Studying the interplay among human mobility, viral transmission, and vaccination can provide significant insights into the factors driving a pandemic. Using the COVID-19 pandemic as a case study, this paper investigates how human mobility, population density, and vaccination affect viral transmission. We employ two data-driven approaches: correlation analysis and structural equation modeling (SEM). Firstly, the correlation analysis reveals a nonuniform relationship between human mobility and disease incidence during the six pandemic periods. The most significant changes in mobility occurred during the initial emergence phase and after the vaccine rollout. We found a positive correlation between mobility and casAe rates early in the pandemic, but later on, they were not positively correlated. Consequently, after the widespread availability of the vaccine, mobility returned to around -5 % of pre-pandemic values as the case incidence decreased. Secondly, we employed SEM to investigate two key aspects. Initially, we explored the association between mobility and COVID-19 incidence during the lockdown and post-lockdown periods for Florida and cross-validated with California, Texas, and New York. Subsequently, we analyzed how vaccination directly and indirectly impacted disease transmission after it became widely available. The findings reveal that vaccination led to a significant drop in case numbers and an increase in mobility, which may have contributed to the subsequent epidemic wave.