Stefanus Raynaldo Septyawan, Muhammad Fakhruddin, Rifky Fauzi, Nuning Nuraini, Chai Jian Tay, Asep K. Supriatna, Thomas Götz, Edy Soewono
Dengue remains a serious public health problem in urban areas; Jakarta and Bandung, Indonesia, are no exception. Our work aims to advance the understanding of dengue transmission dynamics in Bandung by integrating vehicle mobility data from tollgate records into the modeling framework. Most traditional models often overlook the impact of human mobility on the spread of disease. However, this study recognizes the critical role of vehicular movement as a contributing factor to dengue transmission. The research uses a comprehensive approach, combining epidemiological data with high-resolution tollgate records to map population movements. By integrating these mobility data into the infectious disease model, the study aims to refine predictions of dengue hotspots and transmission risk. Hence, incorporating mobility dynamics could significantly enhance the model's accuracy and provide specific insights into patterns of disease spread, helping design more precise and impactful prevention strategies. The research explores the interconnectedness between human mobility and dengue transmission, sheds light on potential routes of disease spread, and identifies areas of increased risk. The findings of this study have implications for public health interventions, highlighting the need to consider mobility in developing proactive measures against dengue outbreaks. The integration of tollgate data provides a foundation for informed decision-making in public health strategies tailored to the unique challenges posed by urban environments. Our findings show that the infection rate and the effective reproduction ratio have strong correlations with the forward weekly infection, which could be used to detect the trend of the weekly infection early on. © 2026 Elsevier Inc.
Department of Mathematics, Institut Teknologi Bandung, Bandung, 40132, Indonesia; Research Center for Computing, National Research and Innovation Agency (BRIN), Bogor, 16911, Indonesia; Department of Mathematics, Faculty of Science, Institut Teknologi Sumatera, Lampung, 35365, Indonesia; Center of Excellence in Predictive Risk and Simulation Modeling, Institut Teknologi Bandung, Bandung, 40132, Indonesia; Centre for Mathematical Sciences, Universiti Malaysia Pahang Al-Sultan Abdullah, Pahang, Gambang, 26300, Malaysia; Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang, 45363, Indonesia; Mathematical Institute, University of Koblenz, Koblenz, 56070, Germany