This paper examined the trend of dengue fever cases obtained from January 1995 to July 2017 from National Notifiable Disease Surveillance System (NNDSS) records, Fiji Ministry of Health and Medical Services. Box-Jenkins technique and model is applied to forecast incidence of dengue cases from August 2017 until December 2018. ARIMA model is proposed to forecast incidence of dengue fever in Fiji through Box-Jenkins approach. The Augmented Dickey Fullers test revealed that the time series data had unit root indicating non-stationary. The Autocorrelation and Partial Auto-correlation
plots of the first order difference of the dengue fever data suggested parameters ARIMA(3,0,4) and ARIMA(3,1,4). The
model ARIMA(3,0,4) was determined as the best fitted model which made a good forecasting performance in estimating the
expected incidence dengue cases with lower Mean Absolute Percentage Error (MAPE) of 1148.319 and lower Bayesian
Information Criterion (BIC) of 11.389. Finally, a forecast for dengue cases was obtained indicating the highest number of cases for December 2018 with estimated cases of 265. The ARIMA model method utilized in this paper forecasted the
incidence trend of dengue fever cases effectively. Such results would be beneficial to health professionals and policy makers in planning of public health interventions and improvement to such disease epidemics. The efficacy of expected cases of dengue fever accomplish not only in detecting outbreaks, but also in delivering decision makers with a reasonable trend of the variability of future observations encompassing both historical, recent information and for evidence based decision making
purposes
