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This paper introduces, analyzes, and numerically investigates a fractional-order SEIR epidemic model employing the normalized Caputo-Fabrizio (NCF) derivative. The model captures memory effects and the role of an exposed (latent) compartment, allowing for more realistic epidemic dynamics. We establish existence, uniqueness, positivity, and population conservation, then propose a robust numerical scheme. The impact of the memory parameter and kernel normalization is illustrated via simulations, with a discussion on their significance for epidemic forecasting and potential real-world applications.
This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)
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