Pneumococcal conjugate vaccines target 10 or 13 specific serotypes. To evaluate the overall efficacy of these products, the vaccine-targeted serotypes are typically aggregated into a single group. However, it is often desirable to evaluate variations in effects for different serotypes. These serotype-specific estimates are often based on small counts, resulting in a high degree of uncertainty (i.e., large standard errors and wide confidence intervals). An alternative is to use a hierarchical Bayesian statistical model, which estimates overall effectiveness while simultaneously providing estimates of serotype-specific vaccine effects. These shrunken serotype-specific estimators often have smaller mean squared errors (MSEs) than unbiased versions due to a large decrease in posterior uncertainty. We re-analyzed published data from a randomized controlled trial on the efficacy of PCV13 against community-acquired pneumonia caused by vaccine-targeted serotype using a hierarchical model. This model provides a potential framework for obtaining estimates of serotype-specific vaccine effects with reduced MSEs.