论文标题
估计2019-NCOV传输潜力的强大随机方法
A Robust Stochastic Method of Estimating the Transmission Potential of 2019-nCoV
论文作者
论文摘要
最近的一场新型冠状病毒（2019-NCOV）爆发迅速发展为全球健康危机。在最近的几项研究工作中，已经对2019-NCOV的传输潜力进行了建模和研究。通过将传染性疾病扩散模型拟合到汇总数据，诸如病毒的基本生殖数字，$ r_ {0} $之类的关键因素。数据包括中国内部和世界上紧密联系的城市报告的案件。在本文中，我们从统计估计的鲁棒性的角度研究了2019-NCOV的传输潜力，鉴于爆发初始阶段的数据质量和及时性。在存在异常值时，已采用样品共识算法来改善模型拟合。强大的估计使我们能够识别两个传输模型簇，这两者都具有很大的关注点，一个具有$ r_0：8 \ sim14 $，可与麻疹相当，另一个则决定了一个大的初始感染组。
The recent outbreak of a novel coronavirus (2019-nCoV) has quickly evolved into a global health crisis. The transmission potential of 2019-nCoV has been modelled and studied in several recent research works. The key factors such as the basic reproductive number, $R_{0}$, of the virus have been identified by fitting contagious disease spreading models to aggregated data. The data include the reported cases both within China and in closely connected cities over the world. In this paper, we study the transmission potential of 2019-nCoV from the perspective of the robustness of the statistical estimation, in light of varying data quality and timeliness in the initial stage of the outbreak. Sample consensus algorithm has been adopted to improve model fitting when outliers are present. The robust estimation enables us to identify two clusters of transmission models, both are of substantial concern, one with $R_0:8\sim14$, comparable to that of measles and the other dictates a large initial infected group.
