COVID-19 Pandemic: Current Scenario, Challenges and Future Perspectives

Background: The new public health emergency of COVID-19 caused by a novel Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which originated in Wuhan, Hubei province, China in December 2019, evolved into a pandemic in no time and is still in progression. The novel virus mainly targets the lower respiratory system, leading to viral pneumonia, with other associated complications of multi organ failure. Discussion(s): The bats, in particular Rhinolophus affinis, is a natural host of SARS-CoV-2 and the virus is considered to have spread to humans through yet controversial intermediate host pangolins. The incubation period ranges from 2-14 days and mode of person-to-person transmission is primari-ly via the direct contact with the infected person or through the droplets generated by the infected person during coughing or sneezing. The initiation of the infection process by SARS-CoV-2 virus is the invasion of lung type II alveolar cells via a receptor protein called angiotensin-converting enzyme 2 (ACE2) present on the cell membrane with glycosylated spike (S) viral protein that medi-ates host cell invasion. The main diagnostic tools employed are molecular methods based on nucleic acid detection engaging real-time quantitative polymerase chain reaction (RT-qPCR) and a new immunoassays based on antibodies IgM/IgG. Conclusion(s): Due to the lack of specific clinically approved anticovid-19 drugs or vaccines that could be used for its prevention or treatment, the current management approach is essentially sup-portive and symptomatic. The precautionary measures like, social distancing, cleaning hands with soap or sanitizers, using disinfectant solutions to decontaminate the surfaces of things and proper ventilation, wearing masks and other protective gears to curb transmission. The knowledge regard-ing COVID-19 therapies is still evolving and collaborative efforts are being put in to discover definitive therapies on different themes in the form of vaccines, repurposing drugs, RNA interfer-ence, docking studies, etc.Copyright © 2021 Bentham Science Publishers.

Detection of Omicron Caused Pneumonia from Radiology Images Using Convolution Neural Network (CNN)

COVID-19 disease caused by the SARS-CoV-2 virus has created social and economic disruption across the world. The ability of the COVID-19 virus to quickly mutate and transfer has created serious concerns across the world. It is essential to detect COVID-19 infection caused by different variants to take preventive measures accordingly. The existing method of detection of infections caused by COVID-19 and its variants is costly and time-consuming. The impacts of the COVID-19 pandemic in developing countries are very drastic due to the unavailability of medical facilities and infrastructure to handle the pandemic. Pneumonia is the major symptom of COVID-19 infection. The radiology of the lungs in varies in the case of bacterial pneumonia as compared to COVID-19-caused pneumonia. The pattern of pneumonia in lungs in radiology images can also be used to identify the cause associated with pneumonia. In this paper, we propose the methodology of identifying the cause (either due to COVID-19 or other types of infections) of pneumonia from radiology images. Furthermore, because different variants of COVID-19 lead to different patterns of pneumonia, the proposed methodology identifies pneumonia, the COVID-19 caused pneumonia, and Omicron caused pneumonia from the radiology images. To fulfill the above-mentioned tasks, we have used three Convolution Neural Networks (CNNs) at each stage of the proposed methodology. The results unveil that the proposed step-by-step solution enhances the accuracy of pneumonia detection along with finding its cause, despite having a limited dataset. © 2023 Tech Science Press. All rights reserved.

MICROFLUIDIC DIAGNOSTIC AND POINT OF CARE DETECTION SYSTEM FOR SARS-COV-2 FROM SALIVA

We present a nucleic acid-based point-of-care diagnostic for the detection of the SARS-CoV-2 from saliva using an additively manufactured microfluidic cartridge. The assay uses reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) to detect the presence of SARS-CoV-2 RNA on-cartridge in a point-of-care optical detection system based on a smartphone. We show positive results within the 10-30 minutes range and integrated biological controls on the cartridge. We demonstrate the microfluidic diagnostic with human patient samples, with results that are consistent with the off-cartridge validation. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

An AI based training framework for Telecommuting Employees to combat perennial skill shortages post pandemic

Telecommuting has become the norm for various organizations due to the impact of COVID-19 pandemic. Telecommuting has positive effects not only on expenses but also on productivity, work flexibility and quality of work. The adoption rate of telecommuting has gone exponentially high especially due to government policies such as social distancing and country-wide lockdown measures. Human resource managers over the globe have reported higher empathy, increased co-ordination, retention and engagement during the lockdown. Provided that, very minimal percentage of workforce operated from their home prior to the coronavirus, it is difficult for employees to adopt the proposed model without any prior training and guidance. This research paper aims to shed light on how the pandemic has impacted the way we work, concerns related to human resource management with main focus on training and development function of HR department. The paper also proposes a framework for training employees to adapt to telecommuting as well as back to office conduct through technological interventions such as Virtual Reality, Artificial Intelligence etc. The overall theoretical framework provides a basic training and development process to reskill and upskill the employees to combat the perennial skill shortages post pandemic. © 2021 IEEE.

Studying structure of Coronaviridae, analyzing their geometry and focusing on the role of electronic applications in health awareness of viruses

Purpose This study aims to focus on electronic applications that have an effective role in raising the awareness of the dangers of viruses' transmission from person-to-person and their positive and important impact on people's lives. Design/methodology/approach The authors illustrated the effects of socializing with infected people on a human body by a model in geometry and how the prospected antibiotic annihilates the structure of the virus. The authors discussed vital operations inside the human body to expound the geometry of objects that are closed under their operations, such as viruses, especially Coronaviridae. Findings Also, the authors discussed some of the e-health applications in Jordan. As e-health activities, programs and applications have been given attention, the authors focused on potentials for constructing strategies that lead to create a featuring health technology. Originality/value Moreover, in this study, the authors explored the structure and geometry of Coronaviridae family, especially coronavirus that causes lots of diseases, and explained its movement mechanism using the mathematical structures.