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Numerical threshold of linearly implicit Euler method for nonlinear infection-age SIR models
Author(s) -
Huizi Yang,
Zhanwen Yang,
Shengqiang Liu
Publication year - 2022
Publication title -
discrete and continuous dynamical systems - b
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.864
H-Index - 53
eISSN - 1553-524X
pISSN - 1531-3492
DOI - 10.3934/dcdsb.2022067
Subject(s) - mathematics , combinatorics
In this paper, we consider a numerical threshold of a linearly implicit Euler method for a nonlinear infection-age SIR model. It is shown that the method shares the equilibria and basic reproduction number \begin{document}$ R_0 $\end{document} of age-independent SIR models for any stepsize. Namely, the disease-free equilibrium is globally stable for numerical processes when \begin{document}$ R_0<1 $\end{document} and the underlying endemic equilibrium is globally stable for numerical processes when \begin{document}$ R_0>1 $\end{document} . A natural extension to nonlinear infection-age models is presented with an initial mortality rate and the numerical thresholds, i.e., numerical basic reproduction numbers \begin{document}$ R^h $\end{document} , are presented according to the infinite Leslie matrix. Although the numerical basic reproduction numbers \begin{document}$ R^h $\end{document} are not quadrature approximations to the exact threshold \begin{document}$ R_0 $\end{document} , the disease-free equilibrium is locally stable for numerical processes whenever \begin{document}$ R^h<1 $\end{document} . Moreover, a unique numerical endemic equilibrium exists for \begin{document}$ R^h>1 $\end{document} , which is locally stable for numerical processes. It is much more important that both the numerical thresholds and numerical endemic equilibria converge to the exact ones with accuracy of order 1. Therefore, the local dynamical behaviors of nonlinear infection-age models are visually displayed by the numerical processes. Finally, numerical applications to the influenza models are shown to illustrate our results.

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