ABSTRACT
The spread and threat of COVID-19 has brought the world under standstill. Educational institutions are not exempt. The pandemic has forced the universities to transform from traditional teaching-learning methods to web-based digital teaching-learning methods. Claims are being made that future teaching would be fully online rather than traditional or in-class mode. There are many challenges in implementation of online classes and at the same time there are possibilities to enhance the knowledge and resources required to build the global online education network. This paper reviews the challenges and possibilities in teaching and learning online, various technological tools and their outcome practiced by the academicians to conduct the lectures and assessment activities. A special attention has been paid to the impact COVID-19 on mental health and anxiety among the staff and student community.
ABSTRACT
SARS-COV-2 (Coronavirus) viral growth kinetics within-host become a key fact to understand the COVID-19 disease progression and disease severity since the year 2020. Quantitative analysis of the viral dynamics has not yet been able to provide sufficient information on the disease severity in the host. The SARS-CoV-2 dynamics are therefore important to study in the context of immune surveillance by developing a mathematical model. This paper aims to develop such a mathematical model to analyse the interaction between the immune system and SARS-CoV-2 within the host. The model is developed to explore the viral load dynamics within the host by considering the role of natural killer cells and T-cell. Through analytical simplifications, the model is found well-posed and asymptotically stable at disease-free equilibrium. The numerical results demonstrate that the influx of external natural killer (NK) cells alone or integrating with anti-viral therapy plays a vital role in suppressing the SARS-CoV-2 growth within-host. Also, within the host, the virus can not grow if the virus replication rate is below a threshold limit. The developed model will contribute to understanding the disease dynamics and help to establish various potential treatment strategies against COVID-19. © 2022 the Author(s), licensee AIMS Press.
ABSTRACT
This paper derived fractional derivatives with Atangana-Baleanu, Atangana-Toufik scheme and fractal fractional Atangana-Baleanu sense for the COVID-19 model. These are advanced techniques that provide effective results to analyze the COVID-19 outbreak. Fixed point theory is used to derive the existence and uniqueness of the fractional-order model COVID-19 model. We also proved the property of boundedness and positivity for the fractional-order model. The Atangana-Baleanu technique and Fractal fractional operator are used with the Sumudu transform to find reliable results for fractional order COVID-19 Model. The generalized Mittag-Leffler law is also used to construct the solution with the different fractional operators. Numerical simulations are performed for the developed scheme in the range of fractional order values to explain the effects of COVID-19 at different fractional values and justify the theoretical outcomes, which will be helpful to understand the outbreak of COVID-19 and for control strategies. © 2022 the Author(s), licensee AIMS Press.
ABSTRACT
The novel coronavirus responsible for COVID-19 has spread to several countries within a considerably short period. The virus gets deposited in the human nasal cavity and moves to the lungs that might be fatal. As per safety guidelines by the World Health Organization (WHO), social distancing has emerged as one of the major factors to avoid the spread of infection. However, different guidelines are being followed across the countries with regards to what should be the safe distance. Thus, the current work is an attempt to understand the virus deposition pattern in the realistic human nasal cavity and also to find the impact of distance that could be termed as a safety measure. This study is performed using Computational Fluid Dynamics as a solution tool to investigate the impact of COVID-19 deposition (i) On a realistic 3D human upper airway model and (ii) 2D social distancing protocol for a distance of 0.6, 1.2, 1.8, and 2.4 m. The results revealed that the regional deposition flux within the nasal cavity was predominantly observed in the external nasal cavity and nasopharyngeal section. Frequent flushing of these regions with saltwater substitutes can limit contamination in healthy individuals. The safe distancing limit estimated with 1 m/s airflow was about 1.8 m. The extensive deposition was observed for distances less than 1.8 m in this study, emphasizing the fact that social distancing advisories are not useful and do not take into account the external dynamics associated with airflow. © 2020 Tech Science Press. All rights reserved.