Time series analysis and prediction model of percentage of influenza-like illness ï¼ILIï¼ cases in Shanghai
Journal Title: Shanghai Journal of Preventive Medicine - Year 2023, Vol 35, Issue 2
Abstract
ObjectiveTo predict the incidence trend of influenza-like illness proportion ï¼ILI%ï¼ in Shanghai using the seasonal autoregressive integrated moving average model ï¼SARIMAï¼ï¼ and to provide an important reference for timely prevention and control measures.MethodsTime series analysis was performed on ILI% surveillance data of Shanghai Municipal Center for Disease Control and Prevention from the 15th week of 2015 to the 52nd week of 2019ï¼ and a prediction model was established. Seasonal autoregressive integrated moving average ï¼SARIMAï¼ model was established using data from the foregoing 212 weeksï¼ and prediction effect of the model was evaluated using data from the latter 36 weeks.ResultsFrom the 15th week of 2015 to the 52nd week of 2019ï¼ the average ILI% in Shanghai was 1.494%ï¼ showing an obvious epidemic peak. SARIMAï¼1ï¼0ï¼0ï¼ ï¼2ï¼0ï¼0ï¼ 52 was finally modeled. The residual of the model was white noise sequenceï¼ and the true values were all within the 95% confidence interval of the predicted values.ConclusionSARIMAï¼1ï¼0ï¼0ï¼ ï¼2ï¼0ï¼0ï¼ 52 can be used for the medium term prediction of ILI% in Shanghaiï¼ and can play an early warning role for the epidemic and outbreak of influenza in Shanghai.
Authors and Affiliations
QIAN Chensi,JIANG Chenyan,XIA Han,ZHENG Yaxu,LIU Xinghang,YANG Mei,XIA Tian,
Keywords
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