title: Modeling epidemic spread with awareness and heterogeneous transmission rates in networks.
abstract: During an epidemic outbreak in a human population, susceptibility to infection can be reduced by raising awareness of the disease. In this paper, we investigate the effects of three forms of awareness (i.e., contact, local, and global) on the spread of a disease in a random network. Connectivity-correlated transmission rates are assumed. By using the mean-field theory and numerical simulation, we show that both local and contact awareness can raise the epidemic thresholds while the global awareness cannot, which mirrors the recent results of Wu et al. The obtained results point out that individual behaviors in the presence of an infectious disease has a great influence on the epidemic dynamics. Our method enriches mean-field analysis in epidemic models.
authors.affiliation: Institute for Cyber Security, University of Texas at San Antonio, San Antonio, TX 78249, USA. shylmath@hotmail.com
authors.forename: Yilun
authors.initials: Y
authors.lastname: Shang
mesh_terms: D004198:Disease Susceptibility; D018562:Disease Transmission, Infectious; D058872:Epidemics; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D008954:Models, Biological