Tang S Y, Xiao Y N, Peng Z H, Shen H B
School of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710119, China.
Center for the Intersection of Mathematics and Life Sciences, School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2020 Apr 10;41(4):480-484. doi: 10.3760/cma.j.cn112338-20200216-00107.
Since December 2019, the outbreak of COVID-19 in Wuhan has spread rapidly due to population movement during the Spring Festival holidays. Since January 23rd, 2020, the strategies of containment and contact tracing followed by quarantine and isolation has been implemented extensively in mainland China, and the rates of detection and confirmation have been continuously increased, which have effectively suppressed the rapid spread of the epidemic. In the early stage of the outbreak of COVID-19, it is of great practical significance to analyze the transmission risk of the epidemic and evaluate the effectiveness and timeliness of prevention and control strategies by using mathematical models and combining with a small amount of real-time updated multi-source data. On the basis of our previous research, we systematically introduce how to establish the transmission dynamic models in line with current Chinese prevention and control strategies step by step, according to the different epidemic stages and the improvement of the data. By summarized our modelling and assessing ideas, the model formulations vary from autonomous to non-autonomous dynamic systems, the risk assessment index changes from the basic regeneration number to the effective regeneration number, and the epidemic development and assessment evolve from the early SEIHR transmission model-based dynamics to the recent dynamics which are mainly associated with the variation of the isolated and suspected population sizes.
自2019年12月以来，由于春节假期期间的人口流动，武汉的新冠疫情迅速蔓延。自2020年1月23日起，中国大陆广泛实施了围堵和接触者追踪策略，随后进行检疫和隔离，检测和确诊率不断提高，有效抑制了疫情的快速传播。在新冠疫情爆发初期，利用数学模型并结合少量实时更新的多源数据来分析疫情的传播风险，评估防控策略的有效性和及时性具有重要的现实意义。在我们之前研究的基础上，根据不同的疫情阶段和数据的完善情况，系统地逐步介绍如何建立符合当前中国防控策略的传播动力学模型。通过总结我们的建模和评估思路，模型公式从自治动力系统转变为非自治动力系统，风险评估指标从基本再生数变为有效再生数，疫情发展和评估从早期基于SEIHR传播模型的动力学演变为近期主要与隔离和疑似人群规模变化相关的动力学。
