Bayesian Evaluation of Three Serological Tests for Diagnosis of Brucella infections in Dromedary Camels Using Latent Class Models

Abstract

Brucellosis is a zoonotic disease with significant economic and public health impacts. The disease has been found in ruminants, including camels, but clinical diagnosis of camel brucellosis is difficult due to the lack of clinical signs. Thus, this study aimed to estimate the sensitivity (Se) and specificity (Sp) of the Buffered Plate Antigen Test (BPAT), Rose Bengal Test (RBT), and indirect ELISA (i-ELISA) for the diagnosis of Brucella infection in dromedary camels imported from Sudan to Egypt. The secondary objective of the study was to calculate the animal-level true prevalence of Brucella infection in imported camels. A cross-sectional study was carried out on 921 apparently healthy camels randomly selected from those imported from Sudan and kept in the quarantine stations in the Shalateen area of the Red Sea Governorate, Egypt, between June 2018 and January 2019. Serum samples were collected and analyzed using BPAT, RBT, and i-ELISA. The posterior estimates [medians and 95% Bayesian probability intervals (95% BPI)] for Se and Sp of the three serological tests were obtained using Bayesian latent class models (BLCMs). The BLCM was fitted with the assumption that the BPAT and RBT tests were conditionally dependent on the true brucellosis status of camels. All tests had comparable and high Se (>86%) and Sp (>98%). The animal-level true prevalence of Brucella infection in imported camels was 8.6% (95% BPI: 6.8 – 10.7). Based on these findings, the three assays could be used for the initial screening of Brucella infection in camels. However, the BPAT and RBT are more suitable for use in camel brucellosis control and eradication program in Egypt because of their low unit cost and fast turnaround time compared to the i-ELISA. In addition, BPAT and RBT could be performed in the field where in-vivo tests are rarely used due to logistic and management constraints. © 2022 Elsevier B.V.