Application of Time Series Analysis in Forecasting and Early Warning of Influenza-Like Illness in Jing'an District, Shanghai

Objective To apply time series analysis in forecasting and early warning of influenza-like illness (ILI) occurred in Jing'an District, Shanghai.

Methods The monthly monitoring data of ILI incidence of adults and children in Jing'an District during July 2011 and July 2014 were modeled with autoregressive integrated moving average model (ARIMA) in time series analysis. Then we predicted the ILI incidence from August to December 2014 by the established model, and tested the model by comparing predicting values and actual values.

Results The monitoring results showed different trends of ILI between children and adults. There were obvious seasonal variations for adults, but not for children. The optimal model was ARIMA (0, 1, 1) for children and ARIMA (1, 0, 0)(1, 1, 0)₁₂ for adults. The parameters of the two models were both statistically significant, and the result of forecast was ideal.

Conclusion ARIMA model could be used to predict the incidence trend of ILI in Jing'an District, but the data of children and adults require separate analysis. Warning thresholds could be set according to the range of forecasting results.