Geodesic
Identification of Parameters for a SEIR-like Epidemiological Model Using Iteratively Regularized Gauss--Newton Method
Numerical methods and programming, Tome 26 (2025) no. 1, pp. 1-16

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We study the problem of identifying the coefficients based on known statistical data for a SEIR-like epidemiological model. The proposed approach to solving this problem is based on the iteratively regularized Gauss–Newton method. We also use one modification of this method, which is able to find quasi-solutions of nonlinear operator equations. We take into account various types of errors in epidemiological statistics. The possibility of predicting the spread of epidemics, as well as determining indicators of its contagion and danger, is discussed.
Keywords: epidemiological model; SEIR; nonlinear operator equation; iteratvely regularized Gauss-Newton method. 
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M. M. Kokurin; A. V. Gavrilova; A. R. Cheha Mohamed. Identification of Parameters for a SEIR-like Epidemiological Model Using Iteratively Regularized Gauss--Newton Method. Numerical methods and programming, Tome 26 (2025) no. 1, pp. 1-16. http://geodesic.mathdoc.fr/item/VMP_2025_26_1_a0/