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An efficient nonstandard computer method to solve a compartmental epidemiological model for COVID-19 with vaccination and population migration.
Herrera-Serrano, Jorge E; Macías-Díaz, Jorge E; Medina-Ramírez, Iliana E; Guerrero, J A.
  • Herrera-Serrano JE; Centro de Ciencias Básicas, Universidad Autónoma de Aguascalientes, Aguascalientes, Mexico; Dirección Académica de Tecnologías de la Información y Mecatrónica, Universidad Tecnológica del Norte de Aguascalientes, Mexico. Electronic address: jorge.herrera@edu.uaa.mx.
  • Macías-Díaz JE; Department of Mathematics and Didactics of Mathematics, School of Digital Technologies, Tallinn University, Estonia; Departamento de Matemáticas y Física, Universidad Autónoma de Aguascalientes, Aguascalientes, Mexico. Electronic address: jemacias@correo.uaa.mx.
  • Medina-Ramírez IE; Departamento de Química, Universidad Autónoma de Aguascalientes, Aguascalientes, Mexico. Electronic address: iemedina@correo.uaa.mx.
  • Guerrero JA; Departamento de Estadística, Universidad Autónoma de Aguascalientes, Aguascalientes, Mexico. Electronic address: jaguerrero@correo.uaa.mx.
Comput Methods Programs Biomed ; 221: 106920, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1926327
ABSTRACT
BACKGROUND AND

OBJECTIVE:

In this manuscript, we consider a compartmental model to describe the dynamics of propagation of an infectious disease in a human population. The population considers the presence of susceptible, exposed, asymptomatic and symptomatic infected, quarantined, recovered and vaccinated individuals. In turn, the mathematical model considers various mechanisms of interaction between the sub-populations in addition to population migration.

METHODS:

The steady-state solutions for the disease-free and endemic scenarios are calculated, and the local stability of the equilibium solutions is determined using linear analysis, Descartes' rule of signs and the Routh-Hurwitz criterion. We demonstrate rigorously the existence and uniqueness of non-negative solutions for the mathematical model, and we prove that the system has no periodic solutions using Dulac's criterion. To solve this system, a nonstandard finite-difference method is proposed.

RESULTS:

As the main results, we show that the computer method presented in this work is uniquely solvable, and that it preserves the non-negativity of initial approximations. Moreover, the steady-state solutions of the continuous model are also constant solutions of the numerical scheme, and the stability properties of those solutions are likewise preserved in the discrete scenario. Furthermore, we establish the consistency of the scheme and, using a discrete form of Gronwall's inequality, we prove theoretically the stability and the convergence properties of the scheme. For convenience, a Matlab program of our method is provided in the appendix.

CONCLUSIONS:

The computer method presented in this work is a nonstandard scheme with multiple dynamical and numerical properties. Most of those properties are thoroughly confirmed using computer simulations. Its easy implementation make this numerical approach a useful tool in the investigation on the propagation of infectious diseases. From the theoretical point of view, the present work is one of the few papers in which a nonstandard scheme is fully and rigorously analyzed not only for the dynamical properties, but also for consistently, stability and convergence.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Topics: Vaccines Limits: Humans Language: English Journal: Comput Methods Programs Biomed Journal subject: Medical Informatics Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Topics: Vaccines Limits: Humans Language: English Journal: Comput Methods Programs Biomed Journal subject: Medical Informatics Year: 2022 Document Type: Article