Modeling of the effect of pneumococcal conjugate vaccination on carriage and transmission of Streptococcus pneumoniae in Kenyan children John Ojal KEMRI-Wellcome.

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Presentation transcript:

Modeling of the effect of pneumococcal conjugate vaccination on carriage and transmission of Streptococcus pneumoniae in Kenyan children John Ojal KEMRI-Wellcome Trust Research Programme

Background Conjugate pneumococcal vaccines have been shown to protect very young vaccinated children and older unvaccinated children. A pneumococcal conjugate vaccine (PCV) has recently been introduced into the Kenyan immunization schedule. However, we do not know the long term population effects of these vaccines in a setting like Kenya Strathmore University International Mathematics Research Meeting

Objective The study aims to model the impact of PCV on pneumococcal transmission and disease using mathematical modelling frameworks. Strathmore University International Mathematics Research Meeting

Unvaccinated Vaccinated

Methods: Model calibration The model will be fitted to pre-vaccination carriage prevalence data to estimate some parameters. The waning rate of vaccine induced protection against carriage and the vaccine efficacy against carriage will act as control parameters Clearance rates to be obtained from studies investigating the nasopharyngeal carriage and clearance rates among Kenyan study subjects Strathmore University International Mathematics Research Meeting

Methods: Likelihood Denote the number of individuals in the ith age group and jth pre-vaccination carriage status in the empirical calibration data by Denote the vectors containing the model output of the serotype distribution in the ith age group by Strathmore University International Mathematics Research Meeting

Methods: Likelihood The counts,, in the ith age group will follow a multinomial distribution with the log- likelihood function given by: The combined log-likelihood for all the age groups is then given by: Strathmore University International Mathematics Research Meeting

Methods: Estimation Given any set of parameters the model generates the steady-state serotype distribution. The likelihood for any given set of parameters is can then be computed using equation 5. The likelihoods are used within a Metropolis- Hastings MCMC algorithm to estimate the best set of parameters that fit the observed data. Strathmore University International Mathematics Research Meeting

Model equations Strathmore University International Mathematics Research Meeting

Force of infection Strathmore University International Mathematics Research Meeting