The COVID-19 pandemic has caused substantial global morbidity and mortality, with considerable variation in outcomes across countries. This ecological study investigates the association between country-level COVID-19 vaccination rates and mortality, considering socioeconomic and demographic factors, using Functional Data Analysis. A scalar-on-function regression framework was applied to analyze 77 countries across six pandemic periods, encompassing the Delta and Omicron variant waves. The response variable was the log-transformed COVID-19 death rate, modeled as a scalar outcome. The primary predictor was the cumulative daily vaccination rate, while covariates included log-transformed population size, percent of adults aged 65 years and older, life expectancy at age 60, and health expenditure in USD. Analysis showed that higher vaccination rates were associated with lower mortality during the initial vaccine rollout phase and during the beginning of the late Delta and Omicron periods, after accounting for socioeconomic and demographic covariates. Results also indicate that the percent of the population aged 65+ and life expectancy at age 60 were consistently significant determinants of COVID-19 mortality, whereas the vaccination rate coefficients varied across periods and were not consistently statistically significant. Model R² values ranged from weak to moderate, suggesting that selected statistical methods and additional contextual factors—such as outbreak timing, containment policies, and healthcare system differences—likely influenced mortality outcomes. This study highlights that while vaccination remains a key tool in mitigating COVID-19 mortality, demographic and structural characteristics play substantial roles in shaping outcomes at the country level. The findings underscore the importance of integrating temporal modeling with contextual considerations in assessing global pandemic responses and can inform future strategies to enhance preparedness and equity in public health interventions.