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    Choosing an epidemiological model structure for the economic evaluation of non-communicable disease public health interventions

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    Author
    Briggs, ADM; Wolstenholme, J; Blakely, T; Scarborough, P
    Date
    2016-05-04
    Source Title
    Population Health Metrics
    Publisher
    BMC
    University of Melbourne Author/s
    Blakely, Antony
    Affiliation
    Melbourne School of Population and Global Health
    Metadata
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    Document Type
    Journal Article
    Citations
    Briggs, A. D. M., Wolstenholme, J., Blakely, T. & Scarborough, P. (2016). Choosing an epidemiological model structure for the economic evaluation of non-communicable disease public health interventions. POPULATION HEALTH METRICS, 14 (1), https://doi.org/10.1186/s12963-016-0085-1.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/257378
    DOI
    10.1186/s12963-016-0085-1
    Abstract
    Non-communicable diseases are the leading global causes of mortality and morbidity. Growing pressures on health services and on social care have led to increasing calls for a greater emphasis to be placed on prevention. In order for decisionmakers to make informed judgements about how to best spend finite public health resources, they must be able to quantify the anticipated costs, benefits, and opportunity costs of each prevention option available. This review presents a taxonomy of epidemiological model structures and applies it to the economic evaluation of public health interventions for non-communicable diseases. Through a novel discussion of the pros and cons of model structures and examples of their application to public health interventions, it suggests that individual-level models may be better than population-level models for estimating the effects of population heterogeneity. Furthermore, model structures allowing for interactions between populations, their environment, and time are often better suited to complex multifaceted interventions. Other influences on the choice of model structure include time and available resources, and the availability and relevance of previously developed models. This review will help guide modelers in the emerging field of public health economic modeling of non-communicable diseases.

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