Article
Version 1
Preserved in Portico This version is not peer-reviewed
Stability and Sensitivity Analysis of the COVID-19 Spread with Comorbid Diseases
Version 1
: Received: 17 October 2022 / Approved: 17 October 2022 / Online: 17 October 2022 (07:42:58 CEST)
A peer-reviewed article of this Preprint also exists.
Nainggolan, J.; Ansori, M.F. Stability and Sensitivity Analysis of the COVID-19 Spread with Comorbid Diseases. Symmetry 2022, 14, 2269. Nainggolan, J.; Ansori, M.F. Stability and Sensitivity Analysis of the COVID-19 Spread with Comorbid Diseases. Symmetry 2022, 14, 2269.
Abstract
This research investigates a model for the COVID-19 outbreak in Indonesia by analyzing comorbid diseases, self-quarantine, government-provided quarantine, and immunization regimens. Some model parameters are derived from academic journals, others are extrapolated from data collected by the Indonesian Ministry of Health in 2020, and others are assumed. Evaluation of the model reveals non-endemic equilibrium points, endemic equilibrium points, and the basic reproduction number (BRN). The contact rate and infected probability factors impact the increase in the number of COVID-19-infected individuals with comorbid disease within a group. According to the sensitivity analysis of the BRN, the key parameters impacting the spread of COVID-19 are the rate of susceptible recruitment, the rate of contact, the COVID-19 infection death rate, and the likelihood of infection. In addition, sensitivity analyses are provided to examine the effect of parameter changes on subpopulations. We discovered that the natural death rate is the most sensitive parameter based on the sensitivity index after reaching equilibrium. Symmetry aspects appear in some of the visualization of the model’s solution and the BRN and parameters’ sensitivity.
Keywords
mathematical model; COVID-19; comorbid disease; sensitivity analysis; basic reproduction number
Subject
Computer Science and Mathematics, Applied Mathematics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
