Evaluation of four molecular detection assays for the diagnosis of Chlamydia pecorum infection in Victorian koalas (Phascolarctos cinereus) using Bayesian latent class analysis

Abstract

Chlamydiosis poses a significant threat to koala health and population viability. Accurate diagnosis of chlamydial infection in koalas at veterinary hospitals informs patient prognosis, biosecurity and determines treatment. However, there is no standardised approach to the diagnosis of chlamydiosis in wildlife hospitals. The performance of available diagnostic tests has not previously been rigorously assessed, and there is a lack of sufficient well-characterised reference samples. This study aimed to estimate the diagnostic accuracy of four molecular detection assays for Chlamydia pecorum infection in koalas using Bayesian latent class analysis (BLCA). Swabs were collected from koalas presen..