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Modeling SARS-CoV-2 and HBV co-dynamics with optimal control.
Omame, Andrew; Abbas, Mujahid.
  • Omame A; Department of Mathematics, Federal University of Technology, Owerri, Nigeria.
  • Abbas M; Abdus Salam School of Mathematical Sciences, Government College University, Katchery Road, Lahore 54000, Pakistan.
Physica A ; 615: 128607, 2023 Apr 01.
Article in English | MEDLINE | ID: covidwho-2274920
ABSTRACT
Clinical reports have shown that chronic hepatitis B virus (HBV) patients co-infected with SARS-CoV-2 have a higher risk of complications with liver disease than patients without SARS-CoV-2. In this work, a co-dynamical model is designed for SARS-CoV-2 and HBV which incorporates incident infection with the dual diseases. Existence of boundary and co-existence endemic equilibria are proved. The occurrence of backward bifurcation, in the absence and presence of incident co-infection, is investigated through the proposed model. It is noted that in the absence of incident co-infection, backward bifurcation is not observed in the model. However, incident co-infection triggers this phenomenon. For a special case of the study, the disease free and endemic equilibria are shown to be globally asymptotically stable. To contain the spread of both infections in case of an endemic situation, the time dependent controls are incorporated in the model. Also, global sensitivity analysis is carried out by using appropriate ranges of the parameter values which helps to assess their level of sensitivity with reference to the reproduction numbers and the infected components of the model. Finally, numerical assessment of the control system using various intervention strategies is performed, and reached at the conclusion that enhanced preventive efforts against incident co-infection could remarkably control the co-circulation of both SARS-CoV-2 and HBV.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: Physica A Year: 2023 Document Type: Article Affiliation country: J.physa.2023.128607

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: Physica A Year: 2023 Document Type: Article Affiliation country: J.physa.2023.128607