Daniel Vigo
Academic Rank(s)
Associate Professor MD, Lic. Psych, DrPH
Phone
604-822-2772
daniel.vigo@ubc.ca
Location
2206 East Mall Vancouver, BC V6T 1Z3
Dr. Vigo is a psychiatrist, licentiate in psychology, and public health specialist, originally from Argentina. In addition to being an Associate Professor at UBC, he serves as the BC’s Chief Scientific Advisor for Psychiatry, Toxic Drugs & Concurrent Disorders, Provincial Medical Lead of the BC Advanced Practice for Assertive Community Treatment, Medical Lead for Tertiary Care for the Regional Mental Health and Substance Use Program at Vancouver Coastal Health, as well as a psychiatrist in an assertive community treatment team.
He has worked in multiple clinical, research, teaching, and leadership roles across the public and private sector, and has published peer-reviewed articles, book chapters, and reports on public health, health systems, global mental health, psychiatric epidemiology, psychopharmacology, psychotherapy, and e-mental health. Dr. Vigo also leads several projects in BC and globally, including on E-Mental Health for University Students, Needs-Based Planning for Mental and Substance Use Disorder Services, and as Chair of the Services and Policy Workgroup of the WHO-World Mental Health Surveys Initiative, the largest global research group producing primary psychiatric epidemiology data.
More information can be found at Dr. Vigo’s Mental Health Systems and Services Laboratory webpage.
Chair, Services and Policy Workgroup of the WHO-World Mental Health Surveys Initiative
Scientist, Centre for Advancing Health Outcomes
Dr. Vigo leads several projects at UBC, including the Needs-Based Planning for Mental and Substance Use Disorder Project, the Student E-Mental Health Project, and several psychiatric epidemiology studies of regional, national, and global scope. The goal of his e-Mental Health portfolio (which includes CIHR and Health Canada funded projects) is to create, administer and evaluate online e-interventions and screening tools, as well as to integrate them with existing brick and mortar services. He is also working in collaboration with the Computer Science department to develop algorithms to predict the risk of developing mental and substance use disorders due to COVID-19. By using machine learning techniques and applying those to health service utilization data, the ultimate goal is to facilitate access to effective treatments.