基于新冠病毒特征及防控措施的传播动力学模型

本文针对现有传染病传播动力学模型的不足,结合新冠病毒(2019-nCoV)特征及防控措施,建立一种新的包含"易感、未隔离潜伏期、已隔离潜伏期、确诊感染、无症状感染、确诊后治愈、无症状感染后治愈、因病死亡"等8个仓室的传染病模型.在模型中考虑状态转移参数的饱和特性,以模拟大量隔离患者对隔离点运行造成的压力、大量确诊患者给医院运行带来的压力.在参数配置方面,考虑状态转移参数在疫情不同发展阶段的时变特性,建立参数辨识模型并利用马尔可夫链蒙特卡罗算法进行求解.此外,从传播规模、传播峰值和传播峰值时间三个维度建立疫情传播风险指标,全面评估疫情传播风险.武汉和国外(美国、西班牙)疫情的案例分析表明,本模型相较于其他经典模型,能够准确拟合新冠肺炎(COVID-19)的传播趋势,揭示疫情传播机理.

Propagation dynamics model considering the characteristics of 2019-nCoV and prevention-control measurements

Considering the deficiency of existing propagation dynamics models, as well as the transmission characteristics of 2019 novel coronavirus (2019-nCoV) and prevention-control measurements, a new infectious disease model is established, which included eight compartments, i.e. susceptible, uninsulated, isolated, diagnosed, asymptomatic, cured after diagnosis, cured after asymptomatic and died of disease. In order to simulate the pressure of a large number of isolated patients on the operation of isolation points and the pressure of a large number of confirmed patients on the operation of hospitals, the saturation characteristics of state transfer parameters are considered in the model. In the aspect of parameter configuration, the time-varying characteristics of state transition parameters in different stages of epidemic development are analyzed. A parameter identification model is established and solved by Markov chain Monte Carlo algorithm. In addition, the risk indicators of epidemic transmission are established from multiple dimensions to comprehensively assess the risk of epidemic transmission. Through the case studies of coronavirus disease 2019 (COVID-19) in Wuhan and foreign countries (America and Spain), the results show that the calculated results are in better agreement with the official data and reveal the mechanism of epidemic transmission compared with other classical dynamics models.