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Hauptverfasser: Bertaglia, Giulia, Iacomini, Elisa, Viguerie, Alex
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2507.20179
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author Bertaglia, Giulia
Iacomini, Elisa
Viguerie, Alex
author_facet Bertaglia, Giulia
Iacomini, Elisa
Viguerie, Alex
contents We present a two-stage methodology for reconstructing Alzheimer's disease (AD) incidence over time using ensemble Kalman inversion (EKI) applied to mortality data. In the first stage, we use EKI to infer temporal trends in all-cause and Alzheimer's-specific mortality by fitting an age-structured demographic model to observed death counts. This yields posterior estimates of evolving population structure and age-specific AD mortality rates. In the second stage, we apply a back-calculation procedure that uses these estimates, along with the hazard of AD-related death following disease onset, to infer time- and age-specific incidence rates. This reverse-inference framework enables the reconstruction of latent disease dynamics in the absence of direct incidence surveillance. By integrating demographic structure, disease-specific hazards, and observed mortality into a coherent inferential pipeline, our approach offers a principled and flexible tool for monitoring chronic disease trends and estimating historical disease burden.
format Preprint
id arxiv_https___arxiv_org_abs_2507_20179
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Ensemble-Based Estimation of Alzheimer's Disease Incidence from Dynamic Population Reconstructions
Bertaglia, Giulia
Iacomini, Elisa
Viguerie, Alex
Dynamical Systems
45Q05, 92B99, 65R99
We present a two-stage methodology for reconstructing Alzheimer's disease (AD) incidence over time using ensemble Kalman inversion (EKI) applied to mortality data. In the first stage, we use EKI to infer temporal trends in all-cause and Alzheimer's-specific mortality by fitting an age-structured demographic model to observed death counts. This yields posterior estimates of evolving population structure and age-specific AD mortality rates. In the second stage, we apply a back-calculation procedure that uses these estimates, along with the hazard of AD-related death following disease onset, to infer time- and age-specific incidence rates. This reverse-inference framework enables the reconstruction of latent disease dynamics in the absence of direct incidence surveillance. By integrating demographic structure, disease-specific hazards, and observed mortality into a coherent inferential pipeline, our approach offers a principled and flexible tool for monitoring chronic disease trends and estimating historical disease burden.
title Ensemble-Based Estimation of Alzheimer's Disease Incidence from Dynamic Population Reconstructions
topic Dynamical Systems
45Q05, 92B99, 65R99
url https://arxiv.org/abs/2507.20179