MODELING OF DENGUE HEMORRHAGIC FEVER IN BOGOR USING BAYESIAN SUR-SAR

Abstract

The purposes of this research are (1) To develop Seemingly Unrelated Regression (SUR) system constructed by correlated Spatial Autoregressive Model (SAR) with Bayesian approach for dynamic analysis of spatial and non-spatial contributions of Dengue Hemorrhagic Fever (DHF) case in Bogor, (2) To evaluate efficiency issues on parameters estimation with SUR system. Markov Chain Monte Carlo (MCMC) sampling scheme was used to estimate all of model parameters with the number of iteration whose burn-in period was discovered. The results indicated that : there was the similar pattern of DHF spread in Bogor during 2009 – 2011, the nearby areas had a significant role to the incidence of DHF in an area in the city of Bogor, and the non-spatial contributions of DHF cases in Bogor during 2009 -2011 included in this model were dynamic. Gain efficiency of parameters estimation on modeling of DHF in Bogor with SAR for each year during 2009-2011 can be obtained if we construct all of SAR with SUR system model.