COVID-19: Challenges, Preventive Measures and Remediation

This review highlights origin, symptoms, diagnosis, causative agents, mode of transmission and persistence of coronavirus disease (COVID-19) through human activities. In the current scenario researchers, doctors and scientists are striving to combat the transmission of COVID-19 among society. Origin and growth of pandemic has raised the serious concern to address the causative agents, mode of transmission, persistence, preventive measures, diagnosis and possibilities of treatment. The broad-spectrum antiviral antiphrastic, complementary and alternative medicines are currently proposed for possible eradication of the pandemic. The current world is relying on, prevention and control of infection through sanitization and quarantine and onwards waiting for appropriate virucidal agents, sanitizers and strategic vaccination and immunization to combat the pandemic of SARS-CoV-2. Eradication of COVID-19 under stringent guidelines of WHO regarding social practices, intensive care, administration of complementary medicines and innovation of vaccines are under active considerations across the world to combat the pandemic.

Deep CNN based Multi Classification of Respiratory Disease using X-Ray Images

COVID-19 debuted in Wuhan, China on December 19, 2019. In a brief period, deadly virus now migrated to practically every country. To avoid the causative agent COVID-19 disease, governments implement a number of strict restrictions, notably prohibiting people from leaving their homes. This paper focused on detecting and classifying disease such as viral pneu-monia, covidand normal from x-ray images using deep learning methods along with pre-trained models. Moreover, validation accuracy of CNN model attained around 91 % while performing layers in neural network. Several investigations examined that identifying disease of covid reached more accuracy around 98% with hybrid and other algorithms without removing noise from particular images. But this work mainly focused on normalizing images to make the computation very efficient, convergence faster too. © 2022 IEEE.

Thyroid dysfunction as a long-term post-COVID-19 complication in mild-to-moderate COVID-19

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), may lead to thyroid disorders, including both thyrotoxicosis and suppression of thyroid function. The aim of the present study was to assess the post-COVID-19 effects on thyroid function in patients without history of thyroid disease after complete recovery from mild-to-moderate COVID-19. Thyroid function tests [thyroid-stimulating hormone (TSH), free thyroxine (fT4), antithyroid antibodies] were performed on 113 patients (median age of 43.0 years;31.0% male) two months after initial SARS-CoV-2 infection. TSH and fT4 were determined again one month later in this observational, prospective study. Thyroid dysfunction was registered in 61.1% of the patients (78.3% subclinical hypothyroidism, 13% subclinical hyperthyroidism and 8.7% overt hypothyroidism) two months after COVID-19. Moderate rather than mild manifestation of COVID-19 was significantly associated with a higher risk of thyroid dysfunction (OR 5.33;95% CI: 1.70–16.69, p = 0.002), presence of thyroglobulin antibodies and need for levothyroxine therapy. At the follow-up, the subclinical hypothyroidism persisted in 28.3% of the subjects. Moreover, the TSH level was significantly reduced in comparison to the second month after the initial COVID-19 infection in all the patients (p < 0.001), but not in those with subclinical hypothyroidism and without hormone replacement therapy. Our findings indicate that COVID-19 could have long-term, negative effects on thyroid function. Therefore, thyroid function testing should be included in the follow-up algorithm of COVID-19 survivors. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Lactoferrin as a Possible Preventive and Therapeutic Agent Against SARS-CoV-2 Infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of novel coro-navirus disease 2019 (COVID-19), a major cause of atypical pneumonia worldwide. Elderly individuals and those with underlying illnesses, such as cardio-vascular and pulmonary diseases, are at a high risk of experiencing severe symptoms and have high mortality rates. There is therefore a major need to develop additional vaccines, effective treatments, and complementary drugs to control this infection. Lactoferrin (LF), a naturally-occurring glycoprotein, is bioactive against viruses and other pathogens. LF has a unique immunomodulatory function and is indispensable for immunity in infants. It is thought to contribute to biological defense in individuals across all generations, not only infants. LF inhibits viral adhesion to host cell surfaces through ionic binding to glycosaminoglycans and/or specific binding to viral structures. Purified LF is cost-effective and orally available as a dietary sup-plement. Here, we review studies on the protective role of LF against common viral infections. Based on this review, we propose that LF can be a possible prophy-lactic or therapeutic agent for COVID-19 disease. © Fuji Technology Press Ltd.

SARS-CoV-2: Next Generation Sequencing and Analysis

Sars-cov-2 is the causative agent responsible for the global pandemic of COVID-19. Bioinformatics tools are used to sequence the viral genome, identify SARS-CoV-2 from all host genomes, and detect its variants. There is no all-in-one tool that can automatically analyse complete sequences, so different bioinformatics resources are needed to work together for detection and characterisation. This paper discusses the use of next-generation sequencing for virus definition and characterization. © 2022 SPIE. All rights reserved.

Mask-Up: A Face Mask Alert App Using Machine Learning

The COVID-19 pandemic has been a challenge for the past two years, and continues to be so, with the virus showing more mutations with time. The use of face masks in public spaces has been proven to be a precautionary measure to minimize the spread of the Coronavirus, which is the causative agent of the disease. However, enforcing the proper wearing of masks, particularly in environments like schools is a daunting task. This study develops a live video camera application that detects proper wearing of face masks by students in schools using a machine learning algorithm. On detecting an improper mask-wearing face, or a face with no mask, the system displays a red message 'No Mask', while a face with a mask properly worn is flagged with a green message 'Mask'. To enforce the proper wearing of masks, on detecting persons improperly wearing masks, the system automatically sends an alert WhatsApp message to the classroom manager (teacher) to take appropriate action. This application would help ease the workload of teachers who have the task of ensuring a quality teaching and learning environment, at the same time safeguarding the health of learners in this COVID-19 era. © 2022 IST-Africa Institute and Authors.

Analysis of SARS-CoV-2 High Infection Spread in India Based on SIRD Model and Structural Insights

SARS-CoV-2, the causative agent of COVID-19 first emerged in Wuhan, China, in 2019. With antigen drift of the RNA beta-coronavirus, a number of variants have appeared, especially, B.1.617 variant, which rapidly spread throughout India and caused a devastating global pandemic. However, the high infectious mechanism is still under discussion. In this paper, the Susceptible-Infectious-Recovered-Deceased (SIRD) model was used for the analysis of B.1.617 variant in India to estimate its higher infectivity than the wild one. With that in mind, animal contact, social network, technology detection and government deals are raised as important drivers of transmission. Furthermore, the paper also revealed that particular special mutations in B.1.617 variant such as T478K, L452R in the S protein might affect viral fitness [1], making it highly infectious, based on the structural and binding affinity comparison to wild-type and B.1.617 variant with human ACE2. © 2022 ACM.

Bioinformatic Analysis of SARS-CoV-2 S Protein

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is the causative agent of the COVID-19 pandemic possibly originated from an open market in Wuhan, China in December 2019. Multiple variants of SARS-CoV-2 virus have been reported from different regions and this may result in lower efficiency in immune response induced by vaccination. The SARS-CoV-2 spike protein (S protein) facilitates the viral entry into human host cells by binding to human angiotensin converting enzyme 2 (ACE2) receptor protein. A number of nonsynonymous mutations located at various domains of S protein have been reported. Specifically, five mutations which are V367F, G476S, D614G, Q675H and A706V have been identified at receptor binding domain (RBD) and S1-S2 linker region, respectively. The biological consequences of these mutations on the structure and function of the protein remain largely unknown. In this study, these five mutations of S protein are characterized using bioinformatics tools to predict the effect of its structure and function involved in the disease pathogenesis. The mutations involved in these two domains are analyzed with secondary structure prediction analysis, protein structure visualization analysis, protein structure stability analysis and pathogenicity prediction analysis. Our result shows that V367F mutations of S protein may affect the secondary structure while D614G and A706V may affect the protein stability. In addition, V367F and A706V may be deleterious to the structure of S protein whereas Q675H mutation may affect the structure of S protein. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

CoviDefender: Digital Personal Guard for Defending Against COVID19

In late 31 December 2019, a cluster of unexplained pneumonia cases was reported in Wuhan, China [1]. A few days later, the causative agent of this mysterious pneumonia was identified as the new COVID-19 virus. Currently, it has been spreading for more than one and a half years and has lost a huge number of lives all over the world. Most people faced this disaster because of their ignorance, carelessness and lack of updates. By the way most people are in lack of knowledge regarding COVID-19 pandemic, symptoms and what should do to survive from that. Those issues are great problems nowadays. 'CoviDefender' is set to offer a solution to this worldwide COVID-19 pandemic problem. This is a new technological solution from a mobile application. 'CoviDefender' is a Smart Assistant for Defending against COVID-19 Pandemic. This can be described as a solution to the ignorance and carelessness of the people who have been the main cause of the spread of this epidemic. © 2021 IEEE.