常用统计预测模型及其在结核病疫情预测中的应用

Commonly used statistical predictive models and their application in tuberculosis prediction

目的选择简便、可靠的统计预测模型,为传染病疫情预测工作提供参考。方法对常见统计预测模型的原理、拟合优度检验与模型筛选进行介绍,并以厦门市结核病疫情为例开展模型应用。结果模型与数据拟合结果显示,11种模型均有统计学意义(P<0.05)。其中R 2最大为Cubic模型,其次为Quadratic模型和Logarithmic模型。Quadratic模型预测2019年7~12月厦门市报告发病数分别为191(95%CI:124-259)、192(95%CI:124-260)、193(95%CI:125-261)、194(95%CI:126-262)、195(95%CI:127-263)和196(95%CI:128-264)。结论常见统计模型可以用于厦门市结核病发病趋势预测,厦门市短期内报告病例数将略有上升趋势。

Objective To assess the predictive models commonly used in statistics,and determine the optimal model(s)for predicting the trend of tuberculosis.Methods Commonly used statistical predictive models were described concerning the principles,goodness of fit test and model selection,and applied to predicting the trend of tuberculosis in Xiamen city for choice of the best one(s)in following prevention and control of the epidemics.Results The fitting results into the model and data showed that 11 models had statistical significance(P<0.05).In the 11 models,the largest R 2 model was Cubic,followed by the Quadratic and Logarithmic.Quadratic model was used,and revealed 191(95%CI:124-259),192(95%CI:124-260),193(95%CI:125-261),194(95%CI:126-262)and 195(95%CI:127-263)and 196 cases of tuberculosis(95%CI:128-264),respectively,reported in Xiamen area from July to December of 2019.Conclusion The commonly used statistical model can be used to predict the incidence trend of tuberculosis in Xiamen area,and the number of reported cases in Xiamen tends to slightly increase in the short term.