ArticleBMC infectious diseases2026
Serotype-specific pneumococcal conjugate vaccine effectiveness in Canadian children: an indirect cohort study using Bayesian hierarchical modeling of multisite data.
Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundPneumococcal conjugate vaccine (PCV) effectiveness (VE) against invasive pneumococcal disease (IPD) varies across Streptococcus pneumoniae serotypes (STs). Combining data from multiple sites helps obtain reliable serotype-specific VE estimates but introduces a hierarchical structure. Ignoring this structure can bias results and overstate statistical significance. This study compared Bayesian hierarchical model (BHM) and frequentist fixed-effect model (FFEM) to estimate serotype-specific VE using multisite surveillance data.
methodsThe indirect cohort method was used to estimate serotype-specific VE by immunization status and time since the last dose. IPD cases among children aged 2-59 months were identified according to laboratory and clinical criteria in four Canadian provinces from 2010 to 2019. The FFEM adjusted for province as a fixed effect, whereas the BHM modeled province as a random intercept to account for province-level variability. Intraclass correlation coefficient (ICC) quantified the proportion of variance attributable to province.
resultsA total of 931 IPD cases were included in the analysis. Based on BHM, ICCs indicated that province-level variation accounted for more than 20% of total variance for ST-7F and ST-19F and approximately 5% for ST-3 and ST-19A. Under PCV13 ≥1 dose, VE was 90% (95% credible intervals [CrI] 68 to 97) for ST-19F, 86% (95%CrI: 37 to 97) for ST-7F, 63% (95%CrI: 26 to 81) for ST-19A and 56% (95%CrI: -9 to 82) for ST-3. VE waned over time, particularly for ST-3, decreasing from 80% (95%Crl: 39 to 94) within 12 months after the third PCV13 dose to -44% (95CrI: -272 to 43) thereafter. When compared with FFEM, BHM produced more stable VE estimates in data-sparse strata and yielded more conservative credible intervals. FFEM, by contrast, often failed to converge.
conclusionsPCV vaccine effectiveness varies across serotypes. Bayesian hierarchical modeling is preferred for estimating serotype-specific VE from multisite studies with sparse or clustered data.
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