Transmission of pneumococcal carriage in families: A latent Markov processmodel for binary longitudinal data

We present a Bayesian data augmentation model to estimate acquisition and c learance rates of carriage of Streptococcus pneumoniae (Pnc) bacteria. The panel observation data comprise 10 measurements of Pnc carriage (carrier/no ncarrier of the bacteria) in all members of 97 families with young children over a period of 2 years. Using natural conditional independence assumptio ns, a transmission model is constructed for the unobserved dependent binary processes of the augmented data. The model explicitly considers carriage t ransmission within the family and carriage acquisition from the surrounding community. The joint posterior of the model parameters and the augmented d ata is explored by Markov chain Monte Carlo sampling. The analysis shows th at in young children the rate of acquiring carriage of three common Pnc ser otypes increases with age. In children less than 2 years old, the duration of carriage is longer than in older family members. Asymptomatic Pnc carria ge is found highly transmittable between members of the same family. In you ng children, the estimated rate of acquiring carriage from a family member carrying Pnc is more than 20-fold to that from acquiring it from the commun ity.