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Clin Infect Dis. Multiple Contributory Factors to the Age Distribution of Disease Cases: A Modeling Study in the Context of Influenza A(H3N2v).

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  • Clin Infect Dis. Multiple Contributory Factors to the Age Distribution of Disease Cases: A Modeling Study in the Context of Influenza A(H3N2v).

    [Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]
    Clin Infect Dis. 2013 Jul;57 Suppl 1:S23-7. doi: 10.1093/cid/cit298.

    Multiple Contributory Factors to the Age Distribution of Disease Cases: A Modeling Study in the Context of Influenza A(H3N2v).


    Gambhir M, Swerdlow DL, Finelli L, Van Kerkhove MD, Biggerstaff M, Cauchemez S, Ferguson NM.

    Source: Modeling Unit, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia.


    Abstract

    Background. 

    In late 2011 and early 2012, 13 cases of human influenza resulted from infection with a novel triple reassortant swine-origin influenza virus, influenza A (H3N2) variant. This variant was notable for its inclusion of the matrix gene from the 2009 influenza A(H1N1) pandemic virus. While most of these confirmed cases were among children, the transmission potential and likely age-dependent susceptibility to the virus was unknown. Preliminary serologic studies indicated that very young children have less protection than older children and adults.


    Methods. 

    We construct a mathematical transmission model of influenza transmission that allows for external zoonotic exposure to infection and show how exposure and susceptibility-related factors contribute to the observed case distribution.


    Results and Conclusions. 

    Age-dependent susceptibility to infection strongly influences epidemic dynamics. The result is that the risk of an outbreak in a highly susceptible age group may be substantially higher than in an older age group with less susceptibility, but exposure-related factors must also be accounted for when interpreting case data.


    KEYWORDS: emerging infection, modeling, novel influenza, zoonosis


    PMID: 23794728 [PubMed - in process]
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