The emergence of coronavirus disease (COVID-19) in late 2019 sparked a global pandemic, profoundly impacting societies and economies worldwide. To mitigate its spread, governments have implemented various preventive measures, prompting extensive research into transmission risk assessment. To evaluate the transmission risk systematically, we developed a framework integrating agent-based modeling (ABM) and computational fluid dynamics (CFD), and applied the framework to a preschool COVID-19 cluster in Singapore as a case study. Individual movement and behaviors are simulated with ABM, and CFD is employed to compute virus particle flow which is critical for transmission risk. In the case study, we categorized the infected individual’s movement into three types based on the initial destinations and evaluated its impact on the transmission risk. Simulation results show that the average risk level is nearly the same for all three movement types and it changes across time depending on the degree of infected individual’s active movement.