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Priority climate and health modelling needs

delete2025-09-13
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PRE
AI
K
Kristie L. Ebi *
P
Peng Bi
K
Kathryn Bowen
M
Michael Bräuer
P
Paul Lester Chua
F
Felipe J. Colón‐González
A
Asya Dimitrova
A
Antonio Gasparrini
N
Nélson Gouveia
S
Shakoor Hajat
I
Ian Hamilton
S
Sherilee L. Harper
T
Tomoko Hasegawa
M
Masahiro Hashizume
C
Clare Heaviside
Y
Yasushi Honda
C
Carole Green
C
Chris Jack
H
Ho Kim
P
Patrick Kinney
B
Brama Koné
S
Sari Kovats
S
Simon J Lloyd
A
Andrew P. Morse
N
Nicholas H. Ogden
S
Shlomit Paz
J
Jeff Price
S
Sadie J. Ryan
J
Jan C. Semenza
R
Rachael C Taylor
B
Bas van Ruijven
A
Ana María Vicedo-Cabrera
R
Rachel Warren
B
Ben Zaitchik
J
Jeremy Hess
DOI:10.1016/j.lanplh.2025.101297delete
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Abstract

Abstract

En 中文
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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T
The Lancet Planetary Health
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0
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121
Citations:
0

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