Projecting climate change impacts on health: A tutorial integrating the latest climate and demographic scenarios.
気候変動の健康への影響予測：最新の気候・人口統計シナリオを統合したチュートリアル (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研究の方法論をステップバイステップで解説する。ロンドンの熱関連死亡を例に、データの取得・処理、不確実性の取り扱い、結果の解釈までを実践的に示す。再現可能なRコードとオープンデータを用いており、研究者や政策立案者が適応策の基礎として活用できる。
English
This tutorial provides a step-by-step methodology for projecting health impacts under climate and demographic scenarios, using heat-related mortality in London as an example. It covers data acquisition, processing, uncertainty propagation, and interpretation, with reproducible R code. Aimed at researchers and policymakers for evidence-based adaptation planning.
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
日本では熱中症対策が重要課題であり、本チュートリアルで示される手法は、国内の地域別・年齢別の健康影響予測に応用可能。国や自治体の適応計画策定に資する。
In the global GX context
This tutorial offers a reproducible framework for climate-health impact projections, relevant for global adaptation planning under IPCC scenarios. It integrates demographic changes, which is crucial for realistic risk assessments in regions like Europe and North America.
👥 読者別の含意
🔬研究者:Provides a reproducible methodological pipeline for climate-health projection studies.
🏢実務担当者:Can be used by public health agencies to adapt heat warning systems and intervention planning.
🏛政策担当者:Demonstrates how demographic trends and climate scenarios jointly affect future health burdens, informing adaptation policy.
📄 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/10.48620/98320first seen 2026-06-21 05:06:41
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