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一个预测新型冠状病毒肺炎流行趋势的简易模型 被引量:2

A simple model of forecasting COVID-19 epidemic
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摘要 目的:分析新型冠状病毒肺炎在武汉市的流行特征,建立预测疫情走势模型。方法:采集官方数据填入Excel表中,生成统计图表,计算每日新增确诊病例平均环比增长率和95%可信区间,据此建立数学模型,预测后续每日新增确诊病例数,并与实际发生每日新增确诊病例数进行比较。结果:平均环比增长率(2020年2月14日—3月8日)为-11.01%,标准差为34.52%,95%可信区间常数为±13.81%。以模型Xn=(1+A±B)n×X0预测8 d(2020年3月8日为起点)的乐观预测新增确诊病例数与实际新增确诊病例数高度接近,经统计学检验,两组数据差异无统计学意义(P>0.05)。结论:以平均环比增长率和95%可信区间为参数的Xn=(1+A±B)n×X0数学模型预测每日新增确诊病例数有一定参考意义。 Objective:To analyze the coronavirus disease 2019(COVID-19) epidemic characteristics,and to predict the epidemic trend.Methods:Official data were input into the Excel table to generate statistics charts,and the daily average quarter-on-quarter new growth confirmed cases and 95% confidence interval were calculated on the basis of a simple mathematical model to predict subsequent new daily numbers of confirmed cases.The predicted results were compared to the actual daily numbers of confirmed cases.Results:The average day-on-day growth rate(from February 14 to March 8,2020) was11.01%,and the standard deviation was 34.52% with 95% confidence interval of(±13.81)%.By the model Xn=(1+A±B)n X0 in forecasting the number of new confirmed cases of 8-days(March 8 as the starting point),the predicted results were close to the actual numbers(P>0.05).Conclusion:The mathematical model of Xn=(1+A±B)n X0 is valuable in predicting the daily new confirmed cases during COVID-19 epidemic.
作者 田斌群 陈道远 田卫群 王行环 刘同族 张银高 郑新民 李世文 TIAN Binqun;CHEN Daoyuan;TIAN Weiqun;WANG Xinghuan;LIU Tongzu;ZHANG Yingao;ZHENG Xinmin;LI Shiwen(Zhongnan Hospital of Wuhan University,Wuhan 430071,Hubei,China;The Engineering College of Chinese University of Hong Koxg,Hong Kong 999077,China;Wuhan University School of Basic Medical Sciences,Wuhan 430071,Hubei,China)
出处 《武汉大学学报(医学版)》 CAS 2021年第1期28-31,共4页 Medical Journal of Wuhan University
关键词 新型冠状病毒肺炎 流行趋势 模型 COVID-19 Epidemic Trend Model
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