title: Effective classification of the prevalence of Schistosoma mansoni.
abstract: OBJECTIVE
  To present an effective classification method based on the prevalence of Schistosoma mansoni in the community.
  
  
  METHODS
  We created decision rules (defined by cut-offs for number of positive slides), which account for imperfect sensitivity, both with a simple adjustment of fixed sensitivity and with a more complex adjustment of changing sensitivity with prevalence. To reduce screening costs while maintaining accuracy, we propose a pooled classification method. To estimate sensitivity, we use the De Vlas model for worm and egg distributions. We compare the proposed method with the standard method to investigate differences in efficiency, measured by number of slides read, and accuracy, measured by probability of correct classification.
  
  
  RESULTS
  Modelling varying sensitivity lowers the lower cut-off more significantly than the upper cut-off, correctly classifying regions as moderate rather than lower, thus receiving life-saving treatment. The classification method goes directly to classification on the basis of positive pools, avoiding having to know sensitivity to estimate prevalence. For model parameter values describing worm and egg distributions among children, the pooled method with 25 slides achieves an expected 89.9% probability of correct classification, whereas the standard method with 50 slides achieves 88.7%.
  
  
  CONCLUSIONS
  Among children, it is more efficient and more accurate to use the pooled method for classification of S. mansoni prevalence than the current standard method.
authors.affiliation: Department of Biostatistics, Harvard University, Boston, MA, USA.
authors.forename: Shira A
authors.initials: SA
authors.lastname: Mitchell
authors.forename: Marcello
authors.initials: M
authors.lastname: Pagano
mesh_terms: D000818:Animals; D000871:Anthelmintics; D018890:Chemoprevention; D002648:Child; D003363:Cost Control; D003661:Decision Support Techniques; D006801:Humans; D008403:Mass Screening / Q000145:classification* / Q000191:economics; D010270:Parasite Egg Count / Q000379:methods*; D015995:Prevalence; D012550:Schistosoma mansoni / Q000302:isolation & purification; D012555:Schistosomiasis mansoni / Q000453:epidemiology* / Q000517:prevention & control*; D012680:Sensitivity and Specificity
chemical_list: D000871:Anthelmintics
keywords: Katz‐Kato; S. mansoni; S. mansoni prevalence estimation; clasificación; classification; control enfermedades; cálculo prevalencia S. mansoni; disease control; estimation; lutte contre les maladies; pooled testing; pruebas de grupo; prévalence; test poolé