Applies Koopman operator with EDMD and tailored dictionary to an SIRSD model to identify dominant modes and predict outbreak peaks from synthetic data across four diseases.
A Nonstandard Finite Difference Scheme for an SEIQR Epidemiological PDE Model
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abstract
This paper introduces a nonstandard finite difference (NSFD) approach to a reaction-diffusion SEIQR epidemiological model, which captures the spatiotemporal dynamics of infectious disease transmission. Formulated as a system of semilinear parabolic partial differential equations (PDEs), the model extends classical compartmental models by incorporating spatial diffusion to account for population movement and spatial heterogeneity. The proposed NSFD discretization is designed to preserve the continuous model's essential qualitative features, such as positivity, boundedness, and stability, which are often compromised by standard finite difference methods. We rigorously analyze the model's well-posedness, construct a structure-preserving NSFD scheme for the PDE system, and study its convergence and local truncation error. Numerical simulations validate the theoretical findings and demonstrate the scheme's effectiveness in preserving biologically consistent dynamics.
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math.DS 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
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A Koopman Operator Framework for Nonlinear Epidemic Dynamics: Application to an SIRSD Model
Applies Koopman operator with EDMD and tailored dictionary to an SIRSD model to identify dominant modes and predict outbreak peaks from synthetic data across four diseases.