Inferring longitudinal patterns of group B Streptococcus colonization during pregnancy

Bronner P Gonçalves; Onur Poyraz; Proma Paul; Joy E Lawn

doi:10.1016/j.isci.2023.107023

Inferring longitudinal patterns of group B Streptococcus colonization during pregnancy

iScience. 2023 Jun 8;26(7):107023. doi: 10.1016/j.isci.2023.107023. eCollection 2023 Jul 21.

Authors

Bronner P Gonçalves^{1

2

3}, Onur Poyraz⁴, Proma Paul^{1

2}, Joy E Lawn^{1

2}

Affiliations

¹ Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
² Maternal, Adolescent, Reproductive & Child Health Centre, London School of Hygiene & Tropical Medicine, London, UK.
³ Department of Comparative Biomedical Sciences, School of Veterinary Medicine, University of Surrey, Guildford, UK.
⁴ Department of Computer Science, Aalto University School of Science, Aalto, Finland.

Abstract

Maternal colonization by Group B Streptococcus (GBS) can lead to severe infection in neonates and has also been associated with prematurity and stillbirth. Better quantitative understanding of the trajectories of GBS carriage during pregnancy is essential for the design of informative epidemiological studies. Here, we describe analyses of published longitudinal data using Bayesian hidden Markov models, which involve the estimation of parameters related to the succession of latent states (infection status) and observations (culture positivity). In addition to quantifying infection acquisition and clearance probabilities, the statistical approach also suggests that for some longitudinal patterns of culture results, pregnant women were likely to have been GBS-colonized despite a negative diagnostic result. We believe this method, if used in future longitudinal studies of maternal GBS colonization, would improve our understanding of the pathologies linked to this bacterium and could also inform maternal GBS vaccine trial design.

Keywords: Microbiology; Statistical computing.