Modeling Dengue Transmission as a Dynamical Biological System with Fuzzy Parametric Uncertainty

Exploring the transmission dynamics of viral infections like dengue is crucial for designing effective control measures. Dengue fever remains a significant vector-borne disease with increasing global incidence, particularly in climate-sensitive regions like tropical and subtropical regions. In this study, we propose a deterministic compartmental model, formulated as a system of ordinary differential equations, to analyze dengue transmission considering temperature effects. Temperature plays a crucial role in transmission dynamics by influencing the life cycle of Aedes mosquitoes and the extrinsic incubation period (EIP) of the dengue virus. Fuzzy logic is incorporated to address uncertainty in biological parameters. This hybrid framework explores a more robust analysis of the system’s dynamics. The stability and the equilibrium points of the proposed model are determined; also, the reproduction number is computed by using the next-generation method. The DFE point shows local stability for [Formula: see text]. The existence of the solution and boundedness are also determined. Finally, MATLAB is used for numerical simulations of the model and graphs are shown to visualize the spread of the disease. It is observed that this hybrid framework is very effective for risk prediction and public health planning strategies in endemic situations. This technique provides a foundation for integrating additional environmental and social factors to understand the model more effectively and for better public health interventions.