Forecasting the Incidence of Mumps in Zibo City Based on a SARIMA Model
نویسندگان
چکیده
This study aimed to predict the incidence of mumps using a seasonal autoregressive integrated moving average (SARIMA) model, and provide theoretical evidence for early warning prevention and control in Zibo City, Shandong Province, China. Monthly mumps data from Zibo City gathered between 2005 and 2013 were used as a training set to construct a SARIMA model, and the monthly mumps in 2014 were defined as a test set for the model. From 2005 to 2014, a total of 8722 cases of mumps were reported in Zibo City; the male-to-female ratio of cases was 1.85:1, the age group of 1-20 years old accounted for 94.05% of all reported cases, and students made up the largest proportion (65.89%). The main serious endemic areas of mumps were located in Huantai County, Linzi District, and Boshan District of Zibo City. There were two epidemic peaks from April to July and from October to January in next year. The fitted model SARIMA (0, 1, 1) (0, 1, 1)12 was established (AIC = 157.528), which has high validity and reasonability. The SARIMA model fitted dynamic changes of mumps in Zibo City well. It can be used for short-term forecasting and early warning of mumps.
منابع مشابه
Seasonality and Forecasting of Monthly Broiler Price in Iran
The objective of this study was to model seasonal behavior of broiler price in Iran that can be used to forecast the monthly broiler prices. In this context, the periodic autoregressive (PAR), the seasonal integrated models, and the Box-Jenkins (SARIMA) models were used as the primary nominates for the forecasting model. It was shown that the PAR (q) model could not be considered as an appropri...
متن کاملRainfall-runoff process modeling using time series transfer function
Extended Abstract 1- Introduction Nowadays, forecasting and modeling the rainfall-runoff process is essential for planning and managing water resources. Rainfall-Runoff hydrologic models provide simplified characterizations of the real-world system. A wide range of rainfall-runoff models is currently used by researchers and experts. These models are mainly developed and applied for simulation...
متن کاملSARIMA for predicting the cases numbers of dengue.
Introduction: Forecasting dengue cases in a population by using time-series modelscan provide useful information that can be used to facilitate the planning of public healthinterventions. The objective of this article was to develop a forecasting model for dengueincidence in Campinas, southeast Brazil, considering the Box-Jenkins modeling approach.Methods: The forecasting model ...
متن کاملA SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil Um modelo SARIMA para predição do número de casos de dengue em Campinas, Estado de São Paulo
Introduction: Forecasting dengue cases in a population by using time-series models can provide useful information that can be used to facilitate the planning of public health interventions. The objective of this article was to develop a forecasting model for dengue incidence in Campinas, southeast Brazil, considering the Box-Jenkins modeling approach. Methods: The forecasting model for dengue i...
متن کاملComparative Study of Four Time Series Methods in Forecasting Typhoid Fever Incidence in China
Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA) model and three different models inspired by neural networks, namely, ba...
متن کامل