Health Technologies

How AI could help to protect against extreme weather’s impact on disease

Climate change-related extreme weather, such as massive flooding and prolonged drought, can lead to dangerous outbreaks of diarrheal diseases particularly in less developed countries – where diarrheal diseases is the third leading cause of death among young children. Now AI is being harnessed to help health systems prepare for, and better deal with, such outbreaks.

An international team of researchers has devised an AI modeling system that could give public health systems weeks or even months to prepare and to save lives.

Working across several institutions, their model relies on temperature, precipitation, previous disease rates, El Niño climate patterns as well as other geographic and environmental factors in three countries – Nepal, Taiwan, and Vietnam – between 2000 and 2019.

Using this data, the researchers trained AI-based models that can predict area-level disease burden with weeks to months ahead of time.

The project was led by senior author from University of Maryland’s School of Public Health (UMD SPH) Amir Sapkota, who said: “Increases in extreme weather events related to climate change will only continue in the foreseeable future. We must adapt as a society.

“The early warning systems outlined in this research are a step in that direction to enhance community resilience to the health threats posed by climate change.

“Knowing expected disease burden weeks to months ahead of time provides public health practitioners crucial time to prepare. This way they are better prepared to respond, when the time comes.”

While the study focused on Nepal, Vietnam, and Taiwan, the findings are “quite applicable to other parts of the world as well, particularly areas where communities lack access to municipal drinking water and functioning sanitation systems,” the researchers said.

They added that AI’s ability to work with huge data sets means that this study is an early step among many that could result in increasingly accurate predictive models for early warning systems.

Sapkota added that this will allow public health systems to prepare communities to protect themselves from a heightened risk of diarrheal outbreaks.

Other institutions involved in the project include Indiana University School of Public Health in Bloomington, the Nepal Health Research Council, the Hue University of Medicine and Pharmacy in Vietnam, Lund University in Sweden, and Chung Yuan Christian University in Taiwan.

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