Objective: This research aims to explore the relationship between climate change and public health, focusing on how environmental changes affect health outcomes across diverse populations.

Methodology: We employ a multidisciplinary approach, integrating data from epidemiological studies, climate models, and health surveys. Advanced data analysis using artificial neural networks (ANNs) will be utilized to assess both direct and indirect health effects related to climate change.

Results and Discussion: Key areas of investigation include the rise in respiratory diseases due to air pollution, the spread of vector-borne diseases, and the mental health impacts associated with climate-related disasters. The ANN model will identify patterns and correlations in the data, enhancing our understanding of these health risks.

Conclusion: The findings aim to provide a comprehensive overview of the health implications of climate change, offering evidence-based recommendations for public health policies and interventions. Ultimately, this research seeks to inform stakeholders and policymakers about the urgent need to address these health challenges and promote adaptive strategies to protect vulnerable populations.

Key words: Climate models, Public health, , health surveys, ANN modeling.