Sensitivity Analysis and Numerical Modeling of Influenza Propagation and Intervention Strategies Under the Fractal-Fractional Operator
บทความในวารสาร
ผู้เขียน/บรรณาธิการ
กลุ่มสาขาการวิจัยเชิงกลยุทธ์
รายละเอียดสำหรับงานพิมพ์
รายชื่อผู้แต่ง: Zarin, R., Humphries, U.W., Khalife, H., ABD., El-Wahed, and Raezah, A.A.
ผู้เผยแพร่: World Scientific Publishing
ปีที่เผยแพร่ (ค.ศ.): 2025
หน้าแรก: 1
หน้าสุดท้าย: 30
จำนวนหน้า: 30
นอก: 0218-348X
eISSN: 1793-6543
URL: https://www.worldscientific.com/doi/10.1142/S0218348X25400584
ภาษา: English-Great Britain (EN-GB)
บทคัดย่อ
This paper introduces a novel nonlinear fractal fractional model to comprehensively analyze influenza epidemics. By integrating fractional calculus and considering nonlinear interactions among individuals, the model utilizes the Fractal-Fractional (FF) operator. This operator, combining fractal and fractional calculus, establishes a unique framework for investigating influenza virus propagation dynamics and potential vaccination strategies. Amid growing concerns over influenza outbreaks, fractional derivatives are employed to address intricate challenges. The proposed model sheds light on virus spread dynamics and countermeasures. The integration of the FF operator enriches analysis, while the application of the fixed point theory of Schauder and Banach demonstrates solution existence and uniqueness. Model validation employs numerical simulations with MATLAB12 .and the Adams{Bashforth method, confirming its ability to capture influenza propagation dynamics accurately. Ulam{Hyers stability techniques ensure the model’s reliability. Beyond its scientific contributions, the model underscores the significance of studying influenza epidemics via mathematical modeling in understanding disease dynamics and guiding effective intervention strategies. Through a synergy of mathematical innovation and epidemiological insights, this study establishes a robust foundation for more effective strategies against influenza epidemics
คำสำคัญ
Algorithms, Fractal-Fractional Operator, Hyers-Ulam Stability, Influenza Epidemic, Numerical Results, Vaccination Effect