Browsing by Author "Guo A"

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    A novel Bayesian Latent Class Model (BLCM) evaluates multiple continuous and binary tests: A case study for Brucella abortus in dairy cattle.
    (Elsevier B.V., 2024-03-01) Wang Y; Vallée E; Compton C; Heuer C; Guo A; Wang Y; Zhang Z; Vignes M
    Bovine brucellosis, primarily caused by Brucella abortus, severely affects both animal health and human well-being. Accurate diagnosis is crucial for designing informed control and prevention measures. Lacking a gold standard test makes it challenging to determine optimal cut-off values and evaluate the diagnostic performance of tests. In this study, we developed a novel Bayesian Latent Class Model that integrates both binary and continuous testing outcomes, incorporating additional fixed (parity) and random (farm) effects, to calibrate optimal cut-off values by maximizing Youden Index. We tested 651 serum samples collected from six dairy farms in two regions of Henan Province, China with four serological tests: Rose Bengal Test, Serum Agglutination Test, Fluorescence Polarization Assay, and Competitive Enzyme-Linked Immunosorbent Assay. Our analysis revealed that the optimal cut-off values for FPA and C-ELISA were 94.2 mP and 0.403 PI, respectively. Sensitivity estimates for the four tests ranged from 69.7% to 89.9%, while specificity estimates varied between 97.1% and 99.6%. The true prevalences in the two study regions in Henan province were 4.7% and 30.3%. Parity-specific odds ratios for positive serological status ranged from 1.2 to 2.2 for different parity groups compared to primiparous cows. This approach provides a robust framework for validating diagnostic tests for both continuous and discrete tests in the absence of a gold standard test. Our findings can enhance our ability to design targeted disease detection strategies and implement effective control measures for brucellosis in Chinese dairy farms.
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    A scoping review on the epidemiology and public significance of Brucella abortus in Chinese dairy cattle and humans
    (Elsevier B.V., 2024-01-31) Wang Y; Vallée E; Heuer C; Wang Y; Guo A; Zhang Z; Compton C
    Brucellosis, caused by Brucella spp., is a re-emerging One Health disease with increased prevalence and incidence in Chinese dairy cattle and humans, severely affecting animal productivity and public health. In dairy cattle, B. abortus is the primary causative agent although infections with other Brucella species occur occasionally. However, the epidemiological and comparative importance of B. abortus in dairy cattle and humans remains inadequately understood throughout China due to the heterogeneity in locations, quality, and study methods. This scoping review aims to describe the changing status of B. abortus infection in dairy cattle and humans, investigate the circulating Brucella species and biovars, and identify factors driving the disease transmission by retrieving publicly accessible literature from four databases. After passing the prespecified inclusion criteria, 60 original articles were included in the final synthesis. Although the reported animal-level and farm-level prevalence of brucellosis in dairy cattle was lower compared to other endemic countries (e.g. Iran and India), it has been reported to increase over the last decade. The incidence of brucellosis in humans displayed seasonal increases. The Rose Bengal Test and Serum Agglutination Test, interpreted in series, were the most used serological test to diagnose Brucella spp. in dairy cattle and humans. B. abortus biovar 3 was the predominant species (81.9%) and biovar (70.3%) in dairy cattle, and B. melitensis biovar 3 was identified as the most commonly detected strain in human brucellosis cases. These strains were mainly clustered in Inner Mongolia and Shannxi Province (75.7%), limiting the generalizability of the results to other provinces. Live cattle movement or trade was identified as the key factor driving brucellosis transmission, but its transmission pattern remains unknown within the Chinese dairy sector. These knowledge gaps require a more effective One Health approach to be bridged. A coordinated and evidence-based research program is essential to inform regional or national control strategies that are both feasible and economical in the Chinese context.