title: Prediction of community prevalence of human onchocerciasis in the Amazonian onchocerciasis focus: Bayesian approach.
abstract: OBJECTIVE
  To develop a Bayesian hierarchical model for human onchocerciasis with which to explore the factors that influence prevalence of microfilariae in the Amazonian focus of onchocerciasis and predict the probability of any community being at least mesoendemic (>20% prevalence of microfilariae), and thus in need of priority ivermectin treatment.
  
  
  METHODS
  Models were developed with data from 732 individuals aged > or =15 years who lived in 29 Yanomami communities along four rivers of the south Venezuelan Orinoco basin. The models' abilities to predict prevalences of microfilariae in communities were compared. The deviance information criterion, Bayesian P-values, and residual values were used to select the best model with an approximate cross-validation procedure.
  
  
  RESULTS
  A three-level model that acknowledged clustering of infection within communities performed best, with host age and sex included at the individual level, a river-dependent altitude effect at the community level, and additional clustering of communities along rivers. This model correctly classified 25/29 (86%) villages with respect to their need for priority ivermectin treatment.
  
  
  CONCLUSIONS
  Bayesian methods are a flexible and useful approach for public health research and control planning. Our model acknowledges the clustering of infection within communities, allows investigation of links between individual- or community-specific characteristics and infection, incorporates additional uncertainty due to missing covariate data, and informs policy decisions by predicting the probability that a new community is at least mesoendemic.
authors.affiliation: Department of Biostatistics and Epidemiology, Oklahoma University Health Sciences Center, Oklahoma City, USA.
authors.forename: Hélène
authors.initials: H
authors.lastname: Carabin
authors.forename: Marisela
authors.initials: M
authors.lastname: Escalona
authors.forename: Clare
authors.initials: C
authors.lastname: Marshall
authors.forename: Sarai
authors.initials: S
authors.lastname: Vivas-Martínez
authors.forename: Carlos
authors.initials: C
authors.lastname: Botto
authors.forename: Lawrence
authors.initials: L
authors.lastname: Joseph
authors.forename: María-Gloria
authors.initials: MG
authors.lastname: Basáñez
mesh_terms: D000293:Adolescent; D000328:Adult; D000818:Animals; D000871:Anthelmintics / Q000627:therapeutic use; D001499:Bayes Theorem; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D007559:Ivermectin / Q000627:therapeutic use; D008297:Male; D009855:Onchocerciasis / Q000188:drug therapy / Q000453:epidemiology*; D015995:Prevalence; D012111:Residence Characteristics; D014687:Venezuela / Q000453:epidemiology
chemical_list: D000871:Anthelmintics; D007559:Ivermectin