During the COVID-19 pandemic, vaccination rates for both COVID-19 vaccines and routine childhood vaccines remained suboptimal in the United States. Vaccine hesitancy, the delay or refusal of recommended childhood vaccines, is well-documented and varies by vaccine. COVID-19 vaccine uptake remained below herd immunity levels due to factors such as rapid development, political polarization, and health concerns. Scarce healthcare resources, including vaccines and ventilators, were allocated using indices like the Social Vulnerability Index and Area Deprivation Index, which measure neighborhood vulnerability based on social determinants of health (e.g., poverty, income, crowding, minority status). Indices can potentially characterize neighborhood-level structural racism which is a fundamental cause of health disparities. While the use of indices aimed to equitably distribute resources, their impact on COVID-19 vaccine uptake is unclear. This thesis contains the findings for four cross-sectional studies assessing the associations between neighborhood vulnerability and vaccination coverage in Philadelphia, PA using the PhilaVax immunization registry. The first study, analyzing registry data through 2021, revealed that Black residents and those in more vulnerable neighborhoods had decreased odds of receiving a COVID-19 vaccine compared to their White affluent counter-parts. The second mid-2022 census tract-level vaccination coverage study in Philadelphia found higher odds of under-vaccination in socioeconomically disadvantaged neighborhoods, suggesting vaccines may not be reaching vulnerable communities. These results highlight ongoing social inequities in vaccination and emphasize the need for robust programs addressing social determinants to improve population health. The third study assessed child and adolescent vaccine up-to-date (UTD) status in 2022, finding higher UTD status in more socially vulnerable neighborhoods. Although UTD status was higher for younger children, it remained suboptimal, with differences observed by race and ethnicity. Mapping revealed associations between UTD coverage and SVI rankings among certain age groups. In the final study, logistic regression and random forest algorithms were compared using the registry data to predict vaccine uptake for HPV, influenza, and COVID-19. Random forest predictions showed slightly higher accuracy overall, varying by vaccine. This thesis evaluates health inequities in vaccination coverage in Philadelphia, aiming to assist public health officials in outbreak preparedness and resource allocation decisions.