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Optimal control strategies on COVID-19 infection to bolster the efficacy of vaccination in India.
- Source :
-
Scientific reports [Sci Rep] 2021 Oct 11; Vol. 11 (1), pp. 20124. Date of Electronic Publication: 2021 Oct 11. - Publication Year :
- 2021
-
Abstract
- The Novel Coronavirus which emerged in India on January/30/2020 has become a catastrophe to the country on the basis of health and economy. Due to rapid variations in the transmission of COVID-19, an accurate prediction to determine the long term effects is infeasible. This paper has introduced a nonlinear mathematical model to interpret the transmission dynamics of COVID-19 infection along with providing vaccination in the precedence. To minimize the level of infection and treatment burden, the optimal control strategies are carried out by using the Pontryagin's Maximum Principle. The data validation has been done by correlating the estimated number of infectives with the real data of India for the month of March/2021. Corresponding to the model, the basic reproduction number [Formula: see text] is introduced to understand the transmission dynamics of COVID-19. To justify the significance of parameters we determined the sensitivity analysis of [Formula: see text] using the parameters value. In the numerical simulations, we concluded that reducing [Formula: see text] below unity is not sufficient enough to eradicate the COVID-19 disease and thus, it is required to increase the vaccination rate and its efficacy by motivating individuals to take precautionary measures.<br /> (© 2021. The Author(s).)
- Subjects :
- Basic Reproduction Number
COVID-19 prevention & control
COVID-19 transmission
COVID-19 virology
Communicable Disease Control standards
Computer Simulation
Humans
India epidemiology
Nonlinear Dynamics
Pandemics statistics & numerical data
SARS-CoV-2 pathogenicity
Vaccination statistics & numerical data
COVID-19 epidemiology
COVID-19 Vaccines administration & dosage
Communicable Disease Control organization & administration
Models, Biological
Pandemics prevention & control
Subjects
Details
- Language :
- English
- ISSN :
- 2045-2322
- Volume :
- 11
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Scientific reports
- Publication Type :
- Academic Journal
- Accession number :
- 34635703
- Full Text :
- https://doi.org/10.1038/s41598-021-99088-0