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基本再生数是传染病动力学中反映传染病传播潜力最重要的参数,对基本再生数的估算是传染病传播风险评估工作的核心内容。该文针对2013年末发生于西非的埃博拉疫情的风险评估问题,提出了改进的最小二乘法作为疫情参数拟合方法,并对该次埃博拉疫情中3个重灾区国家(几内亚、塞拉利昂、利比里亚)境内的早期疫情数据进行了拟合,估算出了疫情的基本再生数,拟合结果与实际数据吻合得较好;通过分析几内亚境内疫情的早期数据,改进前人研究中所采用的基于均匀混合假设的易感者S(susceptible)、携带者E(exposed)、传染者I(infectious)以及移出者R(removed)(SEIR)模型,提出了多次疫情假说模型,较好地解释了几内亚境内疫情数据波动现象。该文提出的拟合标准和传染病动力学建模思路对于确定病毒传播性质、评估防疫措施效果、预测传播趋势以及遏制未来可能出现的疫情有着重要意义。
The basic regeneration number is the most important parameter reflecting the transmission potential of infectious diseases in the dynamics of infectious diseases. The estimation of the basic regeneration number is the core content of the risk assessment of infectious disease transmission. In this paper, aiming at the risk assessment of the Ebola outbreak in West Africa at the end of 2013, an improved least-squares method is proposed to fit the epidemic parameter fitting method. The three severely affected countries in this Ebola outbreak (Guinea, Sierra Leone , Liberia) were used to estimate the basic number of reproductive events in the outbreak and the fitted results were in good agreement with the actual data. By analyzing the early data of outbreaks in Guinea, the data used in previous studies Based on the hypothesis of homogeneous mixture, susceptible, E (exposed), infectious (I) and removed (SEIR) models of multiple assumptions, this paper proposes a series of epidemic hypothesis models, which are well explained Fluctuations in the outbreak data in Guinea. The proposed fitting criteria and epidemiological modeling of infectious diseases are of great significance in determining the nature of virus transmission, in assessing the effectiveness of epidemic prevention measures, predicting the transmission trends, and curbing possible future outbreaks.