新冠肺炎动态病死率分析与疫情预测方法研究

Dynamic case fatality rate analysis and pandemic prediction method of COVID-19

新型冠状病毒感染的肺炎防控是国家安全体系的重要“战场”,疫情趋势预测是开展疫情科学防控和精准防控的重要基础。本文阐述了疫情动态病死率概念,分析了疫情动态病死率函数和时间曲线,提出了动态病死率发展的3个重要拐点,从动态病死率和新增确诊病人数两个维度,构建了拟合曲线函数,并对疫情发展趋势进行了预测。研究发现,截至2月10日,本次疫情动态病死率已经经过了第3个拐点,趋于稳定;预计到2月16日左右,新增确诊人数达到第3个拐点,进入缓慢下降期;预计2月底底至3月初,每日新增确诊人数将在1000人以内,全国最终的“病死率”将在2%~4%左右。该预测方法是一种运用系统外部特征信息来研判疫情发展规律的较为简便快捷的方法,对于科学预测疫情发展趋势具有一定的参考借鉴价值。

How to prevent and control COVID-19 is now becoming an important battlefield of national security system,and the key to scientific and precise prevention and control lies in the pandemic prediction.This paper introduces the concept of dynamic case fatality rate,analyzes the function and time curve of the dynamic case fatality rate,and suggests three important turning points of the development of the dynamic case fatality rate.From the two dimensions of dynamic case fatality rate and number of newly confirmed cases,the fitting curve function is constructed to predict the development trend of the pandemic.The study finds that by February 10th,the dynamic case fatality rate had passed the third turning point and tended to be stable.It is estimated that by February 16th,the number of newly confirmed cases will reach the third turning point and enter into a slow decline period.It is estimated that the number of newly confirmed cases per day will be less than 1000 from the end of February to the beginning of March,and the final“case fatality rate”of the whole country will be 2%~4%.This prediction method is a simple and quick approach to study the pandemic development law by using the external characteristic information of the system,providing certain references for the scientific pandemic prediction.