Simulating the Effectiveness of Wolbachia-Based Vector for Dengue in Bandung Using Disease Spread Model

Dengue remains a significant public health challenge in tropical regions, particularly Indonesia. This study aimed to evaluate the effectiveness of Wolbachia-infected mosquito interventions in reducing dengue transmission in Bandung using a SEIR-SI model extended with spatial dynamics. Dengue case data from 2016 to 2022 were analyzed, with Ujung Berung, a high-risk district, serving as a pilot area for parameter estimation in the non-spatial model. The model employed the fourth-order Runge-Kutta method to solve the system of differential equations, enabling accurate simulations of disease progression. Spatial dynamics were incorporated using an adjacency matrix to represent inter-district mobility, capturing the geographic heterogeneity of dengue transmission. Parameter optimization revealed a significant reduction in the transmission rate due to Wolbachia, with an efficiency factor of 0.4092. Non-spatial model simulations for Ujung Berung highlighted the effectiveness of Wolbachia in delaying infection peaks, achieving a MAPE of 39.61% and an RMSE of 40.76. Spatial simulations further identified Babakan Ciparay and other districts with higher infection rates, emphasizing the critical role of geographic heterogeneity and mobility patterns in shaping dengue dynamics. This research integrates numerical and spatial modeling approaches to provide a scalable approach for dengue prevention. Findings underscore the need for localized and data-driven interventions, with Wolbachia showing strong potential as a sustainable vector control strategy.