A Bayesian approach to estimate the age-specific prevalence of Schistosoma mansoni and implications for schistosomiasis control.

Models that accurately estimate the age-specific infection prevalence of Schistosoma mansoni can be useful for schistosomiasis control programmes, particularly with regard to whether mass drug administration or selected treatment should be employed. We developed a Bayesian formulation of an immigration-death model that has been previously proposed, which used maximum likelihood inference for estimating the age-specific S. mansoni prevalence in a dataset from Egypt. For comparative purposes, we first applied the Bayesian formulation of the immigration-death model to the dataset from Egypt. We further analysed data obtained from a cross-sectional parasitological survey that determined the infection prevalence of S. mansoni among 447 individuals in a village in Côte d'Ivoire. Three consecutive stool samples were collected from each participant and analysed by the Kato-Katz technique. In the Côte d'Ivoire study, the observed S. mansoni infection prevalence was 41.6% and varied with age. The immigration-death model was able to correctly predict 50% of the observed age group-specific point prevalences. The model presented here can be utilized to estimate S. mansoni community infection prevalences, which in turn helps in the strategic planning of schistosomiasis control.