Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1750-2659.2012.00354.x
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dc.titleMultiannual patterns of influenza A transmission in Chinese live bird market systems
dc.contributor.authorPepin, K.M.
dc.contributor.authorWang, J.
dc.contributor.authorWebb, C.T.
dc.contributor.authorSmith, G.J.D.
dc.contributor.authorPoss, M.
dc.contributor.authorHudson, P.J.
dc.contributor.authorHong, W.
dc.contributor.authorZhu, H.
dc.contributor.authorRiley, S.
dc.contributor.authorGuan, Y.
dc.date.accessioned2016-06-01T10:26:59Z
dc.date.available2016-06-01T10:26:59Z
dc.date.issued2013-01
dc.identifier.citationPepin, K.M., Wang, J., Webb, C.T., Smith, G.J.D., Poss, M., Hudson, P.J., Hong, W., Zhu, H., Riley, S., Guan, Y. (2013-01). Multiannual patterns of influenza A transmission in Chinese live bird market systems. Influenza and other Respiratory Viruses 7 (1) : 97-107. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1750-2659.2012.00354.x
dc.identifier.issn17502640
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/124715
dc.description.abstractBackground Avian influenza viruses (AIV) cause huge economic losses in poultry industries and pose a substantial threat to human health. However, predicting AIV epizootics and emergence in humans is confounded by insufficient empirical data on the ecology and dynamics of AIV in poultry systems. To address this gap, we quantified incidence patterns for 13 hemagglutinin subtypes of AIV using 6years of surveillance data that were collected from ten different species of poultry and three different types of poultry holdings (contexts) - retail, wholesale, or farms. Methods We collected 42646 samples in Shantou, China between 2000 and 2006. We screened samples for hemagglutinin subtypes 1-13 of AIV and Avian Paramyxovirus-type-1 (APMV-1) using monospecific antisera in hemagglutination inhibition tests. We analyzed the data to determine seasonality patterns, subtype-host, and subtype-subtype interactions as well as subtype bias in incidence in different contexts. Results H3, H6, H9, and APMV-1 were the most prevalent. No significant seasonality was found when all subtypes were considered together. For most AIV subtypes and APMV-1, there was subtype specificity for host, context, and coinfection partner. H5 showed the most generalized host usage pattern, followed by H9 and H6. Conclusion Subtype-specific patterns because of host, context, and other subtypes suggest that risk assessments that exclude these details are likely inaccurate. Surveillance should include longitudinal sampling of multiple host species in multiple contexts. Quantitative models of control strategies must consider multiple subtypes, hosts, and source contexts to assess the effectiveness of interventions. © 2012 Blackwell Publishing Ltd.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1111/j.1750-2659.2012.00354.x
dc.sourceScopus
dc.subjectAvian influenza
dc.subjectCoinfection
dc.subjectH5N1
dc.subjectHost specificity
dc.subjectLive bird market
dc.subjectRisk
dc.typeArticle
dc.contributor.departmentDUKE-NUS GRADUATE MEDICAL SCHOOL S'PORE
dc.description.doi10.1111/j.1750-2659.2012.00354.x
dc.description.sourcetitleInfluenza and other Respiratory Viruses
dc.description.volume7
dc.description.issue1
dc.description.page97-107
dc.identifier.isiut000312650000015
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