Academic Journal

Mathematical modeling and analysis of Covid-19 infection spreads in India with restricted optimal treatment on disease incidence

Bibliographic Details
Title: Mathematical modeling and analysis of Covid-19 infection spreads in India with restricted optimal treatment on disease incidence
Authors: Debkumar Pal, D Ghosh, P K Santra, G S Mahapatra
Source: Biomath, Vol 10, Iss 1 (2021)
Publisher Information: Bulgarian Academy of Sciences, Institute of Mathematics and Informatics, 2021.
Publication Year: 2021
Collection: LCC:Biology (General)
LCC:Mathematics
Subject Terms: novel coronavirus, sehgir model, basic reproduction number, stability, optimal control., Biology (General), QH301-705.5, Mathematics, QA1-939
Description: This paper presents the current situation and how to minimize its effect in India through a mathematical model of infectious Coronavirus disease (COVID-19). This model consists of six compartments to population classes consisting of susceptible, exposed, home quarantined, government quarantined, infected individuals in treatment, and recovered class. The basic reproduction number is calculated, and the stabilities of the proposed model at the disease-free equilibrium and endemic equilibrium are observed. The next crucial treatment control of the Covid-19 epidemic model is presented in India's situation. An objective function is considered by incorporating the optimal infected individuals and the cost of necessary treatment. Finally, optimal control is achieved that minimizes our anticipated objective function. Numerical observations are presented utilizing MATLAB software to demonstrate the consistency of present-day representation from a realistic standpoint.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1314-684X
1314-7218
Relation: http://www.biomathforum.org/biomath/index.php/biomath/article/view/1378; https://doaj.org/toc/1314-684X; https://doaj.org/toc/1314-7218
DOI: 10.11145/j.biomath.2021.06.147
Access URL: https://doaj.org/article/0aa0feb7cc28482c811ad8c1a527e0b6
Accession Number: edsdoj.0aa0feb7cc28482c811ad8c1a527e0b6
Database: Directory of Open Access Journals
Description
ISSN:1314684X
13147218
DOI:10.11145/j.biomath.2021.06.147