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8 9/ - Iranian Journal of pidemiology Spring 07; (): -9. Original Article Spatiotemporal Analysis of Pulmonary Tuberculosis in Hamadan Province Using Population Attributable Risk Olfatifar M, Hosseini SM, Bahrami M, Karami M, Parvin M - Student Research Committee, Hamadan University of Medical Sciences, Hamadan, Iran - PhD, Modeling of Non-Communicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran -DDS Student, Student Research Committee, Hamadan University of Medical Sciences, Hamadan, Iran Corresponding author: Karami M, ma.karami@umsha.ac.ir (Received 6 April 06; Accepted 0 Augest 06) Background and Objectives: One of the applications of population attributable risk percent (PAR%) is to estimate the disease burden in a population exposed to several risk factors. Therefore, this study was conducted to estimates the PAR% of the space-time clusters of pulmonary tuberculosis. Methods: In this study, the data of pulmonary TB cases were obtained from the health department of Hamadan University of Medical Sciences. After detecting significant clusters using the spatiotemporal scan statistic, PAR% was used to analyze the clusters and to detect the location of clusters more accurately. Results: Four primary space-time clusters and three secondary spatiotemporal clusters were detected for patients with pulmonary tuberculosis and 9% of the patients who did not have a clear state in term of HIV infection. Despite differences in the location of clusters and PAR% attributed to them, the second primary cluster of pulmonary tuberculosis cases (consisting of the cities of Razan, Famenain and Kabudrahang) had the highest amount of PAR% that needs more attention. Conclusion: The presence of significance spatiotemporal clusters in Hamadan highlights the necessity of the use of PAR% to distinguish cluster areas and to implement prevention and control policy. However, more analytical studies are needed to detect the on the determinants of the occurrence of pulmonary TB. Keywords: Spatial analysis, Population attributable risk, Pulmonary tuberculosis, Clustering

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