Detection &amp; Attribution of Climate Change Impacts on Human Health
Creators: name: James, Donna
name: Trust, The Wellcome
Publisher: name: F1000 Research Limited
Year: 2024

description: The purpose of this project was to define the current state-of-the-art in the detection and attribution of human health impacts of human-caused climate change, sometimes shortened as health impact attribution. As this interdisciplinary field of research has emerged over the last decade, the numbers of deaths from extreme heat, storms, floods, many climate-sensitive infectious diseases, and some other climate change-related risks has increased markedly. Health impact attribution has the potential to bring to light these growing costs of climate inaction—but only if the field can catch up to the rapidly-evolving crisis.<br>
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This report provides an overview of the field as it stands today, including reflections on the history of its evolution out of climate science; an overview of the aims and approaches of the current body of literature; a deep dive on the data and tools that have been applied to the problem so far; and suggestions on how the field could progress in the future. Throughout, we reflect on four key areas—data, tools, talent, and policy—at the heart of the Wellcome Trust’s strategy on data science for climate change and health, and we highlight opportunities in each of these areas that could help advance health impact attribution.<br>
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In the last decade, over a dozen studies have demonstrated that human-caused climate change has made the adverse health outcomes of heat waves and other natural disasters more likely or more severe, and, in some cases, increased the burden of childhood diseases and pregnancy complications. These studies only account for a small percent of published research on the health impacts of climate change, but they provide some of the best-supported evidence for contemporary impacts, and will play an important role in climate policy, including loss and damage financing and litigation.<br>
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Future work could help scientists catalogue more of the key health impacts of climate change (e.g., infectious diseases, malnutrition, and mental illness), especially in the frontline communities where investment in adaptation could make the most difference. Strategic investments in data science could help health impact attribution meet its full potential:<br>
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1. Several regions and risks are understudied due to limited high-resolution data on health outcomes across space, time, and high-risk populations. Creating new software interfaces to leverage governmental and commercial health data and enhancing efforts to mine data from published literature and historical records, could put new health impacts of climate change on the map.<br>
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2. A growing number of projects are developing and openly sharing climate models that can support impact attribution research, but processing these data requires technical expertise. Sharing more pre-processed datasets with a health focus in mind or developing open software to automate steps like bias correction, could lower the barrier to entry.<br>
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3. Few researchers are formally trained in every step of the attribution workflow and in different attribution techniques, and best practices in climate science are rapidly evolving but rarely documented. Supporting interdisciplinary teams with Global South leadership, developing standardised protocols for study design and reporting, and embracing open science practices like code sharing could build a better community of practice with the required data science expertise.