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The age pattern of increases in mortality affected by HIV

Author

Listed:
  • David Sharrow

    (University of Washington)

  • Samuel J. Clark

    (Ohio State University)

  • Mark Collinson

    (University of the Witwatersrand)

  • Kathleen Kahn

    (University of the Witwatersrand)

  • Stephen Tollman

    (University of the Witwatersrand)

Abstract

Background: We investigate the sex-age-specific changes in the mortality of a prospectively monitored rural population in South Africa. We quantify changes in the age pattern of mortality efficiently by estimating the eight parameters of the Heligman-Pollard (HP) model of age-specific mortality. In its traditional form this model is difficult to fit and does not account for uncertainty. Objective: (1) To quantify changes in the sex-age pattern of mortality experienced by a population with endemic HIV. 2. To develop and demonstrate a robust Bayesian estimation method for the HP model that accounts for uncertainty. Methods: Bayesian estimation methods are adapted to work with the HP model. Temporal changes in parameter values are related to changes in HIV prevalence. Results: Over the period when the HIV epidemic in South Africa was growing, mortality in the population described by our data increased profoundly with losses of life expectancy of ~15 years for both males and females. The temporal changes in the HP parameters reflect in a parsimonious way the changes in the age pattern of mortality. We develop a robust Bayesian method to estimate the eight parameters of the HP model and thoroughly demonstrate it. Conclusions: Changes in mortality in South Africa over the past fifteen years have been profound. The HP model can be fit well using Bayesian methods, and the results can be useful in developing a parsimonious description of changes in the age pattern of mortality. Comments: The motivating aim of this work is to develop new methods that can be useful in applying the HP eight-parameter model of age-specific mortality. We have done this and chosen an interesting application to demonstrate the new methods.

Suggested Citation

  • David Sharrow & Samuel J. Clark & Mark Collinson & Kathleen Kahn & Stephen Tollman, 2013. "The age pattern of increases in mortality affected by HIV," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(39), pages 1039-1096.
    • Handle: RePEc:dem:demres:v:29:y:2013:i:39
    DOI: 10.4054/DemRes.2013.29.39
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    References listed on IDEAS

    as
    1. Adrian E. Raftery & Le Bao, 2010. "Estimating and Projecting Trends in HIV/AIDS Generalized Epidemics Using Incremental Mixture Importance Sampling," Biometrics, The International Biometric Society, vol. 66(4), pages 1162-1173, December.
    2. Petros Dellaportas & Adrian F. M. Smith & Photis Stavropoulos, 2001. "Bayesian analysis of mortality data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(2), pages 275-291.
    3. Peter Congdon, 1993. "Statistical Graduation in Local Demographic Analysis and Projection," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 156(2), pages 237-270, March.
    4. Robert McNown & Andrei Rogers, 1989. "Forecasting Mortality: A Parameterized Time Series Approach," Demography, Springer;Population Association of America (PAA), vol. 26(4), pages 645-660, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. David J Sharrow & Samuel J Clark & Adrian E Raftery, 2014. "Modeling Age-Specific Mortality for Countries with Generalized HIV Epidemics," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-10, May.
    2. Samuel J. Clark, 2019. "A General Age-Specific Mortality Model With an Example Indexed by Child Mortality or Both Child and Adult Mortality," Demography, Springer;Population Association of America (PAA), vol. 56(3), pages 1131-1159, June.
    3. Wanying Fu & Barry R. Smith & Patrick Brewer & Sean Droms, 2022. "A New Mortality Framework to Identify Trends and Structural Changes in Mortality Improvement and Its Application in Forecasting," Risks, MDPI, vol. 10(8), pages 1-38, August.
    4. Ševčíková, Hana & Raftery, Adrian E., 2016. "bayesPop: Probabilistic Population Projections," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 75(i05).
    5. Monica Alexander & Emilio Zagheni & Magali Barbieri, 2017. "A Flexible Bayesian Model for Estimating Subnational Mortality," Demography, Springer;Population Association of America (PAA), vol. 54(6), pages 2025-2041, December.

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    More about this item

    Keywords

    HIV/AIDS; life expectancy; South Africa; Bayesian inference;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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