Work

Dynamical analysis of a fractional-order epidemic weighted network model and its finite-time control

Year: 2025

Type: article

Abstract: Infectious diseases pose a major threat to public health worldwide, often leading to serious social and economic damage. It is necessary to propose an effective control method to help the disease die out quickly. Given that the weight between nodes represents the intimacy of people, which seriously affects the spread of diseases, a fractional-order epidemic model based on weighted networks is proposed. The stability properties of the system’s equilibrium points are rigorously analyzed through the application of fractional-order Lyapunov stability theory. Furthermore, a finite-time controller is proposed for application in infectious disease management. Finite-time control facilitates rapid reduction of infection rates over short durations, thereby offering a potent instrument for responding to abrupt outbreaks. This control strategy not only substantially mitigates the adverse socioeconomic impacts of the epidemic but also expedites the system’s response time, enabling control measures to more rapidly adapt to the dynamic changes in the epidemic. Finally, the validity of theoretical results is verified by simulation.

Source: Chaos Solitons & Fractals

DOI: 10.1016/j.chaos.2025.116402

Authors: Na Liu, Jia Wang, Junwei Sun, Chong Zhang, Qixun Lan, Wei Deng

Institution: Zhengzhou University of Light Industry

Language: English

Topic: Mathematical and Theoretical Epidemiology and Ecology Models

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

Open Access status: hybrid

Estimated APC paid: $3,970

Funders: National Natural Science Foundation of China, Natural Science Foundation of Henan Province