Evaluating the predictive performance of different data sources to forecast overdose deaths at the neighborhood level with machine learning in Rhode Island.

Abstract

Authors

• John C Halifax
  Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA. Electronic address: john_halifax@berkeley.edu.
• Bennett Allen
  Center for Opioid Epidemiology and Policy, Department of Population Health, Grossman School of Medicine, New York University, New York, NY, USA.
• Claire Pratty
  Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA.
• Victoria Jent
  Center for Opioid Epidemiology and Policy, Department of Population Health, Grossman School of Medicine, New York University, New York, NY, USA.
• Alexandra Skinner
  Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA.
• Magdalena Cerdá
  Center for Opioid Epidemiology and Policy, Department of Population Health, Grossman School of Medicine, New York University, New York, NY, USA.
• Brandon D L Marshall
  Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA.
• Daniel B Neill
  Center for Urban Science and Progress, New York University, New York, NY, USA; Department of Computer Science, Courant Institute for Mathematical Sciences, New York University, New York, NY, USA; Robert F. Wagner Graduate School of Public Service, New York University, New York, NY, USA.
• Jennifer Ahern
  Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA.

Keywords

External Resources