Post-COVID-19 Complications and their Laboratory Findings: A Cohort Study.

Type 2 severe acute respiratory syndrome caused by coronavirus infection has become the most well-known pandemic infectious viral disease in the present century. This study aims to find out the post-COVID-19 infection complications via a well-designed observational study. A total of 986 recovered cases (only the period ranged between 2 to 3 months after recovery) were obtained from public and private hospitals in Kirkuk and Erbil governorates\Iraq. The admitted patients were asked to answer a questionnaire through interviews; the laboratory findings were obtained from the patients. The results suggested that approximately half of post-COVID-19 patients (%45.606) were suffering from chest pain, while (%32.357) of the cases suffered headache and chest pain. Liver enzymes (ALT, AST, and ALP) showed abnormal percent values of 38.6,24.07, and 26.09, respectively. Renal function enzymes, mainly urea, were found to be abnormal in 45.37% of recovered individuals. Furthermore, abnormal LDH levels were found in (77.9%) of post-COVID-19 patients. This finding revealed that chest pain was an inflammatory condition and liver and renal enzyme disturbances, while elevation in LDH was the predominant long-term complication in post-COVID-19 patients.

The Role of Immersive Technologies in Urological Simulation

The purpose of simulation is to refine the process of surgical training through valid, reliable, and feasible platforms. Immersive technology describes a spectrum of simulation platforms which balance the physical world on one end and the virtual world on the other. The value of immersive technology in urological simulation has been evidenced by a prolific literature base. This has demonstrated its pedagogic value and cost-efficiency with increasing investments in science and technology in order to advance the models and modalities available to deliver simulation. Urology is a unique specialty, at the forefront of innovative surgical techniques, with a trend towards progressively minimally invasive surgery, featuring a range of laparoscopic, robotic and endoscopic procedures, each associated with a unique learning curve. As a result, it is important to cater the simulation model to the type of urological procedure practiced and the needs of the learner. This chapter also discusses how the implementation of these technologies both in surgical training and in the operating theatre has been accelerated by several historic pressures on surgical training, such as the introduction of the European Working Time Directive and more recently, the COVID-19 pandemic, which exposed deficiencies in existing systems and reiterated the value of virtual platforms. These technologies are beneficial in the formative years of surgical training, aiding the development of technical and non-technical skills as well as in the real-life operative setting, clinical application, enhancing patient treatment and aiding doctor-patient collaboration. Finally, research and innovation consider the potential of immersive technologies to advance surgical practice and techniques by providing an intermediary between laboratory based research and the real world, bypassing some of the ethical concerns associated with conducting research in the context of surgery. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

High-Cited Papers in Global COVID-19 Vaccine Research

Aim and Background: The coronavirus disease 2019 (Covid-19) virus pandemic is still ravaging the world with its ongoing resurgence and the continuous mutation, suggesting the need for continuous research on safe and effective novel vaccines. Presently several types of vaccines have been developed and emerged in the global market to control COVID-19 virus. Consequently, the knowledge and information on COVID-19 have been expanding at a high level. Researchers need to gain relevant knowledge regarding the different vaccines;however scattered information makes this process time-consuming and laborious. The present study aimed to evaluate the characteristics and trends in global COVID-19 vaccine high-cited literature using bibliometric and visualizations methods and offer some directions and suggestions for future research. Methodology: Studies published between December 2019 and 22 Nov 2022 on COVID-19 vaccines were retrieved from the Scopus database. From the 16026 studies retrieved, 406 were identified as high-cited papers (HCPs) having received 100 or more citations. From the 406 HCPs, information about publications outputs, countries, institutions, journals, keywords, and citation counts was identified. Data analysis and visualization were conducted using Microsoft Excel, VOSviewer and Bibliometrix R software. Result(s): The 406 global HCPs on COVID-19 vaccines research were identified in Scopus database since Dec 2019 till 30 Nov 2022 using a search strategy, which received 123614 citations, averaging 304.17 citations per publication (CPP). An external funding was received by 53.20% (216 publications), which were cited 76107 times (with an average of 352.35 CPP). The 7086 authors from 694 organizations affiliated to 76 countries and publishing in 121 journals were involved in global COVID-19 vaccine research. The most productive countries were USA (n=213), U.K (n=91), China (n=36) and Germany (n=35). The most impactful countries in terms of citations per paper (CPP) and relative citation index (RCI) were South Africa (794.68 and 2.61), Germany (507.11 and 1.67), U.K. (396.59 and 1.30) and Spain (367.5 and 1.121). The most productive organizations were University of Oxford, U.K., Imperial College London, U.K. (n=25 each), Center for Disease Control and Prevention (CDC), USA and Tel Aviv University (n=19 each) and the most impactful organizations were University of Cambridge, U.K (783.4 and 2.57), Emory University, USA (780.1 and 2.56), John Hopkins Bloomberg School of Public Health, USA (702.67 and 2.31) and National Institute of Allergy and Infectious Diseases. USA (676.41 and 2.22). The most productive authors were A.J. Pollard (n=16) and T. Lambe (n=14) (of University of Oxford), O. Tureci and P.R. Dormitzer (n=12 each) (of BioNTechSE, Germany) and the most impactful were D. Cooper (1239.22 and 4.07), K.J. Janseu (1228.11 and 4.03) (BioNTechSE, Germany, K.A. Swanson (987.0 and 3.24) (University of Oxford, U.K.) and P.R. Dormitzer (983 and 3.23) (BioNTechSE, Germany). The most productive journals were New England Journal of Medicine (n=53), The Lancet (n=28), Nature (n=22) and JAMA (N=17). The most impactful journals (as per citations per paper) were New England Journal of Medicine (613.15), Lancet (496.39), Human Vaccines and Immunotherapeutics (369.67) and Nature (360.64). Among population age groups, the major focus was on adults (51.48%) and Middle Aged (39.16%). Among publication types, the major focus was Clinical Studies (26.85%), Epidemiology (22.66%) and Genetics (21.92%). The most significant keywords by frequency of appearances were "Covid-19" (n=388), "Covid-19 Vaccines" (n=357), "Vaccination" (n=221), "Prevention and Control" (n=181) and "Vaccine Immunogenicity" (n=133), Conclusion(s): The HCPs in COVID-19 vaccine research was done mainly by the authors and institutions of high-income Countries (HIC) and was published in high-impact medical journals. Our research has identified the leading countries, institutions, journals, hotspots and development trend in the field that could provide the foundati n for further investigations. The bibliometric analysis will help the clinicians to rapidly identify the potential collaborative partners, identify significant studies, and research topics within their domains of COVID-19 vaccines.Copyright Author (s) 2023.

What Will Be the Most Critical Driver of Population Dynamics: Climate Change, the COVID-19 Pandemic, or Both?

The world has already experienced many extreme weather events and the consequences of these events are severe and will become even more severe in scope and intensity. In addition to the risks and crises associated with climate change, the world has also had to deal with the COVID-19 pandemic, resulting in many deaths and socio-economic and psychological consequences. Since both (climate change and pandemics) affect human life in different ways, including population dynamics in terms of fertility, mortality and migration, this study aims to critically review the literature and discuss whether one or both issues will be the most influential driving force. The study also aims to look at the effects on population dynamics by visiting the arguments, results and implications of different studies to understand the diversified effects on society. The examination of the relevant studies shows that the frequency and magnitude of extreme climate events and COVID-19 are spatially different and the impacts of both events are geographically uneven and impose a double burden on humans and their well-being. For example, due to their vulnerability to the adverse effects of climate change and the recent pandemic, poorer countries have a lower adaptive capacity and generally experience difficulties rebuilding and recovering from losses and damages. In addition, the results of the studies included in the assessment indicate that climate change and the COVID-19 pandemic are likely to affect population dynamics—mortality, migration and fertility. Extreme weather events and the recent pandemic may contribute to mortality differences, migration decisions, and fertility intentions, given the experience of weather events and the recent pandemic. Moreover, the effects of climate change and the pandemic are mixed, with either upward or downward trends, or sometimes both, in demographic components. This study argues for serious consideration of these issues as they will affect population dynamics closely linked to socio-economic, cultural, and political issues. There is an urgent need for detailed studies of the inevitable consequences of climate change and the recent pandemic by examining their impact on population dynamics. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Incidence of diabetic ketoacidosis during COVID-19 pandemic: a meta-analysis of 124,597 children with diabetes.

BACKGROUND: Diabetic ketoacidosis (DKA) is a potentially life-threatening complication of type 1 diabetes mellitus (T1DM) that has increased during the COVID-19 pandemic. This study will not only shed light on such life-threatening complications but also be a step to increase the awareness of healthcare providers about such complications in the upcoming pandemic waves and increased dependence on telemedicine. Thus, we aimed to further investigate the increase of DKA in pediatrics. METHODS: PubMed, Web of Science, and Scopus were broadly searched for studies assessing the incidence of DKA in pediatrics during the COVID-19 pandemic. RESULTS: Our study included 24 papers with a total of 124,597 children with diabetes. A statistically significant increase occurred in the risk of DKA among newly diagnosed T1DM patients during the pandemic (RR 1.41; 95% CI 1.19, 1.67; p < 0.01; I2 = 86%), especially in the severe form of DKA (RR 1.66: 95% CI 1.3, 2.11) when compared to before. CONCLUSION: DKA in newly diagnosed children with T1DM has increased during the pandemic and presented with a severe form. This may reflect that COVID-19 may have contributed not only to the development but also the severity of DKA. IMPACT: Diabetic ketoacidosis (DKA) is a life-threatening complication of type 1 diabetes mellitus (T1DM) that has increased during the COVID-19 pandemic. Our study included 25 papers with a total of 124,597 children with diabetes. A statistically significant increase occurred in the risk of DKA among newly diagnosed T1DM patients during the pandemic. Our findings reflect that COVID-19 may have an altered presentation in T1DM and can be related to DKA severity.

Evaluating the Performance of a Commercially Available AI Algorithm for Automated Detection of Pulmonary Embolism on CECT and CTPA of COVID-19 Patients

Objective To investigate the performance of a commercially available artificial intelligence (AI) algorithm for detection of pulmonary embolism (PE) on contrast-enhanced CTs in patients hospitalized for COVID-19. Patients & Methods Retrospective analysis was performed of all contrast-enhanced chest CTs on patients admitted for COVID-19 between March 2020 and December 2021. Based on the original radiology reports, all PE-positive exams were included (n=527). Using a reversed flow single gate diagnostic accuracy case-control model, a randomly selected cohort of PE-negative exams (n=977) was included. Pulmonary parenchymal disease severity was assessed for all included studies using a semi-quantitative system, the Total Severity Score (TSS). All included CTs were sent for interpretation by the commercially available AI algorithm, Aidoc. Discrepancies between AI and original radiology reports were resolved by three blinded radiologists, who rendered a final determination of indeterminate, positive, or negative. Results A total of 78 studies were found to be discrepant, of which 13 (16.6%) were deemed indeterminate by readers and excluded. The sensitivity and specificity of AI was 93.2%;(95% confidence interval [CI] 90.6-95.2%), and 99.6%;(95% CI 98.9-99.9%), respectively. AI's accuracy for all TSS groups (mild, moderate, severe) was high (98.4%, 96.7%, and 97.2%, respectively). AI was more accurate in PE detection on CTPAs vs CECTs (P < .001), with optimal HU of 362 (P=.048). Conclusion The AI algorithm demonstrated high sensitivity, specificity, and accuracy for PE on contrast enhanced CTs in COVID-19 patients regardless of parenchymal disease. Accuracy was significantly affected by the mean attenuation of the pulmonary vasculature. How this affects the legitimacy of the binary outcomes reported by AI is not yet known.

Prevalence of negative mental health status during COVID-19 pandemic among general population of seven Arab countries: A cross-sectional study of 28843 participants

Background: Previous studies documented a narrow scope of knowledge about the negative mental health status during the lockdown following the COVID-19 pandemic, especially in Arab countries. Aim: We aimed to assess the association between negative mental health status and the COVID-19 pandemic and determine the different factors affecting mental health among the general population of seven Arab countries. Methods: This study is a multinational cross-sectional questionnaire-based survey conducted online from June 11, 2020 to June 25, 2020. The depression, anxiety, and stress Scale 21 Items (DASS-21) and the Event scale–Revised Arabic version (IES-R-13) scales were used. Multiple linear regressions were performed to study the association between the scales' total scores with COVID-19 and demographic characteristics. Results: A total of 28,843 participants from seven Arab countries were included. During the COVID-19 pandemic, the prevalence of mental health disorders has significantly increased. A total of 19006 participants (66%) were affected by variable degrees of depression, 13,688 (47%) had anxiety, and 14,374 (50%) had stress ranging from mild to severe. Higher levels were associated with other factors, such as lower age, female gender, chronic disease, unemployed, fear of getting infected, and a history of psychiatric disorders. Conclusion: Our study findings show an increased incidence of mental disorders during the pandemic. This is expected to play a crucial role in guiding a psychological support strategy provided by healthcare systems to the general public during pandemics.

Evaluating the Performance of a Commercially Available Artificial Intelligence Algorithm for Automated Detection of Pulmonary Embolism on Contrast-Enhanced Computed Tomography and Computed Tomography Pulmonary Angiography in Patients With Coronavirus Disease 2019.

Objective: To investigate the performance of a commercially available artificial intelligence (AI) algorithm for the detection of pulmonary embolism (PE) on contrast-enhanced computed tomography (CT) scans in patients hospitalized for coronavirus disease 2019 (COVID-19). Patients and Methods: Retrospective analysis was performed of all contrast-enhanced chest CT scans of patients admitted for COVID-19 between March 1, 2020 and December 31, 2021. Based on the original radiology reports, all PE-positive examinations were included (n=527). Using a reversed-flow single-gate diagnostic accuracy case-control model, a randomly selected cohort of PE-negative examinations (n=977) was included. Pulmonary parenchymal disease severity was assessed for all the included studies using a semiquantitative system, the total severity score. All included CT scans were sent for interpretation by the commercially available AI algorithm, Aidoc. Discrepancies between AI and original radiology reports were resolved by 3 blinded radiologists, who rendered a final determination of indeterminate, positive, or negative. Results: A total of 78 studies were found to be discrepant, of which 13 (16.6%) were deemed indeterminate by readers and were excluded. The sensitivity and specificity of AI were 93.2% (95% CI, 90.6%-95.2%) and 99.6% (95% CI, 98.9%-99.9%), respectively. The accuracy of AI for all total severity score groups (mild, moderate, and severe) was high (98.4%, 96.7%, and 97.2%, respectively). Artificial intelligence was more accurate in PE detection on CT pulmonary angiography scans than on contrast-enhanced CT scans (P<.001), with an optimal Hounsfield unit of 362 (P=.048). Conclusion: The AI algorithm demonstrated high sensitivity, specificity, and accuracy for PE on contrast-enhanced CT scans in patients with COVID-19 regardless of parenchymal disease. Accuracy was significantly affected by the mean attenuation of the pulmonary vasculature. How this affects the legitimacy of the binary outcomes reported by AI is not yet known.

Treating Children with Hcv Close to Home through a Virtual National Multidisciplinary Network

Background and Aims Hepatitis C virus (HCV) infection is a major global health problem in adults & children. The recent efficacy of Direct Acting Anti-viral therapy (DAA) has cure rates of 99% in adults and adolescents. These drugs were licensed for children 3-12 yrs during the recent coronavirus pandemic. To ensure equitable access, safe & convenient supply during lockdown, we established a virtual national treatment pathway for children with HCV in England & evaluated its feasibility, efficacy & treatment outcomes. Method A paediatric Multidisciplinary Team Operational Delivery Network (pMDT ODN), supported by NHS England (NHSE), was established with relevant paediatric specialists to provide a single point of contact for referrals & information. Referral & treatment protocols were agreed for HCV therapy approved by MHRA & EMA. On referral the pMDT ODN agreed the most appropriate DAA therapy based on clinical presentation & patient preferences, including ability to swallow tablets. Treatment was prescribed in association with the local paediatrician & pharmacist, without the need for children & families to travel to national centres. All children were eligible for NHS funded therapy;referral centres were approved by the pMDT ODN to dispense medication;funding was reimbursed via a national NHSE agreement. Demographic & clinical data, treatment outcomes & SVR 12 were collected. Feedback on feasibility & satisfaction on the pathway was sought from referrers. Results In the first 6 months, 34 children were referred;30- England;4 - Wales;median (range) age 10 (3.9 - 14.5) yrs;15M;19F: Most were genotype type 1 (17) & 3 (12);2 (1);4(4). Co-morbidities included: obesity (2);cardiac anomaly (1);Cystic Fibrosis (1);Juvenile Arthritis (1). No child had cirrhosis. DAA therapy prescribed: Harvoni (21);Epclusa (11);Maviret (2) .27/34 could swallow tablets;3/7 received training to swallow tablets;4/7 are awaiting release of granules.11/27 have completed treatment and cleared virus;of these 7/11 to date achieved SVR 12. 30 children requiring DAA granule formulation are awaiting referral and treatment. Referrers found the virtual process easy to access, valuing opportunity to discuss their patient's therapy with the MDT & many found it educational. There were difficulties in providing the medication through the local pharmacy. However there are manufacturing delays in providing granule formulations because suppliers focused on treatments for COVID, leading to delays in referring and treating children unable to swallow tablets. Conclusion The National HCV pMDT ODN delivers high quality treatment & equity of access for children & young people, 3- 18 yrs with HCV in England, ensuring they receive care close to home with 100% cure rates.

Effects of COVID-19 on Pediatric Cancer Care: A Multicenter Study of 11 Middle Eastern Countries.

During the COVID-19 pandemic, major challenges are facing pediatric cancer centers regarding access to cancer centers, continuity of the anti-cancer therapy, hospital admission, and infection protection precautions. Pediatric oncologists actively treating children with cancer from 29 cancer centers at 11 countries were asked to answer a survey from May 2020 to August 2020 either directly or through the internet. COVID-19 pandemic affected the access to pediatric cancer care in the form of difficulty in reaching the center in 22 (75.9%) centers and affection of patients' flow in 21 (72.4%) centers. Health care professionals (HCP) were infected with COVID-19 in 20 (69%) surveyed centers. Eighteen centers (62%) modified the treatment guidelines. Care of follow-up patients was provided in-hospital in 8(27.6%) centers, through telemedicine in 10 (34.5%) centers, and just delayed in 11 (38%) centers. Pediatric oncologists had different expectations about the future effects of COVID-19 on pediatric cancer care. Seventy-six percent of pediatric oncologists think the COVID-19 pandemic will increase the use of telemedicine. Fifty-five percent of pediatric oncologists think if the COVID-19 pandemic persists, we will need to change chemotherapy protocols to less myelosuppressive ones. Collaborative studies are required to prioritize pediatric cancer management during COVID-19 era.

DCBC_DeepL: Detection and Counting of Blood Cells Employing Deep Learning and YOLOv5 Model

Blood cell identification and counting is critical for doctors and physicians nowadays in order to diagnose and treat a variety of disorders. Platelet identification and counting are frequently performed in the context of many types of sickness such as COVID-19 and others. However, it is frequently costly and time intensive. Additionally, it is not widely available. From this vantage point, it is necessary to develop an efficient technical model capable of detecting and counting three fundamental types of blood cells: platelets, red blood cells, and white blood cells. Thus, this study proposes a deep learning-based model based on the YOLOv5 model with a precision of 0.799. The model consists of thre different layers such as backbone, neck and output layer The model is extremely capable of detecting and counting individual blood cells. Doctors, physicians, and other professionals will be able to detect and count blood cells using real-time images. It will significantly minimise the cost and time associated with detecting and counting blood cells by utilizing real-time blood images. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Perspectives toward e-learning system during Covid-19 pandemic among medical Colleagues, Egypt: A Cross-sectional survey (preprint)

Background: WHO declared the outbreak of COVID-19, which affected the educational system stopping it in Egypt. To maintain the educational process, E-learning was a suggested solution. This study aimed to assess students' satisfaction regarding e-learning experience and effectiveness of this system on medical education in Egyptian universities. Methods: A cross-sectional survey was conducted among medical schools in Egypt during 2020–2021. It was conducted through an online questionnaire composed of four sections: Demographic characteristics, quality of internet connection, the academic characteristics of the participants, and evaluation of the effectiveness of e-learning. We compared the effectiveness of e learning among the clinical and the academic students, and private and governmental universities. Results: Among 90592 medical students in Egypt, 6393 students from 28 universities filled out the questionnaire with a 96.6% response rate. The age of participants ranged from 16 to 29 years old. Also, about 59.3% of them were females. The blended e-learning was the most applied by universities (43.1%), followed by partial type (33.4%), and full type (23.6%). About 73.7% of students had "always/often" constant internet connection. Forty percent of students were "dissatisfied/not satisfied at all", 38.3% showed "neutral" satisfaction, while 21.7% were "satisfied or highly satisfied". There was a significant difference regarding internet connection and availability favoring urban areas compared to rural areas (p<0.001). There was a significant difference favoring the academic education over the clinical education regarding the effectiveness of online learning (p<0.01) and private education over governmental regarding the effectiveness of online learning (p<0.001). Conclusion: E-learning was better for academic education than for clinical education. It was better for private universities than governmental ones. Also, students in rural areas had worse availability and quality internet connection compared with those in urban areas.

Attitude and knowledge towards the effectiveness of nucleic acid-based vaccines among healthcare workers and medical students in the Jordanian population

Since the beginning of the COVID-19 pandemic, catastrophic mortality and morbidity rates and unknown long-term ramifications were caused, leading to focused efforts on implementing effective vaccination. Nucleic acid-based vaccines (NBVs), an emergent advance in vaccine development, presented high efficacy rates but controversy regarding this approach soon spread. This study assesses healthcare workers (HCWs) knowledge and attitude towards NBVs' effectiveness. This cross-sectional study was conducted in Jordan from November 2020 to January 2021 through a web-based questionnaire. 320 participants were split into educated and uneducated groups, with the former being exposed to educational material on NBVs before survey completion. The educated group expressed increased concern towards NBVs' side effects. Specifically, the risk of developing cancer due to genetic modification(40.8%), fever(69.4%), skin rash(58.0%), and amyloid deposition(40.8%) showed a significant difference. The educated group preferred RNA-based NBVs over DNA-based ones(43.9%), had double the response rate, provided more scientifically accurate answers, and showed a more positive attitude towards the ability of NBVs to induce cellular immunity (57.3%) and prevent chronic forms of COVID-19(57.3%) (p < 0.05). Because HCWs are the most integral players in shaping public opinion about NBVs, thorough educational material on NBVs needs to be integrated within the curricula of health-related programs to bridge the gap present. This could prove vital in ensuring the success of the current and future vaccination campaigns. Copyright © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

Predictors of cheating in online exams among business students during the Covid pandemic: Testing the theory of planned behavior

Drawing on the theory of planned behavior (TPB) and prior empirical research, this quantitative study aims to identify the main predictors of academic dishonesty in online exams among undergraduate business students during the COVID-19 pandemic in the United Arab Emirates (UAE). Complete data were collected through online questionnaire from 176 undergraduate business students from different UAE universities. Three proposed conceptual models were tested using structural equation modeling analysis (SEM). Results of SEM demonstrate that, in line with the TPB, students' favorable attitude toward cheating, social norms supportive of cheating, and perceived control over the engagement in cheating are the main predictors of cheating intentions in online exams among business students. This study shows that perceived control and cheating intentions are the direct predictors of actual cheating in online exams. The study also demonstrates that attitude toward cheating, social norms supportive of cheating, and perceived control over cheating indirectly influence actual cheating behavior in online exams. The findings of this study can help university administrators and faculty members understand and curb cheating during online exams among business students not only in the context of the continuing COVID-19 pandemic but also in the years ahead.

The Effect of Nitazoxanide on the Clinical Outcomes in Patients with COVID-19: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND AND OBJECTIVE: Nitazoxanide, a US Food and Drug Administration-approved antiparasitic agent, was reported to be effective in treating coronavirus disease 2019 (COVID-19). The lack of effective and precise treatments for COVID-19 infection earlier in the pandemic forced us to depend on symptomatic, empirical, and supportive therapy, which overburdened intensive care units and exhausted hospital resources. Therefore, the aim of this systematic review and meta-analysis was  to assess the efficacy and safety of nitazoxanide for COVID-19 treatment. METHODS: A systematic review and meta-analysis synthesizing relevant randomized controlled trials from six databases (MedRxiv, WOS, SCOPUS, EMBASE, PubMed, and CENTRAL) until 17 May 2022 was conducted. Risk ratio (RR) for dichotomous outcomes was used and data with a 95% confidence interval (CI) are presented. The protocol was registered in PROSPERO with ID: CRD42022334658. RESULTS: Six randomized controlled trials with 1412 patients were included in the analysis. Nitazoxanide was effective in accelerating viral clearance compared with placebo (RR: 1.30 with 95% CI 1.08, 1.56, p = 0.006) and reducing oxygen requirements (RR: 0.48 with 95% CI 0.39, 0.59, p = 0.00001), but we found no difference between nitazoxanide and placebo in improving clinical resolution (RR: 1.01 with 95% CI 0.94, 1.08, p = 0.88), reducing the mortality rate (RR: 0.88 with 95% CI 0.4, 1.91, p = 0.74), and intensive care unit admission (RR: 0.69 with 95% CI 0.43, 1.13, p = 0.14). Moreover, nitazoxanide was as safe as placebo (RR: 0.9 with 95% CI 0.72, 1.12, p = 0.34). CONCLUSIONS: Compared with placebo, nitazoxanide was effective in expediting viral clearance and decreasing oxygen requirements. However, there was no difference between nitazoxanide and placebo regarding clinical response, all-cause mortality, and intensive care unit admission. Therefore, more large-scale studies are still needed to ascertain the clinical applicability of nitazoxanide in COVID-19.

INTERACTIONS OF AEROSOL DROPLETS WITH VENTILATED AIRFLOWS IN THE CONTEXT OF AIRBORNE PATHOGEN TRANSMISSION

This multidisciplinary study provides a comprehensive visualization of airborne aerosols and droplets coming into contact with crossflows of moving air utilizing both experimental particle measuring methods and multiphase computational fluids dynamics (CFD). The aim of this research is to provide a Eulerian visualization of how these crossflows alter the position and density of an aerosol cloud, with the goal of applying this information to our understanding of social distancing ranges within outdoor settings and ventilated rooms. The results indicate that even minor perpendicular crossflows across the trajectory of an aerosol cloud can greatly reduce both the linear displacement and density of the cloud, with negligible increases in density along the flow path. © 2022 American Society of Mechanical Engineers (ASME). All rights reserved.

Knowledge, attitude, and acceptance regarding COVID-19 vaccines in Sudan

Background COVID-19 is a respiratory disease caused by SARS-CoV-2, a new coronavirus discovered in December 2019 in China. COVID-19 symptoms are similar to those of viral flu but may be more severe, these symptoms can be defended by vaccines, the most distributed 6 candidate vaccines are Pfizer, BioNTech, Moderna, Johnson & Johnson/Janssen AstraZeneca, Sinopharm, Sinovac. In Sudan, the virus has rapidly spread in the country, causing a total of 37,138 confirmed cases with 2,776 deaths till July 21, 2021. We are targeting health workers, medical students, and the general public to assess their behavior regarding COVID-19 vaccines in Sudan, recognize the determinants of their behavior, and identify the factors increasing vaccine acceptance among them. Methods We conducted a pretested cross-sectional online survey involving healthcare workers, medical students, and the general population in Sudan in July and August. We collected the data by sending the survey to social media platforms (e.g., Facebook and WhatsApp). The survey was conducted anonymously without identity-related data. We used both convenience sampling and snowball sampling methods as the participants were asked to forward the survey link to their contacts. The sample size was calculated using Slovin's formula and we estimated the sample size to be 400. Results Of our 400 participants, 36.8% (n = 147) were males and 63.2% (n = 253) were females, the mean age of the participants was 24.17 ± 8.07. The overall vaccine acceptance rate was 48.2% (n = 193) and “Occupation” was the only sociodemographic domain significantly associated with vaccine acceptance, showing a higher acceptance rate among health care workers (p = 0.009). “Afraid of unknown side effects” was the most commonly reported barrier to vaccination (p = 0.33). Conclusion The vaccine acceptance rate is low, and public health authorities and the government in Sudan have a heavy mission for implementing successful vaccination programs with high coverage.

Application of Stem Cell Therapy (SCT) to COVID-19: a scientometric assessment of global publications during 2020-21

Objectives: The study makes a bibliometric evaluation of global publications on "Application of Stem Cell Therapy to Covid-19" during 2020-22.

An analysis of medicaid reimbursement trends in pediatric ophthalmology in Arizona: 2015 to 2021

Introduction: A paucity of data exists regarding reimbursement trends in pediatric ophthalmology, especially regarding the consequences of national policy enacted to minimize the COVID-19 pandemic's effect on access to healthcare. The purpose of this study was to evaluate monetary trends for common pediatric ophthalmology procedures among the Arizona Medicaid population, compared to Medicare data. Method(s): Publicly available Arizona Medicaid and Medicare Physician Fee Schedules from 2015-2021 were utilized. Collected data included reimbursement for common procedural and nonprocedural (examination, imaging) billing codes used in pediatric ophthalmology. Data was adjusted for inflation to 2021 dollars. Result(s): From 2015-2020, the inflation-adjusted average Arizona Medicaid and Medicare reimbursement for all procedures decreased by 9% from 2015-2020 (-2% per year) and 12% (-2% per year), respectively. From 2020-2021, average procedural Medicaid reimbursement increased by 11%, while Medicare decreased by 6%. From 2015 to 2020, average nonprocedural Medicaid and Medicare reimbursement decreased by 16% (-3% per year) and 18% (-4% per year), respectively. Average non-procedural Medicaid reimbursement increased by 8% from 2020-2021, while Medicare decreased by 2%. No significant difference was observed between Arizona and national Medicare trends (P > 0.05). Conclusion/Relevance: Arizona Medicaid and Medicare reimbursement steadily decreased from 2015-2020, but Medicaid reimbursement markedly increased from 2020-2021. This reflects a 6.2% increase in federal Medicaid funding to states enacted by Congress in 2020, which will end after the public health emergency. In light of recent decreases in outpatient utilization due to the COVID-19 pandemic, increased awareness of these trends is needed to maintain adequate access to pediatric ophthalmologic care, particularly among Medicaid enrollees. Copyright © 2022

Microbial (viruses, bacteria and fungi) protective personal clothing

This chapter highlights the new approaches to producing personal protective clothing (PPC) as antimicrobial fabrics such as gloves, gowns and face masks. Antimicrobial colorants, either natural or synthetic dyes, are widely employed in textile applications as bifunctional agents. This chapter also focuses on the potent nanometals (metal nanoparticles, MNPs) in the finishing process and their finishing techniques. Furthermore, many studies have reported on the antimicrobial activities of metal nanoparticles and dyes, however their antiviral activity has not been adequately investigated. The COVID-19 pandemic has increased the urgency of studying the antiviral potentiality of those agents in addition to their cytotoxicity and applicability. Moreover, there are many kinds of PPC according to their application that require different finishing techniques. This chapter provides a review of the applicability of antimicrobial and antiviral agents and the modern techniques used in textile finishing processes to achieve the highest antimicrobial and antiviral activities. © 2022 Elsevier Ltd. All rights reserved.