The COVID-19 pandemic is due to infection caused by the novel SARS-CoV-2 virus that impacts the lower respiratory tract. The spectrum of symptoms ranges from asymptomatic infections to mild respiratory symptoms to the lethal form of COVID-19 which is associated with severe pneumonia, acute respiratory distress, and fatality. To address this global crisis, up-to-date information on viral genomics and transcriptomics is crucial for understanding the origins and global dispersion of the virus, providing insights into viral pathogenicity, transmission, and epidemiology, and enabling strategies for therapeutic interventions, drug discovery, and vaccine development. Therefore, this review provides a comprehensive overview of COVID-19 epidemiology, genomic etiology, findings from recent transcriptomic map analysis, viral-human protein interactions, molecular diagnostics, and the current status of vaccine and novel therapeutic intervention development. Moreover, we provide an extensive list of resources that will help the scientific community access numerous types of databases related to SARS-CoV-2 OMICs and approaches to therapeutics related to COVID-19 treatment.

Purpose: With the easing of restriction measures, repeated community-based sampling for tracking new COVID-19 infections is anticipated for the next 6 to 12 months. A non-invasive, self-collected specimen like saliva will be useful for such public health surveillance. Investigations on the use of saliva for SARS-CoV-2 RT-PCR have largely been among COVID-19 in-pa\tients and symptomatic ambulatory patients with limited work in a community-based screening setting. This study was carried out to address this paucity of data and reported discrepancies in diagnostic accuracy for saliva samples. Patients and Methods: From 29th June to 14th July 2020, adults presenting for COVID-19 testing at a community-based screening facility in Dubai, United Arab Emirates were recruited. Clinical data, nasopharyngeal swab in universal transport media and drooling saliva in sterile containers were obtained. Reverse transcriptase PCR amplification of SARS-CoV-2 RdRp and N genes was used to detect the presence of the SARS-CoV-2 virus. Results: Of the 401 participants, 35 (8.7%) had viral detection in at least one specimen type and the majority (n=20/35; 57.1%) were asymptomatic. Both swab and saliva were positive in 19 (54.2%) patients, while 7 (20.0%) patients had swab positive/saliva negative results. There were 9 (25.7%) patients with saliva positive/swab negative result and this included 5 asymptomatic COVID-19 patients undergoing repeat screening. Using the swab as the reference gold standard, the sensitivity and specificity of saliva were 73.1% (95% CI 52.2– 88.4%) and 97.6% (95% CI 95.5– 98.9%) while the positive and negative predictive values were 67.9% (95% CI 51.5– 80.8%) and 98.1% (95% CI 96.5– 99.0%), respectively. Conclusion: The findings suggest good diagnostic accuracy for saliva and feasibility of utilization of specimen without transport media for SARS-CoV-2 RT-PCR. Saliva represents a potential specimen of choice in community settings and population-based screening.

The SEIR (Susceptible-Exposed-Infected-Removed) model is widely used in epidemiology to mathematically model the spread of infectious diseases with incubation periods. However, the SEIR model prototype is generic and not able to capture the unique nature of a novel viral pandemic such as SARS-CoV-2. We have developed and tested a specialized version of the SEIR model, called SEAHIR (Susceptible-Exposed-Asymptomatic-Hospitalized-Isolated-Removed) model. This proposed model is able to capture the unique dynamics of the COVID-19 outbreak including further dividing the Infected compartment into: (1) “Asymptomatic”, (2) “Isolated” and (3) “Hospitalized” to delineate the transmission specifics of each compartment and forecast healthcare requirements. The model also takes into consideration the impact of non-pharmaceutical interventions such as physical distancing and different testing strategies on the number of confirmed cases. We used a publicly available dataset from the United Arab Emirates (UAE) as a case study to optimize the main parameters of the model and benchmarked it against the historical number of cases. The SEAHIR model was used by decision-makers in Dubai’s COVID-19 Command and Control Center to make timely decisions on developing testing strategies, increasing healthcare capacity, and implementing interventions to contain the spread of the virus. The novel six-compartment SEAHIR model could be utilized by decision-makers and researchers in other countries for current or future pandemics.

Purpose: Microbial coinfections in COVID-19 patients carry a risk of poor outcomes. This study aimed to characterize the clinical and microbiological profiles of coinfections in patients with COVID-19. Methods: A retrospective review of the clinical and laboratory records of COVID-19 patients with laboratory-confirmed infections with bacteria, fungi, and viruses was conducted. Only adult COVID-19 patients hospitalized at participating health-care facilities between February 1 and July 31, 2020 were included. Data were collected from the centralized electronic system of Dubai Health Authority hospitals and Sheikh Khalifa General Hospital Umm Al Quwain. Results: Of 29,802 patients hospitalized with COVID-19, 392 (1.3%) had laboratory-confirmed coinfections. The mean age of patients with coinfections was 49.3± 12.5 years, and a majority were male (n=330 of 392, 84.2%). Mean interval to commencement of empirical antibiotics was 1.2± 3.6) days postadmission, with ceftriaxone, azithromycin, and piperacillin–tazobactam the most commonly used. Median interval between admission and first positive culture (mostly from blood, endotracheal aspirates, and urine specimens) was 15 (IQR 8– 25) days. Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli were predominant in first positive cultures, with increased occurrence of Stenotrophomonas maltophilia, methicillin-resistant Staphylococcus aureus, Acinetobacter baumannii, Candida auris, and Candida parapsilosis in subsequent cultures. The top three Gram-positive organisms were Staphylococcus epidermidis, Enterococcus faecalis, and Staphylococcus aureus. There was variability in levels of sensitivity to antibiotics and isolates harboring mecA, ESBL, AmpC, and carbapenemase-resistance genes were prevalent. A total of 130 (33.2%) patients died, predominantly those in the intensive-care unit undergoing mechanical ventilation or extracorporeal membrane oxygenation. Conclusion: Despite the low occurrence of coinfections among patients with COVID-19 in our setting, clinical outcomes remained poor. Predominance of Gram-negative pathogens, emergence of Candida species, and prevalence of isolates harboring drug-resistance genes are of concern.

The advent of long-read sequencing offers a new assessment method of detecting genomic structural variation (SV) in numerous rare genetic diseases. For autism spectrum disorders (ASD) cases where pathogenic variants fail to be found in the protein-coding genic regions along chromosomes, we proposed a scalable workflow to characterize the risk factor of SVs impacting non-coding elements of the genome. We applied whole-genome sequencing on an Emirati family having three children with ASD using long and short-read sequencing technology. A series of analytical pipelines were established to identify a set of SVs with high sensitivity and specificity. At 15-fold coverage, we observed that long-read sequencing technology (987 variants) detected a significantly higher number of SVs when compared to variants detected using short-read technology (509 variants) (p-value < 1.1020 × 10⁻⁵⁷). Further comparison showed 97.9% of long-read sequencing variants were spanning within the 1–100 kb size range (p-value < 9.080 × 10⁻⁶⁷) and impacting over 5000 genes. Moreover, long-read variants detected 604 non-coding RNAs (p-value < 9.02 × 10⁻⁹), comprising 58% microRNA, 31.9% lncRNA, and 9.1% snoRNA. Even at low coverage, long-read sequencing has shown to be a reliable technology in detecting SVs impacting complex elements of the genome.

Background: The evolution of an undergraduate medical student into an adept physician is perpetual, demanding, and stressful. Several studies have indicated medical students have a higher predominance of mental health problems than other student groups of the same age, where medical education acts as a stressor and may lead to unfavorable consequences such as depression, burnout, somatic complaints, decrease in empathy, dismal thoughts about quitting medical school, self harm and suicidal ideation, and poor academic performance. It is imperative to determine the association between important psychoeducational variables and academic performance in the context of medical education to comprehend the response to academic stress. Objective: The aim of this proof-of-concept study is to determine the relationship between resilience, learning approaches, and stress-coping strategies and how they can collectively predict achievement in undergraduate medical students. The following research questions will be addressed: What is the correlation between the psychoeducational variables resilience, learning approaches, and stress-coping strategies? Can academic performance of undergraduate medical students be predicted through the construction of linear relationships between defined variables employing the principles of empirical modeling? Methods: Study population will consist of 234 students registered for the MBBS (Bachelor of Medicine, Bachelor of Surgery) at Mohammed Bin Rashid University of Medicine and Health Sciences distributed over 4 cohorts. Newly registered MBBS students will be excluded from the study. Various psychoeducational variables will be assessed using prevalidated questionnaires. For learning approaches assessment, the Approaches and Study Skills Inventory for Students questionnaire will be employed. Resilience and stress-coping strategies will be evaluated using the Wagnild-Young resilience scale and a coping strategies scale derived from Holahan and Moos’s Coping Strategies Scale, respectively. Independent variables (resilience, stress-coping strategies, and learning approaches) will be calculated. Scores will be tested for normality by using the Shapiro-Wilk test. An interitem correlational matrix of the dependent and independent variables to test pairwise correlation will be formed using Pearson bivariate correlation coefficients. Regression models will be used to answer our questions with type II analyses of variance in tests involving multiple predictors. Regression analyses will be checked for homogeneity of variance (Levine test) and normality of residuals and multicollinearity (variance inflation factor). Statistical significance will be set at 5% (alpha=.05). Effect sizes will be estimated with 95% CIs. Results: Psychoeducational instruments in the form of validated questionnaire have been identified in relation to the objectives. These questionnaires have been formatted for integration into Google forms such that they can be electronically distributed to the consenting participants. We submitted the proposal to MBRU institutional review board (IRB) for which exemption has been awarded (application ID: MBRU-IRB-2019-013). There is no funding in place for this study and no anticipated start date. Total duration of the proposed research is 12 months. Conclusions: Psychoeducational instruments used in this study will correlate resilience, stress-coping strategies, and learning approaches to academic performance of undergradudate medical students. To the best of our knowledge, no study exploring the multidimensional association of key psychoeducational variables and academic performance in undergraduate medical students has been pursued. Investigated variables, resilience, learning approaches, and stress-coping strategies, are individual traits, however; students’ learning history before they joined MBRU is unknown, so our research will not be able to address this specific aspect. International Registered Report Identifier (IRRID): PRR1-10.2196/14677