High-order reliable numerical methods for epidemic models with non-constant recruitment rate

The mathematical modeling of the propagation of diseases has an important role from both mathematical and biological points of view. In this article, we observe an SEIR-type model with a general incidence rate and a non-constant recruitment rate function. First, we observe the qualitative properties of the continuous system and then apply different numerical methods: first-order and higher-order strong stability preserving Runge-Kutta methods. We give different conditions under which the numerical schemes preserve the positivity and the boundedness of the continuous-time solution. Then, the theoretical results are demonstrated by some numerical experiments.

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Publication Details

Journal
Applied Numerical Mathematics
Published
2024-08-10
DOI
https://doi.org/10.1016/j.apnum.2024.08.008
Citations
4
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
1.58
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article

High-order reliable numerical methods for epidemic models with non-constant recruitment rate

Bálint Takács, Gabriella Svantnerné Sebestyén, István Faragó
4 citations
Applied Numerical Mathematics
COVID-19 epidemiological studies
1.58
article

High-order reliable numerical methods for epidemic models with non-constant recruitment rate

Bálint Takács, Gabriella Svantnerné Sebestyén, István Faragó
article en
4 citations

Abstract

The mathematical modeling of the propagation of diseases has an important role from both mathematical and biological points of view. In this article, we observe an SEIR-type model with a general incidence rate and a non-constant recruitment rate function. First, we observe the qualitative properties of the continuous system and then apply different numerical methods: first-order and higher-order strong stability preserving Runge-Kutta methods. We give different conditions under which the numerical schemes preserve the positivity and the boundedness of the continuous-time solution. Then, the theoretical results are demonstrated by some numerical experiments.

Applied Numerical MathematicsVol. 206
Eötvös Loránd University (HU), Budapest University of Technology and Economics (HU)
Openalex Percentile: Top 19%
COVID-19 epidemiological studies
1.58
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