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Article: Inferring patterns of influenza transmission in swine from multiple streams of surveillance data

TitleInferring patterns of influenza transmission in swine from multiple streams of surveillance data
Authors
KeywordsZoonosis
State–space model
Influenza
Swine
Disease ecology
Infectious disease surveillance
Issue Date2013
PublisherThe Royal Society Publishing. The Journal's web site is located at http://rspb.royalsocietypublishing.org/
Citation
Proceedings of the Royal Society B: Biological Sciences, 2013, v. 280 n. 1762, article no. 20130872 How to Cite?
AbstractSwine populations are known to be an important source of new human strains of influenza A, including those responsible for global pandemics. Yet our knowledge of the epidemiology of influenza in swine is dismayingly poor, as highlighted by the emergence of the 2009 pandemic strain and the paucity of data describing its origins. Here, we analyse a unique dataset arising from surveillance of swine influenza at a Hong Kong abattoir from 1998 to 2010. We introduce a state–space model that estimates disease exposure histories by joint inference from multiple modes of surveillance, integrating both virological and serological data. We find that an observed decrease in virus isolation rates is not due to a reduction in the regional prevalence of influenza. Instead, a more likely explanation is increased infection of swine in production farms, creating greater immunity to disease early in life. Consistent with this, we find that the weekly risk of exposure on farms equals or exceeds the exposure risk during transport to slaughter. We discuss potential causes for these patterns, including competition between influenza strains and shifts in the Chinese pork industry, and suggest opportunities to improve knowledge and reduce prevalence of influenza in the region.
Persistent Identifierhttp://hdl.handle.net/10722/206174
ISSN
2023 Impact Factor: 3.8
2023 SCImago Journal Rankings: 1.692
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorStrelioff, CC-
dc.contributor.authorDhanasekaran, V-
dc.contributor.authorRiley, S-
dc.contributor.authorGuan, Y-
dc.contributor.authorPeiris, JSM-
dc.contributor.authorLloyd-Smith, JO-
dc.date.accessioned2014-10-20T13:39:03Z-
dc.date.available2014-10-20T13:39:03Z-
dc.date.issued2013-
dc.identifier.citationProceedings of the Royal Society B: Biological Sciences, 2013, v. 280 n. 1762, article no. 20130872-
dc.identifier.issn0962-8452-
dc.identifier.urihttp://hdl.handle.net/10722/206174-
dc.description.abstractSwine populations are known to be an important source of new human strains of influenza A, including those responsible for global pandemics. Yet our knowledge of the epidemiology of influenza in swine is dismayingly poor, as highlighted by the emergence of the 2009 pandemic strain and the paucity of data describing its origins. Here, we analyse a unique dataset arising from surveillance of swine influenza at a Hong Kong abattoir from 1998 to 2010. We introduce a state–space model that estimates disease exposure histories by joint inference from multiple modes of surveillance, integrating both virological and serological data. We find that an observed decrease in virus isolation rates is not due to a reduction in the regional prevalence of influenza. Instead, a more likely explanation is increased infection of swine in production farms, creating greater immunity to disease early in life. Consistent with this, we find that the weekly risk of exposure on farms equals or exceeds the exposure risk during transport to slaughter. We discuss potential causes for these patterns, including competition between influenza strains and shifts in the Chinese pork industry, and suggest opportunities to improve knowledge and reduce prevalence of influenza in the region.-
dc.languageeng-
dc.publisherThe Royal Society Publishing. The Journal's web site is located at http://rspb.royalsocietypublishing.org/-
dc.relation.ispartofProceedings of the Royal Society B: Biological Sciences-
dc.subjectZoonosis-
dc.subjectState–space model-
dc.subjectInfluenza-
dc.subjectSwine-
dc.subjectDisease ecology-
dc.subjectInfectious disease surveillance-
dc.subject.meshAbattoirs-
dc.subject.meshEpidemiological Monitoring - veterinary-
dc.subject.meshInfluenza A Virus, H1N1 Subtype - physiology-
dc.subject.meshOrthomyxoviridae Infections - epidemiology - transmission - veterinary - virology-
dc.subject.meshSwine Diseases - epidemiology - transmission - virology-
dc.titleInferring patterns of influenza transmission in swine from multiple streams of surveillance data-
dc.typeArticle-
dc.identifier.emailRiley, S: sriley@hkucc.hku.hk-
dc.identifier.emailGuan, Y: yguan@hkucc.hku.hk-
dc.identifier.emailPeiris, JSM: malik@hkucc.hku.hk-
dc.identifier.authorityDhanasekaran, V=rp02721-
dc.identifier.authorityRiley, S=rp00511-
dc.identifier.authorityGuan, Y=rp00397-
dc.identifier.authorityPeiris, JSM=rp00410-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1098/rspb.2013.0872-
dc.identifier.pmid23658205-
dc.identifier.pmcidPMC3673063-
dc.identifier.scopuseid_2-s2.0-84877333059-
dc.identifier.hkuros240916-
dc.identifier.volume280-
dc.identifier.issue1762-
dc.identifier.spagearticle no. 20130872-
dc.identifier.epagearticle no. 20130872-
dc.identifier.isiWOS:000319385100020-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0962-8452-

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