Projecting climate change impacts on health: A tutorial integrating the latest climate and demographic scenarios
気候変動が健康に与える影響の予測：最新の気候・人口シナリオを統合するチュートリアル (AI 翻訳)
Marcos Quijal-Zamorano, Pierre Masselot, Antonio Gasparrini, Ana M. Vicedo-Cabrera
🤖 gxceed AI 要約
日本語
本チュートリアルは、気候変動と人口動態のシナリオを用いた健康影響予測の手法を段階的に解説する。ロンドンの熱関連死亡率を例に、データのダウンロードから不確実性の伝搬、結果の要約までをRコード付きで提示する。再現性を重視し、政策立案や適応戦略に資する。
English
This tutorial provides a step-by-step guide for projecting health impacts under climate and demographic scenarios. Using heat-related mortality in London, it covers data processing, uncertainty propagation, and output summarization with reproducible R code. It enables researchers and policymakers to integrate evolving climate and demographic conditions for evidence-based adaptation.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本の熱中症対策や気候変動適応計画に応用可能な手法だが、ロンドンをケースとしており日本固有の文脈ではない。データ処理や不確実性の取り扱いは日本の研究者にも参考になる。
In the global GX context
This paper addresses global climate health risk modeling, relevant to IPCC and WHO frameworks. It supports climate adaptation planning, which is a component of broader sustainability, though not directly tied to GX disclosure or decarbonization pathways.
👥 読者別の含意
🔬研究者:Methodology for climate-health projections with reproducible R code, applicable to diverse settings.
🏛政策担当者:Provides a framework for evidence-based adaptation planning under future climate and demographic scenarios.
📄 Abstract（原文）
Anthropogenic climate change has led to a widespread and substantial escalation of adverse health impacts, a trend that is expected to amplify in the coming decades under current climate change projections. Thus, it is imperative to generate reliable and robust estimates of climate-sensitive health impacts in future climate change scenarios. Yet, the integration of climate-demographic scenarios and the interpretation of impact projections remain methodologically complex, highlighting the need for more thorough guidance. We present a step-by-step tutorial for conducting health impact projection studies under climate and demographic scenarios. Using heat-related mortality in London as an illustrative example, the tutorial walks the reader through the entire process: from downloading and processing observed and projected climate and demographic data to addressing core methodological challenges, including temporal and spatial alignment, propagating epidemiological and climate uncertainty, and summarizing health impact outputs. To facilitate reproducibility, the tutorial uses an open-access dataset and R code, allowing users to replicate the complete analysis or adapt it to other settings. It serves as a valuable resource for researchers and policymakers by demonstrating how demographics and climate projections jointly influence future health risks, as suggested by the Intergovernmental Panel on Climate Change. By incorporating evolving demographic and climate conditions, it enables more realistic projections of health impacts and provides a stronger foundation for evidence-based adaptation and mitigation strategies.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1097/ee9.0000000000000489first seen 2026-06-10 04:49:09 · last seen 2026-06-16 04:40:35
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