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Machine-Learning Model for Risk Estimation and Risk Prediction of the Effects of Climate and Air Pollution on Respiratory Disease in Addis Ababa, Ethiopia

Fiseha Wadilo of Armauer Hansen Research Institute in Ethiopia will develop a machine learning model that integrates meteorological and air pollution data with public health data to predict the occurrence of respiratory diseases, enhancing the existing surveillance system in Ethiopia. Meteorological data will encompass seasonal variation in temperature, precipitation, and humidity. Public health data will include information from hospital visits and admissions for respiratory diseases in health facilities in Addis Ababa. The predictive model will serve to better identify the underlying risk factors for respiratory diseases, while helping predict their occurrence to guide preventive measures. The model will be integrated into the existing surveillance system in Ethiopia for influenza-like illnesses and severe acute respiratory infections.

More information about Grand Challenges Ethiopia: Accelerating Catalyzing Solutions for Climate Change's Impact on Health

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