ABSTRACT
We applied sensitivity analysis and optimum control to the COVID-19 model in this research. In addition, the basic reproduction number calculated as 1.57 indicates that this illness is widespread across Indonesia. The most important factor in this model is the contact rate with infected people, with or without comorbidity. Optimal control will minimize the number of infected populations without and with comorbidity, and costs. Numerical experiments will be carried out to describe and compare the graphical models of the spread of COVID-19 with and without controls. From the numerical results and cost-effectiveness analysis on the optimal control problem, it is found that applying a combination of controls can give the best results compared to a single control.
ABSTRACT
We applied sensitivity analysis and optimum control to the COVID-19 model in this research. In addition, the basic reproduction number calculated as 1.57 indicates that this illness is widespread across Indonesia. The most important factor in this model is the contact rate with infected people, with or without comorbidity. Optimal control will minimize the number of infected populations without and with comorbidity, and costs. Numerical experiments will be carried out to describe and compare the graphical models of the spread of COVID-19 with and without controls. From the numerical results and cost-effectiveness analysis on the optimal control problem, it is found that applying a combination of controls can give the best results compared to a single control. © 2023 EJPAM All rights reserved.
ABSTRACT
In this study, we analyze a mathematical model of COVID-19 with comorbidity to understand the transmission dynamics of COVID-19 with other infectious diseases. Mathematical analyses were presented, including model validation, positivity and boundedness of solutions, equilibrium points, basic reproduction number, and stability of the equilibrium point. Moreover, this disease is endemic in Indonesia, with the obtained basic reproduction number R0 = 1.57. As a result, subpopulation infections increased significantly with decreased detection rates for both individuals with or without comorbidities © 2023, International Journal of Mathematics and Computer Science.All Rights Reserved.
ABSTRACT
Comorbidity is defined as the coexistence of two or more diseases in a person at the same time. The mathematical analysis of the COVID-19 model with comorbidities presented includes model validation of cumulative cases infected with COVID-19 from 1 November 2020 to 19 May 2021 in Indonesia, followed by positivity and boundedness solutions, equilibrium point, basic reproduction number (R0), and stability of the equilibrium point. A sensitivity analysis was carried out to determine how the parameters affect the spread. Disease-free equilibrium points are asymptotically stable locally and globally if R0 < 1 and endemic equilibrium points exist, locally and globally asymptotically stable if R0 > 1. In addition, this disease is endemic in Indonesia, with R0 = 1.47. Furthermore, two optimal controls, namely public education and increased medical care, are included in the model to determine the best strategy to reduce the spread of the disease. Overall, the two control measures were equally effective in suppressing the spread of the disease as the number of COVID-19 infections was significantly reduced. Thus, it was concluded that more attention should be paid to patients with COVID-19 with underlying comorbid conditions because the probability of being infected with COVID-19 is higher and mortality in this population is much higher. Finally, the combined control strategy is an optimal strategy that provides an effective guarantee to protect the public from the COVID-19 infection based on numerical simulations and cost evaluations. Copyright © 2023 Rois, Fatmawati, Alfiniyah and Chukwu.
ABSTRACT
The infection dynamics of COVID-19 is difficult to contain due to the mutation nature of the SARS-CoV-2 virus. This has been a public health concern globally with the impact of the pandemic on the world's economy and mode of living. In the present work, we formulate and examine a fractional model of COVID-19 considering the two variants of concern on the disease transmission pathways, namely SARS-CoV-2 and D614G on our model formulation. The existence and uniqueness of our model solutions were analyzed using the fixed point theory. Mathematical analyses were presented, and the model's basic reproduction numbers R-01 and R-02 were determined. The model has three equilibria: the disease-free equilibrium, that endemic for strain 1, and that endemic for strain 2. The locally asymptotic stability of the equilibria was established based on the R-01 and R-02 values. Caputo fractional operator was used to simulate the model to study the dynamics of the model solution. Results from numerical simulations envisaged that an increase in the transmission parameters of strain 1 leads to an increase in the number of infected individuals. On the other hand, an increase in the strain 2 transmission rate gives rise to more infection. Furthermore, it was established that there is an increased number of infections with a negative impact of strain 1 on strain 2 dynamics and vice versa.