Identifying the impact of global warming on population using a clustering based approach

Being one of the contemporary world´s problems, global warming is a complex phenomenon with unavoidable immediate and long-term effects on human health. So far, population health has been little addressed by relating it to the global warming phenomenon. However, the reality of recent years has alerted the medical scientific community on the need to establish how aspects of human pathology are influenced/conditioned by environmental factors altered by global warming. In this paper we are focusing on the problem of identifying populational groups with high risks in the context of global warming. In this direction, a clustering based approach is introduced and an hierarchical agglomerative clustering algorithm is developed. Our approach can be useful in assisting physicians in detecting patients for which special profilactic measures should be developed. An experimental evaluation of the proposed algorithm on a simple case study is provided, emphasizing the potential of our approach.