DOI: https://doi.org/10.26089/NumMet.v26r101

Identification of Parameters for a SEIR-like Epidemiological Model Using Iteratively Regularized Gauss–Newton Method

Authors

  • Mikhail M. Kokurin
  • Anastasiya V. Gavrilova
  • Abdu Rauf Cheha Mohamed

Keywords:

epidemiological model
SEIR
nonlinear operator equation
iteratvely regularized Gauss-Newton method

Abstract

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.


Published

2025-01-26

Issue

Section

Methods and algorithms of computational mathematics and their applications

Author Biographies

Mikhail M. Kokurin

Mari State University,
Institute of Digital Technologies
• Head of Laboratory

Anastasiya V. Gavrilova

Mari State University
• Junior Researcher

Abdu Rauf Cheha Mohamed


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