Authors: Yuchen Li*, The Ohio State University, Harvey Miller, The Ohio State University, Ayaz Hyder, The Ohio State University, Lauren Southerland, The Ohio State University, Gretchen Hammond, Mighty Crow Media, Adam Porr, The Ohio State University
Topics: Medical and Health Geography, Geographic Information Science and Systems, Spatial Analysis & Modeling
Keywords: opioids, overdose, 311 service requests, spatial point pattern analysis, social and neighborhood determinants of health
Session Type: Virtual Paper
Start / End Time: 4:40 PM / 5:55 PM
Room: Virtual 8
Presentation File: No File Uploaded
Opioid use disorder and overdose deaths is a public health crisis in the United States, and there is increasing recognition that its etiology is rooted in part by social determinants such as poverty, isolation, and social upheaval. Limiting research and policy interventions is the low temporal and spatial resolution of publicly available administrative data such as census data. We explore the use of municipal service requests (also known as “311” requests) as high resolution spatial and temporal indicators of neighborhood social distress and opioid misuse. We analyze the spatial associations between georeferenced opioid overdose event (OOE) data from emergency medical service responders and 311 service request data from the City of Columbus, OH, for the time period 2008-2017. We find subset types of 311 requests spatially associate with OOEs and also characterize neighborhoods with lower socioeconomic status in the city, both consistently over time. We also demonstrate that the 311 indicators are capable of predicting OOE hotspots at the neighborhood-level with a high degree of accuracy. Since 311 requests are publicly available and with a high spatial and temporal resolution, they can be effective as opioid overdose surveillance indicators for basic research and applied policy.