ABSTRACT
The SARS-CoV-2 pandemic is an urgent problem with unpredictable properties and is widespread worldwide through human interactions. This work aims to use Caputo-Fabrizio frac-tional operators to explore the complex action of the Covid-19 Omicron variant. A fixed-point the-orem and an iterative approach are used to prove the existence and singularity of the model's system of solutions. Laplace transform is used to generalize the fractional order model for stability and unique solution of the iterative scheme. A numerical scheme is also constructed by using an expo-nential law kernel for the computational and simulation of the Covid-19 Model. The graphs demon-strate that the fractional model of Covid-19 is accurate. In the sense of Caputo-Fabrizio, one can obtain trustworthy information about the model in either an integer or non-integer scenario. This sense also provides useful information about the model's complexity.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
ABSTRACT
Background: Coronavirus disease 2019 (Covid-19) is caused by a novel coronavirus (SARS-CoV-2) infection, while influenza viruses cause the flu. SARS-CoV-2 and influenza virus co-infection seems to be a real and serious concern. Objective(s): This study aims to evaluate the clinical features, laboratory investigations, computed tomography scans, and interventions of Covid-19 patients during seasonal influenza. Method(s): This was a multi-center prospective cohort study that collected data from hospitals, clinics, and laboratories on measurements, treatments, and outcomes from Covid-19 patients admitted to temporary Covid-19 care centers. Result(s): A total of 480 individuals (female, 231 [48.12%];male, 249 [51.88%]) were recruited from March 31st to May 14th, 2021 at five hospitals/clinics in Uttar Pradesh, North India. The patients were divided into six groups based on their age (65+ years [25.41% of cases] being the most affected age) and five groups based on their conditions (asymptomatic 65 [13.54%], mild 94 [19.58%], moderate 206 [42.91%], severe 84 [17.50%] and critical 31 [6.45%]). Patients' outcomes were documented as death (19 [3.95%]), recovery (421 [87.71%]) and under-treatment (40 [8.34%]). Conclusion(s): The most common clinical symptoms reported were fever, sore throat, and dyspnea. The severity was linked to hypoxemia, lymphocytopenia, thrombocytopenia, elevated erythrocyte sedimentation rate (ESR), and high blood urea nitrogen (BUN). The vast majority of patients were given symptomatic treatment. Any onset of fever should be suspected and examined for the viral strain to distinguish between Covid-19 and the seasonal flu. Copyright © 2022 Bentham Science Publishers.
ABSTRACT
The SARS-CoV-2 virus pandemic remains a pressing issue with its unpredictable nature, and it spreads worldwide through human interaction. Current research focuses on the investigation and analysis of fractional epidemic models that discuss the temporal dynamics of the SARS-CoV-2 virus in the community. In this work, we choose a fractional-order mathematical model to examine the transmissibility in the community of several symptoms of COVID-19 in the sense of the Caputo operator. Sensitivity analysis of R0 and disease-free local stability of the system are checked. Also, with the assistance of fixed point theory, we demonstrate the existence and uniqueness of the system. In addition, numerically we solve the fractional model and presented some simulation results via actual estimation parameters. Graphically we displayed the effects of numerous model parameters and memory indexes. The numerical outcomes show the reliability, validation, and accuracy of the scheme. © 2022 the Author(s), licensee AIMS Press.
ABSTRACT
The fractional derivative is an advanced category of mathematics for real-life problems. This work focus on the investigation of 2nd wave of the Corona virus in India. We develop a time fractional order COVID-19 model with effects of the disease which consist of a system of fractional differential equations. The fractional-order COVID-19 model is investigated with AtanganaBaleanu-Caputo fractional derivative. Also, the deterministic mathematical model for the Omicron effect is investigated with different fractional parameters. The fractional-order system is analyzed qualitatively as well as verified sensitivity analysis. Fixed point theory is used to prove the existence and uniqueness of the fractional-order model. Analyzed the model locally as well as globally using Lyapunov first and second derivative. Boundedness and positive unique solutions are verified for the fractional-order model of infection of disease. The concept of fixed point theory is used to interrogate the problem and confine the solution. Solutions are derived to investigate the influence of fractional operator which shows the impact of the disease on society. Simulation has been made to understand the behavior of the virus.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/ 4.0/).
ABSTRACT
In this paper, we study a fractional order COVID-19 model using different techniques and analysis. The sumudu transform is applied with the environment as a route of infection in society to the proposed fractional-order model. It plays a significant part in issues of medical and engineering as well as its analysis in community. Initially, we present the model formation and its sensitivity analysis. Further, the uniqueness and stability analysis has been made for COVID-19 also used the iterative scheme with fixed point theorem. After using the Adams-Moulton rule to support our results, we examine some results using the fractal fractional operator. Demonstrate the numerical simulations to prove the efficiency of the given techniques. We illustrate the visual depiction of sensitive parameters that reveal the decrease and triumph over the virus within the network. We can reduce the virus by the appropriate recognition of the individuals in community of Saudi Arabia. © 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
COVID-19 acts as a serious challenge to the whole world. Epidemiological data of COVID-19 is collected through media and web sources to analyze and investigate a system of nonlinear ordinary differential equation to understand the outbreaks of this epidemic disease. We analyze the diseases free and endemic equilibrium point including stability of the model. The certain threshold value of the basic reproduction number R0 is found to observe whether population is in disease free state or endemic state. Moreover, the epidemic peak has been obtained and we expect a considerable number of cases. Finally, some numerical results are presented which show the effect of parameters estimation and different step size on our obtained solutions at the real data of some countries to check the actual behavior of the COVID-19 at different countries. © This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.