Abstract

• Mental health includes emotional, psychological, and social well-being. As the coronavirus pandemic has spread across the world, the public health crisis has brought with it considerable impact on social and economic. Besides physical health, the psychological impacts of COVID-19 also pose significant risks to mental-wellbeing as the greater levels of stress, depression and anxiety in people. In this paper, patterns of mental health were discovered using public data by machine learning approach. The main contribution of this paper is to provide awareness and nature of mental health to determine the factors that influence mental health across people's lifespans (e.g. genetics, cognition, demographics). This research use three machine learning classifiers: decision tree, random forest and k-nearest neighbour (KNN). The experimental results found that Random Forest classifier achieves the best accuracy.