时间：2018年1月5日周五下午15点

地点：A511会议室

主题：Modeling the Intervention of HIV Transmission across Key Populations

Abstract: The HIV transmissions between multiple key populations make interventions difficult, particularly with multiple transmission behaviors. It remains unclear how significant the role of bridge individuals (who connect multiple communities) is in HIV transmission, and how to develop more effective intervention strategies targeting different transmission modes across key populations. In this research, we proposed a 2-layer social network framework to simulate the HIV transmissions across female sex workers (FSWs) and persons who inject drugs (PWID) through two behaviors: unprotected sex and needle-sharing. We proposed a set of intervention strategies based on the topological properties of individuals in the social network and estimated the efficacy of these strategies. Simulation studies demonstrated that bridge individuals played a significant role in HIV transmissions across the two networks. Prevention on such bridge individuals could help reduce both the scale and speed of HIV transmissions.

Bio: Qingpeng Zhang is an Assistant Professor with the Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong SAR, China. He received the B.S. degree in automation from the Huazhong University of Science and Technology, Wuhan, China, in 2009, and the Ph.D. degree in systems and industrial engineering from The University of Arizona, Tucson, AZ, in 2012. He was a Post-Doctoral Research Associate with The Tetherless World Constellation, Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, a PhD intern at the Pacific Northwest National Laboratory, Richland, WA, and a research intern at the Institute of Automation, Chinese Academy of Science, Beijing, China. He is an Associate Editor of the IEEE Transactions on Computational Social Science and IEEE Transactions on Intelligent Transportation Systems.

His research interests include social computing, complex networks, data mining, and semantic web.