T Vergne
Optimising the detectability of H5N1 and H5N6 highly pathogenic avian influenza viruses in Vietnamese live-bird markets
Vergne, T; Meyer, A; Long, P T; Elkholly, D A; Inui, K; Padungtod, P; Newman, S H; Fournié, G; Pfeiffer, D U
Authors
A Meyer
P T Long
D A Elkholly
K Inui
P Padungtod
S H Newman
G Fournié
D U Pfeiffer
Abstract
Live bird markets (LBMs) are major targets for avian influenza virus (AIV) surveillance programmes. While sampling the LBM environment has become a widely used alternative to the labour-intensive sampling of live poultry, the design of surveillance programmes and the interpretation of their results are compromised by the lack of knowledge about the effectiveness of these sampling strategies. We used latent class models and a unique empirical dataset collated in Vietnamese LBMs to estimate the sensitivity and specificity of five different sample types for detecting AIVs subtypes H5N1 and H5N6: oropharyngeal duck samples, solid and liquid wastes, poultry drinking water and faeces. Results suggest that the sensitivity of environmental samples for detecting H5N1 viruses is equivalent to that of oropharyngeal duck samples; however, taking oropharyngeal duck samples was estimated to be more effective in detecting H5N6 viruses than taking any of the four environmental samples. This study also stressed that the specificity of the current surveillance strategy in LBMs was not optimal leading to some false positive LBMs. Using simulations, we identified 42 sampling strategies more parsimonious than the current strategy and expected to be highly sensitive for both viruses at the LBM level. All of these strategies involved the collection of both environmental and oropharyngeal duck samples.
Citation
Vergne, T., Meyer, A., Long, P. T., Elkholly, D. A., Inui, K., Padungtod, P., Newman, S. H., Fournié, G., & Pfeiffer, D. U. (2019). Optimising the detectability of H5N1 and H5N6 highly pathogenic avian influenza viruses in Vietnamese live-bird markets. https://doi.org/10.1038/s41598-018-37616-1
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 7, 2018 |
Publication Date | Jan 31, 2019 |
Deposit Date | Feb 15, 2019 |
Publicly Available Date | Feb 15, 2019 |
Journal | Scientific Reports (Nature) |
Peer Reviewed | Peer Reviewed |
Volume | 9 |
DOI | https://doi.org/10.1038/s41598-018-37616-1 |
Public URL | https://rvc-repository.worktribe.com/output/1383730 |
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