Active Climate, Earth & Environment Pregnancy, Children & Inherited Conditions

Tracking the impacts of climate change on maternal and child health: the Global Heat Attribution Project (GHAP)

In plain English

AI plain-English summary

A team of researchers is linking 45 million birth records from Africa, Europe, and Latin America with climate data to measure how rising temperatures harm mothers and children. This matters because while scientists know heatwaves are dangerous during pregnancy, they have not been able to pin down exactly how much of that harm is caused specifically by climate change versus natural weather variation. The Global Heat Attribution Project (GHAP) will use statistical methods and machine learning to isolate the health impacts that are directly attributable to a warming climate. This fills a gap: without clear attribution, governments lack the evidence needed to justify spending on adaptation or to hold polluters accountable. If successful, the project will produce 2–4 validated indicators that local health planners, national finance ministries, and global bodies like the Lancet Countdown can use to track heat-related harm in real time. These indicators could shift how resources are allocated—for example, directing cooling interventions to maternity wards in specific districts rather than entire countries. The team will also model which adaptation projects (such as early warning systems or shaded waiting areas) are most cost-effective. The project is not fundamental science; it is designed from the start to produce actionable policy tools.

View original technical description
Detection and attribution studies isolate health impacts specific to climate change, spotlighting the growing health, and socio-economic consequences of climate inaction, providing a baseline for long-term monitoring, and marking a step-change in climate change communication. The three-year GHAP project focuses on measuring heat impacts on maternal and child health by linking climate data with around 45 million birth records from Africa, Europe and Latin America, and upscaling data harmonisation workflows and analysis platforms. Additional data will be sourced throughout. We will develop a suite of software solutions for streamlining attribution analyses. We will use statistical approaches, such as trend-to-trend and event attribution analyses, as well as novel machine learning methodology to quantify impacts of increasing temperatures. Following an indicator-validation protocol, we will select 2-4 indicators to inform sub-national service planning, national resource allocations and global priority setting. We aim to mainstream indicators into global monitoring systems, including the Lancet Countdown. Lastly, we will model effectiveness of adaptation projects, and integrated adaptation and emissions reduction indicators. This project marks a fundamental shift in climate change action through its transdisciplinarity, unprecedented geographical coverage and analytical pipelines with actionable outputs from causal inference to policy modelling. CHANCE and GHINN mechanisms facilitate research-to-policy shifts.

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Researchers

Andrew Boulle (EPMC Awardee)Cathal Walsh (EPMC Awardee)Cathryn Birch (EPMC Awardee)Matthew Chersich (EPMC Awardee)

Related Research

Grants with similar aims, by meaning.

CHAMNHA: Climate, heat and maternal and neonatal health in Africa
CHAMNHA Climate, heat and maternal and neonatal health in Africa
Heat Indicators for Global Health: Surveillance, Early Warning Systems and adaptation-mitigation actions to reduce heat impacts in pregnant women, infants and health workers in the EU and Africa (HIGH Horizons)
Accelerating Action for Extreme Heat and Health
Heat Indicators for Global Health (HIGH Horizons): monitoring, Early Warning Systems and health facility interventions for pregnant and postpartum women, infants and young children and health workers

Original classification

Attriverse: Developing Digital Solutions for Health Impact Attribution

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