The dengue virus has become widespread worldwide in recent decades. It has no specific treatment and affects more than 40% of the entire population in the world. In Thailand, dengue has been a health concern for more than half a century. The highest number of cases in one year was 174,285 in 1987, leading to 1,007 deaths. In the present day, dengue is distributed throughout the entire country. Therefore, dengue has become a major challenge for public health in terms of both prevention and control of outbreaks. Different methodologies and ways of dealing with dengue outbreaks have been put forward by researchers. Computational models and simulations play an important role, as they have the ability to help researchers and officers in public health gain a greater understanding of the virus's epidemic activities. In this context, this dissertation presents a new framework, Modified Agent-Based Modeling (mABM), a hybrid platform between a mathematical model and a computational model, to simulate a dengue outbreak in human and mosquito populations. This framework improves on the realism of former models by utilizing the reported data from several Thai government organizations, such as the Thai Ministry of Public Health (MoPH), the National Statistical Office, and others. Additionally, its implementation takes into account the geography of Thailand, as well as synthetic mosquito and synthetic human populations. mABM can be used to represent human behavior in a large population across variant distances by specifying demographic factors and assigning mobility patterns for weekdays, weekends, and holidays for the synthetic human population. The mosquito dynamic population model (MDP), which is a component of the mABM framework, is used for representing the synthetic mosquito population dynamic and their ecology by integrating the regional model to capture the effect of dengue outbreak. The two synthetic populations can be linked to each other for the purpose of presenting their interactions, and the Local Stochastic Contact Model for Dengue (LSCM-DEN) is utilized. For validation, the number of cases from the experiment is compared to reported cases from the Thailand Vector Borne Disease Bureau for the selected years. This framework facilitates model configuration for sensitivity analysis by changing parameters, such as travel routes and seasonal temperatures. The effects of these parameters were studied and analyzed for an improved understanding of dengue outbreak dynamics.