Assessing climate-driven mortality risk has become an emerging area of research in recent decades. In this paper, we propose a novel approach to explicitly incorporate climate-driven effects into both single- and multi-population stochastic mortality models. The new model consists of two components: a stochastic mortality model, and a distributed lag non-linear model (DLNM). The stochastic component captures the non-climate long-term trend, volatility, and seasonal patterns in mortality rates. The DLNM component captures non-linear and lagged effects of climate variables on mortality, as well as the impact of heat waves and cold waves across different age groups. For model calibration, we propose a novel backfitting algorithm that allows us to disentangle the climate-driven mortality risk from the non-climate-driven stochastic mortality risk. We illustrate the effectiveness and improved short-term (1--18 month) forecasting performance of our model against four alternative models, using data from three European regions: Athens, Lisbon, and Rome. Furthermore, as an application of the proposed modeling framework, we utilize future UTCI data generated from climate models to provide total mortality forecasts into 2045 across these regions under two Representative Concentration Pathway (RCP) scenarios, taking both stochastic mortality improvement trend and climate risk into account. The projections show a noticeable decrease in winter mortality alongside a rise in summer mortality, driven by a general increase in UTCI over time. Although we expect slightly lower overall mortality in the short term under RCP8.5 compared to RCP2.6, a long-term increase in total mortality is anticipated under the RCP8.5 scenario.

翻译：近几十年来，评估气候驱动的死亡风险已成为一个新兴研究领域。本文提出一种新方法，将气候驱动效应明确纳入单种群和多种群随机死亡率模型中。新模型由两个组成部分构成：随机死亡率模型和分布滞后非线性模型（DLNM）。随机成分捕捉死亡率中的非气候长期趋势、波动性和季节性模式；DLNM成分则捕捉气候变量对死亡率的非线性和滞后效应，以及热浪和寒潮对不同年龄组的影响。在模型校准方面，我们提出一种新的回拟合算法，能够将气候驱动的死亡风险与非气候驱动的随机死亡风险分离开来。利用雅典、里斯本和罗马三个欧洲地区的数据，我们展示了模型相较于四个替代模型的有效性及在短期（1-18个月）预测性能上的改进。此外，作为模型框架的应用，我们利用气候模型生成的未来UTCI数据，在两种代表性浓度路径（RCP）情景下，综合考虑随机死亡率改善趋势和气候风险，提供了这些地区至2045年的总死亡率预测。预测显示，随着UTCI随时间普遍升高，冬季死亡率显著下降，夏季死亡率上升。尽管在RCP8.5情景下，我们预计短期内总死亡率略低于RCP2.6情景，但长期来看，RCP8.5情景下的总死亡率预计将上升。