AI models predict diarrheal disease outbreaks related to climate change

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Extreme weather events related to climate change, such as massive floods and prolonged droughts, often cause dangerous outbreaks of diarrheal diseases, especially in developing countries, and diarrheal diseases are the third leading cause of death in young children. It becomes.
A study published in Environmental Research Letters on October 22, 2024, by an international research team led by senior author Amir Sapkota of the University of Maryland School of Public Health (UMD SPH), shows that the risk of such a deadly outbreak is Provide a way to predict. Using AI modeling, we give public health systems weeks and even months to prepare and save lives.
“The increase in extreme weather events related to climate change will continue for the foreseeable future, and we must adapt as a society,” said Sapkota, director of SPH’s Department of Epidemiology and Biostatistics. “The early warning system outlined in this study is a step toward increasing community resilience to the health threats posed by climate change.”
An interdisciplinary team working across multiple institutions will study temperature, precipitation, historical disease incidence, El Niño climate patterns, and other It depended on geographical and environmental factors. Researchers trained an AI-based model that can predict community-level disease burden weeks to months in advance.
“Knowing the expected disease burden weeks to months in advance gives public health workers critical time to prepare, so they can respond when the time comes. We will be ready,” Sapkota said.
Although the study focused on Nepal, Vietnam and Taiwan, “our findings are also highly relevant to other parts of the world, particularly where communities lack access to municipal drinking water and sanitation systems.” ,” said Raul, lead author of the study. Kurtz Cano, associate professor at the Indiana University School of Public Health in Bloomington;
Sapkota said the ability of AI to handle large datasets means this study is the first of many that he hopes will further improve the accuracy of predictive models for early warning systems. said. He hopes this will help public health systems be better prepared to protect communities from the increased risk of diarrhea outbreaks.
The team responsible for the research came from a wide range of disciplines, including atmospheric and ocean sciences, community health research, and water resources engineering. The research team includes UMD’s Department of Epidemiology and Biostatistics and School of Atmospheric and Oceanic Sciences, Indiana University School of Public Health in Bloomington, Nepal Health Research Council, Hue University of Medicine and Pharmacy in Vietnam, Lund University in Sweden and Chung Yuan University in Taiwan. .
Further information: Raul Cruz Cano et al. A prototype early warning system for diarrheal diseases to combat the health threats of climate change in the Asia-Pacific region, Environment Research Letters (2024). DOI: 10.1088/1748-9326/ad8366
Provided by University of Maryland
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