The vulnerability modeling of dengue hemorrhagic fever disease in surabaya based on spatial logistic regression approach

In this paper, we discuss the vulnerability modeling of Dengue Hemorrhagic Fever (DHF) disease in Surabaya, Indonesia based on spatial logistic regression model approach. The model does not only include the factors that effect on the vulnerability of DHF disease but also accommodates the geographical locations simultaneously. This study uses data of the incidence of DHF disease in Surabaya that consist of response variable is specified i.e. endemic and non-endemic DHF region. While the predictor variables are factors of climate, population, and environment. The minimum of Akaike Information Criteia (AIC) value is used to determine the best model. Several weighting functions is used in this model, and we got the best model obtained by using the weighting of Fixed Gaussian function. Based on the best model, obtained prediction accuracy level of vulnerability DHF disease in Surabaya is 81.93%.