Nonlinear dynamics of COVID-19 SEIR infection model with optimal control analysis

Johnson De-Graft Ankamah, Eric Okyere, Sampson Takyi Appiah, Sacrifice Nana-Kyere

Abstract


In this study, we have presented a data-driven SEIR compartmental model for the 2019 coronavirus infections in Ghana. Using the fminsearch optimization routine in Matlab, and the reported cumulative infected cases of COVID-19 in Ghana from 13th March 2020 to 6th October 2020, we have estimated the basic reproduction number, R0 ≈ 1.0413. We have further developed a controlled SEIR dynamical model for COVID-19 disease with a personal protection control strategy. We have derived an optimality system from our proposed optimal control problem. Using the fourth Runge-Kutta iterative scheme with the forward-backward method, we have performed numerical simulations for the model problem. From the numerical results, we can argue that proper personal protection practices can help reduce the disease transmission in the susceptible human population.


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Published: 2021-02-12

How to Cite this Article:

Johnson De-Graft Ankamah, Eric Okyere, Sampson Takyi Appiah, Sacrifice Nana-Kyere, Nonlinear dynamics of COVID-19 SEIR infection model with optimal control analysis, Commun. Math. Biol. Neurosci., 2021 (2021), Article ID 13

Copyright © 2021 Johnson De-Graft Ankamah, Eric Okyere, Sampson Takyi Appiah, Sacrifice Nana-Kyere. 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.

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