Conditional dependence between tests affects the diagnosis and surveillance of animal diseases

Dependence between the sensitivities or specificities of pairs of tests aff ects the sensitivity and specificity of tests when used in combination. Com pared with values expected if tests are conditionally independent, a positi ve dependence in test sensitivity reduces the sensitivity of parallel test interpretation and a positive dependence in test specificity reduces the sp ecificity of serial interpretation. We calculate conditional covariances as a measure of dependence between binary tests and show their relationship t o kappa (a chance-corrected measure of test agreement). We use published da ta for toxoplasmosis and brucellosis in swine, and Johne's disease in cattl e to illustrate calculation methods and to indicate the likely magnitude of the dependence between serologic tests used for diagnosis and surveillance of animal diseases. (C) 2000 Elsevier Science B.V. All rights reserved.