Forecasting Dengue Haemorrhagic Fever Cases in Southern Thailand using ARIMA Models

A univariate time-series analysis method has been used to model and forecast the monthly number of dengue haemorrhagic fever (DHF) cases in southern Thailand. We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1994–2005 and then validated the models using the data collected between January–August 2006. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The ARIMA (1,0,1) model fitting was adequate for the data with the Q-statistic (Q=4.446). This indicated that the autocorrelation function was not significantly different for zero.

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