本文選題：埃博拉病毒　切入點：傳染病傳播　出處：《清華大學學報(自然科學版)》2017年08期 　論文類型：期刊論文

【摘要】：基本再生數(shù)是傳染病動力學中反映傳染病傳播潛力最重要的參數(shù),對基本再生數(shù)的估算是傳染病傳播風險評估工作的核心內(nèi)容。該文針對2013年末發(fā)生于西非的埃博拉疫情的風險評估問題,提出了改進的最小二乘法作為疫情參數(shù)擬合方法,并對該次埃博拉疫情中3個重災區(qū)國家(幾內(nèi)亞、塞拉利昂、利比里亞)境內(nèi)的早期疫情數(shù)據(jù)進行了擬合,估算出了疫情的基本再生數(shù),擬合結(jié)果與實際數(shù)據(jù)吻合得較好;通過分析幾內(nèi)亞境內(nèi)疫情的早期數(shù)據(jù),改進前人研究中所采用的基于均勻混合假設的易感者S(susceptible)、攜帶者E(exposed)、傳染者I(infectious)以及移出者R(removed)(SEIR)模型,提出了多次疫情假說模型,較好地解釋了幾內(nèi)亞境內(nèi)疫情數(shù)據(jù)波動現(xiàn)象。該文提出的擬合標準和傳染病動力學建模思路對于確定病毒傳播性質(zhì)、評估防疫措施效果、預測傳播趨勢以及遏制未來可能出現(xiàn)的疫情有著重要意義。
[Abstract]: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 number of basic regeneration is the core of the risk assessment of infectious disease transmission. In this paper, an improved least square method is proposed as a fitting method for the epidemic parameters in view of the risk assessment of Ebola outbreak that occurred in West Africa in end of 2013. The data of the early epidemic situation in the three worst affected countries (Guinea, Sierra Leone, Liberia) were fitted, and the basic regenerative number of the epidemic was estimated. The fitting results were in good agreement with the actual data. By analyzing the early data of the epidemic situation in Guinea and improving the models used in previous studies, which are based on the hypothesis of uniform mixing of susceptible individuals, carriers Eexposedus, infectious individuals, and emigrants, the multiple epidemic hypothesis models are put forward. The fluctuation phenomenon of epidemic data in Guinea is well explained. The fitting standard and the idea of infectious disease dynamics modeling are put forward in this paper to determine the nature of virus transmission and to evaluate the effect of epidemic prevention measures. It is important to predict the trend of transmission and to contain possible outbreaks in the future.
【作者單位】： 清華大學工程物理系公共安全研究院;
【基金】：國家科技支撐計劃課題(2015BAk12B03)
【分類號】：O175;R512.8
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本文編號：1587433