Dynamic analysis of a Caputo fractional-order SEIR model with a general incidence rate
Abstract This study develops a fractional-order SEIR model with asymptomatic infections and memory effects, introducing a generalized incidence rate to better reflect the nonlinear characteristics of transmission. The Caputo fractional derivative is used to capture memory effects and non-locality, d...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-01400-9 |
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| Summary: | Abstract This study develops a fractional-order SEIR model with asymptomatic infections and memory effects, introducing a generalized incidence rate to better reflect the nonlinear characteristics of transmission. The Caputo fractional derivative is used to capture memory effects and non-locality, dynamically adjusting the order to adapt to complex processes, improving accuracy and fitting. Based on Lyapunov functions, we rigorously prove that the disease-free equilibrium is globally asymptotically stable when $$R_0<1$$ R 0 < 1 , and the endemic equilibrium is globally stable when $$R_0>1$$ R 0 > 1 . Sensitivity analysis identifies key factors influencing disease spread and control. Numerical simulations validate the theoretical results and demonstrate the advantages of the fractional-order model in capturing epidemic dynamics, which traditional integer-order models fail to capture such dynamics. This study contributes to more accurate disease modeling and provides insights for optimizing control strategies for complex infectious diseases. |
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| ISSN: | 2045-2322 |