2007
DOI: 10.1016/j.physa.2007.04.107
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Immunization of susceptible–infected model on scale-free networks

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Cited by 57 publications
(44 citation statements)
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“…Each individual had an opportunity to be the first individual infected, termed the “index case,” also known as “patient zero.” The probability of transmission was equal across all interactions. Furthermore, for simplicity, we assumed susceptible/infected (SI) epidemiological dynamics in which all individuals were initially susceptible to the disease and once infected, after interacting with an infected individual, remained infected (Anderson and May 1991; Barthelemy et al 2004, 2005; Bai et al 2007). To quantify the colony-wide incidence of infection, we examined the proportion of individuals infected by the end of the 20 time steps, referred to as “disease prevalence.” To quantify “transmission speed,” we used the inverse of the number of time steps it took 50% of the colony to become infected.…”
Section: Methodsmentioning
confidence: 99%
“…Each individual had an opportunity to be the first individual infected, termed the “index case,” also known as “patient zero.” The probability of transmission was equal across all interactions. Furthermore, for simplicity, we assumed susceptible/infected (SI) epidemiological dynamics in which all individuals were initially susceptible to the disease and once infected, after interacting with an infected individual, remained infected (Anderson and May 1991; Barthelemy et al 2004, 2005; Bai et al 2007). To quantify the colony-wide incidence of infection, we examined the proportion of individuals infected by the end of the 20 time steps, referred to as “disease prevalence.” To quantify “transmission speed,” we used the inverse of the number of time steps it took 50% of the colony to become infected.…”
Section: Methodsmentioning
confidence: 99%
“…In case of a highly contagious disease which spreads quickly, or in the beginning of an epidemic when the effects of recovery and death can be ignored, the SI model is appropriate for investigating the disease dynamics. 40,41 Furthermore, the SI model has applications in technological communication networks, 42 broadcasting processes, 43 email system services (e.g., Google when membership was only by invitation), and network marketing processes. 44 Analytic methods have been developed for optimizing intervention strategies in case of an epidemic.…”
Section: Literature Reviewmentioning
confidence: 99%
“…They finally investigated a fast spreading strategy in which only local information was available. Bai et al 41 investigated the effect of immunization in the SI model on scale-free networks. They examined random and targeted immunization based on the Barabási-Albert networks.…”
Section: Literature Reviewmentioning
confidence: 99%
“…However, in [6][7][8], Zhou, et al argued that this hypothesis is not always true. For example, for human sexual network, although a few individuals have many sexual partners, their sexual activities are not far beyond a normal level due to physiological limitations.…”
Section: Nonlinear Infectivitymentioning
confidence: 99%