中文摘要：

网络传染病模型的精度是评价模型优劣的标准,其中网络对逼近传染病模型的优劣取决于所选逼近方法的精度。借助SIS传染病模型比较均匀网络上染病邻居数服从泊松分布、多项分布以及基于平均场思想的3种逼近方法的精度,发现在泊松分布下模型的误差最小,即泊松分布下的逼近方法精度最高。

英文摘要：

The accuracy of network-based epidemic models is a criterion of judging these models. Interestingly, judging the pair-approximation models in networks depends on the accuracy of approximation methods. Via SIS models, we compared the accuracy of three approximation methods in the homogeneous networks. The first is based on the number of infected neighborhoods of individuals following Poisson. The second is based the number of infected neighborhoods of individuals following multinomial distribution. The last one is based on the mean-field theory. Then we find the modelunder Poisson distribution with smallest errors, i.e. the accuracy of approximation methods under Poisson distribution is highest.