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Multi-country clustering-based forecasting of healthy life expectancy
Healthy life expectancy (HLE) is an indicator that measures the number of years individuals at a given age are expected to live free of disease or disability. HLE forecasting is essential for planning the provision of health care to elderly populations and appropriately pricing Long Term Care insura...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840427/ https://www.ncbi.nlm.nih.gov/pubmed/36685054 http://dx.doi.org/10.1007/s11135-022-01611-6 |
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author | Levantesi, Susanna Nigri, Andrea Piscopo, Gabriella Spelta, Alessandro |
author_facet | Levantesi, Susanna Nigri, Andrea Piscopo, Gabriella Spelta, Alessandro |
author_sort | Levantesi, Susanna |
collection | PubMed |
description | Healthy life expectancy (HLE) is an indicator that measures the number of years individuals at a given age are expected to live free of disease or disability. HLE forecasting is essential for planning the provision of health care to elderly populations and appropriately pricing Long Term Care insurance products. In this paper, we propose a methodology that simultaneously forecasts HLE for groups of countries and allows for investigating similarities in their HLE patterns. We firstly apply a functional data clustering to the multivariate time series of HLE at birth of different countries for the years 1990–2019 provided by the Global Burden of Disease Study. Three clusters are identified for both genders. Then, we carry out the HLE simultaneous forecasting of the populations within each cluster by a multivariate random walk with drift. Numerical results and the statistical significance of the parameters of the identified multivariate processes are shown. Demographic evidences on the different evolution of HLE between countries are commented. |
format | Online Article Text |
id | pubmed-9840427 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-98404272023-01-17 Multi-country clustering-based forecasting of healthy life expectancy Levantesi, Susanna Nigri, Andrea Piscopo, Gabriella Spelta, Alessandro Qual Quant Article Healthy life expectancy (HLE) is an indicator that measures the number of years individuals at a given age are expected to live free of disease or disability. HLE forecasting is essential for planning the provision of health care to elderly populations and appropriately pricing Long Term Care insurance products. In this paper, we propose a methodology that simultaneously forecasts HLE for groups of countries and allows for investigating similarities in their HLE patterns. We firstly apply a functional data clustering to the multivariate time series of HLE at birth of different countries for the years 1990–2019 provided by the Global Burden of Disease Study. Three clusters are identified for both genders. Then, we carry out the HLE simultaneous forecasting of the populations within each cluster by a multivariate random walk with drift. Numerical results and the statistical significance of the parameters of the identified multivariate processes are shown. Demographic evidences on the different evolution of HLE between countries are commented. Springer Netherlands 2023-01-14 /pmc/articles/PMC9840427/ /pubmed/36685054 http://dx.doi.org/10.1007/s11135-022-01611-6 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Levantesi, Susanna Nigri, Andrea Piscopo, Gabriella Spelta, Alessandro Multi-country clustering-based forecasting of healthy life expectancy |
title | Multi-country clustering-based forecasting of healthy life expectancy |
title_full | Multi-country clustering-based forecasting of healthy life expectancy |
title_fullStr | Multi-country clustering-based forecasting of healthy life expectancy |
title_full_unstemmed | Multi-country clustering-based forecasting of healthy life expectancy |
title_short | Multi-country clustering-based forecasting of healthy life expectancy |
title_sort | multi-country clustering-based forecasting of healthy life expectancy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840427/ https://www.ncbi.nlm.nih.gov/pubmed/36685054 http://dx.doi.org/10.1007/s11135-022-01611-6 |
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