A Reexamination of Connectivity Trends via Exponential Random Graph Modeling in Two IDU Risk Networks

Authors

Kirk Dombrowski, University of Nebraska-LincolnFollow
Bilal Khan, University of Nebraska-LincolnFollow
Katherine McLean, CUNY Graduate Center
Ric Curtis, CUNY John Jay CollegeFollow
Travis Wendel, John Jay College
Evan Misshula, CUNY Graduate Center
Samuel Friedman, NDRI

Date of this Version

12-2014

Citation

Subst Use Misuse. 2013 December ; 48(14): pp. 1485–1497. doi:10.3109/10826084.2013.796987.

Comments

Copyright © 2013 Informa Healthcare USA, Inc. Used by permission.

Abstract

Patterns of risk in injecting drug user (IDU) networks have been a key focus of network approaches to HIV transmission histories. New network modeling techniques allow for a reexamination of these patterns with greater statistical accuracy and the comparative weighting of model elements. This paper describes the results of a reexamination of network data from the SFHR and P90 data sets using Exponential Random Graph Modeling. The results show that “transitive closure” is an important feature of IDU network topologies, and provides relative importance measures for race/ethnicity, age, gender, and number of risk partners in predicting risk relationships.