title: BAYESIAN ANALYSIS TO EVALUATE TESTS FOR THE DETECTION OF MYCOBACTERIUM BOVIS INFECTION IN FREE-RANGING WILD BISON (BISON BISON ATHABASCAE) IN THE ABSENCE OF A GOLD STANDARD.
abstract: We estimated the sensitivity and specificity of the caudal-fold skin test (CFT), the fluorescent polarization assay (FPA), and the rapid lateral-flow test (RT) for the detection of Mycobacterium bovis in free-ranging wild wood bison (Bison bison athabascae), in the absence of a gold standard, by using Bayesian analysis, and then used those estimates to forecast the performance of a pairwise combination of tests in parallel. In 1998-99, 212 wood bison from Wood Buffalo National Park (Canada) were tested for M. bovis infection using CFT and two serologic tests (FPA and RT). The sensitivity and specificity of each test were estimated using a three-test, one-population, Bayesian model allowing for conditional dependence between FPA and RT. The sensitivity and specificity of the combination of CFT and each serologic test in parallel were calculated assuming conditional independence. The test performance estimates were influenced by the prior values chosen. However, the rank of tests and combinations of tests based on those estimates remained constant. The CFT was the most sensitive test and the FPA was the least sensitive, whereas RT was the most specific test and CFT was the least specific. In conclusion, given the fact that gold standards for the detection of M. bovis are imperfect and difficult to obtain in the field, Bayesian analysis holds promise as a tool to rank tests and combinations of tests based on their performance. Combining a skin test with an animal-side serologic test, such as RT, increases sensitivity in the detection of M. bovis and is a good approach to enhance disease eradication or control in wild bison.
authors.affiliation: 1  Animal Welfare Program, University of British Columbia, 2357 Main Mall, Vancouver, British Columbia V6T 1Z4, Canada.
authors.forename: Núria
authors.initials: N
authors.lastname: Chapinal
authors.affiliation: 2  Department of Veterinary Sciences, University of Wyoming, 1000 E University Avenue, Laramie, Wyoming 82070, USA.
authors.forename: Brant A
authors.initials: BA
authors.lastname: Schumaker
authors.affiliation: 3  Metabiota, Unit 7, 1611 Bowen Road, Nanaimo, British Columbia V9S 1G5, Canada.
authors.forename: Damien O
authors.initials: DO
authors.lastname: Joly
authors.affiliation: 4  Wildlife Division, Department of Environment and Natural Resources, Government of the Northwest Territories, 600, 5102 50th Avenue, Yellowknife, Northwest Territories X1A 3S8, Canada.
authors.forename: Brett T
authors.initials: BT
authors.lastname: Elkin
authors.affiliation: 5  Canadian Wildlife Health Cooperative, 52 Campus Drive, Saskatoon, Saskatchewan S7N 5B4, Canada.
authors.forename: Craig
authors.initials: C
authors.lastname: Stephen
mesh_terms: D000818:Animals; D000835:Animals, Wild / Q000382:microbiology; D001499:Bayes Theorem; D016164:Bison / Q000382:microbiology*; D005260:Female; D008297:Male; D009163:Mycobacterium bovis; D012680:Sensitivity and Specificity; D012698:Serologic Tests / Q000662:veterinary; D012882:Skin Tests / Q000662:veterinary; D014376:Tuberculosis / Q000175:diagnosis / Q000382:microbiology / Q000662:veterinary*
keywords: Bayesian analysis; diagnostic tests; serological tests; tuberculin skin tests; wildlife disease; zoonosis