Use of simulation modeling to estimate herd-level sensitivity, specificity, and predictive values of diagnostic tests...

To estimate herd-level sensitivity (HSe), specificity (HSp), and predictive values for a positive (HPVP) and negative (HPVN) test result for several testing scenarios for detection of tuberculosis in cattle by use of simulation modeling.

Empirical distributions of all herds (15,468) and herds in a 10-county area (1,016) in Michigan.

5 test scenarios were simulated: scenario 1, serial interpretation of the caudal fold tuberculin (CFT) test and comparative cervical test (CCT); scenario 2, serial interpretation of the CFT test and CCT, microbial culture for mycobacteria, and polymerase chain reaction assay; scenario 3, same as scenario 2 but specificity was fixed at 1.0; and scenario 4, sensitivity was 0.9 (scenario 4a) or 0.95 (scenario 4b), and specificity was fixed at 1.0.

Estimates for HSe were reasonably high, ranging between 0.712 and 0.840. Estimates for HSp were low when specificity was not fixed at 1.0. Estimates of HPVP were low for scenarios 1 and 2 (0.042 and 0.143, respectively) but increased to 1.0 when specificity was fixed at 1.0. The HPVN remained high for all 5 scenarios, ranging between 0.995 and 0.997. As herd size increased, HSe increased and HSp and HPVP decreased. However, fixing specificity at 1.0 had only minor effects on HSp and HPVN, but HSe was low when the herd size was small.

Tests used for detecting cattle herds infected with tuberculosis work well on a herd basis. Herds with < approximately 100 cattle should be tested more frequently or for a longer duration than larger herds to ensure that these small herds are free of tuberculosis.