Time Series Analysis of Dengue Hemorrhagic Fever Cases and Climate: A Model for Dengue Prediction.

Abstract

Dengue virus transmission depends on dengue vectors, which are sensitive to climate. This study investigated the role of climate in predicting dengue hemorrhagic fever (DHF) incidence. The monthly reported dengue cases and climate data were collected from the district health offices and the Climatological Division of the Meteorological Department of Medan, respectively. A time series analysis using ARIMA was carried out. The influence of climatic on the incidence of DHF was examined by time series regression approach. The number of monthly DHF cases in the periods 2012-2016 represent a seasonal pattern and tend increased. The amount of rainy days at lag of 1 and of 3 months were associated with the increase observed in the incidence of DHF in Medan. The SARIMA (1, 0, 0)(0, 1, 1)12 model was fit and appropriate in predicting DHF incidence in Medan. It might be applied to forecast dengue occurrence in Medan and strengthen evidence base available for dengue prevention and control.