Abstract:

A device comprising a filter attached to a vacuum cleaner was purpose-built to sample rust spores from three potentially high-risk pathways in Australia: passengers, fresh flowers, and sea cargo. The proportion of spores recovered from eight surfaces comparable with those on each pathway (cotton, denim, roses, carnations, chrysanthemums, wood, plastic, and metal) was estimated in the laboratory. Spore recovery percentages were highest for denim clothing (61% Puccinia triticina Erikss. and 62% Uromycladium tepperianum) and lowest for carnations (4% P. triticina Erikss. and 5% U. tepperianum). Subsequently, the device was tested at several locations on the Central Coast of New South Wales, Australia, recently affected by a “myrtle rust” outbreak. Symptomatic and asymptomatic myrtle rust hosts, myrtle rust nonhosts, and inanimate objects (e.g., clothing and vehicles) were sampled in conjunction with the emergency response to the outbreak. A polymerase chain reaction (PCR) assay developed for P. psidii established the presence of myrtle rust, and visual inspections provided spore count estimations. All samples from symptomatic myrtle rust hosts produced positive PCR results and spore count estimations were generally much greater. Several samples from asymptomatic myrtle rust hosts, myrtle rust nonhosts, and inanimate objects also produced positive PCR results; however, there were discrepancies between PCR results and spore count estimations in some of these samples, all of which had <100 spores. This study highlights the utility of the device and analytical methodology, especially during the early stages of a disease outbreak when infection symptoms on plants and contamination on objects is not visible upon gross examination.

Diagnostic testing is used by biosecurity officers for the detection and identification of plant and animal pathogens, often informing high-consequence decisions such as restricting the entry of trade goods. It is rare that such tests can be considered gold standards; however, uncertainty can be reduced by using the results of other tests, measuring performance on samples of known status and incorporating prior knowledge from expert judgement. This article presents an extension to the methods of Joseph et al. (Am J Epidemiol 141:263-272, 1995), and Dendukuri and Joseph (Biometrics 57:158-167, 2001) for Bayesian estimation in the absence of a gold standard test, which allows for the use of incomplete test data. This extension is demonstrated with a novel application: the case study of myrtle rust from Holliday et al. (Plant Dis 97:828-834, 2013), which involves samples from potential biosecurity risk material on importation pathways to Australia. The samples were tested at two laboratories, and prior estimates for pathway prevalence were obtained by expert elicitation. The Bayesian estimation was based on a model with and without covariances for the test results to assess the assumption of conditional independence. The results show that pathogen prevalence, diagnostic sensitivity and diagnostic specificity can be estimated using all available data even where some samples have been subject to only one of two available tests. The results also indicate the importance of consideration of the assumption of conditional independence. The findings enable diagnostic testing laboratories and decision makers to make use of all test results and to explicitly incorporate prior knowledge to estimate pathogen prevalence and test accuracy.

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