ABSTRACT
The pandemic's complexity made it difficult to understand the epidemiological impacts of health interventions, primarily masks and vaccines. Compartmental models alone, which are frequently employed, fall short in evaluating complex systems and heterogeneity of individuals, thus limiting research on these control measures. This study aims to explore the effects of health interventions on Corona Virus Disease 2019 (COVID-19) spread using agent-based modeling and simulation. The SEIR framework of compartmental models is employed along with the specific interventions implemented with NetLogo. Exploring the different scenarios demonstrated that respirators and medical masks, for the types of masks, and Pfizer-BioNTech and Moderna, for the brands of vaccines, are the most effective in reducing infection curve peaks, total infection, and death, when used uniformly. The model can be further extended to comprehend other scenarios and combinations of different control measures for effective planning and policymaking in mitigating the effects of COVID-19. © 2022 IEEE.