title: Bayesian receiver operating characteristic estimation of multiple tests for diagnosis of bovine tuberculosis in Chadian cattle.
abstract: BACKGROUND
  Bovine tuberculosis (BTB) today primarily affects developing countries. In Africa, the disease is present essentially on the whole continent; however, little accurate information on its distribution and prevalence is available. Also, attempts to evaluate diagnostic tests for BTB in naturally infected cattle are scarce and mostly complicated by the absence of knowledge of the true disease status of the tested animals. However, diagnostic test evaluation in a given setting is a prerequisite for the implementation of local surveillance schemes and control measures.
  
  
  RESULTS
  We subjected a slaughterhouse population of 954 Chadian cattle to single intra-dermal comparative cervical tuberculin (SICCT) testing and two recently developed fluorescence polarization assays (FPA). Using a Bayesian modeling approach we computed the receiver operating characteristic (ROC) curve of each diagnostic test, the true disease prevalence in the sampled population and the disease status of all sampled animals in the absence of knowledge of the true disease status of the sampled animals. In our Chadian setting, SICCT performed better if the cut-off for positive test interpretation was lowered from >4 mm (OIE standard cut-off) to >2 mm. Using this cut-off, SICCT showed a sensitivity and specificity of 66% and 89%, respectively. Both FPA tests showed sensitivities below 50% but specificities above 90%. The true disease prevalence was estimated at 8%. Altogether, 11% of the sampled animals showed gross visible tuberculous lesions. However, modeling of the BTB disease status of the sampled animals indicated that 72% of the suspected tuberculosis lesions detected during standard meat inspections were due to other pathogens than Mycobacterium bovis.
  
  
  CONCLUSIONS
  Our results have important implications for BTB diagnosis in a high incidence sub-Saharan African setting and demonstrate the practicability of our Bayesian approach for diagnostic test evaluation.
authors.affiliation: Department of Public Health and Epidemiology, Swiss Tropical Institute, Basel, Switzerland. bmuller@sun.ac.za
authors.forename: Borna
authors.initials: B
authors.lastname: Müller
authors.forename: Penelope
authors.initials: P
authors.lastname: Vounatsou
authors.forename: Bongo Naré Richard
authors.initials: BN
authors.lastname: Ngandolo
authors.forename: Colette
authors.initials: C
authors.lastname: Diguimbaye-Djaïbe
authors.forename: Irene
authors.initials: I
authors.lastname: Schiller
authors.forename: Beatrice
authors.initials: B
authors.lastname: Marg-Haufe
authors.forename: Bruno
authors.initials: B
authors.lastname: Oesch
authors.forename: Esther
authors.initials: E
authors.lastname: Schelling
authors.forename: Jakob
authors.initials: J
authors.lastname: Zinsstag
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D002417:Cattle; D002596:Chad; D016015:Logistic Models; D009163:Mycobacterium bovis / Q000502:physiology; D012372:ROC Curve; D011933:Reagent Kits, Diagnostic / Q000592:standards; D012307:Risk Factors; D014380:Tuberculosis, Bovine / Q000175:diagnosis*
chemical_list: D011933:Reagent Kits, Diagnostic