ABSTRACT
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.
ABSTRACT
This research paper seeks to explore a newly proposed model to assist public educational systems with properly integrating digital technology into their currently practiced teaching and learning processes. Digital learning has been adopted for the past two decades under various forms of internet-based learning, such as online learning, e-learning, blended learning, and hybrid learning. However, those practices and initiatives have encountered many obstacles that crippled educational communities in many parts of the world and prevented them from successfully and sustainably integrating digital learning into their systems. Unfortunately, the crisis of the COVID-19 outbreak has clearly revealed the need for immediate action to find effective methods to ensure the quality implementation of digital learning in K-12 education. Consequently, this paper benefits both individuals and governments with successful and sustainable solutions for K-12 education. This proposed digital education shifting (DES) model was constructed based on several learning theories, mainly the cognitive load theory, constructive learning theory, and connectivism theory. To achieve its objectives, this paper adopts a descriptive method by constructing an open-ended questionnaire to collect experts' opinions and suggestions on DES. The results revealed high agreement among experts on DES effectiveness. © The Author(s) 2023.
ABSTRACT
Covid-19 is a global crisis and the greatest challenge we have faced. It affects people in different ways. Most infected people develop a mild to moderate form of the disease and recover without hospitalization. This presents a problem in spreading the pandemic with unintentionally manner. Thus, this paper provides a new technique for COVID-19 monitoring remotely and in wide range. The system is based on satellite technology that provides a pivotal solution for wireless monitoring. This mission requires a data collection technique which can be based on drones' technology. Therefore, the main objective of our proposal is to develop a mission architecture around satellite technology in order to collect information in wide range, mostly, in areas suffer network coverage. A communication method was developed around a constellation of nanosatellites to cover Saudi Arabia region which is the area of interest in this paper. The new proposed architecture provided an efficient monitoring application discussing the gaps related to thermal imaging data. It reached 15.8 min as mean duration of visibility for the desired area. In total, the system can reach a coverage of 5.8 h/day, allowing to send about 21870 thermal images. © 2023 CRL Publishing. All rights reserved.
ABSTRACT
With the movement of people from the countryside to urban cities, the need to develop services increases as well. The development of services is necessary to accommodate the population growth in terms of transportation, education, and health. Smart cities meet these issues using a comprehensive echo system incorporating smart technologies and enhancing citizens' quality of life. In this paper, we focus on six dimensions of smart cities: living, environment, governance, economy, people, and transportation. In light of these dimensions, we review six smart cities around the world: Dubai, Tokyo, Singapore, Hong Kong, Seoul, and Reykjavik. Moreover, we review Riyadh, Saudi Arabia, as a city aspiring to be fully smart in each dimension. Lastly, we elaborate on the health aspect with regard to the response to the COVID-19 pandemic in all cities under consideration. © 2022 IEEE.
ABSTRACT
Background: MIS-C associated with Covid-19 is characterized by way of persistent fever and is often associated with a stomach ache, vomiting, diarrhea, rash, and conjunctivitis, and other mucocutaneous manifestations. Aim: This work aims to determine the clinical course, safety profile, and inflammatory markers of Multisystem Inflammatory Syndrome in Children (MIS-C) which is associated with Covid-19 children. Methodology: A systematic search was performed over different medical databases to identify Pediatrics studies, which studied the outcome of the MIS-C of Covid-19 children. We conducted a meta-analysis process on the incidence of MIS-C as a primary outcome, and on the estimated level of serum C-Reactive Protein (CRP), ferritin, and D-dimer as secondary outcomes. Six studies were identified involving 1747 children with Covid-19. Our meta-analysis process showed a pooled incidence of MIS-C in Covid-19 children of 39.8%. Concerning the secondary outcome measures, the Fixed-effects model of the meta-analysis process revealed an average estimate CRP level of 223.1 mg/dl, an average estimate ferritin level of 566.5 mg/dl, and an average estimate D-dimer level of 595.6 mg/dl, respectively. Conclusion: To conclude, Covid-19 infection is typically very mild and often asymptomatic in children. Multisystem Inflammatory Syndrome in Children (MIS-C), which is a rare complication associated with Covid-19, presenting after infection as high fever, organ dysfunction, and strongly elevated markers of inflammation.
ABSTRACT
Contactless or non-invasive technology for the monitoring of anomalies in an inconspicuous and distant environment has immense significance in health-related applications, in particular COVID-19 symptoms detection, diagnosis, and monitoring. Contactless methods are crucial specifically during the COVID-19 epidemic as they require the least amount of involvement from infected individuals as well as healthcare personnel. According to recent medical research studies regarding coronavirus, individuals infected with novel COVID-19-Delta variant undergo elevated respiratory rates due to extensive infection in the lungs. This appalling situation demands constant real-time monitoring of respiratory patterns, which can help in avoiding any pernicious circumstances. In this paper, an Ultra-Wideband RADAR sensor x201C;XeThru X4M200x201D;is exploited to capture vital respiratory patterns. In the low and high frequency band, X4M200 operates within the 6.0-8.5 GHz and 7.25-10.20 GHz band, respectively. The experimentation is conducted on six distinct individuals to replicate a realistic scenario of irregular respiratory rates. The data is obtained in the form of spectrograms by carrying out normal (eupnea) and abnormal (tachypnea) respiratory. The collected spectrogram data is trained, validated, and tested using a cutting-edge deep learning technique called Residual Neural Network or ResNet. The trained ResNet modelx2019;s performance is assessed using the confusion matrix, precision, recall, F1-score, and classification accuracy. The unordinary skip connection process of the deep ResNet algorithm significantly reduces the underfitting and overfitting problem, resulting in a classification accuracy rate of up to 90%. IEEE
ABSTRACT
This study aimed to examine the Factor Structure of the teacher satisfaction scale (TSS) with distance education during the Covid-19 pandemic, as well as affirming the (Factorial Invariance) according to gender variable. It also aimed at identifying the degree of satisfaction according to some demographic variables of the sample. The study population consisted of all teachers in public education and faculty members in higher education in the Kingdom of Saudi Arabia. The (TSS) was applied to a random sample representing the study population consisting of (2399) respondents. The results of the study showed that the scale consists of five main factors, with a reliability value of (0.94). The scale also showed a high degree of construct validity through fit indices of the confirmatory factor analysis. The results have shown a gradual consistency of the measure's invariance that reaches the third level (Scalar-invariance) of the Measurement Invariance across the gender variable. The results also showed that the average response of the study sample on the scale reached (3.74) with a degree of satisfaction, as there are no statistically significant differences between the averages of the study sample responses with respect to the gender variable. While there were statistically significant differences in the averages with respect to the variable of the educational level in favor of the middle school and statistically significant differences in the averages attributed to the years of experience variable in favor of those whose experience is less than (5) years.
ABSTRACT
Background: The nearby similarity of the coronaviruses (SARS-CoV, SARS-CoV-2, and MERS-CoV) intimating the possibility of shared immunization. Therefore, this study aimed to assess the differences and similarities between COVID-19 and MERS-CoV: the prospect of co-immunization. Methodology: This study included a cross-sectional random survey that recruited 211 contributors living in the city of Hail, Northern Saudi Arabia, during the period from April 2020 to March 2021. A purposeful electronic questionnaire was deliberated and distributed via various social media sets, regardless of age or gender. Information linked to previous MERS-CoV or COVID19 previous infection was collected. The study population included two groups. Group one: tested for MERS-CoV or COVID19 and found positive. Results: COVID19 and MERS-CoV infections were revealed in 28% and 27% of persons, respectively. Out of the 55 patients infected with MERS-CoV, 24/55(43.6%) were subsequently infected with COVID19. The risk of COVID19 infection associated with previous MERS-Cov infection, Odds Ratio (OR) and 95% confidence interval (95%CI), OR (95%CI) = 2.782(1.436-5.391), P-value = 0.002. Out of 21 persons with a family history of MERS-CoV, 7/21(33%) were subsequently infected with COVID19. Conclusion: Previous MERS-CoV infection does not precludelater COVID19 infection. People with previous MERS-CoV infection are more susceptible to COVID19 infection. Males and older individuals are more susceptible to be infected with COVID19 with severe clinical manifestations.
ABSTRACT
The incessant Coronavirus pandemic has had a detrimental impact on nations across the globe. The essence of this research is to demystify the social media's sentiments regarding Coronavirus. The paper specifically focuses on twitter and extracts the most discussed topics during and after the first wave of the Coronavirus pandemic. The extraction was based on a dataset of English tweets pertinent to COVID-19. The research study focuses on two main periods with the first period starting from March 01,2020 to April 30, 2020 and the second period starting from September 01,2020 to October 31, 2020. The Latent Dirichlet Allocation (LDA) was adopted for topics extraction whereas a lexicon based approach was adopted for sentiment analysis. In regards to implementation, the paper utilized spark platform with Python to enhance speed and efficiency of analyzing and processing large-scale social data. The research findings revealed the appearance of conflicting topics throughout the two Coronavirus pandemic periods. Besides, the expectations and interests of all individuals regarding the various topics were well represented. © 2021. All rights reserved.
ABSTRACT
Background: There has been sizeable speculation regarding the association between the severe Acute breathing Syndrome Coronavirus 2 (SARS-CoV-2) pathogen, coronavirus disorder (COVID-19), and smoking. Aim: This work aims to determine the link between smoking and COVID-19 infection. Materials and Methods: A systematic search was performed over different medical databases to identify Internal Medicine studies, which studied the outcome of the Smokers group versus the Non-Smokers group of COVID-19 patients. Using the meta-analysis process, either with fixed or random-effects models, we conducted a meta-analysis on the prevalence of severe cases as a primary outcome, and on mortality rate as a secondary outcome. Results: Eleven studies were identified involving 146793 patients, 11973 in the Smokers group, and 134820 in the Non-Smokers group. The meta-analysis process revealed that the pooled prevalence of severity among COVID-19 patients was (27.7%), and there is a significant increase in COVID-19 severe cases in the Smokers group compared to the Non-Smokers group (OR=2.11, P=0.032). The pooled mortality rate among COVID-19 patients was (17.2%), and there is a significant increase in mortality in the Smokers group compared to the Non-Smokers group (OR=1.76, P=0.026). Conclusion: To conclude, Patients with any smoking history are vulnerable to severe COVID-19 and worse in-hospital outcomes. In the absence of current targeted therapies, preventative and supportive strategies to reduce morbidity and mortality in current and former smokers are crucial.