Granular mortality modeling with temperature and epidemic shocks: a three-state regime-switching approach

Jens Robben (), Karim Barigou and Torsten Kleinow
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Jens Robben: University of Amsterdam
Karim Barigou: Université catholique de Louvain, LIDAM/ISBA, Belgium
Torsten Kleinow: University of Amsterdam

No 2026013, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: This paper develops a granular regime-switching framework to model mortality deviations from seasonal baseline trends driven by temperature and epidemic shocks. The framework features three states: (1) a baseline state that captures observed seasonal mortality patterns, (2) a summer shock state that captures heat waves and other high mortality events, and (3) a winter shock state that addresses mortality deviations caused by cold spells and strong outbreaks of respiratory diseases due to influenza and COVID-19. Transition probabilities between states are modeled using covariate-dependent multinomial logit functions. These functions incorporate, among others, lagged temperature and influenza incidence rates as predictors, allowing dynamic adjustments to evolving shocks. Calibrated on weekly mortality data across 21 French regions and six age groups, the regime-switching framework accounts for spatial and demographic heterogeneity. Under various projection scenarios for temperature and influenza, we quantify uncertainty in mortality forecasts through prediction intervals constructed using an extensive bootstrap approach. These projections can guide insurance companies, healthcare providers, and hospitals in managing risks and planning resources for potential future shocks.

Keywords: Granular mortality; Regime-switching; Environmental shocks; Respiratory shocks (search for similar items in EconPapers)
Pages: 18
Date: 2026-04-17
Note: In: Insurance Mathematics and Economics, 2026, vol. 128, 103250
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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvar:2026013

DOI: 10.1016/j.insmatheco.2026.103250

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