of coronavirus contraction in dental clinics through limiting aerosol spread during procedures. This study aimed to evaluate the attitude, knowledge, and practices of Middle Eastern dental professionals regarding the use of mouthwash for combatting the coronavirus. Methods: This cross-sectional study was conducted online between the 1st and 15th of September 2021 where a random sample of dental practitioners were enrolled from Saudi Arabia, Qatar, Oman, UAE, Egypt, Turkey, Bahrain, and Kuwait. The survey included questions about the participants' demographics, degree of knowledge and use of mouthwashes for coronavirus. Results: Of the 880 participants filling the questionnaire, the majority were males 500 (56.8%), consultants 324 (36.8%), and based in Egypt 224 (25.5%). Only 5.6% of the enrolled dental practitioners were conscious of the presence of more than four types of medicated mouthwashes. Almost 86% of the participants were unknowledgeable of the benefit of mouthwashes for COVID 19, with an approximately similar percentage (83.2%) of dentists believing that the current literature is deficient. Notably, more than two-thirds of the dentists had a negative attitude towards the role of mouthwashes in disrupting the coronavirus. Also, 43.2% of the participants had a wrong perception of the superiority of chlorhexidine in eradicating the virus as compared to other rinses. Conclusion: Dental professionals based in the Middle East have inadequate knowledge and a negative perception of the role of mouthwashes in minimizing cross-transmission of coronavirus between dentists and patients in dental clinics.

Impact of the COVID-19 pandemic on essential workers in Europe: Subset analysis of a global online survey

Introduction: This study aims to explore how essential workers in Europe differed from the rest of the population in terms of their experiences of social life, access to services, mental well-being, and perceived benefits of the lockdown. Methods: This study used a descriptive analysis to evaluate the overall experiences of the essential workers in Europe. Data analyzed in this study is part of a larger global online cross-sectional survey conducted during April to November 2020 involving post-secondary staff, students and the general population (remote workers). Data of 19,794 participants are included in the current study, and analysis is based on a comparison of participants who self-identified as essential workers, with those who did not using the chi-square test. Results: Mean age was 34.5 years (SD =13.0) for essential workers and 30.2 years (SD =12.4) for the general population (remote workers). While 13.6% of all respondents were essential workers, the proportion was more among older ages (30 and above), females, and those who lived in suburbs. Overall, 46.8% of participants reported increased levels of stress during week 1-2 (51% of essential workers and 46.1% of the other participants, p<0.001). More essential workers reported their social life being great than the rest of the population (25.3% vs. 16.4%, p<0.001), and COVID-19 symptoms (13.6 vs 10.5%, p<0.001). In addition, fewer reported having troubled relationships (16.3% vs. 18.6%, p<0.001) or being able to do sufficient exercise (35.7% vs. 40.5%, p<0.001) than the general population (remote workers). Take-home message: The important role of essential workers during the pandemic cannot be overstated, yet their contributions, especially non-healthcare essential workers, have not been fully appreciated. © 2022 Parvin EFTEKHAR et al.

SDA-COVID-19: Social Distancing App for COVID-19 track and control

COVID-19 is a highly contagious and lethal virus-based disease. Social distancing is the only way to stop the virus from spreading. In this context, the researchers suggest a social distancing application named SDA-COVID-19. The suggested App (SDA-COVID-19) will help individuals maintain social distancing by the exchange of data among phones about potentially infected and/or contaminated people with COVID-19, with whom an individual socialized or came in contact, whereby, an indi-vidual will be alerted if a COVID-19 infected person is in close proximity. Two versions are suggested for SDA-COVID-19 one is Service-Oriented and the other is Bluetooth oriented.

Teledentistry Approaches for Dental Assessments and Consultation During the COVID-19 Pandemic

Introduction: COVID-19 pandemic shows the importance of teledentistry usage to cope with such conditions and to improved the patient access and quality of care. Since dental treatments are highly infectious procedures due to the close proximity to patients required and the extended exposure to aerosols (including water from high- and low-speed handpieces and patients’ saliva and blood). Viruses such as COVID- 19 could be transmitted through these aerosols. As a result dental treatments were limited to emergency only, according to the guidance of the Ministry of Health. This limitation increases the need for means of communication between dental practitioners and patients in order to follow up and provide consultation without direct contact. This could be provided by using telemedicine. Methods: However, the evidence assessing the effectiveness of this intervention is scars. Therefore, The aim of this study is to conduct mixed method research (quantitative and qualitative) to measure the effectiveness of teledentistry usage during the COVID-19 pandemic. To provide an in-depth understanding of the use of teledentistry in assessing urgent dental cases and providing consultations. Results: The sample size for the quantitative part of the study (questionnaire) will include Patients that contacts the virtual clinic and attended to their appointments between 28/4/20 and 30/6/20 (the total will be 125 patients), While the sample for the qualitative part will be dentists who used to work in the call center listed in the virtual clinic database. Conclusion: The outcome of the study is to provide an overview of the use of teledentistry in assessing urgent dental cases and providing consultations and patients satisfaction of the provided service.

Lichen planus after COVID-19 vaccination: A report of two cases

Lichen planus is a T-cell-mediated inflammatory disease that can be associated with preexposure to particular agents encompassing vaccines, viruses, and drugs. The origin of the disease is unknown and has varying clinical presentations, the recent manufactured COVID-19 vaccines have been linked with several cutaneous reactions that are similar to the cutaneous manifestations of COVID-19 virus infection, the majority of people developed cutaneous manifestations after the second dose of Pfizer vaccine, recent cases have been reported as a flare of a preexisting lichen planus following the administering of the Pfizer vaccine. We present a two interesting cases that developed a dermatological condition post Pfizer-BioNTech's COVID-19 vaccine. The first case is a 60-year-old man, with a past medical history of having lichen planus 15 years ago, that have been treated and controlled successfully with topical therapy, flared up following the administration of Pfizer-BioNTech's COVID-19 vaccine. The second case is a 57-year-old female with a past medical history of hypertension and hypothyroidism controlled. Develop the new onset of lichen planus after receiving the third dose of the COVID 19 vaccine. The lesions arise 3 weeks after the third dose.

Optimal Kernel Extreme Learning Machine for COVID-19 Classification on Epidemiology Dataset

Artificial Intelligence (AI) encompasses various domains such as Machine Learning (ML), Deep Learning (DL), and other cognitive technologies which have been widely applied in healthcare sector. AI models are utilized in healthcare sector in which the machines are used to investigate and make decisions based on prediction and classification of input data. With this motivation, the current study involves the design of Metaheuristic Optimization with Kernel Extreme Learning Machine for COVID19 Prediction Model on Epidemiology Dataset, named MOKELM-CPED technique. The primary aim of the presented MOKELM-CPED model is to accomplish effectual COVID-19 classification outcomes using epidemiology dataset. In the proposed MOKELM-CPED model, the data first undergoes pre-processing to transform the medical data into useful format. Followed by, data classification process is performed by following Kernel Extreme (SOS) optimization algorithm is utilized to fine tune the KELM parameters which consequently helps in achieving high detection efficiency. In order to investigate the improved classifier outcomes of MOKELM-CPED model in an effectual manner, a comprehensive experimental analysis was conducted and the results were inspected under diverse aspects. The outcome of the experiments infer the enhanced performance of the proposed method over recent approaches under distinct measures.

Performance improvement of decision tree: A robust classifier using tabu search algorithm

Classification and regression are the major applications of machine learning algorithms which are widely used to solve problems in numerous domains of engineering and computer science. Different classifiers based on the optimization of the decision tree have been proposed, however, it is still evolving over time. This paper presents a novel and robust classifier based on a decision tree and tabu search algorithms, respectively. In the aim of improving performance, our proposed algorithm constructs multiple decision trees while employing a tabu search algorithm to consistently monitor the leaf and decision nodes in the corresponding decision trees. Additionally, the used tabu search algorithm is responsible to balance the entropy of the corresponding decision trees. For training the model, we used the clinical data of COVID-19 patients to predict whether a patient is suffering. The experimental results were obtained using our proposed classifier based on the built-in sci-kit learn library in Python. The extensive analysis for the performance comparison was presented using Big O and statistical analysis for conventional supervised machine learning algorithms. Moreover, the performance comparison to optimized state-of-the-art classifiers is also presented. The achieved accuracy of 98%, the required execution time of 55.6 ms and the area under receiver operating characteristic (AUROC) for proposed method of 0.95 reveals that the proposed classifier algorithm is convenient for large datasets. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

A Novel Framework of Success Using of E-Assessment During Corona Pandemic

Recently, the concept of e-learning has spread widely in many universities around the world under the current circumstances (the Corona pandemic), which made e-learning in many countries' compulsory for all its students in universities in order not to stop the educational process. In light of the great improvement that some countries are witnessing in information and communications technology (ICT) sector and e-learning platforms, it has become very important to pay attention to the electronic assessment (e-assessment) side, which appeared side by side with e-learning systems. This kind of assessment is overcome some of the limitations in the paper-based assessment. One of the advantages of an electronic assessment (e-assessment) is the ability to provide feedback to the student immediately. Most of the universities around the world were providing e-learning to their students as a development option for the education process, on condition that they attend to take the exam in the universities in attendance. But in the Corona crisis, this thing was not possible, especially in subjects that have very large number of students, so (e-assessment) has become a basic option for most universities in order to achieve the principle of social distancing. Therefore, this paper examines the factors that affect academic acceptance of (e-assessment) system.

Implementation of Virtual Consultations for Epilepsy during the COVID-19 Pandemic among Neurologists in Saudi Arabia

Background: To reduce disease exposure, telemedicine has been used to help healthcare systems that have been faced with challenges since the COIVD-19 outbreak in managing emergency departments, outpatient care clinics and providing ongoing care to those with chronic illnesses such as epilepsy. Objectives: The aim of this study is to assess the emergency implementation of virtual consultations among neurologists in Saudi Arabia in the wake of the COVID-19 pandemic. Methods: A cross-sectional study was conducted from August to September 2020 in survey format distributed electronically to neurologists practicing in Saudi Arabia. Descriptive and correlative statistical analyses were performed to identify factors associated with onsite and virtual clinic visits in those treating patients with epilepsy. Results: A total of 92 neurologists participated in the study. The majority of neurologists (75%) care for COVID-19 patients along with their regular clinic duties. There was statistical significance between the duration of the virtual visit in comparison to the onsite clinic visit and the neurologists' views on the future of teleneurology for epilepsy patients(G(2)(4, N = 92) = 18.673, p = 0.001). Conclusion: Virtual consultations have been a way to decrease personal contact and disease exposure since the start of the COVID-19 pandemic. For those suffering with chronic conditions such as epilepsy, telemedicine may be a useful resource in following up with a neurologist and medication changes may be successfully made.