Modeling the Spread of HIV and HCV Infections Based on Identification and Characterization of High-Risk Communities Using Social Media.
BIOINFORMATICS RESEARCH AND APPLICATIONS (ISBRA 2017)(2017)
摘要
Epidemiological dynamics of diseases, which may be transmitted due to sexual behavior or injecting drug use, can vary across demographic, socio-behavioral, and geographic population groups. Typically, studies modeling infection dissemination in such settings use simulated data and employ simplified contact networks. Here, we demonstrate feasibility of simulating HIV/HCV epidemics over a real-world contact network inferred using social media mining. Such networks can lead to more realistic modeling of disease transmission patterns in high-risk population than what is possible at the current state-of-the-art. In particular, we studied how topological characteristics of transmission networks are reflected by viral phylogenies.
更多查看译文
关键词
Social Medium, Transmission Network, Contact Network, Host Network, Epidemiological Dynamic
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络