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Application of optimal control to the dynamics of COVID-19 disease in South Africa.
Gatyeni, S P; Chukwu, C W; Chirove, F; Nyabadza, F.
  • Gatyeni SP; Mathematics and Applied Mathematics Department, University of Johannesburg, Auckland Park Kingsway Campus, 2006, P O Box 524, Johannesburg, South Africa.
  • Chukwu CW; Mathematics and Applied Mathematics Department, University of Johannesburg, Auckland Park Kingsway Campus, 2006, P O Box 524, Johannesburg, South Africa.
  • Chirove F; Mathematics and Applied Mathematics Department, University of Johannesburg, Auckland Park Kingsway Campus, 2006, P O Box 524, Johannesburg, South Africa.
  • Fatmawati; Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Surabaya 60115, Indonesia.
  • Nyabadza F; Mathematics and Applied Mathematics Department, University of Johannesburg, Auckland Park Kingsway Campus, 2006, P O Box 524, Johannesburg, South Africa.
Sci Afr ; 16: e01268, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-2076695
ABSTRACT
SARS-CoV-2 (COVID-19) belongs to the beta-coronavirus family, which include the severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV). Since its outbreak in South Africa in March 2020, it has lead to high mortality and thousands of people contracting the virus. Mathematical analysis of a model without controls was done and the basic reproduction number ( R 0 ) of the COVID-19 for the South African pandemic determined. Permissible controls were introduced and an optimal control problem using the Pontraygain Maximum Principle is formulated. Numerical findings suggest that joint implementation of effective mask usage, physical distancing and active screening and testing, are effective measures to curtail the spread of the disease in the human population. The results obtained in this paper are of public health importance in the control and management of the spread for the novel coronavirus, SARS-CoV-2, in South Africa.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Sci Afr Year: 2022 Document Type: Article Affiliation country: J.sciaf.2022.e01268

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Sci Afr Year: 2022 Document Type: Article Affiliation country: J.sciaf.2022.e01268