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Effect of the COVID-19 frailty heterogeneity on the future evolution of mortality by stratified weighting

Author

Listed:
  • Maria CARANNANTE

    (Difarma Department, University of Salerno)

  • Valeria D’AMATO

    (Difarma Department, University of Salerno)

  • Steven HABERMAN

    (Department Faculty of Actuarial Science and Insurance, Bayes (formerly Cass) Business School, City, University of London)

Abstract

The starting point of our research is the inadequacy of assuming, in the construction of a model of mortality, that frailty is constant for the individuals comprising a demographic population. This assumption is implicitly made by standard life table techniques. The substantial differences in the individual susceptibility to specific causes of death lead to heterogeneity in frailty, and this can have a material effect on mortality models and projections—specifically a bias due to the underestimation of longevity improvements. Given these considerations, in order to overcome the misrepresentation of the future mortality evolution, we develop a stochastic model based on a stratification weighting mechanism, which takes into account heterogeneity in frailty. Furthermore, the stratified stochastic model has been adapted also to capture COVID-19 frailty heterogeneity, that is a frailty worsening due to the COVID-19 virus. Based on different frailty levels characterizing a population, which affect mortality differentials, the analysis allows for forecasting the temporary excess of deaths by the stratification schemes in a stochastic environment.

Suggested Citation

  • Maria CARANNANTE & Valeria D’AMATO & Steven HABERMAN, 2023. "Effect of the COVID-19 frailty heterogeneity on the future evolution of mortality by stratified weighting," JODE - Journal of Demographic Economics, Cambridge University Press, vol. 89(3), pages 513-532, September.
    • Handle: RePEc:ctl:louvde:v:89:y:2023:i:3:p:513-532
    DOI: 10.1017/dem.2023.4
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