Statistical Machine Learning in Environmental Health

The project employs Statistics and Machine learning techniques to analyze the influence of environmental factors, such as air pollution, on public health. Studies reveal strong correlations between exposure to pollutants and the severity of health outcomes, particularly during the COVID-19 pandemic. Research findings indicate that socio-economic and environmental determinants critically affect disease spread and severity. By integrating various data sources, the project aims to enhance predictive models for better health risk assessments. This multidisciplinary approach underscores the importance of addressing environmental health challenges through advanced statistical learning methodologies.