基于时变参数-SIR模型的COVID-19疫情评估和预测

该文基于COVID-19疫情发展到2020年2月1日所呈现的特点，对SIR模型进行了修正，使用易感再生数、当日感染率和潜伏感染率来求解病毒演化动力学方程，研究了感染人数的变化趋势，并分析了政府防控措施对趋势变化产生的影响。结果表明，从2020年1月24日后，政府的防控措施有效降低了病毒蔓延趋势。与1月24日之前呈现的趋势相比，截至2020年2月1日，实际感染人数较原趋势预估人数下降了超1/2。易感再生数、当日再生数和潜伏再生数都大幅度降低。基于目前的趋势，对易感再生数、当日感染率、潜伏感染率随时间的变化进行了分析，利用时变参数对疫情发展进行了预测。结果表明在2020年2月9日左右，疫情发展会达到高峰，随后确诊人数将出现下降。

The Outbreak Assessment and Prediction of COVID-19 Based on Time-varying SIR Model

Based on the early behavior of COVID-19 until February 1st, the SIR model is modified to solve the dynamic equation of virus evolution by using the number of susceptible persons, the probability of infection and the latent infection rate. The change trend of infected persons is studied, and the influence of government administrative actions on the trend is analyzed. The results showed that after January 24th, 2020, the administrative action of the government has effectively slowed down the spread virus and the number of infected people decreased obviously. The number of current infections had reduced more than a half compared with the previous trend forecast according the trend of January 24th, 2020. The number of susceptible persons, the probability of infection and the latent infection rate were all greatly reduced. Based on the current trend and the optimal parameters, it is predicted that the outbreak will peak around February 9th, 2020 and then decline.