tetano
Editor, Senior Moderator
J Biol Dyn
. 2020 Dec;14(1):590-607.
doi: 10.1080/17513758.2020.1788182.
Optimal control strategies for the transmission risk of COVID-19
Legesse Lemecha Obsu[SUP] 1 [/SUP], Shiferaw Feyissa Balcha[SUP] 1 [/SUP]
Affiliations
Abstract
In this paper, we apply optimal control theory to a novel coronavirus (COVID-19) transmission model given by a system of non-linear ordinary differential equations. Optimal control strategies are obtained by minimizing the number of exposed and infected population considering the cost of implementation. The existence of optimal controls and characterization is established using Pontryagin's Maximum Principle. An expression for the basic reproduction number is derived in terms of control variables. Then the sensitivity of basic reproduction number with respect to model parameters is also analysed. Numerical simulation results demonstrated good agreement with our analytical results. Finally, the findings of this study shows that comprehensive impacts of prevention, intensive medical care and surface disinfection strategies outperform in reducing the disease epidemic with optimum implementation cost.
Keywords: COVID-19; basic reproduction number; mathematical modelling; optimal control; sensitivity analysis.
. 2020 Dec;14(1):590-607.
doi: 10.1080/17513758.2020.1788182.
Optimal control strategies for the transmission risk of COVID-19
Legesse Lemecha Obsu[SUP] 1 [/SUP], Shiferaw Feyissa Balcha[SUP] 1 [/SUP]
Affiliations
- PMID: 32696723
- DOI: 10.1080/17513758.2020.1788182
Abstract
In this paper, we apply optimal control theory to a novel coronavirus (COVID-19) transmission model given by a system of non-linear ordinary differential equations. Optimal control strategies are obtained by minimizing the number of exposed and infected population considering the cost of implementation. The existence of optimal controls and characterization is established using Pontryagin's Maximum Principle. An expression for the basic reproduction number is derived in terms of control variables. Then the sensitivity of basic reproduction number with respect to model parameters is also analysed. Numerical simulation results demonstrated good agreement with our analytical results. Finally, the findings of this study shows that comprehensive impacts of prevention, intensive medical care and surface disinfection strategies outperform in reducing the disease epidemic with optimum implementation cost.
Keywords: COVID-19; basic reproduction number; mathematical modelling; optimal control; sensitivity analysis.