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.
Quijal-Zamorano et al. (Mon,) studied this question.