Assessing the sensitivity of bovine tuberculosis surveillance in Canada's cattle population, 2009-2013.
The objectives of this study were (1) to estimate the annual sensitivity of Canada's bTB surveillance system and its three system components (slaughter surveillance, export testing and disease investigation) using a scenario tree modelling approach, and (2) to identify key model parameters that influence the estimates of the surveillance system sensitivity (SSSe). To achieve these objectives, we designed stochastic scenario tree models for three surveillance system components included in the analysis. Demographic data, slaughter data, export testing data, and disease investigation data from 2009 to 2013 were extracted for input into the scenario trees. Sensitivity analysis was conducted to identify key influential parameters on SSSe estimates. The median annual SSSe estimates generated from the study were very high, ranging from 0.95 (95% probability interval [PI]: 0.88-0.98) to 0.97 (95% PI: 0.93-0.99). Median annual sensitivity estimates for the slaughter surveillance component ranged from 0.95 (95% PI: 0.88-0.98) to 0.97 (95% PI: 0.93-0.99). This shows that slaughter surveillance to be the major contributor to overall surveillance system sensitivity with a high probability to detect M. bovis infection if present at a prevalence of 0.00028% or greater during the study period. The export testing and disease investigation components had extremely low component sensitivity estimates-the maximum median sensitivity estimates were 0.02 (95% PI: 0.014-0.023) and 0.0061 (95% PI: 0.0056-0.0066) respectively. The three most influential input parameters on the model's output (SSSe) were the probability of a granuloma being detected at slaughter inspection, the probability of a granuloma being present in older animals (≥12 months of age), and the probability of a granuloma sample being submitted to the laboratory. Additional studies are required to reduce the levels of uncertainty and variability associated with these three parameters influencing the surveillance system sensitivity.
Canadian Food Inspection Agency, Animal Health Science Division, 3200 Sicotte Street, PO Box 5000, Saint-Hyacinthe, Quebec J2S 7C6, Canada. Electronic address: farouk.elallaki@inspection.gc.ca.
Farouk
F
El Allaki
Canadian Food Inspection Agency, Animal Health, Welfare & Biosecurity Division, 59 Camelot Drive, Ottawa, Ontario K1A 0Y9, Canada.
Noel
N
Harrington
Canadian Food Inspection Agency, Animal Health Science Division, 8403 Coronet Road NW, Edmonton, Alberta T6E 4N7, Canada.
Krista
K
Howden
D000818:Animals; D002170:Canada / Q000453:epidemiology; D002417:Cattle; D062665:Epidemiological Monitoring / Q000662:veterinary*; D008962:Models, Theoretical; D011159:Population Surveillance; D015995:Prevalence; D012680:Sensitivity and Specificity; D013269:Stochastic Processes; D014380:Tuberculosis, Bovine / Q000453:epidemiology* / Q000382:microbiology
Bovine tuberculosis; Cattle; Scenario tree; Surveillance sensitivity