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    Identification of Influenza Cases During the H1N1 Pandemic in Massachusetts Using Population-Based Hospital Discharge Data

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    Authors
    Placzek, Hilary
    Madoff, Lawrence C.
    Student Authors
    Hilary Placzek
    UMass Chan Affiliations
    Department of Medicine, Division of Infectious Diseases and Immunology
    Document Type
    Journal Article
    Publication Date
    2011-08-14
    Keywords
    Influenza, Human; Influenza A Virus, H1N1 Subtype; Hospitalization; Epidemiologic Factors; Massachusetts
    Immunology and Infectious Disease
    Influenza Humans
    Life Sciences
    Medicine and Health Sciences
    Public Health
    
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    Link to Full Text
    http://dx.doi.org/10.1371/currents.RRN1256
    Abstract
    Objectives: (1) To characterize the epidemiology of H1N1-related hospitalizations in Massachusetts; and (2) to compare characteristics of those hospitalized during periods of seasonal influenza activity and during the H1N1 pandemic. Methods: Authors applied maximum and minimum criteria to the Massachusetts Hospital Discharge Database to identify H1N1-related hospitalizations. They constructed annual line graphs describing mean frequencies of influenza-like illness(ILI)-related discharges between 2005-2008, and compared these rates to early waves of H1N1 in 2009. Results: During spring and summer 2009, there were significantly higher rates of ILI-related hospital discharges in Massachusetts compared to 2005-2008. Out of 359,344 total discharges between April 26-September 30,2009, H1N1-related hospitalizations ranged from 601 to 10,967 cases. Minimum criteria confirmed that H1N1 affected a younger population (50% were <18>years), with higher rates among African-Americans (18%) and Hispanics (23%) and higher rates of ICU admission (21%) compared to seasonal influenza (39%, 10%, 14%, and 17% respectively). Conclusions: This is the first population-based assessment of epidemiological characteristics of hospitalized H1N1 cases in Massachusetts, and it is the first to include all possible hospitalized cases in the analysis. The authors confirm that large administrative data sets can detect hospitalizations for influenza during a pandemic, but estimated case counts vary widely depending on selection criteria used. Maximum criteria overestimated H1N1 activity, and those meeting minimum criteria resemble published accounts of H1N1-related hospitalizations closely.
    Source
    PLoS Curr. 2011 Aug 14;3:RRN1256. Link to article on publisher's website
    DOI
    10.1371/currents.RRN1256
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/33213
    PubMed ID
    21858253
    Related Resources
    Link to article in PubMed
    Rights
    This research note is distributed under the Creative Commons Attribution 3.0 license.
    ae974a485f413a2113503eed53cd6c53
    10.1371/currents.RRN1256
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