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The spread of the Aedes \textit{aegypti} mosquito, which transmits the dengue, is an important public health issue. One approach to estimating the parameters of dengue epidemics is the agent-based spatial model, such as the MOMA model developed by Mannerat and Daude in 2006, which simulates the interaction between mosquitoes and their environment. It is limited to the study of mosquito dynamics and does not assess dengue dynamics. To this end, the aim of this study was to implement an agent-based model of Aedes \textit{aegypty} for the estimation of dengue epidemic parameters under specific urban social, geographic, and climatic conditions (in Arica- Chile). The model includes three agent types: a female Aedes agent, a spatial object agent representing the physical environment, and world agent representing the simulation environment. The Aedes agent includes entomological and behavioral parameters, while the spatial object is constructed using data on population density, land use, and satellite imagery. During the simulation, there is a fixed time step. Within this time step, Aedes agents can observe their environment and choose targets that satisfy their needs, such as biting, taking nectar, laying eggs, and resting. They prioritize their needs using a behavioral decision-making process. We simulated a dynamic population based on social classification and found a strong relationship between mosquito density and flight patterns, urban topology, and human behavior and density.

agent-based model, mosquito population dynamic, spatial simulation