Bayesian estimation of diagnostic accuracy of fecal smears, fecal PCR and serum ELISA for detecting Mycobacterium avium subsp. paratuberculosis infections in four domestic ruminant species in Saudi Arabia.

Paratuberculosis, a chronic wasting disease affecting domestic and wild ruminants worldwide, is caused by Mycobacterium avium subsp. paratuberculosis (MAP). Various diagnostic tests exist for detecting MAP infection; however, none of them possess perfect accuracy to be qualified as a reference standard test, particularly due to their notably low sensitivity.

Bayesian accuracy estimates for diagnostic tests to detect tuberculosis in captive sun bears (Helarctos malayanus) and Asiatic black bears (Ursus thibetanus) in Cambodia and Vietnam.

Effective control of tuberculosis (TB) depends on early diagnosis of disease, yet available tests are unable to perfectly detect infected individuals. In novel hosts diagnostic testing methods for TB are extrapolated from other species, with unknown accuracy. The primary challenge to evaluating the accuracy of TB tests is the lack of a perfect reference test.

Comparison of Machine Learning Tree-Based Algorithms to Predict Future Paratuberculosis ELISA Results Using Repeat Milk Tests.

Machine learning algorithms have been applied to various animal husbandry and veterinary-related problems; however, its use in Johne's disease diagnosis and control is still in its infancy. The following proof-of-concept study explores the application of tree-based (decision trees and random forest) algorithms to analyze repeat milk testing data from 1197 Canadian dairy cows and the algorithms' ability to predict future Johne's test results. The random forest models using milk component testing results alongside past Johne's results demonstrated a good predictive performance for a future Johne's ELISA result with a dichotomous outcome (positive vs.

Biosecurity adoption in Québec dairy farms: Results from a risk assessment questionnaire analyzed using conventional and unsupervised artificial intelligence methods.

This study documents the current state of biosecurity on dairy farms in Québec following the implementation of a mandatory biosecurity risk evaluation that was part of the proAction accreditation program developed by Dairy Farmers of Canada. Using a cross-sectional design, 3,825 risk assessment questionnaires completed between 2018 and 2021 were extracted from Vigil-Vet database, which is a software used by veterinarians for conducting the proAction risk assessment. Descriptive statistics were used to summarize the practices adopted by dairy producers.

Prevalence of Microbial Isolates Cultured from Endometrial Swab Samples Collected from United Kingdom Thoroughbred Mares from 2014 to 2020.

Determining whether endometrial microbial isolates are pathogens, contaminants, or even part of the "normal" microbiome is extremely complex, particularly given the absence of "gold standard" tests for endometritis. Population-level benchmarking and temporal monitoring can provide novel insights and a wider context to improve understanding. This study aimed to (i) estimate the prevalence of endometrial isolates from swabs of Thoroughbred broodmares in Newmarket, UK between 2014 and 2020; and (ii) evaluate the effects of year, mare age, and cytology findings on isolate prevalence.