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SP6-37 Predicting dengue fever incidence in Selangor using time series analysis technique
  1. S A Shah,
  2. J A Sani
  1. Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia


Introduction The war against dengue fever—the most important vector borne disease in Malaysia, has yet to be won. Throughout the years, Selangor has been the champion, bearing about half of the total number of dengue fever cases in Malaysia. This study aims to develop forecasting models based on the number of dengue fever occurrence in 3 areas in Selangor, namely Sepang, Kuala Selangor and Shah Alam.

Methods Monthly data of dengue fever occurrence based on date of onset of dengue fever symptoms for Sepang, Kuala Selangor and Shah Alam from 2004 to 2007 were collected. Patterns of monthly dengue fever occurrence were used to develop suitable forecasting models. The most suitable models were then used to predict the dengue fever occurrence in 2008.

Results All 3 study locations showed overall increasing trend of dengue cases over the 4 years with seasonal pattern. Forecasting of dengue cases for 2008 was performed using the best model identified for each location, after seasonal factors were accounted for. All models identified for forecasting was found to be suitable as shown by the residual autocorrelation function (ACF) and partial autocorrelation function (PACF).

Conclusion Predicting dengue fever occurrence using time series analysis can be useful in the long term planning of dengue fever control and prevention programme. However, longer period of data are required to allow for validation of the forecasting models, which could not be performed in this study.

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