上海市流感样病例就诊百分比时间序列分析和预测模型研究

钱晨嗣; 姜晨彦; 夏寒; 郑雅旭; 刘星航; 杨妹; 夏天

doi:10.19428/j.cnki.sjpm.2023.22253

上海市流感样病例就诊百分比时间序列分析和预测模型研究

Time series analysis and prediction model of percentage of influenza-like illness （ILI） cases in Shanghai

摘要

摘要:
目的利用季节性差分移动自回归平均模型（SARIMA）预测上海市流感样病例就诊百分比（ILI%）的发病趋势，为及时采取针对性防控措施提供重要的参考依据。
方法对2015年第15周至2019年第52周上海市疾病预防控制中心ILI%监测数据进行时间序列分析并建立预测模型，使用前212周数据建立SARIMA模型，后36周数据评估模型预测效果。
结果 2015年第15周—2019年第52周上海市ILI%平均值为1.494%，有较明显的流行高峰出现。最终建模SARIMA（1，0，0）（2，0，0）₅₂，模型残差为白噪声序列，真实值均在预测值95%置信区间内。
结论 SARIMA（1，0，0）（2，0，0）₅₂可用于上海市ILI%的中期预测，并为全市流感流行和暴发起到预警作用。

Abstract:
Objective To predict the incidence trend of influenza-like illness proportion （ILI%） in Shanghai using the seasonal autoregressive integrated moving average model （SARIMA）， and to provide an important reference for timely prevention and control measures.
Methods Time series analysis was performed on ILI% surveillance data of Shanghai Municipal Center for Disease Control and Prevention from the 15^th week of 2015 to the 52^nd week of 2019， and a prediction model was established. Seasonal autoregressive integrated moving average （SARIMA） model was established using data from the foregoing 212 weeks， and prediction effect of the model was evaluated using data from the latter 36 weeks.
Results From the 15^th week of 2015 to the 52^nd week of 2019， the average ILI% in Shanghai was 1.494%， showing an obvious epidemic peak. SARIMA（1，0，0）（2，0，0）₅₂ was finally modeled. The residual of the model was white noise sequence， and the true values were all within the 95% confidence interval of the predicted values.
Conclusion SARIMA（1，0，0）（2，0，0）₅₂ can be used for the medium term prediction of ILI% in Shanghai， and can play an early warning role for the epidemic and outbreak of influenza in Shanghai.

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