Modelling cause-of-death mortality and the impact of cause-elimination

Alai, Daniel H. and Arnold (-Gaille), Séverine and Sherris, Michael (2015) Modelling cause-of-death mortality and the impact of cause-elimination. Annals of Actuarial Science, 9 (1). pp. 167-186. ISSN 1748-4995. (doi:https://doi.org/10.1017/S174849951400027X) (Full text available)

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http://dx.doi.org/10.1017/S174849951400027X

Abstract

The analysis of causal mortality provides rich insight into changes in mortality trends that are hidden in population-level data. Therefore, we develop and apply a multinomial logistic framework to model causal mortality. We use internationally classified cause-of-death categories and data obtained from the World Health Organization. Inherent dependence amongst the competing causes is accounted for in the framework, which also allows us to investigate the effects of improvements in, or the elimination of, cause-specific mortality. This has applications to scenario-based forecasting often used to assess the impact of changes in mortality. The multinomial model is shown to be more conservative than commonly used approaches based on the force of mortality. We use the model to demonstrate the impact of cause-elimination on aggregate mortality using residual life expectancy and apply the model to a French case study.

Item Type: Article
Uncontrolled keywords: Cause-of-death mortality; Multinomial logistic regression; Cause-elimination; Life expectancy; Mortality forecasts
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Actuarial Science
Depositing User: Daniel Alai
Date Deposited: 05 Jan 2015 17:07 UTC
Last Modified: 20 Mar 2018 15:55 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/46493 (The current URI for this page, for reference purposes)
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