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Lifesaving, delayed deaths and cure in mortality modeling

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  • Finkelstein, Maxim

Abstract

We generalize the lifesaving model to the case when the probability of lifesaving depends on the number of lifesavings in the past. We also suggest a new approach to analyzing the shape of mortality rates based on considering delays in deaths (and possible cure afterwards) which results in the decline of mortality rates. The derived lifetime distribution and the corresponding mortality rate can be used for a more flexible statistical analysis of mortality data.

Suggested Citation

  • Finkelstein, Maxim, 2013. "Lifesaving, delayed deaths and cure in mortality modeling," Theoretical Population Biology, Elsevier, vol. 83(C), pages 15-19.
    • Handle: RePEc:eee:thpobi:v:83:y:2013:i:c:p:15-19
    DOI: 10.1016/j.tpb.2012.10.005
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    References listed on IDEAS

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    1. Maxim Finkelstein, 2012. "Discussing the Strehler-Mildvan model of mortality," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 26(9), pages 191-206.
    2. Finkelstein, Maxim, 2012. "On ordered subpopulations and population mortality at advanced ages," Theoretical Population Biology, Elsevier, vol. 81(4), pages 292-299.
    3. James Vaupel & Anatoli Yashin, 1987. "Repeated resuscitation: How lifesaving alters life tables," Demography, Springer;Population Association of America (PAA), vol. 24(1), pages 123-135, February.
    4. John Bongaarts & Griffith Feeney, 2002. "How Long Do We Live?," Population and Development Review, The Population Council, Inc., vol. 28(1), pages 13-29, March.
    5. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
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    Cited by:

    1. Carl Schmertmann, 2020. "Revivorship and life lost to mortality," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(17), pages 497-512.

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