harbidel/DEPRESSION-PREDICTION

The World Health Organization estimates that 1.3 million Kenyans suffer from untreated major depressive disorder (MDD; commonly known as depression) every year, and that sub-Saharan Africa has the highest prevalence of the illness of any region in the world. Yet mental health treatment in Kenya suffers from a lack of resources and stigmatization. There are only two certified psychiatrists per million people in Kenya. Few facilities exist outside of urban areas and people are unlikely to know about or access them. Can machine learning help alleviate this problem? Smart targeting of potential cases could help enable scarce resources to reach those who most need it and improve or save an untold number of lives. # DEPRESSION-PREDICTION The World Health Organization estimates that 1.3 million Kenyans suffer from untreated major depressive disorder (MDD; commonly known as depression) every year, and that sub-Saharan Africa has the highest prevalence of the illness of any region in the world. Yet mental health treatment in Kenya suffers from a lack of resources and stigmatization. There are only two certified psychiatrists per million people in Kenya. Few facilities exist outside of urban areas and people are unlikely to know about or access them. Can machine learning help alleviate this problem? Smart targeting of potential cases could help enable scarce resources to reach those who most need it and improve or save an untold number of lives. With this in mind, the Busara Center for Behavioral Economics has decided to challenge the data science community in Nairobi, across Africa, and around the world to predict depression cases from routine survey data. A model which accurately predicts which individuals are likely to be depressed from the survey data could be used by mental health providers such as local clinics, NGOs or community health volunteers to reach out to those at risk. We look forward to your solutions to this pressing problem.