Modelling the age distribution of longevity leaders.

Gamma–Gompertz lifespan distribution Human longevity Stochastic model World’s oldest person

Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
04 Sep 2024
Historique:
received: 13 05 2024
accepted: 28 08 2024
medline: 5 9 2024
pubmed: 5 9 2024
entrez: 4 9 2024
Statut: epublish

Résumé

Human longevity leaders with remarkably long lifespan play a crucial role in the advancement of longevity research. In this paper, we propose a stochastic model to describe the evolution of the age of the oldest person in the world by a Markov process, in which we assume that the births of the individuals follow a Poisson process with increasing intensity, lifespans of individuals are independent and can be characterized by a gamma-Gompertz distribution with time-dependent parameters. We utilize a dataset of the world's oldest person title holders since 1955, and we compute the maximum likelihood estimate for the parameters iteratively by numerical integration. Based on our preliminary estimates, the model provides a good fit to the data and shows that the age of the oldest person alive increases over time in the future. The estimated parameters enable us to describe the distribution of the age of the record holder process at a future time point.

Identifiants

pubmed: 39232045
doi: 10.1038/s41598-024-71444-w
pii: 10.1038/s41598-024-71444-w
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

20592

Subventions

Organisme : National Research, Development and Innovation Office
ID : FK142124
Organisme : National Research, Development and Innovation Office
ID : FK142124
Organisme : Deutsche Forschungsgemeinschaft
ID : 460135501, NFDI 29/1

Informations de copyright

© 2024. The Author(s).

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Auteurs

Csaba Kiss (C)

Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, Műegyetem rkp. 3, 1111, Budapest, Hungary.

László Németh (L)

Weierstrass Institute for Applied Analysis and Stochastics, Mohrenstraße 39, 10117, Berlin, Germany. nemeth@wias-berlin.de.
Max Planck Institute for Demographic Research, Konrad-Zuse-Str. 1, 18057, Rostock, Germany. nemeth@wias-berlin.de.

Bálint Vető (B)

Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, Műegyetem rkp. 3, 1111, Budapest, Hungary.
ELKH-BME Stochastics Research Group, Műegyetem rkp. 3, 1111, Budapest, Hungary.

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