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AIM: This study was conducted to provide a clear epidemiological picture of HCV spatial pattern. BACKGROUND: Hepatitis C virus (HCV) is one of the major problems of public health, that its spatial and spatiotemporal pattern remain unclear in Hamadan province. METHODS: We used the scan statistic to identify the spatial and spatiotemporal clusters of HCV in Hamadan province with an emphasis on considering the role of carrier's and injecting drug users (IDUs) cases. We repeated the same analysis to estimate the effect of some influencing factors on the formation of clusters. All HCV cases that had been recorded by deputy health of Hamadan University of Medical Sciences during 2008-2016 were included in this study. RESULTS: The location of the purely spatial cluster for carriers, IDUs and total of cases were similar to each other, a cluster consisting of Toyserkan, Nahavand, Asadabad, Malayer and Bahar cities. However, after adjustment, the location of the identified cluster for both carries and IDUs cases changed to a cluster consisting of Asadabad, Bahar, Toyserkan and Nahavand cities. This cluster also observed for spatiotemporal clusters carriers, IDUs and total of cases even after adjustment. CONCLUSION: Although further studies in individual level are needed, our results revealed that spatial distribution of HCV in Hamadan province (especially in clusters areas) can strongly dependent on the distribution of IDUs cases. Consequently, the effectiveness of HCV combating programs is subjected to properly controlling these case through various counseling, behavioral and therapeutic programs.
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BACKGROUND: Spatial scan statistic has been shown as a useful tool to investigate spatial patterns and detecting the spatial clusters of cancer. This study conducted to study spatial analysis of breast cancer and its late-stage cases, one of the most common women cancers in Iran and the world. METHODS: We used space-time and purely spatial scan statistic implemented in SaTScan software to detect clusters of breast cancer and late-stage cases, at city level by applying Poisson and Bernoulli distribution. Data on 40017 of breast cancer cases that reported to the Ministry of Health and Medical Education (MOHME) during 2005 to 2010 were included. RESULTS: Purely spatial and spatiotemporal high rates significant clusters of breast cancer and its late-stage cases with Poisson distribution were in the same geographical area including southwest, north, and northeast. CONCLUSION: Significant clusters areas have probably differences with other areas in terms of delay in diagnosis and access to appropriate health services because late-stage breast cancer cases had the greatest impact on formation of clusters. However, more studies are essential to be conducted in different areas of country to explain more precisely clusters detected areas and detecting reasonable justification for existence of significant clusters.
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BACKGROUND: This study was conducted to detect clusters of pulmonary TB cases in Hamadan Province, west of Iran. METHODS: All patients with pulmonary tuberculosis recorded in the surveillance system from 2005 to 2013 were studied. The spatial scan statistic was used to detect significant clusters in status of unadjusted and adjusted for age, sex and location residence variables. RESULTS: Clusters with high rate for both purely spatial and space-time analyses were seen in the same geographical areas composed of four city of Asadabad, Bahar, Toyserkan and Nahavand. Adjustment for mentioned variables did not change location of detected clusters with high rates. CONCLUSIONS: Findings revealed evidence of significant clusters in Hamadan Province. Study results may help the health system to develop effective public health interventions and extend preventive interventions. However more study are needed to better explain of detected clusters due to limited access to effecting factors.