Linear and non-linear combination forecasting model of varicella incidence in Chongqing

Abstract

Abstract Varicella is a highly infectious contagious disease, and Chongqing is one of the high incidence areas in China. To understand the epidemic regularity and predict the epidemic trend of varicella is of great significance to the risk analysis and health resource allocation in the health sector. First, we used the ‘STL’ function to decompose the incidence of varicella to understand its trend and seasonality. Second, we established SARIMA model for linear fitting, and then took the residual of the SARIMA model as the sample to fit the LS-SVM model, to explain the non-linearity of the residuals. The monthly varicella incidence peaks in April to June and October to December. Mixed model was compared to SARIMA model, the prediction error of the hybrid model was smaller, and the RMSE and MAPE values of the hybrid model were 0.7525 and 0.0647, respectively, the mixed model had a better prediction effect. Based on the study, the incidence of varicella in Chongqing has an obvious seasonal trend, and a hybrid model can also predict the incidence of varicella well. Thus, hybrid model analysis is a feasible and simple method to predict varicella in Chongqing.