Analysis of rubella antibody distribution from newborn dried blood spots using finite mixture models

Abstract

Eluted dried blood spot specimens from newborn screening, collected in 2004 in North Thames and anonymously linked to birth registration data, were tested for maternally acquired rubella IgG antibody as a proxy for maternal antibody concentration using an enzyme-linked immunosorbent assay. Finite mixture regression models were fitted to the antibody concentrations from 1964 specimens. The Bayesian Information Criterion (BIC) was used as a model selection criterion to avoid over-fitting the number of mixture model components. This allowed investigation of the independent effect of maternal age and maternal country of birth on rubella antibody concentration without dichotomizing the outcome variable using cut-off values set a priori. Mixture models are a highly useful method of analysis in seroprevalence studies of vaccine-preventable infections in which preset cut-off values may overestimate the size of the seronegative population.