title: Tools from ecology: useful for evaluating infection risk models?
abstract: Despite the increasing number of models to predict infection risk for a range of diseases, the assessment of their spatial limits, predictive performance and practical application are not widely undertaken. Using the example of Schistosoma haematobium in Africa, this article illustrates how ecozonation and receiver-operator characteristic analysis can help to assess the usefulness of available models objectively.
authors.affiliation: Dept of Infectious Disease Epidemiology, Imperial College School of Medicine, Norfolk Place, W2 1PG, London, UK. s.brooker@ic.ac.uk
authors.forename: Simon
authors.initials: S
authors.lastname: Brooker
authors.forename: Simon I
authors.initials: SI
authors.lastname: Hay
authors.forename: Don A P
authors.initials: DA
authors.lastname: Bundy
mesh_terms: D000349:Africa / Q000453:epidemiology; D000818:Animals; D002980:Climate; D003141:Communicable Diseases / Q000188:drug therapy / Q000453:epidemiology; D004463:Ecology; D006801:Humans; D008403:Mass Screening; D008954:Models, Biological; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D012307:Risk Factors; D012548:Schistosoma haematobium / Q000187:drug effects / Q000254:growth & development*; D012553:Schistosomiasis haematobia / Q000188:drug therapy / Q000453:epidemiology* / Q000517:prevention & control; D012556:Schistosomicides / Q000008:administration & dosage* / Q000494:pharmacology
chemical_list: D012556:Schistosomicides