Forecasting incidence of dengue in Rajasthan, using time series analyses.
OBJECTIVE
To develop a prediction model for dengue fever/dengue haemorrhagic fever (DF/DHF) using time series data over the past decade in Rajasthan and to forecast monthly DF/DHF incidence for 2011.


METHODS
Seasonal autoregressive integrated moving average (SARIMA) model was used for statistical modeling.


RESULTS
During January 2001 to December 2010, the reported DF/DHF cases showed a cyclical pattern with seasonal variation. SARIMA (0,0,1) (0,1,1) 12 model had the lowest normalized Bayesian information criteria (BIC) of 9.426 and mean absolute percentage error (MAPE) of 263.361 and appeared to be the best model. The proportion of variance explained by the model was 54.3%. Adequacy of the model was established through Ljung-Box test (Q statistic 4.910 and P-value 0.996), which showed no significant correlation between residuals at different lag times. The forecast for the year 2011 showed a seasonal peak in the month of October with an estimated 546 cases.


CONCLUSIONS
Application of SARIMA model may be useful for forecast of cases and impending outbreaks of DF/DHF and other infectious diseases, which exhibit seasonal pattern.
Institute of Health Management Research, Jaipur, India.
Sunil
S
Bhatnagar
Vivek
V
Lal
Shiv D
SD
Gupta
Om P
OP
Gupta
D001499:Bayes Theorem; D003715:Dengue / Q000453:epidemiology*; D005544:Forecasting / Q000379:methods; D006801:Humans; D015994:Incidence; D007194:India / Q000453:epidemiology; D012621:Seasons; D013029:Space-Time Clustering