Estimating serotype-specific efficacy of pneumococcal conjugate vaccines using hierarchical models
AbstractPneumococcal conjugate vaccines (PCVs) target 10 or 13 specific serotypes. To evaluate vaccine efficacy for these products, the vaccine-targeted serotypes are typically aggregated into a single group to estimate an overall effect. However, it is often desirable to evaluate variations in effects for different serotypes. These serotype-specific estimates are often based on small numbers, resulting in a high degree of uncertainty and instability in the individual estimates. A better approach is to use a Bayesian hierarchical statistical model, which estimates an overall effectiveness of the vaccine across all vaccine-targeted serotypes but also allows the effect to vary by serotype. We re-analyzed published data from a large randomized controlled trial on the efficacy of PCV13 against non-bacteremic community-acquired pneumonia caused by vaccine-targeted serotype. This model provides a potential framework for obtaining more credible and stable estimates of serotype-specific vaccine efficacy and effectiveness.