ABSTRACT
Many regions of the world are now facing the second wave of boomed cases of COVID-19. This time, the second wave of this highly infectious disease (COVID-19) is becoming more devastating. To control the existing situation, more mass testing, and tracing of COVID-19 positive individuals are required. Furthermore, practicing to wear a face mask and maintenance of physical distancing are strongly recommended for everyone. Taking all these into consideration, an optimal control problem has been reformulated in terms of nonlinear ordinary differential equations in this paper. The aim of this study is to explore the control strategy of coronavirus-2 disease (COVID-19) and thus, minimize the number of symptomatic, asymptomatic and infected individuals as well as cost of the controls measures. The optimal control model has been analyzed analytically with the help of the necessary conditions of very well-known Pontryagin's maximum principle. Numerical simulations of the optimal control problem are also performed to illustrate the results.
ABSTRACT
SARS-CoV-2, a new and fast circulating coronavirus strain, infected over 214 countries and territories worldwide and caused global health emergencies. The absence of appropriate medicines and vaccinations has further complicated the condition. SARS-CoV-2 main protease (Mpro) is crucial for its propagation, and it is considered a striking target. This study used several computational approaches to determine the probable antagonist of SARS-CoV-2 Mpro from bioactive phytochemicals of Syzygium aromaticum. A total of 20 compounds were screened through in silico approach. The molecular dynamics simulation studies were then carried out for further insights. We found crategolic acid, oleanolic acid, and kaempferol have considerable binding affinity and important molecular contacts with catalytic pocket residues, His41-Cys145. The pharmacological properties through ADMET analysis also showed that these compounds could be used as safe drug candidates. The molecular dynamics simulation study further confirmed these compound's stability with Mpro. However, further detailed in-vitro and in-vivo analyses are compulsory to evaluate the real potentiality of identified compounds.
ABSTRACT
SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is the aetiological agent behind the current pandemic of coronavirus disease 2019 (COVID-19). SARS-CoV-2 main protease plays a dynamic role in mediating viral replication and transcription, which is one of the most probable drug targets against SARS-CoV-2. Ficus carica latex encompasses notable bioactive molecules with various biological properties, including antiviral activities. In this study, latex compounds of Ficus carica were screened to find out active phytochemicals against SARS-CoV-2 main protease through molecular docking, molecular dynamics simulation, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiling. A total of 21 compounds were screened, and the compounds, lupeol, α-amyrin, and luteolin, showed the highest binding affinity and intense interaction with the vital catalytic residue His 41 and Cys 145. The molecular dynamics simulation revealed that the amyrin is the most stable compound with higher binding free energy, suggesting that this compound can compete with the native ligands of the main protease. The ADMET analysis indicated that these phytochemicals have considerable physicochemical, pharmacokinetics, and drug-likeness properties and do not possess any considerable detrimental effects and can be considered as potential drug candidates against SARS-CoV-2. However, further in-vitro, in-vivo, and clinical trials are required to observe the exact efficiency of these compounds. © 2020, Bangladesh Society for Microbiology, Immunology and Advanced Biotechnology. All rights reserved.
ABSTRACT
The present world is in dire straits due to the deadly SARS coronavirus-2 (CoV-2) outbreak, and the experts are trying heart and soul to discover any prevention and/or remedy. The people from all walks of life in the universe are fighting to defeat this novel coronavirus. In this case, doctors are in the front line fighters who have put themselves at a risk. In this paper, we have formulated a non-linear system of five differential equations of COVID-19 based on the tendency of doctors to be infected. The target of this study is to take a look at the transmission of COVID-19 from asymptomatic populations to the doctors. The model is analyzed with the determination of the basic reproduction number, equilibrium, and related stability analysis at both equilibrium points. The graph of the basic reproductive ratio for different parameters has been drawn to show the disease behavior. Finally, we have simulated our model numerically for visualizing the analytical findings. Our study shows that the asymptomatic population increases as the disease (COVID-19) transmission rate increases. The number of infected population increases with the infection rate. These increasing asymptomatic and infected populations lead the doctors to get infected by contacting with them. Thus, the whole medical service system is getting down over time. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
COVID-19 is one of the most highly infectious diseases ever emerged and caused by newly discovered severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has already led the entire world to health and economic crisis. It has invaded the whole universe all most every way. The present study demonstrates with a nine mutually exclusive compartmental model on transmission dynamics of this pandemic disease (COVID-19), with special focus on the transmissibility of symptomatic and asymptomatic infection from susceptible individuals. Herein, the compartmental model has been investigated with mathematical analysis and computer simulations in order to understand the dynamics of COVID-19 transmission. Initially, mathematical analysis of the model has been carried out in broadly by illustrating some well-known methods including exactness, equilibrium and stability analysis in terms of basic reproduction number. We investigate the sensitivity of the model with respect to the variation of the parameters' values. Furthermore, computer simulations are performed to illustrate the results. Our analysis reveals that the death rate from coronavirus disease increases as the infection rate increases, whereas infection rate extensively decreases with the increase of quarantined individuals. The quarantined individuals also lead to increase the concentration of recovered individuals. However, the infection rate of COVID-19 increases more surprisingly as the rate of asymptomatic individuals increases than that of the symptomatic individuals. Moreover, the infection rate decreases significantly due to increase of self-immunity rate. © 2020 Tech Science Press. All rights reserved.