A Machine Learning Based Analysis Between Climate Change and Human Health: A Correlational Study

Climate change has huge impact in human health. Social and environmental determinants of health are affected by climate change. According to World Health Organization (WHO) states that the strokes, most heart diseases, cancers, diabetes, chronic kidney diseases are the top causes of death. Although there are direct factors behind these diseases, climate change could have an invisible role in the rise of these diseases. Researchers are using various technologies to find correlations between climate change and human health, particularly trying to find out which elements of the weather are more responsible. Although there are explicit reasons for the formation of these diseases. But few studies have been conducted on passive factors that have a hidden but serious effect on the formation of these diseases. In this regard, machine learning approach can help us to correlate between the features of climate and various human diseases. Following that, the study uses Pearson, Spearman and Phi-K algorithms to determine the possibilities of correlation between human health and climate change. The research states that Carbon Monoxide (CO) have 98% of correlation and carbon dioxide (CO2) has 95% of correlation with cardiovascular disease (Ca).