Fractional-order modeling of dengue dynamics: exploring reinfection mechanisms with the Atangana–Baleanu derivative

Dengue fever poses ongoing public health challenges due to its complex reinfection dynamics and antibody-dependent enhancement (ADE). To address limitations in classical models, this study proposes a novel fractional-order model utilizing the Atangana–Baleanu–Caputo derivative to capture memory and non-local effects inherent in dengue transmission. The model explicitly incorporates reinfection mechanisms and stages of infection, offering a more accurate depiction of disease progression. The existence and uniqueness of solutions are established using fixed-point theory, and the global stability of equilibria is analyzed via Lyapunov methods. Model fitting with real-world data from Thailand in 2023 confirms predictive accuracy, while sensitivity analysis identifies the biting and mosquito mortality rates as critical parameters influencing the basic reproduction number. This framework enhances the realism of epidemic models and provides actionable insights for designing targeted public health interventions in dengue-endemic regions.