Prevalence Projections of Chronic Diseases and Impact of Public Health Intervention

Authors

  • Pierre Joly,

    Corresponding author
    1. University of Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
    2. INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
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  • Célia Touraine,

    Corresponding author
    1. University of Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
    2. INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
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  • Aurore Georget,

    1. University of Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
    2. INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
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  • Jean-François Dartigues,

    1. University of Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
    2. INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
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  • Daniel Commenges,

    1. University of Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
    2. INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
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  • Hélène Jacqmin-Gadda

    1. University of Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
    2. INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France
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Summary

The estimation of future prevalences of chronic diseases is essential for public health policy. Using incidence estimates from cohort data and demographic projections for general mortality and population sizes, we propose a method based on a general illness–death model to make prevalence projections for chronic diseases. In contrast to previously published methods, we account for differences between global mortality and mortality of healthy subjects and compare two assumptions regarding the secular trend for mortality of diseased subjects. Then we develop a methodology to estimate changes in future disease prevalences resulting from prevention campaign to reduce the frequency or the excess risk associated with a risk factor. The methods are applied for estimating dementia prevalence in France between 2010 and 2030.

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