Adverse effects of COVID-19 Pfizer-BioNTech vaccine in children aged 5-18 years in Saudi Arabia

Coronavirus disease 2019 (COVID-19) can infect children of all ages. Despite the fact that children have a lower risk of exposure and are tested less frequently than adults, their incidence is similar to that of adults. The most effective way to prevent COVID-19 infection is by vaccination. The study's objective was to document vaccination side effects in children aged 5 to 18 years. This cross-sectional study had 303 participating kids between the ages of 5 and 18 in its sample. During the months of March and April 2022, a validated modified questionnaire was circulated as a Google form to KSA citizens via social networking sites. The questionnaire asked questions about the participant's background, socio-demographic information, vaccination history, the mild and major adverse effects of the Pfizer vaccine and how those symptoms affected the child's health and quality of life. There was a total of 303 responses;all of them received two doses of the Pfizer-BioNTech covid-19 vaccine. They were 163 female children (54 %) and 140 males (46 %). The most frequently reported minor adverse effects were body tiredness (88.2%), moderate fever (76.5%), mild headache (72.3%) and discomfort, redness and swelling at the injection site (90.7%). The most reported severe side effects were severe headache (32.8%) and high fever (21.8%). Only five children (4.2%) required hospitalization for 1-3 days. The most common side effects for the Pfizer Covid-19 were the mild and moderate one including pain, redness and swelling at the injection site, fatigue, fever and headache. Most of the symptoms were not severe to need hospital admission.

Exploring the Dynamics of COVID-19 with a Novel Family of Models

Much effort has recently been expended in developing efficient models that can depict the true picture for COVID-19 mortality data and help scientists choose the best-fit models. As a result, this research intends to provide a new G family for both theoretical and practical scientists that solves the concerns typically encountered in both normal and non-normal random events. The new-G distribution family is able to generate efficient continuous univariate and skewed models that may outperform the baseline model. The analytic properties of the new-G family and its sub-model are investigated and described, as well as a theoretical framework. The parameters were estimated using a classical approach along with an extensive simulation study to assess the behaviour of the parameters. The efficiency of the new-G family is discussed using one of its sub-models on COVID-19 mortality data sets. © 2023 by the authors.

Instructors Experience of using Cloud Computing Based Applications in Saudi Arabia

With the recent global spread of the COVID-19 (also known as the corona virus) pandemic, several governments have attempted to control its transmission through preventive and precautionary measures. Education is one of the factors that has been impacted by the pandemic. As a result, to limit the spread of the virus, many countries adopted distance education instead of traditional education to ensure the continuity of the educational process. Cloud computing is a technology that offers numerous advantages in the field of education. The Kingdom of Saudi Arabia was one of the countries that had decided and continues to use various cloud platforms for distance education. In this study, we look at how effective cloud computing platforms are in the learning process in Saudi Arabian schools. The primary goal of this research was to investigate the teacher's ability to access different cloud computing services, as well as their ease of use and utility, by evaluating the effectiveness of these platforms as a mode of teaching before and after the pandemic. A total of 559 male and female schoolteachers' data was collected using self-administered questionnaires in Al-Bahah region and was analyzed using the IBM SPSS Statistics software. The analysis of this study expanded our understanding on the possibility of using educational platforms across schools in the kingdom. The findings also revealed that the use of cloud platforms during the pandemic increased by 28% in the region which have now become integral part of education. Furthermore, the findings revealed that teachers frequently encountered difficulties in implementing cloud-based educational processes, particularly in rural and mountainous areas. © 2023 IEEE.

Classification and Prediction of Significant Cyber Incidents (SCI) using Data Mining and Machine Learning (DM-ML)

The rapid growth in technology and several IoT devices make cyberspace unsecure and eventually lead to Significant Cyber Incidents (SCI). Cyber Security is a technique that protects systems over the internet from SCI. Data Mining and Machine Learning (DM-ML) play an important role in Cyber Security in the prediction, prevention, and detection of SCI. This study sheds light on the importance of Cyber Security as well as the impact of COVID-19 on cyber security. The dataset (SCI as per the report of the Center for Strategic and International Studies (CSIS)) is divided into two subsets (pre-pandemic SCI and post-pandemic SCI). Data Mining (DM) techniques are used for feature extraction and well know ML classifiers such as Naïve Bayes (NB), Support Vector Machine (SVM), Logistic Regression (LR) and Random Forest (RF) for classification. A centralized classifier approach is used to maintain a single centralized dataset by taking inputs from six continents of the world. The results of the pre-pandemic and post-pandemic datasets are compared and finally conclude this paper with better accuracy and the prediction of which type of SCI can occur in which part of the world. It is concluded that SVM and RF are much better classifiers than others and Asia is predicted to be the most affected continent by SCI. Author

Differences in Users' Insights and Increase in The Acceptance Level for Using The BYOD Approach in Government, Non-Profit Organizations, and Private Sectors in Saudi Arabia

Digital transformation represents one of the main obstacles facing several government, private, and non-profit sectors that help stabilize digital transformation in the Arabic region. One of the helpful ways to improve the level of freedom, productivity, and flexibility among employees to accept the BYOD approach is using their own devices to perform their work both in and outside the workplace. This study focuses to present the differences between the main three economic sectors, which represent the most important pillars of the economy in Saudi Arabia within the Kingdom's Vision 2030. BYOD also has great importance to the stakeholders for raising their awareness by expressing the implications, if the concept of BYOD is widely and correctly adopted. The study uses the diffusion of innovation (DOI) framework and quantitative analysis data to determine the main dimensions and important factors that help increase the awareness of the target audience. The number of participants in this study was 830, and the participants are mixing between the government, private, and non-profit sectors. The main findings showed a significant impact of several factors such as the importance of knowledge, ease of use, employee satisfaction, risk awareness, and attention to increase the level of acceptance in three main sectors study for using the BYOD approach widespread and professional use.

When learning was disrupted in Saudi Arabia: Full-scale distance e-learning as a solution to face COVID-19

This case study investigated the experiences of Saudi university students and faculty concerning a switch to e-learning from the traditional mode of lecturing in response to the national lockdown started in March 2020 due to the COVID-19 pandemic. By using purposive sampling of eight Twitter feeds (five Saudi universities, one faculty association and two from the Ministry of Education), this study thematically analyzed over 2,000 social media (Twitter) postings in Spring 2020 to investigate how Saudi students and faculty members met this crisis head on. Four major concerns over the use of emergency distance education to complete semester studies emerged: (1) information technology and technical issues, (2) understanding online learning materials, (3) student assessment issues, and (4) faculty compliance and student support. Findings showed there is a need to train faculty and students to engage with distance learning, embrace fair and balanced student assessment strategies, and implement course design intelligence. © KONINKLIJKE BRILL NV, LEIDEN, 2022.

Teaching in the pandemic era in Saudi Arabia

In March 2020, as the world was still baffled with the unknowns of the COVID-19 pandemic, Alghamdi began documenting how teaching and learning in higher education changed its face as a result of the global health outbreak. The outbreak of the novel coronavirus (SARS-CoV-2) was first reported from Wuhan, China, and soon swept the world over. Teachers across the globe, including Saudi Arabia, began undertaking a plethora of on-the-ground work to combat and alleviate the impact of the pandemic. Teaching in the Pandemic Era in Saudi Arabia presents to educators, parents, and other interested readers a variety of perspectives, challenges, and highlights of the teaching methods that could be useful in the era of COVID-19. Its purposes are to not only document an important time of human history, education, and the outbreak of unknown pandemics but also outline strategies to serve as insights into and predictions of the unknown future of humanity, diseases, and human learning. © 2022 by Koninklijke Brill NV, Leiden, The Netherlands. All rights reserved.

Saudi Teachers' Attitudes towards using Online Learning for Young Children during the Covid-19 Pandemic

The outbreak of Covid-19 and consequent school closures created a considerable challenge for educational systems around the world. Many countries have shifted to online learning and other digital alternatives to ensure continuity in education. Within this global and historical context of the Covid-19 pandemic, the present study aimed to explore teachers' attitudes towards the use of online learning for young children in Saudi Arabia. A total of 346 early childhood teachers were surveyed during school closures and the concomitant shift to online learning and teaching. The teachers who participated were recruited from public and private kindergartens and early childhood centers. The respondents completed a survey consisting of two scales developed for the purposes of this study. The first scale explored teachers' general attitudes towards using online learning strategies with young children (10 items). The second scale explored teachers' attitudes towards using online learning with young children based on their professional experience during the Covid-19 pandemic (10 items). The findings indicated that the majority of the respondents held positive attitudes about the use of online learning as an alternative to regular schooling. However, some beliefs varied among respondents, for example, whether online learning is developmentally and educationally appropriate for young children, and whether it creates or lacks a learning atmosphere. In addition, chi-square test results for both scales indicated statistically significant associations between teacher attitudes towards using online learning and years of teaching experience. However, no statistically significant associations were found for both scales between teacher attitudes and geographic area (urban/rural) or school type (public/private). Implications for teaching during and beyond the pandemic are discussed. © 2022 Society for Research and Knowledge Management. All rights reserved.

Infection-Control knowledge, attitude, practice and risk perception of occupational exposure to COVID-19 among dentists: A cross-sectional survey.

Background: COVID-19 is a potentially fatal disease that was announced as a global pandemic at the beginning of the year 2020. Aim: The purpose of our cross-sectional study was to evaluate the infection-control knowledge, attitude, practice, and risk perception of occupational exposure to COVID-19 among multinational dentists. Patients and Methods: A self-designed, 33-item, English questionnaire was created and distributed through social media and digital communication platforms. The questionnaire covered the demographic data, knowledge and perception of the occupational risk of the COVID-19 infections, and compared some infection control measures taken before and after this global pandemic. The results were analyzed, and four scores were used to assess the aforementioned parameters. Results: A total of 300 multinational dentists answered our survey, with the majority being females (59%) and aging from 25 to 44 years old (68%). We found that a statistically significant relationship exists between attitude and nationality, country of practice, medical condition, and the practicing specialty (P < 0.05). In addition, risk perception had a statistically significant correlation with nationality, smoking habits, education level, and specialty (P < 0.05). Furthermore, there was a statistically significant correlation between the practice score and the gender, age, smoking habits, education level, nature of the practice (private or governmental), and academia affiliation (P < 0.05). Conclusions: The study sample had good compliance with the instructions and guidelines of the World Health Organization (WHO) and the Centre for Disease Control (CDC), with most of them improving their infection control precautions after the virus's emergence according to the said guidelines. Furthermore, our participants were fearful of the COVID-19 virus and the fact of being potential transmitters. Despite saying that, the significant majority of them reported being confident in treating COVID-19-positive patients.

Sentiment analysis for Arabic tweet about the COVID-19 Worldwide Epidemic

The purpose of this article was to highlight the sentiment analysis for specific Arabic tweets related to the COVID-19 Worldwide Epidemic. The technique proposed in this paper focused on using the machine learning algorithm with the purpose of applying sentiment analysis on a dataset which contained 4,575 Arabic tweets on the COVID-19 pandemic while also employing the Logistic Regression and Naive Bayes algorithms as classifiers for comparing the achieved results between them. This study showed the suitability and efficiency of a system using machine learning models for the analysis of Arabic tweets. The experimental outcomes revealed that the highest accuracy was reached by employing the Logistic Regression algorithm", namely, 97%". Twitter is one of the most widely used gateways of social media for the people who want to express their opinions and emotions. This study contributes to highlighting the task of sentiment analysis for the Arabic tweets about the COVID-19 pandemic by predicting the people's awareness about the Coronavirus in the Arab World.

A Unified Decision-Making Technique for Analysing Treatments in Pandemic Context

The COVID-19 pandemic has triggered a global humanitarian disaster that has never been seen before. Medical experts, on the other hand, are undecided on the most valuable treatments of therapy because people ill with this infection exhibit a wide range of illness indications at different phases of infection. Further, this project aims to undertake an experimental investigation to determine which treatments for COVID-19 disease is the most effective and preferable. The research analysis is based on vast data gathered from professionals and research journals, making this study a comprehensive reference. To solve this challenging task, the researchers used the HF AHP-TOPSIS Methodology, which is a well-known and highly effective Multi-Criteria Decision Making (MCDM) technique. The technique assesses the many treatment options identified through various research papers and guidelines proposed by various countries, based on the recommendations of medical practitioners and professionals. The review process begins with a ranking of different treatments based on their effectiveness using the HF-AHP approach and then evaluates the results in five different hospitals chosen by the authors as alternatives. We also perform robustness analysis to validate the conclusions of our analysis. As a result, we obtained highly corroborative results that can be used as a reference. The results suggest that convalescent plasma has the greatest rank and priority in terms of effectiveness and demand, implying that convalescent plasma is the most effective treatment for SARS-CoV-2 in our opinion. Peepli also has the lowest priority in the estimation. © 2022 Tech Science Press. All rights reserved.

Cybersecurity threats to Healthcare Sectors during Covid-19

This paper has discussed cybersecurity threats and their mitigation of measures to be taken in the healthcare sector. Due to the corona pandemic, the cases of cybersecurity hiked up, bringing havoc to online operators. As many governments were busy combating the pandemic, cybercriminals took advantage primarily to attack healthcare systems globally. Furthermore, the healthcare sector has been prone to attacks due to its vulnerability. It has faced challenges in keeping patient's data confidential, thus making its ng its accessibility easy by attackers. As a result, this paper has highlighted the appropriate measures to be taken by the health care sector in terms of hospital system infrastructures and safety. The paper has also discussed the common cybersecurity threats to the health sector via diverse methodologies as studied in the literature review of this paper. © 2022 IEEE.

Computer Science Graduation Project During Covid-19 Pandemic: Challenges and Solutions

The graduation project is one of the most challenging courses in the computer science curriculum since it combines all the skills that have been learned in the whole program. Covid-19 pandemic and all the consequences that come with it made teaching graduation projects burdensome. In this paper, the author documents the experience of teaching such a course in Covid-19 pandemic times including challenges, and solutions, and reflection on that experience. A compelling idea for the graduation project has been proposed to be implemented at the college. The idea includes implementing a cybersecurity lab, that has been divided into several teams, using old PCs at the building of the college of computer science and information systems, Najran University, Saudi Arabia. The challenges that arose during Covid-19 lockdown and fully virtual learning experience times have been documented. The solution to those challenges has been proposed, and a reflection on the whole teaching experience has been reported.

Impact of Covid-19 on asthmatic patients in Western region in Saudi Arabia

Background: Respiratory symptoms are a characteristic feature present in covid-19 patients, and they usually range from mild to severe. Asthma is a chronic disease involving the airways that carry air in and out of the lungs. However, there is limited resources that discuss the relation between asthma and prevalence of COVID-19. Aims: Identify the impact of covid-19 on asthmatic patients. Methodology: This is a descriptive cross-sectional study that was conducted to study the impact of COVID-19 on asthmatic patients, which was conducted using a prepared questionnaire which was distributed online among 300 patients with asthma. After collecting the data, MS Excel was used for data entry while SPSS version 24 was used for data analysis. Results: In this study, we were able to collect data from 311 asthmatic patients in response to our questionnaire. Most of the asthmatic patients were females (67.2%) with a ratio of females: males of 2:1. Moreover, most patients thought that they control their asthma well and only 13.5% indicated that they had frequent emergency visits because of asthma. The prevalence of COVID-19 in asthmatic patients was 64.3 % where a third of patients needed to go to hospital because of their bad condition, 12.6 % needed to be hospitalized in ICU and 56.4 % needed oxygen. Moreover, severity of COVID-19 symptoms and outcomes are related to the control of asthma where better control of asthma was associated with better outcomes including lower need for ICU admission and oxygen need. Conclusion: Prevalence of COVID-19 in asthmatic patients was much higher than the general population especially in female patients aged between 31-40 years old. Moreover, COVID-19 had more severe outcomes in asthmatic patients including higher prevalence of ICU admission and oxygen need. Poorer outcomes of COVID-19 were associated with poor control of asthma.

Barriers influencing diabetic adults' demand for diabetic retinopathy screening during the covid-19 pandemic in Taif city;patients' perspectives

Background: Diabetic Retinopathy (DR) is a complication of uncontrolled Diabetic mellitus (DM). It affects the vision-related quality of life significantly, and it is one of the leading causes of blindness. Various socio-cultural elements affect eye health-seeking behavior and barriers to access DR screening services (DRSS) by people with DM (PwDM). However, studies assessing barriers to DR screening among people with diabetes in Saudi Arabia are limited. The principal aim of this study was to evaluate the barriers to DR screening among Saudi diabetics during the COVID-19 pandemic. Methods: This was a cross-sectional, survey-based study conducted in Taif, Saudi Arabia, from October 2020 to September 2021. Data was collected using a predesigned self-administered online questionnaire. Then data were analyzed by the SPSS program, version 25 at a level of significance of 0.05. Results: A total of 1042 adults with diabetes were enrolled in the study. About 39% of them had diabetes duration of fewer than five years. Around 3.8% of the participants agreed that poor glycemic control enhances diabetic retinopathy progression, 18.9% agreed that diabetic individuals might have advanced diabetic retinopathy despite having good vision, 7.5% agreed that comorbidities enhance diabetic retinopathy progression and 3.9% agreed that DR can be detected early might save vision. Conclusion: Finally, the study found that patients had an appropriate degree of awareness on DR;however, several knowledge areas should be improved. Furthermore, our findings demonstrated that COVID-19 caused a delay in patient care, resulting in poorer outcomes in patients with DR.

An automated real-time face mask detection system using transfer learning with faster-rcnn in the era of the covid-19 pandemic

Today, due to the pandemic of COVID-19 the entire world is facing a serious health crisis. According to the World Health Organization (WHO), people in public places should wear a face mask to control the rapid transmission of COVID-19. The governmental bodies of different countries imposed that wearing a face mask is compulsory in public places. Therefore, it is very difficult to manually monitor people in overcrowded areas. This research focuses on providing a solution to enforce one of the important preventativemeasures of COVID-19 in public places, by presenting an automated system that automatically localizes masked and unmasked human faces within an image or video of an area which assist in this outbreak of COVID-19. This paper demonstrates a transfer learning approach with the Faster-RCNN model to detect faces that are masked or unmasked. The proposed framework is built by fine-tuning the state-of-the-art deep learning model, Faster-RCNN, and has been validated on a publicly available dataset named Face Mask Dataset (FMD) and achieving the highest average precision (AP) of 81% and highest average Recall (AR) of 84%. This shows the strong robustness and capabilities of the Faster-RCNN model to detect individuals with masked and un-masked faces. Moreover, this work applies to real-time and can be implemented in any public service area. © 2022 Tech Science Press. All rights reserved.

Security performance In Online Education systems in Saudi Arabia

Due to the spread of the COVID-19 virus globally and the transformation of traditional education into virtual education to reduce human contact and maintain social distancing, the Ministry of Education in the Kingdom of Saudi Arabia decided to solve the problem through distance education using a blackboard. For universities, colleges and Madrasati platform for all school categories. This search aims to identify weaknesses in e-learning platforms and discuss possible solutions to avoid them;the focus will be on the problem of unauthorized access. The percentage change in the percentage increase in the percentage increase in the area. The central issue of e-learning is that students can learn science courses in addition to sharing data. Viewpoint and contact in IS, study destination, international migration and other destination, network and international network. This virtual learning can help students develop new capabilities. This project explicitly centred around security and protection worries as the significant issues limiting understudy commitment. Due to the spread of the COVID-19 virus globally and the transformation of traditional education into virtual education to reduce human contact and maintain social distancing, the Ministry of Education in the Kingdom of Saudi Arabia decided to solve the problem through distance education using a blackboard. For universities, colleges and Madrasati platform for all school categories. This search aims to identify weaknesses in e-learning platforms and discuss possible solutions to avoid them. The focus will be on the problem of unauthorized access. The percentage change in the percentage increase in the percentage increase in the area. The central issue of e-learning is that students can learn science courses in addition to sharing data. Viewpoint and contact in IS, study destination, international migration and other destination, network and international network. This virtual learning can help students develop new capabilities. This paper explicitly centred around security and protection worries as the significant issues limiting understudy commitment.

Colorectal cancer screening during covid-19 pandemic;A systematic review

The pandemic of COVID 19 has led to the postponement of all elective procedures including screening colonoscopy due to the rising risk of infection with covid-19. Routine use of screening tests for colorectal cancer is not applicable during covid 19 pandemic including colonoscopy, computed tomographic colonography, colon capsule endoscopy, and fecal immunochemical test. Focused reviewing of the impact of covid-19 on the various diagnostic modalities for colorectal cancer screening is the objective of this review. Databases of PubMed, Embase, and Cochrane Library were searched for literature published before June 2020. This narrative review was created from a conscious dissection of different data obtained from the related articles. Careful categorical writing of the recommendations was done in an easy simple manner. The risk of the spread of COVID 19 infection could be higher after using aerosol-generating procedures such as upper and lower GIT endoscopy. Also, CT might raise the risk of infection. Colon capsule endoscopy may be considered a potentially valuable procedure for colorectal cancer screening during the pandemic of COVID 19. During the post-COVID-19 recovery phase, it is expected to have a high demand for colonoscopy services as waiting lists will grow in that time. Colon capsule endoscopy may be considered a valuable diagnostic modality for prioritizing those who will need screening colonoscopy. Colon capsule endoscopy seems to be superior to other modalities for the screening of colorectal cancer during the pandemic of COVID 19 while postponement of colonoscopy service. Colon capsule endoscopy can be used for triaging those requiring further endoscopic procedures. © 2021 Teikyo University School of Medicine. All rights reserved.

Immune monitoring of kidney transplant recipients after SARS-CoV-2 mRNA vaccination

Background: There is limited data on the safety and efficacy of SARS-CoV-2 mRNA vaccines in kidney transplant recipients (KTRs). Methods: We conducted a prospective, multi-center study of 58 adult KTRs receiving mRNA-BNT162b2 or mRNA-1273 vaccines to assess vaccine safety and efficacy. Primary outcome was biopsy-proven rejection within 3 months of vaccination. Secondary outcomes included adverse events, serum creatinine, proteinuria, donor-derived cell-free DNA (ddcfDNA) levels, and antibody and cellular immunity generation against SARSCoV-2. Results: Median age was 62 with 41% females. Median time post-transplantation was 48 months. Only one patient (2%) developed acute cellular rejection though patient had been recently converted to belatacept. There were no severe adverse events or deaths during follow-up. Two patients (3%) developed SARS-CoV-2 infection, one of whom required hospitalization. There was no significant change in serum creatinine, proteinuria or ddcfDNA during the study. Following vaccination, 36%, 25% and 20% of KTRs developed anti-spike, anti-S1 and anti-RBD antibodies. KTRs on mycophenolate-based and steroid-maintenance regimens were less likely to develop an anti-spike antibody response. 100% of KTRs with anti-spike and anti-RBD antibodies had a neutralizing response, compared to 44% in KTRs with anti-spike but without anti-RBD antibodies (RR 2.25, 95% CI 1.08-4.67). There was a significant increase in IFN-gamma spots per 106 PBMCs incubated with S1 peptides following vaccination (p=0.0143). Conclusions: SARS-CoV-2 vaccination in KTRs was safe and associated with the generation of cellular immune response and in a third of patients with anti-spike antibody response. The degree of protection gained by these responses needs to be evaluated in future studies.

Side effects following COVID-19 vaccination: A cross-sectional survey with age-related outcomes in Saudi Arabia

Side effects represent a major determinant of vaccination acceptance. With the newly developed COVID-19 vaccines, there is a growing need for more investigations on vaccination safety, in real practice. With this growing need, the current study investigated the side effects experienced during days 1, 2, and 3 after the first dose of the Oxford—AstraZeneca vaccine among vaccine recipients at King Abdullah bin Abdulaziz University Hospital (KAAUH), Riyadh, Saudi Arabia. A particular emphasis was how age (≤50-year-old versus >50-year-old) affects the frequency and the severity of the side effects. A cross-sectional study was performed using a telephone-based survey. The study involved individuals who received the first dose of the Oxford-AstraZeneca COVID-19 vaccine from February 28 - March 12, 2021, at KAAUH. A total of 528 vaccine recipients were involved, of whom 77.5% were ≤50 years old. The common side effects were myalgia, headache, and fever. Adults aged ≤50 years old showed a higher incidence and intensity of reactions than the >50-year-old group. Areas, where significant differences have been, found included myalgia, headache, fever palpitation, sore throat, and gastrointestinal symptoms (p-value is less than 0.05 for all). The COVID-19 vaccine was safe and well-tolerated. The ≤50-year-old group was more prone to side effects compared to the >50-year-old group. Further studies are needed to more establish such an observation. © 2021. Journal of Advanced Pharmacy Education & Research ;Published by SPER Publication.