Diagnostic performance of ID screen MVV-CAEV Indirect Screening ELISA in identifying small ruminant lentiviruses-infected goats

Pol J Vet Sci. 2014;17(3):501-6. doi: 10.2478/pjvs-2014-0072.

Abstract

Diagnostic performance of ID Screen MVV-CAEV Indirect Screening ELISA in identifying goats infected with small ruminant lentiviruses (SRLV) was evaluated. In total 299 serum samples from the collection of the Laboratory of Veterinary Epidemiology and Economics--109 truly positive and 190 truly negative--were used. To be enrolled in the study a serum sample had to come from at least 2 year-old goat which had reacted identically in two serological surveys preceding sample collection and was kept in a herd of stable serological status confirmed at least twice during preceding 5 years. Moreover, in seropositive herds at least 20% of goats had to be serologically positive at the moment when the serum sample was collected for the study. The test proved to have high accuracy. Area under curve was 98.8% (95% CI: 97.5%, 100%). Diagnostic performance of the test was almost identical (Youlden's index of 90%, sensitivity > 90% and specificity > 95%) within a fairly wide range of cut-off values--between 20% and 60%. At manufacturer's cut-off of 50% sensitivity and specificity were 91.7% (95% CI: 85.0%, 95.6%) and 98.9% (95% CI: 96.2%, 99.7%), respectively. For this cut-off positive likelihood ratio was 87 (95% CI: 22, 346) and negative likelihood ratio was 0.08 (95% CI: 0.04, 0.16). In conclusion, the results of this study indicate that ID Screen MVV-CAEV Indirect Screening ELISA is a highly accurate diagnostic test for SRLV infection.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Enzyme-Linked Immunosorbent Assay / methods
  • Enzyme-Linked Immunosorbent Assay / veterinary*
  • Goat Diseases / diagnosis
  • Goat Diseases / virology*
  • Goats
  • Lentivirus Infections / diagnosis
  • Lentivirus Infections / veterinary*
  • Lentivirus Infections / virology
  • Lentiviruses, Ovine-Caprine*
  • Sensitivity and Specificity