Open AccessA mathematical model for human-to-human transmission of COVID-19: a case study for Turkey's data
Author(s) -
Süleyman Cengizci,
Aslıhan Dursun Cengizci,
Ömür Uğur
Publication year - 2021
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2021480
Subject(s) - basic reproduction number , solver , mathematics , finite element method , ordinary differential equation , stability (learning theory) , nonlinear system , population , galerkin method , transmission (telecommunications) , mathematical model , computer science , epidemic model , mathematical optimization , differential equation , statistics , mathematical analysis , engineering , machine learning , physics , structural engineering , telecommunications , demography , quantum mechanics , sociology
In this study, a mathematical model for simulating the human-to-human transmission of the novel coronavirus disease (COVID-19) is presented for Turkey's data. For this purpose, the total population is classified into eight epidemiological compartments, including the super-spreaders. The local stability and sensitivity analysis in terms of the model parameters are discussed, and the basic reproduction number, $ R_{0} $, is derived. The system of nonlinear ordinary differential equations is solved by using the Galerkin finite element method in the FEniCS environment. Furthermore, to guide the interested reader in reproducing the results and/or performing their own simulations, a sample solver is provided. Numerical simulations show that the proposed model is quite convenient for Turkey's data when used with appropriate parameters.