Social distancing is an effective population-level mitigation strategy to prevent COVID19 propagation but it does not reduce the number of susceptible individuals and bears severe economic and psychological consequences. A vaccine has recently been developed but its deployment will be limited and not immediate. Designing an optimal combination of these two intervention strategies is a priority, but a mechanistic understanding of the interplay between these strategies is missing. To tackle this challenge we developed an age-structured deterministic model in which vaccines are deployed during the pandemic to individuals who, in the eye of public health, are susceptible (do not show symptoms). The model allows for flexible and dynamic prioritization strategies with shifts between target groups. We find that social distancing applied uniformly to all ages and with vaccination targeted towards adults (20-59) or elderly (60+) work in synergism but up to a threshold beyond which vaccination is not efficient. The inefficiency threshold can be eliminated by targeting social distancing at the age groups that are not vaccinated and the optimal strategy is to prioritize vaccines to elderly. Nevertheless, while vaccination reduces hospitalizations, it does not affect the time it takes to eliminate the virus from the population, which is affected only by social distancing. Finally, the same reduction in hospitalization can be achieved via different combination of strategies, giving decision makers flexibility in choosing public health policies. Our study provides insights into the factors that affect vaccination success and provides methodology to test different intervention strategies in a way that will align with ethical guidelines.