Pattern mining analysis of pulmonary TB cases in Hamadan province: Using space-time cube

Background and aims: One of the most common approach to understanding spatial and temporal trends of event data is to break it up into a series of time snapshots. Therefore space-time cube method applied in order to portray the likely trend in occurrence of the pulmonary tuberculosis (TB) cases. Methods: In this study, information of all patients with pulmonary TB recorded in surveillance system of Hamadan University of Medical Sciences from 2005 to 2013 years were studied. After geocoding the residence location address of pulmonary TB cases and converted to point layer, the space-time cube was used to detect likely trends in occurrence of tuberculosis. Then, based on the space-time cube results the Emerging Hot Spot Analysis was run to clustering hot and cold spots. Results: There was significant increasing trend in occurrence of pulmonary TB cases. The statistic trend was 2.1871 and P-value was 0.0287, as well as 36 hot spots locations was detected that have been form approximately in central areas of province. Conclusion: Significantly increasing trend in occurrence of TB cases and existence of hot spot, especially intensifying hot spots in central areas of province can represent pay more attention to this disease in mentioned areas in order to detect the change in epidemiological face and to implement suitable prevention programs.