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Social Network Analysis


Social network analysis is a technique that goes beyond sociology to influence everything from network science more generally, to epidemiology, to systems theory approaches throughout medicine.

The REACH Lab has advanced epidemiological science through the creation of the MABUSE simulation platform, a large agent based network simulator capable of modeling HIV and HCV co-infection dynamics across multiple network layers, and across a range of risk scenarios. More recently we have begun work on two network data collection techniques using smart phones on the one hand (ODIN), and tablet devices on the other (SNAPT). Together, these new software implementations will significantly improve social science network data collection in the field.

Recent Blog Posts for Injection Risk Networks in Rural Puerto Rico

REACH researchers Roberto Abadie, Bilal Khan, and Kirk Dombrowski recently contributed to a paper published in the December issue of Drug

Members of the REACH lab published a paper in Substance Use and Misuse in November titled "Injection Partners, HCV, and

Injection drug users are at exceedingly heightened risk for contracting infectious diseases like Hepatitis C and HIV, and risk behaviors

REACH graduate research assistant Ian Duncan presented at the annual American Society of Criminology conference in November. Duncan's presentation titled

Ongoing results of studies concerning the United States War on Drugs uncover how policies have raised the incarceration rates of

While injection drug use poses a large risk for the spread of infectious diseases like HIV and HCV, people who

Funded Projects:

Funding for network-based research at the REACH Lab includes “Injection Drug User Network Topologies and HIV Stabilization Dynamics”  NIDA RC1 DA028476-01, “Network Topological Factors Affecting Long-term Stabilization of HIV Rates Among Injecting Drug Users” National Science Foundation BCS-0752680, “Addressing HCV-related hepatocellular carcinoma: the current and future epidemics” (PI Holly Hagan, NYU) NIDA R01 DA034637, “Applying Behavioral-Ecological Network Models to Enhance Distributed Spectrum Access in Cognitive Radio” National Science Foundation AST-1443985, “Towards a cellphone-based infrastructure for harvesting dynamic interaction network data” National Science Foundation, SMA-1338485, “REU Site: Undergraduate Research Opportunities to Broaden Participation in Minority Health Research” National Science Foundation SMA-1461132, “Modeling Social Behavior via Dynamic Network Interaction” NIGMS R01 GM118427.