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A mathematical system of COVID-19 disease model: Existence, uniqueness, numerical and sensitivity analysis.
Sadri, Khadijeh; Aminikhah, Hossein; Aminikhah, Mahdi.
Afiliación
  • Sadri K; Department of Mathematics, Near East University TRNC, Mersin 10, Nicosia, 99138, Turkey.
  • Aminikhah H; Department of Applied Mathematics and Computer Science, Faculty of Mathematical Sciences, University of Guilan, P.O. Box 1914, Rasht, 41938, Iran.
  • Aminikhah M; Center of Excellence for Mathematical Modelling, Optimization and Combinational Computing (MMOCC), University of Guilan, P.O. Box 1914, Rasht, 41938, Iran.
MethodsX ; 10: 102045, 2023.
Article en En | MEDLINE | ID: mdl-36742367
A compartmental mathematical model of spreading COVID-19 disease in Wuhan, China is applied to investigate the pandemic behaviour in Iran. This model is a system of seven ordinary differential equations including individual behavioural reactions, governmental actions, holiday extensions, travel restrictions, hospitalizations, and quarantine. We fit the Chinese model to the Covid-19 outbreak in Iran and estimate the values of parameters by trial-error approach. We use the Adams-Bashforth predictor-corrector method based on Lagrange polynomials to solve the system of ordinary differential equations. To prove the existence and uniqueness of solutions of the model we use Banach fixed point theorem and Picard iterative method. Also, we evaluate the equilibrium points and the stability of the system. With estimating the basic reproduction number R 0 , we assess the trend of new infected cases in Iran. In addition, the sensitivity analysis of the model is assessed by allocating different parameters to the system. Numerical simulations are depicted by adopting initial conditions and various values of some parameters of the system.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: MethodsX Año: 2023 Tipo del documento: Article País de afiliación: Turquía Pais de publicación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: MethodsX Año: 2023 Tipo del documento: Article País de afiliación: Turquía Pais de publicación: Países Bajos