Abstract
The epidemic of drug abuse is a serious public health issue in the U.S. The number of overdose deaths involving prescription opioids and illicit drugs has continuously increased over the last few years. This study aims to develop a geospatial model that identifies geospatial clusters in terms of socioeconomic and demographic characteristics with an unsupervised machine learning algorithm. Then, we suggest the most important features affecting heroin overdose both negatively and positively. The findings of this study may inform policymakers about strategies to mitigate the drug overdose crisis.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 55th Hawaii International Conference on System Sciences |
| Pages | 5715-5724 |
| State | Published - Jan 4 2022 |
Keywords
- drug overdose
- Location Intelligence Research in System Sciences
- unsupervised machine learning
- k-means algorithms
- geospatial clusters