Abstract:
ObjectiveTo explore the application of time series analysis for mumps prediction, and to establish ARIMA model to predict mumps cases per month in Shanghai.
MethodsData were collected on monthly reports about mumps cases from China Information System for Disease Control and Prevention between January 2005 and December 2016;ARIMA model was established for predicting the trend of mumps in 2017 by SPSS.
ResultsARIMA (1, 0, 0)(1, 1, 0)12 model could well fit the time series trend for mumps occurrence.The predicted values of monthly cases well matched the actual cases and the average relative error was 8.79%;2 656 cases were predicted in 2017.
ConclusionARIMA model could well simulate the changing trend of mumps cases in time series.Compared with the cases in 2016, mumps cases reported in number is predicted to be relatively stable in 2017.