COVID-19 transmission model with discrete time approach
Abstract
In this research, we developed model of SIR for COVID-19 spread. The model is represented by a deterministic discrete-time model. The model is constructed with divided the population into three compartments, namely Susceptible, Infected, and Recovered denoted by S, I, and R, respectively. This research aims to formulate a model for describing the spread of COVID-19 with a data-driven approach. In this research, the model parameters were estimated using the nonlinear least squares method. The data used are daily cases of COVID-19 data in West Java, Indonesia. In addition, other parameters such as birthrate and mortality rate were calibrated using population data and mortality data in the pre-pandemic period. Finally, through numerical simulation, the population dynamics is observed in the model that has been formed based on the estimated parameters.
- Published
- 19 September 2022
- Volume
- 2022 (2022)
- License
- CC BY 3.0
Copyright © 2022 D.S. Pangestu, S.T. Tresna, F. Inayaturohmat, N. Anggriani. 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.
Cite this article
D. S. Pangestu, S. T. Tresna, F. Inayaturohmat, N. Anggriani, COVID-19 transmission model with discrete time approach, Commun. Math. Biol. Neurosci. 2022 (2022), 93. https://doi.org/10.28919/cmbn/7622
BibTeX
@article{Pangestu2022,
author = {Pangestu, D.S. and Tresna, S.T. and Inayaturohmat, F. and Anggriani, N.},
title = {COVID-19 transmission model with discrete time approach},
journal = {Commun. Math. Biol. Neurosci.},
volume = {2022},
year = {2022},
pages = {93},
doi = {10.28919/cmbn/7622}
}