Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Brazil.
Cad Saude Publica. 2011 Sep;27(9):1809-18. doi: 10.1590/s0102-311x2011000900014.
This study aimed to develop a forecasting model for the incidence of dengue in Ribeirão Preto, São Paulo State, Brazil, using time series analysis. The model was performed using the Seasonal Autoregressive Integrated Moving Average (SARIMA). Firstly, we fitted a model considering monthly notifications of cases of dengue recorded from 2000 to 2008 in Ribeirão Preto. We then extracted predicted values for 2009 from the adjusted model and compared them with the number of cases observed for that year. The SARIMA (2,1,3)(1,1,1)12 model offered best fit for the dengue incidence data. The results showed that the seasonal ARIMA model predicts the number of dengue cases very effectively and reliably, and is a useful tool for disease control and prevention.
本研究旨在使用时间序列分析为巴西圣保罗州里贝朗普雷图建立登革热发病率预测模型。该模型采用季节性自回归综合移动平均（SARIMA）进行。首先，我们拟合了一个考虑 2000 年至 2008 年里贝朗普雷托每月登革热病例报告的模型。然后，我们从调整后的模型中提取 2009 年的预测值，并将其与当年观察到的病例数进行比较。SARIMA（2,1,3）（1,1,1）12 模型对登革热发病率数据的拟合效果最佳。结果表明，季节性 ARIMA 模型能够非常有效地预测登革热病例数，是疾病控制和预防的有用工具。
