本文關(guān)鍵詞：復(fù)雜網(wǎng)絡(luò)上具有多感染階段的傳染病傳播模型，由筆耕文化傳播整理發(fā)布。

復(fù)雜網(wǎng)絡(luò)上具有多感染階段的傳染病傳播模型

Epidemic model with multiple infections stages on complex networks

[1] [2]

LIAO Liefa,MENG Xiangmao （School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China）

江西理工大學(xué)信息工程學(xué)院,江西贛州341000

文章摘要：針對(duì)傳染病傳播模型缺乏多感染階段的不足,結(jié)合SIR和SEIR兩種傳播模型的特性,提出了一種改進(jìn)的具有多感染階段的SIR傳染病傳播模型（即SInR模型）。該模型充分考慮了不同感染階段的非均勻感染力對(duì)不同網(wǎng)絡(luò)結(jié)構(gòu)上傳染病傳播及傳播閾值的影響;同時(shí)引入相對(duì)感染力及傳播時(shí)間尺度的概念,從網(wǎng)絡(luò)結(jié)構(gòu)、網(wǎng)絡(luò)規(guī)模及相對(duì)感染力方面進(jìn)行了仿真研究。仿真中無(wú)標(biāo)度網(wǎng)絡(luò)采用BA模型的生成算法,而小世界網(wǎng)絡(luò)采用WS模型的生成算法。由仿真可知,感染節(jié)點(diǎn)在整個(gè)感染過(guò)程中大致服從泊松分布,因此在SInR模型下無(wú)標(biāo)度網(wǎng)絡(luò)的傳播速度更快,范圍更廣;相對(duì)感染力對(duì)于傳染病的大規(guī)模爆發(fā)存在著一個(gè)閾值,當(dāng)感染力大于閾值時(shí)傳染病才能大范圍地爆發(fā)傳播,而小于閾值時(shí)傳染病只會(huì)局域小范圍傳播直至消失,無(wú)標(biāo)度網(wǎng)絡(luò)的感染力閾值為0.2,小世界網(wǎng)絡(luò)的感染力閾值為0.24;隨著網(wǎng)絡(luò)規(guī)模的增大,傳播時(shí)間尺度也在增大,相應(yīng)的傳播速度就會(huì)降低。仿真結(jié)果表明：該模型下無(wú)標(biāo)度網(wǎng)絡(luò)傳染病傳播速度更快且影響范圍更大;無(wú)標(biāo)度網(wǎng)絡(luò)的相對(duì)傳染力的傳播閾值小于小世界網(wǎng)絡(luò),設(shè)置合理閾值有利于降低傳染病的傳播影響力。

Abstr：For the deficiency of the epidemic propagation models lacking of multiple infections stages, referring to the characteristics of two traditional propagation models including SIR and SEIR, an improved SIR epidemic propagation model with multiple infections stages, named SInR model, was put forward. Different infectious stages with non-uniform infectiousness which impacts on the spread of the epidemic in different network structures and the spread threshold were considered; meanwhile, relative infectiousness and propagation time were introduced to the model, and the simulations on network construction, network scale and relative infectiousness were also given. In the simulation, scale-free networks and small-world networks respectively used BA model generation algorithm and WS model generation algorithm. The infected nodes obeyed Poisson distribution in process of infection, thus the propagation speed of scale-free networks was faster as well as wider transmission under SInR model. There was a spread threshold of relative infectiousness for massive outbreak, when the relative infectiousness was greater than the threshold, the epidemic would outbreak in a wide range; otherwise, the epidemic would only spread in a local small range until it disappeared. The threshold of scale-free networks was 0. 2, while that of small-world networks was 0. 24. The propagation time scale increased and the corresponding propagation speed decreased while the network scale increased. The simulation results show that epidemic disease spreads faster and the influence range is larger on scale-free network under this model. In addition, the spread threshold value of relative infectiousness of scale-free network is less than the small world＇s and s

文章關(guān)鍵詞：

Keyword：:epidemic disease propagation model SInR model complex network relative infectiousness

課題項(xiàng)目：國(guó)家自然科學(xué)基金資助項(xiàng)目（71061008）; 江西省研究生創(chuàng)新專項(xiàng)基金資助項(xiàng)目（YC2013-S198）

  本文關(guān)鍵詞：復(fù)雜網(wǎng)絡(luò)上具有多感染階段的傳染病傳播模型，由筆耕文化傳播整理發(fā)布。