tetano
Editor, Senior Moderator
Proc Biol Sci. 2013 May 8;280(1762):20130872. Print 2013.
Inferring patterns of influenza transmission in swine from multiple streams of surveillance data.
Strelioff CC, Vijaykrishna D, Riley S, Guan Y, Peiris JS, Lloyd-Smith JO.
Source
Department of Ecology and Evolutionary Biology, University of California, , Los Angeles, CA 90095, USA, Laboratory of Virus Evolution, Program in Emerging Infectious Diseases, Duke-NUS Graduate Medical School, , 8 College Road, Singapore , 169857, Republic of Singapore, State Key Laboratory of Emerging Infectious Diseases and Department of Microbiology, The University of Hong Kong, , 21 Sassoon Road, Pokfulam, Hong Kong, People's Republic of China, Department of Community Medicine and School of Public Health, The University of Hong Kong, , 21 Sassoon Road, Pokfulam, Hong Kong, People's Republic of China, State Key Laboratory of Emerging Infectious Diseases and School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, , 21 Sassoon Road, Pokfulam, Hong Kong, People's Republic of China, MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, , London, UK, Fogarty International Center, National Institutes of Health, , Bethesda, MD 20892, USA.
Abstract
Swine 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.
KEYWORDS:
disease ecology, infectious disease surveillance, influenza, state?space model, swine, zoonosis
PMID:
23658205
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/23658205
Inferring patterns of influenza transmission in swine from multiple streams of surveillance data.
Strelioff CC, Vijaykrishna D, Riley S, Guan Y, Peiris JS, Lloyd-Smith JO.
Source
Department of Ecology and Evolutionary Biology, University of California, , Los Angeles, CA 90095, USA, Laboratory of Virus Evolution, Program in Emerging Infectious Diseases, Duke-NUS Graduate Medical School, , 8 College Road, Singapore , 169857, Republic of Singapore, State Key Laboratory of Emerging Infectious Diseases and Department of Microbiology, The University of Hong Kong, , 21 Sassoon Road, Pokfulam, Hong Kong, People's Republic of China, Department of Community Medicine and School of Public Health, The University of Hong Kong, , 21 Sassoon Road, Pokfulam, Hong Kong, People's Republic of China, State Key Laboratory of Emerging Infectious Diseases and School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, , 21 Sassoon Road, Pokfulam, Hong Kong, People's Republic of China, MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, , London, UK, Fogarty International Center, National Institutes of Health, , Bethesda, MD 20892, USA.
Abstract
Swine 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.
KEYWORDS:
disease ecology, infectious disease surveillance, influenza, state?space model, swine, zoonosis
PMID:
23658205
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/23658205