Introduction:  Tuberculosis is the long-lasting infectious disease caused by bacteria called Mycobacteriumtuberculosis. Globally, in 2016 alone, approximately 10.4 million new cases have occurred worldwide. In 2016 only 182 (ranging, 128-245) thousand TB incidence, of which 14 (9.6-19) was related to HIV co-infection has occurred in Ethiopia and the estimated notified co-infected people was 103330 (81%). The rate incidence of the cases for the same year is found to be 177/100000. Africa has shared around 25% of the incidence and specifically in Ethiopia around 82,000 was caught by Tuberculosis.

Objectives: This study has been aimed to model the counts of Tuberculosis cases using Bayesian hierarchical approach. It is also designed to determine the influential predictors of TB cases. The study has also aimed to see the variation of TB incidences across districts of Jimma zone.

Methods: The study has been conducted in Jimma zone of entire districts and the data is basically secondary which is obtained from Jimma zone health office. The counts of Tuberculosis cases have been analyzed with factors like gender, HIV co-infection, Population density and age of patients. The Integrated Nested Laplace Approximation (INLA) method of Bayesian approach which has been used to determine the influential determinants of TB cases.

Results and Conclusion: The descriptive results indicated that, without considering the effect of sex and ages, Nono bench district accounted minimum (2%) TB cases, whereas Seka Chokorsa recorded to have the highest (12%). The numbers of male cases in each district were greater than those of females, except for districts of Agaro, Gomma, Limmu Seka and Kersa. The results of the model indicated that all the covariates under study have been found to be significantly affecting the status of Tb cases in Jimma zone. Finally, it also clearly shown that the distribution of TB was varying across districts and Seke Chokorsa district was with more sever of the disease.

Key words:  Tuberculosis, Bayesian, Jimma zone