Long-term outcomes in COVID-19 patients admitted to intensive care in Denmark: A nationwide observational study.

BACKGROUND: Among ICU patients with COVID-19, it is largely unknown how the overall outcome and resource use have changed with time, different genetic variants, and vaccination status. METHODS: For all Danish ICU patients with COVID-19 from March 10, 2020 to March 31, 2022, we manually retrieved data on demographics, comorbidities, vaccination status, use of life support, length of stay, and vital status from medical records. We compared patients based on the period of admittance and vaccination status and described changes in epidemiology related to the Omicron variant. RESULTS: Among all 2167 ICU patients with COVID-19, 327 were admitted during the first (March 10-19, 2020), 1053 during the second (May 20, 2020 to June 30, 2021) and 787 during the third wave (July 1, 2021 to March 31, 2022). We observed changes over the three waves in age (median 72 vs. 68 vs. 65 years), use of invasive mechanical ventilation (81% vs. 58% vs. 51%), renal replacement therapy (26% vs. 13% vs. 12%), extracorporeal membrane oxygenation (7% vs. 3% vs. 2%), duration of invasive mechanical ventilation (median 13 vs. 13 vs. 9 days) and ICU length of stay (median 13 vs. 10 vs. 7 days). Despite these changes, 90-day mortality remained constant (36% vs. 35% vs. 33%). Vaccination rates among ICU patients were 42% as compared to 80% in society. Unvaccinated versus vaccinated patients were younger (median 57 vs. 73 years), had less comorbidity (50% vs. 78%), and had lower 90-day mortality (29% vs. 51%). Patient characteristics changed significantly after the Omicron variant became dominant including a decrease in the use of COVID-specific pharmacological agents from 95% to 69%. CONCLUSIONS: In Danish ICUs, the use of life support declined, while mortality seemed unchanged throughout the three waves of COVID-19. Vaccination rates were lower among ICU patients than in society, but the selected group of vaccinated patients admitted to the ICU still had very severe disease courses. When the Omicron variant became dominant a lower fraction of SARS-CoV-2 positive patients received COVID treatment indicating other causes for ICU admission.

Covid-19 Vaccines and mRNA Technology: Not as New as Many Believe

When the mRNA COVID-19 vaccines were announced in December 2020 the world was excited that a vaccine was available to combat the coronavirus pandemic. One of the most frequent comments was a desire to wait because the vaccine technology was "so new.” This article will concentrate on the mRNA vaccines not familiar to the public and is intended to explain the developmental timeline before and after the genome of COVID-19 was announced. We discuss Operation Warp Speed and SARS-CoV-2 and specifically the development of Messenger RNA (mRNA) vaccines and concurrent other types of vaccines. Other topics of discussion include COVID-19 variants;effectiveness of mRNA vaccines;and late news about the Pfizer-BioNTech COVID-19 vaccine. The article conclusion discusses implications for nurses as they continue to follow future developments, become competent in communicating viral epidemiology, and educate patients and families about vaccine options © 2022,Online Journal of Issues in Nursing. All Rights Reserved.

Covid-19 variants: Impact on transmissibility and virulence

The genetic evolution of SARS-CoV-2 began in February 2020, with G614 spike protein strains superseding D614 strains globally. Since then with each subsequent mutations, the SARS-CoV-2 variants of concern, namely Alpha, Beta, Gamma, Delta and Omicron, superseded the previous one to become the dominant strain during the pandemic. By the end of November 2022, the Omicron variant and its descendent lineages account for 99.9% of sequences reported globally. All five VOCs have mutations located in the RBD of the spike protein, resulting in increased affinity of the spike protein to the ACE2 receptors resulting in enhanced viral attachment and its subsequent entry into the host cells. In vitro studies showed the mutations in spike protein help increase the viral fitness, enhancing both transmissibility and replication. In general, Alpha, Beta, Gamma, and Delta variants, were reported with higher transmissibility of 43-90%, around 50%, 170-240%, or 130-170% than their co-circulating VOCs, respectively. The Omicron however was found to be 2.38 times and 3.20 times more transmissible than Delta among the fully-vaccinated and booster-vaccinated households. Even the SARS-Cov-2 Omicron subvariants appear to be inherently more transmissible than the ones before. With the broader distribution, enhanced evasion, and improved transmissibility, SARS-CoV-2 variants infection cause severe diseases due to immune escape from host immunity and faster replication. Reports have shown that each subsequent VOC, except Omicron, cause increased disease severity compared with those infected with other circulating variants. The Omicron variant infection however, appears to be largely associated with a lower risk of hospitalisation, ICU admission, mechanical ventilation, and even a shorter length of hospital stay. It has been shown that the relatively much slower replication of the Omicron variants in the lung, resulted in a less severe disease.Copyright © 2022, Malaysian Society of Pathologists. All rights reserved.

Forecasting Omicron Variant of Covid-19 with ANN Model in European Countries – Number of Cases, Deaths, and ICU Patients

Accurate predictions of time series are increasingly required to support judgments in a variety of decisions. Several predictive models are available to support these predictions, depending on how each field offers a data variety with varied behavior. The use of artificial neural networks (ANN) at the beginning of the COVID-19 pandemic was significant since the tool may offer forecasting data for various conditions and hence assist in governing critical choices. In this context, this paper describes a system for predicting the daily number of cases, fatalities, and Intensive Care Unit (ICU) patients for the next 28 days in five European countries: Portugal, the United Kingdom, France, Italy, and Germany. The database selection is based on comparable mitigation processes to analyze the impact of safety procedure flexibilization with the most recent numbers of COVID-19. Additionally, it is intended to check the algorithm's adaptability to different variants throughout time. The network's input data has been normalized to account for the size of the countries in the study and smoothed by seven days. The mean absolute error (MAE) was employed as a comparing criterion of two datasets, one with data from the beginning of the pandemic and another with data from the last year, since all variables (cases, deaths, and ICU patients) may be tendentious in percentage analysis. The best architecture produced a general MAE prediction for the 28 days ahead of 256,53 daily cases, 0,59 daily deaths, and 1,63 ICU patients, all numbers normalized by million people. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Vaccination and variants: A COVID-19 multi-strain model evolution for the Philippines

Coronavirus disease 2019 (COVID-19) management and response is a challenging task due to the uncertainty and complexity of the nature surrounding the virus. In particular, the emergence of new variants and the polarizing response from the populace complicate government efforts to control the pandemic. In this study, we developed a compartmental model that includes (1) a vaccinated compartment, (2) reinfection after a particular time, and (3) COVID-19 variants dominant in the Philippines. Furthermore, we incorporated stochastic terms to capture uncertainty brought about by the further evolution of the new variants and changing control measures via parametric perturbation. Results show the importance of booster shots that increase the vaccine-induced immunity duration. Without booster shots, simulations showed that the dominant strain would still cause significant infection until 31 December 2023. Moreover, our stochastic model output showed significant variability in this case, implying greater uncertainty with future predictions. All these adverse effects, fortunately, can be effectively countered by increasing the vaccine-induced immunity duration that can be done through booster shots. Copyright © 2023 Campos, Raza, Arcede, Martinez and Caga-anan.

Evaluation of Variants and the Effect of Vaccine on Mortality in Pregnant and Postpartum Women Infected with COVID-19

Objective: Due to the anatomical, physiological, and immunological changes associated with pregnancy, pregnant women are a population at risk of coronavirus disease-2019 (COVID-19) disease-related morbidity and mortality. There aren't enough studies on the conditions of pregnant and puerperal women who are being followed up in intensive care. The goal of this study was to determine if there was a link between variant status, vaccination status, and mortality in pregnant and puerperal women who were monitored in the intensive care unit during the transition from the alpha to the delta variation. Materials and Methods: The study was designed as a 6-month prospective observational study that occurred between August 1, 2021, and February 1, 2022. Age, present comorbidities, vaccination status, gravida, parity, gestational age (for pregnant women), variant status, birth style (cesarean section or normal delivery), and COVID-19 medical therapies in the critical care unit were all recorded. Results: During the observation period, forty patients were enrolled in the study. The patients average age was 30.9±5.2. The pregnant patients' median gestational week was 32 weeks and 2 days. While 30 of the patients had no concomitant conditions, two had gestational diabetes, four had hypothyroidism, three had chronic hypertension, and one had Wilson's disease. In 37.5% of the patients, intubation was required. During the follow-up in intensive care, ten individuals died. The patients in the intensive care unit spent an average of 12.1±11.8 days there. While 7 (19.4%) of the 36 patients with alpha variants died, 3 (75%) of the 4 patients with delta variants died, a statistically significant difference (p=0.042). Conclusion: In the pregnant population admitted to the intensive care unit, the delta variant was associated with a greater mortality rate. In our research, we discovered that the vaccination rate among pregnant women admitted to the intensive care unit was quite low. (English) [ FROM AUTHOR] Amaç: Gebelikle ilişkili anatomik, fizyolojik ve immünolojik değişiklikler nedeniyle gebeler koronavirüs hastalığı-2019'a (COVÍD-19) bağlı morbidite ve mortalite açısından risk altındaki popülasyonlardan biridir. Yoğun bakımda takip edilen gebe ve lohusa kadınların durumları ile ilgili yeterli çalışma bulunmamaktadır. Bu çalışmanın amacı, toplumda alfa varyasyonundan delta varyasyonuna geçiş sırasında yoğun bakım ünitesinde izlenen hamile ve lohusa kadınlarda varyant durumu, aşı durumu ve mortalite arasında bir bağlantı olup olmadığını görmekti. Gereç ve Yöntem: Çalışma 1 Ağustos 2021 ile 1 Şubat 2022 tarihleri arasında gerçekleştirilen 6 aylık prospektif gözlemsel bir çalışma olarak tasarlandı. Yaş, mevcut komorbiditeler, aşılanma durumu, gravida, parite, gebelik haftası (hamileler için), varyant durumu, doğum şekli (sezaryen veya normal doğum) ve yoğun bakım ünitesindeki COVÍD-19 tıbbi tedavilerinin tümü kaydedildi. Bulgular: Gözlem süresi boyunca, çalışmaya kırk hasta alındı. Hastaların yaş ortalaması 30,9±5,2 idi. Gebe hastaların medyan gebelik haftası 32 hafta 2 gündü. Hastaların 30'unda eşlik eden hastalık bulunmazken, ikisinde gestasyonel diyabet, dördünde hipotiroidi, üçünde kronik hipertansiyon ve birinde Wilson hastalığı vardı. Hastaların %37,5'inde entübasyon gerekti. Yoğun bakımda yapılan takipte on hasta hayatını kaybetti. Yoğun bakım yatış süresi burada ortalama 12,1±11,8 gün olarak tespit edildi. Alfa varyantı olan 36 hastanın 7'si (%19,4), delta varyantı olan 4 hastanın 3'ü (%75) mortaliteyle sonuçlandı ve aradaki fark istatistiksel olarak anlamlıydı (p=0,042). Sonuç: Yoğun bakım ünitesine kabul edilen gebe popülasyonda delta varyantı daha yüksek bir ölüm oranı ile ilişkilendirilmiştir. Araştırmamızda yoğun bakım ünitesine kabul edilen gebelerde aşılanma oranının oldukça düşük olduğunu tespit ettik. (Turkish) [ FROM AUTHOR] Copyright of Turkish Journal of Intensive Care is the property of Galenos Yayinevi Tic. LTD. STI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Identifying promising druggable binding sites and their flexibility to target the receptor-binding domain of SARS-CoV-2 spike protein.

The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for viral infection. The interaction of its receptor-binding domain (RBD) with the human angiotensin-converting enzyme 2 (ACE2) protein is required for the virus to enter the host cell. We identified RBD binding sites to block its function with inhibitors by combining the protein structural flexibility with machine learning analysis. Molecular dynamics simulations were performed on unbound or ACE2-bound RBD conformations. Pockets estimation, tracking and druggability prediction were performed on a large sample of simulated RBD conformations. Recurrent druggable binding sites and their key residues were identified by clustering pockets based on their residue similarity. This protocol successfully identified three druggable sites and their key residues, aiming to target with inhibitors for preventing ACE2 interaction. One site features key residues for direct ACE2 interaction, highlighted using energetic computations, but can be affected by several mutations of the variants of concern. Two highly druggable sites, located between the spike protein monomers interface are promising. One weakly impacted by only one Omicron mutation, could contribute to stabilizing the spike protein in its closed state. The other, currently not affected by mutations, could avoid the activation of the spike protein trimer.

A comparison of transmissibility of SARS-CoV-2 variants of concern.

BACKGROUND: The World Health Organization (WHO) has currently detected five Variants of Concern of SARS-CoV-2 having the WHO labels of 'Alpha', 'Beta', 'Gamma', 'Delta' and 'Omicron'. We aimed to assess and compare the transmissibility of the five VOCs in terms of basic reproduction number, time-varying reproduction number and growth rate. METHODS: Publicly available data on the number of analyzed sequences over two-week windows for each country were extracted from covariants.org and GISAID initiative database. The ten countries which reported the highest number of analyzed sequences for each of the five variants were included in the final dataset and was analyzed using R language. The epidemic curves for each variant were estimated utilizing the two-weekly discretized incidence data using local regression (LOESS) models. The basic reproduction number was estimated with the exponential growth rate method. The time-varying reproduction number was calculated for the estimated epidemic curves by the ratio of the number of new infections generated at time step t to the total infectiousness of infected individuals at time t, using the EpiEstim package. RESULTS: The highest R0 for the variants Alpha (1.22), Beta (1.19), Gamma (1.21), Delta (1.38) and Omicron (1.90) were reported from Japan, Belgium, the United States, France and South Africa, respectively. Nine out of ten epidemic curves with the highest estimated growth rates and reproduction numbers were due to the Omicron variant indicating the highest transmissibility. CONCLUSIONS: The transmissibility was highest in the Omicron variant followed by Delta, Alpha, Gamma and Beta respectively.

Assessment of GO-Based Protein Interaction Affinities in the Large-Scale Human-Coronavirus Family Interactome.

SARS-CoV-2 is a novel coronavirus that replicates itself via interacting with the host proteins. As a result, identifying virus and host protein-protein interactions could help researchers better understand the virus disease transmission behavior and identify possible COVID-19 drugs. The International Committee on Virus Taxonomy has determined that nCoV is genetically 89% compared to the SARS-CoV epidemic in 2003. This paper focuses on assessing the host-pathogen protein interaction affinity of the coronavirus family, having 44 different variants. In light of these considerations, a GO-semantic scoring function is provided based on Gene Ontology (GO) graphs for determining the binding affinity of any two proteins at the organism level. Based on the availability of the GO annotation of the proteins, 11 viral variants, viz., SARS-CoV-2, SARS, MERS, Bat coronavirus HKU3, Bat coronavirus Rp3/2004, Bat coronavirus HKU5, Murine coronavirus, Bovine coronavirus, Rat coronavirus, Bat coronavirus HKU4, Bat coronavirus 133/2005, are considered from 44 viral variants. The fuzzy scoring function of the entire host-pathogen network has been processed with ~180 million potential interactions generated from 19,281 host proteins and around 242 viral proteins. ~4.5 million potential level one host-pathogen interactions are computed based on the estimated interaction affinity threshold. The resulting host-pathogen interactome is also validated with state-of-the-art experimental networks. The study has also been extended further toward the drug-repurposing study by analyzing the FDA-listed COVID drugs.

Identifying a more severe emergent COVID-19 variant using Emergency Departments' routinely collected clinical measures.

Objective: To determine whether a clinical scoring system (the mPRIEST score) could be used to identify an emerging coronavirus disease 2019 (COVID-19) variant with increased clinical severity. Design: Cross sectional study comparing two time periods (Delta and Omicron waves). Setting: Public Emergency Departments in Northern Sydney Local Health District. Participants: Patients presenting during August 2021 (Delta wave) and January 2022 (Omicron wave) with confirmed COVID-19. Data on age, gender, temperature, heart rate, systolic blood pressure, respiratory rate, oxygen saturation and mental status were extracted from patients' electronic medical records to assess clinical disease severity at presentation. Main outcome measures: Modified Pandemic Respiratory Infection Emergency System Triage (mPRIEST) score calculated using routinely collected data. Results: A sample of 262 records of COVID-19 positive patients presenting during the Delta and initial Omicron waves were reviewed with 205 having COVID-19 as their primary diagnosis. During the Delta wave 48.1% had scores above 4 compared to 35.1% for the Omicron wave (p = 0.03). The median score was also significantly higher for the Delta group (4 vs 3; p = 0.01). Hospitalisations, admissions to ICU and deaths during admission were higher among patients presenting during the Delta wave than among those presenting during the Omicron wave. Conclusion: The mPRIEST score was significantly higher for patients for whom the predominant circulating variant was Delta than those for whom the predominant circulating variant was Omicron. This finding is consistent with international reporting of severity measured by hospital admission data and demonstrates the score's possible ability to identify an emergent strain with higher morbidity and mortality.

Cyclophilin A-mediated mitigation of coronavirus SARS-CoV-2.

Human cyclophilin A (hCypA) is important for the replication of multiple coronaviruses (CoVs), and cyclosporine A inhibitors can suppress CoVs. The emergence of rapidly spreading severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants has sparked concerns that mutations affect the binding ability of the spike (S) protein to the angiotensin-converting enzyme 2 (ACE2) cell receptor, affecting the severity of coronavirus disease (COVID-19). Far-western blotting and surface plasmon resonance (SPR) results revealed that hCypA interacts strongly with the viral SARS-CoV-2 receptor-binding domain (RBD), with a binding affinity of 6.85 × 10-8 M. The molecular interaction between hCypA and the viral protein interface was shown using three-dimensional structural analysis, which revealed the blocking of key residues on the RBD interface by hCypA. The RBD facilitates binding to the ACE2 receptor. The hCypA-S protein complex suppressed the binding of RBD to the ACE2 receptor, which a required event for CoV entry into the host cell. The reliability of this postulated blocking mechanism of the hCypA-SARS-CoV2 RBD complex with ACE was confirmed by SPR and molecular interaction lateral flow (MILF) strip assay, which offers the immunochromatographic signal read-outs. The emergence of new SARS-CoV-2 variants with key mutations in RBD had a negligible effect on the binding of the RBD variants to hCypA, indicating an effective mitigation strategy for SARS-CoV-2 variants. The MILF strip assay results also highlight the neutralizing effect of hCypA by effectively blocking RBD (wild type and its variants) from binding ACE2. Given the importance of hCypA in viral entry regulation, it has the potential to be used as a target for antiviral therapy.

Classifications of COVID-19 Variants Using Rough Set Theory

Since January 2020, the corona epidemic has created havoc worldwide. Although this virus has been mutated many times, the recent variant is more fatal for humans. Increasing active and death cases in the globe as well as in our country affect the psychological well-being of the people. India has experienced all variants including Alpha variant (B.1.1.7), Delta variant (B.1.617.2), and Omicron variant (B.1.1.529). All variants have some common symptoms along with extended symptoms. In this paper, we propose a rule base to classify and predict the variants of COVID-19 using a rough set approach. Our approach works for the elimination of redundant symptoms to create effective reduct, core, and selection of important symptoms to maintain the accuracy in a rule base. Our rules are validated to computer-generated data with 90% accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Blockchain based integrity assurance framework for COVID-19 information management & decision making at National Command Operation Center, Pakistan

The uncontrollable spread of contagious disease COVID-19 is a perennial threat to mankind and has resulted in an unprecedented lockdowns in several countries including Pakistan which in turn has caused an adverse socio-economic impact to all industries. The strategic leadership and concerned state authorities are trying hard to combat and control the spread of COVID-19 pandemic. The effective use of Information Management & Decision Support (IMDS) System can play significant role in combating pandemic and its spread, managing relief actions effectively, accessing vulnerable communities to roll out targeted subsidies by ensuring the coordinated effort and subsequent implementation. Reliable information is significantly critical to assist government and public health agencies in determining the best way forward to control this global health emergency. Therefore, this paper aims to strengthen capacity of IMDS System used by government institutions and authorities for decision making and information dissemination. In this research work, we addressed the integrity-based issues that include completeness, correctness, and freshness of data by proposing a block chain-based integrity protection mechanism. The proposed novel framework is a cascaded formulation of Integrity Assurance (IA) Protocol, Cryptographic Merkle Hash Tree, Digital Signature, and Blockchain. Beside cascaded formulation, two (2) schemes for MHT Generation are also presented in the framework. The proposed framework ensures fairness, completeness, and correctness of data that will be very helpful for secure data management, integration, and utilization in analysis for decision-making. The proposed framework achieved an accuracy of more than 98.09% with better quantitative performance in standard evaluation parameters. © 2023 John Wiley & Sons, Ltd.

Classifications of COVID-19 Variants Using Rough Set Theory

Since January 2020, the corona epidemic has created havoc worldwide. Although this virus has been mutated many times, the recent variant is more fatal for humans. Increasing active and death cases in the globe as well as in our country affect the psychological well-being of the people. India has experienced all variants including Alpha variant (B.1.1.7), Delta variant (B.1.617.2), and Omicron variant (B.1.1.529). All variants have some common symptoms along with extended symptoms. In this paper, we propose a rule base to classify and predict the variants of COVID-19 using a rough set approach. Our approach works for the elimination of redundant symptoms to create effective reduct, core, and selection of important symptoms to maintain the accuracy in a rule base. Our rules are validated to computer-generated data with 90% accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Covid-19 variants: Impact on transmissibility and virulence

The genetic evolution of SARS-CoV-2 began in February 2020, with G614 spike protein strains superseding D614 strains globally. Since then with each subsequent mutations, the SARS-CoV-2 variants of concern, namely Alpha, Beta, Gamma, Delta and Omicron, superseded the previous one to become the dominant strain during the pandemic. By the end of November 2022, the Omicron variant and its descendent lineages account for 99.9% of sequences reported globally. All five VOCs have mutations located in the RBD of the spike protein, resulting in increased affinity of the spike protein to the ACE2 receptors resulting in enhanced viral attachment and its subsequent entry into the host cells. In vitro studies showed the mutations in spike protein help increase the viral fitness, enhancing both transmissibility and replication. In general, Alpha, Beta, Gamma, and Delta variants, were reported with higher transmissibility of 43-90%, around 50%, 170-240%, or 130-170% than their co-circulating VOCs, respectively. The Omicron however was found to be 2.38 times and 3.20 times more transmissible than Delta among the fully-vaccinated and booster-vaccinated households. Even the SARS-Cov-2 Omicron subvariants appear to be inherently more transmissible than the ones before. With the broader distribution, enhanced evasion, and improved transmissibility, SARS-CoV-2 variants infection cause severe diseases due to immune escape from host immunity and faster replication. Reports have shown that each subsequent VOC, except Omicron, cause increased disease severity compared with those infected with other circulating variants. The Omicron variant infection however, appears to be largely associated with a lower risk of hospitalisation, ICU admission, mechanical ventilation, and even a shorter length of hospital stay. It has been shown that the relatively much slower replication of the Omicron variants in the lung, resulted in a less severe disease. Copyright © 2022, Malaysian Society of Pathologists. All rights reserved.

Nucleic acid testing of SARS-CoV-2: A review of current methods, challenges, and prospects.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has brought a huge threat to public health and the global economy. Rapid identification and isolation of SARS-CoV-2-infected individuals are regarded as one of the most effective measures to control the pandemic. Because of its high sensitivity and specificity, nucleic acid testing has become the major method of SARS-CoV-2 detection. A deep understanding of different diagnosis methods for COVID-19 could help researchers make an optimal choice in detecting COVID-19 at different symptom stages. In this review, we summarize and evaluate the latest developments in current nucleic acid detection methods for SARS-CoV-2. In particular, we discuss biosensors and CRISPR-based diagnostic systems and their characteristics and challenges. Furthermore, the emerging COVID-19 variants and their impact on SARS-CoV-2 diagnosis are systematically introduced and discussed. Considering the disease dynamics, we also recommend optional diagnostic tests for different symptom stages. From sample preparation to results readout, we conclude by pointing out the pain points and future directions of COVID-19 detection.

Does Fear of COVID-19 Prolongation Lead to Future Career Anxiety Among Adolescents? The Mediating Role of Depressive Symptoms.

The outbreak of the COVID-19 pandemic has influenced the lives of individuals from all different age groups. In particular, the prolongation of COVID-19 and the emergence of virus variants, such as Omicron, Delta and Alpha, have caused trauma to university students amid expectations that the associated economic, social, and psychological outcomes could affect their future careers. The current study, therefore, examines how the fear of COVID-19 prolongation may affect future career anxiety (FCA) among adolescents and to what extent depressive symptoms may determine such a relationship. Using a cross-sectional design, a survey was conducted to assess depressive symptoms, FCA, and fear of COVID-19 prolongation among 605 university students in Oman, an Arabic-speaking country located in the Gulf region. Using structural equation modeling, the results showed that there were significant standardized direct effects (unmediated) of fear of COVID-19 on depression from COVID-19 and of depression from COVID-19 on FCA. Additionally, depression from COVID-19 mediated the relationship between fear of COVID-19 and FCA. The results are discussed within the Omani context of mental health service accessibility challenges and the dominant culture of perceiving mental health services with social stigma. Supplementary Information: The online version contains supplementary material available at 10.1007/s40653-022-00506-w.

Rapid Conductometric Detection of SARS-CoV-2 Proteins and Its Variants Using Molecularly Imprinted Polymer Nanoparticles.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) biosensors have captured more attention than the conventional methodologies for SARS-CoV-2 detection due to having cost-effective platforms and fast detection. However, these reported SARS-CoV-2 biosensors suffer from drawbacks including issues in detection sensitivity, degradation of biomaterials on the sensor's surface, and incapability to reuse the biosensors. To overcome these shortcomings, molecularly imprinted polymer nanoparticles (nanoMIPs) incorporated conductometric biosensor for highly accurate, rapid, and selective detection of two model SARS-CoV-2 proteins: (i) receptor binding domain (RBD) of the spike (S) glycoprotein and (ii) full length trimeric spike protein are introduced. In addition, these biosensors successfully responded to several other SARS-CoV-2 RBD spike protein variants including Alpha, Beta, Gamma, and Delta. Our conductometric biosensor selectively detects the two model proteins and SARS-CoV-2 RBD spike protein variant samples in real-time with sensitivity to a detection limit of 7 pg mL-1 within 10 min of sample incubation. A battery-free, wireless near-field communication (NFC) interface is incorporated with the biosensor for fast and contactless detection of SARS-CoV-2 variants. The smartphone enabled real-time detection and on-screen rapid result for SARS-CoV-2 variants can curve the outbreak due to its ability to alert the user to infection in real time.

Modeling recurrence of COVID-19 and its variants using recurrent neural network

Coronavirus disease 19 (COVID-19), a disease caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), began as the flu and gradually developed into a highly infectious global pandemic leading to the death of over 6 million people in about 200 countries of the world. Its pathogenic nature has qualified it as a deadly disease, causing moderate and severe respiratory difficulty in infected individuals with the ability to mutate into different variants of the first version. As a result, different government agencies and health institutions have sought solutions within and outside the clinical space. This paper models COVID-19 possible recurrence as variants and predicts that the subsequent waves will be more severe than the first wave. Long short-term memory network (LSTM) was used to predict the future occurrence of COVID-19 and forecast the virus's pattern. Machine evaluation was performed using precision, recall, F1-score, an area under the curve (AUC), and accuracy evaluation metrics. Datasets obtained were used to test the data. The collected characteristics were passed on to the system classification network, demonstrating the function's value based on the system's accuracy. The results showed that the COVID-19 variants have a higher disastrous effect within three months after the first wave. © 2023, Institute of Advanced Engineering and Science. All rights reserved.

Conversations With Individuals on the Fence about CV-19 Vaccination: Analysis of Lives Saved by Vaccine vs. Natural Infection Mortality and Other Reflections.

As of June 15, 2021, from 672,000 to 912,000 deaths have been averted through vaccination of 48% of the US population. Because 52% remain unvaccinated, 728,000 to 988,000 lives remain at risk. These deaths can be spared, and the pandemic stopped in its tracks provided a final national vaccination rate of 84% is achieved. We aim to demonstrate in our analysis the number of lives saved that can be attributed to CV-19 vaccination vs the mortality rate of natural infection seen in unvaccinated individuals. However, time is short given the recent exponential rise of the highly contagious SARS-CoV-2 Delta variant. Delta infection results in a thousand-fold increase in viral load and a transmissibility 2.25x that of the original SARS-CoV-2 strain. Predominance of the Delta variant has already resulted in Covid-19 surges in area with low vaccination rates. An aggressive and timely vaccination campaign is being attempted. We hope our analysis helps convince individuals 'on the fence' that vaccination is essential if the pandemic is to be ended in the United States.