title: A Bayesian approach to estimate the age-specific prevalence of Schistosoma mansoni and implications for schistosomiasis control.
abstract: 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.
authors.affiliation: Molecular Parasitology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia; School of Population Health, The University of Queensland, Brisbane, Australia.
authors.forename: Giovanna
authors.initials: G
authors.lastname: Raso
authors.forename: Penelope
authors.initials: P
authors.lastname: Vounatsou
authors.forename: Donald P
authors.initials: DP
authors.lastname: McManus
authors.forename: Eliézer K
authors.initials: EK
authors.lastname: N'Goran
authors.forename: Jürg
authors.initials: J
authors.lastname: Utzinger
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000818:Animals; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D003141:Communicable Diseases / Q000453:epidemiology*; D007560:Cote d'Ivoire / Q000453:epidemiology; D003430:Cross-Sectional Studies; D004534:Egypt / Q000453:epidemiology; D005243:Feces / Q000469:parasitology; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010270:Parasite Egg Count; D015995:Prevalence; D012550:Schistosoma mansoni / Q000302:isolation & purification; D012552:Schistosomiasis / Q000453:epidemiology*