Priority climate and health modelling needs.

Ebi, Kristie L; Bi, Peng; Bowen, Kathryn; Brauer, Michael; Chua, Paul LC; Colón-González, Felipe J; Dimitrova, Asya; Gasparrini, AntonioORCID logo; Gouveia, Nelson; Hajat, ShakoorORCID logo; +26 more...Hamilton, Ian; Harper, Sherilee; Hasegawa, Tomoko; Hashizume, Masahiro; Heaviside, Clare; Honda, Yasushi; Green, Carole; Jack, Chris; Kim, Ho; Kinney, Patrick; Kone, Brama; Kovats, Sari; Lloyd, Simon J; Morse, Andrew P; Ogden, Nicholas H; Paz, Shlomit; Price, Jeff; Ryan, Sadie J; Semenza, Jan C; Sheehan, Timothy; Taylor, Rachael; van Ruijven, Bas; Vicedo-Cabrera, Ana Maria; Warren, Rachel; Zaitchik, Ben; and Hess, Jeremy J (2025) Priority climate and health modelling needs. The Lancet Planetary Health. 101297-. ISSN 2542-5196 DOI: 10.1016/j.lanplh.2025.101297 (In Press)
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Climate and health modelling is necessary for improving understanding of the current and future distribution and timing of climate-related health risks. However, underinvestment in this area has limited the understanding required to inform policies that enable multisectoral interventions to safeguard health. We synthesised insights from a survey of 65 global climate and health modelling experts and 36 participants in a hybrid meeting to identify priority strategies for enhancing the validity, utility, and policy relevance of climate and health models. Foundational investments to support modelling included strengthening research capacity, establishing a network of multinational centres of excellence for transdisciplinary research and capacity building, improving data collection and sharing infrastructure, investing in scenario development and quantitative elaboration, assessing adaptation effectiveness, and committing to intermodel comparisons and interdisciplinary modelling activities. Specific recommendations included updating the 2014 WHO Quantitative Risk Assessment to cover a wider range of causal pathways and health endpoints, using interdisciplinary methods that facilitate model intercomparisons. Additional recommendations included supporting modelling of a broader set of climate-health outcomes, developing models to support early warning systems and investments in their implementation, evaluation, and maintenance, and improving health system capacity for modelling in low-resource settings.


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