Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41450, first published .
Small Area Forecasting of Opioid-Related Mortality: Bayesian Spatiotemporal Dynamic Modeling Approach

Small Area Forecasting of Opioid-Related Mortality: Bayesian Spatiotemporal Dynamic Modeling Approach

Small Area Forecasting of Opioid-Related Mortality: Bayesian Spatiotemporal Dynamic Modeling Approach

Cici Bauer   1 , PhD ;   Kehe Zhang   1 , MS ;   Wenjun Li   2 , PhD ;   Dana Bernson   3 , MPH ;   Olaf Dammann   4, 5 , MD, PhD ;   Marc R LaRochelle   6, 7 , MPH, MD ;   Thomas J Stopka   4, 8, 9 , MHS, PhD

1 Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States

2 Department of Public Health, University of Massachusetts Lowell, Lowell, MA, United States

3 Office of Population Health, Department of Public Health, The Commonwealth of Massachusetts, Boston, MA, United States

4 Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States

5 Department of Gynecology and Obstetrics, Hannover Medical School, Hannover, Germany

6 Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States

7 Grayken Center for Addiction, Boston Medical Center, Boston, MA, United States

8 Department of Urban and Environmental Policy and Planning, Tufts University, Medford, MA, United States

9 Department of Community Health, Tufts University, Medford, MA, United States

Corresponding Author:

  • Cici Bauer, PhD
  • Department of Biostatistics and Data Science
  • School of Public Health
  • The University of Texas Health Science Center at Houston
  • 1200 Pressler Street, Room E819
  • Houston, TX, 77030
  • United States
  • Phone: 1 713-500-9581
  • Email: cici.x.bauer@uth.tmc.edu