Bayesian Survival Dagum 3 Parameter Link Function Models in the Suppression of Dengue Fever in Bojonegoro

Dengue Hemorrhagic Fever (DHF) is currently attacking residential areas unprepared to prevent the spread of the Aedes Aegypti mosquito. This has resulted in many residents suffering from DHF and eventually decreases economic productivity in the particular area or country. Furthermore, if the infected people’s ability to recover from this disease tends to be slow, the economic strait will continue to weaken and the death risk will rise. In addition to health quality and economy, other factors such as knowledge and awareness of the danger of DHF also influence how fast the recovery rate of the infected people in a particular area, especially in Bojonegoro. Taking into consideration these factors, a mathematical modeling can be carried out to estimate the duration of survival rate comprehensively. A survival model is a mathematical model to estimate the duration of a certain population’s resistance to an event. This study aims to find out what factors affect the recovery rate of DHF, such as length of hospitalization, sex, age, education, occupation, marital status, hematocrit levels, thrombocyte count, and hemoglobin count. The model used is the Survival Dagum 3 Parameter Link Function which parameters were estimated using the Bayesian MCMC-Gibbs Sampling method. The best survival model found was Dagum 3 parameter with normal distribution random effects. The factors that influence DHF were Sex (X1), Age (X2), Education (X3), Occupation (X4), Hematocrit Level (X5), Thrombocyte Count (X6), and Marital Status (X8).