Development of temporal modeling for prediction of dengue infection in northeastern Thailand.
OBJECTIVE
To model the monthly number of dengue fever cases in northeastern Thailand using time series analysis.


METHODS
Autoregressive Integrated Moving Average (ARIMA) models have been developed on the monthly data collected from January 1981 to December 2006 and validated using the data from January 2007 to April 2010.


RESULTS
The ARIMA (3,1,4) model has been found as the most suitable model with the least Akaike Information Criterion (AIC) of 14.060 and Mean Absolute Percent Error (MAPE) of 7.000. The model was further validated by the Portmanteau test with no significant autocorrelation between residuals at different lag times.


CONCLUSIONS
Early warning based on the data in the previous months could assist in improving vector control, community intervention, and personal protection.
Center of Excellence for Ecoinformatics, School of Science, Walailak University, Thasala, Nakhon Si Thammarat, Thailand.
Siriwan
S
Wongkoon
Mullica
M
Jaroensutasinee
Krisanadej
K
Jaroensutasinee
D000818:Animals; D003625:Data Collection; D003715:Dengue / Q000453:epidemiology* / Q000517:prevention & control; D004199:Disease Vectors; D006801:Humans; D015233:Models, Statistical; D013785:Thailand / Q000453:epidemiology