During the COVID-19 pandemic, residents of color living in disadvantaged communities in Philadelphia, Pennsylvania had disproportionately higher rates of cases, hospitalizations, and deaths, as well as lower rates of COVID-19 vaccination compared to largely white communities. Given these disparities, our objective was to evaluate differences in neighborhood vulnerability by COVID-19 vaccination coverage at the census tract level in Philadelphia and to compare the performance of two statistical place-based measures of disadvantage (“disadvantage indices”). Neighborhood vulnerability was characterized by the CDC Social Vulnerability Index (SVI) and COVID-19 Community Vulnerability Index (CCVI). COVID-19 vaccination coverage (percent of population with 1+ vaccine doses) was obtained at the census tract level through OpenDataPhilly. Kruskal-Wallis tests showed a statistically significant difference in the median vulnerability score (p>0.001 for both SVI and CCVI, separately) between census tracts with similar vaccination coverage. Except for census tracts with <20% coverage, which had lower vulnerability scores (<60^th percentile), tracts with higher coverage rates had lower overall vulnerability scores for both SVI and CCVI. SVI and CCVI were also highly correlated (Pearson correlation coefficient [95% CI] = 0.94 [0.93-0.95], p<0.001), suggesting similar performance between these indices in characterizing vulnerability. Our finding of lower vaccination rates among census tracts with higher vulnerability suggests that these communities should be prioritized for COVID-19 vaccination outreach. Using disadvantage indices can aid with both routine and emergency public health programming, beyond COVID-19, and can help guide resource allocation to neighborhoods that may have a disproportionately greater need, mitigating existing health disparities.