Use of cross-reactive serological assays for detecting novel pathogens in wildlife: assessing an appropriate cutoff for henipavirus assays in African bats

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Author(s)
Peel, Alison J
McKinley, Trevelyan J
Baker, Kate S
Barr, Jennifer A
Crameri, Gary
Hayman, David TS
Feng, Yan-Ru
Broder, Christopher C
Wang, Lin-Fa
Cunningham, Andrew A
Wood, James LN
Griffith University Author(s)
Year published
2013
Metadata
Show full item recordAbstract
Reservoir hosts of novel pathogens are often identified or suspected as such on the basis of serological assay results, prior to the isolation of the pathogen itself. Serological assays might therefore be used outside of their original, validated scope in order to infer seroprevalences in reservoir host populations, until such time that specific diagnostic assays can be developed. This is particularly the case in wildlife disease research. The absence of positive and negative control samples and gold standard diagnostic assays presents challenges in determining an appropriate threshold, or 'cutoff', for the assay that enables ...
View more >Reservoir hosts of novel pathogens are often identified or suspected as such on the basis of serological assay results, prior to the isolation of the pathogen itself. Serological assays might therefore be used outside of their original, validated scope in order to infer seroprevalences in reservoir host populations, until such time that specific diagnostic assays can be developed. This is particularly the case in wildlife disease research. The absence of positive and negative control samples and gold standard diagnostic assays presents challenges in determining an appropriate threshold, or 'cutoff', for the assay that enables differentiation between seronegative and seropositive individuals. Here, multiple methods were explored to determine an appropriate cutoff for a multiplexed microsphere assay that is used to detect henipavirus antibody binding in fruit bat plasma. These methods included calculating multiples of 'negative' control assay values, receiver operating characteristic curve analyses, and Bayesian mixture models to assess the distribution of assay outputs for classifying seropositive and seronegative individuals within different age classes. As for any diagnostic assay, the most appropriate cutoff determination method and value selected must be made according to the aims of the study. This study is presented as an example for others where reference samples, and assays that have been characterised previously, are absent.
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View more >Reservoir hosts of novel pathogens are often identified or suspected as such on the basis of serological assay results, prior to the isolation of the pathogen itself. Serological assays might therefore be used outside of their original, validated scope in order to infer seroprevalences in reservoir host populations, until such time that specific diagnostic assays can be developed. This is particularly the case in wildlife disease research. The absence of positive and negative control samples and gold standard diagnostic assays presents challenges in determining an appropriate threshold, or 'cutoff', for the assay that enables differentiation between seronegative and seropositive individuals. Here, multiple methods were explored to determine an appropriate cutoff for a multiplexed microsphere assay that is used to detect henipavirus antibody binding in fruit bat plasma. These methods included calculating multiples of 'negative' control assay values, receiver operating characteristic curve analyses, and Bayesian mixture models to assess the distribution of assay outputs for classifying seropositive and seronegative individuals within different age classes. As for any diagnostic assay, the most appropriate cutoff determination method and value selected must be made according to the aims of the study. This study is presented as an example for others where reference samples, and assays that have been characterised previously, are absent.
View less >
Journal Title
Journal of Virological Methods
Volume
193
Copyright Statement
© 2013 Elsevier. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
Subject
Applied statistics
Microbiology
Veterinary diagnosis and diagnostics
Veterinary virology
Medical microbiology