4.4 Article

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

期刊

JOURNAL OF VIROLOGICAL METHODS
卷 193, 期 2, 页码 295-303

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jviromet.2013.06.030

关键词

Serology; Multiplex; Eidolon helvum; Emerging diseases; Microsphere binding assay

资金

  1. University of Cambridge, Institute of Zoology
  2. Australian Animal Health Laboratory
  3. Charles Slater Trust
  4. Zebra Foundation for Veterinary Zoological Education provided travel
  5. Biotechnology and Biological Sciences Research Council [BB/I012192/1]
  6. Wellcome Trust
  7. Research and Policy for Infectious Disease Dynamics (RAPIDD)
  8. Science and Technology Directorate
  9. Department of Homeland Security
  10. Fogarty International Center, USA
  11. Department for Environment
  12. Food and Rural Affairs (Defra) [SEV3500]
  13. Royal Society Wolfson Research Merit
  14. Alborada Trust
  15. BBSRC [BB/I012192/1] Funding Source: UKRI
  16. Biotechnology and Biological Sciences Research Council [BB/I012192/1] Funding Source: researchfish

向作者/读者索取更多资源

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. (C) 2013 The Authors. Published by Elsevier B.V. All rights reserved.

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