The optimization of harm reduction services in Massachusetts through the use of GIS: Location-allocation analyses, 2019-2021.

Autor: Parbs JR; Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States. Electronic address: joshua.parbs@tufts.edu., Srinivasan S; Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States., Pustz J; Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States., Bayly R; Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States., Shrestha S; Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States., Lewis O; Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States., Kimmel S; Sections of General Internal Medicine and Infectious Diseases, Boston Medical Center and Boston University Chobanian and Avedisian School of Medicine, United States; Massachusetts Department of Public Health, United States., Meehan T; JSI Research & Training Institute, Inc., Boston, United States., Babakhanlou-Chase H; Massachusetts Department of Public Health, United States., Stopka TJ; Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States.
Jazyk: angličtina
Zdroj: Preventive medicine [Prev Med] 2024 Sep; Vol. 186, pp. 108088. Date of Electronic Publication: 2024 Jul 30.
DOI: 10.1016/j.ypmed.2024.108088
Abstrakt: Background: Fatal opioid-related overdoses (OOD) continue to be a leading cause of preventable death across the US. Opioid Overdose Education and Naloxone Distribution programs (OENDs) play a vital role in addressing morbidity and mortality associated with opioid use, but access to such services is often inequitable. We utilized a geographic information system (GIS) and spatial analytical methods to inform prioritized placement of OEND services in Massachusetts.
Methods: We obtained addresses for OEND sites from the Massachusetts Department of Public Health and address-level fatal OOD data for January 2019 to December 2021 from the Massachusetts Registry of Vital Records and Statistics. Using location-allocation approaches in ArcGIS Pro, we created p-median models using locations of existing OEND sites and fatal OOD counts to identify areas that should be prioritized for future OEND placement. Variables included in our analysis were transportation mode, distance from public schools, race and ethnicity, and location feasibility.
Results: Three Massachusetts communities - Athol, Dorchester, and Fitchburg - were identified as priority sites for new OEND locations using location-allocation models based on capacity to maximize OOD prevention. Communities identified by the models for OEND placement had similar demographics and overdose rates (42.8 per 100,000 vs 40.1 per 100,000 population) to communities with existing OEND programs but lower naloxone kit distribution rates (2589 doses per 100,000 vs 3704 doses per 100,000). Further models demonstrated differential access based on location and transportation.
Conclusion: Our analyses identified key areas of Massachusetts with greatest need for OEND services. Further, these results demonstrate the utility of using spatial epidemiological methods to inform public health recommendations.
Competing Interests: Declaration of competing interest Dr. Kimmel is supported by K23DA054363 from the National Institute on Drug Abuse.
(Copyright © 2024 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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