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41538 Characterizing Opioid Overdose Hotspots for Targeted Overdose Prevention and Treatment

Published online by Cambridge University Press:  31 March 2021

Elizabeth A. Samuels
Affiliation:
Brown Emergency Medicine
William Goedel
Affiliation:
Brown University School of Public Health
Lauren Conkey
Affiliation:
Rhode Island Department of Health
Jennifer Koziol
Affiliation:
Rhode Island Department of Health
Sarah Karim
Affiliation:
Rhode Island Department of Health
Rachel P. Scagos
Affiliation:
Rhode Island Department of Health
Lee Ann Jordison Keeler
Affiliation:
Brown Emergency Medicine
Rachel Yorlets
Affiliation:
Brown University School of Public Health
Neha Reddy
Affiliation:
Warren Alpert Medical School of Brown University
Sara Becker
Affiliation:
Brown University School of Public Health
Roland Merchant
Affiliation:
Brigham and Women’s Hospital
Brandon D. L. Marshall
Affiliation:
Brown University School of Public Health
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Abstract

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ABSTRACT IMPACT: Identifying factors associated with opioid overdoses will enable better resource allocation in communities most impacted by the overdose epidemic. OBJECTIVES/GOALS: Opioid overdoses often occur in hotspots identified by geographic and temporal trends. This study uses principles of community engaged research to identify neighborhood and community-level factors associated with opioid overdose within overdose hotspots which can be targets for novel intervention design. METHODS/STUDY POPULATION: We conducted an environmental scan in three overdose hotspots’‘ two in an urban center and one in a small city’‘ identified by the Rhode Island Department of Health as having the highest opioid overdose burden in Rhode Island. We engaged hotspot community stakeholders to identify neighborhood factors to map within each hotspot. Locations of addiction treatment, public transportation, harm reduction programs, public facilities (i.e., libraries, parks), first responders, and social services agencies were converted to latitude and longitude and mapped in ArcGIS. Using Esri Service Areas, we will evaluate the service areas of stationary services. We will overlay overdose events and use logistic regression identify neighborhood factors associated with overdose by comparing hotspot and non-hotspot neighborhoods. RESULTS/ANTICIPATED RESULTS: We anticipate that there will be differing neighborhood characteristics associated with overdose events in the densely populated urban area and those in the smaller city. The urban area hotspots will have overlapping social services, addiction treatment, and transportation service areas, while the small city will have fewer community resources without overlapping service areas and reduced public transportation access. We anticipate that overdoses will occur during times of the day when services are not available. Overall, overdose hotspots will be associated with increased census block level unemployment, homelessness, vacant housing, and low food security. DISCUSSION/SIGNIFICANCE OF FINDINGS: Identifying factors associated with opioid overdoses will enable better resource allocation in communities most impacted by the overdose epidemic. Study results will be used for novel intervention design to prevent opioid overdose deaths in communities with high burden of opioid overdose.

Type
Health Equity & Community Engagement
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Association for Clinical and Translational Science 2021