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Comparison of Two Rift Valley Fever Serological Tests in Cameroonian Cattle Populations Using a Bayesian Latent Class Approach
Rift Valley Fever is an important zoonotic viral disease of livestock occurring across much of Africa causing acute febrile illness, abortion, and neonatal death in livestock particularly sheep and cattle and a range of disease in humans from mild flu-like symptoms to more severe haemorrhagic fever...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702286/ https://www.ncbi.nlm.nih.gov/pubmed/31475162 http://dx.doi.org/10.3389/fvets.2019.00258 |
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author | de Bronsvoort, Barend M. C. Bagninbom, Jean-Marc Ndip, Lucy Kelly, Robert F. Handel, Ian Tanya, Vincent N. Morgan, Kenton L. Ngu Ngwa, Victor Mazeri, Stella Nfon, Charles |
author_facet | de Bronsvoort, Barend M. C. Bagninbom, Jean-Marc Ndip, Lucy Kelly, Robert F. Handel, Ian Tanya, Vincent N. Morgan, Kenton L. Ngu Ngwa, Victor Mazeri, Stella Nfon, Charles |
author_sort | de Bronsvoort, Barend M. C. |
collection | PubMed |
description | Rift Valley Fever is an important zoonotic viral disease of livestock occurring across much of Africa causing acute febrile illness, abortion, and neonatal death in livestock particularly sheep and cattle and a range of disease in humans from mild flu-like symptoms to more severe haemorrhagic fever and death. Understanding the epidemiology requires well-evaluated tools including antibody detection ELISAs. It is well-recognized that tests developed in one population do not necessarily perform as well when used in different populations and it is therefore important to assess tests in the populations in which they are to be used. Here we describe the performance of a commercial RVF ELISA (ID.Vet) and an in-house plaque reduction neutralization test (PRNT(80)). A Bayesian no gold standard latent class model for two tests and ≥2 populations based on the Hui-Walter model was used to estimate the test parameters using a range of populations based on geographical separation and age to assess consistency of performance across different sub-populations. The ID.Vet ELISA had an estimated diagnostic sensitivity (Se) of 0.854 (0.655–0.991 95%BCI) and specificity (Sp) of 0.986 (0.971–0.998 95%BCI) using all the data and splitting the population by geographical region compared to 0.844 (0.660–0.973 95%BCI) and 0.981 (0.965–0.996 95%BCI) for the PRNT(80). There was slight variation in the mean Se and Sp in different sub-populations mainly in Se estimates due to small numbers of positives in the sub-populations but the 95% BCI generally overlapped suggesting a very consistent performance across the different geographical areas and ages of animals. This is one of few reports of serological evidence of RVF in Central Africa and strongly suggests the virus is actively circulating in this cattle population. This has important public health implications and RVF should be considered as a differential in both livestock disease cases as well as human febrile cases in West and Central Africa not just East Africa. We also demonstrate that the performance of the commercial ELISA is comparable to the PRNT(80) but has the advantages of speed, lower cost and no containment needs making it a much more useful test for low and middle income settings (LMICs). |
format | Online Article Text |
id | pubmed-6702286 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-67022862019-08-30 Comparison of Two Rift Valley Fever Serological Tests in Cameroonian Cattle Populations Using a Bayesian Latent Class Approach de Bronsvoort, Barend M. C. Bagninbom, Jean-Marc Ndip, Lucy Kelly, Robert F. Handel, Ian Tanya, Vincent N. Morgan, Kenton L. Ngu Ngwa, Victor Mazeri, Stella Nfon, Charles Front Vet Sci Veterinary Science Rift Valley Fever is an important zoonotic viral disease of livestock occurring across much of Africa causing acute febrile illness, abortion, and neonatal death in livestock particularly sheep and cattle and a range of disease in humans from mild flu-like symptoms to more severe haemorrhagic fever and death. Understanding the epidemiology requires well-evaluated tools including antibody detection ELISAs. It is well-recognized that tests developed in one population do not necessarily perform as well when used in different populations and it is therefore important to assess tests in the populations in which they are to be used. Here we describe the performance of a commercial RVF ELISA (ID.Vet) and an in-house plaque reduction neutralization test (PRNT(80)). A Bayesian no gold standard latent class model for two tests and ≥2 populations based on the Hui-Walter model was used to estimate the test parameters using a range of populations based on geographical separation and age to assess consistency of performance across different sub-populations. The ID.Vet ELISA had an estimated diagnostic sensitivity (Se) of 0.854 (0.655–0.991 95%BCI) and specificity (Sp) of 0.986 (0.971–0.998 95%BCI) using all the data and splitting the population by geographical region compared to 0.844 (0.660–0.973 95%BCI) and 0.981 (0.965–0.996 95%BCI) for the PRNT(80). There was slight variation in the mean Se and Sp in different sub-populations mainly in Se estimates due to small numbers of positives in the sub-populations but the 95% BCI generally overlapped suggesting a very consistent performance across the different geographical areas and ages of animals. This is one of few reports of serological evidence of RVF in Central Africa and strongly suggests the virus is actively circulating in this cattle population. This has important public health implications and RVF should be considered as a differential in both livestock disease cases as well as human febrile cases in West and Central Africa not just East Africa. We also demonstrate that the performance of the commercial ELISA is comparable to the PRNT(80) but has the advantages of speed, lower cost and no containment needs making it a much more useful test for low and middle income settings (LMICs). Frontiers Media S.A. 2019-08-14 /pmc/articles/PMC6702286/ /pubmed/31475162 http://dx.doi.org/10.3389/fvets.2019.00258 Text en Copyright © 2019 Bronsvoort, Bagninbom, Ndip, Kelly, Handel, Tanya, Morgan, Ngu Ngwa, Mazeri and Nfon. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Veterinary Science de Bronsvoort, Barend M. C. Bagninbom, Jean-Marc Ndip, Lucy Kelly, Robert F. Handel, Ian Tanya, Vincent N. Morgan, Kenton L. Ngu Ngwa, Victor Mazeri, Stella Nfon, Charles Comparison of Two Rift Valley Fever Serological Tests in Cameroonian Cattle Populations Using a Bayesian Latent Class Approach |
title | Comparison of Two Rift Valley Fever Serological Tests in Cameroonian Cattle Populations Using a Bayesian Latent Class Approach |
title_full | Comparison of Two Rift Valley Fever Serological Tests in Cameroonian Cattle Populations Using a Bayesian Latent Class Approach |
title_fullStr | Comparison of Two Rift Valley Fever Serological Tests in Cameroonian Cattle Populations Using a Bayesian Latent Class Approach |
title_full_unstemmed | Comparison of Two Rift Valley Fever Serological Tests in Cameroonian Cattle Populations Using a Bayesian Latent Class Approach |
title_short | Comparison of Two Rift Valley Fever Serological Tests in Cameroonian Cattle Populations Using a Bayesian Latent Class Approach |
title_sort | comparison of two rift valley fever serological tests in cameroonian cattle populations using a bayesian latent class approach |
topic | Veterinary Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702286/ https://www.ncbi.nlm.nih.gov/pubmed/31475162 http://dx.doi.org/10.3389/fvets.2019.00258 |
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