Models Of Coronavirus Infection Research Articles

Mathematical analysis of fractional-order Caputo’s derivative of coronavirus disease model via Laplace Adomian decomposition method

BackgroundThe world's survival ability has been threatened by the COVID-19 outbreak. The possibility of the virus reemerging in the future should not be disregarded, even if it has been confined to certain areas of the world after wreaking such havoc. This is because it is impossible to prove that the virus has been totally eliminated. This research attempts to investigate the spread and control of the COVID-19 virus in Nigeria using the Caputo fractional order derivative in a proposed model.ResultsWe proposed a competent nine-compartment model of Corona virus infection. It starts by demonstrating that the model is epidemiologically sound in terms of solution existence and uniqueness. The basic reproduction threshold R0 was determined using the next-generation matrix technique. We applied the Laplace-Adomian decomposition method to the fractional-order Caputo's derivative model of the Corona virus disease to produce the approximate solution of the model analytically. The obtained results, in the form of an infinite series, were simulated using the MAPLE 18 package to investigate the effect of fractional order derivative on the dynamics of COVID-19 transmission in the model and shed light on methods of eradication. The graphical interpretations of the simulation process were shown and discussed accordingly.ConclusionsThe study reveals the effect of the Caputo fractional order derivative in the transmission dynamics of the disease. Individual recovery was found to be greatest at an integer order, which represents the full implementation of other factors such as treatment, vaccination, and disease transmission reduction. Hence, we advised that researchers, government officials, and health care workers make use of the findings of this study to provide ways in which disease transmission will be reduced to a minimum to stop the prevalence of COVID-19 by applying the findings of this study.

Dynamical aspects of corona virus infection

In this paper, we consider five mathematical models of corona virus infection. The first model is a mathematical model of corona virus entry. The second model is a mathematical model for interactions of virus N-protein and viral RNA. Here, we prove that phosphorylated N protein increases the affinity of viral RNA. The third model is a mathematical model of virion assembly. It is a six-dimensional model. But there is an invariant three-dimensional submodel, which we can prove has a positive stable equilibrium. The fourth model is a model of an enzyme inhibitor that blocks viral replication. The fifth model is a model of a virus and a vaccine.

COVID-19 Pandemic: Time to Revive the Cyclophilin Inhibitor Alisporivir.

December 2019 saw the emergence of a new epidemic of pneumonia of varying severity, called COVID-19, caused by a newly identified coronavirus, SARS-CoV-2. No therapeutic option is available to treat this infection that has already killed more than 235,000 people worldwide. This Viewpoint summarizes the strong scientific arguments supporting the use of alisporivir, a non-immunosuppressive analogue of cyclosporine A with potent cyclophilin inhibition properties that has reached Phase 3 clinical development, for the treatment of COVID-19. They include the strong cyclophilin dependency of the lifecycle of many coronaviruses, including SARS-CoV and MERS-CoV, and preclinical data showing strong antiviral and cytoprotective properties of alisporivir in various models of coronavirus infection, including SARS-CoV-2. Alisporivir should be tested without delay on both virological and clinical endpoints in patients with or at-risk of severe forms of SARS-CoV-2 infection.