
Estimating Serotype-specific Efficacy of Pneumococcal Conjugate Vaccines Using Hierarchical Models
Author(s) -
Joshua L. Warren,
Daniel M Weinberger
Publication year - 2020
Publication title -
epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.901
H-Index - 173
eISSN - 1531-5487
pISSN - 1044-3983
DOI - 10.1097/ede.0000000000001135
Subject(s) - serotype , pneumococcal conjugate vaccine , vaccine efficacy , confidence interval , bayesian probability , estimator , streptococcus pneumoniae , conjugate vaccine , conjugate , medicine , statistics , virology , biology , mathematics , vaccination , microbiology and biotechnology , antibiotics , mathematical analysis
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 reanalyzed published data from a randomized controlled trial on the efficacy of 13-valent pneumococcal conjugate vaccine (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.