Evaluating serological tests for foot-and-mouth disease while accounting for different serotypes and uncertain vaccination status.


Journal

Preventive veterinary medicine
ISSN: 1873-1716
Titre abrégé: Prev Vet Med
Pays: Netherlands
ID NLM: 8217463

Informations de publication

Date de publication:
May 2023
Historique:
received: 12 09 2022
revised: 23 02 2023
accepted: 06 03 2023
medline: 14 4 2023
pubmed: 13 3 2023
entrez: 12 3 2023
Statut: ppublish

Résumé

Controlling foot-and-mouth disease (FMD) by vaccination requires adequate population coverage and high vaccine efficacy under field conditions. To assure veterinary services that animals have acquired sufficient immunity, strategic post-vaccination surveys can be conducted to monitor the coverage and performance of the vaccine. Correct interpretation of these serological data and an ability to derive exact prevalence estimates of antibody responses requires an awareness of the performance of serological tests. Here, we used Bayesian latent class analysis to evaluate the diagnostic sensitivity and specificity of four tests. A non-structural protein (NSP) ELISA determines vaccine independent antibodies from environmental exposure to FMD virus (FMDV), and three assays measuring total antibodies derived from vaccine antigen or environmental exposure to two serotypes (A, O): the virus neutralisation test (VNT), a solid phase competitive ELISA (SPCE), and a liquid phase blocking ELISA (LPBE). Sera (n = 461) were collected by a strategic post-vaccination monitoring survey in two provinces of Southern Lao People's Democratic Republic (PDR) after a vaccination campaign in early 2017. Not all samples were tested by every assay and each serotype: VNT tested for serotype A and O, whereas SPCE and LPBE tested for serotype O, and only NSP-negative samples were tested by VNT, with 90 of them not tested (missing by study design). These data challenges required informed priors (based on expert opinion) for mitigating possible lack of model identifiability. The vaccination status of each animal, its environmental exposure to FMDV, and the indicator of successful vaccination were treated as latent (unobserved) variables. Posterior median for sensitivity and specificity of all tests were in the range of 92-99 %, except for the sensitivity of NSP (∼66%) and the specificity of LPBE (∼71 %). There was strong evidence that SPCE outperformed LPBE. In addition, the proportion of animals recorded as having been vaccinated that showed a serological immune response was estimated to be in the range of 67-86 %. The Bayesian latent class modelling framework can easily and appropriately impute missing data. It is important to use field study data as diagnostic tests are likely to perform differently on field survey samples compared to samples obtained under controlled conditions.

Identifiants

pubmed: 36906937
pii: S0167-5877(23)00053-3
doi: 10.1016/j.prevetmed.2023.105889
pii:
doi:

Substances chimiques

Antibodies, Viral 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

105889

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no conflict of interest in publishing this paper.

Auteurs

Geoff Jones (G)

School of Mathematical and Computational Sciences, Massey University, Palmerston North, New Zealand.

Cord Heuer (C)

EpiCentre, School of Veterinary Science, Massey University, Palmerston North, New Zealand.

Wes Johnson (W)

Department of Statistics, University of California, Irvine, USA.

Douglas Begg (D)

Animal Health Laboratory, Diagnostic and Surveillance Services, Biosecurity New Zealand, Ministry for Primary Industries, New Zealand.

Andrew McFadden (A)

Animal Health Laboratory, Diagnostic and Surveillance Services, Biosecurity New Zealand, Ministry for Primary Industries, New Zealand.

Ashish Sutar (A)

World Organisation for Animal Health, Sub-Regional Representation for Southeast Asia, Bangkok, Thailand.

Ronello Abila (R)

World Organisation for Animal Health, Sub-Regional Representation for Southeast Asia, Bangkok, Thailand.

Clare Browning (C)

The Pirbright Institute, Ash Road, Pirbright, Surrey GU24 0NF, UK.

Ginette Wilsden (G)

The Pirbright Institute, Ash Road, Pirbright, Surrey GU24 0NF, UK.

Anna B Ludi (AB)

The Pirbright Institute, Ash Road, Pirbright, Surrey GU24 0NF, UK.

Syseng Khounsy (S)

Department of Livestock and Fisheries, Ministry of Agriculture and Forestry, Vientiane, Lao PDR.

Supatsak Subharat (S)

EpiCentre, School of Veterinary Science, Massey University, Palmerston North, New Zealand. Electronic address: s.subharat@massey.ac.nz.

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Classifications MeSH