Harnessing the power of machine learning to link climate change and health

For the first time, researchers from the London School of Hygiene & Tropical Medicine, Mercator Research Institute on Global Commons and Climate Change and the University of Leeds deploy machine learning algorithms to scan evidence on climate change and health across the world. Funded by the Foreign, Commonwealth and Development Office, they used machine learning to map the global published evidence on climate change, weather and health from 2013 to 2020 and produce an online interactive results platform. The approach identified the effects on health of air quality and heat to be the most frequently studied in an evidence base dominated by studies from high-income countries and China. There is currently very limited evidence from low- and middle-income countries that suffer most from the health consequences of climate change. Evidence on the impact of climate change on mental health and on maternal and child health is extremely limited.