At the end of 2019, the COVID-19 virus began to appear and quickly spread throughout the world. It transmits the infection to the respiratory tract by the transmission of pathogens within bioaerosols during speaking, coughing, and sneezing. Therefore, understanding the dynamics of aerosols plays an important role in developing mitigation strategies against droplet infections. Computational modeling, using fluid and computational dynamics, has become a useful feature in studying and visualizing the diffusion of micro-droplets that are difficult to reach using experimental methods. Through this study, the effects of using cloth face masks and social distancing, both recommended by the World Health Organization to the general public to avoid rapid transmission of COVID-19, were determined. This study made a comparison between different structural masks and the difference between social distancing with different porous masks at the droplet diameter during breathing from 0.5 µm to 2.5 µm. The results showed the effectiveness of wearing masks in reducing the risk of infection transmission. Also, with lower mask porosity, lower air permeability means higher filtration efficiency, trapping airborne particles more effectively, especially for small infection-carrying particle sizes, and, therefore, lowering the required social distancing. From the comparison, it is concluded that sample 6 has the highest efficiency of 82.9% compared to other samples (1, 2, 3, 4, and 5), which have efficiencies of 77.1%, 77.1%, 74.3%, 80.0%, and 65.7%, respectively