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arXiv physics/0610138physics.bio-phphysics.soc-ph
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无标度网络上易感-感染模型的免疫

Immunization of Susceptible-Infected Model on Scale-Free networks

Wen-Jie Bai, Tao Zhou, Bing-Hong Wang

摘要:

本文研究了Barabási-Albert(BA)网络上易感染(SI)模型的两种主要免疫策略:随机免疫和靶向免疫.对于异质结构,当接种比例很小时,随机策略的效果很差,而目标策略偏好接种程度最大的个体,即使接种的群体数量很小,也能显著抑制传染病传播。该解析解可以反映接种群体数量与接种速度变化的关系。

英文摘要:

In this paper, we investigate two major immunization strategies, random immunization and targeted immunization, of the susceptible-infected (SI) Model on the Barabási-Albert (BA) networks. For the heterogenous structure, the random strategy is quite ineffective if the vaccinated proportion is quite small, while the targeted one which prefers to vaccinate the individuals with the largest degree can sharply depress the epidemic spreading even only a small amount of population are vaccinated. The analytical solution is also obtained,which can capture the trend of velocity change versus the amount of vaccinated population.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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