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    The future excess fraction model for calculating burden of disease

    240977_240977.pdf (493.4Kb)
    Access Status
    Open access
    Authors
    Fritschi, Lin
    Chan, J.
    Hutchings, S.
    Driscoll, T.
    Wong, A.
    Carey, Renee
    Date
    2016
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Fritschi, L. and Chan, J. and Hutchings, S. and Driscoll, T. and Wong, A. and Carey, R. 2016. The future excess fraction model for calculating burden of disease. BMC Public Health. 16 (1): 386.
    Source Title
    BMC Public Health
    DOI
    10.1186/s12889-016-3066-1
    ISSN
    1471-2458
    School
    Epidemiology and Biostatistics
    Remarks

    This open access article is distributed under the Creative Commons license http://creativecommons.org/licenses/by/4.0/

    URI
    http://hdl.handle.net/20.500.11937/20272
    Collection
    • Curtin Research Publications
    Abstract

    BACKGROUND: Estimates of the burden of disease caused by a particular agent are used to assist in making policy and prioritizing actions. Most estimations have employed the attributable fraction approach, which estimates the proportion of disease cases or deaths in a specific year which are attributable to past exposure to a particular agent. While this approach has proven extremely useful in quantifying health effects, it requires historical data on exposures which are not always available. METHODS: We present an alternative method, the future excess fraction method, which is based on the lifetime risk approach, and which requires current rather than historical exposure data. This method estimates the future number of exposure-related disease cases or deaths occurring in the subgroup of the population who were exposed to the particular agent in a specific year. We explain this method and use publically-available data on current asbestos exposure and mesothelioma incidence to demonstrate the use of the method. CONCLUSIONS: Our approach to modelling burden of disease is useful when there are no historical measures of exposure and where future disease rates can be projected on person years at risk.

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