AI4OE

Spatial Big Data and GIS Analytics

Public health studies are moving towards Public Health 2.0 and Precision Public Health, driven by the availability of big data at large scales and finer geospatial resolutions, including electronic health records (EHR), user generated data, and consolidated data from multiple data sources. This offers a compelling opportunity to enhance opioid epidemic studies with improved accuracy for timely intervention and prevention.
We take a GIS and big spatial data driven approach to study community and region level patterns and variations at fine spatial resolutions, and the impact of demographic and socio-economical factors on opioid epidemic. We also discover resource dispartities in NY, which needs to be improved.

Projects:

Opioid poisoning in New York State with implications for targeted interventions

References:























Association of Opioid Use Disorder With 2016 Presidential Voting Patterns in New York State at Census Tract Level

References:
Anthony Xiang, Wei Hou, Sina Rashidian, Richard N Rosenthal, Kayley Abell-Hart, Xia Zhao and Fusheng Wang: Association of Opioid Use Disorder With 2016 Presidential Voting Patterns: A Cross-Sectional Study in New York State at Census Tract Level. JMIR Public Health Surveill 2021;7(4):e23426



































Undertanding geospatial disparities of treatment resources for opioid overdose

References:
Kayley Abell-Hart, Sina Rashidian, Dejun Teng, Richard N Rosenthal and Fusheng Wang: Where Opioid Overdose Patients Live Far From Treatment: Geospatial Analysis of Underserved Populations in New York State. JMIR Public Health and Surveillance. 2022;8(4):e32133